social media as a new market research paper

Social Media Marketing: A Literature Review on Consumer Products

Proceedings of the International Conference on Business & Information (ICBI) 2020

15 Pages Posted: 10 Jun 2021

A Siriwardana

University of Kelaniya

Date Written: November 19, 2020

Social media is used by billions of people around the world and has fast become one of the defining technologies of our time. Social media allows people to freely interact with others and offers multiple ways for marketers to reach and engage with consumers. Due to its dynamic and emergent nature, the effectiveness of social media as a marketing communication channel has presented many challenges for marketers. It is considered to be different to traditional marketing channels. Many organizations are investing in their social media presence because they appreciate the need to engage in existing social media conversations in order to build their consumer brand. Social Medias are increasingly replacing traditional media, and more consumers are using them as a source of information about products, services and brands. The purpose of this paper is to focus on where to believe the future of social media lie when considering consumer products. The Paper followed a deductive approach and this paper attempts to review current scholarly on social media marketing literature and research, including its beginnings, current usage, benefits and downsides, and best practices. Further examinations to uncover the vital job of social media, inside a digitalized business period in promoting and branding consumer products. As a result of the comprehensive analysis, it undoubtedly displays that social media is a significant power in the present marketing scene.

Keywords: Consumer Products, Customer Engagement, Digitalization, Social Media

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A Siriwardana (Contact Author)

University of kelaniya ( email ).

Kelaniya Sri Lanka Kelaniya, Western 11600 Sri Lanka

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Information Systems: Behavioral & Social Methods eJournal

Social media marketing strategy: definition, conceptualization, taxonomy, validation, and future agenda

• Conceptual/Theoretical Paper
• Open access
• Published: 10 June 2020
• Volume 49 , pages 51–70, ( 2021 )

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• Fangfang Li   ORCID: orcid.org/0000-0002-4883-1730 1 ,
• Jorma Larimo 1 &
• Leonidas C. Leonidou 2  

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Although social media use is gaining increasing importance as a component of firms’ portfolio of strategies, scant research has systematically consolidated and extended knowledge on social media marketing strategies (SMMSs). To fill this research gap, we first define SMMS, using social media and marketing strategy dimensions. This is followed by a conceptualization of the developmental process of SMMSs, which comprises four major components, namely drivers, inputs, throughputs, and outputs. Next, we propose a taxonomy that classifies SMMSs into four types according to their strategic maturity level: social commerce strategy, social content strategy, social monitoring strategy, and social CRM strategy. We subsequently validate this taxonomy of SMMSs using information derived from prior empirical studies, as well with data collected from in-depth interviews and a quantitive survey among social media marketing managers. Finally, we suggest fruitful directions for future research based on input received from scholars specializing in the field.

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Introduction

The past decade has witnessed the development of complex, multifarious, and intensified interactions between firms and their customers through social media usage. On the one hand, firms are taking advantage of social media platforms to expand geographic reach to buyers (Gao et al. 2018 ), bolster brand evaluations (Naylor et al. 2012 ), and build closer connections with customers (Rapp et al. 2013 ). On the other hand, customers are increasingly empowered by social media and taking control of the marketing communication process, and they are becoming creators, collaborators, and commentators of messages (Hamilton et al. 2016 ). As the role of social media has gradually evolved from a single marketing tool to that of a marketing intelligence source (in which firms can observe, analyze, and predict customer behaviors), it has become increasingly imperative for marketers to strategically use and leverage social media to achieve competitive advantage and superior performance (Lamberton and Stephen 2016 ).

Despite widespread understanding among marketers of the need to engage customers on social media platforms, relatively few firms have properly strategized their social media appearance and involvement (Choi and Thoeni 2016 ; Griffiths and Mclean 2015 ). Rather, for most companies, the ongoing challenge is not to initiate social media campaigns, but to combine social media with their marketing strategy to engage customers in order to build valuable and long-term relationships with them (Lamberton and Stephen 2016 ; Schultz and Peltier 2013 ). However, despite the vast opportunities social media offer to companies, there is no clear definition or comprehensive framework to guide the integration of social media with marketing strategies, to gain a rigorous understanding of the nature and role of social media marketing strategies (SMMSs) (Effing and Spil 2016 ).

Although some reviews focusing on the social media phenomenon are available (e.g., Lamberton and Stephen 2016 ; Salo 2017 ), to date, an integrative evaluation effort focusing on the strategic marketing perspective of social media is missing. This is partly because the social media literature largely derives elements from widely disparate fields, such as marketing, management, consumer psychology, and computer science (Aral et al. 2013 ). Moreover, research on SMMSs mainly covers very specific, isolated, and scattered aspects, which creates confusion and limits understanding of the subject (Lamberton and Stephen 2016 ). Furthermore, research deals only tangentially with a conceptualization, operationalization, and categorization of SMMSs, which limits theory advancement and practice development (Tafesse and Wien 2018 ).

To address these problems, and also to respond to repeated pleas from scholars in the field (e.g., Aral et al. 2013 ; Guesalaga 2016 ; Moorman and Day 2016 ; Schultz and Peltier 2013 to identify appropriate strategies to leverage social media in today’s changing marketing landscape, we aim to systematically consolidate and extend the knowledge accumulated from previous research on SMMSs. Specifically, our objectives are fivefold: (1) to clearly define SMMS by blending issues derived from the social media and marketing strategy literature streams; (2) to conceptualize the process of developing SMMSs and provide a theoretical understanding of its constituent parts; (3) to provide a taxonomy of SMMSs according to their level of strategic maturity; (4) to validate the practical value of this taxonomy using information derived from previous empirical studies, as well as from primary data collection among social media marketing managers; and (5) to develop an agenda for promising areas of future research on the subject.

Our study makes three major contributions to the social media marketing literature. First, it offers a definition and a conceptualization of SMMS that help alleviate definitional deficiency and increase conceptual clarity on the subject. By focusing on the role of social connectedness and interactions in resource integration, we stress the importance of transforming social media interactions and networks into marketing resources to help achieve specific strategic goals for the firm. In this regard, we provide theoretical justification of social media from a strategic marketing perspective. Second, using customer engagement as an overarching theory, we develop a model conceptualizing the SMMS developmental process. Through an analysis of each component of this process, we emphasize the role of insights from both firms and customers to better understand the dynamics of SMMS formulation. We also suggest certain theories to specifically explain the particular role played by each of these components in developing sound SMMSs. Third, we propose a taxonomy of SMMSs based on their level of strategic maturity that can serve as the basis for developing specific marketing strategy concepts and measurement scales within a social media context. We also expect this taxonomy to provide social media marketing practitioners with fruitful insights on why to select and how to use a particular SMMS in order to achieve superior marketing results.

Defining SMMS

Although researchers have often used the term “social media marketing strategy” in their studies (e.g., Choi and Thoeni 2016 ; Kumar et al. 2013 ; Zhang et al. 2017 ), they have yet to propose a clear definition. Despite the introduction of several close terms in the past, including “social media strategy” (Aral et al. 2013 ; Effing and Spil 2016 ), “online marketing strategy” (Micu et al. 2017 ), and “strategic social media marketing” (Felix et al. 2017 ), these either fail to take into consideration the different functions/features of social media or neglect key marketing strategy issues. What is therefore required is an all-encompassing definition of SMMS that will capture two fundamental elements—namely, social media and marketing strategy. Table 1 draws a comparison between social media and marketing strategy on five dimensions (i.e., core, orientation, resource, purpose, and premise) and presents the resulting profile of SMMS.

• Social media

In a marketing context, social media are considered platforms on which people build networks and share information and/or sentiments (Kaplan and Haenlein 2010 ). With their distinctive nature of being “dynamic, interconnected, egalitarian, and interactive organisms” (Peters et al. 2013 , p. 281), social media have generated three fundamental shifts in the marketplace. First, social media enable firms and customers to connect in ways that were not possible in the past. Such connectedness is empowered by various platforms, such as social networking sites (e.g., Facebook), microblogging sites (e.g., Twitter), and content communities (e.g., YouTube), that allow social networks to build from shared interests and values (Kaplan and Haenlein 2010 ). In this regard, “social connectedness” has also been termed as “social ties” (e.g., Muller and Peres 2019 ; Quinton and Wilson 2016 ), and the strength and span of these ties determine whether they are strong or weak (Granovetter 1973 ). Prior studies have shown that tie strength is an important determinant of customer referral behaviors (e.g., Verlegh et al. 2013 ).

Second, social media have transformed the way firms and customers interact and influence each other. Social interaction involves “actions,” whether through communications or passive observations, that influence others’ choices and consumption behaviors (Chen et al. 2011 ). Nair et al. ( 2010 ) labeled such social interactions as “word-of-mouth (WOM) effect” or “contagion effects.” Muller and Peres ( 2019 ) argue that social interactions rely strongly on the social network structure and provide firms with measurable value (also referred to as “social equity”). In social media studies, researchers have long recognized the importance of social influence in affecting consumer decisions, and recent studies have shown that people’s connection patterns and the strength of social ties can signify the intensity of social interactions (e.g., Aral and Walker 2014 ; Katona et al. 2011 ).

Third, the proliferation of social media data has made it increasingly possible for companies to better manage customer relationships and enhance decision making in business (Libai et al. 2010 ). Social media data, together with other digital data, are widely characterized by the 3Vs (i.e., volume, variety, and velocity), which refer to the vast quantity of data, various sources of data, and expansive real-time data (Alharthi et al. 2017 ). A huge amount of social media data derived from different venues (e.g., social networks, blogs, forums) and in various formats (e.g., text, video, image) can now be easily extracted and usefully exploited with the aid of modern information technologies (Moe and Schweidel 2017 ). Thus, social media data can serve as an important source of customer analysis, market research, and crowdsourcing of new ideas, while capturing and creating value through social media data represents the development of a new strategic resource that can improve marketing outcomes (Gnizy 2019 ).

• Marketing strategy

According to Varadarajan ( 2010 ), a marketing strategy consists of an integrated set of decisions that helps the firm make critical choices regarding marketing activities in selected markets and segments, with the aim to create, communicate, and deliver value to customers in exchange for accomplishing its specific financial, market, and other objectives. According to the resource-based view of the firm (Barney 1991 ), organizational resources (e.g., financial, human, physical, informational, relational) help firms enhance their marketing strategies, achieve sustainable competitive advantage, and gain better performance. These resources can be either tangible or intangible and can be transformed into higher-order resources (i.e., competencies and capabilities), enabling the delivery of superior value to targeted buyers (Hunt and Morgan 1995 ; Teece and Pisano 1994 ).

Different marketing strategies can be arranged on a continuum, on which transaction marketing strategy and relationship marketing strategy represent its two ends, while in between are various mixed marketing strategies (Grönroos 1991 ). Webster ( 1992 ) notes that long-standing customer relationships should be at the core of marketing strategy, because customer interaction and engagement can be developed into valuable relational resources (Hunt et al. 2006 ). Morgan and Hunt ( 1999 ) also claim that firms capitalizing on long-term and trustworthy customer relationships can help design value-enhancing marketing strategies that will subsequently generate competitive advantages and lead to superior performance.

From a strategic marketing perspective, social media interaction entails a process that allows not only firms, but also customers to exchange resources. For example, Hollebeek et al. ( 2019 ) assert that customers can devote operant (e.g., knowledge) and operand (e.g., equipment) resources while interacting with firms. Importantly, Gummesson and Mele ( 2010 ) argue that interactions occur not simply in dyads, but also between multiple actors within a network, underscoring the critical role of network interaction in resource integration. Notably, customer-to-customer interactions are also essential, especially for the higher level of engagement behaviors (Fehrer et al. 2018 ).

Thus, social media interconnectedness and interactions (i.e., between firm–customer and between customer–customer) can be considered strategic resources, which can be further converted into marketing capabilities (Morgan and Hunt 1999 ). A case in point is social customer relationship management (CRM) capabilities, in which the firm cultivates the competency to use information generated from social media interactions to identify and develop loyal customers (Trainor et al. 2014 ). With the expanding role of social media from a single communication tool to one of gaining customer and market knowledge, marketers can strategically develop distinct resources from social media based on extant organizational resources and capabilities.

Drawing on the previous argumentation, we define SMMS as an organization’s integrated pattern of activities that, based on a careful assessment of customers’ motivations for brand-related social media use and the undertaking of deliberate engagement initiatives, transform social media connectedness (networks) and interactions (influences) into valuable strategic means to achieve desirable marketing outcomes. This definition is parsimonious because it captures the uniqueness of the social media phenomenon, takes into consideration the fundamental premises of marketing strategy, and clearly defines the scope of activities pertaining to SMMS.

Although the underlying roots of traditional marketing strategy and SMMS are similar, the two strategies have three distinctive differences: (1) as opposed to the traditional approach, which pays peripheral attention to the heterogeneity of motivations driving customer engagement, SMMS emphasizes that social media users must be motivated on intellectual, social, cultural, or other grounds to engage with firms (and perhaps more importantly with other customers) (Peters et al. 2013 ; Venkatesan 2017 ); (2) the consequences of SMMS are jointly decided by the firm and its customers (rather than by individual actors’ behaviors), and it is only when the firm and its customers interact and build relationships that social media technological platforms become real resource integrators (Singaraju et al. 2016 ; Stewart and Pavlou 2002 ); and (3) while customer value in traditional marketing strategies is narrowly defined to solely capture purchase behavior through customer lifetime value, in the case of SMMS, this value is expressed through customer engagement, comprising both direct (e.g., customer purchases) and indirect (e.g., product referrals to other customers) contributions to the value of the firm (Kumar and Pansari 2016 ; Venkatesan 2017 ).

Conceptualizing the process of developing SMMSs

The conceptualization of the process of developing SMMSs is anchored on customer engagement theory, which posits that firms need to take deliberate initiatives to motivate and empower customers to maximize their engagement value and yield superior marketing results (Harmeling et al. 2017 ). Kumar et al. ( 2010 ) distinguish between four different dimensions of customer engagement value, namely customer lifetime value, customer referral value, customer influence value, and customer knowledge value. This metric has provided a new approach for customer valuation, which can help marketers to make more effective and efficient strategic decisions that enable long-term value contributions to customers. In a social media context, this customer engagement value enables firms to capitalize on crucial customer resources (i.e., network assets, persuasion capital, knowledge stores, and creativity), of which the leverage can provide firms with a sustainable competitive advantage (Harmeling et al. 2017 ).

Customer engagement theory highlights the importance of understanding customer motivations as a prerequisite for the firm to develop effective SMMSs, because heterogeneous customer motivations resulting from different attitudes and attachments can influence their social media behaviors and inevitably SMMS outcomes (Venkatesan 2017 ). It also stresses the role of inputs from both firm (i.e., social media engagement initiatives) and customers (i.e., social media behaviors), as well as the importance of different degrees of interactivity and interconnectedness in yielding sound marketing outcomes (Harmeling et al. 2017 ). Pansari and Kumar et al. ( 2017 ) argue that firms can benefit from such customer engagement in both tangible (e.g., higher revenues, market share, profits) and intangible (e.g., feedbacks or new ideas that help to product/service development) ways.

Based on consumer engagement theory, we therefore conceive the process of developing an SMMS as consisting of four interlocking parts: (1) drivers , that is, the firm’s social media marketing objectives and the customers’ social media use motivations; (2) inputs , that is, the firm’s social media engagement initiatives and the customers’ social media behaviors; (3) throughputs , that is, the way the firm connects and interacts with customers to exchange resources and satisfy needs; and (4) outputs , that is, the resulting customer engagement outcome. Figure 1 shows this developmental process of SMMS, while Table 2 indicates the specific theoretical underpinnings of each part comprising this process.

A conceptualization of the process of developing social media marketing strategies

Firms’ social media marketing objectives

Though operating in a similar context, SMMSs may differ depending on the firm’s strategic objectives (Varadarajan 2010 ). According to resource dependence theory (Pfeffer and Salancik 1978 ), the firm’s social media marketing objectives can be justified by the need to acquire external resources (which do not exist internally) that will help it accommodate the challenges of environmental contingencies. In a social media context, customers can serve as providers of resources, which can take several forms (Harmeling et al. 2017 ). Felix et al. ( 2017 ) distinguish between proactive and reactive social media marketing objectives, which can differ by the type of market targeted (e.g., B2B vs. B2C) and firm size. While for proactive objectives, firms use social media to increase brand awareness, generate online traffic, and stimulate sales, in the case of reactive objectives, the emphasis is on monitoring and analyzing customer activities.

Customers’ social media use motivations

Social media use motivations refer to various incentives that drive people’s selection and use of specific social media (Muntinga et al. 2011 ). The existence of these motivations is theoretically grounded on uses and gratifications theory (Katz et al. 1973 ), which maintains that consumers are actively and selectively involved in media usage to gratify their psychological and social needs. In a social media context, motivations can range from utilitarian and hedonic purposes (e.g., incentives, entertainment) to relational reasons (e.g., identification, brand connection) (Rohm et al. 2013 ). Muntinga et al. ( 2011 ) also categorize consumer–brand social media interactions as motivated primarily by entertainment, information, remuneration, personal identity, social interaction, and empowerment.

Firms’ social media engagement initiatives

Firms take initiatives to motivate and engage customers so that they can make voluntary contributions in return (Harmeling et al. 2017 ; Pansari and Kumar 2017 ). These firm actions can also be theoretically explained by resource dependence theory (Pfeffer and Salancik 1978 ), which argues that firms need to take initiatives to encourage customers to interact with them, to generate useful autonomous contributions that will alleviate resource shortages. Harmeling et al. ( 2017 ) identify two primary forms of a firm’s marketing initiatives to engage customers using social media: task-based and experiential. While task-based engagement initiatives encourage customer engagement behaviors with structured tasks (e.g., writing a review) and usually take place in the early stages of the firm’s social media marketing efforts, experiential engagement initiatives employ experiential events (e.g., multisensory events) to intrinsically motivate customer engagement and foster emotional attachment. Thus, firm engagement initiatives can be viewed as a continuum, where at one end, the firm uses monetary rewards to engage customers and, at the other end, the firm proactively works to deliver effective experiential incentives to motivate customer engagement.

Customers’ social media behaviors

The use of social media by customers yields different behavioral manifestations, ranging from passive (e.g., observing) to active (e.g., co-creation) (Maslowska et al. 2016 ). These customer social media behaviors can be either positive (e.g., sharing) or negative (e.g., create negative content), depending on customers’ attitudes and information processes during interactions (Dolan et al. 2016 ). Harmeling et al. ( 2017 ) characterize customers with positive behaviors as “pseudo marketers” because they contribute to firms’ marketing functions using their own resources, while those with negative behaviors may turn firm-created “hashtags” into “bashtags.” Drawing on uses and gratifications theory, Muntinga et al. ( 2011 ) also categorize customers’ brand-related behaviors in social media into three groups: consuming (e.g., reading a brand’s posts), contributing (e.g., rating products), and creating (e.g., publishing brand-related content).

Throughputs

Within the context of social media, both social connectedness and social interaction can be explained by social exchange theory, which proposes that social interactions are exchanges through which two parties acquire benefits (Blau 1964 ). Based on this theory, such a social exchange involves a sequence of interactions between firms and customers that are usually interdependent and contingent on others’ actions, with the goal to generate sound relationships (Cropanzano and Mitchell 2005 ). Thus, successful exchanges can advance interpersonal connections (referred to as social exchange relationships) with beneficial effects for the interacting parties (Cropanzano and Mitchell 2005 ).

Social connectedness

Social connectedness indicates the number of ties an individual has on social networks (Goldenberg et al. 2009 ), while Kumar et al. ( 2010 ) define connectedness with additional dimensions, including the number of connections, the strength of the connections, and the location in the network. Social media research suggests that connectedness has a significant impact on social influence. For example, Hinz et al. ( 2011 ) show that the use of “hubs” (highly connected people) in viral marketing campaigns can be eight times more successful than strategies using less connected people. Verlegh et al. ( 2013 ) also examine the impact of tie strength on making referrals in social media and confirm that people tend to interpret ambiguous information received from strong ties positively, but negatively when this information comes from weak ties.

Social interaction

Social interaction within a social media context is quite complex, as it represents multidirectional and interconnected information flows, rather than a pure firm monologue (Hennig-Thurau et al. 2013 ). This is because, on the one hand, social media have empowered customers to be equal actors in firm–customer interactions through sharing, gaming, expressing, and networking, while, on the other hand, customer–customer interactions have emerged as a growing market force, as customers can influence each other with regard to their attitudinal or behavioral changes (Peters et al. 2013 ). Chen et al. ( 2011 ) identify two types of social interactions—namely, opinion- or preference-based interactions (e.g., WOM) and action- or behavior-based interactions (e.g., observational learning)—with each requiring different strategic actions to be taken. Chahine and Malhotra ( 2018 ) also show that two-way (multiway) interaction strategies that allow reciprocity result in higher market reactions and more positive relationships.

• Customer engagement

The outputs are expressed in terms of customer engagement, which reflects the outcome of firm–customer (as well as customer–customer) connectedness and interaction in social media (Harmeling et al. 2017 ). Footnote 1 It is essentially a reflection of “the intensity of an individual’s participation in and connection with an organization’s offerings and/or organizational activities, which either the customer or the firm initiates” (Vivek et al. 2012 , p. 127). The more customers connect and interact with the firm’s activities, the higher is the level of customer engagement created (Kumar and Pansari 2016 ; Malthouse et al. 2013 ) and the higher the customer’s value addition to the firm (Pansari and Kumar 2017 ). Although the theoretical explanation of the notion of customer engagement has attracted a great deal of debate among scholars in the field, research (e.g., Brodie et al. 2011 ; Hollebeek et al. 2019 ; Kumar et al. 2019 ) has also begun adopting the service-dominant (S-D) logic (Vargo and Lusch 2004 ) because of its emphasis on customers’ interactive and value co-creation experiences in market relationships. Following the service-dominant (S-D) logic, Hollebeek et al. ( 2019 ) stress the role of customer resource integration, customer knowledge sharing, and learning as foundational in the customer engagement process, which can subsequently lead to customer individual/interpersonal operant resource development and co-creation.

Despite its pivotal role in social media marketing, extant literature has not yet attained agreement on the specific measurement of customer engagement. For example, Muntinga et al. ( 2011 ) conceptualize customer engagement in social media as comprising three stages: consuming (e.g., following, viewing content), contributing (e.g., rating, commenting), and creating (e.g., user-generated content). Maslowska et al. ( 2016 ) propose three levels of customer engagement behaviors: observing (e.g., reading content), participating (e.g., commenting on a post), and co-creating (e.g., partaking in product development). Moreover, Kumar et al. ( 2010 ) distinguish between transactional (i.e., buying the product) and non-transactional (i.e., sharing, commenting, referring, influencing) behaviors of customer engagement derived from social media connectedness and interactions.

Taxonomy of SMMSs

The distinctive differences among firms engaged in social media marketing with regard to their strategic objectives, organizational resources and capabilities, and focal industries and market structures, imply that there must also be differences in the SMMSs pursued. In this section, we first explain the criteria classifying SMMSs into different groups and then provide an analysis of their content.

Classification criteria of SMMSs

Drawing from the extant literature, we propose three important criteria that can be used to distinguish SMMSs: the nature of the firm’s strategic social media objectives with regard to using social media, the direction of interactions taking place between the firm and the customers, and the level of customer engagement achieved.

Strategic social media objectives refer to the specific organizational goals to be achieved by implementing SMMSs (Choi and Thoeni 2016 ; Felix et al. 2017 ). These can range from transactional to relational-oriented, depending on the strategist’s mental models of business–customer interactions (Rydén et al. 2015 ). Different mental models have a distinctive impact on managers’ social media sense-making, which is responsible for framing the specific role defined by social media in their marketing activities (Rydén et al. 2015 ). Rydén et al. ( 2015 ) identify four types of social media marketing objectives with four different mental models that can guide SMMSs —namely, to promote and sell (i.e., business-to-customers), to connect and collaborate (i.e., business-with-customers), to listen and learn (i.e., business-from-customers), and to empower and engage (i.e., business-for-customers).

The direction of the social media interactions can take three different forms. These include (1) one-way interaction , that is, traditional one-way communication in which the firm disseminates content (e.g., advertising) on social media and customers passively observe and react (Hoffman and Thomas 1996 ); (2) two-way interaction , that is, reciprocal and interactive communication with exchanges on social media, which can be further distinguished into firm-initiated interaction (in which the firm takes the initiative to begin the conversation) and customer participation (by liking, sharing, or commenting on the content) and customer-initiated interaction (in which the customer is the initiator of conversations by inquiring, giving feedback, or even posting negative comments about the firm, while the firm listens and responds to customer voice) (Van Noort and Willemsen 2012 ); and (3) collaborative interaction, that is, the highest level of interaction that builds on frequent and reciprocal activities in which both the firm and the customer have the power to influence each other (Joshi 2009 ).

With regard to the level of customer engagement, as noted previously, this heavily depends on the strength of connections and the intensity of interactions between the firm and the customers in social media, comprising both transactional and non-transactional elements (Kumar et al. 2010 ). Because customer engagement is the result of a dynamic and iterative process, which makes specifying the exact stage from participating to producing rather difficult (Brodie et al. 2011 ), we adopt the approach proposed by various scholars in the field (e.g., Dolan et al. 2016 ; Malthouse et al. 2013 ) to view this as a continuum, ranging from very low levels of engagement (e.g., “liking” a page) to very high levels of engagement (e.g., co-creation).

Types of SMMSs

With these three classificatory criteria, we can identify four distinct SMMSs, representing increasing levels of strategic maturity: social commerce strategy, social content strategy, social monitoring strategy, and social CRM strategy. Footnote 2 Fig.  2 illustrates this taxonomy for SMMSs, Table 3 shows the differences between these four strategies, while Appendix Table 6 provides real company examples using these strategies. In the following, we analyze each of these SMMSs by explaining their nature and characteristics, the particular role played by social media, and the specific organizational capabilities required for their adoption.

Taxonomy of social media marketing strategies

Social commerce strategy

Social commerce strategy refers to the “exchange-related activities that occur in, or are influenced by, an individual’s social network in computer-mediated social environments, whereby the activities correspond to the need recognition, pre-purchase, purchase, and post-purchase stages of a focal exchange” (Yadav et al. 2013 , p. 312). Rydén et al. ( 2015 , p. 6) claim that this way of using social media is not to create conversation and/or engagement; rather, the reasons for “the initial contact and the end purpose are to sell.” Similarly, Malthouse et al. ( 2013 ) argue that social media promotional activities do not actively engage customers because they do not make full use of the interactive role of social media. Thus, social commerce strategy can be considered as the least mature SMMS because it has a mainly transactional nature and is preoccupied with short-term goal-oriented activities (Grönroos 1994 ). It is essentially a one-way communication strategy intended to attract customers in the short run.

In this strategy, social media are claimed to be the new selling tool that has changed the way buyers and sellers interact (Marshall et al. 2012 ). They offer a new opportunity for sellers to obtain customer information and make the initial interaction with the customer more efficient (Rodriguez et al. 2012 ). Meanwhile, firms are also increasingly using social media as promising outlets for promotional/advertising purposes given their global reach (e.g., Dao et al. 2014 ; Zhang and Mao 2016 ), especially to the millennial generation (Confos and Davis 2016 ). However, as firms’ social media activities in this strategy are more transactional-oriented, customers tend to be passive and reactive. Customers contribute transactional value through purchases, but without a higher level of engagement. Therefore, we conclude that, within the context of this strategy, customers exchange their monetary resources (e.g., purchases) with the firm’s promotional offerings.

To better develop this strategy, Guesalaga ( 2016 ) highlights the need to understand the drivers of using social media in the selling process. He further stresses that personal commitment plays a crucial role in using social media as selling tools. Similarly, Järvinen and Taiminen ( 2016 ) urged for an integration of marketing with the sales department in order to gain better insights from social media marketing efforts. The importance of synergistic effects between social media and traditional media (e.g., press mentions, television, in-store promotions) has also been stressed in supporting social commerce activities (e.g., Jayson et al. 2018 ; Kumar et al. 2016 ; Stephen and Galak 2012 ). Thus, selling capabilities are crucial in this strategy, requiring the possession of adequate selling skills and the use of multiple selling channels to synergize social media effects.

Social content strategy

Social content strategy refers to “the creation and distribution of educational and/or compelling content in multiple formats to attract and/or retain customers” (Pulizzi and Barrett 2009 , p. 8). Thus, this type of SMMS aims to create and deliver timely and valuable content based on customer needs, rather than promoting products (Järvinen and Taiminen 2016 ). By attracting audiences with valuable content, the increase in customer engagement may ultimately boost product/service sales (Malthouse et al. 2013 ). Holliman and Rowley ( 2014 , p. 269) also claim that content marketing is a customer-centric strategy and describe the value of content as “being useful, relevant, compelling, and timely.” Therefore, this strategy provides a two-way communication in which firms take the initiative to deliver useful content and customers react positively to this content. The basic premises of this strategy are to create brand awareness and popularity through content virality, stimulate customer interactions, and spread positive WOM (De Vries et al. 2012 ; Swani et al. 2017 ).

Social media in this strategy have been widely used as communication tools for branding and WOM purposes (Holliman and Rowley 2014 ; Libai et al. 2013 ). On the one hand, firms generate content by their own efforts on social media (termed as ‘firm-generated’ or ‘marker-generated’ content) to actively engage consumers. On the other hand, firms encourage customers to generate the content (termed as ‘user-generated’ content) through the power of customer-to-customer interactions, as in the case of exchanging comments and sharing the brand-related content. In this way, firms provide valuable content in exchange for customer-owned resources, such as network assets and persuasion capital, to generate positive WOM and achieve a sustainable trusted brand status.

To pursue a social content strategy, firms build on capabilities focusing on how content is designed and presented (expressed in the form of a social message strategy) and how content is disseminated (expressed in the form of a seeding strategy). Thus, understanding customer engagement motivations and social media interactive characteristics is central to designing valuable content and facilitating customer interactions that would help to stimulate content sharing among customers (Malthouse et al. 2013 ). Designing compelling and valuable content in order to transform passive social media observers into active participants and collaborators is also key capability required by firms adopting this strategy (Holliman and Rowley 2014 ). Empowering customers and letting them speak for the brand is another way to engage customers with brands. Therefore, in this strategy, marketing communication capabilities are important for effective marketing content development and dissemination.

Social monitoring strategy

Social monitoring strategy refers to “a listening and response process through which marketers themselves become engaged” (Barger et al. 2016 , p. 278). In contrast with social content strategy, which is more of a “push” communication approach with content delivered, social monitoring strategy requires the firm’s active involvement in the whole communication process (from content delivery to customer response) (Barger et al. 2016 ). More specifically, social monitoring strategy is not only to observe and analyze the behaviors of customers in social media (Lamberton and Stephen 2016 ), but also to actively search for and respond to customer online needs and complaints (Van Noort and Willemsen 2012 ). A social monitoring strategy is thus characterized by a two-way communication process, in which the initiation comes from customers who comment and behave on social media, while the company takes advantage of customer behavior data to listen, learn, and react to its customers. Thus, the key objective of this strategy is to enhance customer satisfaction and cultivate stronger relationships with customers through ongoing social media listening and responding.

With today’s abundance of attitudinal and behavioral data, firms adopting this strategy use social media platforms as “tools” or “windows” to listen to customer voices and gain important market insights to support their marketing decisions (Moe and Schweidel 2017 ). Moreover, Carlson et al. ( 2018 ) argue that firms can take advantage of social media data to identify innovation opportunities and facilitate the innovation process. Hence, social media monitoring enables firms to assess consumers’ reactions, evaluate the prosperity of social media marketing initiatives, and allocate resources to different types of conversations and customer groups (Homburg et al. 2015 ). In other words, customers in this strategy are expected to be active in social media interactions, providing instantaneous and real-time feedback. This has in a way helped product development and experience improvements with resource inputs from customers’ knowledge stores.

Social monitoring strategy emphasizes the importance of carefully listening and responding to social media activities to have a better understanding of customer needs, gain critical market insights, and build stronger customer relationships (e.g., Timoshenko and Hauser 2019 ). It therefore requires firms to be actively involved in the whole communication process with customers, as customer engagement is not dependent on rewards, but is developed through the ongoing reciprocity between the firm and its customers (Barger et al. 2016 ). Thus, organizational capabilities, such as marketing sensing through effective information acquisition, interpretation and responding, are essential for the successful implementation of this strategy. More specifically, monitoring and text analysis techniques are needed to gather and capture social media data rapidly (Schweidel and Moe 2014 ). Noting the damage caused by electronic negative word of mouth (e-NWOM) on social media, firms adopting this strategy also require special capabilities to appropriately respond to customer online complaints and requests (Kim et al. 2016 ).

Social CRM strategy

Among the four SMMSs identified, social CRM strategy is characterized by the highest degree of strategic maturity, because it reflects “a philosophy and a business strategy supported by a technology platform, business rules, processes, and social characteristics, designed to engage the customer in a collaborative conversation in order to provide mutually beneficial value in a trusted and transparent business environment” (Greenberg 2009 , p. 34). The concept of social CRM is designed to combine the benefits derived from both the social media dimension (e.g., customer engagement) and the CRM dimension (e.g., customer retention) (Malthouse et al. 2013 ). In contrast with the traditional CRM approach, which assumes that customers are passive and only contribute to customer life value, social CRM strategy emphasizes the active role of customers who are empowered by social media and can make a contribution to multiple forms of value (Kumar et al. 2010 ). In brief, a social CRM strategy is a form of collaborative interaction, including firm–customer, inter-organizational, and inter-customer interactions, that are intended to engage and empower customers, so as to build mutually beneficial relationships with the firm and lead to superior performance.

Social media have become powerful enablers of CRM (Choudhury and Harrigan 2014 ). For example, Charoensukmongkol and Sasatanun ( 2017 ) argue that the integration of social media and CRM provides a possibility for firms to segment their customers based on similar characteristics, and can customize marketing offerings to the specific preferences of individual customers. With social CRM strategy, firms can enhance the likelihood of customer engagement through one-to-one social media interactions. Customers at this stage are collaborative and interactive in value creation, such as voluntarily providing innovative ideas and collaborating with brands (Jaakkola and Alexander 2014 ). Hence, besides resource like network assets, persuasion capital, and knowledge stores, engaged customers also contribute their creativity resource for value co-creation.

Social CRM capability is “a firm-level capability and refers to a firm’s competency in generating, integrating, and responding to information obtained from customer interactions that are facilitated by social media technologies” (Trainor et al. 2014 , p. 271). Therefore, firms should be extremely creative to combine social media data with its CRM system, as well as to link the massive social media data on customer activities to other data sources (e.g., customer service records) to generate better customer-learning and innovation opportunities (Choudhury and Harrigan 2014 ; Moe and Schweidel 2017 ). Social CRM strategy also emphasizes the significance of reciprocal information sharing and collaborations that are supported by the firm’s culture and commitment, operational resources, and cross-functional cooperation (Malthouse et al. 2013 ; Schultz and Peltier 2013 ). To sum up, social CRM capabilities, organizational learning capabilities connected with relationship management and innovation are essential prerequisites to building an effective social CRM strategy.

Validation of proposed SMMSs

Using the previously developed classification of SMMSs (i.e., social commerce strategy, social content strategy, social monitoring strategy, and social CRM strategy) as a basis, we reviewed the pertinent literature to collate useful knowledge supporting the content of each of these strategies. Table 4 provides a summary of the key empirical insights derived from the extant studies reviewed, together with resulting managerial lessons.

To validate the practical usefulness of our proposed classificatory framework of SMMSs, we first conducted a series of in-depth interviews with 15 social media marketing practitioners, who had their own firm/brand accounts on social media platforms, at least one year of social media marketing experience, and at least three years’ experience in their current organization (see Web Appendix 1 ). Interviewees represented companies located in China (8 companies), Finland (5 companies), and Sweden (2 companies) and involved in a variety of industries (e.g., digital tech, tourism, food, sport). All interviews were based on a specially designed guide (which was sent to participants in advance to prepare them for the interview) and were audiotaped and subsequently transcribed verbatim (see Web Appendix 2 ).

The main findings of this qualitative study are the following: (1) social media are mainly used as a key marketing channel to achieve business objectives, which, however, differentiates in terms of product-market type, organization size, and managerial mindset; (2) distinct differences exist across organizations in terms of their social media initiatives to deliver content, generate reactions, and develop social CRM; (3) there are marked variations in customer engagement levels across participant firms, resulting from the adoption of different SMMSs; (4) the firm’s propensity to use a specific SMMSs is enhanced by infrastructures, systems, and technologies that help to actively search, access, and integrate data from different sources, as well as facilitate the sharing and coordination of activities with customers; and (5) the adoption of a specific SMMS does not follow a sequential pattern in terms of strategic maturity development, but rather, depends on the firm’s strategic objectives, its willingness to commit the required resources, and the deployment of appropriate organizational capabilities.

To further confirm the existence of differences in profile characteristics among the four types of SMMSs, we conducted an electronic survey among a sample of 52 U.S. social media marketing managers who were randomly selected. For this purpose, we designed a structured questionnaire incorporating the key parameters related to SMMSs, namely firms’ strategic objectives, firms’ engagement initiatives, customers’ social media behaviors, social media resources and capabilities required, direction of interactions, and customer engagement levels (see Web Appendix 3 ).

Specifically, we found that: (1) each of the four SMMSs emphasize different types of strategic objectives, ranging from promoting and selling, in the case of social commerce strategy, to empowering and engaging in social CRM strategy; (2) experiential engagement initiatives geared to customer engagement were more evident at the advanced level, as opposed to the lower level strategies; (3) passive customer social media behaviors were more characteristic of the social commerce strategy, while more active customer behaviors were observed in the case of social CRM strategy; (4) the more advanced the maturity of the SMMS employed, the higher the level customer engagement, as well as the higher requirements in terms of organizational resources and specialized capabilities; and (5) one-way interaction was associated more with social commerce strategy, two-way interaction was more evident in the social content strategy and the social monitoring strategy, and collaborative interaction was a dominant feature in the social CRM strategy (see Web Appendix 4 ).

Future research directions

While the extant research offers insightful information and increased knowledge on SMMSs, there is still plenty of room to expand this field of research with other issues, especially given the rapidly changing developments in social media marketing practice. To gain a more accurate picture about the future of research on the subject, we sought the opinions of academic experts in the field through an electronically conducted survey among authors of academic journal articles written on the subject. We specifically asked them: (1) to suggest the three most important areas that research on SMMSs should focus on in the future; (2) within each of the areas suggested, to indicate three specific topics that need to be addressed more; and (3) within each topic, to illustrate analytical issues that warrant particular attention (see Web Appendix 5 ). Altogether, we received input from 43 social media marketing scholars who suggested 6 broad areas, 13 specific topics, and 82 focal issues for future research, which are presented in Table 5 .

Among the research issues proposed, finding appropriate metrics to measure performance in SMMSs seems to be an area to which top priority should be given. This is because performance is the ultimate outcome of these strategies, for which there is still little understanding due to the idiosyncratic nature of social media as a marketing tool (e.g., Beckers et al. 2017 ; Trainor et al. 2014 ). In particular, it is important to shed light on both short-term and long-term performance, as well as its effectiveness, efficiency, and adaptiveness aspects (e.g., Barger et al. 2016 ). Another key priority area stressed by experts in the field involves integrating to a greater extent various strategic issues regarding each of the marketing-mix elements in a social media context. This would help achieve better coordination between traditional and online marketing tools (e.g., Kolsarici and Vakratsas 2018 ; Kumar et al. 2017 ).

Respondents in our academic survey also stressed the evolutionary nature of knowledge with regard to each of the four SMMSs and proposed multiple issues for each of them. Particular attention should be paid to how inputs from customers and firms are interrelated in each of these strategies, taking into consideration the central role played by customer engagement behaviors and firm initiatives (e.g., Sheng 2019 ). Respondents also pinpointed the need for more emphasis on social CRM strategy (which is relatively under-researched), while there should also be a closer assessment of new developments in both marketing (e.g., concepts and tools) and social media (e.g., technologies and platforms) that can lead to the emergence of new types of SMMSs (e.g., Ahani et al. 2017 ; Choudhury and Harrigan 2014 ).

Respondents also noted that up to now the preparatory phase for designing SMMSs has been overlooked, and that therefore there is a need to shed more light on this because of its decisive role in achieving positive results. For example, issues relating to market/competitor analysis, macro-environmental scanning, and target marketing should be carefully studied in conjunction with formulating sound SMMSs, to better exploit opportunities and neutralize threats in a social media context (e.g., De Vries et al. 2017 ). By contrast, our survey among scholars in the field stressed the crucial nature of issues relating to SMMS implementation and control, which are of equal, or even greater, importance than those of strategy formulation (e.g., Järvinen and Taiminen 2016 ). The academics also indicated that, by their very nature, social media transcend national boundaries, thus leaving plenty of room to investigate the international ramifications of SMMSs, using cross-cultural research (e.g., Johnston et al. 2018 ).

Implications and conclusions

Theoretical implications.

Given the limited research on SMMSs, this study has several important theoretical implications. First, we are taking a step in this new theoretical direction by providing a workable definition and conceptualization of SMMS that combines both social media and marketing strategy dimensions. The study complements and extends previous research (e.g., Harmeling et al. 2017 ; Singaraju et al. 2016 ) that emphasized the value of social media as resource integrator in exchanging customer-owned resources, which can provide researchers with new angles to address the issue of integrating social media with marketing strategy. Such integrative efforts can have a meaningful long-term impact on building a new theory (or theories) of social media marketing. They also point to a deeper theoretical understanding of the roles played by resource identification, utilization, and reconfiguration in a SMMS context.

We have also extended the idea of “social interaction” and “social connectedness” in a social media context, which is critical because the power of a customer enabled by social media connections and interactions is of paramount importance in explaining the significance of SMMSs (Hennig-Thurau et al. 2013 ). More importantly, our study suggests that firms should take the initiative to motivate and engage customers, which will lead to wider and more extensive interactions. In particular, we show that a firm can leverage its social media usage through the use of different engagement initiatives to enforce customer interactivity and interconnectedness. Such enquiries can provide useful theoretical insights into the strategic marketing role played by social media in today’s highly digitalized and globalized world.

We are also furthering the customer engagement literature by proposing an SMMS developmental process. As firm–customer relationships evolve in a social media era, it is critical to identify those factors that have an impact on customer engagement. Although prior studies (e.g., Harmeling et al. 2017 ; Pansari and Kumar 2017 ) have demonstrated the engagement value contributed by customers and the need for engagement initiatives taken by firms, we are extending this idea to provide a more holistic view by highlighting the role of insights from both firms and customers to better understand the dynamics of SMMS formulation. We also suggest certain theories to specifically explain the role played by each of the components of the process in developing sound SMMSs. We capture the unique characteristics of social media by suggesting that these networks and interactions are tightly interrelated with the outcome of SMMS, which is customer engagement. Our proposed SMMS developmental process may therefore provide critical input for new studies focusing on customer engagement research.

 Finally, we build on various criteria to distinguish among four SMMSs, each representing a different level of strategic maturity. We show that a SMMS is not homogeneous, but needs to be understood in a wider, more nuanced way, as having different strategies relying on different goals and deriving insights from firms and their customers, ultimately leading to different customer engagement levels. In this regard, the identification of the key SMMSs stemming from our analysis can serve as the basis for developing specific marketing strategy constructs and scales within a social media context. We also indicate that different SMMSs can be implemented and yield superior competitive advantage only when the firm is in a position to devote to it the right amount and type of resources and capabilities (e.g., Gao et al. 2018 ; Kumar and Pansari 2016 ).

Managerial implications

Our study also has serious implications for managers. First, our analysis revealed that the ever-changing digital landscape on a global scale calls for a reassessment of the ways to strategically manage brands and customers in a social media context. This requires companies to understand the different goals for using social media and to develop their strategies accordingly. As a starting point, firms could explore customer motivations for using social media and effectively deploy the necessary resources to accommodate these motivations. They should also think carefully about how to engage customers when implementing their marketing strategies, because social media become resource integrators only when customers interact with and provide information on them (Singaraju et al. 2016 ).

Managers need to set objectives at the outset to guide the effective development, implementation, and control of SMMSs. Our study suggests four key SMMSs achieving different business goals. For example, the goal of social commerce strategy is to attract customers with transactional interests, that of social content strategy and social monitoring strategy is to deliver valuable content and service to customers, and that of social CRM strategy is to build mutually beneficial customer relationships by integrating social media data with current organizational processes. Unfortunately, many companies, especially smaller ones, tend to create their social media presence for a single purpose only: to disseminate massive commercial information on their social media web pages in the hope of attracting customers, even though these customers may find commercially intensive content annoying.

This study also suggests that social media investments should focus on the integration of social media platforms with internal company systems to build special social media capabilities (i.e., creating, combining, and reacting to information obtained from customer interactions on social media). Such capabilities are vital in developing a sustainable competitive advantage, superior market and financial performance. However, to achieve this, firms must have the right organizational structural and cultural transformation, as well as substantial management commitment and continuous investment.

Lastly, social media have become powerful tools for CRM, helping to transform it from traditional one-way interaction to collaborative interaction. This implies that customer engagement means not only encouraging customer engagement on social media, but also proactively learning from and collaborating with customers. As Pansari and Kumar et al. ( 2017 ) indicate, customer engagement can contribute both directly (e.g., purchase) and indirectly (e.g., customer knowledge value) to the firm. Therefore, interacting with customers via social media provides tremendous opportunities for firms to learn more about their customers and opens up new possibilities for product/service co-creation.

Conclusions

The exploding use of social media in the past decade has underscored the need for guidance on how to build SMMSs that foster relationships with customers, advance customer engagement, and increase marketing performance. However, a comprehensive definition, conceptualization, and framework to guide the analysis and development of SMMSs are lacking. This can be attributed to the recent introduction of social media as a strategic marketing tool, while both academics and practitioners still lack the necessary knowledge on how to convert social media data into actionable strategic marketing tools (Moe and Schweidel 2017 ). This insufficiency also stems from the fact that the adoption of more advanced SMMSs requires the possession of specific organizational capabilities that can be used to leverage social media, with the support of a culture that encourages breaking free from obsolete mindsets, emphasizing employee skills with intelligence in data and customer analytical insights, and operational excellence in organizational structure and business processes (Malthouse et al. 2013 ).

Our study takes the first step toward addressing this issue and provides useful guidelines for leveraging social media use in strategic marketing. In particular, we provide a systematic consolidation and extension of the extant pertinent SMMS literature to offer a robust definition, conceptualization, taxonomy, and validation of SMMSs. Specifically, we have amply demonstrated that the mere use of social media alone does not generate customer value, which instead is attained through the generation of connections and interactions between the firm and its customers, as well as among customers themselves. These generated social networks and influences can subsequently be used strategically for resource transformation and exchanges between the interacting parties. Our conceptualization of the SMMS developmental process also suggests that firms first need to recognize customers’ motivations to engage in brand-related social media activities and encourage their voluntary contributions.

Although the four SMMSs identified in our study (i.e., social commerce strategy, social content strategy, social monitoring strategy, and social CRM strategy) denote progressing levels of strategic maturity, their adoption does not follow a sequential pattern. As our validation procedures revealed, this will be determined by the firm’s strategic objectives, resources, and capabilities. Moreover, the success of the various SMMSs will depend on the firm’s ability to identify and leverage customer-owned resources, as in the case of transforming customers from passive receivers of the firm’s social media offerings to active value contributors. It will also depend on the firm’s willingness to allocate resources in order to foster collaborative conversations, develop appropriate responses, and enhance customer relationships. These will all ultimately help to build a sustainable competitive advantage and enhance business performance.

Although in our conceptualization of the process of developing SMMSs we treat customer engagement as the output of this process, we fully acknowledge that firms’ ultimate objective to engage in social media marketing activities is to improve their market (e.g., customer equity) and financial (e.g., revenues) performance. In fact, extant social media marketing research (e.g., Kumar et al. 2010 ; Kumar and Pansari 2016 ; Harmeling et al. 2017 ) repeatedly stresses the conducive role of customer engagement in ensuring high performance results.

SMMSs are difficult to operationalize by focusing solely on the elements of the marketing mix (i.e., product, price, distribution, and promotion), mainly because many other important parameters are involved in their conceptualization, such as relationship management, market development, and business innovation issues. However, each SMMS seems to have a different marketing mix focus, with social commerce strategy emphasizing advertising and sales, social content strategy emphasizing branding and communication, social monitoring strategy emphasizing service and product development, and social CRM strategy emphasizing customer management and innovation.

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Li, F., Larimo, J. & Leonidou, L.C. Social media marketing strategy: definition, conceptualization, taxonomy, validation, and future agenda. J. of the Acad. Mark. Sci. 49 , 51–70 (2021). https://doi.org/10.1007/s11747-020-00733-3

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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.

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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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EFFECTIVENESS OF SOCIAL MEDIA AS A MARKETING TOOL: AN EMPIRICAL STUDY

International Journal of Marketing, Financial Services & Management Research Vol.1 Issue 11, November 2012, ISSN 2277 3622 Online available at www.indianresearchjournals.com

In an era where technology prevails, entrepreneurs as well as marketers see the need to keep up with the fast pace of change or risk being outdated. Gone are the days when a pure-bricks business model will thrive well in current market scenario. It is practically impossible to design a marketing strategy without considering social networks. Social media had become really important gradient in today’s marketing mix in general and in promotion mix in particular. Adapting some form of marketing online through social media is a key node for all businesses, especially in an industry where trends constantly change such as fashion and handicrafts. The paper carries out empirical research to understand the effectiveness of social media as a marketing tool and an effort has been made to analyze the extent social media helps consumers in buying decision making. In addition strategies have been suggested for maximizing the effectiveness. Various statistical tests have been applied to support the research hypothesis.

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The New Rules of Marketing Across Channels

• Joshua Bowers,
• Denise Linda Parris,
• Qiong Wang,
• Danny McRae,
• Francisco Guzmán,
• Mark Bolino

Strategies for navigating a new kind of communication landscape: the “echoverse.”

The Internet and AI tools are transforming marketing communications within a complex, interactive landscape called the echoverse. While marketing has evolved since the proliferation of the Internet, in the echoverse, a diverse network of human and nonhuman actors — consumers, brands, AI agents, and more — continuously interact, influence, and reshape messages across digital platforms. Traditional one-way and two-way communication models give way to omnidirectional communication. The authors integrated communication theory and theories of marketing communications to create a typology of marketing communication strategies consisting of three established strategies — 1) promotion marketing, 2) relationship marketing, and 3) customer engagement marketing — and their proposed strategy, 4) echoverse marketing. The authors also recommend three strategies for marketers to make the shift from leading messaging to guiding messaging: 1) Enable co-creation and co-ownership, 2) Create directed learning opportunities, and 3) Develop a mindset of continuous learning.

Today, companies must navigate a new kind of communication landscape: the “ echoverse .” This new terrain is defined by a complex web of feedback loops and reverberations that are created by consumers, brands, news media, investors, communities, society, and artificial intelligence (AI) agents. This assemblage of actors continuously interact, influence, and respond to each other across a myriad of digital channels, platforms, and devices, creating a dynamic where messages circulate and echo, being amplified, modified, or dampened by ongoing interactions.

• JB Joshua Bowers is Co-CEO of Pavilion Intelligence, a marketing science consultancy and upcycled timber operation. He has a Ph.D. in Marketing from the University of Oklahoma and is a leader in new product development for enterprise and marketing technology.
• DP Denise Linda Parris is Co-CEO Pavilion Intelligence, a marketing science consultancy and upcycled timber operation. She has been a professional athlete, entrepreneur, and academic with research focused on servant leadership, societal impact, and marketing technology.
• QW Qiong Wang is the Ruby K. Powell Professor of Marketing and Associate Professor of Marketing and Supply Chain at the University of Oklahoma’s Price College of Business. Her research focuses on the processes and boundaries of inter-organizational issues, including the development and management of strategic partnerships, marketing strategies, and supply chain management.
• DM Danny McRae is a technology professional with over 20 years of experience in information architecture.
• FG Francisco Guzmán is Professor of Marketing at the University of North Texas’ G. Brint Ryan College of Business. His research focuses on how brands can drive social transformation.
• MB Mark Bolino is the David L. Boren Professor and the Michael F. Price Chair in International Business at the University of Oklahoma’s Price College of Business. His research focuses on understanding how an organization can inspire its employees to go the extra mile without compromising their personal well-being.

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• DOI: 10.21512/becossjournal.v6i2.11794
• Corpus ID: 270859559

Digital Marketing: A Case Study of Social Media Marketing of Indonesia Real Estate Companies

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32 References

How enterprise architecture leads to organisational benefits.

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Identifying Digital Transformation Paths in the Business Model of SMEs during the COVID-19 Pandemic

Content marketing capability building: a conceptual framework, digital marketing as a strategy to defend msmes in the covid-19 pandemic, going digital the impact of social media marketing on retail website traffic, orders and sales, does digital marketing platforms affect business performance a mini-review approach, social media marketing gains importance after covid-19, digital transformation strategies of trade enterprises: key areas, development and implementation algorithms, integrating social media and digital media as new elements of integrated marketing communication for creating brand equity, related papers.

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Top 10 Digital Marketing Trends For 2024

Stay ahead of the game with the top digital marketing trends for 2024. Discover why having a solid strategy is key to success in the ever-evolving digital landscape.

It’s been a year of considerable disruptions in digital marketing so far.

Right now, the industry is dealing with the integration of generative AI and the impact this is going to have on user behaviour and how people search. Alongside the relentless updates that Google keeps throwing at us.

SEO is changing and the industry is trying to adapt whilst accepting the uncertainty.

But, it’s not all catastrophic, there is a lot of opportunity ahead for those that can evolve to embrace the new.

To help marketers and brands thrive amidst uncertainty, I’ve outlined trends to focus on, guided by strategic insights and Yogi Berra’s timeless wisdom,

“Predictions are hard, especially about the future.” – Yogi Berra

Digital marketers can no doubt relate to Yogi’s sentiment, acknowledging the challenge of what lies ahead.

These, then, are the top 10 digital marketing trends for 2024:

1. Strategy: “If You Don’t Know Where You Are Going, You Might Wind Up Someplace Else.”

Why is “strategy” this year’s top trend instead of the latest technology?

Well, as Yogi once observed, “If you don’t know where you are going, you might wind up someplace else.”

According to Spencer Stuart’s 2024 CMO Tenure Study , the average tenure of chief marketing officers (CMOs) at Fortune 500 companies in 2023 was 4.2 years .

The study also found the average tenure of CMOs at B2B companies was 4.5 years. It was 4.0 years for CMOs at B2C companies. And it was just 3.1 years at the consumer-heavy top 100 advertisers.

So, developing a digital marketing strategy that will generate above-average results within a couple of years is the key to keeping your job as the CMO of a big brand.

And if you don’t master the art and science of creating a digital marketing strategy that generates business outcomes, then you won’t land one of the CMO jobs that turn over each year.

In other words, learning to use the latest technology is necessary, but it won’t get digital marketing leaders and executives where they want to go.

• Read more: What Is A Digital Marketing Strategy? 5 Steps To Create One

2. Generative AI: “Predictions Are Hard, Especially About The Future.”

Yogi also said, “Predictions are hard, especially about the future.” So, it’s tempting to ask generative AI tools to predict their own future.

OpenAI’s ChatGPT 3.5 says:

“AI and machine learning have been transforming digital marketing for years, but 2024 is poised to see these technologies become even more integral. From chatbots and predictive analytics to personalized content and ad targeting, AI will enhance customer experiences and drive efficiency. Brands leveraging AI can expect to see improved ROI and deeper customer insights.”

Google’s Gemini (formerly Bard) says:

“It ain’t science fiction anymore. Artificial intelligence (AI) is taking center stage, from crafting personalized chatbots that convert like crazy to optimizing campaigns with laser precision. Don’t fear the robot takeover, embrace it!”

And Anthropic’s Claude 3 says:

“Artificial intelligence writing assistants like Claude have been making waves, and in 2024 we’ll see these tools become ubiquitous in content marketing. They’ll help scale content creation while maintaining quality.”

But AI can’t see the big picture for your organization. It can’t empathize with people . And it can’t be creative like you. So, AI needs you in the driver’s seat to make it work effectively.

• Read more: Generative AI And SEO Strategy: Getting The Most Out Of Your Tools

3. SEO: “It Ain’t Over Till It’s Over.”

Some pundits think SEO is dead. But as Yogi declared, “It ain’t over till it’s over.”

That’s because SEO pros have the remarkable ability to adapt to constant change or new information. Often, this means adjusting to the latest Google algorithm updates . But this also includes rethinking strategies based on the recent Google API “leak.”

Now, Rand Fishkin and Mike King were the first to report on the leaked documents. Although Google has officially acknowledged that these internal documents are authentic , it has also cautioned against jumping to conclusions based on the leaked files alone.

What should savvy SEO pros do?

Well, I’ve known Fishkin for more than 20 years. And he has the experience, expertise, authoritativeness, and trustworthiness (E-E-A-T) you’ve heard about.

So, I’m going to follow Fishkin’s recommendations, including:

• Hire writers with established reputational authority that Google already associates with quality content.
• Supplement link-building with public relations to increase branded search demand. (I’ll say more on this below.)
• “Think about SEO as being more geographically specific than you think it is even for web search results.”
• Move beyond parsing Google’s public statements and embrace experimentation and testing to uncover what produces results.
• Read more: Google Ranking Systems & Signals 2024

4. Link Building: “Always Go To Other People’s Funerals; Otherwise, They Won’t Go To Yours.”

I spotted this trend a long time ago, and I spoke about it at SES London 2009 in a session titled, “Beyond Linkbait: Getting Authoritative Mentions Online.”

Back then, I said link bait tactics can be effective “if you focus on the underlying quality as well as ingenuity needed to get other websites to link to you.”

I also provided a couple of case studies that showed British SEO professionals how to “approach journalists, bloggers, and other authoritative sources to enhance your company’s online reputation, whether or not you get links.”

But getting authoritative mentions without links didn’t translate. People on the other side of the pond thought I was saying something unintentionally funny like, “Always go to other people’s funerals; otherwise, they won’t go to yours.”

Hopefully, Fishkin’s recommendation will enable a lot more SEO pros to finally understand the underlying wisdom of supplementing link building with public relations .

As he clearly explained at MozCon, “If you get a whole bunch of links in one day and nothing else, guess what? You manipulated the link graph. If you’re really a big brand, people should be talking about you.”

• Read more: Link Building In 2024: What Works, What Doesn’t, And What’s Next?

5. Paid Media: “It’s Déjà Vu All Over Again.”

Everyone knows that Google, Meta, and other paid media are adding AI to their advertising platforms faster than the speed of sound. So, this might be mistaken as background noise.

But I’ve spotted the signal in the noise. Today’s frenzy to provide AI solutions is remarkably like the frenzy to provide programmatic solutions a decade ago. As Yogi said, “It’s déjà vu all over again.”

This means that digital marketers – and their agencies – can quickly refresh their “programmatic” workflow and turn it into “AI” best practices.

For example, Google touted a five-step programmatic workflow five years ago.

It consisted of:

• Organize audience insights.
• Design compelling creative.
• Execute with integrated technology.
• Reach audiences across screens.
• Measure the impact.

Why is today’s process of buying and selling digital media in an automated fashion so similar? Because AI is just fulfilling the early promise of programmatic to engage with consumers in the moments that matter most.

But there’s one significant difference between then and now.

As you’ll read below, it’s the improved ability to integrate your advertising platforms with your analytics platform to measure the impact of campaigns on brand awareness and lead generation .

• Read more: Paid Media Marketing In 2024: 7 Changes Marketers Should Make

6. Analytics: “You Can Observe A Lot By Watching.”

Performance marketers integrated their advertising platforms with their analytics platform more than a decade ago to measure the impact of their campaigns on “conversions.”

But brand marketers rarely focused on their analytics data because “brand awareness” was something they measured when consumers initially saw their display ads or watched their video ads.

A funny thing happened after Google Analytics 4 rolled out last summer. A “Business objectives” collection replaced the “Life cycle” collection of reports and one business objective you can now track is “Raise brand awareness.”

For example, brand marketers can now use traffic acquisition, demographic details, user acquisition, as well as which pages and screens users visit to measure brand awareness in places that are less vulnerable to ad fraud.

Another business objective you can now track is “Generate leads.”

So, digital marketers can measure any user action that’s valuable to their organization, including:

• Scrolling to 90% or more of their blog post.
• Downloading a whitepaper.
• Subscribing to their newsletter.
• Playing at least 50% of a product video.
• Completing a tutorial.
• Submitting a registration form.

And as Yogi noted, “You can observe a lot by watching.”

• Read more: 5 Google Analytics Reports Every PPC Marketer Needs To Know About

7. Content Marketing: “When You Come To A Fork In The Road, Take It.”

In the summer of 2020, the Content Marketing Institute and MarketingProfs fielded their annual survey and found that “Content marketers are resilient. Most have met the challenges of the pandemic head-on.”

In response to the pandemic, B2B and B2C marketers:

• Increased time spent talking with customers.
• Revisited their customer/buyer personas .
• Re-examined the customer journey.
• Changed their targeting/messaging strategy.
• Changed their distribution strategy.
• Adjusted their editorial calendar .
• Put more resources toward social media/online communities.
• Changed their website.
• Changed their products/services.
• Adjusted their key performance indicators (KPIs) .
• Changed their content marketing metrics (e.g., set up new analytics/dashboards).

In other words, many content marketers totally overhauled their process for creating a content marketing plan from stem to stern.

For some, 2020 was the year of quickly adapting their content marketing strategy. For others, it was the year to finally develop one.

According to BrightEdge, content marketers are now “ preparing for a Searchquake ,” a tectonic shift in the content marketing landscape triggered by Google’s Search Generative Experiences (SGE) .

But content marketers now know exactly what to do. As Yogi directed, “When you come to a fork in the road, take it.”

• Read more: The Three Pillars Of Content Marketing Strategy

8. Video Creation: “If You Can’t Imitate Him, Don’t Copy Him.”

I teach an online class at the New Media Academy in Dubai on “Influencer Marketing and AI.” This may seem like an odd combination of topics, but they’re related to another class I teach on “Engaging Audiences through Content.”

I tell my students that creating great content is hard. That’s why marketers start using influencers or AI to create video content that their audience will find valuable and engaging. Then, they learn that there’s more to learn.

For example, AI can create realistic and imaginative scenes from text instructions. But AI can’t be creative like humans. So, the heart of every great video is still innovative, surprising, human-led creativity.

I show them “OpenAI Sora’s first short film – ‘Air Head,’ created by shy kids,” a Toronto-based production company.

Then, I ask them to apply what they have learned by using Synthesia , Runway , or invideo AI to generate a short video for their capstone project.

Invariably, they report that AI video generators can create realistic and imaginative scenes from text instructions but aren’t creative like shy kids.

Or, as Yogi put it, “If you can’t imitate him, don’t copy him.”

• Read more: Video Marketing: An In-Depth Guide For Every Business Owner Today

9. Influencer Marketing: “Nobody Goes There Anymore. It’s Too Crowded.”

The Influencer Marketing Hub says, “Most marketers believe that finding and selecting the best, most relevant influencers to be the most difficult part of influencer marketing.”

That’s ironic because HypeAuditor offers an influencer discovery platform that enables marketers to search through a database of 137.5 million influencers on Instagram, YouTube, TikTok, X (formerly Twitter), and Twitch.

It also enables marketers to apply filters to discover the perfect partners for their brand.

This apparent contradiction reminds me of Yogi’s comment, “Nobody goes there anymore. It’s too crowded.”

But it also indicates that most marketers are looking at influencer identification through the wrong end of the telescope. What should they do instead?

Well, I show the students in my “Influencer Marketing and AI” class how to use SparkToro to get a free report on the audience that searches for “Dubai.”

SparkToro estimates that 446,000 to 654,000 people search for “Dubai” monthly. And it uncovers the websites they visit, the keywords they search for, and their gender demographics.

SparkToro also identifies the sources of influence for this audience, including high-affinity accounts and hidden gems, so marketers can invest in the right ones.

• Read more: How To Collaborate With Local Influencers To Drive Global B2B Content Marketing Success

10. Social Media: “The Future Ain’t What It Used To Be.”

I’m a big believer in “the rule of three.”

So, I wasn’t startled when I received an email from Jennifer Radke inviting me to attend “an exciting webinar focused on a high-level look into using ChatGPT for social media!”

But I was shocked when Katie Delahaye Paine shared a link to new research by Asana’s Work Innovation Lab and Meltwater, which found that “only 28% of marketing professionals have received training on how to use AI tools effectively.”

I was also horrified when I read a column by Mark Ritson in MarketingWeek that argued, “AI’s strength is automating high-volume, short-term marketing activity, which means social media could become a cesspool of synthetic content.”

Hey, I was having lunch with Chris Shipley in 2004 when she coined the term “social media.” So, I remember when social media still had a promising future.

But, as Yogi once declared, “The future ain’t what it used to be.”

So, social media marketing has three options:

• They can get upskilled to use AI tools more effectively.
• They can get reskilled to identify the right influencers.
• They can update their resumes and look for new jobs.
• Read more: 20 Awesome Examples Of Social Media Marketing

Picking Digital Marketing Trends Is Like Playing Moneyball

Some skeptics may question this counter-intuitive lineup of the top 10 digital marketing trends for 2024. Some of my selections seem to throw out conventional wisdom.

I recently watched the movie Moneyball (2011) for a second time. I was reminded that the Oakland Athletics baseball team’s general manager, Billy Beane (Brad Pitt), and assistant general manager, Peter Brand (Jonah Hill), used sabermetrics to analyze players.

This produced an epiphany: Picking digital marketing trends is like playing Moneyball. If you want to win against competitors with bigger budgets, then you need to find strategic insights, critical data, tactical advice, and digital marketing trends that conventional wisdom has overlooked.

And where did I come up with the whimsical idea of matching each trend with one of Yogi’s memorable quotes? Was it inspiration or hallucination?

I recently watched the documentary It Ain’t Over (2022) for the first time. It’s about New York Yankee Hall of Fame catcher Yogi Berra. And it supported Yogi’s claim, “I really didn’t say everything I said.”

But sportswriters kept attributing these Yogi-isms to the catcher because these “distilled bits of wisdom … like good country songs … get to the truth in a hurry,” as Allan Barra, the author of a book on Yogi, has explained.

And that strategic insight produced this year’s update – by a human – as opposed to last year’s top 10 digital marketing trends by ChatGPT.

More resources:

• 5 Key Enterprise SEO And AI Trends For 2024 
• SEO Trends 2024
• PPC Trends 2024

Featured Image: SuPatMaN/Shutterstock

Greg Jarboe is president of SEO-PR, which he co-founded with Jamie O’Donnell in 2003. Their digital marketing agency has won ...

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Role of Social Media Marketing Activities in Influencing Customer Intentions: A Perspective of a New Emerging Era

Khalid jamil.

1 School of Economics and Management, North China Electric Power University, Beijing, China

Rana Faizan Gul

Muhammad usman shehzad.

2 Department of Management Sciences and Engineering, Zhengzhou University, Zhengzhou, China

Syed Hussain Mustafa Gillani

3 Faisalabad Business School, National Textile University, Faisalabad, Pakistan

Fazal Hussain Awan

Associated data.

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

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.

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 ).

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 .

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.

Discriminant validity.

CI, continuance intention; PI, participate intention; PUI, purchase intention; Sat, satisfaction; SI, social identification; SMMA, social media marketing activities.

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 ).

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 ).

Hypothesis testing.

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 ).

A mediation analysis.

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

Author contributions.

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

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.

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

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Unlocking the Power of Effective Networking

Networking may feel daunting, but it is crucial for expanding contacts. Try engaging in activities relevant to your industry to effectively grow your network.

NEW YORK – Networking immediately frightens many people, yet it is very important to expand your contact list. Fortunately, networking does not have to be limited to exchanging cards or a short and seemingly pointless conversation. It can also be nice to strike up a conversation with someone in your industry. Here are six ways to more effectively expand your network.

1. Networking goes both ways

The purpose of networking is for you to learn more about another person, and for your conversation partner to learn about you and your company as well. Therefore, it is always best to start the conversation by introducing yourself. Tell your name and the name of your company, your position in the company, etc. After the introduction, you can ask some pointed questions to exchange more information:

• What products or services does your company offer?
• Who are your customers?
• Who is in charge of determining purchases?
• In what ways do you differentiate yourself from the competition

2. Evaluate your contacts

Even if you are very good at networking, it is impossible to include every person in your field or industry in your network. Therefore, it is important to filter so that you can see who is most worth the effort to build a relationship with. Ask yourself whether or not you can help each other. You really want to be able to contribute something and not just be a name in a person's address book. Conversely, you should evaluate others in the same way.

One trick to making good contacts is to look back at your past. You may have once studied with someone who knows a lot of people today. His or her network may also be of interest to you, so it is worthwhile to contact that person again. You can catch up, and possibly that old acquaintance could be the link to a very useful new contact in your network. On LinkedIn, for example, you often see an old classmate or colleague being the intermediary to a new contact.

3. Mingle with people

Sitting at home is not going to help you make new contacts. Networking also means actively participating in activities. Do something that you yourself are fascinated by, such as golf or cooking classes, and you will definitely meet people with the same interests.

Even in the business world, people from certain sectors often meet in the same cafes and restaurants. Try to find out where people from your sector have lunch or go for drinks at the end of the work week. Especially in relaxed situations, people are more social and it is easier to strike up a conversation.

If there is a charity fundraiser somewhere, be sure to attend. That's the ideal place to meet people and you immediately make a good impression because you are behind a good cause.

4. Always go for a second date

Unless the first meeting was seriously disappointing, there will always be a second date. Even professionally, it's good to see someone a second time. After all, it is difficult during an introduction to determine whether a contact is worthy of a place in your network. Typically, you don't have much time to get to know someone better.

Of course, you don't have to meet with everyone in the room for lunch or a cup of coffee. Therefore, a conversation is very important. Based on that, you should try to find out if there is potential in a relationship. If there isn't, it's better to keep starting conversations until you meet someone who does interest you. Then be sure to exchange contact information so that you can arrange a second date in the future.

5. Take advantage of social media

You certainly don't have to be active on social media all day to look for contacts, but it is worthwhile, for example, in the run-up to a conference to see if anyone is coming who might be of interest to your network. Some social media also lends itself better to professional contacts, so be sure to check out LinkedIn. Or a look at a company's website can also reveal a lot. Afterwards, you can follow certain people on Twitter, for example.

Social media is also the ideal place to share relevant articles. Be sure to get involved in discussions and answer or ask questions. That way you become an active member of a community and show yourself as someone with expertise in your field.

6. Maintain good relationships

If you have a good network, then it is important to maintain your relationship with your best contacts. That also means you're going to have to pick and choose, because the larger your network, the harder it is to build really meaningful relationships. Limit yourself to five to 10 people in your network that you really put energy into. So keep in regular contact and make sure it's interesting to them as well. Sharing a useful article or giving an update on your career can lead to valuable interactions.

There will also always be new contacts added to your network, which is why you should re-evaluate regularly. Perhaps someone was very useful last year, but that person is now much less interesting than someone you just met. That doesn't mean you should blow bridges right away. You can reconnect from time to time, because you never know if that person will ever become an important part of your network again.

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First study to measure toxic metals in tampons shows arsenic and lead, among other contaminants

• By Elise Proulx
• 3 min. read ▪ Published July 3
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Tampons from several brands that potentially millions of people use each month can contain toxic metals like lead, arsenic, and cadmium, a new study led by a UC Berkeley researcher has found.

Tampons are of particular concern as a potential source of exposure to chemicals, including metals, because the skin of the vagina has a higher potential for chemical absorption than skin elsewhere on the body. In addition, the products are used by a large percentage of the population on a monthly basis—50–80% of those who menstruate use tampons—for several hours at a time.

“Despite this large potential for public health concern, very little research has been done to measure chemicals in tampons,” said lead author Jenni A. Shearston , a postdoctoral scholar at the UC Berkeley School of Public Health and UC Berkeley’s Department of Environmental Science, Policy, & Management. “To our knowledge, this is the first paper to measure metals in tampons. Concerningly, we found concentrations of all metals we tested for, including toxic metals like arsenic and lead.”

Metals have been found to increase the risk of dementia, infertility, diabetes, and cancer. They can damage the liver, kidneys, and brain, as well as the cardiovascular, nervous, and endocrine systems. In addition, metals can harm maternal health and fetal development.

“Although toxic metals are ubiquitous and we are exposed to low levels at any given time, our study clearly shows that metals are also present in menstrual products, and that women might be at higher risk for exposure using these products,” said study co-author Kathrin Schilling , assistant professor at Columbia University Mailman School of Public Health.

Researchers evaluated levels of 16 metals (arsenic, barium, calcium, cadmium, cobalt, chromium, copper, iron, manganese, mercury, nickel, lead, selenium, strontium, vanadium, and zinc) in 30 tampons from 14 different brands. The metal concentrations varied by where the tampons were purchased (US vs. EU/UK), organic vs. non-organic, and store- vs. name-brand. However, they found that metals were present in all types of tampons; no category had consistently lower concentrations of all or most metals. Lead concentrations were higher in non-organic tampons but arsenic was higher in organic tampons.

Metals could make their way into tampons a number of ways: The cotton material could have absorbed the metals from water, air, soil, through a nearby contaminant (for example, if a cotton field was near a lead smelter), or some might be added intentionally during manufacturing as part of a pigment, whitener, antibacterial agent, or some other process in the factory producing the products.

“I really hope that manufacturers are required to test their products for metals, especially for toxic metals,” said Shearston. “It would be exciting to see the public call for this, or to ask for better labeling on tampons and other menstrual products.”

For the moment, it’s unclear if the metals detected by this study are contributing to any negative health effects. Future research will test how much of these metals can leach out of the tampons and be absorbed by the body; as well as measuring the presence of other chemicals in tampons.

Additional authors include: Kristen Upson of the College of Human Medicine, Michigan State University; Milo Gordon, Vivian Do, Olgica Balac, and Marianthi-Anna Kioumourtzoglou of Columbia University Mailman School of Public Health; and Khue Nguyen and Beizhan Yan of Lamont-Doherty Earth Observatory of Columbia University.

Funding was provided by the National Institute of Environmental Health Sciences; the National Heart, Lung, and Blood Institute; and the National Institute of Nursing Research.

In the Media:

• Tampons contain toxic metals such as lead and arsenic, UC Berkeley study finds – San Francisco Chronicle
• Toxic Tampon Warning As Arsenic and Lead Found in Common Menstrual Products – Newsweek
• Some tampons found to contain LEAD and other toxic metals that could be absorbed into the body, alarming study suggests – Daily Mail

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