Critical Factors for Acceptance of Social Commerce: A Case Study in Oman

Abstract

The study aims to assess the acceptance of social commerce and participate in social commerce amongst Omani people. The questions of the survey Instrument were prepared in English later converted into Arabic. The survey instrument was having two parts; the first part sought the demographic information like age, gender, education, occupation etc. The second part of the instrument was related to the variables, which was in 5-point Likert scale, where 5 means strongly agree while 1 meaning strongly disagree. The data was collected using online and offline surveys, making the number of the valid responses to 478. A conceptual model was developed using the following variables. The selected variables such as "Familiarity" (F), "Trust" (T), "Perceived usefulness" (PU), "Perceived ease of use" (PEU), "Intention to Purchase" (IP). The hypothesis was tested using structural equation modelling. The results indicate that all six hypotheses were supported. The F, T and PEU, and PU was found to be positive and significant related to intention to purchase (p-value 0.003, 0.001, 0.000. & 0.007). Amongst the four, p value of F was found to be the lowest and PU was found to be the highest. This indicate F was strong indicator of IP as compared to others. PUE relates to PU, and F was related to IP.

1. Introduction

The Activity of buying and selling goods and services is known as commerce. When this activity is done electronically, it is called E-commerce or Electronic commerce. This can include doing any activity associated with the process of commerce whether it be selection of goods or services, delivery, payment or any other process. When it is performed electronically then it becomes E-commerce.

Electronic commerce has evolved over decades and diversified itself in many different formats including buying through e-commerce websites or portals, mobile commerce, Automatic vending machines, electronic payments, e-delivery of E-Products or services, drone delivery of physical products etc. (Alraja & Malkawi, 2015; Alraja et al., 2016; Hussein et al., 2017; Uddin et al., 2016).

The era of Web 2.0 brought a new form of socializing and user generated contents called social media. Although social media original purpose was socializing it was used for several business purposes including commercial branding and communications (Lee et al., 2016) as well as academic. (Farooque & Aref, 2019, Farooque & Kadam, 2018). With advent of social media, a variant of E-commerce has evolved called as social commerce (SC) (Alraja et al., 2020). It is a branch of E-commerce, which involves interactions between multiple parties on the social media platform, inducing the buyers and sellers. According to Lam et al. (2019) “it is subset of electronic commerce that involves social media, and user contributions to assist online buying and selling of products and services”

Commerce was always a social activity, whether online or offline, usually it involved a lot of negotiations, discussion, consultations, and contemplations before taking a decision to buying, especially the product or servicing required for long term or the product or services with high initial investments. Social commerce is a more precise manifestation of this concept. Turban et al. (2018) used another term social business, referring to e-commerce dealings brought thru social media (Turban et al., 2018)

With availability of digital infrastructure and commitment by government, Oman as an e-ready country is placed quite high and looks promising for future opportunities of doing e-business, according to (Jamil et al., 2016). Several organizations commercial as well as non-commercial try to create and improve their online representation utilizing web presence and social engagement (Farooque et al., 2020). Information and communication technology (ICT) adoption by Trade, Industry, education and health care become obvious to deal with the crises caused by Covid-19 Pandemic. Although it was adopted in online teaching but on small scale. (Sayed et al., 2008, Vengatesan et al., 2018).

Online Buys in GCC is exceptionally low compared to other developed nations. The potential for e-commerce within the Middle East is exceptionally high, coordination and transport systems, rising web infiltration and a developing segment of tech-savvy youths can work as a catalyst to this emerging field.

Here is a look at the E-commerce improvement within the locale. Most of Oman’s populace buy items through remote e-portals; the trade potential of homegrown e-commerce stages is astonishing. It may also be noted that despite Oman’s smartphone usage ranking among the top in the Middle East, only 8 percent of the population opted for m shopping (Nambiar, 2019). According to a report published by Data portal (Kemp, 2020) there was 92% internet penetration in Oman, and There were 2.80 million social media users in Oman in January 2020. The present work tries to study the factors that influence an Omani individual’s intention to take part in or purchase from a SC platform, similar study was conducted by Rahman et al. (2020) for Indonesian consumers.

2. Literature Review

2.1. E-Commerce in Oman

Perceived risk and perceived ease of use can be considered as silent indicators of e-Commerce acceptance in sultanate of Oman (ALraja & Aref, 2015). Moreover, perceived Usefulness (PU), facilitating conditions (FC), and social influence (SI) have a significant and positive influence on the consumers’ behavioral intention to switch into electronic purchasing. While, the findings demonstrated that there is no significant effect by Perceived ease of use (PEU) on the consumers in China (Zhou, Zhang, Tan, Tseng, & Zhang, 2020) as well as in Oman (Alraja & Said Kashoob, 2019). Similarly, regarding M-commerce, the factors that contribute to its adoption is Trust according to (Naqvi & Al-Shihi, 2014), they also found most of the users have concern with security, privacy and trust, which prevents M-commerce adoption at large scale.

Recently, Tarhini et al. (2019) found that various factors which contribute to the consumers M-commerce adoption are Performance Expectancy (PE), Facilitating conditions (FC), hedonic motivation (HM), price value (PV) Habit (HB), Trust (TR), System Quality (SQ), and Information Quality (IQ). According to Belwal et al. (2020), apprehension to adopt e-commerce and concern regarding security, could be because of the reason that consumer protection initiatives in Oman are well entrenched for offline transactions, but are relatively new and limited for e-commerce (Belwal et al., 2020). According to Belwal et al. (2020), hesitation to adopt electroniccommerce and apprehension about security, could be because of the reason that consumer protection initiatives in Oman are well defined for traditional transactions, but are far removed and restricted for e-commerce (Belwal et al., 2020).

2.2. Hypothesis Development

Based on previous published studies, the conceptual model and hypothesis was developed using the variables are discussed below:

2.2.1. Familiarity and Trust (F&T)

The term “Familiarity” means close acquaintance with something. In this case, it means the extent of knowledge or awareness among consumers about the platform or the seller (Alraja et al., 2019; Sánchez-Franco & Roldán, 2015). Nguyen & Nguyen (2020) found that familiarity of risks and usefulness along with Trust impacts consumer’s selection of Online payment system. Al-Adwan & Kokash (2019) conducted a survey of 237 Facebook users who were undergraduate students of a private university in Jordan. The collected data was analyzed using PLS -SEM. The researchers found that familiarity has the positive effect on customers’ trust, and affects the purchase intentions. Increased familiarity with a SNS facilitates searching information on social commerce constructs that includes comments, rating, forums etc. (Al-Adwan & Kokash, 2019). Yahia et al. (2018) conducted a survey of Instagram users in GCC, they discovered that reputation and price advantage have the greatest impact on trust, but those habits weaken the impact. Contrary to the expected results social interactions with the social commerce vendors, which indicate familiarity, decrease trust. Differentiation in products reduces trust. However, social support has a detrimental impact on this effect. The other findings were that platform’s perceived ease of use, fascinating conditions, hedonic motives and habits increase social commerce intent (Yahia et al., 2018).

According to Mittendorf (2018) intentions to buy on the online platform is determined by their trust in the intermediary and their trust in providers. Farivar et al. (2017) collected data through survey and using decision-making models including trust and habit, the collected data was analyzed using SEM, the results showed that habit moderates the relationships between commerce risk and purchase intentions and between trust toward the social commerce site and purchase intentions (Farivar et al., 2017). According to Liang & Turban, (2011) the frequent sharing of supportive information can also enhance friendship and trust among members, which may further increase the intention to conduct commercial activities (Liang et al., 2011) as well as reduce the risk which affect the intention to switch to online purchasing (Alraja & Chikhi, 2015). Moreover, considering the privacy of users (Rashed & Alraja, 2015; Alkhariji et al., 2021; Chicha et al., 2021). Familiarity and trust play a major role in mediating exchange between venders and consumers. Both the variable has positive effects on consumers’ perceived usefulness of each social commerce platform (Gibreel et al., 2018; Sharma et al., 2019).

2.2.2. Perceived Usefulness (PU)

Perceived usefulness means the number of users make out that modern technology will assist to develop their performance. This stick to explain the term useful: “able to be used usefully”. A system which a consumer trusts in the presence of a positive relation between use and performance is the one high in perceived usefulness (Davis, 1989). On the other hand, (Soundarapandiyan & Ganesh, 2017) and Sheglabo et al. (2017) findings indicate that perceived usefulness has positive influence on users’ intention to use information and communication technology (Sheglabo et al., 2017; Soundarapandiyan & Ganesh, 2017). The rational users are prepared to obtain all the available benefits over online shopping (Alraja & Said Kashoob, 2019).

2.2.3. Perceived Ease of Use (PEU)

A degree of how users are willing to use new technology without specific difficulty is known as perceived ease of use (Davis, 1989). This track takes from “ease” which means “independence from great effort or difficulty”. Effort is a limited source that an individual might gave to the several activities for which they are liable (Radner & Rothschild, 1975). Customers are more expected to accept an application if they perceived it will be easier for them to use rather than the other (Davis, 1989). The ability to speedily and appropriately complete tasks by users with convenience and no disappointment (Alraja, 2015; Pu et al., 2011), who intended to imply decision efficiency, that is, the extent of assistance by a recommender system to help users rapidly find the items they are looking for. Another study also confirmed that perceived usefulness significantly influenced by perceived ease of use in TAM, and that is consistent with earlier studies (Chow et al., 2012; Davis et al., 1989; Joo et al., 2014). According to Joo et al. (2018) educators can perceive usefulness of technology when they perceive ease of use of it. Hence, in this study if people think that using s-commerce is easy for them in their daily purchase process, they will tend to adopt this technology for shopping activities.

2.2.4. Intention to Purchase (IP)

Wang and Yu (2017) surveyed 217 active consumers within social commerce; the survey was conducted at two stages prepurchase and post-purchase. The researcher found that social commerce contents and observing other consumer purchase, significantly affect consumer’s intention to buy. This increases likelihood of actual buying and information sharing i.e. intention to participate with on social commerce sites (Wang & Yu, 2017). According to Sohn and Kim (2020) the intention to purchase in social commerce is influenced by economy, necessity, reliability, and sales promotion (Sohn & Kim, 2020, Pham 2020). Tham et al. (2019) identified different types of risks that have positive impact on consumer’s online shopping which includes product risk, convenience risk, and return policy risk.

3. Methodology

The study was conducted with to assess the acceptance of social commerce amongst Omani people and to find what are the factors by which an Omani nationals intention to take part in social commerce is influenced. The “familiarity” (F), “trust”, (T) “perceived usefulness” (PU), and “perceived ease of use” (PEU) were the variables considered in this model. Three of these Variables “trust”, (T) “perceived usefulness” (PU), and “perceived ease of use” (PEU) were also adopted by Khan et al. (2020) with regards to Fintech.

The questionnaire was designed taking into consideration above mentioned variables based on previous similar studies. The variable was adopted from previous works were as follows. “Trust” (T), three item adopted from Gefen and Straub (2004) and Pavlou and Gefen (2004). “Familiarity” (F), three items adopted from Gefen et al. (2003) and Gefen (2000). “Intention to purchase” (IP), two items adopted from Liang et al. (2011). “Perceived ease of use”, (PEU) four items adopted from Gefen and Straub (2000). “Perceived usefulness”, PU four items adopted from Gefen and Straub, 2000). The questions of the survey Instrument were formerly prepared in English and were later converted into Arabic, as most of the respondents may not have not been very comfortable with English. Moreover, in order to ensure the accuracy of the translation, the faculty members who are experts in both languages further rechecked it. Based on their feedback, a slight modification was made.

Furthermore, a pilot study was conducted by distributing, the questionnaire amongst faculty and students, who had some social commerce experience. Some ambiguous and redundant items in the instrument was eliminated based on their feedback. The final version was later distributed online and manually to the targeted respondents from Oman.

The survey instrument was having two parts; the first part sought the demographic information like age, gender, education, occupation etc. The second part of the instrument was related to the variables, which was in 5-point Likert scale, where 5 means strongly agree while 1 meaning strongly disagree. The data was collected using online and offline surveys, total 563 responses were received, out of which 85 were rejected because of incomplete or incorrect response, making the number of the valid responses to 478.

4. Results and Discussion

The data have been collected from various categories are illustrated demographically in Table 1. The data is categorized by gender, age and education. In gender category, 64.44% and 35.56% are female and male respectively. The age was further classified as 20–30, 30–40, 40–50 years and respondents were 83.25%, 11.29% and 4.81% respectively. The education classification has been considered based on degree level such as general diploma, higher diploma, bachelor and master’s degree holders.

Table 1: Demographic Information

The survey Instrument was validated using discriminant and convergent validity, while Structural equation modelling was adopted to test the hypotheses, similar approach was adopted by (Alraja et al., 2021; Bugshan & Attar, 2020).

To ensure appropriateness of each item of scale, normality check was conducted. The results are given in Table 2. The results indicate that skewness between –0.5 and –1, the kurtosis was between –1 and +1.5. The data was normally distributed (Alkhaldi et al., 2017). The composite reliability and Cronbach’s alpha was between greater than threshold value i.e. 0.70 (Alraja, 2016; Malkawi et al., 2010). All the Average variance extracted (AVE) was greater than 0.5.

Table 2: Descriptive Statistics and Measurement Validity

4.1. Discriminant Validity

The above Table 3 indicate the results of discriminant validity, Fornell-Larcker criteria was used to compare AVE value with possible construct correlation. The square root of AVE value is expected to be more than the correlation of others constructs. Significant discriminant validity is evident from Table 3.

Table 3: Fornell-Larcker Criterion

Discriminant validity was also accessed using outer loading as given in Table 4 (Hammami et al., 2015; Kasem et al., 2015). Each indicator outer loading on its allocated construct was more than its cross loading with other constructs. The results of these tests confirm that the items, construct are valid and reliable for further analysis.

Table 4: Cross Loadings

Table 5 shows the correlation among the variables. It shows the linear relationship among the variables.

Table 5: Collinearity Statistics (VIF)

The Structural equation modelling was used to test the framed hypotheses (Alraja et al., 2019, 2020). The results obtained from the structural model analysis regarding the acceptance or rejection of the hypothesis is summarized in Table 6 and Figure 1.

Table 6: Hypotheses Results

Figure 1: Structural Model

As evident from the above-mentioned table, all six hypotheses were supported. The F, T and PEU, and PU was found to be positive and significant related to intention to purchase (p-value 0.003, 0.001, 0.000. & 0.007). Amongst the four, p value of F found to lowest and PU was highest. This indicate F was strong indicator of IP as compared to others. PUE relates to PU, and F was related to IP.

4.2. Discussion

The study was conducted in order to find out the factors that contribute to SC acceptance in Oman. The IP through social commerce is influenced by several factors including F, T, PU and PEU. Moreover, F influences T, and PEU influences PU. Similar finding were also reported by (Farivar et al., 2017).

The study contributes to the body of knowledge; in context of new technology and business model in general, particularly SC with reference to Oman region. It gives an overview of the consumer’s attitude towards social commerce, which contribute to overall growth of the local economy. Familiarity is an important concept in case of technology adoption, more the user is familiar with using the system, more likely he will prefer to use it and it will increase the trust in the system. Hence, in order to promote social commerce, it is necessary that businesses should try to make their present and prospective consumers get familiar with the application usage. The vendors can try to lead social media users to E-commerce, and business consumer to social media usage. According to (Alraja et al., 2019), user familiarity in using the new equipment and knowhow along with their trust in these will increase their probability of adopting them.

T is influenced by F, which influences the IP. Any kind of business is based the value of T between the buyers and sellers. In case of electronic commerce, most of the time, the seller is not visible or known, which reduces the value of T and hence reducing the IP. However, SC varies in this context with other form of e-commerce, as there is some knowledge and visibility of the seller, which increases the trust; from the hypothesis, it is also shown that trust itself is a strong indicator of intention to purchase. So it is important that to build the trust with the vendors, with system and with the media.

Ease of use in buying any good or services is an important aspect in a business transaction. If the consumer feels that it is easy to buy from the system, he/she will adopt it. In case of some goods or services in countries like Oman, it is difficult to purchase or sell them from regular market due several factors like high rents, advertisement costs, etc. social commerce can be a good alternative in this case. Hence, it is recommended, that social commerce vendors should work for improving the perception of ease of use amongst the prospective customers.

PU is influenced by PEU and influences IP. The idea of usability increases the intention to purchase. Once the consumers are convinced that the system has usability, then they can adapt it. The Omani people are already convinced with the usefulness of the social media, so they can easily adapt it for conducting commerce through social media.

5. Conclusion

Our finding is restricted to Oman which is one of the developing countries in Asia. Similar researches regarding other developing nations can give more insight about the situation and the findings can be generalized. The models did not take into consideration about the moderating effects of other variables. The present study does not include the effect on demographic variables on purchase decisions.