Keywords

1 Introduction

In recent years, online shopping has become a dominant form of online commercial activity, with statistics predicting global e-commerce sales to reach $4.5 trillion by 2021 [1]. One reason for this rapid growth may be attributed to the increasing integration of social media technologies within the online shopping interface, resulting in a more socially oriented form of online shopping appropriately termed social commerce [2]. Social commerce has been regarded as a subset of e-commerce, characterized by use of social technologies that allow for user-generated content [2]. Because of the growing popularity of social commerce, it is becoming the focus of several research studies [3, 4]. One area of research that warrants attention is how consumers’ purchasing behavior are influenced in the social commerce context.

This study draws on the stimulus-organism-response (SOR) framework [5] as the theoretical foundation to trace the antecedents and mediators that influence a consumer’s purchasing intention in the social commerce context. The stimuli are the social presence and security perceptions that an individual is privy to when he/she makes the initial contact with the social commerce platform. The organism refers to the internal process that occurs after this initial contact, which, in the case of social commerce, is the formation of a trusting belief. The response is the decision to purchase on-line.

Many studies have been conducted in the past to examine the effect of social commerce on businesses and consumers’ intention to make purchases through social commerce platforms. The motivation of this study is to focus on social commerce as a medium used to buy products in the context of e-commerce for Canadian consumers.

The purpose of this study is to provide a deeper understanding of the role that social media play when consumers are making online purchases. There has been very little research on this topic and this study aims to fill this gap. We are posing the following research question:

What factors influence the intention to purchase when consumers are engaged in social commerce.

2 Literature View

2.1 Social Commerce

Online shopping (E-commerce) refers to buying and selling of products over the internet [6]. Social commerce is a sub-set that uses social technologies that allow user-generated content [2]. However, the difference between social commerce and e-commerce has been met with confusion and much debate and the term social commerce itself has seen multiple definitions [3, 4]. Research identifies two broad views in terms of its conceptualization [3, 4] the first view of social commerce consists only of social networking sites (like Facebook, Twitter, Instagram). In the second view, social commerce is much broader and includes any website that uses social media technologies to facilitate online transactions. In this view, traditional e-commerce sites like Amazon and eBay can be considered social commerce because of their use of social media technologies [7]. The development of Web 2.0 technologies, which has enabled social media such as blogs, online communities, forums and social networks, has changed the framework of the web [8], by allowing user interaction and sharing.

With the help of social commerce, vendors can reach different markets by incorporating the social interactions of consumers [9]. Web-based associations give an option to organizations to build effective connection with their customers [10]. These will create positive value for consumers and will help vendors refine their marketing strategies [11].

In contrast to shopping in physical stores, online interaction does not give a consumer the chance of having direct human contact [12], and has lead to an automated, unknown and neutral relationship between vendor and consumer [13]. However, with the wide-spread use of social media technologies, and its incorporation in the social commerce medium, this neutral relationship is shifting, and there is a more dynamic relationship between the consumer and vendor.

The intention of this literature review is to examine some factors that influence the purchasing behaviour of consumers on social commerce platform.

2.2 Social Presence (SP)

Social presence is an important notion in social media and social commerce infrastructure. Social presence is known as interacting and socializing inside a website. To be specific, social presence is “the extent to which a medium allows users to experience others as psychologically present” [14, p. 2]. The notion of social presence is found in the social presence theory that clarifies the capability of a communication method to transfer social signs [15]. A media is considered likeable if it allows human dealings, friendliness, and reactivity [14]. Customer reviews and recommendations provide electronic vendors a way to have a personalized relationship with the customers, that is the underlying framework of social presence [16]. Good features of social commerce websites strengthen the perception of social presence, such as images and recommendations, etc. Naylor et al. [17] showed that the Like feature of Facebook helps to strengthen the customers brand opinion and purchase intentions. Gefen and Straub [12] suggest that pictures and text can convey personal presence in the same manner as do personal photographs or letters. Hassanein and Head [14] showed emotive text and pictures of humans as resulting in higher perceptions of social presence within websites.

Since human interaction is viewed as a precondition of trust [18] the buyer’s web interactions should also contribute to the building of trust online. A website with high social presence conveys more information and social cues and is perceived to be more transparent [19], which may lead to feelings of trust.

Hypothesis 1: Social Presence has a positive influence on Trust when consumers are intending to purchase online.

2.3 Security Perception (SEP)

Security is a very important consideration in online shopping and has been cited as one of the main concerns consumers require in their decision to pursue online purchases [20,21,22,23,24,25]. Security perception can be defined as the extent to which a person trusts that the online vendor or website is secure. Transfer of important information like credit card details is considered of significant value.

Because of the many risks involved with security over the internet, online vendors are taking measures to safeguard the data of their customers. Common online security concerns involve the security of credit cards, third-party services, and online privacy [26] and [27]. It is mentioned by Furnell [28] that showing policy statements and presenting a third-party seal like Verisign in the website are important factors to make consumers feel safe to perform a transaction. Because of the many risks involved with security over the internet, online vendors are taking measures to safeguard the data of their customers. These mechanisms help vendors gain the trust of their customers resulting in positive intentions to purchase.

If customer feels a sense of security with the safety procedure put in place, then it will likely impact their perceptions of trust, which ultimately affect their intention to purchase. Thus, it leads to the following hypothesis:

Hypothesis 2: Security Perception has a positive influence on Trust when consumers are intending to purchase online.

2.4 Perceived Internet Privacy Risk (PIPR)

An individual’s perceived internet privacy refers to their beliefs about whether or not there is a risk of disclosure of their private information which they input over the Internet. [29]. These risks show the degree to which individuals believe they might lose their privacy. Privacy has been studied by researchers in a wide range of disciplines [30] although research on internet privacy has only surfaced in the last few years. Privacy risk could include leakage or misuse of personal information [31, 32]. Privacy concerns influence the readiness of providing personal information to transact on the Internet. A lot of consumers are reluctant to shop online due to privacy and personal information submission concerns [33]. To overcome this fear of consumers, online business is taking steps to safeguard user’s private information. However, if individuals feel that there are not enough online safeguards to ensure privacy of their personal information, this can have a negative impact on their development of trusting beliefs in the vendor. This leads to the following hypothesis:

Hypothesis 3: Perceived Internet Privacy Risk has a negative influence on Trust when consumers are intending to purchase online.

2.5 Willingness to Provide Personal Information to Transact (WPPIT)

An individual’s willingness to provide personal information to transact describes one’s “willingness to provide personal information required to complete transactions on the Internet” [29, p. 219]. This construct differs from an individual’s perceived internet privacy risk (PIPR) which refers to “Concerns about opportunistic behavior related to the personal information submitted over the Internet by the respondent” [29, p. 219]. One’s willingness to provide personal information to transact suggests the extent to which an individual is likely to trust another party enough to provide them with personal information that can result in a transaction over the internet. In this sense, trust may play an important role in developing such a willingness. Culnan and Armstrong [34] found aid for the idea that users would be more willing to provide information if they knew who will have access to it and how it will be used. This leads to the following two hypotheses:

Hypothesis 4: Willingness to Provide Personal Information to Transact has a positive influence on Trust when consumers are intending to purchase online.

Hypothesis 5: Willingness to Provide Personal Information to Transact has a positive influence on consumer purchase intention.

2.6 Trust (T)

Trust is a construct in e-commerce [35, 36] and social commerce [38,39,40,41]. Hart and Saunders [42] have defined trust as the confidence that another party will behave as expected, combined with expectations of the other party’s good will. Zucker [43] has defined trust as a set of shared social expectations that are essential for and determine social behavior, enabling individuals to respond to each other without the explicit specification of contractual details. As several definitions of trust have been proposed [44], we adopt the view that trust is about the consumer’s belief that sellers will keeps their promises based on user generated feedback posted on the social networking sites (SNSs) (e.g. Facebook, WhatsApp, Yahoo) page regarding the quality of business offerings. Several factors influence customers intention to purchase from e-vendors, among these factors trust is found to positively influence customer retention [20, 45, 46]. If customers have less trust in an online business, they will be less inclined to engage in transactions on the web [47,48,49].

Online trust has multiple dimensions and is a major factor in an online purchase. Researchers have indicated that trust plays a role as mediator between website design details and intention to purchase [50, 51]. Given the context of social commerce, uncertainty is usually higher due to the high level of user-generated content and the lack of face-to-face interactions [41]. With the help of social commerce and the development of Web 2.0, trust can be increased, thereby reducing customers’ fear of online purchase. Web 2.0 has different applications like ratings, recommendations and review, which can be a helpful solution to increase trust. The greater the trust in the online vendor, the greater the purchase intention.

Hypothesis 6: Trust has a positive, significant influence on purchase intention.

2.7 Purchase Intention (PI)

Purchase intentions in social commerce contexts refer to the customers’ intentions to engage in online purchases from e-vendors on social networking sites (SNSs) like (Facebook, WhatsApp, Yahoo). Intentions are the determinants of behaviour and defined as “the strength of one’s intentions to perform a specific behaviour” ([52, p. 288]. Purchase intention is the result of various factors that influence the online shopping customer. Jarvenpaa et al. [53] have discussed that a customer will buy more from the online marketplace if the business is capable to win the trust of the customer.

3 Theoretical Foundation and Research Model

3.1 Stimulus Organism Response (SOR)

The study of purchase intention, which has a direct link to consumer behaviour, has grown over the last two decades, from the traditional store shopping to the present internet-based ones. Despite the changes, the fundamental aspects have remained, and researchers have adapted the SOR model to study different industrial sectors and business types. Based on the literature review, a conceptual model was developed on the stimulus-organism-response framework to guide this research. Since [5] suggested that environmental stimuli (S) lead to an emotional reaction (O) that evokes behavioral responses (R), the model has been applied in various retail settings to explain the consumer decision making process [54, 55]. As online retailing has grown [56], researchers have begun to focus on various aspects of this new medium using the S-O-R framework [57]. Past researchers have used Stimulus Organism Response (S-O-R), to examine the direct and indirect effects of retail environmental characteristics on impulse buying behavior [58].

In the context of this study, the stimuli include the various elements in the social commerce platform that indicate the presence of others (social presence) [14, 36, 59,60,61] as well as the elements that induce perceptions of security [38, 39] and those that help indicate perceptions of privacy risk and willingness to provide personal information to transact [38, 40]. The organism in the context of this study is the trusting belief in the online vendor. Morgan and Hunt [62] disclosed that trust is an important factor in the success of the social organization. This can be extrapolated to social commerce, to suggest that trust forms an important component of success in the viability of the social commerce platform. Research suggests that trust plays a central role in influencing consumer decisions through both e-commerce [35,36,37] and social commerce [61, 63,64,65]. The response in this study refers to the outcomes that individuals will receive once they experience stimuli in the social commerce platform: their emotional state of forming trusting beliefs is aroused and, the response is their purchase intention (Fig. 1).

Fig. 1.
figure 1

Source: Mehrabian and Russell (1974).

S-O-R framework.

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3.2 Research Model

The research model is shown in Fig. 2.

Fig. 2.
figure 2

Proposed research model.

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4 Methodology

4.1 Survey

The methodology is deductive. A questionnaire was used to collect data to validate the research model using a specialized software tool [66]. A seven-point Likert scale was used to measure each item, and all scales were adapted from the extant literature to ensure content validity.

Participants were asked about their opinions and judgements concerning the following five variables: social presence, security perception, perceived internet privacy risk, willingness to provide personal information to transact and trust.

The survey was user-friendly and, with the help of the Qualtrics software, some built-in attention filters were added to the survey, where participants had to answer a question with a very specific answer. The questionnaire was distributed through the Student Research Pool (SRP) to a convenient sample of undergraduate students at Ryerson University in Toronto, Canada.

4.2 Analysis

Partial Least Squares has been chosen as the statistical tool because of its ability to simultaneously evaluate both the measurement and structural model, allowing for rigorous analysis [67]. The specific tool was SmartPLS [68]. PLS has the advantage that it can model latent constructs that do not conform to the conditions of normality, and it can handle small to medium sample sizes [69]. It has recently been enhanced to include moderator analysis and heterotrait-monotrait (HTMT) ratio of correlations for discriminant analysis [68].

Initial analysis consisted of obtaining the maximum, minimum mean, median, and standard deviation for the research variables of social presence, security perception, perceived internet privacy risk, willingness to provide personal information to transact, perceived usefulness, trust and purchase intention. Cronbach’s alpha (reliability coefficient) was used to measure the internal consistency and reliability of the dataset obtained from the questionnaires [42]. The Fornell-Larcker table and heterotrait-monotrait (HTMT) ratio of correlations were used to Lastly, we calculated the path coefficients and their significance.carry out discriminant validity.

5 Results

5.1 Descriptive Statistics

594 completed questionnaires were returned. After eliminating unfilled, partially filled and those which failed the attention filters, 245 valid responses were included in the analysis, which is a completion rate of 41.3%. The survey participants were 30% (n = 73) male and 70% (n = 172) female. See Table 1.

Table 1. Descriptive statistics of sample.
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5.2 Measurement Model

The measurement model, or outer model, represents the relationship between constructs and their corresponding indicator variables [70]. The values in Table 2 are measuring each indicator’s impact on the allocated variable construct [70]. The correlation coefficients were greater than 0.724 [71] for the majority of the indicators. See Table 2. However, we dropped Social Presence (SP) from the model because of its non-converging indicators.

Table 2. Outer Loadings.
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The reliability and validity of the constructs were tested by calculating Cronbach’s alpha, composite reliability and average variance extracted. Cronbach’s alpha was greater than 0.7 [72], where Cronbach’s alpha 0.724 or higher is considered acceptable in most research studies and is considered to be reliable [73]. The composite reliability was greater than 0.7, for composite reliability, where a value greater than 0.70 is considered adequate in exploratory research [70]. The average variance extracted was greater than 0.5 [68]). See Table 3.

Table 3. Construct reliability and validity.
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The Heterotrait - Monotrait Ratio (HTMT) criterion is a new approach to assess discriminant validity and is considered superior to the other approaches such as Fornell-Larcker criterion and (partial) cross-loadings [70]. The HTMT should be less than 1 [70]. See Table 4. All values are less than 1, which supports the discriminant validity among the constructs. The PLS algorithm was run to calculate the Fornell-Larcker criterion from the cross loadings to assess the discriminant validity. Based on the Fornell-Larcker criterion, the AVE square root of every construct should be more than the highest correlation construct with any other in the model [74]. See Table 5.

Table 4. Heterotrait - Monotrait Ratio (HTMT) value.
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Table 5. Fornell-Larcker Scores.
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5.3 Structural Model

The coefficient of determination, denoted as R2, is the most commonly used measurement to evaluate the strength of the relationships in the structural model [70]. The R2 value ranges between 0 and 1, and it represents how closely the model with the independent variables explains the variation of the dependent variable. The higher levels indicate that more of the variance is due to the independent variables [70]. In our research model, “purchase intention” has a R2 = 0.165, which is not in the moderate range from 0.5 to 0.75 [75]. However, according to [76]  suggested R2 values for endogenous latent variables are assessed as follows: 0.26 (substantial), 0.13 (moderate), 0.02 (weak). Joseph et al. [71] addressed the difficulty of providing rules of thumb for acceptable R2 as it is reliant upon the model complexity and the research discipline. While R2 values of 0.20 are deemed as high in disciplines such as consumer behavior, R2 values of 0.75 would be perceived as high in success driver studies (e.g., in studies that aim at explaining customer satisfaction or loyalty).

Significance was determined by running the bootstrapping calculations with 5000 samples and no sign change. Four paths were significant. Table 6 shows security perception to trust is significantly and positively correlated. t-values greater than 1.96 represent a significance with probability of 95% that the hypothesis is true.

Table 6. Summary of results
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6 Discussion

This study investigated the influence of social presence, trust, security perception, perceived internet privacy risk and willingness to provide personal information on consumers’ intention to purchase via a social commerce platform. The data illustrates which of the five elements have influence on consumers purchase intention. Four hypotheses are supported, while one hypothesis was rejected at the significance level of p < 0.05 (indicated by t > 1.96) (Table 6).

Dropped - Hypothesis 1: Social Presence has a positive influence on Trust when consumers are intending to purchase online.

As online purchasing does not give consumer’s the opportunity to interact face to face with the vendor, it is important for the social commerce websites to strengthen the perception of social presence, by incorporating good features such as images and recommendations, etc. Naylor et al. [17] showed that the Like feature of Facebook helps to strengthen brand opinion and purchase intentions. Unfortunately, when empirically testing the model, it was determined that social presence was not measured well as its indicators did not converge even though they were based on the extant literature [36, 37]. We therefore eliminated social presence from the model. One reason for the non-converging indicators of social presence may be because the data was collected via an online questionnaire which lacks realism, and the sample of students were not able to visualize the possible personal relationship with the website defined in the questionnaire. Future research should further investigate the indicators so that social presence can be measured with valid scales.

Supported - Hypothesis 2: Security Perception has a positive influence on Trust when consumers are intending to purchase online.

Because many users feel that the Internet is not a safe environment for online shopping, online websites must put in place security measures to protect customers’ data. Transfer of important information like credit card details is considered of significant value [77]. As previously noted, Furnell [28] mentioned that a third-party seal like Verisign on the website is an important factor in the perception of security from the consumer’s viewpoint. When customers feel a sense of security with the safety procedures put in place by the online vendor, they will be more inclined to make a purchase.

Not Supported - Hypothesis 3: Perceived Internet Privacy Risk has a negative influence on Trust when consumers are intending to purchase online.

Privacy risk over the internet could include leakage or misuse of personal information, such as insider revelation or forbidden access [31]. Despite the many risks involved with disclosing personal information over the internet, online vendors are taking measures to safeguard the data of their consumers. However, this hypothesis was not supported. This may be because in the context of this study the sample of university students do not consider privacy risk over the internet to be an issue. They are already sharing personal information via social media and, from the results of this study, are not concerned about the risk to their privacy.

Supported - Hypothesis 4: Willingness to Provide Personal Information to Transact has a positive influence on Trust when consumers are intending to purchase online.

Supported - Hypothesis 5: Willingness to Provide Personal Information to Transact has a positive influence on consumer purchase intention.

Some individuals have a greater propensity to share personal information. They may not care about their data being shared or they may believe that the websites provide sufficient security. Our results show that individuals who are willing to share are more ready to place their trust in the website and they are more ready to purchase online. Again, this may be a reflection of the sample of students, who tend to pay less attention to privacy concerns.

Supported - Hypothesis 6: Trust has a positive, significant influence on purchase intention.

Trust is an important element in the context of online purchasing. If customers have trust in an online business, they will engage in transactions on the web [47,48,49]. The greater the trust in the online vendor the greater the purchase intention. Our results show that security perception, willingness to provide personal information to transact and trust has a positive influence on purchase intention.

6.1 Theoretical Contributions

This research study has proposed and empirically validated a research model that evaluates the factors that influence an individual’s intention to purchase in the context of social commerce. This study draws on the stimulus-organism-response (SOR) framework [5] as a theoretical guide to map the antecedents involved in influencing a consumer’s purchasing intention. SOR posits that stimuli (stimulus) in an individual’s environment can work through various internal processes within the individual (organism) to elicit an outward reaction (response). This research sought to examine whether social presence and security elements in the social commerce platform (stimulus) can impact a consumer’s trust in the platform (organism) and how this in turn impacts his/her intent to engage in a purchase through that platform (response).

The final research model indicates that security elements inherent within the social commerce platform do indeed impact consumers’ trust in the platform and their privacy perceptions, and that these go on to impact a consumer’s purchasing intention.

There are multiple theoretical contributions of this study. The first contribution is that the SOR model has been applied to the newer context of social commerce to map the factors impacting a consumer’s purchasing intention. As social commerce is a new mode of online shopping, research in this area is only just emerging. As such, this study bridges this gap in the literature by identifying security elements as important aspects of the social commerce interface that work through trust and privacy perceptions to influence a consumer’s intent to purchase through the medium. Although purchase intentions of consumers have been studied within the broader e-commerce context [37], we examine this within the social commerce context.

6.2 Implications for Practice

This study makes important practical contributions. Vendors should make their online business platform sociably attractive through rich content. Good features of social commerce websites strengthen the perception of social presence, such as images and recommendations, etc. Vendors should also include security elements to improve sales within the social commerce context. Security elements provide a sense of safety when transacting online, and, as suggested by this study, they can lead to greater trust in the platform as well as decrease perceptions of privacy risk.

Trust is an important construct that besides encouraging one’s initial purchase intention, can also lead to recurring and repeat purchases [39]. Thus, if a platform can encourage and build trust, it can lead not only to initial purchase intention, but may facilitate future purchases. Furthermore, privacy is an important topic today, with attention given to the importance of protecting privacy online [78]. If a social commerce platform, through highlighting security elements within its interface, can enhance privacy perceptions, this in turn can translate to more confident consumers that are willing to engage in transactions through the platform.

6.3 Limitations and Future Research

This study utilized a convenience sample of undergraduate university students obtained through the Student Research Pool (SRP) at Ryerson University. This is a limitation because this sample does not represent the general population. Furthermore, this subset is more likely to consist of proficient internet users who may be more trusting and less likely to be concerned about loss of privacy. As such, for this specialized subset of the population, even limited security perceptions may bolster a stronger trusting intention in the platform, and stronger perceptions of privacy, leading to more of a willingness to provide information and then to purchase online. Future studies may find it useful to test this model against a more generalized population. Convenience samples have, however, been utilized in numerous research studies, and although this is a limitation, it is still an acceptable method of sampling [79]. Another limitation is that this study used a questionnaire, and questionnaires are sometimes lacking in realism, especially when examining a consumer’s intent to purchase. Assessing an individual’s purchase intention through a questionnaire may not necessarily reflect whether the individual is in fact likely to engage in the actual transaction. Future studies may attempt to incorporate an experimental procedure, or a natural experiment developed in a manner that incorporates mundane realism.

Finally, this study utilized a more positivist approach in addressing its research questions. The study’s findings could be further strengthened by including a qualitative component to aid in triangulation of the results. The qualitative component could be in the form of open-ended questions aimed at better understanding the perceptions of the participants regarding underlying factors motivating their purchase intention through the social commerce medium.

Future research can further examine this model in different countries. For example, what factors influence purchase intention on social commerce platforms amongst Chinese consumers vs. Canadians, or Pakistani consumers vs. Canadians. Furthermore, understanding personality traits and their influence on purchase intention in social commerce may also provide valuable insight. This study looked at purchase intention in social commerce; it may also be interesting to see how these same factors influence impulse purchasing within the social commerce context.

Further research can be conducted to critically review and investigate the construct of social presence as it was dropped due to its non-convergent indicators.

7 Conclusion

This research study provides a deeper understanding of consumer purchase behaviour in the online social commerce context. As social commerce is a newer mode of online shopping, with researchers regarding it as a subset of e-commerce, research in this area is only just emerging. Because of the rapid uptake of social commerce usage by consumers, there is a pressing need for scholarly contributions to this developing field. This study provides one such contribution, by tracing the factors involved in influencing a consumer’s purchase intent through this medium. This research highlights that security elements inherent in the platform (those that allow a consumer to feel secure about his/her transaction) can lead to trust formation and the development of privacy perceptions, and that these in turn can influence a consumer’s willingness to provide personal information regarding a transaction, ultimately influencing his/her purchase intention. By developing this research model, which is grounded in the stimulus-organism-response framework, this study provides a novel theoretical contribution. It also provides a practical contribution by allowing vendors to understand the elements of the social commerce interface that motivate a consumer’s purchase behaviour through their platform.