An Analysis of Factors Affecting Intention to Purchase Products and Services in Social Commerce

As a result of the popularity and growth of social networks, consumers often rely on recommendations and suggestions from online friends to make buying decisions. Through social commerce, people are driven from inefficient individual decisions toward collaborative decision-making with higher efficiency. In this paper, we study the factors that affect customer decisions on the purchase of recommended products and services in the context of social commerce. A total of 327 individuals on three popular social networks in Iran (i.e. Facebook, Cloob, and Telegram) were surveyed. Analysis of the results using the PLS-SEM approach revealed that: (1) Social commerce constructs has a positive effect on social support and relationship quality. (2) Perceived usefulness has a positive effect on relationship quality and intention to purchase. (3) social support has a positive effect on relationship quality and (4) relationship quality has a positive effect on intention to purchase.


Introduction
Social commerce, also known as social business, refers to e-commerce activities conducted through social media. Thus, it may be considered as a branch of e-commerce which involves the use of social media to assist e-commerce transactions and other activities. It also supports social interaction and collaboration between the users (Liang et al., 2011). Therefore, social commerce is essentially a combination of e-commerce, e-marketing, support technologies, and social media content. In other words, social commerce is created by integrating e-commerce, e-marketing, and Web 2.0/social media. This integration is supported by a number of theories such as social capital, social psychology, consumer behavior, and online collaboration and has resulted in the development of many useful website and applications that create social commerce (Stephen & Toubia, 2010). These websites and applications have the potential to be used as sources of information for products and services. Furthermore, customers are enabled to create content and share their information and experiences about products and services. This is extremely important and appealing to manufacturers and service providers since it influences the customer decision-making process (Hajli, 2014a). Therefore, this paper investigates the factors that affect the adoption of social commerce.

Social Commerce
The development of Social Networks (SN) has resulted in a new paradigm of e-commerce known as social commerce. Although a standard definition of social commerce is lacking, generally, the concept refers to the provision of e-commerce activities and transactions through social media using Web 2.0 tools. Therefore, social commerce may be considered as a branch of e-commerce capable of supporting online social interactions of buying and selling products and services via SNs. In fact, social commerce is a combination of commerce and social activities (Hajli & Sims, 2015).
Social commerce supports social interactions to assist users in making decisions and obtaining products in online markets and communities. Given user participation as a key element, social commerce has a considerable impact on business and contributes to developing products, attaining market goals, and increasing sales (Stephen & Toubia, 2010). It allows individuals to participate in activities pertaining to marketing, selling, comparing, and sharing products and services in online markets and communities through social media (Liang et al., 2011).
The new form of business created by social media helps customers make well-informed and accurate decisions. Additionally, customers are able to find products with lower prices (Kim et al., 2013). In fact, customers can access knowledge and experiences of others to find similar products with lower prices, thus gaining greater bargaining power through social commerce (Hajli, 2014a).

Relationship Quality
Relationship quality is an important concept in relationship marketing which refers to the closeness and strength of a relationship and plays a critical role in increasing customer loyalty. Also, it has been introduced as the evaluation of the strength of the relationship between the service provider and the customer and the final assessment of service providing user (Taylor et al., 2011).
Given the intangible nature of services, customers could be unwilling to trust the service provider. Relationship quality serves to minimize this lack of trust and enhance the relationship between the customer and the company, eventually leading to greater loyalty and profitability (Caceres & Paparoidamis, 2007).
Relationship quality comprises three components: trust, satisfaction, and commitment (De wulf, et. al, 2001). A large body of literature exists on the individual impacts of these three components. For instance, Chen et al. (2009) demonstrated that trust plays a key role in following consumer-to-consumer websites. In another study, Teo et al. (2009) showed that trust and e-commerce success are related.
Many researchers have studied the impact of one or more components of relationship quality on purchase intention and behavior. For instance, Homburg et al. (2005) explored the impact of satisfaction on willingness to pay; and Verhoef et al. (2001) related commitment, satisfaction, and trust to consumer referrals and the number of services purchased. In this last study, all three components of relationship quality had an effect on referrals, but only the commitment factor significantly influenced the number of services purchased. Cronin and Taylor (1992), on the other hand, established that customer satisfaction was the most predictive of customers' intentions. Bloemer et al. (1998) established that different relationship quality components were important in different industries.
Therefore, the following is hypothesized: H1: Relationship quality has a positive impact on user's intention to purchase.

Social Support
Social support is a multidimensional construct defined as perceptions or experiences of caring, responding, and supporting people in a social group (Taylor et al., 2004). House (1981) identified four types of social support: emotional, instrumental, informational, and appraisal. Since the creation of content and relationships are the main features of social commerce, social support in social commerce revolves around informational and emotional support. Informational support refers to cognitive feelings arising from the content of recommendations, advice, or the knowledge that may prove beneficial in solving problems (Liang et al., 2011). Emotional support, on the other hand, pertains to experiences that are affected by emotional concerns including caring, understanding, and empathy (Coulson et al., 2011).
Stronger social support results in increased mutual understanding and greater warmth in the relationship. In other words, it can serve to fulfill the customers' needs, motivating them to interact with each other. As interactions and support information develop, higher levels of customer satisfaction and warmer relationships are observed.
In previous studies, social support has been shown to improve relationship quality (Rishka et al., 2013). Therefore, we predict that greater social support leads to close and warm relationships with higher quality. It is hypothesized that: H2: Social support has a positive impact on relationship quality.

Social Commerce Constructs
Refers to tools derived from social commerce such as online forums, communities, ratings, reviews, and recommendations (Hajli, 2013). These tools generate textual information capable of influencing customer buying behaviors (Hajli, 2015). Individuals use them to add value to their information. Also, they can be used to share information, express opinions and emotions regarding current or future products and services. Social commerce

Instrument
A total of five constructs are considered in this study: social commerce constructs, perceived usefulness, ُ◌social support, relationship quality and intention to purchase on social commerce. A questionnaire was used to measure the constructs. Answers were given on a five-point Likert scale of 1 (completely disagree) to 5 (completely agree).

Data Collection
The survey was conducted on the users of two popular non-Iranian SNs, namely Facebook and Telegram, as well as an Iranian SN called Cloob (www.cloob.com). In addition to their popularity, Facebook and Telegram were selected to represent web-based and application-based SNs, respectively. An online version of the questionnaire was used. In doing so, subsequent to designing the online survey, an access link was shared in groups and forums on the aforementioned SNs. After dropping the incomplete responses, a total of 327 responses were used for analysis purposes. Demographic characteristics of the respondents are shown in Table 1. In this paper, the Structural Equation Modelling (SEM) approach and Partial Least Squares (PLS) are used for evaluating the hypotheses and confirming reliability and validity.

Reliability
Among the various methods for testing reliability, Composite Reliability (CR) is recommended for PLS (Raykov, 1998). Values exceeding the threshold of 0.7 indicate acceptable CR (McLure Wasko and Faraj, 2005). As evident in Table 2, all constructs meet the threshold and are thus acceptable. Moreover, Cronbach's alpha for all constructs is larger than 0.7, demonstrating sufficient reliability.

Validity
To ensure content validity, measurements for all constructs of the study are obtained from relevant literature on e-commerce and social commerce. The constructs, as well as the pertinent items and references, can be seen in Table 2.

Measurement Model
The estimation results from SmartPLS software are shown in Figure 2. According to the results, all the paths among constructsare positive and significant at the 0.05 level. The model validity is assessed by R square value and the structural paths (Chwelos et al., 2001). The results of the R square indicate that almost 36% of the variance in the intention to purchase was accounted for by relationship quality and perceived usefulness. It means intention to purchase was, as hypothesized, affected by relationship quality and perceived usefulness. The result also shows that 28% of the variance relationship quality was accounted for by social commerce construct, perceived usefulness and social support. The R square for social support means that 42% of the variance in this construct was accounted for by Social commerce constructs. Hence, the result of R square shows a satisfactory level of explanation.
According to the results of path coefficients relationship quality (0.363) and perceive usefulness ( role. Thus, firms can leverage social commerce tools (e.g. forums) on social commerce websites or integrate these tools into their existing e-commerce platforms to create an environment wherein customers are able to discuss their products and services. Thus, a social environment is created and relationship quality is enhanced resulting in customer loyalty and higher company value. Through social support, such circumstances become particularly beneficial to the success of product or brand development efforts.
Secondly, social media owners or business managers must gain benefits by understanding why consumers use these websites. For instance, by learning that users are interested in entertainment and searching SNs and implementing such features, one can attract a greater number of consumers.
Thirdly, by learning about the consumers' true opinions and intentions regarding social commerce, business managers will be able to eliminate weaknesses, fulfill consumer needs, and create a superior shopping experience. Furthermore, business managers can leverage social media to contact potential consumers and remain in communication with existing ones.