social media and online business research paper

Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review

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• Published: 02 February 2021
• Volume 25 , pages 971–993, ( 2023 )

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• Yogesh K. Dwivedi 1 ,
• Elvira Ismagilova 2 ,
• Nripendra P. Rana 2 &
• Ramakrishnan Raman 3  

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Social media plays an important part in the digital transformation of businesses. This research provides a comprehensive analysis of the use of social media by business-to-business (B2B) companies. The current study focuses on the number of aspects of social media such as the effect of social media, social media tools, social media use, adoption of social media use and its barriers, social media strategies, and measuring the effectiveness of use of social media. This research provides a valuable synthesis of the relevant literature on social media in B2B context by analysing, performing weight analysis and discussing the key findings from existing research on social media. The findings of this study can be used as an informative framework on social media for both, academic and practitioners.

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1 Introduction

The Internet has changed social communications and social behaviour, which lead to the development of new forms of communication channels and platforms (Ismagilova et al. 2017 ). Social media plays an important part in the digital transformation of businesses (Kunsman 2018 ). Digital transformation refers to the globally accelerated process of technical adaptation by companies and communities as a result of digitalisation (Sivarajah et al. 2019 ; Westerman et al. 2014 ). Web is developed from a tool used to provide passive information into the collaborative web, which allows and encourages active user engagement and contribution. If before social networks were used to provide the information about a company or brand, nowadays businesses use social media in their marketing aims and strategies to improve consumers’ involvement, relationship with customers and get useful consumers’ insights (Alalwan et al. 2017 ). Business-to-consumer (B2C) companies widely use social media as part of their digital transformation and enjoy its benefits such as an increase in sales, brand awareness, and customer engagement to name a few (Barreda et al. 2015 ; Chatterjee and Kar 2020 ; Harrigan et al. 2020 ; Kamboj et al. 2018 ; Kapoor et al. 2018 ).

From a marketing and sales research perspective, social media is defined as “the technological component of the communication, transaction and relationship building functions of a business which leverages the network of customers and prospects to promote value co-creation” (Andzulis et al. 2012 p.308). Industrial buyers use social media for their purchase as they compare products, research the market and build relationships with salesperson (Itani et al. 2017 ). Social media changed the way how buyers and sellers interact (Agnihotri et al. 2016 ) by enabling open and broad communications and cooperation between them (Rossmann and Stei 2015 ). Social media is an important facilitator of relationships between a company and customers (Agnihotri et al. 2012 ; Tedeschi 2006 ). Customers are more connected to companies, which make them more knowledgable about product selection and more powerful in buyer-seller relationships (Agnihotri et al. 2016 ). Social media also helps companies to increase business exposure, traffic and providing marketplace insight (Agnihotri et al. 2016 ; Stelzner 2011 ). As a result, the use of social media supports business decision processes and helps to improve companies’ performance (Rossmann and Stei 2015 ).

Due to digitalisation customers are becoming more informed and rely less on traditional selling initiatives (Ancillai et al. 2019 ). Buyers are relying more on digital resources and their buying process more often involves the use of social media. For example, in the research B2B buyer survey, 82% of buyers stated that social media content has a significant impact on the purchase decision (Ancillai et al. 2019 ; Minsky and Quesenberry 2016 ). As a result, these changes in consumer behaviour place high pressure on B2B salespeople and traditional sales companies (Ancillai et al. 2019 ). By using evidence from major B2B companies and consultancy report some studies claim that social media can be applied in sales to establish effective dialogues with buyers (Ancillai et al. 2019 ; Kovac 2016 ; McKinsey and Company 2015 ).

Now, business-to-business (B2B) companies started using social media as part of their digital transformation. 83% of B2B companies use social media, which makes it the most common marketing tactic (Pulizzi and Handley 2017 ; Sobal 2017 ). More than 70% of B2B companies use at least one of the “big 4” social media sites such as LinkedIn, Twitter, Facebook and YouTube. Additionally, 50% of the companies stated that social media has improved their marketing optimization and customer experience, while 25% stated that their revenue went up (Gregorio 2017 ; Sobal 2017 ). Even though B2B companies are benefitting from social media used by marketers, it is argued that research on that area is still in the embryonic stage and future research is needed (Salo 2017 ; Siamagka et al. 2015 ; Juntunen et al. 2020 ; Iannacci et al. 2020 ). There is a limited understanding of how B2B companies need to change to embrace recent technological innovations and how it can lead to business and societal transformation (Chen et al. 2012 ; Loebbecke and Picot 2015 ; Pappas et al. 2018 ).

The topic of social media in the context of B2B companies has started attracting attention from both academics and practitioners. This is evidenced by the growing number of research output within academic journals and conference proceedings. Some studies provided a comprehensive literature review on social media use by B2B companies (Pascucci et al. 2018 ; Salo 2017 ), but focused only on adoption of social media by B2B or social media influence, without providing the whole picture of the use of social media by B2B companies. Thus, this study aims to close this gap in the literature by conducting a comprehensive analysis of the use of social media by B2B companies and discuss its role in the digital transformation of B2B companies. The findings of this study can provide an informative framework for research on social media in the context of B2B companies for academics and practitioners.

The remaining sections of the study are organised as follows. Section 2 offers a brief overview of the methods used to identify relevant studies to be included in this review. Section 3 synthesises the studies identified in the previous section and provides a detailed overview. Section 4 presents weight analysis and its findings. Next section discusses the key aspects of the research, highlights any limitations within existing studies and explores the potential directions for future research. Finally, the paper is concluded in Section 6 .

2 Literature Search Method

The approach utilised in this study aligns with the recommendations in Webster and Watson ( 2002 ). This study used a keyword search-based approach for identifying relevant articles (Dwivedi et al. 2019b ; Ismagilova et al. 2020a ; Ismagilova et al. 2019 ; Jeyaraj and Dwivedi 2020 ; Williams et al. 2015 ). Keywords such as “Advertising” OR “Marketing” OR “Sales” AND TITLE (“Social Media” OR “Web 2.0” OR “Facebook” OR “LinkedIn” OR “Instagram” OR “Twitter” OR “Snapchat” OR “Pinterest” OR “WhatsApp” OR “Social Networking Sites”) AND TITLE-ABS-KEY (“B2B” OR “B to B” OR “Business to Business” OR “Business 2 Business”) were searched via the Scopus database. Scopus database was chosen to ensure the inclusion of only high quality studies. Use of online databases for conducting a systematic literature review became an emerging culture used by a number of information systems research studies (Dwivedi et al. 2019a ; Gupta et al. 2019 ; Ismagilova et al. 2020b ; Muhammad et al. 2018 ; Rana et al. 2019 ). The search resulted in 80 articles. All studies were processed by the authors in order to ensure relevance and that the research offered a contribution to the social media in the context B2B discussion. The search and review resulted in 70 articles and conference papers that formed the literature review for this study. The selected studies appeared in 33 separate journals and conference proceedings, including journals such as Industrial Marketing Management, Journal of Business and Industrial Marketing and Journal of Business Research.

3 Literature Synthesis

The studies on social media research in the context of B2B companies were divided into the following themes: effect of social media, adoption of social media, social media strategies, social media use, measuring the effectiveness of use of social media, and social media tools (see Table 1 ). The following subsections provide an overview of each theme.

3.1 Effect of Social Media

Some studies focus on the effect of social media for B2B companies, which include customer satisfaction, value creation, intention to buy and sales, building relationships with customers, brand awareness, knowledge creation, perceived corporate credibility, acquiring of new customers, salesperson performance, employee brand engagement, and sustainability (Table 2 ).

3.1.1 Customer Satisfaction

Some studies investigated how the use of social media affected customer satisfaction (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Rossmann and Stei 2015 ). For example, Agnihotri et al. ( 2016 ) investigated how the implementation of social media by B2B salesperson affects consumer satisfaction. Salesperson’s social media use is defined as a “salesperson’s utilization and integration of social media technology to perform his or her job” (Agnihotri et al. 2016 , p.2). The study used data from 111 sales professionals involved in B2B industrial selling to test the proposed hypotheses. It was found that a salesperson’s use of social media will have a positive effect on information communication, which will, in turn, lead to improved customer satisfaction with the salesperson. Also, it was investigated that information communication will be positively related to responsiveness, which impacts customer satisfaction.

Another study by Rossmann and Stei ( 2015 ) looked at the antecedents of social media use, social media use by B2B companies and their effect on customers. By using data from 362 chief information officers of B2B companies the study found the following. Social media usage of sales representative has a positive impact on customer satisfaction. Age has a negative effect on content generation. It seems that older salespeople use social media in passive ways or interacting with the customer rather than creating their own content. It was found that the quality of corporate social media strategy has a positive impact on social media usage in terms of the consumption of information, content generation, and active interaction with customers. Also, the expertise of a salesperson in the area of social media has a positive impact on social media usage.

3.1.2 Value Creation

Research in B2B found that social media can create value for customers and salesperson (Agnihotri et al. 2012 ; Agnihotri et al. 2017 ). Agnihotri et al. ( 2012 ) proposed a theoretical framework to explain the mechanisms through which salespeople’s use of social media operates to create value and propose a strategic approach to social media use to achieve competitive goals. The study draws on the existing literature on relationship marketing, task–technology fit theory, and sales service behavior to sketch a social media strategy for business-to-business sales organizations with relational selling objectives. The proposed framework describes how social media tools can help salespeople perform service behaviors (information sharing, customer service, and trust-building) leading to value creation.

Some researchers investigated the role of the salesperson in the value creation process after closing the sale. By employing salesperson-customer data within a business-to-business context, Agnihotri et al. ( 2017 ) analysed the direct effects of sales-based CRM technology on the post-sale service behaviors: diligence, information communication, inducements, empathy, and sportsmanship. Additionally, the study examines the interactive effects of sales-based CRM technology and social media on these behaviors. The results indicate that sales-based CRM technology has a positive influence on salesperson service behaviors and that salespeople using CRM technology in conjunction with social media are more likely to exhibit higher levels of SSBs than their counterparts with low social media technology use. Data were collected from 162 salespeople from India. SmartPLS was used to analyse the data.

3.1.3 Intention to Buy and Sales

Another group of studies investigated the effect of social media on the level of sales and consumer purchase intention (Ancillai et al. 2019 ; Itani et al. 2017 ; Salo 2017 ; Hsiao et al. 2020 ; Mahrous 2013 ). For example, Itani et al. ( 2017 ) used the theory of reasoned actions to develop a model that tests the factors affecting the use of social media by salesperson and its impact. By collecting data from 120 salespersons from different industries and using SmartPLS to analyse the data, it was found that attitude towards social media usefulness did not affect the use of social media. It was found that social media use positively affects competitive intelligence collection, adaptive selling behaviour, which in turn influenced sales performance. Another study by Ancillai et al. ( 2019 ) used in-depth interviews with social selling professionals. The findings suggest that the use of social media improves not only the level of sales but also affects relationship and customer performance (trust, customer satisfaction, customer referrals); and organisational performance (organisational selling performance and brand performance).

It was investigated that social media has a positive effect on the intention to purchase (Hsiao et al. 2020 ; Mahrous 2013 ). For instance, Mahrous ( 2013 ) by reviewing the literature on B2B and B2C companies concluded that social media has a significant influence on consumer buying behaviour.

3.1.4 Customer Relationships

Another group of studies focused on the effect of social media on customer relationships (Bhattacharjya and Ellison 2015 ; Gáti et al. 2018 ; Gruner and Power 2018 ; Hollebeek 2019 ; Iankova et al. 2018 ; Jussila et al. 2011 ; Kho 2008 ; Niedermeier et al. 2016 ; Ogilvie et al. 2018 ). For example, Bhattacharjya and Ellison ( 2015 ) investigated the way companies build relationships with customers by using responsive customer relationship management. The study analysed customer relationship management activities from Twitter account of a Canadian company Shopify (B2B service provider). The company uses Twitter to engage with small business customers, develops and consumers. Jussila et al. ( 2011 ), by reviewing the literature, found that social media leads to increased customer focus and understanding, increased level of customer service and decreased time-to-market.

Gáti et al. ( 2018 ) focused their research efforts on social media use in customer relationship performance, particularly in customer relations. The study investigated the adoption and impact of social media by salespeople of B2B companies. By using data of 112 salespeople from several industries the study found that the intensity of technology use positively affects attitude towards social media, which positively affects social media use. Intensive technology use in turn positively affects customer relationship performance (customer retention). PLS-SEM was applied for analysis.

Another study by Gruner and Power ( 2018 ) investigated the effectiveness of the use of multiple social media platforms in communications with customers. By using data from 208 large Australian organisations, the paper explores how companies’ investment in one form of social media impacts activity on another form of social media. A regression analysis was performed to analyse the data. It was found that widespread activities on LinkedIn, Twitter and YouTube have a negative effect on a company’s marketing activity on Facebook. Thus, having it is more effective for the company to focus on a specific social media platform in forming successful inter-organisational relationships with customers.

Hollebeek ( 2019 ) proposed an integrative S-D logic/resource-based view (RBV) model of customer engagement. The proposed model considers business customer actors and resources in driving business customer resource integration, business customer resource integration effectiveness and business customer resource integration efficiency, which are antecedents of business customer engagement. Business customer engagement, in turn, results in business customer co-creation and relationship productivity.

Niedermeier et al. ( 2016 ) investigated the use of social media among salespeople in the pharmaceutical industry in China. Also, the study investigated the impact of social media on building culturally specific Guanxi relationships-it involves the exchange of factors to build trust and connection for business purpose. By using in-depth interviews with 3 sales managers and a survey of 42 pharmaceutical sales representatives that study found that WeChat is the most common social media platform used by businesses. Also, it was found to be an important tool in building Guanxi. Future studies should focus on other industries and other types of cultural features in doing business.

Ogilvie et al. ( 2018 ) investigated the effect of social media technologies on customer relationship performance and objective sales performance by using two empirical studies conducted in the United States. The first study used 375 salespeople from 1200 B2B companies. The second study used 181 respondents from the energy solution company. It was found that social media significantly affects salesperson product information communication, diligence, product knowledge and adaptability, which in turn affect customer relationship performance. It was also found that the use of social media technologies without training on technology will not lead to good results. Thus, the results propose that companies should allocate the resources required for the proper implementation of social media strategies. Future research should examine how the personality traits of a salesperson can moderate the implementation of social media technologies.

While most of the studies focused on a single country, Iankova et al. ( 2018 ) investigated the perceived effectiveness of social media by different types of businesses in two countries. By using 449 respondents from the US and the UK businesses, it was found that social media is potentially less important, at the present time, for managing ongoing relationships in B2B organizations than for B2C, Mixed or B2B2C organizations. All types of businesses ascribe similar importance to social media for acquisition-related activities. Also it was found that B2B organizations see social media as a less effective communication channel, and to have less potential as a channel for the business.

3.1.5 Brand Awareness

Some researchers argued that social media can influence brand awareness (Ancillai et al. 2019 ; Hsiao et al. 2020 ). For instance, Hsiao et al. ( 2020 ) investigated the effect of social media in the fashion industry. By collecting 1395 posts from lookbook.nu and employing regression analysis it was found that the inclusion of national brand and private fashion brands in the post increased the level of popularity which leads to purchasing interest and brand awareness.

3.1.6 Knowledge Creation

Multiple types of collaborative web tools can help and significantly increase the collaboration and the use of the distributed knowledge inside and outside of the company (McAfee 2006 ). Kärkkäinen et al. ( 2011 ) by analysing previous literature on social media proposed that social media use has a positive effect on sharing and creation of customer information and knowledge in the case of B2B companies.

3.1.7 Corporate Credibility

Another study by Kho ( 2008 ) states the advantages of using social media by B2B companies, which include faster and more personalised communications between customer and vendor, which can improve corporate credibility and strengthen the relationships. Thanks to social media companies can provide more detailed information about their products and services. Kho ( 2008 ) also mentions that customer forums and blog comments in the B2B environment should be carefully monitored in order to make sure that inappropriate discussions are taken offline and negative eWOM communications should be addressed in a timely manner.

3.1.8 Acquiring New Customers

Meire et al. ( 2017 ) investigated the impact of social media on acquiring B2B customers. By using commercially purchased prospecting data, website data and Facebook data from beverage companies the study conducted an experiment and found that social media us an effective tool in acquiring B2B customers. Future work might assess the added value of social media pages for profitability prediction instead of prospect conversion. When a longer timeframe becomes available (e.g., after one year), the profitability of the converted prospects can be assessed.

3.1.9 Salesperson Performance

Moncrief et al. ( 2015 ) investigated the impact of social media technologies on the role of salesperson position. It was found that social media affects sales management functions (supervision, selection, training, compensation, and deployment) and salesperson performance (role, skill, and motivation). Another study by Rodriguez et al. ( 2012 ) examines the effect of social media on B2B sales performance by using social capital theory and collecting data from 1699 B2B salespeople from over 25 different industries. By employing SEM AMOS, the study found that social media usage has a positive significant relationship with selling companies’ ability to create opportunities and manage relationships. The study also found that social media usage has a positive and significant relationship with sales performance (based on relational measurers of sales that focus on behaviours that strengthen the relationship between buyers and sellers), but not with outcome-based sales performance (reflected by quota achievement, growth in average billing size, and overall revenue gain).

3.1.10 Employee Brand Management

The study by Pitt et al. ( 2018 ) focuses on employee engagement with B2B companies on social media. By using results from Glassdoor (2315 five-star and 1983 one-star reviews for the highest-ranked firms, and 1013 five star and 1025 one-star reviews for lowest ranked firms) on employee brand engagement on social media, two key drivers of employee brand engagement by using the content analysis tool DICTION were identified-optimism and commonality. Individuals working in top-ranked companies expressed a higher level of optimism and commonality in comparison with individuals working in low-ranked companies. As a result, a 2 × 2 matrix was constructed which can help managers to choose strategies in order to increase and improve employee brand engagement. Another study by Pitt et al. ( 2017 ) focused on employee engagement of B2B companies on social media. By using a conceptual framework based on a theory of word choice and verbal tone and 6300 reviews collected from Glassdoor and analysed using DICTION. The study found that employees of highly ranked B2B companies are more positive about their employer brand and talk more optimistically about these brands. For low ranked B2B companies it was found that employees express a greater level of activity, certainty, and realism. Also, it was found that they used more aggressive language.

3.1.11 Sustainability

Sustainability refers to the strategy that helps a business “to meet its current requirements without compromising its ability to meet future needs” (World Commission Report on Environment and Development 1987 , p 41). Two studies out of 70 focused on the role of social media for B2B sustainability (Sivarajah et al. 2019 ; Kasper et al. 2015 ). For example, Sivarajah et al. ( 2019 ) argued that big data and social media within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities.

Another study by Kasper et al. ( 2015 ) proposed the Social Media Matrix which helps companies to decide which social media activities to execute based on their corporate and communication goals. The matrix includes three parts. The first part is focusing on social media goals and task areas, which were identified and matched. The second part consists of five types of social media activities (content, interaction/dialog, listening and analysing, application and networking). The third part provides a structure to assess the suitability of each activity type on each social media platform for each goal. The matrix was successfully tested by assessing the German B2B sector by using expert interviews with practitioners.

Based on the reviewed studies, it can be seen that if used appropriately social media have positive effect on B2B companies before and after sales, such as customer satisfaction, value creation, intention to buy and sales, customer relationships, brand awareness, knowledge creation, corporate credibility, acquiring new customers, salesperson performance, employee brand management, and sustainability. However, limited research is done on the negative effect of social media on b2b companies.

3.2 Adoption of Social Media

Some scholars investigated factors affecting the adoption of social media by B2B companies (Buratti et al. 2018 ; Gáti et al. 2018 ; Gazal et al. 2016 ; Itani et al. 2017 ; Kumar and Möller 2018 ; Lacka and Chong 2016 ). For instance, Lacka and Chong ( 2016 ) investigated factors affecting the adoption of social media by B2B companies from different industries in China. The study collected the data from 181 respondents and used the technology acceptance model with Nielsen’s model of attributes of system acceptability as a theoretical framework. By using SEM AMOS for analysis the study found that perceived usability, perceived usefulness, and perceived utility positively affect adoption and use of social media by B2B marketing professionals. The usefulness is subject to the assessment of whether social media sites are suitable means through which marketing activities can be conducted. The ability to use social media sites for B2B marketing purposes, in turn, is due to those sites learnability and memorability attributes.

Another study by Müller et al. ( 2018 ) investigated factors affecting the usage of social media. By using survey data from 100 Polish and 39 German sensor suppliers, it was found that buying frequency, the function of a buyer, the industry sector and the country does not affect the usage of social media in the context of sensor technology from Poland and Germany. The study used correlation analysis and ANOVA.

Lashgari et al. ( 2018 ) studied the adoption and use of social media by using face-to-face interviews with key managers of four multinational corporations and observations from companies’ websites and social media platforms. It was found that that the elements essential in forming the B2B firm’s social media adoption strategies are content (depth and diversity), corresponding social media platform, the structure of social media channels, the role of moderators, information accessibility approaches (public vs. gated-content), and online communities. These elements are customized to the goals and target group the firm sets to pursue. Similarly, integration of social media into other promotional channels can fall under an ad-hoc or continuous approach depending on the scope and the breadth of the communication plan, derived from the goal.

Similar to Lashgari et al. ( 2018 ), Shaltoni ( 2017 ) used data from managers. The study applied technology organisational environmental framework and diffusion of innovations to investigate factors affecting the adoption of social media by B2B companies. By using data from marketing managers or business owners of 480 SMEs, the study found that perceived relative advance, perceive compatibility, organizational innovativeness, competitor pressure, and customer pressure influence the adoption of social media by B2B companies. The findings also suggest that many decision-makers in B2B companies think that Internet marketing is not beneficial, as it is not compatible with the nature of B2B markets.

Buratti et al. ( 2018 ) investigated the adoption of social media by tanker shipping companies and ocean carriers. By using data from 60 companies the following was found. LinkedIn is the most used tool, with a 93.3% adoption rate. Firm size emerges as a predictor of Twitter’s adoption: big companies unveil a higher attitude to use it. Finally, the country of origin is not a strong influential factor in the adoption rate. Nonetheless, Asian firms clearly show a lower attitude to join SM tools such as Facebook (70%) and LinkedIn (86.7%), probably also due to governmental web restrictions imposed in China. External dimensions such as the core business, the firm size, the geographic area of origin, etc., seem to affect network wideness. Firm size, also, discriminates the capacity of firms to build relational networks. Bigger firms create networks larger than small firms do. Looking at geographical dimensions, Asian firms confirm to be far less active on SM respect to European and North American firms. Finally, the study analyzed the format of the contents disclosed by sample firms, observing quite limited use of photos and videos: in the sample industries, informational contents seem more appropriate for activating a dialogue with stakeholders and communication still appears formulated in a very traditional manner. Preliminary findings suggest that companies operating in conservative B2B services pursue different strategic approaches toward SMM and develop ad hoc communication tactics. Nonetheless, to be successful in managing SM tools, a high degree of commitment and a clear vision concerning the role of SM within communication and marketing strategy is necessary.

Gazal et al. ( 2016 ) investigated the adoption and measuring of the effectiveness of social media in the context of the US forest industry by using organisational-level adoption framework and TAM. By using data from 166 companies and performing regression analysis, the following results were received. Years in business, new sales revenue, product type, amount of available information on a company website, perceived importance of e-commerce and perceived ease of use of social media significantly affected social media use. Also, it was found that companies’ strategies and internal resources and capabilities and influence a company’s decision to adopt social media. Also, it was found that 94 of respondents do not measure the ROI from social media use. The reason is that the use of social media in marketing is relatively new and companies do not possess the knowledge of measuring ROI from the use of social media. Companies mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with the key audience, audience participation, moving from monologue to dialogue with consumers. Facebook was found to be the most effective social media platform reported by the US forest industry.

The study by Kumar and Möller ( 2018 ) investigated the role of social media for B2B companies in their recruitment practices. By using data from international B2B company with headquarter in Helsinki, Finland comprised of 139 respondents it was found that brand familiarity encourages them to adopt social media platforms for a job search; however, the effect of the persuasiveness of recruitment messages on users’ adoption of social media platforms for their job search behavior is negative. The study used correlation analysis and descriptive analysis to analyse the data.

Nunan et al. ( 2018 ) identified areas for future research such as patterns of social media adoption, the role of social media platforms within the sales process, B2B consumer engagement and social media, modeling the ROI of social media, and the risks of social media within B2B sales relationships.

The study by Pascucci et al. ( 2018 ) conducted a systematic literature review on antecedents affecting the adoption and use of social media by B2B companies. By reviewing 29 studies published in academic journal and conferences from 2001 to 2017, the study identified external (pressure from customers, competitors, availability of external information about social media) and internal factors (personal characteristics -managers age, individual commitment, perceptions of social media-perceived ease of use, perceived usefulness, perceived utility), which can affect adoption of social media.

The study by Siamagka et al. ( 2015 ) aims to investigate factors affecting the adoption of social media by B2B organisations. The conceptual model was based on the technology acceptance model and the resource-based theory. AMOS software and Structural equation modelling were employed to test the proposed hypotheses. By using a sample of 105 UK companies, the study found that perceived usefulness of social media is influenced by image, perceived ease of use and perceived barriers. Also, it was found that social media adoption is significantly determined by organisational innovativeness and perceived usefulness. Additionally, the study tested the moderating role of organisational innovativeness and found that it does not affect the adoption of social media by B2B organisations. The study also identified that perceived barriers to SNS (uncertainty about how to use SNS to achieve objectives, employee’s lack of knowledge about SNS, high cost of investment needed to adopt the technology) have a negative impact on perceived usefulness of social media by B2B organisations. The study also used nine in-depth interviews with B2B senior managers and social media specialists about adoption of social media by B2B. It was found that perceived pressure from stakeholders influences B2B organisations’ adoption intention of social media. Future research should test it by using quantitative methods.

While most of the studies focused on the antecedents of social media adoption by B2B companies, Michaelidou et al. ( 2011 ) investigated the usage, perceived barriers and measuring the effectiveness of social media. By using data from 92 SMEs the study found that over a quarter of B2B SMEs in the UK are currently using SNS to achieve brand objectives, the most popular of which is to attract new customers. The barriers that prevent SMEs from using social media to support their brands were lack of staff familiarity and technical skills. Innovativeness of a company determined the adoption of social media. It was found that most of the companies do not evaluate the effectiveness of their SNS in supporting their brand. The most popular measures were the number of users joining the groups/discussion and the number of comments made. The findings showed that the size of the company does not influence the usage of social media for small and medium-sized companies. Future research should investigate the usage of social media in large companies and determine if the size can have and influence on the use. The benefits of using social media include increasing awareness and communicating the brand online. B2B companies can employ social media to create customer value in the form of interacting with customers, as well as building and fostering customer relationships. Future research should investigate the reasons why most of the users do not assess the effectiveness of their SNS. Future research should also investigate how the attitude towards technology can influence the adoption of social media.

Based on the reviewed studies it can be seen that the main factors affecting the adoption of social media by B2B companies are perceived usability, technical skills of employees, pressure from stakeholders, perceived usefulness and innovativeness.

3.3 Social Media Strategies

Another group of studies investigated types of strategies B2B companies apply (Cawsey and Rowley 2016 ; Huotari et al. 2015 ; Kasper et al. 2015 ; McShane et al. 2019 ; Mudambi et al. 2019 ; Swani et al. 2013 ; Swani et al. 2014 ; Swani et al. 2017 ; Watt 2010 ). For example, Cawsey and Rowley ( 2016 ) focused on the social media strategies of B2B companies. By conducting semi-structured interviews with marketing professionals from France, Ireland, the UK and the USA it was found that enhancing brand image, extending brand awareness and facilitating customer engagement were considered the most common social media objective. The study proposed the B2B social media strategy framework, which includes six components of a social media strategy: 1) monitoring and listening 2) empowering and engaging employees 3) creating compelling content 4) stimulating eWOM 5) evaluating and selecting channels 6) enhancing brand presence through integrating social media.

Chirumalla et al. ( 2018 ) focused on the social media engagement strategies of manufacturing companies. By using semi-structured interviews (36), observations (4), focus group meetings (6), and documentation, the study developed the process of social media adoption through a three-phase engagement strategy which includes coordination, cooperation, and co-production.

McShane et al. ( 2019 ) proposed social media strategies to influence online users’ engagement with B2B companies. Taking into consideration fluency lens the study analysed Twitter feeds of top 50 social B2B brands to examine the influence of hashtags, text difficulty embedded media and message timing on user engagement, which was evaluated in terms of likes and retweets. It was found that hashtags and text difficulty are connected to lower levels of engagement while embedded media such as images and videos improve the level of engagement.

Swani et al. ( 2014 ) investigate the use of Twitter by B2B and B2C companies and predict factors that influence message strategies. The study conducted a longitudinal content analysis by collecting 7000 tweets from Fortune 500 companies. It was found that B2B and B2C companies used different message appeals, cues, links and hashtags. B2B companies tend to use more emotional than functional appeals. It was found that B2B and B2C companies do not use hard-sell message strategies.

Another study by Swani et al. ( 2013 ) aimed to investigate message strategies that can help in promoting eWOM activity for B2B companies. By applying content analysis and hierarchical linear modeling the study analysed 1143 wall post messages from 193 fortune 500 Facebook accounts. The study found that B2B account posts will be more effective if they include corporate brand names and avoid hard sell or explicitly commercial statement. Also, companies should use emotional sentiment in Facebook posts.

Huotari et al. ( 2015 ) aimed to investigate how B2B marketers can influence content creation in social media. By conducting four face-to-face interviews with B2B marketers, it was found that a B2B company can influence content creation in social media directly by adding new content, participating in a discussion and removing content through corporate user accounts and controlling employees social media behaviour. Also, it can influence it indirectly by training employees to create desired content and perfuming marketing activities that influence other users to create content that is favorable for the company.

Most of the studies investigated the strategies and content of social media communications of B2B companies. However, the limited number of studies investigated the importance of CEO engagement on social media in the company’s strategies. Mudambi et al. ( 2019 ) emphasise the importance of the CEO of B2B companies to be present and active on social media. The study discusses the advantages of social media presence for the CEO and how it will benefit the company. For example, one of the benefits for the CEO can be perceived as being more trustworthy and effective than non-social CEOs, which will benefit the company in increased customer trust. Mudambi et al. ( 2019 ) also discussed the platforms the CEO should use and posting frequencies depending on the content of the post.

From the above review of the studies, it can be seen that B2B companies social media strategies include enhancing brand image, extending brand awareness and facilitating customer engagement. Companies use various message strategies, such as using emotional appeal, use of brand names, and use of hashtags. Majority of the companies avoid hard sell or explicitly commercial statement.

3.4 Social Media Use

Studies investigated the way how companies used social media and factors affecting the use of social media by B2B (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ; Habibi et al. 2015 ). For example, Vasudevan and Kumar ( 2018 ) investigated how B2B companies use social media by analysing 325 brand posts of Canon India, Epson India, and HP India on Linkedin, Facebook, and Twitter. By employing content analysis the study found that most of the posts had a combination of text and message. More than 50% of the posts were about product or brand-centric. The study argued that likes proved to be an unreliable measure of engagement, while shares were considered a more reliable metric. The reason was that likes had high spikes when brand posts were boosted during promotional activities.

Andersson and Wikström ( 2017 ) used case studies of three B2B companies to investigate reasons for using social media. It was found that companies use social media to enhance customer relationships, support sales and build their brands. Also, social media is used as a recruiting tool, a seeking tool, and a product information and service tool.

Bell and Shirzad ( 2013 ) aimed to conduct social media use analysis in the context of pharmaceutical companies. The study analysed 54,365 tweets from the top five pharmaceutical companies. The study analysed the popular time slots, the average number of positive and negative tweets and its content by using Nvivo9.

Bernard ( 2016 ) aims to examine how chief marketing officers use social media. By using case studies from IBM experience with social media it was found that B2B CMO’s are not ready to make use of social media. It was proposed that social media can be used for after-sales service, getting sales leads, engaging with key influencers, building the company’s reputation and enhancing the industry status of key individuals. B2B firms need to exploit the capabilities of processing massive amounts of data to get the most from social media.

Bolat et al. ( 2016 ) explore how companies apply mobile social media. By employing a grounded theory approach to analyse interviews from 26 B2B company representatives from UK advertising and marketing sector companies. It was found that companies use social media for branding, sensing market, managing relationships, and developing content.

Denktaş-Şakar and Sürücü ( 2018 ) investigated how social media usage influence stakeholder engagement focusing on the corporate Facebook page of 30 3PLs companies. In total 1532 Facebook posts were analysed. It was found that the number of followers, post sharing frequency, negatively affect stakeholder engagement. It was found that content including photos facilitates more stakeholder engagement (likes, comment, share) in comparison with other forms. Vivid posts and special day celebration posts strengthen relationships with stakeholders.

Dyck ( 2010 ) discussed the advantages of using social media for the device industry. Social media can be used for product innovation and development, to build a team and collaborate globally. Also, there is an opportunity to connect with all of the stakeholders needed in order to deliver the device to the market. Additionally, it provides to receive feedback from customers (doctors, hospitals) in real-time.

The study by Guesalaga ( 2016 ) draws on interactional psychology theory to propose and test a model of usage of social media in sales, analysing individual, organizational, and customer-related factors. It was found that organizational competence and commitment to social media are key determinants of social media usage in sales, as well as individual commitment. Customer engagement with social media also predicts social media usage in sales, both directly and (mostly) through the individual and organizational factors analysed, especially organizational competence and commitment. Finally, the study found evidence of synergistic effects between individual competence and commitment, which is not found at the organizational level. The data obtained by surveying 220 sales executives in the United States were analysed using regression analysis.

Habibi et al. ( 2015 ) proposed a conceptual model for the implementation of social media by B2B companies. Based on existing B2B marketing, social media and organisational orientational literature the study proposed that four components of electronic market orientation (philosophical, initiation, implementation and adoption) address different implementation issues faced in implementing social media.

Katona and Sarvary ( 2014 ) presented a case of using social media by Maersk-the largest container shipping company in the world. The case provided details on the program launch and the integration strategy which focused on integrating the largest independent social media operation into the company’s broader marketing efforts.

Moore et al. ( 2013 ) provided insights into the understanding of the use of social media by salespersons. 395 salespeople in B2B and B2C markets, utilization of relationship-oriented social media applications are presented and examined. Overall, findings show that B2B practitioners tend to use media targeted at professionals whereas their B2C counterparts tend to utilize more sites targeted to the general public for engaging in one-on-one dialogue with their customers. Moreover, B2B professionals tend to use relationship-oriented social media technologies more than B2C professionals for the purpose of prospecting, handling objections, and after-sale follow-up.

Moore et al. ( 2015 ) investigated the use of social media between B2B and B2C salespeople. By using survey data from 395 sales professionals from different industries they found that B2B sales managers use social selling tools significantly more frequently than B2C managers and B2C sales representatives while conducting sales presentations. Also, it was found that B2B managers used social selling tools significantly more frequently than all sales representatives while closing sales.

Müller et al. ( 2013 ) investigated social media use in the German automotive market. By using online analysis of 10 most popular car manufacturers online social networks and surveys of six manufacturers, 42 car dealers, 199 buyers the study found that social media communication relations are widely established between manufacturers and (prospective) buyers and only partially established between car dealers and prospective buyers. In contrast to that, on the B2B side, social media communication is rarely used. Social Online Networks (SONs) are the most popular social media channels employed by businesses. Manufacturers and car dealers focus their social media engagement, especially on Facebook. From the perspective of prospective buyers, however, forums are the most important source of information.

Sułkowski and Kaczorowska-Spychalska ( 2016 ) investigated the adoption of social media by companies in the Polish textile-clothing industry. By interviewing seven companies representatives of small and medium-sized enterprises the study found that companies started implementing social media activities in their marketing activities.

Vukanovic ( 2013 ) by reviewing previous literature on social media outlined advantages of using social media for B2B companies, which include: increase customer loyalty and trust, building and improving corporate reputation, facilitating open communications, improvement in customer engagement to name a few.

Keinänen and Kuivalainen ( 2015 ) investigated factors affecting the use of social media by B2B customers by conducting an online survey among 82 key customer accounts of an information technology service company. Partial least squares path modelling was used to analysed the proposed hypotheses. It was found that social media private use, colleague support for using SM, age, job position affected the use of social media by B2B customers. The study also found that corporate culture, gender, easiness to use, and perception of usability did not affect the use of social media by B2B customers.

By using interviews and survey social media research found that mostly B2B companies use social media to enhance customer relationships, support sales, build their brands, sense market, manage relationships, and develop content. Additionally, some companies use it social media as a recruitment tool. The main difference between B2B and B2C was that B2B sales managers use social selling tools significantly more frequently than B2C managers.

3.5 Measuring the Effectiveness of Social Media

It is important for a business to be able to measure the effectiveness of social media by calculating return on investment (ROI). ROI is the relationship between profit and the investment that generate that profit. Some studies focused on the ways B2B companies can measure ROI and the challenges they face (Gazal et al. 2016 ; Michaelidou et al. 2011 ; Vasudevan and Kumar 2018 ). For example, Gazal et al. ( 2016 ) investigated the adoption and measuring of the effectiveness of social media in the context of the US forest industry by using organisational-level adoption framework and TAM. By using data from 166 companies it was found that 94% of respondents do not measure the ROI from social media use. The reason is that the use of social media in marketing is relatively new and companies do not possess the knowledge of measuring ROI from the use of social media. Companies mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with the key audience, audience participation, moving from monologue to dialogue with consumers).

Another study by Michaelidou et al. ( 2011 ) found that most of the companies do not evaluate the effectiveness of their SNS in supporting their brand. The most popular measures were the number of users joining the groups/discussion and the number of comments made.

Vasudevan and Kumar ( 2018 ) investigated how B2B companies use social media and measure ROI from social media by analysing 325 brand posts of Canon India, Epson India, and HP India on Linkedin, Facebook, and Twitter. By employing content analysis the study found that most of the post has a combination of text and message. More than 50% of the posts were about product or brand-centric. The study argued that likes proved to be an unreliable measure of engagement, while shares were considered a more reliable metric. The reason was that likes had high spikes when brand posts were boosted during promotional activities. Future research should conduct longitudinal studies.

By reviewing the above studies, it can be concluded that companies still struggle to find ways of measuring ROI and applying correct metrics. By gaining knowledge in how to measure ROI from social media activities, B2B companies will be able to produce valuable insights leading to better marketing strategies (Lal et al. 2020 ).

3.6 Social Media Tools

Some studies proposed tools that could be employed by companies to advance their use of social media. For example, Mehmet and Clarke ( 2016 ) proposed a social semiotic multimodal (SSMM) framework that improved the analysis of social media communications. This framework employs multimodal extensions to systemic functional linguistics enabling it to be applying to analysing non-language as well as language constituents of social media messages. Furthermore, the framework also utilises expansion theory to identify, categorise and analyse various marketing communication resources associated with marketing messages and also to reveal how conversations are chained together to form extended online marketing conversations. This semantic approach is exemplified using a Fairtrade Australia B2B case study demonstrating how marketing conversations can be mapped and analysed. The framework emphasises the importance of acknowledging the impact of all stakeholders, particularly messages that may distract or confuse the original purpose of the conversation.

Yang et al. ( 2012 ) proposed the temporal analysis technique to identify user relationships on social media platforms. The experiment was conducted by using data from Digg.com . The results showed that the proposed techniques achieved substantially higher recall but not very good at precision. This technique will help companies to identify their future consumers based on their user relationships.

Based on the literature review, it can be seen that B2B companies can benefit by using the discussed tools. However, it is important to consider that employee should have some technical skills and knowledge to use these tools successfully. As a result, companies will need to invest some resources in staff training.

4 Weight Analysis

Weight analysis enables scrutiny of the predictive power of independent variables in studied relationships and the degree of effectiveness of the relationships (Jeyaraj et al. 2006 ; Rana et al. 2015 ; Ismagilova et al. 2020a ). The results of weight analysis are depicted in Table 3 providing information about an independent variable, dependent variable, number of significant relationships, number of non-significant relationships, the total number of relationships and weight. To perform weight analysis, the number of significant relationships was divided by the total number of analysed relationships between the independent variable and the dependent variable (Jeyaraj et al. 2006 ; Rana et al. 2015 ). For example, the weight for the relationship between attitude towards social media and social media is calculated by dividing ‘1’ (the number of significant relationships) by ‘2’ (the total number of relationships) which equals 0.5.

A predictor is defined as well-utilised if it was examined five or more times, otherwise, it is defined as experimental. It can be seen from Table 3 that all relationships were examined less than five times. Thus all studied predictors are experimental. The predictor is defined as promising when it has been examined less than five times by existing studies but has a weight equal to ‘1’ (Jeyaraj et al. 2006 ). From the predictors affecting the adoption of social media, it can be seen that two are promising, technical skills of employees and pressure from stakeholders. Social media usage is a promising predictor for acquiring new customers, sales, stakeholder engagement and customer satisfaction. Perceived ease of use and age of salesperson are promising predictors of social media usage. Even though this relationship was found to be significant every time it was examined, it is suggested that this variable, which can also be referred to as experimental, will need to be further tested in order to qualify as the best predictor. Another predictor, average rating of product/service, was examined less than five times with a weight equal to 0.75, thus it is considered as an experimental predictor.

Figure 1 shows the diagrammatic representation of the factors affecting different relationships in B2B social media with their corresponding weights, based on the results of weight analysis. The findings suggest that promising predictors should be included in further empirical studies to determine their overall performance.

Diagrammatic representation of results of weight analysis. Note: experimental predictors

It can be seen from Fig. 1 that social media usage is affected by internal (e.g. attitude towards social media, technical skills of employees) and external factors (e.g. pressure from stakeholders) of the company. Also, the figure depicts the effect of social media on the business (e.g. sales) and society (e.g. customer satisfaction).

5 Discussion

In reviewing the publications gathered for this paper, the following themes were identified. Some studies investigated the effect of social media use by B2B companies. By using mostly survey to collect the data from salespeople and managers, the studies found that social media has a positive effect on number of outcomes important for the business such as customer satisfaction, value creation, intention to buy and sales, customer relationships, brand awareness, knowledge creation, corporate credibility, acquiring new customers, salespersons performance, employee brand management, and sustainability. Most of the outcomes are similar to the research on social media in the context of B2C companies. However, some of the outcomes are unique for B2B context (e.g. employee brand management, company credibility). Just recently, studies started investigating the impact of the use of social media on sustainability.

Another group of studies looked at the adoption of social media by B2B companies (Buratti et al. 2018 ; Gáti et al. 2018 ; Gazal et al. 2016 ; Itani et al. 2017 ; Kumar and Möller 2018 ). The studies investigated it mostly from the perspectives of salespersons and identify some of the key factors which affect the adoption, such as innovativeness, technical skills of employees, pressure from stakeholders, perceived usefulness, and perceived usability. As these factors are derived mostly from surveys conducted with salespersons findings can be different for other individuals working in the organisation. This it is important to conduct studies that will examine factors affecting the adoption of social media across the entire organisation, in different departments. Using social media as part of the digital transformation is much bigger than sales and marketing, it encompasses the entire company. Additionally, most of the studies were cross-sectional, which limits the understanding of the adoption of social media by B2B over time depending on the outcomes and environment (e.g. competitors using social media).

Some studies looked at social media strategies of B2B companies (Cawsey and Rowley 2016 ; Huotari et al. 2015 ; Kasper et al. 2015 ; McShane et al. 2019 ; Mudambi et al. 2019 ). By employing interviews with companies’ managers and analysing its social media platforms (e.g. Twitter) it was found that most of the companies follow the following strategies: 1) monitoring and listening 2) empowering and engaging employees 3) creating compelling content 4) stimulating eWOM 5) evaluating and selecting channels 6) enhancing brand presence through integrating social media (Cawsey and Rowley 2016 ). Some studies investigated the difference between social media strategies of B2B and B2C companies. For example, a study by Swani et al. ( 2017 ) focused on effective social media strategies. By applying psychological motivation theory the study examined the key differences in B2B and B2C social media message strategies in terms of branding, message appeals, selling, and information search. The study used Facebook posts on brand pages of 280 Fortune companies. In total, 1467 posts were analysed. By using Bayesian models, the results showed that the inclusion of corporate brand names, functional and emotional appeals and information search cues increases the popularity of B2B messages in comparison with B2C messages. Also, it was found that readers of B2B content show a higher message liking rate and lower message commenting rate in comparison with readers of B2C messages.

The next group of studies looked at social media use by B2B companies (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ; Habibi et al. 2015 ). B2B companies use social media for enhancing and managing customer relationships (Andersson and Wikström 2017 ; Bolat et al. ( 2016 ); branding (Andersson and Wikström 2017 ; Bolat et al. 2016 ), sensing market (Bolat et al. 2016 ) and co-production (Chirumalla et al. 2018 ). Additionally, it was mentioned that some of the B2B companies use social media as a recruiting tool, and tool which helps to collaborate globally (Andersson and Wikström 2017 ; Dyck 2010 ).

It is important for companies to not only use social media to achieve positive business outcomes but also it is important to measure their achievements. As a result, some of the studies focused on the measuring effectiveness of social media (Gazal et al. 2016 ; Michaelidou et al. 2011 ; Vasudevan and Kumar 2018 ). Surprisingly, it was found that not so many companies measure ROI from social media (Gazal et al. 2016 ; Michaelidou et al. 2011 ). The ones who do it mostly use quantitative metrics (number of site visits, number of social network friends, number of comments and profile views) and qualitative metrics (growth of relationships with key audience, audience participation, moving from monologue to dialogue with consumers) (Gazal et al. 2016 ). Some future studies should investigate how ROI influences the strategy of B2B companies over period of time.

The last group of studies focused on social media tools used by B2B companies (Keinänen and Kuivalainen 2015 ; Mehmet and Clarke 2016 ; Yang et al. 2012 ). By using number of social media tools (Social Semiotic Multimodal) companies are able to improve their analysis of social media communications and identify their future consumers based on their user relationships. Studies investigating barriers and factors adoption of various social media tools by B2B companies are needed.

After reviewing studies on b2B social media, weight analysis was performed. Based on the results of weight analysis the conceptual model for future studies was proposed (Fig.  2 ). It is important to note that a limited number of studies focused and empirically tested factors affecting the adoption, use, and effect of social media. As a result, identified factors were considered as experimental (examined less than five times). It is too early to label these experimental predictors as worst or best, thus their further investigation is encouraged.

Social media impact on digital transformation and sustainable societies

Additionally, our review of the literature on B2B social media identified dominant research methods used by scholars. Qualitative and quantitative techniques were used by most of these studies. Closer analysis of 70 publications reviewed in this study revealed the multiple techniques applied for gathering data. Quantitative methods used in the studies mostly used surveys (see Table 4 ).

The data was mostly gathered from salespersons, managers and data from social media platforms (e.g. Twitter, Facebook). Just a limited number of studies employed consumer reported data (see Table 5 ).

On the other hand, publications using qualitative methods mainly used interviews and web scraping for the collection of the required data. To analyse the data studies used a variety of techniques including SEM, regression analysis and content analysis being one of the most used (see Table 6 ).

5.1 Digital Transformation and Sustainability Model

Based on the conducted literature review and adapting the model by Pappas et al. ( 2018 ) Fig. 2 presents the digital transformation and sustainability model in the context of B2B companies, which conceptualise the social media ecosystems, and the factors that need to collaborate to enable the use of social media towards the achievement of digital transformation and the creation of sustainable societies. The model comprises of social media stakeholders, the use of social media by B2B companies, and effect of social media on business and society.

5.1.1 Social Media Stakeholders

Building on the discussion and model provided by Pappas et al. ( 2018 ), this paper posits that the social media ecosystem comprises of the data stakeholders (company, society), who engage on social media (posting, reading, using information from social media). The use of social media by different stakeholders will lead to different effects affecting companies, customers and society. This is an iterative process based on which the stakeholders use their experience to constantly improve and evolve their use of social media, which has impacts on both, business and society. The successful implementation of this process is key to digital transformation and the creation of sustainable societies. Most of the current studies (Andersson et al. 2013 ; Bernard 2016 ; Bolat et al. 2016 ; Denktaş-Şakar and Sürücü 2018 ; Dyck 2010 ; Guesalaga 2016 ) focus mostly on the company as a stakeholder. However, more research is needed on other types of stakeholders (e.g. society).

5.1.2 Use of Social Media by B2B Companies

Social media affects not only ways how companies connect with their clients, but it is also changing their business models, the way how the value is delivered and profit is made. To successfully implement and use social media, B2B companies need to consider various social media tools, antecedents/barriers of its adoption, identify suitable social media strategies which are in line with the company’s overall strategy, and measure effectiveness of the use of social media. There are various factors that affect the use of social media by B2B companies. The study found that social media usage is influenced by perceived ease of use, adoption of social media, attitude towards social media and age of salesperson.

The majority of the studies focus on the management of the marketing department. However, digital transformation is much bigger than just marketing as it encompasses the entire organisation. As a result, future studies should look like the entire organisation and investigate barriers and factors affecting the use of social media.

It is crucial for companies to design content which will be noticed on social media by their potential, actual and former customers. Social media content should be interesting and offer some beneficial information, rather than just focus on services the company provides. Companies could use fresh views on relevant industry news, provide information how they are contributing to society and environment, include humour in their posts, share information about the team, make it more personal. It is also useful to use images, infographics, and video content.

It is also important for companies to measure digital marketing actions. More studies are needed on how to isolate the impact of specific media marketing actions to demonstrate their impact on the desired business outcomes (Salo 2017 ). Thus, future studies can consider how particular social media channels (e.g. Facebook, LinkedIn) in a campaign of a new product/ service influence brand awareness and sales level. Also, a limited number of studies discussed the way B2B companies can measure ROI. Future research should investigate how companies can measure intangible ROI, such as eWOM, brand awareness, and customer engagement (Kumar and Mirchandani 2012 ). Also, future research should investigate the reasons why most of the users do not assess the effectiveness of their SNS. Furthermore, most of the studies focused on likes, shares, and comments to evaluate social media engagement. Future research should focus on other types of measures. More research needs considering the impact of legislation on the use of social media by companies. Recent B2B studies did not consider recent legislation (General Data Protection Regulation 2018 ) in the context B2B (Sivarajah et al. 2019 ).

5.1.3 Effect of Social Media on Business and Society

Social media plays an important part in the company’s decision-making process. Social media can bring positive changes into company, which will result in improving customer satisfaction, value creation, increase in sales, building relationships with customers, knowledge creation, improve the perception of corporate credibility, acquisition of new customers, and improve employment brand engagement. Using information collected from social media can help companies to have a set of reliable attributes that comprise social, economic and environmental aspects in their decision-making process (Tseng 2017 ). Additionally, by using social media B2B companies can provide information to other stakeholders on their sustainability activities. By using data from social media companies will be able to provide products and services which are demanded by society. It will improve the quality of life and result in less waste. Additionally, social media can be considered as a tool that helps managers to integrate business practices with sustainability (Sivarajah et al. 2019 ). As a result, social media use by B2B companies can lead to business and societal changes.

A limited number of studies investigated the effect of social media on word of mouth communications in the B2B context. Future research should investigate the differences and similarities between B2C and B2B eWOM communications. Also, studies should investigate how these types of communications can be improved and ways to deal with negative eWOM. It is important for companies to respond to comments on social media. Additionally, future research should investigate its perceived helpfulness by customers.

Majority of studies (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Rossmann and Stei 2015 ; Agnihotri et al. 2012 ; Agnihotri et al. 2017 ; Itani et al. 2017 ; Salo 2017 ; Bhattacharjya and Ellison 2015 ; Gáti et al. 2018 ; Gruner and Power 2018 ; Hollebeek 2019 ) investigated positive effect of social media such consumer satisfaction, consumer engagement, and brand awareness. However, it will be interesting to consider the dark side of social media use such as an excessive number of requests on social media to salespeople (Agnihotri et al. 2016 ), which can result in the reduction of the responsiveness; spread of misinformation which can damage the reputation of the company.

Studies were performed in China (Lacka and Chong 2016 ; Niedermeier et al. 2016 ), the USA (Guesalaga 2016 ; Iankova et al. 2018 ; Ogilvie et al. 2018 ), India (Agnihotri et al. 2017 ; Vasudevan and Kumar 2018 ), the UK (Bolat et al. 2016 ; Iankova et al. 2018 ; Michaelidou et al. 2011 ). It is strongly advised that future studies conduct research in other countries as findings can be different due to the culture and social media adoption rates. Future studies should pay particular attention to other emerging markets (such as Russia, Brazil, and South Africa) as they suffer from the slow adoption rate of social media marketing. Some companies in these countries still rely more on traditional media for advertising of their products and services, as they are more trusted in comparison with social media channels (Olotewo 2016 ). The majority of studies investigate the effect of social media in B2B or B2C context. Future studies should pay attention to other contexts (e.g. B2B2B, B2B2C). Another limitation of the current research on B2B companies is that most of the studies on social media in the context of B2B focus on the effect of social media use only on business outcomes. It is important for future research to focus on societal outcomes.

Lastly, most of the studies on social media in the context of B2B companies use a cross-sectional approach to collect the data. Future research can use the longitudinal approach in order to advance understanding of social media use and its impact over time.

5.2 Research Propositions

Based on the social media research in the context of B2B companies and the discussion above the following is proposed, which could serve as a foundation for future empirical work.

Social media is a powerful tool to deliver information to customers. However, social media can be used to get consumer and market insights (Kazienko et al. 2013 ). A number of studies highlighted how information obtained from a number of social media platforms could be used for various marketing purposes, such as understanding the needs and preferences of consumers, marketing potential for new products/services, and current market trends (Agnihotri et al. 2016 ; Constantinides et al. 2008 ). It is advised that future research employs a longitudinal approach to study the impact of social media use on understanding customers. Therefore, the following proposition can be formulated:

Proposition 1

Social media usage of B2B companies has a positive influence on understanding its customers.

By using social media companies can examiner valuable information on competitors. It can help to understand competitors’ habits and strategies, which can lead to the competitive advantage and help strategic planning (Dey et al. 2011 ; Eid et al. 2019 ; Teo and Choo 2001 ). It is advised that future research employs a longitudinal approach to study the impact of social media use on understanding its competitors. As a result, using social media to understand customers and competitors can create business value (Mikalef et al. 2020a ) for key stakeholders and lead to positive changes in the business and societies. The above discussion leads to the following proposition:

Proposition 2

Social media usage of B2B companies has a positive influence on understanding its competitors.

Proposition 3

Culture influences the adoption and use of social media by B2B companies.

Usage of social media can result in some positive marketing outcomes such as building new customer relationships, increasing brand awareness, and level of sales to name a few (Agnihotri et al. 2016 ; Ancillai et al. 2019 ; Dwivedi et al. 2020 ; Rossmann and Stei 2015 ). However, when social media is not used appropriately it can lead to negative consequences. If a company does not have enough resources to implement social media tools the burden usually comes on a salesperson. A high number of customer inquiries, the pressure to engage with customers on social media, and monitor communications happening on various social media platforms can result in the increased workload of a salesperson putting extra pressure (Agnihotri et al. 2016 ). As a result, a salesperson might not have enough time to engage with all the customers online promptly or engage in reactive and proactive web care. As a result, customer satisfaction can be affected as well as company reputation. To investigate the negative impact of social media research could apply novel methods for data collection and analysis such as fsQCA (Pappas et al. 2020 ), or implying eye-tracking (Mikalef et al. 2020b ). This leads to the following proposition:

Proposition 4

Inappropriate use of social media by B2B companies has a negative effect on a) customer satisfaction and b) company reputation.

According to Technology-Organisation-Environment (TOE) framework environmental context significantly affects a company’s use of innovations (Abed 2020 ; Oliveira and Martins 2011 ). Environment refers to the factors which affect companies from outside, including competitors and customers. Adopting innovation can help companies to change the rules of the competition and reach a competitive advantage (Porter and Millar 1985 ). In a competitive environment, companies have a tendency to adopt an innovation. AlSharji et al. ( 2018 ) argued that the adoption of innovation can be extended to social media use by companies. A study by AlSharji et al. ( 2018 ) by using data from 1700 SMEs operating in the United Arab Emirates found that competitive pressure significantly affects the use of social media by SMEs. It can be explained by the fact that companies could feel pressure when other companies in the industry start adopting a particular technology and as a result adopt it to remain competitive (Kuan and Chau 2001 ). Based on the above discussion, the following proposition can be formulated:

Proposition 5

Competitive pressure positively affects the adoption of social media by B2B companies.

Companies might feel that they are forced to adopt and use IT innovations because their customers would expect them to do so. Meeting customers’ expectations could result in adoption of new technologies by B2B companies. Some research studies investigated the impact of customer pressure on companies (AlSharji et al. 2018 ; Maduku et al. 2016 ). For example, a study by Maduku et al. ( 2016 ) found that customer pressure has a positive effect on SMEs adoption of mobile marketing in the context of South Africa. Future research could implement longitudinal approach to investigate how environment affects adoption of social media by B2B companies. This leads to the formulation of the following proposition:

Proposition 6

Customer pressure positively affects the adoption of social media by B2B companies.

6 Conclusion

The aim of this research was to provide a comprehensive systematic review of the literature on social media in the context of B2B companies and propose the framework outlining the role of social media in the digital transformation of B2B companies. It was found that B2B companies use social media, but not all companies consider it as part of their marketing strategies. The studies on social media in the B2B context focused on the effect of social media, antecedents, and barriers of adoption of social media, social media strategies, social media use, and measuring the effectiveness of social media. Academics and practitioners can employ the current study as an informative framework for research on the use of social media by B2B companies. The summary of the key observations provided from this literature review is the following: [i] Facebook, Twitter, and LinkedIn are the most famous social media platforms used by B2B companies, [ii] Social media has a positive effect on customer satisfaction, acquisition of new customers, sales, stakeholder engagement, and customer relationships, [iii] In systematically reviewing 70 publications on social media in the context of B2B companies it was observed that most of the studies use online surveys and online content analysis, [iv] Companies still look for ways to evaluate the effectiveness of social media, [v] Innovativeness, pressure from stakeholders, perceived usefulness, and perceived usability have a significant positive effect on companies’ adoption to use social media, [vi] Lack of staff familiarity and technical skills are the main barriers that affect the adoption of social media by B2B, [vii] Social media has an impact not only on business but also on society, [viii] There is a dark side of social media: fake online reviews, an excessive number of requests on social media to salespeople, distribution of misinformation, negative eWOM, [ix] Use of social media by companies has a positive effect on sustainability, and [x] For successful digital transformation social media should change not only the way how companies integrate it into their marketing strategies but the way how companies deliver values to their customers and conduct their business. This research has a number of limitations. First, only publications from the Scopus database were included in literature analysis and synthesis. Second, this research did not use meta-analysis. To provide a broader picture of the research on social media in the B2B context and reconcile conflicting findings of the existing studies future research should conduct a meta-analysis (Ismagilova et al. 2020c ). It will advance knowledge of the social media domain.

Abed, S. S. (2020). Social commerce adoption using TOE framework: An empirical investigation of Saudi Arabian SMEs. International Journal of Information Management, 53 , 102118.

Article   Google Scholar  

Agnihotri, R., Kothandaraman, P., Kashyap, R., & Singh, R. (2012). Bringing “social” into sales: The impact of salespeople’s social media use on service behaviors and value creation. Journal of Personal Selling and Sales Management, 32 (3), 333–348. https://doi.org/10.2753/PSS0885-3134320304 .

Agnihotri, R., Dingus, R., Hu, M. Y., & Krush, M. T. (2016). Social media: Influencing customer satisfaction in B2B sales. Industrial Marketing Management, 53 , 172–180. https://doi.org/10.1016/j.indmarman.2015.09.003 .

Agnihotri, R., Trainor, K. J., Itani, O. S., & Rodriguez, M. (2017). Examining the role of sales-based CRM technology and social media use on post-sale service behaviors in India. Journal of Business Research, 81 , 144–154. https://doi.org/10.1016/j.jbusres.2017.08.021 .

Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics, 34 (7), 1177–1190.

AlSharji, A., Ahmad, S. Z., & Bakar, A. R. A. (2018). Understanding social media adoption in SMEs. Journal of Entrepreneurship in Emerging Economies, 10 (2), 302–328.

Ancillai, C., Terho, H., Cardinali, S., & Pascucci, F. (2019). Advancing social media driven sales research: Establishing conceptual foundations for B-to-B social selling. Industrial Marketing Management, 82 , 293–308. https://doi.org/10.1016/j.indmarman.2019.01.002 .

Andersson, S., & Wikström, N. (2017). Why and how are social media used in a B2B context, and which stakeholders are involved? Journal of Business and Industrial Marketing, 32 (8), 1098–1108. https://doi.org/10.1108/JBIM-07-2016-0148 .

Andersson, S., Evers, N., & Griot, C. (2013). Local and international networks in small firm internationalization: Cases from the Rhône-Alpes medical technology regional cluster. Entrepreneurship & Regional Development, 25 (9–10), 867–888.

Andzulis, J. M., Panagopoulos, N. G., & Rapp, A. (2012). A review of social media and implications for the sales process. Journal of Personal Selling & Sales Management, 32 (3), 305–316.

Barreda, A. A., Bilgihan, A., Nusair, K., & Okumus, F. (2015). Generating brand awareness in online social networks. Computers in Human Behavior, 50 , 600–609.

Bell, D., & Shirzad, S, R. (2013). Social media domain analysis (SoMeDoA): A pharmaceutical study. 9th international conference on web information systems and technologies, 561–570.  https://doi.org/10.5220/0004499105610570 .

Bernard, M. (2016). The impact of social media on the B2B CMO. Journal of Business and Industrial Marketing, 31 (8), 955–960. https://doi.org/10.1108/JBIM-10-2016-268 .

Bhattacharjya, J., & Ellison, A, B. (2015). Building business resilience with social media in B2B environments: The emergence of responsive customer relationship management processes on twitter. Working Conference on Virtual Enterprises doi: https://doi.org/10.1007/978-3-319-24141-8_15 .

Bolat, E., Kooli, K., & Wright, L. T. (2016). Businesses and mobile social media capability. Journal of Business and Industrial Marketing, 31 (8), 971–981. https://doi.org/10.1108/JBIM-10-2016-270 .

Buratti, N., Parola, F., & Satta, G. (2018). Insights on the adoption of social media marketing in B2B services. TQM Journal, 30 (5), 490–529. https://doi.org/10.1108/TQM-11-2017-0136 .

Cawsey, T., & Rowley, J. (2016). Social media brand building strategies in B2B companies. Marketing Intelligence and Planning, 34 (6), 754–776. https://doi.org/10.1108/MIP-04-2015-0079 .

Chatterjee, S., & Kar, A. K. (2020). Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India. International Journal of Information Management, 53 , 102103.

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36 , 1165–1188.

Chirumalla, K., Oghazi, P., & Parida, V. (2018). Social media engagement strategy: Investigation of marketing and R&D interfaces in manufacturing industry. Industrial Marketing Management, 74 , 138–149. https://doi.org/10.1016/j.indmarman.2017.10.001 .

Constantinides, E., Romero, C. L., & Boria, M. A. G. (2008). Social media: A new frontier for retailers?. In European retail research (pp. 1–28) . Wiesbaden: Gabler Verlag.

Google Scholar  

Denktaş-Şakar, G., & Sürücü, E. (2018). Stakeholder engagement via social media: An analysis of third-party logistics companies. Service Industries Journal, 40 , 866–889. https://doi.org/10.1080/02642069.2018.1561874 .

Dey, L., Haque, S, M., Khurdiya, A., & Shroff, G. (2011). Acquiring competitive intelligence from social media. In proceedings of the 2011 joint workshop on multilingual OCR and analytics for noisy unstructured text data (pp. 1-9) . https://doi.org/10.1145/2034617.2034621 .

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019a). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21 (3), 719–734.

Dwivedi, Y, K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Galanos, V. (2019b). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management , 101994, doi: https://doi.org/10.1016/j.ijinfomgt.2019.08.002 .

Dwivedi, Y, K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., ... & Kumar, V. (2020). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management , 102168, doi: https://doi.org/10.1016/j.ijinfomgt.2020.102168 .

Dyck, P. V. (2010). As social media evolves, the device industry must also. Medical Device and Diagnostic Industry, 32 (8).

Eid, R., Abdelmoety, Z., & Agag, G. (2019). Antecedents and consequences of social media marketing use: An empirical study of the UK exporting B2B SMEs. Journal of Business & Industrial Marketing., 35 , 284–305.

Gáti, M., Mitev, A., & Bauer, A. (2018). Investigating the impact of salespersons’ use of technology and social media on their customer relationship performance in B2B settings. Trziste, 30 (2), 165–176. https://doi.org/10.22598/mt/2018.30.2.165 .

Gazal, K., Montague, I., Poudel, R., & Wiedenbeck, J. (2016). Forest products industry in a digital age: Factors affecting social media adoption. Forest Products Journal, 66 (5-6), 343–353. https://doi.org/10.13073/FPJ-D-15-00007 .

General Data Protection Regulation (2018). Guide to the General Data Protection Regulation. Available at https://www.gov.uk/government/publications/guide-to-the-general-data-protection-regulation . Accessed 28 Jan 2021.

Gregorio, J. (2017). 10 reasons to diversify your digital marketing efforts. Digital marketing Philippines. Available at https://digitalmarketingphilippines.com/10-reasons-to-diversify-your-digital-marketing-efforts// Accessed on April , 27 , 2019.

Gruner, R. L., & Power, D. (2018). To integrate or not to integrate? Understanding B2B social media communications. Online Information Review, 42 (1), 73–92. https://doi.org/10.1108/OIR-04-2016-0116 .

Guesalaga, R. (2016). The use of social media in sales: Individual and organizational antecedents, and the role of customer engagement in social media. Industrial Marketing Management, 54 , 71–79. https://doi.org/10.1016/j.indmarman.2015.12.002 .

Gupta, P., Chauhan, S., & Jaiswal, M. P. (2019). Classification of smart city research-a descriptive literature review and future research agenda. Information Systems Frontiers, 21 (3), 661–685.

Habibi, F., Hamilton, C. A., Valos, M. J., & Callaghan, M. (2015). E-marketing orientation and social media implementation in B2B marketing. European Business Review, 27 (6), 638–655. https://doi.org/10.1108/EBR-03-2015-0026 .

Harrigan, P., Miles, M. P., Fang, Y., & Roy, S. K. (2020). The role of social media in the engagement and information processes of social CRM. International Journal of Information Management, 54 , 102151.

Hollebeek, L. D. (2019). Developing business customer engagement through social media engagement-platforms: An integrative SD logic/RBV-informed model. Industrial Marketing Management, 81 , 89–98.

Hsiao, S. H., Wang, Y. Y., Wang, T., & Kao, T. W. (2020). How social media shapes the fashion industry: The spillover effects between private labels and national brands. Industrial Marketing Management, 86 , 40–51.

Huotari, L., Ulkuniemi, P., Saraniemi, S., & Mäläskä, M. (2015). Analysis of content creation in social media by B2B companies. Journal of Business and Industrial Marketing, 30 (6), 761–770. https://doi.org/10.1108/JBIM-05-2013-0118 .

Iankova, S., Davies, I., Archer-Brown, C., Marder, B., & Yau, A. (2018). A comparison of social media marketing between B2B, B2C and mixed business models. Industrial Marketing Management, 81 , 169–179. https://doi.org/10.1016/j.indmarman.2018.01.001 .

Iannacci, F., Fearon, C., & Pole, K. (2020). From acceptance to adaptive acceptance of social media policy change: A set-theoretic analysis of b2b SMEs. Information Systems Frontiers , 1-18. https://doi.org/10.1007/s10796-020-09988-1 .

Ismagilova, E., Dwivedi, Y. K., Slade, E., & Williams, M. D. (2017). Electronic word of mouth (eWOM) in the marketing context: A state of the art analysis and future directions . Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-52459-7 .

Ismagilova, E., Hughes, L., Dwivedi, Y. K., & Raman, K. R. (2019). Smart cities: Advances in research—An information systems perspective. International Journal of Information Management, 47 , 88–100.

Ismagilova, E., Slade, E. L., Rana, N. P., & Dwivedi, Y. K. (2020a). The effect of electronic word of mouth communications on intention to buy: A meta-analysis. Information Systems Frontiers, 22 , 1203–1226. https://doi.org/10.1007/s10796-019-09924-y .

Ismagilova, E., Slade, E., Rana, N. P., & Dwivedi, Y. K. (2020b). The effect of characteristics of source credibility on consumer behaviour: A meta-analysis. Journal of Retailing and Consumer Services, 53 , 101736.

Ismagilova, E., Rana, N, P., Slade, E., & Dwivedi, Y, K. (2020c). A meta-analysis of the factors affecting eWOM providing behaviour. European Journal of Marketing. doi: https://doi.org/10.1108/EJM-07-2018-0472 , ahead-of-print.

Itani, O. S., Agnihotri, R., & Dingus, R. (2017). Social media use in B2b sales and its impact on competitive intelligence collection and adaptive selling: Examining the role of learning orientation as an enabler. Industrial Marketing Management, 66 , 64–79. https://doi.org/10.1016/j.indmarman.2017.06.012 .

Jeyaraj, A., & Dwivedi, Y. K. (2020). Meta-analysis in information systems research: Review and recommendations. International Journal of Information Management, 55 , 102226.

Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21 (1), 1–23.

Juntunen, M., Ismagilova, E., & Oikarinen, E. L. (2020). B2B brands on twitter: Engaging users with a varying combination of social media content objectives, strategies, and tactics. Industrial Marketing Management, 89 , 630–641.

Jussila, J. J., Kärkkäinen, H., & Leino, M. (2011). Benefits of social media in business-to-business customer interface in innovation. 15th International Academic MindTrek Conference: Envisioning Future Media Environments . MindTrek, 2011 , 167–174. https://doi.org/10.1145/2181037.2181065 .

Kamboj, S., Sarmah, B., Gupta, S., & Dwivedi, Y. (2018). Examining branding co-creation in brand communities on social media: Applying the paradigm of stimulus-organism-response. International Journal of Information Management, 39 , 169–185.

Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K., & Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers, 20 (3), 531–558.

Kärkkäinen, H., Jussila, J., & Janhonen, J. (2011). Managing customer information and knowledge with social media in business-to-business companies. ACM International Conference Proceeding Series, doi: https://doi.org/10.1145/2024288.2024309 .

Kasper, H., Koleva, I., & Kett, H. (2015). Social media matrix matching corporate goals with external social media activities doi: https://doi.org/10.1007/978-3-662-46641-4_17 .

Katona, Z., & Sarvary, M. (2014). Maersk line: B2B social media-“it’s communication, not marketing. California Management Review , 56(3), 142–156. doi: https://doi.org/10.1525/cmr.2014.56.3.142 .

Kazienko, P., Szozda, N., Filipowski, T., & Blysz, W. (2013). New business client acquisition using social networking sites. Electronic Markets, 23 (2), 93–103. https://doi.org/10.1007/s12525-013-0123-9 .

Keinänen, H., & Kuivalainen, O. (2015). Antecedents of social media B2B use in industrial marketing context: Customers’ view. Journal of Business and Industrial Marketing, 30 (6), 711–722. https://doi.org/10.1108/JBIM-04-2013-0095 .

Kho, N. D. (2008). B2B gets social media. EContent, 31 (3), 26–30.

Kovac, M. (2016). Social media works for B2B sales, too. Harvard Business Review. Retrieved from https://hbr.org/2016/01/social-media-worksfor-b2b-sales-too . Accessed on April , 27 , 2020 .

Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & Management, 38 (8), 507–521.

Kumar, V., & Mirchandani, R. (2012). Increasing the ROI of social media marketing. MIT Sloan Management Review, 54 (1), 55–61.

Kumar, A., & Möller, K. (2018). Extending the boundaries of corporate branding: An exploratory study of the influence of brand familiarity in recruitment practices through social media by B2B firms. Corporate Reputation Review, 21 (3), 101–114. https://doi.org/10.1057/s41299-018-0046-7 .

Kunsman, T. (2018). Internal marketing: Why your company should prioritize it. https://everyonesocial.com/blog/internal-marketing/ . Accessed on September, 25, 2019.

Lacka, E., & Chong, A. (2016). Usability perspective on social media sites' adoption in the B2B context. Industrial Marketing Management, 54 , 80–91. https://doi.org/10.1016/j.indmarman.2016.01.001 .

Lal, B., Ismagilova, E., Dwivedi, Y.,. K., & Kwayu, S. (2020). Return on Investment in Social Media Marketing: Literature review and suggestions for future research. In Digital and Social Media Marketing (pp. 3–17) . Cham: Springer.

Lashgari, M., Sutton-Brady, C., Solberg Søilen, K., & Ulfvengren, P. (2018). Adoption strategies of social media in B2B firms: A multiple case study approach. Journal of Business and Industrial Marketing, 33 (5), 730–743. https://doi.org/10.1108/JBIM-10-2016-0242 .

Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24 (3), 149–157.

Maduku, D. K., Mpinganjira, M., & Duh, H. (2016). Understanding mobile marketing adoption intention by south African SMEs: A multi-perspective framework. International Journal of Information Management, 36 (5), 711–723.

Mahrous, A, A. (2013). Social media marketing: Prospects for marketing theory and practice on the social web. E-marketing in developed and developing countries: Emerging practices (pp. 56-68) doi: https://doi.org/10.4018/978-1-4666-3954-6.ch004 Retrieved from www.scopus.com .

McAfee, A. P. (2006). Enterprise 2.0: The dawn of emergent collaboration. Enterprise, 2 , 15–26.

McKinsey & Company (2015). Transforming the business through social tools. McKinsey.com , ( http://www.mckinsey.com/industries/high-tech/our-insights/transformingthe-business-through-social-tools ).

McShane, L., Pancer, E., & Poole, M. (2019). The influence of B to B social media message features on brand engagement: A fluency perspective. Journal of Business-to-Business Marketing, 26 (1), 1–18. https://doi.org/10.1080/1051712X.2019.1565132 .

Mehmet, M. I., & Clarke, R. J. (2016). B2B social media semantics: Analysing multimodal online meanings in marketing conversations. Industrial Marketing Management, 54 , 92–106. https://doi.org/10.1016/j.indmarman.2015.12.006 .

Meire, M., Ballings, M., & Van den Poel, D. (2017). The added value of social media data in B2B customer acquisition systems: A real-life experiment. Decision Support Systems, 104 , 26–37. https://doi.org/10.1016/j.dss.2017.09.010 .

Michaelidou, N., Siamagka, N. T., & Christodoulides, G. (2011). Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands. Industrial Marketing Management, 40 (7), 1153–1159. https://doi.org/10.1016/j.indmarman.2011.09.009 .

Mikalef, P., Pappas, I. O., Krogstie, J., & Pavlou, P. A. (2020a). Big data and business analytics: A research agenda for realizing business value. Information & Management, 57 (1), 103237.

Mikalef, P., Sharma, K., Pappas, I, O., & Giannakos, M. (2020b). Seeking information on social commerce: An examination of the impact of user-and marketer-generated content through an eye-tracking study. Information Systems Frontiers , 1-14, doi: https://doi.org/10.1007/s10796-020-10034-3 .

Minsky, L., & Quesenberry, K, A. (2016). How B2B sales can benefit from social selling . Harvard Business Review. Available at https://hbr.org/2016/11/84-of-b2b-sales-start-with-a-referral-not-a-salesperson . Accessed 28 Jan 2021.

Moncrief, W. C., Marshall, G. W., & Rudd, J. M. (2015). Social media and related technology: Drivers of change in managing the contemporary sales force. Business Horizons, 58 (1), 45–55. https://doi.org/10.1016/j.bushor.2014.09.009 .

Moore, J. N., Hopkins, C. D., & Raymond, M. A. (2013). Utilization of relationship-oriented social media in the selling process: A comparison of consumer (B2C) and industrial (B2B) salespeople. Journal of Internet Commerce, 12 (1), 48–75. https://doi.org/10.1080/15332861.2013.763694 .

Moore, J. N., Raymond, M. A., & Hopkins, C. D. (2015). Social selling: A comparison of social media usage across process stage, markets, and sales job functions. Journal of Marketing Theory and Practice, 23 (1), 1–20. https://doi.org/10.1080/10696679.2015.980163 .

Mudambi, S. M., Sinha, J. I., & Taylor, D. S. (2019). Why B-to-B CEOs should be more social on social media. Journal of Business-to-Business Marketing, 26 (1), 103–105. https://doi.org/10.1080/1051712X.2019.1565144 .

Muhammad, S. S., Dey, B. L., & Weerakkody, V. (2018). Analysis of factors that influence customers’ willingness to leave big data digital footprints on social media: A systematic review of literature. Information Systems Frontiers, 20 (3), 559–576.

Müller, L., Griesbaum, J., & Mandl, T. (2013). Social media relations in the german automotive market. Paper presented at the proceedings of the IADIS international conference ICT, society and human beings 2013, Proceedings of the IADIS International Conference e-Commerce 2013, 19–26.

Müller, J. M., Pommeranz, B., Weisser, J., & Voigt, K. I. (2018). Digital, social media, and Mobile marketing in industrial buying: Still in need of customer segmentation? Empirical evidence from Poland and Germany. Industrial Marketing Management, 73 , 70–83. https://doi.org/10.1016/j.indmarman.2018.01.033 .

Niedermeier, K. E., Wang, E., & Zhang, X. (2016). The use of social media among business-to-business sales professionals in China: How social media helps create and solidify guanxi relationships between sales professionals and customers. Journal of Research in Interactive Marketing, 10 (1), 33–49. https://doi.org/10.1108/JRIM-08-2015-0054 .

Nunan, D., Sibai, O., Schivinski, B., & Christodoulides, G. (2018). Reflections on “social media: Influencing customer satisfaction in B2B sales” and a research agenda. Industrial Marketing Management, 75 , 31–36. https://doi.org/10.1016/j.indmarman.2018.03.009 .

Ogilvie, J., Agnihotri, R., Rapp, A., & Trainor, K. (2018). Social media technology use and salesperson performance: A two study examination of the role of salesperson behaviors, characteristics, and training. Industrial Marketing Management, 75 , 55–65. https://doi.org/10.1016/j.indmarman.2018.03.007 .

Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. Electronic Journal of Information Systems Evaluation, 14 (1), 110.

Olotewo, J. (2016). Social media marketing in emerging markets. International Journal of Online Marketing Research, 2 (2), 10–18.

Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2018). Big data and business analytics ecosystems: Paving the way towards digital transformation and sustainable societies. Information Systems and e-Business Management, 16 , 479–491.

Pappas, I. O., Papavlasopoulou, S., Mikalef, P., & Giannakos, M. N. (2020). Identifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approach. International Journal of Information Management, 53 , 102128.

Pascucci, F., Ancillai, C., & Cardinali, S. (2018). Exploring antecedents of social media usage in B2B: A systematic review. Management Research Review, 41 (6), 629–656. https://doi.org/10.1108/MRR-07-2017-0212 .

Pitt, C. S., Plangger, K. A., Botha, E., Kietzmann, J., & Pitt, L. (2017). How employees engage with B2B brands on social media: Word choice and verbal tone. Industrial Marketing Management, 81 , 130–137. https://doi.org/10.1016/j.indmarman.2017.09.012 .

Pitt, C. S., Botha, E., Ferreira, J. J., & Kietzmann, J. (2018). Employee brand engagement on social media: Managing optimism and commonality. Business Horizons, 61 (4), 635–642. https://doi.org/10.1016/j.bushor.2018.04.001 .

Porter, M. E., & Millar, V. E. (1985). How information gives you competitive advantage. Harvard Business Review, 63 (4), 149–160.

Pulizzi, J., & Handley, A. (2017). B2C content marketing-2018 benchmarks, budgets, and trends—North America. Available at https://contentmarketinginstitute.com/wp-content/uploads/2016/09/2017_B2B_Research_FINAL.pdf Accessed on April , 27 , 2020.

Rana, N. P., Dwivedi, Y. K., & Williams, M. D. (2015). A meta-analysis of existing research on citizen adoption of e-government. Information Systems Frontiers, 17 (3), 547–563.

Rana, N. P., Luthra, S., Mangla, S. K., Islam, R., Roderick, S., & Dwivedi, Y. K. (2019). Barriers to the development of smart cities in Indian context. Information Systems Frontiers, 21 (3), 503–525.

Rodriguez, M., Peterson, R. M., & Krishnan, V. (2012). Social media's influence on business-to-business sales performance. Journal of Personal Selling and Sales Management, 32 (3), 365–378. https://doi.org/10.2753/PSS0885-3134320306 .

Rossmann, A., & Stei, G. (2015). Sales 2.0 in business-to-business (B2B) networks: Conceptualization and impact of social media in B2B sales relationships . Paper presented at the Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft Fur Informatik (GI), 244 67–78. Available at https://subs.emis.de/LNI/Proceedings/Proceedings244/67.pdf . Accessed 28 Jan 2021.

Salo, J. (2017). Social media research in the industrial marketing field: Review of literature and future research directions. Industrial Marketing Management, 66 , 115–129. https://doi.org/10.1016/j.indmarman.2017.07.013 .

Shaltoni, A. M. (2017). From websites to social media: Exploring the adoption of internet marketing in emerging industrial markets. Journal of Business and Industrial Marketing, 32 (7), 1009–1019. https://doi.org/10.1108/JBIM-06-2016-0122 .

Siamagka, N. T., Christodoulides, G., Michaelidou, N., & Valvi, A. (2015). Determinants of social media adoption by B2B organizations. Industrial Marketing Management, 51 , 89–99. https://doi.org/10.1016/j.indmarman.2015.05.005 .

Sivarajah, U., Irani, Z., Gupta, S., & Mahroof, K. (2019). Role of big data and social media analytics for business to business sustainability: A participatory web context. Industrial Marketing Management . https://doi.org/10.1016/j.indmarman.2019.04.005 .

Sobal, A. (2017). 30 statistics about B2B social media usage. Available at https://www.weidert.com/blog/statistics-about-b2b-social-media-usage Accessed on April , 27 , 2020.

Stelzner, M. (2011). 2012 social media marketing industry report. Social media examiner . Available at https://www.socialmediaexaminer.com/socialmedia-marketing-industry-report-2012/ . Accessed 28 Jan 2021.

Sułkowski, Ł., & Kaczorowska-Spychalska, D. (2016). Social media in the process of marketing evolution in polish textile-clothing industry. Fibres and Textiles in Eastern Europe, 24 (5), 15–20. https://doi.org/10.5604/12303666.1215521 .

Swani, K., Milne, G., & Brown, B. P. (2013). Spreading the word through likes on facebook: Evaluating the message strategy effectiveness of fortune 500 companies. Journal of Research in Interactive Marketing, 7 (4), 269–294. https://doi.org/10.1108/JRIM-05-2013-0026 .

Swani, K., Brown, B. P., & Milne, G. R. (2014). Should tweets differ for B2B and B2C? An analysis of fortune 500 companies' twitter communications. Industrial Marketing Management, 43 (5), 873–881. https://doi.org/10.1016/j.indmarman.2014.04.012 .

Swani, K., Milne, G. R., Brown, B. P., Assaf, A. G., & Donthu, N. (2017). What messages to post? Evaluating the popularity of social media communications in business versus consumer markets. Industrial Marketing Management, 62 , 77–87. https://doi.org/10.1016/j.indmarman.2016.07.006 .

Tedeschi, B. (2006). Like shopping? Social networking? Try social shopping. New York Times, 11 , 09.

Teo, T. S., & Choo, W. Y. (2001). Assessing the impact of using the internet for competitive intelligence. Information & Management, 39 (1), 67–83.

Tseng, M. L. (2017). Using social media and qualitative and quantitative information scales to benchmark corporate sustainability. Journal of Cleaner Production, 142 , 727–738.

Vasudevan, S., & Kumar, F. J. P. (2018). Social media and B2B brands: An Indian perspective. International Journal of Mechanical Engineering and Technology, 9 (9), 767–775.

Vukanovic, Z. (2013). Managing social media value networks: From publisher (broadcast) to user-centric (broadband-narrowcast) business models. Handbook of social media management: Value chain and business models in changing media markets (pp. 269-288) doi: https://doi.org/10.1007/978-3-642-28897-5_16 .

Wang, Y., Rod, M., Ji, S., & Deng, Q. (2017). Social media capability in B2B marketing: Toward a definition and a research model. Journal of Business and Industrial Marketing, 32 (8), 1125–1135. https://doi.org/10.1108/JBIM-10-2016-0250 .

Watt, I. (2010). Changing visions of parliamentary libraries: From the enlightenment to Facebook. IFLA Journal, 36 (1), 47–60. https://doi.org/10.1177/0340035209359574 .

Webster, J., & Watson, R.,. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS quarterly, 26 (2), xiii–xxiii.

Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading digital: Turning technology into business transformation . Boston, MA: Harvard Business Press.

Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28 (3), 443–488.

World Commission Report on Environment and Development. (1987). Our Common Future . Oxford: Oxford University Press.

Yang, C. C., Yang, H., Tang, X., & Jiang, L. (2012). Identifying implicit relationships between social media users to support social commerce. In ACM international conference proceeding series (pp. 41–47). https://doi.org/10.1145/2346536.2346544 .

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Dwivedi, Y.K., Ismagilova, E., Rana, N.P. et al. Social Media Adoption, Usage And Impact In Business-To-Business (B2B) Context: A State-Of-The-Art Literature Review. Inf Syst Front 25 , 971–993 (2023). https://doi.org/10.1007/s10796-021-10106-y

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Emerging trends in social media marketing: a retrospective review using data mining and bibliometric analysis

• Abu Bashar 1 ,
• Mohammad Wasiq 2 ,
• Brighton Nyagadza   ORCID: orcid.org/0000-0001-7226-0635 3 , 4 &
• Eugine Tafadzwa Maziriri 5  

Future Business Journal volume  10 , Article number:  23 ( 2024 ) Cite this article

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The study conducts a comprehensive retrospective analysis of the social media marketing literature along with text mining and bibliometric analysis using data obtained from the Scopus database. The analysis is conducted for the literature published during 2007–2022 using VOSviewer application and Biblioshiny. The analysis revealed the publication trend and emerging themes in the research landscape of social media marketing. This study has pointed towards important theoretical and practical implications pertaining to the social media marketing. It contributes to the understanding of social media marketing research by identifying and listing the best journal, authors, country, documents, most occurred words, social and intellectual structure, and emerging research trends. The results revealed that social media marketing research is at the focal point of the researchers throughout the word. This study found that there are lack of studies from firm perspective especially small retailers; adoption of disruptive technologies such as AI, ML and block chain and its impact need more exploration.

Introduction

The term social media came in limelight in the early 1990s, and now, it became an inseparable entity of almost every individual having an estimated 2 billion + active users globally [ 24 ]. Social media is a dorm of computer-based programme that allows users to connect, create and share information and exchange views and ideas via specific virtual communities and groups (Aydin 2020). The advancement in technology especially mobile applications and cloud-based analytics had enabled firms to offer and connect to their customers in real time. The proliferation of e-commerce web and mobile applications gives rise to the tremendous growth of social media networks and has transformed the ways of communication between business and consumers who generally shares common interests and demographics [ 144 ]. Social media marketing can be regarded as a form of online marketing, and it has seen manifold growth in the recent past. The marketers are leveraging on social media platform to reach, interact, offer, and transact with their probable customers.

Many firms and brands are relying on the word-of-mouth marketing, and social media had played instrumental role in spreading word of mouth among their customers in a rapid manner that was never before. Additionally, the firms are leveraging social media network platform to expand globally [ 144 ]. Social media has influenced the way consumers were searching for information, evaluating them, and making purchase decision. Moreover, social media became an inseparable integral part of businesses to sustain in this digital disruptive world. The accessibility, ease of use, real-time bound activities and global reach have made social media as a unique marketing tool. Social media enables firm to create a virtual unique platform to mark their online presence, communicate with their target customers and engage with them to increase their revenue [ 90 ]. The increasing importance of social media as a marketing tool has attracted scholars especially researchers in the domain of online buying behaviour in the last decade. Therefore, existing literature on social media marketing is being continuously reviewed by scholars to understand the current trends and suggest the future directions. In recent years, researchers have studied the importance of social media in marketing from various aspects of its application. Few of the important bibliometric studies on social media marketing are mainly focussing on the social networks and platforms. Social media platforms and its role in the evolution and performance of social enterprise conducted by revealed that proper social media strategy is not only helping in increasing revenue and profitability, but also fostering confidence among the consumers. Similarly, bibliometric analysis on the pattern of co-creation , influencers , sentiments and stock market predictions and interactive digital marketing in the context of social media is conducted over the recent few years.

None of the current studies have focussed on the overall role, i.e. integrating and analysing studies focussed on behavioural intentions, impulse purchases, customer engagement, customer loyalty and recommender management of social media in the marketing landscape. The recent advancement in the mobile-based applications had forced the organizations to adopt marketing tools which are readily available to the consumers in real time [ 13 ]. This study is an attempt to gather quality articles pertaining to the marketing applications of social media and analyse its effectiveness as a marketing tool. This article will help the academicians to have a holistic idea about the research trends in social media marketing that will prove conducive to design marketing strategies for industry practitioners. To the best of our knowledge, such comprehensive review of social media as a marketing tool has never been conducted.

The rest of the article is organized as follows. The next section is based on the review of literature. The research methodology adopted for this study is described in section “ methods ”. Section “ Results ” is based on the data analysis and its interpretation, while limitations of this study and future research directions are presented in section “ Discussion ”. Conclusion is made in section “ Conclusions ”.

Review of literature

The current trends of the marketing research in the social media domain predicts that the traditional marketing is going to be entirely disrupted by the adoption of social media-based marketing. The marketing activities such as advertising, promotional programmes and branding seem to be entirely designed and applied using social media tools [ 144 ]. Social media adoption is on rise because of its wide presence in the masses and its easiness of access and operate. Therefore, social media became the first choice of the marketers to promote their products and services to reach to their target audience [ 39 ].

Social media is a specialized software application that connect people in an online environment, where they can interact with each other, share contents and their feedback in the relevant groups about their experiences with a brand or organization [ 137 ]. The marketers realized the importance of social media marketing and started using them as an integral part of their overall marketing strategies [ 89 ]. Social media platforms enable consumers to freely interact with their fellow users on these applications and discuss openly about the advantages or disadvantages of the products [ 20 , 80 ]. So, marketers look at social media as an opportunity to build their brand image and positively position their products in the mind of their target audience [ 123 ]. The word of mouth of the consumers is also of great concern for the firms, as it may harm the brand positioning if not managed in an appropriate manner [ 141 ].

Various social media platforms such as Facebook, Twitter, Instagram, Snapchat and LinkedIn are being used by companies based on their target audience and the products they promote. As noted by [ 74 ], Snapchat is more favourite among youths, LinkedIn is more useful for reaching to mature professionals, so the marketers are selecting the platforms that suits their marketing strategy. The literatures shows that social media users are reacting more on interactive advertising rather than informational one, and it promotes interactions and cultivates the in-group messaging among the users of a particular social media platform [ 11 ].

The synthesis of the recent literatures reveals that opinion leader is playing a crucial role around the online space, so the organizations need to select carefully their leaders who can foster confidence about the firm and positive image of the brands [ 25 ]. Moreover, content is the bone of the social media marketing, and marketers need to carefully select, design and present to their markets. The emotional appeals in the messaging and overall content have been found more influential as customers has responded more often as compared to any other appeals in the social media marketing space [ 92 , 109 ]. In a similar study, it has been found that consumers are finding live videos streaming more trustworthy and authentic as compared to pre-recorded videos [ 23 ].

Therefore, it can be concluded that social media marketing is having a greater impact on the firm, and it can bring variety of positive and negative outcomes. Studies have shown that social media marketing is having positive and substantial impact on the consumer behaviour and especially on consumer retention [ 52 ]. The social media marketing efforts also play an important role in shaping the positive purchase intentions [ 144 ], brand meaning [ 58 ], brand loyalty [ 128 ], brand sustainability (X. [ 142 , 143 ], hotels [ 76 ], luxury brands [ 10 ], educational institutions [ 83 ], brand equity [ 63 ], positive electronic word of mouth [ 87 ], intention to engage online[ 127 ], etc.

Previous review studies on social media marketing and its effectiveness highlighted important aspects of its applications in marketing processes. Review studies have either used a specific database like web of science/Scopus [ 7 , 93 ] or studied a specific relationship such as brand–consumer interaction [ 101 ] in the context of social media marketing. Moreover, previous review studies focussed on specific applications such as evolving trends in Facebook marketing [ 94 ], a comprehensive comparative review of social media and social networks [ 144 ] and rise of social media in sports [ 78 ]. Moreover, previous studies reviewed the influence and effectiveness of social media for a specific sector/industry such as medical [ 90 ], tourism [ 78 ], hospitality and business-to-business applications as a digital mediation [ 68 ]. There is a lack of studies which has comprehensively mapped the marketing applications of social media and measured its effectiveness using bibliometric analysis. This study is an attempt to holistically examine the applications and effectiveness of social media as a marketing tool using state-of-the-art bibliometric analysis.

The development and probable future trends of a field of study can be analysed using various review techniques that can fulfil the specific objective of research. A systematic literature review (SLR) is conducted to identify, analyse, evaluate and summarize the overall findings of research in a field; it focusses on the methodological approach, theoretical framework, etc. [ 95 ]. Meta-analysis is an empirical statistical technique which combines the results of multiple studies on a given problem and then estimate the overall effect and direction of the relationship (Hassan) [ 14 , 48 , 86 , 104 , 106 ]. While bibliometric technique is a computer-assisted methodology that helps in measuring performance by identifying the core theme, sub-themes, prolific authors, most influential country, intellectual and social structure of the research [ 6 , 48 ]. For current study, bibliometric research design is adopted to fulfil the objectives of the study which helps in identifying the major trends in social media marketing using network analysis techniques [ 135 ]. It is one of the most used research methods which enables analysis of large volume of data to statistically estimate and visualize the research trends in a particular field of study [ 103 ]. This method is widely employed by other researchers in analysis and predicting the future expansion of research in a particular domain of research [ 12 ], Hassan, [ 49 , 62 , 104 , 106 ].

This review is conducted in two steps; first, the descriptive analysis such as the trend of research publication, best authors and top journals of the social media research is presented and then co-citation and co-occurrence analysis are presented. For descriptive analysis, Biblioshiny applications of R is used; it allows researchers to explore their data and run descriptive analysis and present them in an intuitive tabular and graphic form [ 5 ]. While for co-citation and co-occurrence analysis, VOSviewer software application is employed, it is a tool which produce output in network form—the networks are the combinations of various clusters that enables researchers to find the trending themes and sub-themes in a given area of research [ 126 ].

Scopus database is used for searching and downloading articles based on the applications of social media in marketing. The TITLE-ABS-KEY was searched using most appropriate keywords pertaining to the application of social media in marketing. The keywords such as “Social media marketing”, “Social networking sites”, “Social media platforms”, “Facebook marketing”, “Social network advertising”, “Social media purchasing”, and “digital marketing using social media” were searched using variety of combinations of Boolean operators (AND/OR) syntax. The inclusion of articles is based on certain criteria such as span of publication during (2007–2022), written in English language, must be either research article or reviews, and most importantly, the main theme of the literature must be on the application of social media as a marketing tool.

First search results in 2753 research articles, which are then carefully investigated for the defined inclusion criteria, book chapters, conference papers, short notes, editorial notes, etc., were removed. Literatures published in languages other than English were removed. Then, the researchers looked at tittle and abstract of each article to make sure that the central idea of research is based on the aspects of social media as a marketing tool. The final sample consists of 1232 articles, which then exported in .CSV format for further processing and analysis.

The following table is a snapshot of the data used in this bibliometric analysis.

This dataset consists of 1232 articles out of which 1183 are research articles and 83 reviews articles as presented in Table  1 . There are 58,528 references cited in these studies and the average citations per documents stands at 23.23. These papers were published by 562 sources and written by 2953 authors. It is worth noting that 2994 authors have published on social media marketing, while only 173 documents are single-authored, and all other documents are multi-authored. Documents per author is 0.411, while 2.43 authors are there per document; it shows strong collaborations among authors and collaboration index stands at 2.71.

The following section presents the descriptive analysis of data that is conducted using the Biblioshiny application. The .CVS file of the final data was uploaded on web service provided by Biblioshiny called bibliometrix application for further analysis.

Annual publications

The trends of publication over the years are depicted in Fig.  1 ; it is obvious that this area of research started in the mid of 2000s that signifies the importance of adoption of social media tools for marketing activities. Since then, there have been an exponential increase in the number of publications. From 2015 onwards, there were substantial research for understanding the effectiveness of social media as a marketing tool. As we see that there are already 65 articles published by November 2022—at the time of data extraction for this study. The trend shows that there will be continued research efforts to unveil the various aspects of social media marketing that can help marketers to understand consumer behaviour and make winning marketing strategies.

Annual publication trends in applications of social media in marketing

From thematic perspective, the trend can be further classified into themes which have been identified from the analysis. The early age (2000–2009) of social media marketing can be attributed to its application in advertising on social media platforms and network. This era also fuelled the development of customer groups and community where customers can interact and express their views about brands. Adoption of disruptive technologies defines trends from 2010 to 2017; during this period, smart recommendation systems, automatic feedback analysis and grievance redressal mechanisms introduced on social media. The human machine interaction signifies the trends from 2018 till date. The introduction of social robots, integration of augmented and virtual reality, real-time behavioural intelligence and super personalization can be treated as emerging themes.

Influential sources

Table  2 illustrates the most important journals publishing on the applications of social media in marketing. Top 20 journals based on total number of publications along with their total citations, and indices of h, g and m are presented.

The “Journal of Research in Interactive Marketing” is the most productive journal which has published 56 articles and been cited by 1841 times. This journal is the top-notch source in the production and dissemination of research based on interactive marketing. Few of the important themes of this journal over the years are social media influencers [ 131 ], personalization [ 97 ], adoption of disruptive technologies such as artificial intelligence and machine learning for web personalization [ 50 ] and customer experience [ 4 ], brand–consumer interaction using social media [ 131 ].

The second influential journal publishing on social media marketing is “Journal of Business Research”. This journal published 25 quality articles and been cited 2207 times. This is interesting to note that it has published articles less than half of the “Journal of Research in Interactive Marketing” but cited more often than that. This journal has contributed in the comprehension of the phenomenon of social media marketing by publishing on important aspects such as fake news and social media marketing [ 30 ], social media and brand equity [ 145 ], customer engagement via social media [ 40 ] and use of social media for B2B marketing [ 122 ].

Sustainability (Switzerland) is the third most important source that publishes on social media marketing. It has published 20 articles and attracted only 197 citations since its starting publications. This journal is publishing important aspects of social media-based marketing such as implementation of green marketing using social media [ 85 ], impact of social media on environmental sustainability [ 27 ], digital co-creation [ 22 ] and role of social media in organizational sustainability [ 138 ].

The other journals in the list have also contributed immensely to the growth of social media marketing research and its implications for the businesses.

Most prolific authors

The most prolific authors researching and publishing on social media marketing are presented in Table  3 ; this selection is based on the number of papers published by an author over the period, and their total citations and h-index are also presented for a better comprehension. The first author in the list is Kumar V; he has published six quality articles on the applications of social media tools in marketing. Some of the most influential articles published are “Engaging luxury brand consumers on social media”, “Synergistic effects of social media and traditional marketing on brand sales: capturing the time-varying effects”, “Creating a measurable social media marketing strategy: Increasing the value and ROI of intangibles and tangibles for Hokey Pokey”, “Increasing the ROI of social media marketing” and “An evolutionary road map to winning with social media marketing”. All the above-mentioned articles are focussing on specific marketing applications of social media. The second author in the list is Dwivedi YK with four papers and 718 citations and with an h-index of 4. The important articles published are “Examining the impact of social commerce dimensions on customers’ value cocreation: The mediating effect of social trust”, “Measuring social media influencer index- insights from Facebook, Twitter, and Instagram”, and “Social media marketing: Comparative effect of advertisement sources”. With four publications and 664 citations, Rana NP is the third most influential authors in the research domain of social media marketing. The most influential literature published by Rana NP is “Do Social Media Marketing Activities Improve Brand Loyalty? An Empirical Study on Luxury Fashion Brands”, “Social media marketing: Comparative effect of advertisement sources”, “social media in marketing: A review and analysis of the existing literature”. Rana NP has authored various articles in collaboration with Dwivedi YK as well.

Most important documents

Table 4 presents the top research papers published on the application of social media in marketing. These papers are listed based on their number of citations it has attracted over the years. The top document is written by Kozinets RV and focussed on the importance of the virtual online crowd, where consumers come together to discuss, share their opinion that results in collective innovation. Moreover, this paper emphasizes on the proliferation of networking technology that made online collaboration easy to access and interact; technologies help innovation to take new heights that ultimately impact the consumption patterns of the consumers. This paper has been cited 1077 times with an annual average of 83.

The second influential document found in this dataset is about social media marketing that was published in 2012 and cited 996 times by then. This paper has analysed the importance of social media in marketing from important aspects such as self-expression, socializing, brand interactions and the social communities that have substantial influence on the consumer purchasing intentions and purchasing behaviour. In addition, this paper also touches the importance of the impulsive buying activities on social media platforms; consumers are getting intimated with intuitive advertisements on social media platforms and landing to the e-commerce websites that instigate impulse shopping urges [ 13 ].

The paper published by Journal of Business Research and written by Kim AJ stands third in the list of most influential articles. This paper has investigated the role of social media in enhancing the customer equity with a special focus on luxury fashion brands. This paper was published in 2012 and attracted 904 citations by then. This paper explored the influence of social media marketing activities on customer perceived value, brand equity and customer equity. The findings favour the proposition that customer equity is highly enhanced by social media marketing activities.

The other documents in the list have also been contributed to the understanding and expansion of the area of social media marketing research. Few of the important themes discussed in these papers are measuring ROI of social media, creative social media marketing activities, online reviews, user-generated contents, influencer marketing, etc.

Most productive countries

The countries contributed most to the research stream of social media marketing are illustrated in Table  5 . The countries are selected based on the number of citations of their articles. The greatest number of research articles are contributed by USA; it has produced 222 research papers, and these papers have been cited 7065 times with an average article citation of 31.82. It indicates the adoption of social media as a marketing tool in the USA; the researchers are studying the underlying factors which are crucial to understand consumer behaviour in the space of social media marketing activities.

Moreover, it also indicates that countries having better networking facilities and high bandwidth internet can exploit the advantages of social media marketing more efficiently than the countries not at par in terms of internet and networking facilities. The other two important countries are UK and China with 3195 and 1674 citations, respectively. It can be noticed that there is huge disparity among top 3 countries in terms of publications and number of times it had been cited. Nevertheless, the trend is showing that the proliferation of internet technology and availability of high-quality internet will boost the adoption of social media among users and social media marketing among the business firms.

Citation analysis of the documents

Citation analysis is the method of assessing the quality and impact of an organization, author, source, etc., derived from the quantitative analysis of the citations to references [ 103 ]. VOSviewer application is employed for this purpose, and minimum number of citations of a document was kept 10. The network thus obtained contains four clusters based on the grouping of a specific theme in social media marketing (Fig. 2 ).

Citation analysis of documents

The largest cluster (red) of the network is made up of 134 documents and consists of large nodes which specifies the greater number of citations these documents received over the time. The important aspects of social media marketing in this cluster are mainly focussed on the information processing that can be further used to make strategies pertaining to the social media consumers [ 88 ]; analysis of the online conversation among users is of enormous importance because it is crucial in affecting the consumer behaviour either positively or negatively about the firm and its products [ 2 , 31 , 66 ]. B2B semantics is useful for understanding the deep inside thoughts of the firms and their leaders that ultimately shapes their behaviour [ 34 , 128 ]. In addition, the application of big data analytics tools is for processing and analysing the large amount of data to learn pattern of consumer interaction and activities on the social media network platforms [ 55 , 74 , 110 ]. Another important consideration in this cluster is about the use of sentiment analysis and opinion mining for managing the expectations of the consumers and offering them most customized products as per their unique needs.

The green cluster, second major in the network, is made of 93 documents. This cluster of this citation network is found to accumulate documents that addressed the research concerns of consumer behaviour from the perspective of social media marketing. The role of social media-based marketing in shaping the consumer intention to purchase [ 37 , 84 , 123 ], the impact of personalized content and its impact on consumer behaviour [ 19 , 140 ], consumer social media participation and its impact on overall profitability of the firm [ 26 , 29 ], persuasive advertisement and its impact on customer engagement [ 42 , 67 , 113 ].

Third cluster (blue) consists of 69 documents on various important aspects of the social media marketing from the perspective of customer engagement. The documents which have formed the basis of this cluster are essentially addressing the concepts of mutual sustainable relationship between customers and e-retailers are perceived value that a customer assessed about the product of services that meets their unique expectations [ 44 , 82 ]. The service quality on the shopping websites and applications is crucial to persuade customers to revisit and explore which ultimately increase the chances of customer engagement, while poor service quality demoralizes customers and decreases the level of engagement significantly [ 34 , 133 , 134 ]. In addition, customer experience that includes important factors such as personalization, tailoring of offers to match unique expectation of customers, are substantial in the course of customer engagement [ 116 , 123 ]. Customer engagement cannot be achieved if customer satisfaction is not central to a firm, and it must be the prime focus, and marketers needs to make all possible efforts to not only satisfy, but also delight their target customers [ 33 , 41 , 43 ].

Keyword co-occurrence analysis

The keyword co-occurrence analysis can be referred to as a method of analysing the similarities and proximity between knowledge structure that is based on the semantics of the words which are closely related but not exactly the same [ 13 ]. For this analysis, VOSviewer software is employed, and it is among the best tools for scientific data visualization and mapping of co-occurrence of similar keywords to discover the emerging trends in a specific area of research [ 12 ].

The criteria for a keyword to be included in the network was that a keyword must have a frequency of at least 15. The frequency of occurrence is set as 15, to make sure the inclusion of significant keywords that can help in visualizing the scientific landscape. The network thus obtained is based on 235 keywords out of 4061 and presented in Fig.  3 . This network is based on three specific clusters having combined keywords pertaining to a specific aspect of the social media marketing.

Keywords co-occurrence analysis

The largest cluster of the network is represented by red colour and consists of 110 keywords. This cluster is made up of keywords that signifies the importance of technology in social media marketing and social networks. This cluster also explains the importance and adoption of disruptive technologies in the application of social media in marketing activities. The role of artificial intelligence [ 57 , 73 , 130 ], machine learning [ 72 , 74 , 109 ], learning algorithms [ 9 , 31 , 121 ], sentiment analysis [ 109 ], learning systems [ 9 , 130 ], CRM tools [ 29 , 125 ], customer interactions [ 42 , 117 ], customer reviews [ 116 , 124 ] and recommender applications [ 98 , 112 ] has been studied over the period to implement them efficiently for better business outcome. Moreover, this cluster is having important implications for the designers, developers, and implementers of the social media marketing campaigns; it is crucial for the organizations to first collect the large amount of data resulting from the customer exploration of their web portals and process them to learn the trends and expectations of the consumers. This comprehension can further be used to design marketing efforts across the channels to reach to target markets, motivate them to interact over social media and engage into activities that can lead to profitable business transactions.

The second largest cluster (green) consists of 64 keywords; careful analysis of this cluster reveals that this cluster has combined the keyword which is centred around consumer behaviour on social media platforms. The important perspectives of consumer behaviour that can be visualized in this cluster are perceived value [ 79 , 129 ], purchase intentions [ 52 , 99 , 100 ], brand value [ 17 , 115 ], brand loyalty [ 10 , 133 ], brand image [ 107 , 114 ], ethics [ 28 , 91 ], green behaviour [ 10 , 130 ], sustainability aspects [ 99 , 130 ], millennials [ 10 , 34 , 35 ], generation [ 39 , 118 ], and customer engagement [ 99 , 107 , 140 ]. Therefore, it is quite evident that social media tools are being used in almost all facets of consumer behaviour; the above studies also concluded that the use of social media marketing tools has a positive and substantial impact on consumer behaviour.

The third and last cluster (blue) of this network is made of 51 items. This cluster has accumulated keywords which are focussed on the human aspects of social media marketing. As it is obvious from the network that the largest node in this cluster is “human” and “humans”, which specifies the interaction of machine, i.e. computers with human [ 36 , 58 , 139 ]. The human computer interface is a trending research stream in social media marketing, where efforts are made to understand the best practices to interact with computers in a more efficient manner [ 129 , 136 ]. The another important concept in this cluster is about psychology which is quite important for the marketers to understand the cognitive process of consumer when presented with marketing stimuli using social media marketing tools [ 59 , 117 ]. Few other keywords which dominated this cluster are health education and monitoring health using social media applications [ 28 ], young adults [ 81 , 130 ], selection of advertising topics [ 1 , 51 ], etc.

Trends in social media marketing

The network analysis helps in the identifications of emerging trends in the research of social media marketing. The social media networks allow users to interact and share their thoughts and experience with a brand which in turn helps in viral marketing [ 120 ]. The possibility of sharing podcast and video contents has fuelled the interactivity among users [ 15 ]. The reviews and feedback are of enormous importance for the marketers to listen the voice of the customers and adapt accordingly [ 54 ].

One of the major trends is about real-time personalization on the social networks; the recommender system is recommending most sought-after products to the customer in real-time web exploration. The personalization in real time is achieved using technologies such as artificial intelligence, machine learning and predictive analytics that helps in gaining deeper insights into behavioural intentions [ 3 , 96 ].

The introduction of augmented reality and virtual reality is another latest trend that have revolutionized the way marketing was being carried out using social media networks. The augmented reality has enabled the customers to virtually look at desired aspects such as suitability, colour combinations, fittings and virtual trials [ 39 ]. It gives consumers the confidence to immediately decide to purchase and quick gratifications [ 119 ]. The impulse purchasing mechanism is also trending on social media platforms; the firms are appropriately designing and putting across their offerings that creates urge to buy impulsively [ 61 ].

Influencer marketing and brand endorsement are not a new trend, but it is one of the major trends that is going to stay for a while. The brands are associating with influencers who have huge followers and witnessed better results as good as running paid advertisement campaigns [ 39 ].

Live streaming has been adopted by various firms to reach to specific segments of their target markets using webinar or a platform showcase [ 18 ]. It gives them opportunity to socialize and interact with prospective customers and engage with them through Q & A sessions or collaborative contents [ 18 ].

Themes and sub-themes in social media marketing

The detailed analysis of the networks of citations and keyword co-occurrence analysis helps in identifying themes and sub-themes which are emerged from the clusters of the network. Table 6 is representing the main themes and sub-themes along with related studies.

Each research study is having certain limitations and so as this one. One of the major limitations is about citation bases analysis; the selection of articles is based on the number of citations it has received. There might be important studies on social media that may have not been included in the analysis because it did not receive many citations. Moreover, we selected research literature written in English language and either article or review paper; there might be quality articles that left behind.

As far as future direction of research is concerned, it is obvious that social media marketing is evolving at ever high pace and there is a need for deeper investigation into this phenomenon. Careful investigation of the networks unveils important areas of future research expansion. First, the adoption of social media among consumers, what are the factors that hinders the usage of social media and technological barriers that restricts the customers to use social media are needed to be explored further. Studies have shown that one of biggest barrier in the adoption of social networks and platforms is the availability of high speed affordable internet networks [ 132 ]. Therefore, TAM model needed to be revisited from social media perspective, and additional components can be added to understand the adoption of technology and social media applications. A versatile model could be developed that can be used in variety of technology adoption scenarios and can be generalized in various environments. There is a need of study to understand the firm capabilities required and preparedness to adopt social media marketing practices.

The second important area of research is from the firm perspective; still it is not very much clear that how disruptive digital transformation and technologies such as artificial intelligence, Internet of Things, machine learning, deep learning, etc., can be implemented to get maximum ROI and that can persuade consumers to transact with them. Studies have focussed on artificial intelligence applications such as recommendation system which is positively influencing the consumer behaviour especially purchase intention [ 10 , 53 ]. The future studies can help in building a comprehensive model that could be used by the firm to evaluate their investment, ROI, perceived value to customer and overall consumer behaviour.

Thirdly, there is a lack of study on the influence of social media marketing on small retail firms. More studies are warranted to seek clarity about the effectiveness of social media as a marketing tool for smaller firm, which social media tool and tactics will be more advantageous for these firms. Researchers are also encouraged to empirically explore the small retailer’s perspective of adopting social media tools for their marketing activities. There shall be a mechanism to gauge the outcome of social media marketing on their brand awareness, customer growth, sales, and overall profitability of smaller retailers.

Fourth important area of research could be the deliberations of the social content. Content is the core of social media platforms; studies have shown that consumers tend to get attracted and spend more time on the social network where they can create their own content in an easy manner. Content is also crucial in terms of its suitability across platforms and ethical implications.

Therefore, researchers can study and analyse the most appropriate content across the social media platforms, devices and for a specific business. Researchers can explore the critical aspects of social content such as most suitable content for C2C interaction, firm reaction on a specific customer content, content to combat competitions, etc.

Fifth area of future research could be the monitoring of social media, how a firm shall record and acknowledge complaints of the customers. The sub-themes in monitoring can be to find out the best listening mechanisms of consumer activities that can be further analysed using predictive analysis mechanism to develop strategies to engage customers in the way they might be looking for. Another investigation can be done to seek clarity about the mechanism of watching and listening customers, i.e. whether there should be a fully automated process or hybrid one. This is important for the firms to understand the probable capital investment in the implementation of monitoring and responding process. This subject can be further investigated from the CRM perspective. Research can be extended to understand the role of various social media platforms on customer engagement, and what should be the capability of the CRM to exploit maximum from customer created content.

Conclusions

Bibliometric analysis is performed to have a comprehensive understanding of the applications of social media for marketing activities. The aim of the research was to investigate the research trends and emerging themes using the Scopus database. The findings of the research reveal the most important journals, authors, documents, and their intellectual structure. Moreover, it is found that research in the application of social media as a marketing tool is growing at an ever-increasing rate. Scholars around the world are collaborating with each other to comprehend the phenomenon and suggest strategies that can help firms to exploit the power of social media platforms in their marketing tactics. The outcomes of the research shown that there are certain areas of social media marketing landscape which need more scholarly attention; current literature has not considered these essential factors in detail. The findings suggest that current extant literature can be expanded by appending research in the areas such as modelling social media marketing ROI, social content strategies, monitoring and responding social media activities, social media strategies for smaller retailers, etc. This study has enumerated important implications along with the analysis for the businesses. The outcomes would also be helpful for social media enthusiasts and prospective social media marketing researchers.

Availability of data and materials

Not applicable.

Abbreviations

Customer-to-customer

Customer relationship management

Return on investment

Technology acceptance model

Abuljadail M, Ha L (2019) Engagement and brand loyalty through social capital in social media. Int J Internet Mark Advert 13(3):197–217. https://doi.org/10.1504/IJIMA.2019.102557

Article   Google Scholar  

Aghdam SM, Jafari Navimipour N (2016) Opinion leaders selection in the social networks based on trust relationships propagation. Karbala Int J Mod Sci 2(2):88–97. https://doi.org/10.1016/j.kijoms.2016.02.002

Aknine S, Slodzian A, G. Q. I. T. for W, et al (2003) Web personalisation for users protection: a multi-agent method. Springer

Aljukhadar M, Bériault Poirier A, Senecal S (2020) Imagery makes social media captivating! Aesthetic value in a consumer-as-value-maximizer framework. J Res Interact Mark 14(3):285–303. https://doi.org/10.1108/JRIM-10-2018-0136

Alshater MM, Hassan MK, Khan A, Saba I (2020) Influential and intellectual structure of Islamic finance: a bibliometric review. Int J Islam Middle East Financ Manag. https://doi.org/10.1108/IMEFM-08-2020-0419

Alshater MM, Saba I, Supriani I, Rabbani MR (2022) Fintech in islamic finance literature: a review. Heliyon, Cambridge

Google Scholar  

Alves H, Fernandes C, Raposo M (2016) Social media marketing: a literature review and implications. Psychol Mark 33(12):1029–1038. https://doi.org/10.1002/mar.20936

Ameur K, Benblidia N, Khouas SO (2016) Dimensions reordering for visual mining of association rules using parallel set. Int J Data Anal Tech Strat 8(4):296–315. https://doi.org/10.1504/IJDATS.2016.081362

Aswani R, Kar AK, Vigneswara Ilavarasan P (2018) Detection of Spammers in Twitter marketing: a hybrid approach using social media analytics and bio inspired computing. Inf Syst Front 20(3):515–530. https://doi.org/10.1007/s10796-017-9805-8

Bali S, Bélanger CH (2019) Exploring the use of Facebook as a marketing and branding tool by hospital foundations. Int J Nonprofit Volunt Sect Mark. https://doi.org/10.1002/nvsm.1641

Bashar A, Ahmad I, Wasiq M (2012) Effectiveness of social media as a marketing tool: an empirical study. Int J Mark Financ Serv Manag Res 2(11):88–99

Bashar A, Rabbani MR, Khan S, Ali MAMd (2021) Data driven finance: a bibliometric review and scientific mapping. 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021, pp 161–166. https://doi.org/10.1109/ICDABI53623.2021.9655898

Bashar A, Singh S (2022) Impulsive buying on social media platforms: a bibliometric review. J Contemp Issues Bus Govern 28(3):386–420

Bashar A, Jreisat A, Kaur J, Al-Mohamad S, Rabbani MR (2022) Looking into corporate boardrooms through the lens of gender diversity: a bibliometric review and META analysis. Planning 17(5):1593–1603

Bello-Orgaz G, Mesas RM, Zarco C, Rodriguez V, Cordón O, Camacho D (2020) Marketing analysis of wineries using social collective behavior from users’ temporal activity on Twitter. Inform Process Manag. https://doi.org/10.1016/j.ipm.2020.102220

Bello MJG (2019) Cloud-based conversational agents for user acquisition and engagement. In M VM, F D, H M, P C (eds) 9th International Conference on Cloud Computing and Services Science, CLOSER 2019. SciTePress, pp 528–534. https://doi.org/10.5220/0007766105280534

Beneke J, Blampied S, Miszczak S, Parker P (2014) Social networking the brand-an exploration of the drivers of brand image in the South African beer market. J Food Prod Mark 20(4):362–389. https://doi.org/10.1080/10454446.2013.807402

Bharadwaj N, Ballings M, Naik PA, Moore M, Arat MM (2022) A new livestream retail analytics framework to assess the sales impact of emotional displays. J Mark 86(1):27–47. https://doi.org/10.1177/00222429211013042

Bhardwaj P, Adhikari RS, Ahuja V (2018) An analytical study of the facebook content management strategies of dominos India. In: Digital marketing and consumer engagement: concepts, methodologies, tools, and applications, pp 1091–1105. IGI Global. https://doi.org/10.4018/978-1-5225-5187-4.ch055

Bilkova R, Zelenka Z (2015) Social network marketing: An examination of marketing behavior of small businesses. In S KS (ed) 26th International Business Information Management Association Conference - Innovation Management and Sustainable Economic Competitive Advantage: From Regional Development to Global Growth, IBIMA 2015. International Business Information Management Association, IBIMA, pp 2171–2180

Buckley S, Ettl M, Jain P, Luss R, Petrik M, Ravi RK, Venkatramani C (2014) Social media and customer behavior analytics for personalized customer engagements. IBM J Res Develop. https://doi.org/10.1147/JRD.2014.2344515

Calcagni F, Maia AA, James C-S et al (2019) Digital co-construction of relational values: understanding the role of social media for sustainability. Springer 14(5):1309–1321. https://doi.org/10.1007/s11625-019-00672-1

Chang H-L, Chou Y-C, Wu D-Y, Wu S-C (2018) Will firm’s marketing efforts on owned social media payoff? A quasi-experimental analysis of tourism products. Decis Support Syst 107:13–25. https://doi.org/10.1016/j.dss.2017.12.011

Chawla Y, Chodak G (2021) Social media marketing for businesses: organic promotions of web-links on Facebook. J Bus Res 135:49–65. https://doi.org/10.1016/j.jbusres.2021.06.020

Chellam A, Chaturvedi A, Ramanathan L (2020) Data visualization: visualization of social media marketing analysis data to generate effective business revenue model. In: Data visualization: trends and challenges toward multidisciplinary perception. Springer, Singapore, pp 75–92. https://doi.org/10.1007/978-981-15-2282-6_5

Cheung TY, Ye Z, Chiu DKW (2020) Value chain analysis of information services for visually impaired people: a case study of contemporary technological solutions. Library Hi Tech 39(2):625–642. https://doi.org/10.1108/LHT-08-2020-0185

Chuang HM, Liao YD (2021) Sustainability of the benefits of social media on socializing and learning: An empirical case of facebook. Sustainability (Switzerland). https://doi.org/10.3390/su13126731

Cox T, Park JH (2014) Facebook marketing in contemporary orthodontic practice: a consumer report. J World Federation Orthod 3(2):e43–e47. https://doi.org/10.1016/j.ejwf.2014.02.003

Doligalski T (2013) Social network marketing: customer value, CRM, and competitive actions. In: Marketing in the Cyber Era: strategies and emerging trends. IGI Global, pp 96–113. https://doi.org/10.4018/978-1-4666-4864-7.ch007

Domenico GD, Sit J, Ishizaka A, Nunan D (2021) Fake news, social media and marketing: a systematic review. J Bus Res 124:329–341. https://doi.org/10.1016/j.jbusres.2020.11.037

Domeniconi G, Semertzidis K, Moro G, Lopez V, Kotoulas S, Daly EM (2017) Identifying conversational message threads by integrating classification and data clustering. In: H M, F C (eds) 5th International Conference on Data Management Technologies and Applications, DATA 2016. Springer Verlag, vol 737, pp 25–46. https://doi.org/10.1007/978-3-319-62911-7_2

DSouza S, Rabbani MR, Hawaldar IT, Kumar AJ (2022) Impact of bank efficiency on the profitability of the Banks in India: an empirical analysis using panel data approach. Int J Financ Stud (Forthcoming)

Duffett RG (2015) Effect of Gen Y’s affective attitudes towards facebook marketing communications in South Africa. Electron J Inform Syst Develop Ctries 68:1–27. https://doi.org/10.1002/j.1681-4835.2015.tb00488.x

Ebrahimi P, Khajeheian D, Fekete-Farkas M (2021) A sem-nca approach towards social networks marketing: evaluating consumers’ sustainable purchase behavior with the moderating role of eco-friendly attitude. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph182413276

Article   PubMed   PubMed Central   Google Scholar  

Ebrahimi P, Salamzadeh A, Gholampour A, Fekete-Farkas M (2021) Social networks marketing and Hungarian online consumer purchase behavior: the microeconomics strategic view based on IPMA matrix. Acad Strateg Manag J 20(4):1–7

Fagerstrøm A, Ghinea G (2011) Co-creation of value through social network marketing: a field experiment using a facebook campaign to increase conversion rate. In Human Interface and the Management of Information: Interacting with Information - Symposium on Human Interface 2011, Held as Part of HCI International 2011: Vol. 6772 LNCS (Issue PART 2, pp 229–235). https://doi.org/10.1007/978-3-642-21669-5_27

Faiers A, Cook M, Neame C (2007) Towards a contemporary approach for understanding consumer behaviour in the context of domestic energy use. Energy Policy 35(8):4381–4390. https://doi.org/10.1016/j.enpol.2007.01.003

Fusté-Forné F, Filimon N (2021) Using social media to preserve consumers’ awareness on food identity in times of crisis: the case of bakeries. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph18126251

Ghouse SM, Duffett RG, Chaudhary M (2022) How Twitter advertising influences the purchase intentions and purchase attitudes of Indian millennial consumers? Int J Internet Mark Advert 16(1–2):142–164. https://doi.org/10.1504/IJIMA.2022.120973

Gligor D, Bozkurt S, Russo I (2019) Achieving customer engagement with social media: a qualitative comparative analysis approach. J Bus Res 101:59–69. https://doi.org/10.1016/j.jbusres.2019.04.006

Groothuis D, Spil TAM, Effing R (2020) Facebook marketing intelligence. In: B TX (ed) 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 (vols. 2020-Janua). IEEE Computer Society, pp 2559–2568

Gulay Ozturk R (2014) Friendvertising: a new advertising strategy in social network marketing. In: Digital arts and entertainment: concepts, methodologies, tools, and applications. IGI Global, vol 3, pp 1575–1600. https://doi.org/10.4018/978-1-4666-6114-1.ch078

Gulay Ozturk R (2015) FRIENDVERTISING: A new advertising strategy in social network marketing. In: Social Media and Networking: Concepts, Methodologies, Tools, and Applications (Vols. 4–4, pp 2051–2075). IGI Global. https://doi.org/10.4018/978-1-4666-8614-4.ch094

Han K-S (2016) Study of structural relationship between the value proposition of facebook brand fan pages and commitment and engagement. Indian J Sci Technol. https://doi.org/10.17485/ijst/2016/v9i41/103927

Hassan MK, Bashar A, Rabbani MR, Choudhury T (2022) An insight into the Fintech and Islamic Finance Literature: a bibliometric and visual analysis. In: FinTech in Islamic Financial Institutions: Scope, Challenges, and Implications in Islamic Finance. Springer International Publishing, Cham, pp 131–156

Hassan MK, Rabbani MR, Ali MA (2020) Challenges for the Islamic Finance and banking in post COVID era and the role of Fintech. J Econ Coop Develop 43(3):93–116

Hassan MK, Rabbani MR, Brodmann J, Bashar A, Grewal H (2022) Bibliometric and Scientometric analysis on CSR practices in the banking sector. Rev Financ Econ

Hassan MK, Raza Rabbani M (2022) Sharia governance standards and the role of AAOIFI: a comprehensive literature review and future research agenda. J Islamic Account Bus Res. https://doi.org/10.1108/JIABR-04-2022-0111

Hindley C, Smith MK (2017) Cross-cultural issues of consumer behaviour in hospitality and tourism. In: The Routledge Handbook of Consumer Behaviour in Hospitality and Tourism. Taylor and Francis, pp 86–96. https://doi.org/10.4324/9781315659657

Huang R, Ha S, Kim SH (2018) Narrative persuasion in social media: an empirical study of luxury brand advertising. J Res Interact Mark 12(3):274–292. https://doi.org/10.1108/JRIM-07-2017-0059/FULL/HTML

Iannelli L, Giglietto F, Rossi L, Zurovac E (2020) Facebook digital traces for survey research: assessing the efficiency and effectiveness of a facebook ad–based procedure for recruiting online survey respondents in niche and difficult-to-reach populations. Soc Sci Comput Rev 38(4):462–476. https://doi.org/10.1177/0894439318816638

Imtiaz R, Ul Ain Kazmi SQ, Amjad M, Aziz A (2019) The impact of social network marketing on consumer purchase intention in Pakistan: a study on female apparel. Manag Sci Lett. https://doi.org/10.5267/j.msl.2019.3.015

Ioanid A, Deselnicu DC, Militaru G (2017) Branding in the age of social media: How entrepreneurs use social networks to boost their service-based businesses. Balkan Region conference on engineering and business education 3(1):79–85. https://doi.org/10.1515/cplbu-2017-0011

Jaakonmäki R, Müller O, vom Brocke J (2017) The impact of content, context, and creator on user engagement in social media marketing. In: B TX, S R (eds) 50th Annual Hawaii International Conference on System Sciences, HICSS 2017. IEEE Computer Society, vols 2017-Janua, pp 1152–1160

Jami Pour M, Hosseinzadeh M, Amoozad Mahdiraji H (2021) Exploring and evaluating success factors of social media marketing strategy: a multi-dimensional-multi-criteria framework. Foresight 23(6):655–678. https://doi.org/10.1108/FS-01-2021-0005

Jiang L, Erdem M (2017) Twitter-marketing in multi-unit restaurants: Is it a viable marketing tool? J Foodserv Bus Res 20(5):568–578. https://doi.org/10.1080/15378020.2016.1222746

Jung YJ, Kim J (2016) Facebook marketing for fashion apparel brands: Effect of other consumers’ postings and type of brand comment on brand trust and purchase intention. J Glob Fash Market 7(3):196–210. https://doi.org/10.1080/20932685.2016.1162665

Jussila J, Madhala P (2019) Cognitive computing approaches for human activity recognition from tweets—A case study of twitter marketing campaign. In V A, L MD (eds) Research and Innovation Forum, Rii Forum 2019. Springer, pp 153–170. https://doi.org/10.1007/978-3-030-30809-4_15

Kachniewska M (2015) Gamification and social media as tools for tourism promotion. In: Handbook of research on effective advertising strategies in the Social Media Age. IGI Global, pp 17–51. https://doi.org/10.4018/978-1-4666-8125-5.ch002

Kao L-J, Huang Y-P (2014) Mining implict outlier purchasing behaviors from fan group marketing data. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014, pp 1048–1053. https://doi.org/10.1109/SCIS-ISIS.2014.7044662

Karim W, Abdul M, Chowdhury M, Al Masud A, Arifuzzaman M (2021) Analysis of Factors influencing Impulse Buying behavior towards e-tailing sites: An application of SOR model. Cmr-JournalOrg. https://doi.org/10.7903/cmr.20457

Kaur G, Singh M, Singh S (2021) Mapping the literature on financial well-being: A systematic literature review and bibliometric analysis. Int Soc Sci J 71(241–242):217–241. https://doi.org/10.1111/issj.12278

Kawaf F, Istanbulluoglu D (2019) Online fashion shopping paradox: the role of customer reviews and facebook marketing. J Retail Consum Serv 48:144–153. https://doi.org/10.1016/j.jretconser.2019.02.017

Khan S, Rabbani MR (2020) Chatbot as Islamic Finance Expert (CaIFE): when finance meets artificial intelligence. In: 2020 International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2020), Seoul, South Korea, pp 1–5

Khan S, Rabbani MR (2021) Artificial intelligence and NLP based chatbot as islamic banking and finance expert. Int J Inform Retr Res (IJIRR) 11(3):65–77

Kim YS, Tran VL (2013) Assessing the ripple effects of online opinion leaders with trust and distrust metrics. Expert Syst Appl 40(9):3500–3511. https://doi.org/10.1016/j.eswa.2012.12.058

Kovco A, Vranesic P, Aleksic-Maslac K (2018) Advantages of WCA facebook advertising with analysis and comparison of efficiency to classic facebook advertising. WSEAS Trans Bus Econ 15:73–79

Kumar B, Sharma A, Vatavwala S, Kumar P (2020) Digital mediation in business-to-business marketing: a bibliometric analysis. Ind Mark Manage 85:126–140. https://doi.org/10.1016/j.indmarman.2019.10.002

Leung XY, Bai B, Stahura KA (2015) The marketing effectiveness of social media in the hotel industry: a comparison of facebook and twitter. J Hosp Tourism Res 39(2):147–169. https://doi.org/10.1177/1096348012471381

Leung XY, Baloglu S (2015) Hotel facebook marketing: an integrated model. Worldwide Hosp Tour Themes 7(3):266–282. https://doi.org/10.1108/WHATT-03-2015-0011

Leung XY, Jiang L (2018) How do destination Facebook pages work? An extended TPB model of fans’ visit intention. J Hosp Tour Technol 9(3):397–416. https://doi.org/10.1108/JHTT-09-2017-0088

Li X, Guo Y, Sheng Y, Chen Y (2020) Characterizing social marketing behavior of e-commerce celebrities and predicting their value. In: 2020 IEEE INFOCOM conference on computer communications workshops, INFOCOM WKSHPS 2020, pp 1166–1171. https://doi.org/10.1109/INFOCOMWKSHPS50562.2020.9162757

Liao S-H, Hsian P-Y, Wu G-L (2014) Mining user knowledge for investigating the facebook business model: the case of Taiwan users. Appl Artif Intell 28(7):712–736. https://doi.org/10.1080/08839514.2014.927695

Liao S-H, Yang C-A (2021) Big data analytics of social network marketing and personalized recommendations. Soc Network Anal Min. https://doi.org/10.1007/s13278-021-00729-z

Liu Y, Wan H, Yang X (2010). Social network based marketing in mobile phone users’ community. In: 2010 international conference on machine vision and human-machine interface, MVHI 2010, pp 669–672. https://doi.org/10.1109/MVHI.2010.11

Lo YC, Fang C-Y (2018) Facebook marketing campaign benchmarking for a franchised hotel. Int J Contemp Hosp Manag 30(3):1705–1723. https://doi.org/10.1108/IJCHM-04-2017-0206

Lokshina I, Lanting CJM (n.d.) A qualitative evaluation of IoT-driven eHealth: knowledge management, business models and opportunities, deployment and evolution

López-Carril S, Escamilla-Fajardo P, González-Serrano MH, Ratten V, González-García RJ (2020) The rise of social media in sport: a bibliometric analysis. Int J Innov Technol Manag. https://doi.org/10.1142/S0219877020500418

Lupa-Wójcik I (2020) Emotions aroused by the most popular content on Facebook and their virality on the example of selected industries. In: K C, V C (eds) 7th European Conference on Social Media, ECSM 2020. Academic Conferences International, pp 154–162. https://doi.org/10.34190/ESM.20.022

Maziriri ET, Nyagadza B, Mapuranga M, Maramura TC (2022) Habitual Facebook use as a prognosticator for life satisfaction and psychological well-being: Social safeness as a moderator. Arab Gulf J Sci Res (AGJSR) 40(2):153–179. https://doi.org/10.1108/AGJSR-04-2022-0011

Mejova Y, Weber I, Fernandez-Luque L (2018) Online health monitoring using facebook advertisement audience estimates in the United States: evaluation study. JMIR Public Health Surveill. https://doi.org/10.2196/publichealth.7217

Moyer C, Griffin RJ, Pokrywczynski J (2018) Take me out to the facebook page. J Digit Soc Media Mark 6(4):357–370

Muangmee C (2021) Effects of Facebook advertising on sustainable brand loyalty and growth: case of Thai start-up businesses. Transnatl Corp Rev. https://doi.org/10.1080/19186444.2021.1986340

Mulero O, Adeyeye M, Ajibesin AA (2012) Determinants of user acceptance of online social networks marketing. International conference on communication, internet, and information technology, CIIT 2012:338–345. https://doi.org/10.2316/P.2012.773-013

Nabivi E (2020) Implementation of green marketing concept through social media activities: a systematic literature review. J Mark Consum Behav Emerg Mark 2/2020(11):55–67. https://doi.org/10.7172/2449-6634.jmcbem.2020.2.4

Naeem MA, Karim S, Rabbani MR, Bashar A, Kumar S (2022) Current state and future directions of green and sustainable finance: a bibliometric analysis. Qualit Res Financ Mark (ahead-of-p)

Nassar MA (2012) Harnessing the power of social networks for branding hotel services: evidence from the egyptian hotel sector. Innov Mark 8(2):58–66

Nastisin L, Fedorko R, Vavrecka V, Bacík R, Rigelský M (2019) Quantitative study of selected Facebook marketing communication engagement factors in the optics of different post types. Innov Mark 15(3):16–25. https://doi.org/10.21511/im.15(3).2019.02

Nobre H, Silva D (2014) Social network marketing strategy and SME strategy benefits. J Transnatl Manag 19(2):138–151. https://doi.org/10.1080/15475778.2014.904658

Nusair K, Butt I, Nikhashemi SR (2019) A bibliometric analysis of social media in hospitality and tourism research. Int J Contemp Hosp Manag 31(7):2691–2719. https://doi.org/10.1108/IJCHM-06-2018-0489

Nuseir MT, AlShawabkeh A, Leibfried EL (2021) Factors affecting the use of social networks as a customer relationship management tool. Int J Bus Inform Syst 38(2):179–199. https://doi.org/10.1504/IJBIS.2021.119182

Nyagadza B, Mazuruse G, Simango K, Chikazhe L, Tsokota T, Macheka L (2023) Examining the influence of social media eWOM on consumers’ purchase intentions of commercialised indigenous fruits (IFs) products in FMCGs retailers, Sustainable Technology & Entrepreneurship (STE). Elsevier España. https://doi.org/10.1016/j.stae.2023.100040

Nyagadza, B. (2022). Search engine marketing and social media marketing predictive trends, Journal of Digital & Media Policy (JDMP), Vol.13 [Issue 3] pp. 407–425, Intellect Publishers, Bristol, United Kingdom (UK), (DHET/SCOPUS). DOI: https://doi.org/10.1386/jdmp_00036_1

Othman N, Mohd Suki N, Mohd Suki N (2021) Evolution trends of facebook marketing in digital economics growth: a bibliometric analysis. Int J Interact Mobile Technol 15(20):68–82. https://doi.org/10.3991/ijim.v15i20.23741

Paul J, Lim WM, O’Cass A, Hao AW, Bresciani S (2021) Scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR). Int J Consum Stud. https://doi.org/10.1111/IJCS.12695

Pearson A (2019) Personalisation the artificial intelligence way. J Digit Soc Media Mark 7(3):245–269

Pelletier MJ, Krallman A, Adams FG, Hancock T (2020) One size doesn’t fit all: a uses and gratifications analysis of social media platforms. J Res Interact Mark 14(2):269–284. https://doi.org/10.1108/JRIM-10-2019-0159/FULL/HTML

Phelan KV, Chen H-T, Haney M (2013) “Like” and “Check-in”: How hotels utilize Facebook as an effective marketing tool. J Hosp Tour Technol 4(2):134–154. https://doi.org/10.1108/JHTT-Jul-2012-0020

Poolperm P, Thongmak M (2021) The influence of facebook marketing using gamification on consumers purchase intention. In: 27th Annual Americas Conference on Information Systems, AMCIS 2021

Prabowo H, Bramulya R, Yuniarty (2020) Student purchase intention in higher education sector: the role of social network marketing and student engagement. Manag Sci Lett 10(1):103–110. https://doi.org/10.5267/j.msl.2019.8.012

Qin YS (2020) Fostering brand–consumer interactions in social media: the role of social media uses and gratifications. J Res Interact Mark 14(3):337–354. https://doi.org/10.1108/JRIM-08-2019-0138/FULL/HTML

Rabbani MR (2020) The competitive structure and strategic positioning of commercial banks in Saudi Arabia. Int J Emerg Technol 11(3):43–46

Rabbani MR, Ali MAM, Rahiman H, Atif M, Zulfikar Z, Naseem Y (2021) The response of Islamic financial service to Covid-19 pandemic: the social open innovation of financial system. J Open Innov: Technol Market Complex

Rabbani MR, Bashar A, Hawaldar IT, Shaik M, Selim M (2022). What do we know about crowdfunding and P2P lending research? A bibliometric review and meta-analysis. J Risk Financ Manag. https://doi.org/10.3390/jrfm15100451

Rabbani MR et al (2021) Text mining and visual analytics in research: Exploring the innovative tools. International conference on decision aid sciences and application (DASA) 2021:1087–1091

Rabbani MR, Kayani U, Bawazir HS, Hawaldar IT (2022) A commentary on emerging markets banking sector spillovers: Covid-19 vs GFC pattern analysis. Heliyon 8(3):e09074

Article   CAS   PubMed   PubMed Central   Google Scholar  

Radpour R, Honarvar AR (2018) Impact of social networks on brand value based on customer behavior using structural equations. Int J Cust Relations Mark Manag 9(3):50–67. https://doi.org/10.4018/IJCRMM.2018070104

Raveendirarasa V, Amalraj CRJ (2020) Sentiment analysis of Tamil-English code-switched text on social media using sub-word level LSTM. In: 5th international conference on information technology research, ICITR 2020. https://doi.org/10.1109/ICITR51448.2020.9310817

Romero Moreno FY, Sanchez Martelo CA, Alfonso Corredor BY, Sanchez Cifuentes JF, Ospina López JP (2020) Sentiment analysis to the opinions generated in the social network twitter: political marketing. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao 2020(E35):187–203

Rozas L, Castronuovo L, Busse P, Mus S, Barnoya J, Garrón A, Tiscornia MV, Guanieri L (2021) Data on the Facebook marketing strategies used by fast-food chains in four Latin American countries during the COVID-19 lockdowns. BMC Res Notes. https://doi.org/10.1186/s13104-021-05870-8

Samala N, Katkam BS, Bellamkonda RS, Rodriguez RV (2020) Impact of AI and robotics in the tourism sector: a critical insight. J Tour Futures. https://doi.org/10.1108/JTF-07-2019-0065

Sevli O, Küçüksille EU (2017) Advertising recommendation system based on dynamic data analysis on Turkish speaking Twitter users. Tehnicki Vjesnik 24(2):571–578. https://doi.org/10.17559/TV-20151020205558

Shareef MA, Mukerji B, Alryalat MAA, Wright A, Dwivedi YK (2018) Advertisements on Facebook: Identifying the persuasive elements in the development of positive attitudes in consumers. J Retail Consum Serv 43:258–268. https://doi.org/10.1016/j.jretconser.2018.04.006

Sharma R, Alavi S, Ahuja V (2017) Generating trust using Facebook-A study of 5 online apparel brands. In: S Y, A V, D D, S Y, B D, T Y, T JM, A N (eds) 5th international conference on information technology and quantitative management, ITQM 2017. Elsevier B.V, vol 122, pp 42–49. https://doi.org/10.1016/j.procs.2017.11.339

Sharma R, Alavi S, Ahuja V (2019) Generation of trust using social networking sites: a comparative analysis of online apparel brands across social media platforms. Int J Manag Pract 12(4):405–425. https://doi.org/10.1504/IJMP.2019.102532

Sijabat DCS, Saputra FD, Ikhsan RB, Yuniarty (2020) The impact of social network marketing and customer engagement on purchase intentions in wedding service business. In: 5th International Conference on Information Management and Technology, ICIMTech 2020, pp 97–102. https://doi.org/10.1109/ICIMTech50083.2020.9211285

Smith D, Hernández-García A, Agudo Peregrina AF, Hair Jr JF (2016) Social network marketing: A segmentation approach to understanding purchase intention. In: G. J., J. J., R. E., M. P., & M. D. (Eds.), 7th International Conference on Social Media and Society, SMSociety 2016. Association for Computing Machinery. DOI: https://doi.org/10.1145/2930971.2930992

Spackman JS, Larsen R (2017) Evaluating the impact of social media marketing on online course registration. J Contin Higher Educ 65(3):151–165. https://doi.org/10.1080/07377363.2017.1368774

Sugawara E, Nikaido H (2014) Properties of AdeABC and AdeIJK efflux systems of Acinetobacter baumannii compared with those of the AcrAB-TolC system of Escherichia coli . Antimicrob Agents Chemother 58(12):7250–7257. https://doi.org/10.1128/AAC.03728-14

Tang S (2018) When social advertising meets viral marketing: sequencing social advertisements for influence maximization. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018, pp 176–183

Thingom C, Yeon G (2017) An integration of big data and cloud computing. In B V, S SC, J A (eds), 1st International Conference on Data Engineering and Communication Technology, ICDECT 2016. Springer Verlag, vol 469, pp 729–737. https://doi.org/10.1007/978-981-10-1678-3_70

Tiwary NK, Kumar RK, Sarraf S, Kumar P, Rana NP (2021) Impact assessment of social media usage in B2B marketing: a review of the literature and a way forward. J Bus Res 131:121–139. https://doi.org/10.1016/j.jbusres.2021.03.028

Toor A, Husnain M, Hussain T (2017) The impact of social network marketing on consumer purchase intention in Pakistan: Consumer engagement as a mediator. Asian J Bus Account 10(1):167–199

Tu Y, Zhao M, Jones C (2014). Insights into social media and online digital music. In: Digital Arts and Entertainment: Concepts, Methodologies, Tools, and Applications. IGI Global, vol 2, pp 684–710. https://doi.org/10.4018/978-1-4666-6114-1.ch032

Tussyadiah IP (2012) A concept of location-based social network marketing. J Travel Tour Mark 29(3):205–220. https://doi.org/10.1080/10548408.2012.666168

Van Eck NJ, Waltman L (2019) VOSviwer Manual version 1.6.10. In: CWTS Meaningful metrics

Varma M, Dhakane N, Pawar A (2020) Evaluation of impact of instagram on customer preferences: the significance of online marketing. Int J Sci Technol Res 9(2):548–554

Vasudevan S, Kumar FJP (2018) Social media and B2B brands: an Indian perspective. Int J Mech Eng Technol 9(9):767–775

Vasudevan S, Peter Kumar FJ (2018) Brand social engagement: learnings from Indian real estate websites. Int J Civil Eng Technol 9(7):1861–1870

Wajid A, Awan MJ, Ferooz F, Shoukat S, Anwar M, Mazhar M (2021) Facebook marketing analytics. In: 4th International conference on innovative computing, ICIC 2021. https://doi.org/10.1109/ICIC53490.2021.9693023

Wang CL (2021) New frontiers and future directions in interactive marketing: Inaugural Editorial. J Res Interact Mark 15(1):1–9. https://doi.org/10.1108/JRIM-03-2021-270/FULL/HTML

Wang G, Tan GW-H, Yuan Y, Ooi K-B, Dwivedi YK (2021) Revisiting TAM2 in behavioral targeting advertising: a deep learning-based dual-stage SEM-ANN analysis. Technol Forecast Soc Chang. https://doi.org/10.1016/j.techfore.2021.121345

Wang SS, Lin Y-C, Liang T-P (2018) Posts that attract millions of fans: the effect of brand-post congruence. Electron Commer Res Appl 28:73–85. https://doi.org/10.1016/j.elerap.2017.12.010

Wang Z, Zhao H, Zhang G, Zhang J (2017) An ACP-based approach for complex social network marketing system. Xitong Gongcheng Lilun yu Shijian/Syst Eng Theory Pract 37(11):2897–2907. https://doi.org/10.12011/1000-6788(2017)11-2897-11

Article   CAS   Google Scholar  

Wasiq M, Bashar A, Akmal S, Rabbani MR, Saifi MA, Nawaz N, Nasef YT (2023) Adoption and applications of blockchain technology in marketing: a retrospective overview and bibliometric analysis. Sustainability 15(4):3279

Wright LT, Gaber H, Robin R, Cai H (2018) Content strategies for facebook marketing: a case study of a leading fast-food brand page. In: Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer Nature, pp 779–791. https://doi.org/10.1007/978-3-319-66023-3_246

Wu Y, Stewart M, Liu R (2015) Social networking sites and marketing strategies. In Handbook of Research on Integrating Social Media into Strategic Marketing. IGI Global, pp 207–239. https://doi.org/10.4018/978-1-4666-8353-2.ch013

Yang S, Zeng X (2018) Sustainability of government social media: A multi-analytic approach to predict citizens’ mobile government microblog continuance. Sustainability (Switzerland). https://doi.org/10.3390/su10124849

Article   PubMed Central   Google Scholar  

Yarahmadi F, Yarahmadi F, Nader BS (2022) Investigating the impact of social network marketing on the bank customers’ profitability. In: Contributions to Management Science. Springer Science and Business Media Deutschland GmbH, pp 119–134. https://doi.org/10.1007/978-3-030-86028-8_7

Yoo K-H, Lee W (2017) Facebook marketing by hotel groups: Impacts of post content and media type on fan engagement. In: Advances in social media for travel, tourism and hospitality: new perspectives, practice and cases. Taylor and Francis, pp 131–146. https://doi.org/10.4324/9781315565736

Yoon Y, Deng R, Joo J (2022) The effect of marketing activities on Web Search Volume: an empirical analysis of Chinese Film Industry Data. Appl Sci (Switzerland). https://doi.org/10.3390/app12042143

Zhang B, Mildenberger M, Howe PD, Marlon J, Rosenthal SA, Leiserowitz A (2020) Quota sampling using Facebook advertisements. Polit Sci Res Methods 8(3):558–564. https://doi.org/10.1017/psrm.2018.49

Zhang X, Gong Y, Peng L (2020) The impact of interdependence on behavioral engagement in online communities. Mark Intell Plan 38(4):417–431. https://doi.org/10.1108/MIP-05-2019-0285

Zhao H, Huang Y, Wang Z (2020) Comparison between social media and social networks in marketing research: a bibliometric view. Nankai Bus Rev Int 12(1):122–151. https://doi.org/10.1108/NBRI-12-2019-0072

Zollo L, Filieri R, Rialti R, Yoon S (2020) Unpacking the relationship between social media marketing and brand equity: The mediating role of consumers’ benefits and experience. J Bus Res 117:256–267. https://doi.org/10.1016/j.jbusres.2020.05.001

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Bashar, A., Wasiq, M., Nyagadza, B. et al. Emerging trends in social media marketing: a retrospective review using data mining and bibliometric analysis. Futur Bus J 10 , 23 (2024). https://doi.org/10.1186/s43093-024-00308-6

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• Social media marketing
• Bibliometrics
• Biblioshiny
• Social media networks
• Social media platforms
• Marketing tools

ORIGINAL RESEARCH article

Role of social media marketing activities in influencing customer intentions: a perspective of a new emerging era.

• 1 School of Economics and Management, North China Electric Power University, Beijing, China
• 2 Department of Management Sciences and Engineering, Zhengzhou University, Zhengzhou, China
• 3 Faisalabad Business School, National Textile University, Faisalabad, Pakistan

The aim of this study is to explore social media marketing activities (SMMAs) and their impact on consumer intentions (continuance, participate, and purchase). This study also analyzes the mediating roles of social identification and satisfaction. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. We used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Data were collected from 353 respondents, and structural equation modeling (SEM) was used to analyze the data. Results show that SMMAs have a significant impact on the intentions of users. Furthermore, social identification mediates the relationship between social media activities and satisfaction, and satisfaction mediates the relationship between social media activities and the intentions of users. This will help marketers how to attract customers to develop their intentions. This is the first novel study that used SMMAs to address the user intentions with the role of social identification and satisfaction in the context of Pakistan.

Introduction

There has been tremendous growth in the use of social media platforms such as WhatsApp, Instagram, and Facebook over the past decade ( Chen and Qasim, 2021 ). People are using these platforms to communicate with one another, and popular brands use them to market their products. Social activities have been brought from the real world to the virtual world courtesy of social networking sites. Messages are sent in real time which now enable people to interact and share information. As a result, companies consider social media platforms as vital tools for succeeding in the online marketplace ( Ebrahim, 2020 ). The use of social media to commercially promote processes or events to attract potential consumers online is referred to as social media marketing (SMM). With the immense rise in community websites, a lot of organizations have started to find the best ways to utilize these sites in creating strong relationships and communications with users to enable friendly and close relationships to create online brand communities ( Ibrahim and Aljarah, 2018 ).

Social media marketing efficiently fosters communications between customers and marketers, besides enabling activities that enhance brand awareness ( Hafez, 2021 ). For that reason, SMM remains to be considered as a new marketing strategy, but how it impacts intentions is limited. But, to date, a lot of research on SMM is focused on consumer’s behavior, creative strategies, content analysis and the benefits of user-generated content, and their relevance to creating virtual brand communities ( Ibrahim, 2021 ).

New channels of communication have been created, and there have been tremendous changes in how people interact because of the internet developing various applications and tools over time ( Tarsakoo and Charoensukmongkol, 2020 ). Companies now appreciate that sharing brand information and consumer’s experience is a new avenue for brand marketing due to the widespread use of smartphones and the internet, with most people now relying on social media brands. Therefore, developing online communities has become very efficient. Social groups create a sense of continuity for their members without meeting physically ( Yadav and Rahman, 2017 ). A community that acquires products from a certain brand is referred to as a virtual brand community. Customers are not just interested in buying goods and services but also in creating worthwhile experiences and strong relationships with other customers and professionals. So, when customers are part of online communities, there is a cohesion that grows among the customers, which impacts the market. Therefore, it is up to the companies to identify methods or factors that will encourage customers to take part in these communities ( Ismail et al., 2018 ).

The online community’s nature is like that of actual communities when it comes to creating shared experiences, enabling social support, and attending to the members’ need to identify themselves, regardless of the similarities and variances existing between real-world communities and online communities ( Seo and Park, 2018 ). Regarding manifestations and technology, online communities are distinct from real-life communities since the former primarily use computers to facilitate their operation. A certain brand product or service is used to set up a brand community. Brand communities refer to certain communities founded based on interactions that are not limited by geographical restrictions between brand consumers ( Chen and Lin, 2019 ). Since consumers’ social relationships create brand communities, these communities have customs, traditions, rituals, and community awareness. The group members learn from each other and share knowledge about a product, hence appreciating each other’s actions and ideas. So, once a consumer joins a particular brand community, automatically, the brand becomes a conduit and common language linking the community members together because of sharing brand experiences ( Arora and Sanni, 2019 ).

Based on the perspective of brand owners, most research has focused on how social communities can benefit brands. However, there are also some discussions regarding the benefits that come from brand community members according to the members themselves to analyze how social community impacts its members ( Shareef et al., 2019 ). Consumer’s behavior is influenced by value so, when a consumer is constantly receiving value, it leads to consumer’s loyalty toward that brand. According to Alalwan et al. (2017) , a valuable service provider will create loyalty to a company and enhance brand awareness. Consumer value is essentially used in evaluating social networking sites. With better and easier options to create websites coming around, most consumers are attracted to a social community to know about a company and its goods. Furthermore, operators can learn consumer’s behavior through maintaining social interactions with customers. However, the social community should have great value. It should be beneficial to the potential customers by providing them with information relevant to the brand in question. Furthermore, customers should be able to interact with one another, thus creating a sense of belonging. From that, it is evident that a brand social community’s satisfaction affects community retention and selection.

Literature Review

Social media marketing activities.

Most businesses use online marketing strategies such as blogger endorsements, advertising on social media sites, and managing content generated by users to build brand awareness among consumers ( Wang and Kim, 2017 ). Social media is made up of internet-associated applications anchored on technological and ideological Web 2.0 principles, which enables the production and sharing of the content generated by users. Due to its interactive characteristics that enable knowledge sharing, collaborative, and participatory activities available to a larger community than in media formats such as radio, TV, and print, social media is considered the most vital communication channel for spreading brand information. Social media comprises blogs, internet forums, consumer’s review sites, social networking websites (Twitter, Blogger, LinkedIn, and Facebook), and Wikis ( Arrigo, 2018 ).

Social media facilitates content sharing, collaborations, and interactions. These social media platforms and applications exist in various forms such as social bookmarking, rating, video, pictures, podcasts, wikis, microblogging, social blogs, and weblogs. Social networkers, governmental organizations, and business firms are using social media to communicate, with its use increasing tremendously ( Cheung et al., 2021 ). Governmental organizations and business firms use social media for marketing and advertising. Integrated marketing activities can be performed with less cost and effort due to the seamless interactions and communication among consumer partners, events, media, digital services, and retailers via social media ( Tafesse and Wien, 2018 ).

According to Liu et al. (2021) , marketing campaigns for luxury brands consist of main factors such as customization, reputation, trendiness, interaction, and entertainment which significantly impact customers’ purchase intentions and brand equity. Activities that involve community marketing accrue from interactions between events and the mental states of individuals, whereas products are external factors for users ( Parsons and Lepkowska-White, 2018 ). But even though regardless of people experience similar service activities, there is a likelihood of having different ideas and feelings about an event; hence, outcomes for users and consumers are distinct. In future marketing, competition will focus more on brand marketing activities; hence, the marketing activities ought to offer sensory stimulation and themes that give customers a great experience. Now brands must provide quality features but also focus on enabling an impressive customer’s experience ( Beig and Khan, 2018 ).

Social Identification

A lot of studies about brand communities involve social identification, appreciating the fact that a member of a grand community is part and parcel of that community. Social identity demystifies how a person enhances self-affirmation and self-esteem using comparison, identity, and categorization ( Chen and Lin, 2019 ). There is no clear definition of the brand community or the brand owner, strengthening interactions between the community and its members or creating a rapport between the brand and community members. As a result, members of a community are separated into groups based on their educational attainment, occupation, and living environment. Members of social networks categorize each other into various groups or similar groups according to their classification in social networks ( Salem and Salem, 2021 ).

Brand identification and identification of brand communities emanate from a similar process. Users can interact freely, hence creating similar ideologies about the community, alongside strengthening bonds among members, hence enabling them to identify with that community. The brand community identity can also be considered as a convergence of values between the principles of the social community and the values of the users ( Wibowo et al., 2021 ).

According to Lee et al. (2021) , members of a brand social community share their ideas by taking part in community activities to help create solutions. When customers join a brand community, they happily take part in activities or discussions and are ready to help each other. So, it is evident that social community participation is impacting community identity positively. Community involvement entails a person sharing professional understanding or knowledge with other members to enhance personal growth and create a sense of belonging ( Gupta and Syed, 2021 ). According to Haobin Ye et al. (2021) , it is high time community identity be incorporated in virtual communities since it is a crucial factor that affects the operations of virtual communities. Also, community identity assists in facilitating positive interactions among members of the community, encouraging them to actively take part in community activities ( Assimakopoulos et al., 2017 ). This literature review suggests that social communities need members to work together. Individuals who can identify organizational visions and goals become dedicated to that virtual company.

Satisfaction

Customer’s satisfaction involves comparing expected and after-service satisfaction with the standards emanating from accumulated previous experiences. According to implementation confirmation theory, satisfaction is a consumer’s expected satisfaction with how the services have lived up to those expectations. Customers usually determine the level of satisfaction by comparing the satisfaction previously experienced and the current one ( Pang, 2021 ).

According to recent studies, community satisfaction impacts consumer’s loyalty and community participation. A study community’s level of satisfaction is determined by how its members rate it ( Jarman et al., 2021 ). Based on previous interactions, the community may be evaluated. When the members are satisfied with their communities, it is manifested through joyful emotions, which affect the behavior of community members. In short, satisfaction creates active participation and community loyalty ( Shujaat et al., 2021 ).

Types of Intentions

A lot of studies about information and marketing systems have used continuance intention in measuring if a customer continues to use a certain product or service. The willingness of customers to continue using a good or service determines if service providers will be successful or not. According to Zollo et al. (2020) , an efficient information marketing system should persuade users to use it, besides retaining previous users to guarantee continued use.

Operators of social networks must identify the reason propelling continued use of social network sites, alongside attracting more users. Nevertheless, previous studies on information systems in the last two decades have mainly concentrated on behavior–cognition approaches, for instance, the technology acceptance model (TAM), theory of planned behavior (TPB), and theory of reasoned action (TRA) with their variants ( Tarsakoo and Charoensukmongkol, 2020 ; Jamil et al., 2021b ). According to Ismail et al. (2018) , perceived use and satisfaction positively impact a user’s continuance intention. The continued community members’ participation has two intentions. Continuance intention is the first one. It defines the community member’s intent to keep on using the community ( Beig and Khan, 2018 ; Dunnan et al., 2020 ). Then, recommendation intention, also known as mouth marketing, describes every informal communication that takes place among community members regarding the virtual brand community. Previous studies about members of a virtual community mostly entailed the continuous utilization of information systems ( Seo and Park, 2018 ; Sarfraz et al., 2021 ). Unlike previous studies, this study focuses on factors that support the continued participation of community members. So, besides determining how usage purpose affects continuance intention, the study also investigated the factors that influence users’ willingness to take part in community activities ( Gul et al., 2021 ).

Nevertheless, it is hard to determine and monitor whether a certain action occurred (recommendation or purchase) during empirical investigations. Consumers will seek relevant information associated with their external environment and experiences when purchasing goods ( Shareef et al., 2019 ). Once they have collected significant information, they will evaluate it, and draw comparisons from which customer’s behavior is determined. Since purchase intention refers to a customer’s affinity toward a particular product, it is a metric of a customer’s behavioral intention. According to Liu et al. (2021) , the probability of a customer buying a particular product is known as an intention to buy. So, when the probability is high, it simply means that the willingness to purchase is high. Past studies consider purchase intention as a factor that can predict consumer’s behavior alongside the subjective possibility of consumer’s purchases. According to Chen and Qasim (2021) , from a marketing viewpoint, if a company wants to retain its community besides achieving community targets while establishing successful marketing via the community, at least three objectives are needed. They include membership continuance intention, which entails members living up to their promises in the community and also the willingness to belong to the community ( Yadav and Rahman, 2018 ; Naseem et al., 2020 ). On the other side, community recommendation intention entails the willingness of members to recommend or refer community members to other people who are not members ( Jamil et al., 2021a ; Mohsin et al., 2021 ). The next consideration is the community participation intention of a member, which involves their willingness to participate in the activities of the brand community. Unlike past literature about using information systems, this study demystified how SMMAs influence purchase intention and participation intention ( Alalwan et al., 2017 ).

Development of Hypotheses

People with similar interests can get a virtual platform to discuss and share ideas courtesy of social media. Sustained communication of social media allows users to create a community. Long-lasting sharing of growth and information fosters the development of strong social relationships. The information posted on social media platforms by an individual positively correlates with the followers the user has. Regarding the discussion above, we proposed the following hypothesis:

H1: Social media marketing activities (SMMAs) have a significant impact on social identification.

The study of Farivar and Richardson (2021) on users’ continuance intention confirmed that it is influenced by satisfaction after service. Social media studies are also of the thought that satisfaction significantly affects continuance intention. So, a consumer will measure the satisfaction of service after using it. Mahendra (2021) claims that satisfaction influences repurchase behavior. Repurchase intention emanates from a customer’s satisfaction with a good or service. People who have similar interests may interact and cooperate in a virtual world via social media platforms. A community on social media may be formed by regularly connecting with people and exchanging information with them. Members benefit from long-term information and growth exchanges that enable them to create strong social relationships. A lot of studies have pointed out that repurchase intention and customer’s satisfaction are positively and highly related. Besides, marketing studies noted that satisfactory experience after using a product would impact the intention of future repurchase. Hence, we proposed the following hypothesis:

H2: SMMAs have a significant impact on satisfaction.

The study by Suman et al. (2021) on American consumer’s behavior suggested that members taking part in community activities (meetups, discussion, and browsing) influence their brand-associated behavior. According to Di Minin et al. (2021) , the brand identity of a consumer has a positive impact on satisfaction. Consumers capitalize on online communities to share their experiences and thoughts about a grand regularly and easily ( Sirola et al., 2021 ). These experiences make up the customer to brand experiences and establish a sense of belonging, trust, and group identity. In a nutshell, this study suggests that identity will enable members to recognize their community, hence confirming that members have similar experiences and feelings with a particular brand and feel united in the group ( Shujaat et al., 2021 ). Strong group identity means that members are integrated closely into the brand communities and highly regard the community. Hence, we proposed the following hypothesis:

H3: Social identification has a significant impact on satisfaction.

Brand communities are beneficial in the sense that they enable sharing of marketing information, managing a community, and exploring demands ( Dutot, 2020 ). These activities are likely to enhance consumer’s rights and increase customer’s satisfaction ( Sahibzada et al., 2020 ). A customer who makes an online transaction will be highly satisfied with a website that provides a great experience ( Koçak et al., 2021 ). Enhancing customer’s satisfaction, encouraging customer intentions, creating community loyalty, and fostering communication and interactions between community users are crucial to lasting community platform management ( Pang, 2021 ). Hence, we proposed the following hypotheses:

H4: Satisfaction has a significant impact on continuance intention.

H5: Satisfaction has a significant impact on participate intention.

H6: Satisfaction has a significant impact on purchase intention.

Thaler (1985) proposed transaction utility theory, in which consumers’ willingness to spend money is influenced by their perceptions of value. Researchers such as Dodds (1991) claimed that buyers only become ready to purchase after they have established a sense of value for a product. According to Petrick et al. (2001) , a product’s quality is dependent on the customer’s satisfaction. Several studies have shown that enjoyment, perceived value, and behavioral intention are all linked together. Hence, we proposed the following hypothesis:

H7: Social identification mediates the relationship between SMMA and satisfaction.

When it comes to information systems, Bhattacherjee et al. (2008) discovered that people’s continual intention is derived from their satisfaction with the system after they have used it. Studies on employee’s satisfaction in the workplace have shown that it has a substantial influence on CI. The amount of satisfaction that users have with the system that they have previously used is the most important factor in determining their CI, according to research on information system utilization intention.

In other words, the customer’s contentment with the product leads to the establishment of a desire to buy the thing again, as mentioned by Assimakopoulos et al. (2017) . Numerous studies show a strong link between customer’s satisfaction and their propensity to return for another transaction. According to a lot of marketing studies, customers who have a pleasant experience with a product are more likely to repurchase it. Hence, we proposed the following hypotheses:

H8: Satisfaction mediates the relationship between social identification and continuance intention.

H9: Satisfaction mediates the relationship between social identification and participate intention.

H10: Satisfaction mediates the relationship between social identification and purchase intention.

Figure 1 shows the research framework of this study.

Figure 1. Conceptual framework.

Conceptual Framework

Research methodology.

This study designed a questionnaire according to the hypotheses stated above. The participants in this study were experienced users of two social media platforms Facebook and Instagram in Pakistan. A self-administered questionnaire was used to collect data from respondents. A pilot study with 40 participants was carried out. Since providing recommendations, revisions were made to the final questionnaire to make it more understandable for the study’s respondents. To ensure the content validity of the measures, three academic experts of marketing analyzed and make improvements in the items of constructs. The experts searched for spelling errors and grammatical errors and ensured that the items were correct. The experts have proposed minor text revisions to social identification and satisfaction items and advised that the original number of items is to be maintained. This study used an online community to invite Facebook and Instagram users to complete the questionnaire in the designated online questionnaire system. Online questionnaires have the following advantages ( Tan and Teo, 2000 ): (1) sampling is not restricted to a single geological location, (2) lower cost, and (3) faster questionnaire responses. A total of 353 questionnaires were returned from respondents. There were 353 appropriate replies considered for the final analysis.

The study used items established from prior research to confirm the reliability and validity of the measures. All items are evaluated through 5-point Likert-type scales where “1” (strongly disagree), “3” (neutral), and “5” (strongly agree).

Dependent Variable

To get a response about three dimensions of intention (continuance, participate, and purchase), we used eight items adopted from prior studies;

1. Continuance intention is measured by three items from the study of Bhattacherjee et al. (2008) , and the sample item is, “I intend to continue buying social media rather than discontinue its use.”

2. Participate intention is evaluated by three items from the work of Debatin et al. (2009) , and the sample item is, “my intentions are to continue participating in the social media activities.”

3. Purchase intention was determined by two items adapted from the work of Pavlou et al. (2007) , and the sample item is, “I intend to buy using social media in the near future.”

Independent Variable

To analyze the five dimensions of SMMAs, we used eleven items adopted from a prior study of Kim and Ko (2012) .

1. Entertainment is determined by two items and the sample item is, “using social media for shopping is fun.”

2. Interaction is evaluated by three items, and the sample item is, “conversation or opinion exchange with others is possible through brand pages on social media.”

3. Trendiness is measured by two items, and the sample item is, “contents shown in social media is the newest information.”

4. Customization is measured by two items, and the sample item is, “brand’s pages on social media offers customized information search.”

5. Word of mouth is measured by two items, and the sample item is, “I would like to pass along information on the brand, product, or services from social media to my friends.”

Mediating Variables

We used two mediating variables in this study,

1. Social identification was measured with five items adopted from the prior study of Bhattacharya and Sen (2003) , and the sample item is, “I see myself as a part of the social media community.”

2. Satisfaction was evaluated with six items adopted from the study of Chen et al. (2015) , and the sample item is, “overall, I am happy to purchase my desired product from social media.”

This research employs a partial least square (PLS) modeling technique, instead of other covariance-based approaches such as LISREL and AMOS. The reason behind why we pick PLS-SEM is that it is most suitable for confirmatory and also exploratory research ( Hair Joe et al., 2016 ). Structural equation modeling (SEM) has two approaches, namely covariance-based and PLS-SEM ( Hair et al., 2014 ). PLS is primarily used to validate hypotheses, whereas SEM is most advantageous in hypothesis expansion ( Podsakoff et al., 2012 ). A PLS-SEM-based methodology would be done in two phases, first weighing and then measurement ( Sarstedt et al., 2014 ). PLS-SEM is ideal for a multiple-order, multivariable model. To do small data analysis is equally useful in PLS-SEM ( Hair et al., 2014 ). PLS-SEM allows it easy to calculate all parameter calculations ( Hair Joe et al., 2016 ). The present analysis was conducted using SmartPLS 3.9.

Model Measurement

Table 1 shows this study model based on 31 items of the seven variables. The reliability of this study model is measured with Cronbach’s alpha ( Hair Joe et al., 2016 ). As shown in Table 1 , all items’ reliability is robust, Cronbach’s alpha (α) is greater than 0.7. Moreover, composite reliability (CR) fluctuates from.80 to.854, which surpassed the prescribed limit of 0.70, affirming that all loadings used for this research have shown up to satisfactory indicator reliability. Ultimately, all item’s loadings are over the 0.6 cutoff, which meets the threshold ( Henseler et al., 2015 ).

Table 1. Inner model evaluation.

The Cronbach’s alpha value for all constructs must be greater than 0.70 is acceptable ( Hair et al., 2014 ). All the values of α are greater than 0.7 as shown in Table 1 and Figure 2 .

Figure 2. Measurement model.

Convergent validity is measured by CR and AVE, and scale reliability for each item ( Hair Joe et al., 2016 ). The scholar says that CR and AVE should be greater than 0.7 and 0.5, respectively. By utilizing CR and average variance extracted scores, convergent validity was estimated ( Fornell and Larcker, 1981 ). As elaborated in Table 3 , the average variance extracted scores of all the indicators are greater than 0.50 and CR is higher than.70 which is elaborating an acceptable threshold of convergent validity and internal consistency. It is stated that a value of CR, that is, not less than 0.70, is acceptable and evaluated as a good indicator of internal consistency ( Sarstedt et al., 2014 ). Moreover, average variance extracted scores of more than 0.50 demonstrate an acceptable convergent validity, as this implies that a specific construct with greater than 50% variations is clarified by the required indicators.

Table 2. A mediation analysis.

Table 3. Discriminant validity.

This study determines the discriminant validity through two techniques named Fornell–Larcker criterion and heterotrait–monotrait (HTMT) ( Hair Joe et al., 2016 ). In line with Fornell and Larcker (1981) , the upper right-side diagonal values should be greater than the correlation with other variables, which is the square root of AVE, which indicates the discriminant validity of the model. Table 3 states that discriminant validity was developed top value of variable correlation with itself is highest. The HTMT ratios must be less than 0.85, although values in the range of 0.90 to 0.95 are appropriate ( Hair Joe et al., 2016 ). Table 3 displays that all HTMT ratios are less than 0.90, which reinforces the statement that discriminant validity was supported in this study’s classification.

To determine the problem of multicollinearity in the model, VIF was calculated for this purpose. The experts said that if the value of VIF is greater than 5, there is no collinearity issue in findings ( Hair et al., 2014 ). The results indicate that the inner value of VIF for all indicators must fall in the range of 1.421 to 1.893. Furthermore, these study findings show no issue of collinearity with data, and the study has stable results.

To evaluate “the explanatory power of the model,” the R 2 value was analyzed for every predicted variable. It shows the degree to which independent variables illustrate the dependent variables. R 2 value in “between 0 and 1 with higher values shows a higher level of predictive accuracy. Subsequent values of R 2 describe 0.25 for weak, 0.50 for moderate, and 0.75 for” substantial. An appropriate model is indicated by R 2 greater than 0.5 in primary results. In Figure 2 , the value of R 2 greater than 0.5 on all exogenous constructs, which also means that the model has strong predictive accuracy ( Hair Joe et al., 2016 ).

Table 4 displays the percentage of variance clarified for every variable: 62.7% of continuous intention, 55.5% of participate intention, 54.5% for purchase intention, 80.9% for satisfaction, and 81.8% for social identification. In general, results demonstrate that values of R 2 of endogenous variables are greater than 80%, which is the sign of a substantial “parsimonious model” ( Sarstedt et al., 2014 ). Most importantly, the outputs give a significant validation of the model. Q 2 values of all four 5 latent variables suggest that the model is extremely predictive ( Hair et al., 2014 ).

Table 4. Predictive accuracy and relevance of the model.

Hypothesis Testing

This study evaluates the significance of relationships using bootstrapping at 5,000 with a replacement sample ( Hair Joe et al., 2016 ; Awan et al., 2021 ). The findings show that SMMAs have significant relationship with social identification (β = 0.905, t -value = 36.570, p = 0.000) which accept the H1. The findings show that SMM significantly influences the satisfaction (β = 0.634, t -value = 8.477, p = 0.000). Social identification has significant positive relationship with satisfaction as shown in Table 5 (β = 0.284, t -value = 4.348, p = 0.000) which accept the H3. The results show that satisfaction has significant relationship with continuous intention (β = 0.792, t -value = 15.513, p = 0.000) which support the H4. The findings show that satisfaction has strong positive relationship with participant intention (β = 0.745, t -value = 12.041, p = 0.000), which support the H5. The findings show that satisfaction has strong positive relationship with purchase intention (β = 0.739, t -value = 12.397, p = 0.000) which support the H6. The findings of the current investigation support H1, H2, H3, H4, H5, and H6. The results show that H4, H1a, H1b, H3a, H3b, H2a, and H2b are accepted (refer to Table 5 and Figure 3 ).

Table 5. Hypothesis testing.

Figure 3. Structural model.

Preacher and Hayes (2008) argue that if the VIF value is greater than 80%, then it shows full mediation, and value of VIF equal to 20 to 80% which indicate the partial mediation and if VIF falls below 20%, then there is no mediation. The findings show that social identification mediates the relationship between SMM and satisfaction (β = 0.213, t -value = 3.570, p -value = 0.000) and indirect effect (β = 0.257, t -value = 4.481, p -value = 0.000) with variance accounted for (VAF) 75% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes and Preacher, 2010 ). The findings show that satisfaction mediates the relationship between social identification and continuous intention (β = 0.342, t -value = 3.435, p -value = 0.000) and indirect effect (β = 0.225, t -value = 4.636, p -value = 0.000) with VAF 64% which show partial mediation. In this, the VAF describes the size of the indirect effect in relation to the total effect ( Hayes, 2009 ). The findings show that satisfaction mediates the relationship between social identification and participant intention (β = 0.324, t -value = 5.325, p -value = 0.000) and indirect effect (β = 0.211, t -value = 4.338, p -value = 0.000) with VAF 73% which show partial mediation. The findings show that satisfaction mediates the relationship between social identification and purchase intention (β = 0.312, t -value = 3.434, p -value = 0.000) and indirect effect (β = 0.3.213, t -value = 5.437, p -value = 0.000) with VAF 78% which show partial mediation (refer to Table 2 ).

Discussion and Conclusion

The study was about SMMAs as proposed by Kim and Ko (2012) , and it investigated which factors influence social media usage. The findings of the study include the following:

Most studies about social websites have not exhausted the impact of SMMAs. According to this study, SMMAs significantly affect social identification, which ultimately influences purchase decisions, participation decisions, continuance intention, and satisfaction. The study demystified social media usage intention. The findings were that SMMAs could sustain corporate brands. According to Beig and Khan (2018) , unlike blog marketing and keyword advertising that were associated with content, SMM gets to the targeted audiences to enhance the impact of the information being shared by creating strong relationships in the online community. Therefore, service providers of social media must put into consideration means of increasing the impact of SMMAs. To boost SMMAs, operators should increase activity on the forum. The members of a community can be allowed to explain the guiding factors behind choosing a particular brand over that of competitors for other members to know the competing brands. From the discussions and sharing of knowledge, members get an opportunity to understand why they like a particular brand, thus enhancing brand loyalty and community cohesion ( Yadav and Rahman, 2017 ).

The study also confirmed that most administrators are concerned with the influence of brand community management in creating business advantage. According to Tarsakoo and Charoensukmongkol (2020) , marketing strategies and tools have undergone tremendous changes since the inception of social media. Consumers no longer must rely on traditional media to acquire information about a product before making their purchase since social media can effectively and easily avail such information. For that reason, social media service providers must come up with effective measures of controlling publication timing, frequency, and content to achieve the set marketing targets. According to this study, if a company can successfully assist users to easily identify with a particular brand community, strong relationships will be fostered between the consumers and the brand, hence creating customer’s loyalty ( Ebrahim, 2020 ). Besides, users may stop using competitors’ products. So, companies need to appreciate that proper management of online strategies and brand community in creating community identity enhances brand’s competitiveness and inspires members of the brand community to shun using goods and services from competitors.

Limitations and Recommendations

Regardless of the efforts geared toward enabling in-depth data collection, research methodology, and research structure, there were still various limitations that ought to be dealt with in studies to be conducted in the future. For instance, using online questionnaires in data collection, some members might have been very willing to fill them because of their community identity, hence enabling self-selection bias that may impact the validity and authenticity of the outcomes. Besides, a cross-sectional sample was used in the study; hence, results from the analysis can only demystify individual usage patterns on well-known social media. Nevertheless, the different social media platforms provide different services; hence, long-term usage needs long-term observation. The outcomes of growth model analysis with the experimental values and browsing experiences of users at the various phases in longitudinal studies to be conducted in the future may be increasingly conclusive on casual relationships with variables. The third limitation of the study is that different countries or areas have different preferences regarding social media. Future studies should unravel the reasons behind individuals from various cultural backgrounds or countries using different social media platforms and what might be the demands and motivations behind their preferences. Besides, new social networking sites such as Facebook and Twitter have unique characteristics which are different from traditional sites. Future studies should also focus on this shift. For this study, the emphasis was on SMMAs’ influence on user’s behavior and usage demands.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

This study was partly supported by the National Social Science Foundation of China (no. 19ZDA081).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The reviewer ZA declared a shared affiliation with one of the authors, SG, to the handling editor at time of review.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., and Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telem. Inform. 34, 1177–1190. doi: 10.1016/j.tele.2017.05.008

CrossRef Full Text | Google Scholar

Arora, A. S., and Sanni, S. A. (2019). Ten years of ‘social media marketing’research in the Journal of Promotion Management: Research synthesis, emerging themes, and new directions. J. Promot. Manag. 25, 476–499. doi: 10.1080/10496491.2018.1448322

Arrigo, E. (2018). Social media marketing in luxury brands. Manag. Res. Rev. 41, 657–679. doi: 10.1108/MRR-04-2017-0134

Assimakopoulos, C., Antoniadis, I., Kayas, O. G., and Dvizac, D. (2017). Effective social media marketing strategy: Facebook as an opportunity for universities. International J. Retail Distribut. Manag. 45, 532–549. doi: 10.1108/IJRDM-11-2016-0211

Awan, F. H., Dunnan, L., Jamil, K., Gul, R. F., Guangyu, Q., and Idrees, M. (2021). Impact of Role Conflict on Intention to leave Job with the moderating role of Job Embeddedness in Banking sector employees. Front. Psychol. 12:719449. doi: 10.3389/fpsyg.2021.719449

Beig, F. A., and Khan, M. F. (2018). Impact of social media marketing on brand experience: A study of select apparel brands on Facebook. Vision 22, 264–275. doi: 10.1177/0972262918785962

Bhattacharya, C. B., and Sen, S. (2003). Consumer–company identification: A framework for understanding consumers’ relationships with companies. J. Marke. 67, 76–88. doi: 10.1509/jmkg.67.2.76.18609

Bhattacherjee, A., Perols, J., and Sanford, C. (2008). Information technology continuance: A theoretic extension and empirical test. J. Comput. Inform. Systems 49, 17–26.

Google Scholar

Chen, S. C., and Lin, C. P. (2019). Understanding the effect of social media marketing activities: The mediation of social identification, perceived value, and satisfaction. Technol. Forecast. Soc. Change 140, 22–32. doi: 10.1016/j.techfore.2018.11.025

Chen, X., and Qasim, H. (2021). Does E-Brand experience matter in the consumer market? Explaining the impact of social media marketing activities on consumer-based brand equity and love. J. Consumer Behav. 20, 1065–1077. doi: 10.1002/cb.1915

Chen, Y.-S., Lin, C.-Y., and Weng, C.-S. (2015). The influence of environmental friendliness on green trust: The mediation effects of green satisfaction and green perceived quality. Sustainability 7, 10135–10152.

Cheung, M. L., Pires, G. D., Rosenberger, P. J. III, Leung, W. K. S., and Ting, H. (2021). Investigating the role of social media marketing on value co-creation and engagement: An empirical study in China and Hong Kong. Austral. Marke. J. 29, 118–131. doi: 10.1016/j.ausmj.2020.03.006

Debatin, B., Lovejoy, J. P., Horn, A.-K., and Hughes, B. N. (2009). Facebook and online privacy: Attitudes, behaviors, and unintended consequences. J. Comput. Med. Commun. 15, 83–108.

Di Minin, E., Fink, C., Hausmann, A., Kremer, J., and Kulkarni, R. (2021). How to address data privacy concerns when using social media data in conservation science. Conservat. Biol. 35, 437–446. doi: 10.1111/cobi.13708

PubMed Abstract | CrossRef Full Text | Google Scholar

Dodds, W. B. (1991). In search of value: how price and store name information influence buyers’ product perceptions. J. Consumer Marke. 8, 15–24. doi: 10.1108/07363769110034974

Dunnan, L., Jamil, K., Abrar, U., Arain, B., Guangyu, Q., and Awan, F. H. (2020). “Analyzing the green technology market focus on environmental performance in Pakistan,” in 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (ICoMET) (Sukkur: IEEE), 1–5. doi: 10.1016/s1351-4180(08)70002-3

Dutot, V. (2020). A social identity perspective of social media’s impact on satisfaction with life. Psychol. Marke. 37, 759–772. doi: 10.1111/j.1547-5069.2011.01394.x

Ebrahim, R. S. (2020). The role of trust in understanding the impact of social media marketing on brand equity and brand loyalty. J. Relat. Marke. 19, 287–308. doi: 10.1080/15332667.2019.1705742

Farivar, F., and Richardson, J. (2021). Workplace digitalisation and work-nonwork satisfaction: the role of spillover social media. Behav. Inform. Technol. 40, 747–758. doi: 10.1080/0144929x.2020.1723702

Fornell, C., and Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. J. Marke. Res. 18, 39–50. doi: 10.2307/3151312

Gul, R. F., Liu, D., Jamil, K., Baig, S. A., Awan, F. H., and Liu, M. (2021). Linkages between market orientation and brand performance with positioning strategies of significant fashion apparels in Pakistan. Fashion Textiles 8, 1–19.

Gupta, M., and Syed, A. A. (2021). Impact of online social media activities on marketing of green products. International J. Organizat. Anal. [Epub online ahead of print]. doi: 10.1108/IJOA-02-2020-2037

Hafez, M. (2021). The impact of social media marketing activities on brand equity in the banking sector in Bangladesh: the mediating role of brand love and brand trust. International J. Bank Marke. 39, 1353–1376. doi: 10.1108/IJBM-02-2021-0067

Hair, J. F. Jr., Sarstedt, M., Hopkins, L., and Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). Eur. Bus. Rev. 26, 106–121. doi: 10.1108/EBR-10-2013-0128

Hair Joe, J., Sarstedt, M., Matthews, L. M., and Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: part I – method. Eur. Bus. Rev. 28, 63–76. doi: 10.1108/EBR-09-2015-0094

Haobin Ye, B., Fong, L. H. N., and Luo, J. M. (2021). Parasocial interaction on tourism companies’ social media sites: antecedents and consequences. Curr. Issues Tourism 24, 1093–1108. doi: 10.1080/13683500.2020.1764915

Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Commun. Monogr. 76, 408–420. doi: 10.1080/03637750903310360

Hayes, A. F., and Preacher, K. J. (2010). Quantifying and testing indirect effects in simple mediation models when the constituent paths are nonlinear. Multiv. Behav. Res. 45, 627–660. doi: 10.1080/00273171.2010.498290

Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Marke. Sci. 43, 115–135. doi: 10.1007/s11747-014-0403-8

Ibrahim, B. (2021). Social Media Marketing Activities and Brand Loyalty: A Meta-Analysis Examination. J. Promot. Manag. 28, 60–90.

Ibrahim, B., and Aljarah, A. (2018). Dataset of relationships among social media marketing activities, brand loyalty, revisit intention Evidence from the hospitality industry in Northern Cyprus. Data Brief 21, 1823–1828. doi: 10.1016/j.dib.2018.11.024

Ismail, A. R., Nguyen, B., and Melewar, T. C. (2018). Impact of perceived social media marketing activities on brand and value consciousness: roles of usage, materialism and conspicuous consumption. International J. Internet Marke. Adv. 12, 233–254. doi: 10.1504/ijima.2018.10013343

Jamil, K., Liu, D., Gul, R. F., Hussain, Z., Mohsin, M., Qin, G., et al. (2021b). Do remittance and renewable energy affect CO2 emissions? An empirical evidence from selected G-20 countries. Energy Environ. [preprint]. doi: 10.1177/0958305X211029636

Jamil, K., Hussain, Z., Gul, R. F., Shahzad, M. A., and Zubair, A. (2021a). The effect of consumer self-confidence on information search and share intention. Inform. Discov. Deliv. [Epub online ahead of print]. doi: 10.1108/IDD-12-2020-0155

Jarman, H. K., Marques, M. D., McLean, S. A., Slater, A., and Paxton, S. J. (2021). Social media, body satisfaction and well-being among adolescents: A mediation model of appearance-ideal internalization and comparison. Body Image 36, 139–148. doi: 10.1016/j.bodyim.2020.11.005

Kim, A. J., and Ko, E. (2012). Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. J. Bus. Res. 65, 1480–1486. doi: 10.1016/j.jbusres.2011.10.014

Koçak, O., İlme, E., and Younis, M. Z. (2021). Mediating Role of Satisfaction with Life in the Effect of Self-Esteem and Education on Social Media Addiction in Turkey. Sustainability 13:9097. doi: 10.3390/su13169097

Lee, H.-W., Kim, S., and Liew, J. (2021). Spectator sports as context for examining observers’ agreeableness, social identification, and empathy in a high-stakes conflict situation. Psychol. Rep. 124, 1788–1806. doi: 10.1177/0033294120948228

Liu, X., Shin, H., and Burns, A. C. (2021). Examining the impact of luxury brand’s social media marketing on customer engagement: Using big data analytics and natural language processing. J. Bus. Res. 125, 815–826. doi: 10.1016/j.jbusres.2019.04.042

Mahendra, P. T. (2021). Improve Customer Satisfaction through Product Innovation in Social Media. Hum. Soc. Sci. 4, 3719–3729. doi: 10.1007/s11356-021-14885-4

Mohsin, M., Zhu, Q., Naseem, S., Sarfraz, M., and Ivascu, L. (2021). Mining Industry Impact on Environmental Sustainability, Economic Growth, Social Interaction, and Public Health: An Application of Semi-Quantitative Mathematical Approach. Processes 9:972. doi: 10.3390/pr9060972

Naseem, S., Fu, G. L., Mohsin, M., Aunjam, M. S., Rafiq, M. Z., Jamil, K., et al. (2020). Development of an inexpensive functional textile product by applying accounting cost benefit analysis. Industria Textila 71, 17–22. doi: 10.35530/it.071.01.1692

Pang, H. (2021). Identifying associations between mobile social media users’ perceived values, attitude, satisfaction, and eWOM engagement: The moderating role of affective factors. Telematics Inform. 59:101561. doi: 10.1016/j.tele.2020.101561

Parsons, A. L., and Lepkowska-White, E. (2018). Social media marketing management: A conceptual framework. J. Internet Commerce 17, 81–95. doi: 10.1080/15332861.2018.1433910

Pavlou, P. A., Liang, H., and Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly 31, 105–136. doi: 10.2307/25148783

Petrick, J. F., Backman, S. J., Bixler, R., and Norman, W. C. (2001). Analysis of golfer motivations and constraints by experience use history. J. Leisure Res. 33, 56–70. doi: 10.1080/00222216.2001.11949930

Podsakoff, P. M., MacKenzie, S. B., and Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 63, 539–569. doi: 10.1146/annurev-psych-120710-100452

Preacher, K. J., and Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 40, 879–891. doi: 10.3758/brm.40.3.879

Sahibzada, U. F., Cai, J., Latif, K. F., and Sahibzada, H. F. (2020). Knowledge management processes, knowledge worker satisfaction, and organizational performance. Aslib J. Inform. Manag. 72, 112–129. doi: 10.1108/AJIM-10-2019-0276

Salem, S. F., and Salem, S. O. (2021). Effects of social media marketing and selected marketing constructs on stages of brand loyalty. Global Bus. Rev. 22, 650–673. doi: 10.1177/0972150919830863

Sarfraz, M., Mohsin, M., Naseem, S., and Kumar, A. (2021). Modeling the relationship between carbon emissions and environmental sustainability during COVID-19: A new evidence from asymmetric ARDL cointegration approach. Environ. Devel. Sustain. 23, 16208–16226. doi: 10.1007/s10668-021-01324-0

Sarstedt, M., Ringle, C. M., Henseler, J., and Hair, J. F. (2014). On the emancipation of PLS-SEM: A commentary on Rigdon (2012). Long Range Plan. 47, 154–160. doi: 10.1016/j.lrp.2014.02.007

Seo, E.-J., and Park, J.-W. (2018). A study on the effects of social media marketing activities on brand equity and customer response in the airline industry. J. Air Transp. Manag. 66, 36–41. doi: 10.1016/j.jairtraman.2017.09.014

Shareef, M. A., Mukerji, B., Dwivedi, Y. K., Rana, N. P., and Islam, R. (2019). Social media marketing: Comparative effect of advertisement sources. J. Retail. Consum. Ser. 46, 58–69. doi: 10.1016/j.jretconser.2017.11.001

Shujaat, A., Rashid, A., and Muzaffar, A. (2021). Exploring the Effects of Social Media Use on Employee Performance: Role of Commitment and Satisfaction. Pennsylvania: IGI Global, 1788–1809.

Sirola, A., Kaakinen, M., Savolainen, I., Paek, H.-J., Zych, I., and Oksanen, A. (2021). Online identities and social influence in social media gambling exposure: A four-country study on young people. Telematics Inform. 60:101582. doi: 10.1016/j.tele.2021.101582

Suman, C., Chaudhary, R. S., Saha, S., and Bhattacharyya, P. (2021). An attention based multi-modal gender identification system for social media users. Mult. Tools Appl. 1183, 1–23. doi: 10.1109/access.2021.3136552

Tafesse, W., and Wien, A. (2018). Implementing social media marketing strategically: an empirical assessment. J. Marke. Manag. 34, 732–749. doi: 10.1080/0267257x.2018.1482365

Tan, M., and Teo, T. S. H. (2000). Factors influencing the adoption of Internet banking. J. Assoc. Inform. Syst. 1:5.

Tarsakoo, P., and Charoensukmongkol, P. (2020). Dimensions of social media marketing capabilities and their contribution to business performance of firms in Thailand. J. Asia Bus. Stud. 14, 441–461. doi: 10.1108/JABS-07-2018-0204

Thaler, R. (1985). Mental accounting and consumer choice. Marke. Sci. 4, 199–214. doi: 10.1287/mksc.4.3.199

Wang, Z., and Kim, H. G. (2017). Can social media marketing improve customer relationship capabilities and firm performance? Dynamic capability perspective. J. Interact. Marke. 39, 15–26. doi: 10.1016/j.intmar.2017.02.004

Wibowo, A., Chen, S.-C., Wiangin, U., Ma, Y., and Ruangkanjanases, A. (2021). Customer behavior as an outcome of social media marketing: The role of social media marketing activity and customer experience. Sustainability 13:189. doi: 10.3390/su13010189

Yadav, M., and Rahman, Z. (2017). Measuring consumer perception of social media marketing activities in e-commerce industry: Scale development & validation. Telematics Inform. 34, 1294–1307. doi: 10.1016/j.tele.2017.06.001

Yadav, M., and Rahman, Z. (2018). The influence of social media marketing activities on customer loyalty. Benchmarking 25, 3882–3905. doi: 10.1108/BIJ-05-2017-0092

Zollo, L., Filieri, R., Rialti, R., and Yoon, S. (2020). Unpacking the relationship between social media marketing and brand equity: The mediating role of consumers’ benefits and experience. J. Bus. Res. 117, 256–267. doi: 10.1016/j.jbusres.2020.05.001

Keywords : social media marketing activities, social identification, satisfaction, continuance intention, participate intention, purchase intention

Citation: Jamil K, Dunnan L, Gul RF, Shehzad MU, Gillani SHM and Awan FH (2022) Role of Social Media Marketing Activities in Influencing Customer Intentions: A Perspective of a New Emerging Era. Front. Psychol. 12:808525. doi: 10.3389/fpsyg.2021.808525

Received: 03 November 2021; Accepted: 20 December 2021; Published: 17 January 2022.

Reviewed by:

Copyright © 2022 Jamil, Dunnan, Gul, Shehzad, Gillani and Awan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Syed Hussain Mustafa Gillani, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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• Published: 16 March 2020

Exploring the role of social media in collaborative learning the new domain of learning

• Jamal Abdul Nasir Ansari 1 &
• Nawab Ali Khan 1  

Smart Learning Environments volume  7 , Article number:  9 ( 2020 ) Cite this article

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This study is an attempt to examine the application and usefulness of social media and mobile devices in transferring the resources and interaction with academicians in higher education institutions across the boundary wall, a hitherto unexplained area of research. This empirical study is based on the survey of 360 students of a university in eastern India, cognising students’ perception on social media and mobile devices through collaborative learning, interactivity with peers, teachers and its significant impact on students’ academic performance. A latent variance-based structural equation model approach was followed for measurement and instrument validation. The study revealed that online social media used for collaborative learning had a significant impact on interactivity with peers, teachers and online knowledge sharing behaviour.

Additionally, interactivity with teachers, peers, and online knowledge sharing behaviour has seen a significant impact on students’ engagement which consequently has a significant impact on students’ academic performance. Grounded to this finding, it would be valuable to mention that use of online social media for collaborative learning facilitate students to be more creative, dynamic and research-oriented. It is purely a domain of knowledge.

Introduction

The explosion of Information and Communication Technology (ICT) has led to an increase in the volume and smoothness in transferring course contents, which further stimulates the appeasement of Digital Learning Communities (DLCs). The millennium and naughtiness age bracket were Information Technology (IT) centric on web space where individual and geopolitical disperse learners accomplished their e-learning goals. The Educause Center for Applied Research [ECAR] ( 2012 ) surveyed students in higher education mentioned that students are pouring the acceptance of mobile computing devices (cellphones, smartphones, and tablet) in Higher Education Institutions (HEIs), roughly 67% surveyed students accepted that mobile devices and social media play a vital role in their academic performance and career enhancement. Mobile devices and social media provide excellent educational e-learning opportunities to the students for academic collaboration, accessing in course contents, and tutors despite the physical boundary (Gikas & Grant, 2013 ). Electronic communication technologies accelerate the pace of their encroachment of every aspect of life, the educational institutions incessantly long decades to struggle in seeing the role of such devices in sharing the contents, usefulness and interactivity style. Adoption and application of mobile devices and social media can provide ample futuristic learning opportunities to the students in accessing course contents as well as interaction with peers and experts (Cavus & Ibrahim, 2008 , 2009 ; Kukulska-Hulme & Shield, 2008 ; Nihalani & Mayrath, 2010 ; Richardson & Lenarcic, 2008 , Shih, 2007 ). Recently Pew Research Center reported that 55% American teenage age bracket of 15–17 years using online social networking sites, i.e. Myspace and Facebook (Reuben, 2008 ). Social media, the fast triggering the mean of virtual communication, internet-based technologies changed the life pattern of young youth.

Use of social media and mobile devices presents both advantages as well as challenges, mostly its benefits seen in terms of accessing course contents, video clip, transfer of the instructional notes etc. Overall students feel that social media and mobile devices are the cheap and convenient tools of obtaining relevant information. Studies in western countries have confronted that online social media use for collaborative learning has a significant contribution to students’ academic performance and satisfaction (Zhu, 2012 ). The purpose of this research project was to explore how learning and teaching activities in higher education institutions were affected by the integration and application of mobile devices in sharing the resource materials, interaction with colleagues and students’ academic performance. The broad goal of this research was to contemporise the in-depth perspectives of students’ perception of mobile devices and social media in learning and teaching activities. However, this research paper paid attention to only students’ experiences, and their understanding of mobile devices and social media fetched changes and its competency in academic performance. The fundamental research question of this research was, what are the opinions of students on social media and mobile devices when it is integrating into higher education for accessing, interacting with peers.

A researcher of the University of Central Florida reported that electronic devices and social media create an opportunity to the students for collaborative learning and also allowed the students in sharing the resource materials to the colleagues (Gikas & Grant, 2013 ). The result of the eight Egyptian universities confirmed that social media have the significant impact on higher education institutions especially in term of learning tools and teaching aids, faculty members’ use of social media seen at a minimum level due to several barriers (internet accessibility, mobile devices etc.).

Social media and mobile devices allow the students to create, edit and share the course contents in textual, video or audio forms. These technological innovations give birth to a new kind of learning cultures, learning based on the principles of collective exploration and interaction (Selwyn, 2012 ). Social media the phenomena originated in 2005 after the Web2.0 existence into the reality, defined more clearly as “a group of Internet-based applications that build on the ideological and technological foundation of web 2.0 and allow creation and exchange of user-generated contents (Kaplan & Haenlein, 2010 ). Mobile devices and social media provide opportunities to the students for accessing resources, materials, course contents, interaction with mentor and colleagues (Cavus & Ibrahim, 2008 , 2009 ; Richardson & Lenarcic, 2008 ).

Social media platform in academic institutions allows students to interact with their mentors, access their course contents, customisation and build students communities (Greenhow, 2011a , 2011b ). 90% school going students currently utilise the internet consistently, with more than 75% teenagers using online networking sites for e-learning (DeBell & Chapman, 2006 ; Lenhart, Arafeh, & Smith, 2008 ; Lenhart, Madden, & Hitlin, 2005 ). The result of the focus group interview of the students in 3 different universities in the United States confirmed that use of social media created opportunities to the learners for collaborative learning, creating and engaging the students in various extra curriculum activities (Gikas & Grant, 2013 ).

Research background and hypotheses

The technological innovation and increased use of the internet for e-learning by the students in higher education institutions has brought revolutionary changes in communication pattern. A report on 3000 college students in the United States revealed that 90% using Facebook while 37% using Twitter to share the resource materials as cited in (Elkaseh, Wong, & Fung, 2016 ). A study highlighted that the usage of social networking sites in educational institutions has a practical outcome on students’ learning outcomes (Jackson, 2011 ). The empirical investigation over 252 undergraduate students of business and management showed that time spent on twitter and involvement in managing social lives and sharing information, course-related influences their performance (Evans, 2014 ).

Social media for collaborative learning, interactivity with teachers, interactivity with peers

Many kinds of research confronted on the applicability of social media and mobile devices in higher education for interaction with colleagues.90% of faculty members use some social media in courses they were usually teaching or professional purposes out of the campus life. Facebook and YouTube are the most visited sites for the professional outcomes, around 2/3rd of the all-faculty use some medium fora class session, and 30% posted contents for students engagement in reading, view materials (Moran, Seaman, & Tinti-Kane, 2011 ). Use of social media and mobile devices in higher education is relatively new phenomena, completely hitherto area of research. Research on the students of faculty of Economics at University of Mortar, Bosnia, and Herzegovina reported that social media is already used for the sharing the materials and exchanges of information and students are ready for active use of social networking site (slide share etc.) for educational purposes mainly e-learning and communication (Mirela Mabić, 2014 ).

The report published by the U.S. higher education department stated that the majority of the faculty members engaged in different form of the social media for professional purposes, use of social media for teaching international business, sharing contents with the far way students, the use of social media and mobile devices for sharing and the interactive nature of online and mobile technologies build a better learning environment at international level. Responses on 308 graduate and postgraduate students in Saudi Arabia University exhibited that positive correlation between chatting, online discussion and file sharing and knowledge sharing, and entertainment and enjoyment with students learning (Eid & Al-Jabri, 2016 ). The quantitative study on 168 faculty members using partial least square (PLS-SEM) at Carnegie classified Doctoral Research University in the USA confirmed that perceived usefulness, external pressure and compatibility of task-technology have positive effect on social media use, the higher the degree of the perceived risk of social media, the less likely to use the technological tools for classroom instruction, the study further revealed that use of social media for collaborative learning has a positive effect on students learning outcome and satisfaction (Cao, Ajjan, & Hong, 2013 ). Therefore, the authors have hypothesized:

H1: Use of social media for collaborative learning is positively associated with interactivity with teachers.

Additionally, Madden and Zickuhr ( 2011 ) concluded that 83% of internet user within the age bracket of 18–29 years adopting social media for interaction with colleagues. Kabilan, Ahmad, and Abidin ( 2010 ) made an empirical investigation on 300 students at University Sains Malaysia and concluded that 74% students found to be the same view that social media infuses constructive attitude towards learning English (Fig. 1 ).

Research Model

Reuben ( 2008 ) concluded in his study on social media usage among professional institutions revealed that Facebook and YouTube used over half of 148 higher education institutions. Nevertheless, a recent survey of 456 accredited United States institutions highlighted 100% using some form of social media, notably Facebook 98% and Twitter 84% for e-learning purposes, interaction with mentors (Barnes & Lescault, 2011 ).

Information and communication technology (ICT), such as web-based application and social networking sites enhances the collaboration and construction of knowledge byway of instruction with outside experts (Zhu, 2012 ). A positive statistically significant relationship was found between student’s use of a variety of social media tools and the colleague’s fellow as well as the overall quality of experiences (Rutherford, 2010 ). The potential use of social media leads to collaborative learning environments which allow students to share education-related materials and contents (Fisher & Baird, 2006 ). The report of 233 students in the United States higher educations confirmed that more recluse students interact through social media, which assist them in collaborative learning and boosting their self-confidence (Voorn & Kommers, 2013 ). Thus hypotheses as

H2: Use of social media for collaborative learning is positively associated with interactivity with peers.

Social media for collaborative learning, interactivity with peers, online knowledge sharing behaviour and students’ engagement

Students’ engagement in social media and its types represent their physical and mental involvement and time spent boost to the enhancement of educational Excellency, time spent on interaction with peers, teachers for collaborative learning (Kuh, 2007 ). Students’ engagement enhanced when interacting with peers and teacher was in the same direction, shares of ideas (Chickering & Gamson, 1987 ). Engagement is an active state that is influenced by interaction or lack thereof (Leece, 2011 ). With the advancement in information technology, the virtual world becomes the storehouse of the information. Liccardi et al. ( 2007 ) concluded that 30% students were noted to be active on social media for interaction with their colleagues, tutors, and friends while more than 52% used some social media forms for video sharing, blogs, chatting, and wiki during their class time. E-learning becomes now sharp and powerful tools in information technology and makes a substantial impact on the student’s academic performance. Sharing your knowledge will make you better. Social network ties were shown to be the best predictors of online knowledge sharing intention, which in turn associated with knowledge sharing behaviour (Chen, Chen, & Kinshuk, 2009 ). Social media provides the robust personalised, interactive learning environment and enhances in self-motivation as cited in (Al-Mukhaini, Al-Qayoudhi, & Al-Badi, 2014 ). Therefore, it was hypothesised that:

H3: Use of social media for collaborative learning is positively associated with online knowledge sharing behaviour.

Broadly Speaking social media/sites allow the students to interact, share the contents with colleagues, also assisting in building connections with others (Cain, 2008 ). In the present era, the majority of the college-going students are seen to be frequent users of these sophisticated devices to keep them informed and updated about the external affair. Facebook reported per day 1,00,000 new members join; Facebook is the most preferred social networking sites among the students of the United States as cited in (Cain, 2008 ). The researcher of the school of engineering, Swiss Federal Institute of Technology Lausanne, Switzerland, designed and developed Grasp, a social media platform for their students’ collaborative learning, sharing contents (Bogdanov et al., 2012 ). The utility and its usefulness could be seen in the University of Geneva and Tongji University at both two educational places students were satisfied and accept ‘ Grasp’ to collect, organised and share the contents. Students use of social media will interact ubiquity, heterogeneous and engaged in large groups (Wankel, 2009 ). So we hypotheses

H4: More interaction with teachers leads to higher students’ engagement.

However, a similar report published on 233 students revealed that social media assisted in their collaborative learning and self-confidence as they prefer communication technology than face to face communication. Although, the students have the willingness to communicate via social media platform than face to face (Voorn & Kommers, 2013 ). The potential use of social media tools facilitates in achieving higher-level learning through collaboration with colleagues and other renewed experts in their field (Junco, Heiberger, & Loken, 2011 ; Meyer, 2010 ; Novak, Razzouk, & Johnson, 2012 ; Redecker, Ala-Mutka, & Punie, 2010 ). Academic self-efficacy and optimism were found to be strongly related to performance, adjustment and consequently both directly impacted on student’s academic performance (Chemers, Hu, & Garcia, 2001 ). Data of 723 Malaysian researchers confirmed that both male and female students were satisfied with the use of social media for collaborative learning and engagement was found positively affected with learning performance (Al-Rahmi, Alias, Othman, Marin, & Tur, 2018 ). Social media were seen as a powerful driver for learning activities in terms of frankness, interactivity, and friendliness.

Junco et al. ( 2011 ) conducted research on the specific purpose of the social media; how Twitter impacted students’ engagement, found that it was extent discussion out of class, their participation in panel group (Rodriguez, 2011 ). A comparative study conducted by (Roblyer, McDaniel, Webb, Herman, & Witty, 2010 ) revealed that students were more techno-oriented than faculty members and more likely using Facebook and such similar communication technology to support their class-related task. Additionally, faculty members were more likely to use traditional techniques, i.e. email. Thus hypotheses framed is that:

H5: More interaction with peers ultimately leads to better students’ engagement.

Social networking sites and social media are closely similar, which provide a platform where students can interact, communicate, and share emotional intelligence and looking for people with other attitudes (Gikas & Grant, 2013 ). Facebook and YouTube channel use also increased in the skills/ability and knowledge and outcomes (Daniel, Isaac, & Janet, 2017 ). It was highlighted that 90% of faculty members were using some sort of social media in their courses/ teaching. Facebook was the most visited social media sites as per study, 40% of faculty members requested students to read and views content posted on social media; majority reports that videos, wiki, etc. the primary source of acquiring knowledge, social networking sites valuable tool/source of collaborative learning (Moran et al., 2011 ). However, more interestingly, in a study which was carried out on 658 faculty members in the eight different state university of Turkey, concluded that nearly half of the faculty member has some social media accounts.

Further reported that adopting social media for educational purposes, the primary motivational factor which stimulates them to use was effective and quick means of communication technology (Akçayır, 2017 ). Thus hypotheses formulated is:

H6: Online knowledge sharing behaviour is positively associated with the students’ engagement.

Using multiple treatment research design, following act-react to increase students’ academic performance and productivity, it was observed when self–monitoring record sheet was placed before students and seen that students engagement and educational productivity was increased (Rock & Thead, 2007 ). Student engagement in extra curriculum activities promotes academic achievement (Skinner & Belmont, 1993 ), increases grade rate (Connell, Spencer, & Aber, 1994 ), triggering student performance and positive expectations about academic abilities (Skinner & Belmont, 1993 ). They are spending time on online social networking sites linked to students engagement, which works as the motivator of academic performance (Fan & Williams, 2010 ). Moreover, it was noted in a survey of over 236 Malaysian students that weak association found between the online game and student’s academic performance (Eow, Ali, Mahmud, & Baki, 2009 ). In a survey of 671 students in Jordan, it was revealed that student’s engagement directly influences academic performance, also seen the indirect effect of parental involvement over academic performance (Al-Alwan, 2014 ). Engaged students are perceptive and highly active in classroom activities, ready to participate in different classroom extra activities and expose motivation to learn, which finally leads in academic achievement (Reyes, Brackett, Rivers, White, & Salovey, 2012 ). A mediated role of students engagement seen in 1399 students’ classroom emotional climate and grades (Reyes et al., 2012 ). A statistically significant relation was noticed between online lecture and exam performance.

Nonetheless, intelligence quotient, personality factors, students must be engaged in learning activities as cited in (Bertheussen & Myrland, 2016 ). The report of the 1906 students at 7 universities in Colombia confirmed that the weak correlation between collaborative learning, students faculty interaction with academic performance (Pineda-Báez et al., 2014 ) Thus, the hypothesis

H7: Student's Engagement is positively associated with the student's academic performance.

Methodology

To check the students’ perception on social media for collaborative learning in higher education institutions, Data were gathered both offline and online survey administered to students from one public university in Eastern India (BBAU, Lucknow). For the sake of this study, indicators of interactivity with peers and teachers, the items of students engagement, the statement of social media for collaborative learning, and the elements of students’ academic performance were adopted from (AL-Rahmi & Othman, 2013 ). The statement of online knowledge sharing behaviour was taken from (Ma & Yuen, 2011 ).

The indicators of all variables which were mentioned above are measured on the standardised seven-point Likert scale with the anchor (1-Strongly Disagree, to 7-Strongly Agree). Interactivity with peers was measured using four indicators; the sample items using social media in class facilitates interaction with peers ; interactivity with teachers was measured using four symbols, the sample item is using social media in class allows me to discuss with the teacher. ; engagement was measured using three indicators by using social media I felt that my opinions had been taken into account in this class ; social media for collaborative learning was measured using four indicators collaborative learning experience in social media environment is better than in a face-to-face learning environment ; students’ academic performance was measured using five signs using social media to build a student-lecturer relationship with my lecturers, and this improves my academic performance ; online knowledge sharing behaviour was assessed using five symbols the counsel was received from other colleague using social media has increased our experience .

Procedure and measurement

A sample of 360 undergraduate students was collected by convenience sampling method of a public university in Eastern India. The proposed model of study was measured and evaluated using variance based structured equation model (SEM)-a latent multi variance technique which provides the concurrent estimation of structural and measurement model that does not meet parametric assumption (Coelho & Duarte, 2016 ; Haryono & Wardoyo, 2012 ; Lee, 2007 ; Moqbel, Nevo, & Kock, 2013 ; Raykov & Marcoulides, 2000 ; Williams, Rana, & Dwivedi, 2015 ). The confirmatory factor analysis (CFA) was conducted to ensure whether the widely accepted criterion of discriminate and convergent validity met or not. The loading of all the indicators should be 0.50 or more (Field, 2011 ; Hair, Anderson, Tatham, & Black, 1992 ). And it should be statistically significant at least at the 0.05.

Demographic analysis (Table 1 )

The majority of the students in this study were females (50.8%) while male students were only 49.2% with age 15–20 years (71.7%). It could be pointed out at this juncture that the majority of the students (53.9%) in BBAU were joined at least 1–5 academic pages for their getting information, awareness and knowledge. 46.1% of students spent 1–5 h per week on social networking sites for collaborative learning, interaction with teachers at an international level. The different academic pages followed for accessing material, communication with the faculty members stood at 44.4%, there would be various forms of the social networking sites (LinkedIn, Slide Share, YouTube Channel, Researchgate) which provide the facility of online collaborative learning, a platform at which both faculty members and students engaged in learning activities.

As per report (Nasir, Khatoon, & Bharadwaj, 2018 ), most of the social media user in India are college-going students, 33% girls followed by 27% boys students, and this reports also forecasted that India is going to become the highest 370.77 million internet users in 2022. Additionally, the majority of the faculty members use smartphone 44% to connect with the students for sharing material content. Technological advantages were the pivotal motivational force which stimulates faculty members and students to exploits the opportunities of resource materials (Nasir & Khan, 2018 ) (Fig. 2 ).

Reasons for Using Social Media

When the students were asked for what reason did they use social media, it was seen that rarely using for self-promotion, very frequently using for self-education, often used for passing the time with friends, and so many fruitful information the image mentioned above depicting.

Instrument validation

The structural model was applied to scrutinize the potency and statistically significant relationship among unobserved variables. The present measurement model was evaluated using Confirmatory Factor Analysis (CFA), and allied procedures to examine the relationship among hypothetical latent variables has acceptable reliability and validity. This study used both SPSS 20.0 and AMOS to check measurement and structural model (Field, 2013 ; Hair, Anderson, et al., 1992 ; Mooi & Sarstedt, 2011 ; Norusis, 2011 ).

The Confirmatory Factor Analysis (CFA) was conducted to ensure whether the widely accepted criterion of discriminant and convergent validity met or not. The loading of all the indicators should be 0.70 or more it should be statistically significant at least at the 0.05 (Field, 2011 ; Hair, Anderson, et al., 1992 ).

CR or CA-based tests measured the reliability of the proposed measurement model. The CA provides an estimate of the indicators intercorrelation (Henseler & Sarstedt, 2013 . The benchmark limits of the CA is 0.7 or more (Nunnally & Bernstein, 1994 ). As per Table 2 , all latent variables in this study above the recommended threshold limit. Although, Average Variance Extracted (AVE) has also been demonstrated which exceed the benchmark limit 0.5. Thus all the above-specified values revealed that our instrument is valid and effective. (See Table 2 for the additional information) (Table 3 ).

In a nutshell, the measurement model clear numerous stringent tests of convergent validity, discriminant validity, reliability, and absence of multi-collinearity. The finding demonstrated that our model meets widely accepted data validation criteria. (Schumacker & Lomax, 2010 ).

The model fit was evaluated through the Chi-Square/degree of freedom (CMIN/DF), Root Mean Residual (RMR), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), and Goodness of fit index (GFI) and Tucker-Lewis Index (TLI). The benchmark limit of the CFI, TLI, and GFI 0.90or more (Hair et al., 2016 ; Kock, 2011 ). The model study demonstrated in the table, as mentioned above 4 that the minimum threshold limit was achieved (See Table 4 for additional diagnosis).

Path coefficient of several hypotheses has been demonstrated in Fig.  3 , which is a variable par relationship. β (beta) Coefficients, standardised partial regression coefficients signify the powers of the multivariate relationship among latent variables in the model. Remarkably, it was observed that seven out of the seven proposed hypotheses were accepted and 78% of the explained variance in students’ academic performance, 60% explained variance in interactivity with teachers, 48% variance in interactivity with peers, 43% variance in online knowledge sharing behaviour and 79% variance in students’ engagement. Social media collaborative learning has a significant association with teacher interactivity(β = .693, P  < 0.001), demonstrating that there is a direct effect on interaction with the teacher by social media when other variables are controlled. On the other hand, use of social media for collaborative learning has noticed statistically significant positive relationship with peers interactivity (β = .704, p  < 0.001) meaning thereby, collaborative learning on social media by university students, leads to the high degree of interaction with peers, colleagues. Implied 10% rise in social media use for learning purposes, expected 7.04% increase in interaction with peers.

Path Diagram

Use of social media for collaborating learning has a significant positive association with online knowledge sharing behaviour (β = .583, p  < 0.001), meaning thereby that the more intense use of social media for collaborative learning by university students, the more knowledge sharing between peers and colleagues. Also, interaction with the teacher seen the significant statistical positive association with students engagement (β = .450, p  < 0.001), telling that the more conversation with teachers, leads to a high level of students engagement. Similarly, the practical interpretation of this result is that there is an expected 4.5% increase in student’s participation for every 10% increase in interaction with teachers. Interaction with peers has a significant positive association with students engagement (β = .210, p  < 0.001). Practically, the finding revealed that 10% upturn in student’s involvement, there is a 2.1% increase in peer’s interaction. There is a significant positive association between online knowledge sharing behaviour and students engagement (β = 0.247, p  < 0.001), and finally students engagement has been a statistically significant positive relationship with students’ academic performance (β = .972, p  < 0.001), this is the clear indication that more engaged students in collaborative learning via social media leads to better students’ academic performance.

Discussion and implication

There is a continuing discussion in the academic literature that use of such social media and social networking sites would facilitate collaborative learning. It is human psychology generally that such communication media technology seems only for entertainment, but it should be noted here carefully that if such communication technology would be followed with due attention prove productive. It is essential to acknowledge that most university students nowadays adopting social media communication to interact with colleagues, teachers and also making the group be in touch with old friends and even a convenient source of transferring the resources. In the present era, the majority of the university students having diversified social media community groups like Whatsapp, Facebook pages following different academic web pages to upgrade their knowledge.

Practically for every 10% rise in students’ engagement, expected to be 2.1% increase in peer interaction. As the study suggested that students engage in different sites, they start discussing with colleagues. More engaged students in collaborative learning through social media lead better students’ academic performance. The present study revealed that for every 10% increase in student’s engagement, there would be an expected increase in student academic performance at a rate of 9.72. This extensive research finding revealed that the application of online social media would facilitate the students to become more creative, dynamics and connect to the worldwide instructor for collaborative learning.

Accordingly, the use of online social media for collaborative learning, interaction with mentors and colleagues leadbetter student’s engagement which consequently affects student’s academic performance. The higher education authority should provide such a platform which can nurture the student’s intellectual talents. Based on the empirical investigation, it would be said that students’ engagement, social media communication devices facilitate students to retrieve information and interact with others in real-time regarding sharing teaching materials contents. Additionally, such sophisticated communication devices would prove to be more useful to those students who feel too shy in front of peers; teachers may open up on the web for the collaborative learning and teaching in the global scenario and also beneficial for physically challenged students. It would also make sense that intensive use of such sophisticated technology in teaching pedagogical in higher education further facilitates the teachers and students to interact digitally, web-based learning, creating discussion group, etc. The result of this investigation confirmed that use of social media for collaborative learning purposes, interaction with peers, and teacher affect their academic performance positively, meaning at this moment that implementation of such sophisticated communication technology would bring revolutionary, drastic changes in higher education for international collaborative learning (Table 5 ).

Limitations and future direction

Like all the studies, this study is also not exempted from the pitfalls, lacunas, and drawbacks. The first and foremost research limitation is it ignores the addiction of social media; excess use may lead to destruction, deviation from the focal point. The study only confined to only one academic institution. Hence, the finding of the project cannot be generalised as a whole. The significant positive results were found in this study due to the fact that the social media and mobile devices are frequently used by the university going students not only as a means of gratification but also for educational purposes.

Secondly, this study was conducted on university students, ignoring the faculty members, it might be possible that the faculty members would not have been interested in interacting with the students. Thus, future research could be possible towards faculty members in different higher education institutions. To the authors’ best reliance, this is the first and prime study to check the usefulness and applicability of social media in the higher education system in the Indian context.

Concluding observations

Based on the empirical investigation, it could be noted that application and usefulness of the social media in transferring the resource materials, collaborative learning and interaction with the colleagues as well as teachers would facilitate students to be more enthusiastic and dynamic. This study provides guidelines to the corporate world in formulating strategies regarding the use of social media for collaborative learning.

Availability of data and materials

The corresponding author declared here all types of data used in this study available for any clarification. The author of this manuscript ready for any justification regarding the data set. To make publically available of the data used in this study, the seeker must mail to the mentioned email address. The profile of the respondents was completely confidential.

Akçayır, G. (2017). Why do faculty members use or not use social networking sites for education? Computers in Human Behavior, 71 , 378–385.

Article   Google Scholar  

Al-Alwan, A. F. (2014). Modeling the relations among parental involvement, school engagement and academic performance of high school students. International Education Studies, 7 (4), 47–56.

Al-Mukhaini, E. M., Al-Qayoudhi, W. S., & Al-Badi, A. H. (2014). Adoption of social networking in education: A study of the use of social networks by higher education students in Oman. Journal of International Education Research, 10 (2), 143–154.

Google Scholar  

Al-Rahmi, W. M., Alias, N., Othman, M. S., Marin, V. I., & Tur, G. (2018). A model of factors affecting learning performance through the use of social media in Malaysian higher education. Computers & Education, 121 , 59–72.

Al-Rahmi, W. M., & Othman, M. S. (2013). Evaluating student’s satisfaction of using social media through collaborative learning in higher education. International Journal of Advances in Engineering & Technology, 6 (4), 1541–1551.

Arbuckle, J. (2008). Amos 17.0 user's guide . Chicago: SPSS Inc..

Barnes, N. G., & Lescault, A. M. (2011). Social media adoption soars as higher-ed experiments and reevaluates its use of new communications tools . North Dartmouth: Center for Marketing Research. University of Massachusetts Dartmouth.

Bertheussen, B. A., & Myrland, Ø. (2016). Relation between academic performance and students’ engagement in digital learning activities. Journal of Education for Business, 91 (3), 125–131.

Bogdanov, E., Limpens, F., Li, N., El Helou, S., Salzmann, C., & Gillet, D. (2012). A social media platform in higher education. In Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON) (pp. 1–8). IEEE.

Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/windows: basic concepts, applications, and programming . Thousand Oaks: Sage.

Cain, J. (2008). Online social networking issues within academia and pharmacy education. American Journal of Pharmaceutical Education. https://doi.org/10.5688/aj720110 .

Cao, Y., Ajjan, H., & Hong, P. (2013). Using social media applications for educational outcomes in college teaching: a structural equation analysis. British Journal of Educational Technology, 44 (4), 581–593. https://doi.org/10.1111/bjet.12066 .

Cavus, N., & Ibrahim, D. (2008). A mobile tool for learning English words, Online Submission (pp. 6–9) Retrieved from http://libezproxy.open.ac.uk/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=ED504283&site=ehost-live&scope=site .

Cavus, N., & Ibrahim, D. (2009). M-learning: An experiment in using SMS to support learning new English language words. British Journal of Educational Technology, 40 (1), 78–91.

Chemers, M. M., Hu, L. T., & Garcia, B. F. (2001). Academic self-efficacy and first-year college student performance and adjustment. Journal of Educational Psychology, 93 (1), 55–64. https://doi.org/10.1037/0022-0663.93.1.55 .

Chen, I. Y. L., Chen, N.-S., & Kinshuk. (2009). International forum of Educational Technology & Society Examining the factors influencing participants’ knowledge sharing behavior in virtual learning communities published by : International forum of Educational Technology & Society Examining the factor. Educational Technology & Society, 12 (1), 134–148.

Chickering, A. W., & Gamson, Z. F. (1987). Seven principles for good practise in undergraduate education. AAHE bulletin, 3 , 7.

Coelho, J., & Duarte, C. (2016). A literature survey on older adults' use of social network services and social applications. Computers in Human Behavior, 58 , 187–205.

Connell, J. P., Spencer, M. B., & Aber, J. L. (1994). Educational risk and resilience in African-American youth: Context, self, action, and outcomes in school. Child Development, 65 (2), 493–506.

Daniel, E. A., Isaac, E. N., & Janet, A. K. (2017). Influence of Facebook usage on employee productivity: A case of university of cape coast staff. African Journal of Business Management, 11 (6), 110–116. https://doi.org/10.5897/AJBM2017.8265 .

DeBell, M., & Chapman, C. (2006). Computer and internet use by students in 2003. Statistical analysis report. NCES 2006-065. National Center for education statistics.

Dziuban, C., & Walker, J. D. (2012). ECAR Study of Undergraduate Students and Information Technology, 2012 (Research Report) . Louisville: EDUCAUSE Centre for Applied Research.

Eid, M. I. M., & Al-Jabri, I. M. (2016). Social networking, knowledge sharing, and student learning: The case of university students. Computers and Education, 99 , 14–27. https://doi.org/10.1016/j.compedu.2016.04.007 .

Elkaseh, A. M., Wong, K. W., & Fung, C. C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: A structural equation modeling analysis. International Journal of Information and Education Technology, 6 (3), 192.

Eow, Y. L., Ali, W. Z. b. W., Mahmud, R. b., & Baki, R. (2009). Form one students’ engagement with computer games and its effect on their academic achievement in a Malaysian secondary school. Computers and Education, 53 (4), 1082–1091. https://doi.org/10.1016/j.compedu.2009.05.013 .

Evans, C. (2014). Twitter for teaching: Can social media be used to enhance the process of learning? British Journal of Educational Wiley Online Library, 45 (5), 902–915. https://doi.org/10.1111/bjet.12099 .

Fan, W., & Williams, C. M. (2010). The effects of parental involvement on students’ academic self-efficacy, engagement and intrinsic motivation. Educational Psychology, 30 (1), 53–74. https://doi.org/10.1080/01443410903353302 .

Field, A. (2011). Discovering statistics using SPSS: (and sex and drugs and rock'n'roll) (Vol. 497). London: Sage.

Field, A. (2013). Factor analysis using SPSS. Scientific Research and Essays, 22 (June), 1–26. https://doi.org/10.1016/B978-0-444-52272-6.00519-5 .

Fisher, M., & Baird, D. E. (2006). Making mLearning work: Utilizing mobile technology for active exploration, collaboration, assessment, and reflection in higher education. Journal of Educational Technology Systems, 35 (1), 3–30.

Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones &amp; social media. Internet and Higher Education Mobile, 19 , 18–26. https://doi.org/10.1016/j.iheduc.2013.06.002 .

Greenhow, C. (2011a). Online social networks and learning. On the horizon, 19 (1), 4–12.

Greenhow, C. (2011b). Youth, learning, and social media. Journal of Educational Computing Research, 45 (2), 139–146. https://doi.org/10.2190/EC.45.2.a .

Hair Anderson, R. E., Tatham, R. L., & Black, W. C. (1992). Multivariate data analysis. International Journal of Pharmaceutics . https://doi.org/10.1016/j.ijpharm.2011.02.019 .

Hair Jr., J. F., Sarstedt, M., Matthews, L. M., & Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: part I–method. European Business Review.

Harrington, D. (2009). Confirmatory factor analysis . Oxford university press.

Haryono, S., & Wardoyo, P. (2012). Structural Equation Modeling (Vol. 331).

Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28 (2), 565–580.

Jackson, C. (2011). Your students love social media… and so can you. Teaching Tolerance, 39 , 38–41.

Junco, R., Heiberger, G., & Loken, E. (2011). The effect of twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27 (2), 119–132.

Kabilan, M. K., Ahmad, N., & Abidin, M. J. Z. (2010). Facebook: An online environment for learning of English in institutions of higher education? The Internet and Higher Education, 13 (4), 179–187.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53 (1), 59–68.

Kock, N. (2011). Using WarpPLS in e-collaboration studies: Mediating effects, control and second order variables, and algorithm choices. International Journal of e-Collaboration (IJeC), 7 (3), 1–13.

Kuh, G. D. (2007). What student engagement data tell us about college readiness. Peer Review, 9 (1), 4–8.

Kukulska-Hulme, A., & Shield, L. (2008). An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction. ReCALL, 20 (3), 271–289.

Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach (Wiley series in probability and statistics). Ecotoxicology and Environmental Safety, 73 . https://doi.org/10.1016/j.ecoenv.2009.09.012 .

Leece, R. (2011). Engaging students through social media. Journal of the Australian and New Zealand Student Services Association, 38 , 10–14 Retrieved from https://www.researchgate.net/profile/Anthony_Jorm/publication/235003484_Introduction_to_guidelines_for_tertiary_education_institutions_to_assist_them_in_supporting_students_with_mental_health_problems/links/0c96052ba5314e1202000000.pdf#page=67 .

Lenhart, A., Arafeh, S., & Smith, A. (2008). Writing, technology and teens . Pew Internet & American Life Project.

Lenhart, A., Madden, M., & Hitlin, P. (2005). Teens and technology (p. 2008). Washington, DC: Pew Charitable Trusts Retrieved September 29.

Liccardi, I., Ounnas, A., Pau, R., Massey, E., Kinnunen, P., Lewthwaite, S., …, Sarkar, C. (2007). The role of social networks in students’ learning experiences. In ACM Sigcse Bulletin (39, 4, 224–237).

Ma, W. W. K., & Yuen, A. H. K. (2011). Understanding online knowledge sharing: An interpersonal relationship perspective. Computers & Education, 56 (1), 210–219.

Madden, M., & Zickuhr, K. (2011). 65% of online adults use social networking sites. Pew Internet & American Life Project, 1 , 14.

Meyer, K. A. (2010). A comparison of web 2.0 tools in a doctoral course. The Internet and Higher Education, 13 (4), 226–232.

Mirela Mabić, D. G. (2014). Facebook as a learning tool. Igarss, 2014 (1), 1–5. https://doi.org/10.1007/s13398-014-0173-7.2 .

Mooi, E., & Sarstedt, M. (2011). A concise guide to market research: The process, data, and methods using IBM SPSS statistics . Springeringer. https://doi.org/10.1007/978-3-642-12541-6 .

Moqbel, M., Nevo, S., & Kock, N. (2013). Organizational members’ use of social networking sites and job performance. Information Technology & People, 26 (3), 240–264. https://doi.org/10.1108/ITP-10-2012-0110 .

Moran, M., Seaman, J., & Tinti-Kane, H. (2011). Teaching, learning, and sharing: How Today’s higher education faculty use social media (pp. 1–16). Babson survey research group, (April. https://doi.org/10.1016/j.chb.2013.06.015 .

Nasir, J. A., & Khan, N. A. (2018). Faculty member usage of social media and mobile devices in higher education institution. International Journal of Advance and Innovative Research, 6 (1), 17–25.

Nasir, J. A., Khatoon, A., & Bharadwaj, S. (2018). Social media users in India: A futuristic approach. International Journal of Research and Analytical Reviews, 5 (4), 762–765 Retrieved from http://ijrar.com/ .

Nihalani, P. K., & Mayrath, M. C. (2010). Statistics I. Findings from using an iPhone app in a higher education course. In White Paper .

Norusis, M. (2011). IBM SPSS statistics 20 brief guide (pp. 1–170). IBM Corporation Retrieved from http://www.ibm.com/support .

Novak, E., Razzouk, R., & Johnson, T. E. (2012). The educational use of social annotation tools in higher education: A literature review. The Internet and Higher Education, 15 (1), 39–49.

Nunnally, J. C., & Bernstein, I. H. (1994). Psychological theory .

Pineda-Báez, C., José-Javier, B. A., Rubiano-Bello, Á., Pava-García, N., Suárez-García, R., & Cruz-Becerra, F. (2014). Student engagement and academic performance in the Colombian University context. RELIEVE-Revista Electrónica de Investigación y Evaluación Educativa, 20 (2), 1–19.

Raykov, T., & Marcoulides, G. A. (2000). A First Course in Structural Equation Modeling .

Redecker, C., Ala-Mutka, K., & Punie, Y. (2010). Learning 2.0-the impact of social media on learning in Europe. Policy brief. JRC scientific and technical report. EUR JRC56958 EN, Available from http://bit.ly/cljlpq . Accessed 6 Feb 2011.

Reuben, B. R. (2008). The use of social Media in Higher Education for marketing and communications : A guide for professionals in higher education (Vol. 5) Retrieved from httpdoteduguru comwpcontentuploads200808socialmediainhighereducation pdf)). https://doi.org/10.1108/S2044-9968(2012)0000005018 .

Book   Google Scholar  

Reyes, M. R., Brackett, M. A., Rivers, S. E., White, M., & Salovey, P. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104 (3), 700–712. https://doi.org/10.1037/a0027268 .

Richardson, J., & Lenarcic, J. (2008). Text Messaging as a Catalyst for Mobile Student Administration: The “Trigger” Experience. International Journal of Emerging Technologies & Society, 6 (2), 140–155.

Roblyer, M. D., McDaniel, M., Webb, M., Herman, J., & Witty, J. V. (2010). Findings on Facebook in higher education: A comparison of college faculty and student uses and perceptions of social networking sites. The Internet and Higher Education, 13 (3), 134–140.

Rock, M. L., & Thead, B. K. (2007). The effects of fading a strategic self-monitoring intervention on students’ academic engagement, accuracy, and productivity. Journal of Behavioral Education, 16 (4), 389–412. https://doi.org/10.1007/s10864-007-9049-7 .

Rodriguez, J. E. (2011). Social media use in higher education : Key areas to consider for educators. MERLOT Journal of Online Learning and Teaching, 7 (4), 539–550 https://doi.org/ISSN1558-9528 .

Rutherford, C. (2010). Using online social media to support Preservice student engagement. MERLOT Journal of Online Learning and Teaching, 6 (4), 703–711 Retrieved from http://jolt.merlot.org/vol6no4/rutherford_1210.pdf .

Schumacker, R. E., & Lomax, R. G. (2010). A Beginner’s Guide to structural equation modeling (3rd ed.). New York: Taylor & Francis Group.

Selwyn, N. (2012). Making sense of young people, education and digital technology: The role of sociological theory. Oxford Review of Education, 38 (1), 81–96.

Shih, Y. E. (2007). Setting the new standard with mobile computing in online learning. The International Review of Research in Open and Distributed Learning, 8 (2), 1–16.

Skinner, E. A., & Belmont, M. J. (1993). Motivation in the classroom: Reciprocal effects of teacher behavior and student engagement across the school year. Journal of educational psychology, 85 (4), 571.

Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5). Boston: Pearson.

Voorn, R. J., & Kommers, P. A. (2013). Social media and higher education: Introversion and collaborative learning from the student’s perspective. International Journal of Social Media and Interactive Learning Environments, 1 (1), 59–73.

Wankel, C. (2009). Management education using social media. Organization Management Journal, 6 (4), 251–262.

Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of Enterprise Information Management, 28 (3), 443–488.

Zhu, C. (2012). Student satisfaction, performance, and knowledge construction in online collaborative learning. Journal of Educational Technology & Society, 15 (1), 127–136.

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Jamal Abdul Nasir Ansari: The first author of this manuscript has performed all sorts of necessary works like the collection of data from respondents, administration of the questionnaire. Collection of information from the respondents was quite challenging. The author faced a lot of difficulties while collecting data. The main contribution of the author in this manuscript is that the entire work, like data analysis and its interpretation performed by him. Additionally, the author has tried to explore and usefulness of social media and its applicability in transferring the course contents. Nawab Ali Khan: The second author of this manuscript has checked all types of grammatical issues, and necessary corrections wherever required. The author(s) read and approved the final manuscript.

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Ansari, J.A.N., Khan, N.A. Exploring the role of social media in collaborative learning the new domain of learning. Smart Learn. Environ. 7 , 9 (2020). https://doi.org/10.1186/s40561-020-00118-7

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