The role of trust and social presence in social commerce purchase intention

Hassan, Masoodul; Iqbal, Zeeshan; Khanum, Bakhtawar Article The role of trust and social presence in social commerce purchase intention Pakistan Journal of Commerce and Social Sciences (PJCSS) Provided in Cooperation with: Johar Education Society, Pakistan (JESPK) Suggested Citation: Hassan, Masoodul; Iqbal, Zeeshan; Khanum, Bakhtawar (2018) : The role of trust and social presence in social commerce purchase intention, Pakistan Journal of Commerce and Social Sciences (PJCSS), ISSN 2309-8619, Johar Education Society, Pakistan (JESPK), Lahore, Vol. 12, Iss. 1, pp. 111-135 This Version is available at: https://hdl.handle.net/10419/188338 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc/4.0/ Pakistan Journal of Commerce and Social Sciences 2018, Vol. 12 (1), 111-135 Pak J Commer Soc Sci The Role of Trust and Social Presence in Social Commerce Purchase Intention Masoodul Hassan Department of Commerce, Bahauddin Zakariya University, Multan, Pakistan Email: [email protected]u.pk Zeeshan Iqbal (Corresponding author) Department of Commerce, Bahauddin Zakariya University, Multan, Pakistan Email: [email protected] Bakhtawar Khanum Department of Commerce, Bahauddin Zakariya University, Multan, Pakistan Email: mominkhan234[email protected]m Abstract Social commerce is a new advancement of e-commerce that merges the commercial and social activities by deploying social technologies into e-commerce sites. Social commerce reintroduces e-commerce from the perspective of social media/ networks. This study was aimed to evaluate the individuals’ intention towards social commerce in Pakistani context. The research model was examined in the light of positivist paradigm adapted questionnaire distributed among the people to yield data about the study constructs. The researchers employed PLS-SEM approach by using Smart PLS software to examine the hypothesized relationships. The findings suggest that social presence significantly influences the individuals’ intention towards social commerce with the mediation of customers’ experience. Furthermore, trust disposition, integrity of seller, competency of seller, and benevolence of seller positively shape the trust in marketplace. Moreover, trust in marketplace directly and significantly influences the individuals’ electronic word-of- mouth and purchase intention towards social commerce. Theoretically, these findings contribute to a better understanding of the effect of social presence and trusting beliefs on individuals’ electronic word-of-mouth and purchase intention towards social commerce. Finally, practical implications for nurturing thriving businesses in social commerce environment along with limitations and directions for future research have also been provided. Keywords: social commerce, social network sites (SNS), trust in marketplace, purchase intention, electronic word of mouth (eWOM), online shopping. 1. Introduction Social commerce is rapidly growing phenomena around the world (Pomirleanu et al., 2013; Sturiale and Scuderi, 2013; Vongsraluang and Bhatiasevi, 2016; Lal, 2017; Yahia et al., 2018). Social commerce is a form of commerce where social media plays the mediating role in any business dealing, including convergence between the online and offline Trust and Social Presence in Social Commerce 112 environments (Zhang and Wang, 2012; Yahia et al., 2018). It is gaining popularity because of the fame of social networking sites such as Yahoo, Facebook, Instagram, LinkedIn, WhatsApp and Twitter (Liang et al., 2011). The active users of the social networking sites are increasing day by day as ‘Digital in 2017’ reported that 2.8 billion people are now using social media worldwide with the penetration rate of 37 percent (Hootsuite, 2017). Furthermore, the emergence of social networking sites provides an opportunity to businessmen to conduct business activities in an innovative way i.e. social commerce (Yahia et al., 2018). Social commerce has changed the ways of doing business i.e. business moves from marketplace to market space. It brings substantial changes to business environment and customers’ mind set (Zhang and Benyoucef, 2016). It reshaped the traditional electronic commerce (Hew et al., 2016) by combining the power of social networking with online shopping (Wesson, 2010) and introducing new ways for the marketing of business offerings through social platforms (Turban et al., 2010; Zhang et al., 2015). Social networking sites enable the businessmen and marketers to promote their businesses, products and services to the large audience by using social media i.e. Facebook, Yahoo, WhatsApp, Twitter, Instagram etc. Pakistan has 31 million active social media users with the penetration rate of 16 percent (Hootsuite, 2017). Furthermore, Vision 2025 of Pakistan also focuses on the importance and adoption of technological developments in business activities (Ministry of Planning, Development and Reform, 2015). Therefore, in order to gain competitive edge, it is very important to understand the customers’ behavior and their intentions towards the social commerce. In the existing research, although, trust contributes a vital role in enhancing online purchase intentions (Heijden et al., 2003; Weisberg et al., 2011; Kim, and Peterson, 2017; Bhandari and Rodgers, 2018). However, little research is found concerning the users’ trust and purchase intentions link within the context of social commerce (Yahia et al., 2018; Lu et al., 2016). Moreover, few studies have focused on trust, social presence, and social commerce purchase intention (Hajli, 2015; Lu et al., 2016). Besides, some researchers have recommended that consumers are majorly influenced by electronic word of mouth-online customer reviews-on social commerce platforms (Hajli, 2015: Ahmad and Laroche, 2017). Moreover, although, different studies are available in Pakistani context that measures the customers’ intention towards e-commerce (Khurshid et al., 2014; Akhlaq and Ahmed, 2015; Rigas and Riaz, 2015; Ahmad et al., 2016) by employing various theoretical lenses i.e. technology acceptance model, theory of reasoned action, theory of planned behavior etc. However, only fewer researchers tried to study the phenomena of social commerce in Pakistani context (Hasan and Fatima, 2012; Talat et al., 2013). Finally, within this background, none of the studies in existing research has proposed and empirically tested the parsimonious model linking structurally the inter-relationships of trusting beliefs, social presence with customers’ purchase intentions and electronic word of mouth. Furthermore, researchers also claimed that there is lack of empirical work on social commerce, and there is a need to study the phenomena of social commerce by examining the drivers for social commerce in terms of trust, social support and the platform characteristics (Yahia et al., 2018). Therefore, this study aimed to provide in-depth knowledge about the drivers of customers’ intention towards the social commerce in Hassan et al. 113 Pakistani context through the theoretical lens of social presence theory. Theoretically, the current study contributes to a better understanding of the effect of social presence and trusting beliefs on individuals’ electronic word-of-mouth and purchase intention towards social commerce. Moreover, practically the study contributes to nurture thriving businesses in social commerce in developing country like Pakistan. 2. Review of Literature 2.1. Social Commerce Social commerce (s-commerce) is defined as the commerce in which business activities and transactions are conducted through the social media (Liang and Turban, 2011). S- commerce has changed the ways of doing business as it brings substantial changes to business environment and customers’ mind set (Zhang and Benyoucef, 2016; Yahia et al., 2018). It reshaped the traditional electronic commerce (Hew et al., 2016, Mikalef et al., 2017) by combining the power of social networking with online shopping (Wesson, 2010) and introducing new methods for the marketing of business offerings through social platforms (Turban et al., 2010; Zhang et al., 2015). It gained popularity in the field of marketing (Huang and Benyoucef, 2013), because social networks, such as Yahoo, WhatsApp, Twitter, LinkedIn, Instagram, and Facebook, enable the individuals to easily promote their business products and services to the large audience. Social networks also offer an opportunity to the stakeholders to vigorously contribute in value creation process by giving suggestions and feedback. S-commerce incorporates four major attributes in value creation process: (1) individuals, (2) social networks, (3) stakeholders’/ community interactions, and (4) commercial activities (Huang and Benyoucef, 2013). Hence, scommerce is considered to be combination of social and commercial activities (Liang and Turban, 2011; Zhou et al., 2013; Mikalef et al., 2017). As compare to e-commerce, s-commerce is relatively new business phenomena but it quickly comes into practice (Kim and Park, 2013; Barnes, 2014). Moreover, according Internet Retailer's Social Media 500, the total social network-derived online sales reached at $3.9 billion (Top500Guide.com). Furthermore, Smith (2015) stated that among all the social networks (Facebook, WhatsApp, Twitter, Pinterest, WeChat, Yahoo, LinkedIn, Instagram etc.), Facebook is the leading platform for social commerce that accounts for 64 percent of total social revenue. According to Business Insider (2015), social media enlarged its stake of e-commerce exchange approximately 200 percent between the first quarters of 2014 and 2015. Hence, s-commerce is the hotcake for researchers and no one can ignore the impact of social media. 2.2. Social Presence The idea of social presence is grounded in the social presence theory (Short et al., 1976). Social presence is defined as “the extent to which the social commerce environment enables a customer to establish a personal, warm, intimate and sociable interaction with others” (Zhang et al. 2014). Several authors advocated the multiple dimensions of social presence i.e. social context, interactivity, online communication (Tu and McIsaac, 2002), perception of others, self-projection, social identification (Caspi and Blau, 2008), awareness, affective social presence, cognitive social presence (Shen and Khalifa, 2009), Trust and Social Presence in Social Commerce 114 social presence of web, social presence of interaction, perceptions of others (Lu et al., 2016). In current study, social presence has three sub-domains viz., social presence of web, social presence of interaction, and social presence of others. Social presence of web refers to the capacity of a website to communicate a sense of friendliness (Gefen and Straub, 2004). Whereas, social presence of interaction is the ability of a website to provide platform to interact with seller. Traditionally, there was no direct interaction held between seller and buyer of e-commerce (Lu et al., 2016). But social commerce enabled the buyers and sellers to interact and to share their views with each other. Through this facility of social commerce, sellers/ producers can convince the buyers towards purchase of products or services. Several researchers suggested that SP of interaction is one of the key dimensions of social presence (Tu and McIsaac, 2002; Caspi and Blau, 2008). Furthermore, Mardsen, (2010) stated that people learn from and be impressed by the perceptions and experiences of others. During online commerce, individuals hardly believe on the information delivered by the online sellers on website (Lu et al., 2016), however, they believe more on the information disclosed by their closed-ones (Cialdini, 2001). If the views of existing customers of social commerce are positive, this will deliver positive signal to others (Chen et al., 2011) and ultimately people will more likely to engage in social commerce. Hence, the above discussed literature leads researchers to draw the following hypotheses:  H1:Social presence is positively associated with the experience of online shopping websites.  H2:Social presence is positively associated with social commerce purchase intention. 2.3. Customers’ Experience Customers’ experience is defined as all direct and indirect cognitive and affective exposure of the individuals to the social commerce, which is related to buying behavior (Klaus and Maklan, 2012). The individuals’ experience derives from a set of interactions with ecommerce activities (Gentile, Spiller and Noci, 2007). Clients having good experiences are more confident in their decisions, and therefore are not influenced by the negative views of others i.e. risk perceptions (Simpson, Siguaw and Cadogan, 2008). Several researchers advocated the positive relationship between customers’ experience and purchase intention (Kim and Choi, 2013; Sefian et al., 2013). If the social presence of the business is good and attractive, the people will take more interest in browsing the website of the business. Further, this will positively influence the customers’ experience and they will more likely to engage in buying behavior. The above discussion leads researchers to draw the following hypothesis:  H3:Customers’ experience is positively associated with purchase intention.  H4:Customers’ experience mediates the relationship between social presence and purchase intention. 2.4 Trusting Beliefs In this study, researchers include four types of trusting beliefs as independent constructs in the research model viz., trust disposition, integrity of seller, competency of seller, and benevolence of seller. Trust disposition can be explained as the extent to which individuals Hassan et al. 115 having belief or faith in humanity and adopting a trusting formula towards others (McKnight et al., 2002; Ridings et al., 2002). Morgan and Hunt (1994) also disclosed that trust is an important factor in the success of e-commerce/ e-business or social commerce. Integrity is the individuals’ beliefs that a business makes good faith promises on the superiority of the business offerings (products & services) provided to its customers (McKnight and Chervany, 2001). In the context of social commerce, it is about the SNS consumer’s belief that the seller will keeps his/ her promises as shown in the social network (e.g. Facebook, WhatsApp, Yahoo) page regarding the quality of business offerings. Competency of seller is defined as the perceptions of individuals about the knowledge, experience, and overall expertise of a seller (Cheung and Lee, 2000). It is the inner ability of a seller that brings customers towards the higher trust on the online vendor/ seller (Lu et al., 2016). Competency is one of the major attributes of trustworthiness (Barber, 1983; Cheung and Lee, 2000; Walter, Mueller and Helfert, 2000; McKnight and Chervany, 2001; Sirdeshmukh et al., 2002; Lu et al., 2016). It is an assessment of the other party (seller) whether he/she is useful for completing the desired goal, or can provide the expected outcomes (Tan and Thoen, 2000). Furthermore, it positively shapes the buyers’ trust level on the online seller (Lu et al., 2016). Benevolence refers to the vendors’ affection with their consumers. Benevolence is an individual’s trust that the seller cares about his/ her promises and is encouraged to act in honest manners (McKnight and Chervany, 2001). In social commerce perspective, it is individuals’ belief that the seller cares and concerned in his/ her well-being. Benevolence of seller positively shape the trust in marketplace (Lu et al., 2016). Hence, the overall discussion leads researchers to draw the following hypotheses:  H5:Trust disposition is positively associated with trust in marketplace.  H6:Integrity of seller is positively associated with trust in marketplace.  H7:Competency of seller is positively associated with trust in marketplace.  H8:Benevolence of seller is positively associated with trust in marketplace. 2.5. Trust in Marketplace In the context of social commerce, trust in marketplace can be explained as the individuals’ believes that the marketplace has honest dealers, fair business rules, procedures, and outcomes (Pavlou and Gefen, 2004). In social commerce, trust plays an important role in buying decision of a customer (Yen, Chang and Chiang, 2014; Akman and Mishra, 2017; Yahia et al., 2018). High trust in marketplace can lead individuals to engage in social commerce (Yen, Chang and Chiang, 2014; Lu, Zeng and Fan, 2016; Hung et al., 2018). Numerous research studies disclosed that there is positive association between trust in marketplace and intention towards social commerce (McKnight and Chervany, 2001; Pavlou, 2003; Lu, Zeng and Fan, 2016; Akman and Mishra, 2017; Yahia et al., 2018). Behavioral intention is an important predictor of individual’s actual behavior (Ajzen, 1991). It can be described as the individuals’ readiness to engage or not to engage in a particular behavior (Warshaw and Davis, 1985). Specifically, to the context of current study, purchase intention is delineated as the readiness to engage in s-commerce. Trust and Social Presence in Social Commerce 116 Furthermore, if the people have trust in marketplace, they will more likely to disseminate the features and benefits of social commerce to others. This implied that trust in market place also has an influence on the electronic word-of-mouth (EWOM). According to Hennig-Thurau et al. (2004), EWOM is the favourable or unfavourable comments or expressions from the stakeholders’ side about the business or business offerings via internet. Several marketing researchers highlight the importance of EWOM (Lee et al., 2012; See-To and Ho, 2014). Forman et al. (2008) disclosed that EWOM directly affects the sales of the company. This discussion leads researchers to draw following hypotheses:  H9: Trust in marketplace is positively associated with purchase intention.  H10: Electronic world-of-mouth is positively influenced by trust in marketplace. 2.6. Research Model In the light of above discussed literature and proposed hypotheses, the researchers developed the following research model (see figure-01). Trusting beliefs (trust disposition, integrity of seller, competency of seller, benevolence of seller) are positively associated with trust-in-marketplace. Furthermore, trust-in-marketplace is positively attached with individuals’ intention to engage in electronic world-of-mouth and social commerce purchase intention. Finally, the figure-01 represents that social presence has a positive and direct relationship with individuals’ intention towards social commerce and also through the mediation of customers’ experience of online shopping websites. Figure 1: Research Model Trusting Beliefs Hassan et al. 117 3. Research Methodology 3.1. Sampling & Data Collection In this study, researchers employed positivist research methodology, whereby a research instrument was adapted in order to collect data from respondents (Hair et al., 2016). The sample of this study included those personalities who are engaged in online shopping. Further, the data was yielded by conducting self-administrated questionnaire based survey and by sending the research questionnaire to the respondents via social media and emails. In addition, purposive sampling techniques was utilized to yield data from the respondents. The rationale for using purposive sampling method is its ability to yield more acute data. Moreover, all the items of the research questionnaire were measured on five point Likert scale (as proposed by Likert, 1932). The researchers collect data from variety of respondents, i.e. teachers, students, managers, assistants, housewives, employees of different businesses etc., from the various cities of Pakistan. Prior to data collection, the researchers have determined the part of population to be taken as a sample for the study (Ary et al., 2013). Researchers have used the Cochran’s formula (Cochran, 1963) to determine the sample size: Sample Size (SS) = [Z2 * P * (1 – P)]/ C2 Where Z= Z-value, P= percentage picking a choice, C= confidence interval From this formula the sample of at least 300 can be taken into consideration for effective and reliable results. Besides using Cochran’s formula, a sample of 200 respondents or more is considered to be adequate (Anderson and Gerbing, 1988; Kline, 2015). 3.2. Study Instrument As this study based on the positivist paradigm, where the role of researchers is limited to the data collection and interpretation. The positivist researchers are independent, therefore a research instrument was adapted for data collection and to measure the relationship of study variables. All constructs of this study were measured through multiple items adapted from prior studies (see table-1). Table 1: Development of Research Questionnaire Construct name Adapted from No. of items Social presence Gefen and Straub (2004), Caspi and Blau (2008), Hess et al. (2009) 12 Customers’ experience Bart et al. (2005) 3 Purchase intention Gefen and Straub (2004) 3 Trust-in-marketplace Pavlou and Gefen (2004) 4 Trust disposition Gefen and Straub (2004) 6 Integrity of seller McKnight et al. (2002); Gefen and Straub (2004) 4 Competence of seller As above 4 Benevolence of sellers As above 4 Electronic word-of-mouth (EWOM) Kim et al. (2008) 3 Trust and Social Presence in Social Commerce 118 4. Data Analysis After collecting the data, SPSS and SmartPLS software were used to analyze the data and to evaluate the hypothesized relationships. SPSS software was used for the demographic analysis of the respondents. Further, researchers applied PLS-SEM approach by using SmartPLS software (Ringle et al., 2005) to analyze the yielded data about the study constructs and to evaluate the hypothesized relationships. The rationale for using PLSSEM approach lies in its ability to evaluate multiple relationships (Hair et al., 2016). Further, PLS-SEM is better approach as compared to CB-SEM (Hair, Hollingsworth, Randolph, and Chong, 2017). In addition, Hair et al. (2017) stated rules of thumb for using choosing PLS-SEM approach as “the measurement philosophy is estimation with the composite factor model using total variance. The research objective is to explain the relationships between exogenous and endogenous constructs. The structural and/or measurement models are complex (many constructs = 6+ and many indicators = 50+).” Further, in SmartPLS software, the data was analyzed at 2 stages: (1) PLS Algorithm, where the multicollinearity statistics, reliability, validity and predictive power of the model were assessed, and (2) Boot-strapping, where the beta-coefficients, standard deviation, tvalues and p-values were assessed. 4.1. Demographic Analysis The table-02 represents all key information about the respondents i.e. gender, age, online shopping experience, and incidence of online shopping. The results revealed that from 306 respondents, 85 were male respondents i.e. 27.78% of the overall sample, while 221 were female coving 72.22% respondents of the whole sample. This implied that Pakistani females are more engaged in online shopping. Further, most of the respondents are from the age group of 25– 30 years old. This revealed that young generation is actively engaged in online shopping. Moreover, the frequency of online shopping of the respondents was also assessed. The results disclosed that most of the respondents engage in online shopping “once in a month” that covers 63.39% participants of the study, 59 respondents engage in online shopping several times in a month, 49 respondents conduct online shopping lesser than once in a month, and only 4 participants involve in online shopping several times in a week that covers only 1.30% respondents (see Table-02). Finally, the researchers examined the trend of most commonly online purchased products viz., clothing and footwear, food and health products, skincare, cosmetics & jewelry, books, computers, mobiles & accessories, and sports equipment/ products. The results revealed that clothing and footwear products were most commonly purchased through online shopping (see Table-2). Hassan et al. 125 Furthermore, customers’ experience is positively and significantly associated with the social commerce purchase intention [see figure-2(b); path coefficient= 0.483; R-square = 23.4 percent). Figure-3(b): Association between Customers’ Experience and Purchase Intention Moreover, the figure-2(c) graphical represents the total effect of social presence on social commerce purchase intention (path coefficient= 0.634, R-square= 40.2 percent). Figure-2(c): SEM Model for Total Effect of Social Presence on Purchase Intention In addition, figure-03 graphically represents the SEM results of association between social presence and purchase intention in the presence of customers’ experience. The figure-03 shows that social presence has the significant influence on customers’ experience (path coefficient= 0.457, R-square= 20.9 percent), and social commerce purchase intention (path coefficient= 0.521, R-square= 44.6 percent) respectively. However, with the mediation of customers’ experience, the strength of relationship between social presence and purchase intention reduced (path coefficient= 0.521) and the predictive power increased (R-square= 44.6 percent). This implied that customers’ experience partially mediates the relationship between social presence and social commerce purchase intention (see figure-03). Trust and Social Presence in Social Commerce 126 Figure 3: SEM Model-Social Presence, Purchase Intention Link in the Presence of Customer Experience The figure-04 shows the outer loadings of the multiple items of the constructs, path coefficients and values of R-square for overall effects. The figure-04 represents that trust disposition, integrity of seller, competency of seller and benevolence of seller collectively explain 40.6 percent variance in trust-in-marketplace. Furthermore, trust-in-marketplace, social presence and customers’ experience collectively predict 46.3 percent variance in social commerce purchase intention. Figure 4: SEM Model for Overall Effects Trust Disposition Integrity of Seller Competency of Seller Benevolence of Seller Trust-in- Marketplace (R-square = 0.406) Purchase Intention (R-square = 0.463) Electronic World-of-Mouth (R-square = 0.071) Customers’ Experience (R-square= 0.209) Social Presence 0.10 4 0.45 7 0.242 Hassan et al. 127 5. Discussion and Conclusion The underlying objective of this study was to evaluate the customers’ intention towards social commerce purchase. The empirical results of this study revealed the positive relationship between social presence and customers’ experience with social commerce (β= 0.457, t= 8.394, p< 0.001) and between social presence and individuals’ intention to engage in social commerce (β= 0.521, t= 8.486, p< 0.001). This implied that if the social presence of online available products is attractive and effective, the customers more likely to engage in social commerce purchase. Further, the customers’ experience positively and significantly influences the customers’ intention towards social commerce purchase (β= 0.242, t= 3.524, p< 0.001). The customers having good experiences were more likely to engage in social commerce purchase (Kim and Choi, 2013; Sefian, Jaini, Sharudin and Abdullah, 2013). Therefore, the companies having online shopping centers should always try to reduce the interruptions during online shopping and try to make online shopping easy and friendly for the people in order to positively shape their intention towards social commerce. Moreover, the findings of the study confirm the partial mediation of customers’ experience between social presence and individuals’ intention to engage in social commerce (see table-9, table-10), hence proved H1, H2, H3 and H4 of the present study. The statistical results of the study confirm the positive impact of trust disposition, integrity of seller, competency of seller, and benevolence of seller on trust in marketplace (β= 0.410, t= 5.585, p< 0.001; β= 0.147, t= 2.022, p< 0.01; β= 0.104, t= 1.702, p< 0.05; β= 0.268, t= 4.389, p< 0.001, respectively). These four determinants viz., trust disposition, integrity of seller, competency of seller, and benevolence of seller, proved as good predictors of trust in marketplace i.e. R-square= 40.6 percent. This implied that if the seller has good level of trust disposition, the buyers will have more trust in market place. In addition, moral soundness of the seller will also increase the trust of customers on marketplace. Further, the competencies/ abilities of the seller to fulfil his/her promises will increase the trust in marketplace. Last but not least, the inclination by the seller to do benovolent acts will boost the level of trust of the customers on the marketplace. These results are in line with the findings of numerous researchers (McKnight and Chervany, 2001; McKnight et al., 2002; Ridings et al., 2002; Sirdeshmukh, Singh and Sabol, 2002; Lu, Fan and Zhou, 2016). Further, trust in marketplace positively and significantly influence the customers’ intention towards the social commerce (β=0.168, t= 2.956, p< 0.01). This meant that if the individuals have positive perceptions and trust on social commerce, they will more likely to engage in social commerce (McKnight and Chervany, 2001; Pavlou, 2003; Lu, Zeng and Fan, 2016; Akman and Mishra, 2017). People feel hesitant to engage in social commerce, if they have negative perception about marketplace (Lu, Zeng and Fan, 2016). Trust is an important construct that positively shape the individuals’ intention towards social commerce (Yen, Chang and Chiang, 2014; Lu, Zeng and Fan, 2016; Yahia et al., 2018). Therefore, the social commerce based marketplaces should reduce the complexities, take legal action against fraudulent sellers, and make safe business environment. If the marketplace successfully wins the trust of people, this will lead towards the high usage of social commerce. Trust in marketplace can enhance the individuals’ willingness to participate in online shopping, reduce risk perceptions (Chiles and McMackin 1996; Gefen, Trust and Social Presence in Social Commerce 128 2000; Hung et al., 2018). In addition, trust in marketplace will also increase the electronic word of mouth (Nisbet, 2006). Empirical results of the study revealed that trust in marketplace positively and significantly influences the intention to engage in EWOM (β=0.267, t= 4.461, p< 0.001), however the predictive power is limited (R-square= 7.1 percent). This implied that if the customers have trust on the social commerce marketplace, they will share the experiences and benefits of using social commerce to others (Lee et al., 2012; See-To and Ho, 2014). Furthermore, Chu and Kim (2011) also disclosed the similar findings. This meant that trust in marketplace will ultimately proliferate the electronic word of mouth and motivate the people towards the social commerce. 5.1. Theoretical Implications In Pakistan, researchers paid little attention to the phenomena of social commerce, however the use of social commerce is at peak level in Pakistan now. This study fills up the gap of lack of research on social commerce in Pakistan and offers meaningful insightful to the academicians regarding the emerging phenomenon of social commerce and the role of trust in purchase intention. The current study evaluates the role of trust in marketplace in order to measure the individuals’ intention towards social commerce by taking the sample of Pakistani people. The results revealed that trust is an important element of individuals’ intention towards social commerce (McKnight et al., 2002; Lu et al., 2016). The findings of this study will have long-term impacts on e-commerce, e-business, social commerce, marketing and consumers’ behavior research as it provides the basis for developing empirical research on social commerce in Pakistan. The research model of this study can be used to measure the persons’ intention towards other mode of electronic business. In addition, this study upgrades our knowledge on how trust in marketplace and social presence of a business through trusting beliefs and customers’ experience respectively impact the buyers’ intention towards social commerce. Besides that, this study also adds value to the existing literature by exploring how the trust in marketplace influences the eWOM of a product. 5.2. Practical Implications The current study also offers some managerial implications. The results of this study suggest that the feeling of friendliness and affectionate in social commerce platformsupsurges individuals’ intention towards social commerce. WhatsApp and Facebook have newly introduced GIF buttons to improve the expressions of feelings in the social network sites. Consequently, if the social commerce providers (sellers) add these attractive tools into their social commerce pages/ website, this may enrich social presence. Furthermore, Bente, Rüggenberg, Krämer and Eschenburg (2008) stated that online businesses could improve the feeling of social presence in the platform by offering people with their avatars. Furthermore, the companies having online shopping centers should always try to reduce the interruptions during online shopping and try to make online shopping easy & friendly for the people in order to positively shape their intention towards social commerce. The social commerce based marketplaces should reduce the complexities, take legal action against fraudulent sellers, and make safe business environment. Finally, the policy makers should always focus on how to win the trust of people. Definitely this will upsurge the customers-based and sales volume of social commerce. Trust in marketplace is a serious Hassan et al. 129 concernparticularly in the context of social commerce and it plays a paramount role in rising the individuals’ intention towards social commerce. People will more likely to engage in social commerce if they have more trust on social platform (Hung, Yu and Chiu, 2018). Therefore, businesses who were offering social commerce should try to win the trust of customers by carefully managing the trusting beliefs viz., trust disposition, integrity of seller, competency of seller and benevolence of seller. Furthermore, they should always attempt to leave positive signal in the marketplace through electronic word-of mouth (Kim and Park, 2013). 5.3. Limitations of This Study and Future Research Directions This study will serve as foundation for future research in the context of social commerce, however, it also has some limitations. First of all, the researchers focused on some factors of social commerce purchase intention viz., social presence, customers’ experience, trust in marketplace, electronic word of mouth, however other factors such as willingness to cocreate with social commerce, perceived usefulness, social influence, awareness, price of goods, quality of goods, delivery time etc. are not the part of this study. Future research studies should focus on these factors. Secondly, the majority of the participants of this study were the students from different universities of Pakistan. The students do not represent the majority of population in Pakistan, therefore we cannot generalize the findings of the current study. We suggest that future research studies should collect data from the participants of different age group. In addition, researchers used survey questionnaire to collect data from the respondents, however, other data collection techniques such as, semi-structured interviews can also be used to evaluate the intention of the individuals. Another fruitful avenue for future research studies is to investigate the impacts of trust in marketplace and EWOM in different cultural contexts. As Li et al. (2009) stated “the Internet is a global medium, but its content is local to each country.” Such exploration will be valuable for the academicians and policy makers in the understanding of role of culture in social commerce purchase intention. REFERENCES Ahmad, Z., Jun, M., Khan, I., Abdullah, M., & Ghauri, T. A. (2016). Examining Mediating Role of Customer Loyalty for Influence of Brand Related Attributes on Customer Repurchase Intention. Journal of Northeast Agricultural University (English Edition), 23(2), 89-96. Ahmad, S. N., & Laroche, M. (2017). Analyzing electronic word of mouth: A social commerce construct. International Journal of Information Management, 37(3), 202-213. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. Akhlaq, A., & Ahmed, E. (2015). Digital commerce in emerging economies: Factors associated with online shopping intentions in Pakistan. International Journal of Emerging Markets, 10(4), 634-647. Akman, I., & Mishra, A. (2017). Factors influencing consumer intention in social commerce adoption. Information Technology & People, 30(2), 356-370. Trust and Social Presence in Social Commerce 130 Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423. Ary, D., Jacobs, L. C., Irvine, C. K. S., & Walker, D. (2013). Introduction to Research in Education. Cengage Learning. Bhandari, M., & Rodgers, S. (2018). What does the brand say? Effects of brand feedback to negative eWOM on brand trust and purchase intentions. International Journal of Advertising, 37(1), 125-141. Barber, B. (1983). The logic and limits of trust. New Brunswick, New Jersey, United States: Rutgers University Press. Barnes, N. G. (2014). Social commerce emerges as big brands position themselves to turn" follows"," likes" and" pins" into sales. American Journal of Management, 14(4), 11-18. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (2005). Are the drivers and role of online trust the same for all web sites and consumers? A large-scale exploratory empirical study. Journal of Marketing, 69(4), 133-152. Bente, G., Rüggenberg, S., Krämer, N. C., & Eschenburg, F. (2008). Avatar-mediated networking: Increasing social presence and interpersonal trust in net-based collaborations. Human Communication Research, 34(2), 287–318. Blanco-Oliver, A., Veronesi, G., & Kirkpatrick, I. (2016). Board heterogeneity and organisational performance: The mediating effects of line managers and staff satisfaction. Journal of Business Ethics, 1(1), 1-15. Business Insider (2015). It’s time for retailers to start paying close attention to social media. [Online] Available: Retrieved from: http://www.businessinsider.de/social-commerce- 2015-report-2015-6 (May 25th, 2017). Caspi, A., & Blau, I. (2008). Social presence in online discussion groups: Testing three conceptions and their relations to perceived learning. Social Psychology of Education, 11(3), 323-346. Chen, Y., Wang, Q., & Xie, J. (2011). Online social interactions: a natural experiment on word of mouth versus observational learning. Journal of Marketing Research, 48(2), 238-254. Cheung, C., & Lee, M. K. (2000). Trust in Internet shopping: A proposed model and measurement instrument in Proceedings of the America’s Conference on Information Systems (AMCIS, 2000). Long Beach, California, USA. Chiles, T. H., & McMackin, J. F. (1996). Integrating variable risk preferences, trust, and transaction cost economics. Academy of Management Review, 21(1), 73-99. Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655-690), Springer Berlin Heidelberg. Chu, S. C., & Kim, Y. (2011). Determinants of consumer engagement in electronic word-of- mouth (eWOM) in social networking sites. International Journal of Advertising, 30(1), 47-75. Hassan et al. 131 Cialdini, R. B. (2001). Harnessing the science of persuasion. Harvard Business Review, 79(9), 72-81. Cochran, W. G., 1963. Sampling Techniques, 2nd edition, John Wiley and Sons, Inc., New York. Curty, R. G., & Zhang, P. (2013). Website features that gave rise to social commerce: a historical analysis. Electronic Commerce Research and Applications, 12(4), 260-279. Forman, C., Ghose, A., & Wiesenfeld, B. (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291-313. Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(3), 382-388. Gefen, D. (2000). E-commerce: the role of familiarity and trust, Omega: The International Journal of Management Science 28(6), 725-737. Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-commerce and the importance of social presence: experiments in e-products and e-services. Omega, 32(6), 407-424. Gentile, C., Spiller, N., & Noci, G. (2007). How to sustain the customer experience: An overview of experience components that co-create value with the customer. European Management Journal, 25(5), 395-410. George, D. (2011). SPSS for Windows Step by Step: A Simple Study Guide and Reference, 17.0 update, 10/e, Pearson Education, India. Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications. Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458. Hajli, N. (2015). Social commerce constructs and consumer's intention to buy. International Journal of Information Management, 35(2), 183-191. Hasan, S. S., & Fatima, E. (2012). Social Networking Websites: Conduit for Women Entrepreneurs in Pakistan. International Journal of Computing and Corporate Research, 2(5), 1-17. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word- of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18(1), 38–52. Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(1), 277–319. Hess, T., Fuller, M., & Campbell, D. (2009). Designing interfaces with social presence: Using vividness and extraversion to create social recommendation agents. Journal of the Association for Information Systems, 10(12), 889-919. Trust and Social Presence in Social Commerce 132 Hew, J. J., Lee, V. H., Ooi, K. B., & Lin, B. (2016). Mobile social commerce: The booster for brand loyalty? Computers in Human Behavior, 59(1), 142-154. Hootsuite (2017). Digital in 2017. [Online] Available: https://hootsuite.com/newsroom/press-releases/digital-in-2017-report (June 17th, 2017). Huang, Z., & Benyoucef, M. (2013). From e-commerce to social commerce: A close look at design features. Electronic Commerce Research and Applications, 12(4), 246-259. Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management Journal, 20(2), 195–204. Hung, S. Y., Yu, A. P. I., & Chiu, Y. C. (2018). Investigating the factors influencing small online vendors’ intention to continue engaging in social commerce. Journal of Organizational Computing and Electronic Commerce, 28(1), 9-30. Iacobucci, D., Saldanha, N., & Deng, X. (2007). A meditation on mediation: Evidence that structural equations models perform better than regressions. Journal of Consumer Psychology, 17(2), 139–153. Internet Retailer's Social Media 500 (2016). SOCIAL 500. [Online] Available: http://www.top500guide.com/social-500/ (January 11th, 2017), Khurshid, A., Rizwan, M., & Tasneem, E. (2014). Factors contributing towards adoption of E-banking in Pakistan. International Journal of Accounting and Financial Reporting, 4(2), 437-455. Kim, Y., & Peterson, R. A. (2017). A Meta-analysis of Online Trust Relationships in E- commerce. Journal of Interactive Marketing, 38, 44-54. Kim, H., & Choi, B. (2013). The influence of customer experience quality on customers' behavioral intentions. Services Marketing Quarterly, 34(4), 322-338. Kim, J. W., Choi, J., Qualls, W., & Han, K. (2008). It takes a marketplace community to raise brand commitment: the role of online communities. Journal of Marketing Management, 24(3-4), 409-431. Kim, S., & Park, H. (2013). Effects of various characteristics of social commerce (scommerce) on consumers’ trust and trust performance. International Journal of Information Management, 33(2), 318-332. Klaus, P., & Maklan, S. (2012). EXQ: a multiple item scale for assessing service experience. Journal of Service Management, 23(1), 5-33. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford Press. Lal, P. (2017). Analyzing determinants influencing an individual׳ s intention to use social commerce website. Future Business Journal, 3(1), 70-85. Lee, D., Kim, H. S., & Kim, J. K. (2012). The role of self-construal in consumers’ electronic word of mouth (eWOM) in social networking sites: A social cognitive approach. Computers in Human Behavior, 28(3), 1054-1062. Hassan et al. 133 Liang, T. P., Ho, Y. T., Li, Y. W., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality? International Journal of Electronic Commerce, 16(2), 69-90. Liang, T. P., & Turban, E. (2011). Introduction to the special issue social commerce: a research framework for social commerce. International Journal of Electronic Commerce, 16(2), 5-14. Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22, 140-155. Lu, B., Zeng, Q., & Fan, W. (2016). Examining macro-sources of institution-based trust in social commerce marketplaces: An empirical study. Electronic Commerce Research and Applications, 20(1), 116-131. Mardsen, P. (2010). Social commerce: Monetizing social media. Hamburg, Germany: Syzygy Deutschland Gmbh. McKnight, H. D., & Chervany, N. L. (2001). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International Journal of Electronic Commerce, 6(2), 35-59. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: an integrative typology. Information Systems Research, 13(3), 334-359. Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38. Mikalef, P., Pappas, I. O., & Giannakos, M. N. (2017). Value co-creation and purchase intention in social commerce: the enabling role of word-of-mouth and trust. Twenty-third Americas Conference on Information Systems, Boston, 2017. Ministry of Planning, Development & Reform (2015). Vision 2025 of Pakistan. [Online] Available: http://pc.gov.pk/web/vision (November 3rd, 2017). Nisbet, E.C. (2006). The engagement model of opinion leadership: testing validity within a European context. International Journal of Public Opinion Research, 18(1), 3–30. Palmatier, R. W., Dant, R. P., Grewal, D. and Evans, K. R. (2006). Factors Influencing the Effectiveness of Relationship Marketing: A Meta-Analysis. Journal of Marketing, 70 (10), 136-153. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134. Pavlou, P. A., & Gefen, D. (2004). Building effective online marketplaces with institutionbased trust. Information Systems Research, 15(1), 37-59. Pomirleanu, N., Schibrowsky, J. A., Peltier, J., & Nill, A. (2013). A review of internet marketing research over the past 20 years and future research direction. Journal of Research in Interactive Marketing, 7(3), 166-181. Trust and Social Presence in Social Commerce 134 Ridings, C. M., Gefen, D., & Arinze, B. (2002). Some antecedents and effects of trust in virtual communities. The Journal of Strategic Information Systems, 11(3), 271-295. Rigas, D., & Riaz, N. (2015, August). E-Commerce purchase intention in emerging markets: The influence of gender and culture. In International Conference on Cross- Cultural Design (pp. 90-100). Springer International Publishing. Ringle, C, Wende, S., & Will, A. (2005). SmartPLS2.0 (M3) edn, Hamburg. Retrieved from http://www.smartpls.de/ See-To, E. W., & Ho, K. K. (2014). Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust–A theoretical analysis. Computers in Human Behavior, 31(1), 182-189. Sefian, M. N. I. M., Jaini, A., Sharudin, N. N., & Abdullah, M. H. (2013). Determining Factors that Influence Customers Patronage Intention: The Case Study of Radix Fried Chicken (RFC), the Local Home-grown Fast Food Chain Restaurant in Malaysia. In International Conference on Business and Management, Chiang Mai-Bangkok. Shen, K., & Khalifa, M. (2009). Design for social presence in online communities: a multidimensional approach. AIS Transactions on Human-Computer Interaction, 1(2), 33- 54. Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications, Hoboken, NJ: John Wiley & Sons, Ltd. Simpson, P. M., Siguaw, J. A., & Cadogan, J. W. (2008). Understanding the consumer propensity to observe. European Journal of Marketing, 42(1/2), 196-221. Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing, 66(1), 15-37. Smith (2015). Facebook is leading the way in social commerce. Retrieved from: http://www.businessinsider.com/social-commerce-2015-report-2015-7 Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13(1), 290-312. Sturiale, L., & Scuderi, A. (2013). Evaluation of social media actions for the agrifood system. Procedia Technology, 8(1), 200-208. Talat, A., Azar, S., & Yousaf, M. W. (2013). Investigating social commerce as an alternate model for online commerce in developing countries: A case of Pakistani economy. Pakistan Journal of Commerce and Social Sciences, 7(1), 223-242. Tan, Y. H., & Thoen, W. (2000). Toward a generic model of trust for electronic commerce. International Journal of Electronic Commerce, 5(2), 61-74. Tu, C. H., & McIsaac, M. (2002). The relationship of social presence and interaction in online classes. The American Journal of Distance Education, 16(3), 131-150. Turban, E., Bolloju, N., & Liang, T. P. (2010). Social commerce: an e-commerce perspective. In Proceedings of the 12th International Conference on Electronic Commerce: Roadmap for the Future of Electronic Business (pp. 33-42), Honolulu, United States of America.