1. Introduction
The term “social commerce” was first used by Yahoo in 2005 to describe the user-generated content (UGC) about the products/services and sellers in its shopping platform as a shopping feature, but this feature was already used by Amazon and eBay in the late 1990s without a tag [1]. Social networking sites (SNS) and social media applications simplified the engagement of users with s-commerce. Likewise, e-commerce sites have rapidly adjusted themselves, accelerating the development of social commerce (s-commerce) [2]. Accordingly, we can affirm that e-commerce, Web 2.0, and social media, the three pillars of s-commerce, helped the formation and development of s-commerce [3]. S-commerce is the new form of commerce, where strengthened connections between users have become the central focus of firms seeking to have a better relationship with them in order to explore the potential of this phenomenon and foster loyalty [4,5]. Surely, consumer loyalty is the ultimate goal of every firm, but first, they have to create a purchase intention among consumers, which is one of the most important steps of consumer behavior leading to loyalty. S-commerce plays an important role at this point, as it hosts a huge amount of UGC which affects consumer purchase intention. Coupled with the social side of s-commerce, purchase intention becomes one of the most significant variables to study. The body of academic research on purchase intention in traditional or e-commerce environments is large; however, the s-commerce field is still new and attracts attention from practitioners and academicians, as s-commerce has grown tremendously.
Empowered by social commerce, users can make better purchase decisions as they profit from other users’ information, experience, and social knowledge [6,7]. These users also share their views based on their experience and increase their social presence on SNS and s-commerce platforms, making the online social environment more trustworthy [8]. This positive influence plays an important role in the user’s online purchase intention and makes it easy for them to transact on social platforms.
Enhancing user participation makes online purchasing a more social experience while allowing companies to connect tightly with consumers [9,10]. Accordingly, companies aim to arrange the most engaging social experiences for their actual and potential customers in order to trigger their purchase intention [2,11]. Purchase intention in an online environment increases consumer-to-consumer and consumer-to-brand interactions. Surely, the more consumers are connected to companies, the more likely are their purchase intentions, positive purchase decisions, and repeating purchases [12,13]. Many variables influence online purchase intention and researchers have also investigated these variables in the s-commerce context; they have identified website design, website quality, perceived value and usefulness of the interface, information and interaction level, time efficiency, trust, and social support (e.g., [14,15]). In order to better understand the consumer perspective in social commerce, ref. [3] adopted existing consumer behavior models to this new environment. Ref. [16] investigated the role of s-commerce factors on the purchase decision. Refs. [17,18] have also worked on factors increasing purchase intention in s-commerce and showed the importance of trust and social presence. The most important step of any online transaction, hence, of an s-commerce transaction, is the purchase intention. The relationship between purchase intention and s-commerce, and the information gathered in academic works using these two keywords, are useful to advance knowledge in the s-commerce context. The results of this article will cover the research gap, particularly at the intersection of these two concepts, and help researchers develop new models of consumer behavior or purchase decision specifically considering s-commerce. Accordingly, given the development and interest in s-commerce, and despite all these works, there is still a need to identify and analyze the main clusters and lines of research to better understand s-commerce and its evolution. In this way, this study can help practitioners engage the most effective marketing strategies aligned with consumer expectations and also help researchers follow the main research themes. Thus, a bibliometric literature review is realized to observe these trends. Bibliometric analysis and review papers are the best tools to summarize the research status quo in any field. Bibliometric analysis also designates the developments and possible future research directions; thus, this analysis method has drawn attention from scholars from different fields [19,20,21,22,23,24]. This analysis method uses scientific databases to quantify the extant research in certain fields according to the number of citations, partnerships in articles, journals, authors, and their countries, with the help of specific software, such as Gephi and Vos viewer [25,26]. In this way, the bibliometric analysis easily shows research gaps, advances the field, and facilitates investigation in the right direction.
Although there are various databases, to eliminate data duplication and the cleaning process, and in order to have an easy, precise look at the literature, only the ScienceDirect database, which is one of the most extensive databases for high-quality academic works, is used. This is because the databases are not readied for bibliometric analysis. The data extracted included 71 articles published in the ScienceDirect database since 2013. This work aims to contribute by identifying the most productive journals and authors in the development of the field. Moreover, the keywords, citations, and general themes of these 71 works are also investigated thoroughly, given that there has not been such specific bibliometric research based on the intersection of the “purchase intention” and “s-commerce” keywords. The analysis is conducted on the last decade with data exported in February 2022 to answer the following questions:
How is the yearwise development of the topic?
What are the most highly cited publications and authors?
What are the most highly cited journals?
Which country/region has the most cited publications?
What are the other important keywords in the field?
What are the major themes of the field?
Our work is organized as follows: The next section provides a brief overview of the literature on s-commerce and purchase intention. Then, a third section is based on Methodology and Results. The final section synthesizes the conclusion, with both theoretical and practical implications, with the limitations of the study. Future research areas are also considered in this final part.
2. Literature
S-commerce, based on social platforms, creates an interactive environment that enables consumers to socialize, express themselves, and share information and opinions with others as well as with businesses [3]. This is a new way of doing business for companies using social media. They easily reach users and their entourage and friends on social platforms. S-commerce’s three main characteristics are: social technologies, community interactions, and business activities [13]. Consequently, s-commerce combines these three characteristics and supports social interaction in online commerce [1].
SNS and platforms use the social side of all users as a part of commercial activities by automatically adding their evaluations, reviews, purchases, and opinions to the social network [27]. Researchers identified consumers as the main driver of s-commerce. They are opinion seekers expecting information-rich, engaging, personalized, and easy online shopping experiences [28,29].
Consumers can search for and find the information they need about brands, products, or services on an s-commerce platform through shared notes and comments, recommendations, and references [29,30]. Thus, the information and the popularity of online social networks have been the drivers of e-consumers’ purchasing decisions on s-commerce sites [31].
According to [32], purchase intention is the anticipated or planned future behavior of consumers, that is, the probability of the beliefs and attitudes to be implemented. The purchase intention involves ideas such as, “I must do …”, “I will do …”, or “I will …”. So, purchasing intentions have been defined as the likelihood of future purchases of a service or product [33]. Often considered in the marketing literature as a proxy for actual consumer purchases, the intention to purchase is defined as a subjective probability of purchase based on the degree of planning of the act of purchase [34].
Purchase intention can be considered as a component of the consumer’s cognitive behavior in the purchase process. Purchasing decision-making is a cognitive process leading to the selection of a product or service among several options [35,36]. Two research streams attempted to examine this decision-making process. One involves evaluating the process using a variety of decision models, frameworks, and theories. For example, ref. [37] proposed the fundamental theory of rational decision-making that guides current research on the development of rationality theory. Other models resemble the design-choice model of intelligence [38]. These models suggest that purchase decision-making is realized in four main activities: seeking information, evaluating alternatives, developing attitudes towards products and services, and making a purchasing decision [39]. Alternatively, ref. [40] developed and proposed a five-step purchasing model that includes: needs recognition, research, evaluation, purchasing, and post-purchase. All these models consider that the consumer sequentially uses an important amount of information in every phase of the purchasing process. Additionally, ref. [41] developed the model of ambiguity and the model of limited rationality to examine the decision-making process. The second research stream in the field explores decision-making by examining consumer behaviors, including attitudes toward purchasing [42,43], purchase intentions [44], and consumer perceptions [45,46] and feelings about web systems [47], using behavioral theories such as reasoned action theory, planned behavior theory, and the technology acceptance model.
In the s-commerce context, the purchase intention is also the decision of the user to take part in web-based purchasing from social platforms [48,49]. This decision is subjective. Hence, the companies have to encourage consumers to use these platforms as the aim of the s-commerce activities is to mobilize social networks to increase profits. Accordingly, it is substantial for companies to increase the user’s transaction volume and sharing and recommendation activities. Many studies highlight the importance of encouraging users to participate in online brand communities [50]. This is because, to make the purchase, the user can go through any SNS marketplace. Then, the buyer and seller can directly interact and negotiate a price. Accordingly, the engagement of users in these platforms can lead to purchase intention [51]. The intent to purchase can also be expressed by sharing, and the mention “I like”. There is a two-way relationship of influence between purchase intention and s-commerce. If a consumer is satisfied, they will talk to their friends, and if they express dissatisfaction, they will talk about it a lot more, so the company/seller must manage its reputation on social media.
Another line of research in purchase intention considers the consumer-platform relationship as a determinant of purchase intention [52,53,54]. These works suggest that better relationships in s-commerce sites are achieved through social interactions, useful content, and real-time communications to help consumers’ decision-making process [55,56].
The social interactions between users are efficient at every stage of consumers’ decision-making process, as the content created by other users is more powerful than that of companies. This content includes recommendations, referrals, ratings, reviews, and information exchange that helps users make better decisions [57,58]. It must be also emphasized that the flow and design of the websites are also crucial for purchase intentions through repeated website visits [59]. Therefore, s-commerce depends on the use of Web 2.0 technologies by social networks and platforms, as they support, motivate, and help users make purchasing decisions.
S-commerce has deeply changed consumer behavior and purchasing habits [60]. Consumers became more and more informed and powerful, and companies inevitably put them at the center of their focus. Moreover, s-commerce and related variables, especially purchase intention, drew a lot of attention so our work will try to shed light on these two concepts via the last decade’s important research.
3. Method
The bibliometric analysis is an objective and quantitative method to investigate any research stream. It is vigorous and useful for finding out the emerging topics in a research field [61,62]. Moreover, this method is used in similar fields to our work, such as e-commerce [63] and marketing [64].
Accordingly, in an effort to identify the trends and future directions in the s-commerce and purchase intention domain, we used bibliometric analysis. The analysis of literature, publications, authors, and citations is supported by a summary of findings and methods used in the collected literature. The bibliometric analysis encompasses 71 finalized research papers published in the ScienceDirect database. These papers were identified in February 2022 using “social commerce” and “purchase intention” as keywords for the search within the title, keywords, and abstracts. Then, we narrowed our data using the 2013 to 2022 time period to better evaluate and interpret the trends and gain an overview of this topic. The keywords aimed to ensure the identification of papers directly working on the relation between s-commerce and purchase intention.
4. Results
The analysis in the study covered research papers in all languages and countries available, as the study seeks to shed light on the field and to display the developments in research on s-commerce and its relationship with purchase intention. The study investigates research for a decade from 2013 to 2022. To have a better insight into the substance of s-commerce, we first extracted the annual scientific production. Although the publication trend on this subject started slightly earlier than 2013, 2013–2022 is a good time interval to see the pattern of the research stream as the number of works escalated towards 2022.
The weak number in 2014 may be due to the use of different jargon by the researchers at that time to mean s-commerce. The purchase intention was already a settled term in the marketing world. The majority of research papers appeared in the last three years of the time frame. This pattern is pertinent to the development of social commerce which grew considerably, especially due to confinement at the global level. The proliferation of the research can also be attributed to the increasing number of users worldwide. Figure 1 shows the yearwise number of research papers, where the maximum number of articles were published in the year 2021 (14) and the minimum in the year 2014 (1).
Overall, 71 articles on s-commerce and purchase intention in the last decade appeared in the journals in the ScienceDirect database. This approach ensures reliability and consideration of quality articles that will provide accurate information on the directions and important concepts of s-commerce. Among these journals, The International Journal of Information Management is the journal with the most contributions. Figure 2 also shows other contributing journals. The most-contributing journal published 15 research papers within the decade and it represents 21% of the total publications. Following journals are Journal of Retailing with nine articles, and Information & Management, Electronic Commerce Research, and Applications, each with eight articles. Although the keywords are “social commerce” and “purchase intention”, the information management-related journals first take the lead due to the novelty and technical aspect of the domain; then, the retail and consumer perspective-based journals consider the issue. Surely, the gap in the literature is filled with more of the business and psychological aspects of the issue in other magazines not covered in our database. Even this figure showing the most-contributing journals indicates the development pattern of a new technology-based topic in the literature. This pattern is confirmed in many similar areas, e.g., [1].
In the case of the most-contributing authors in research papers on s-commerce and purchase intention, the bibliometric analysis found that among the most-contributing authors, no author is highlighted because they have almost the same number of papers. However, authors who publish the most on social commerce are shown in Figure 3. Among the top ten researchers, Chinese researchers are the majority. Researchers from the USA, India, and Europe follow the top ten. Considering the rapid development of social platforms and the support from online commercial activities in the first two countries, the advanced level can have many explanations, as these two countries are supporting the transition to the digital economy and have higher research expenditures compared to other countries. Universities are also a particular strength of these two countries, as they have about 170 universities ranked among the top 500 for the number of patent applicants in new technologies and artificial intelligence. Accordingly, they have a higher number of companies and research institutions publishing and working on new technologies and their impact on society. Moreover, the extent of the programs on computer technology and the huge amount of data available for researchers in these two countries are all supporting factors for this high level of contribution [65]. China and the USA are advanced in this topic, as technology and innovation fuel economic growth and knowledge creation as well.
An analysis of keywords was undertaken for a total of 71 articles with records that included keywords in the ScienceDirect database between 2013 and 2022. There were 287 keywords listed, 257 (90%) of which were used only once, and 20 (7%) keywords were used twice. Figure 4 shows the keywords used. The five most used keywords are “purchase intention” (used twenty-one times), which headed the list, followed by “social commerce” (nineteen times), “social media” (eight times), “trust” (seven times), and “e-commerce” (six times).
As depicted in Figure 4, a bibliometric study was performed to examine the development of the s-commerce field using the two main keywords. The bibliometric networks are visualized by the VOSviewer software, using “social commerce” and “purchase intention” as the main research keywords.
The correlated keywords allow us to visualize the network of keywords that appear around our main keywords to understand the developing directions of the field and to identify future research areas.
The keywords “social media”, “trust”, and “e-commerce” are the most used keywords around our two main keywords. E-commerce and social media, as mentioned before, can be described as the pillars of s-commerce with Web 2.0, as e-commerce involves the use of Web 2.0-based digital technologies to facilitate online sales and transactions with the help of perceived convenience and reduced costs [66]; and social media provides users with real-time information about a brand and its products/services to make it easier for users to make an online purchase decision. Social media activities realized by other users create a purchase intention by minimizing uncertainties and building trust around the brand. Accordingly, “trust” is the third most used keyword in our analysis. In the online environment, and especially in s-commerce, trust is essential for the relationship as it plays an important role in the development of relationships, communication, and acceptance of new technologies [67]. E-commerce websites are used together with social media platforms to increase trust, connectivity, and interactivity, providing many-to-many communication channels to accommodate consumer demands and needs. Therefore, trust is an important determinant of the development of s-commerce.
To ascertain the importance and influence of an article in its field, there are many methods; however, the simplest and one of the most objective methods is to see the number of citations it received [68]. In this way, the trendsetter articles, their impact on the dynamics of the field, and the way the research stream follows can be understood. Therefore, the most frequently cited ten articles for the years 2013 through 2022 are presented in Table 1.
During the period considered, the most frequently cited article was published in 2016. The article, “Social presence, trust, and social commerce purchase intention: An empirical research” by [12] (406 times), headed the list, followed by “Intention to purchase on social commerce websites across cultures: A cross-regional study” [69] (260 times) and “Consumers’ decisions in social commerce context: An empirical investigation” [60] (238 times). These three articles and the journals in the top ten show that s-commerce is an interdisciplinary field where information plays a central role. Surely, due to the chosen keywords, a second important point in these research works is the social aspect of purchase intention. This is already seen from the journal titles and the topics undertaken in these three most cited articles, which are based on social interactions, [69] social support, and community’s [12,16] impact on purchase intention and social shopping.
In order to enrich our analysis based on yearwise publication, most frequent journals, authors, citation frequencies, and visualization of keyword network, we also investigated the general theme and method of 71 articles in our database (Appendix A Table A1). This will inform about the most researched domains at the s-commerce and purchase intention intersection. A total of 51/71 (71.8%) of articles are empirically based on online, mail, or face-to-face surveys, while 91% of the studies in the field are based on a quantitative methodology. The studies using qualitative methods (6%) and reviews (3%) follow these works. The major themes that appear from these studies are based on the impact of social interaction, trust, perceived value by the user, and information. These four dominant themes conform with the nodes in Figure 4. Social interaction, trust, perceived value, and information are the most prominent variables in the field.
The research on s-commerce has received tremendous attention since 2013 due to the growth of SNS. S-commerce has an increasing influence on consumers’ buying behavior, especially via the mutual influence process between the users. The four themes support this as all of the themes stem from the users’ interaction.
5. Conclusions
The main purpose of this study was to shed light on the s-commerce phenomenon and its intersection with purchase intention by using the literature on the issue to enhance knowledge about this new way of commerce gaining popularity since the 2010s. The bibliometric method gives comprehensive statistics about the developing trends and the direction of a specific area, and helps us focus on a narrow field in the literature [76].
The bibliometrics of s-commerce- and purchase intention-related articles were analyzed over 10 years from 2013 to 2022. A steady increase was observed in the cumulative number of articles published throughout the specific observation period. The three top-ranking keywords for “social commerce”- and “purchase intention”-related articles were purchase intention, s-commerce, and social media. The three journals with the most articles in this category were International Journal of Information Management, Journal of Retailing and Consumer Services and Information & Management.
To add new results and knowledge to the literature, the general theme and methods of the articles in the selected database were studied and four major themes related to the interaction of users have emerged. Although s-commerce is still a new way of doing business, it has an increasing influence on consumers’ purchase intention, especially with its interactivity.
Interactivity changed the structure of online business and the relationship between all the actors in the market [77,78]. S-commerce is naturally based on this interactivity, which puts all online users, communities, and firms together with the unique possibility to interact, publish, and share, and also to obtain information about companies, brands, products, and services [79]. In addition, this information is considered more reliable than official information or advertisements by other potential clients [80]. Therefore, it is very important for firms seeking to have an online presence, brand awareness, and better relationships with all users to foster loyalty and trust. Besides trust, the information acquired by users increases the perceived value (more varieties, better shopping experience, and better-targeted products and services for specific needs) [45,81], while minimizing the product/service related risks. The four major research themes based on the social aspect of s-commerce and purchase intention are also a result of the evolution of users who became more social [82]. The social aspect and its impact on consumers’ purchase intention and purchase behavior is also supported by social support, social presence, and social influence theories used in many studies in the field, e.g., [82,83].
This study provides an overview of the s-commerce concept and the consumer’s purchase intention and shows, with the bibliometric data and general themes, the development of the field and new paths for academics and practitioners. By reviewing the 71 studies in our work, this paper provided academics with four major themes that attract scholars’ attention and showed the evolution and trends in the area. The journals that lead the field and these topics will help find the gaps in the purchase intention and s-commerce area.
This study contributes to the s-commerce literature by providing an overview of s-commerce and delineating the factors affecting the purchase intention in the s-commerce context.
The research through bibliometric analysis will inform academic researchers about the evolution, trends, and important factors in s-commerce. Hence, the research will enable researchers to identify research gaps to be filled by further studies in the future. From the theoretical perspective, s-commerce is relatively new, so it is relevant to try to shed light on this field. The analysis extends the knowledge on purchase intention in the s-commerce context.
E-commerce, social media, and trust are key factors in the s-commerce field, according to the last decades’ works. These three factors are shown by the bigger nodes in Figure 4 and play an important role in purchase intention; they can extend the social support theory in the literature on purchase intention over s-commerce [3]. The major themes that appeared in the study can also guide the future directions of the field. Therefore, this study will be of value in enriching other studies related to purchase intention in social commerce.
We see the importance of technological development which enabled the growth of s-commerce since 2013. The many-to-many communication and social theories that support the interaction of consumers are also emphasized. So, the firms should work on facilitating that communication with their s-commerce approach. This approach should be user-centered and encourage participation in the communication. In this way, firms can have better relationships with users, and understand them and foster loyalty. Technological advances, tracking possibilities, and insights from user behavior and user-generated content may help achieve better practices, because users look for personalized, informative, and better experiences and technology drives s-commerce. S-commerce offers a new set of business models challenging traditional businesses and e-commerce businesses.
This analysis is realized using “social commerce” and “purchase intention” as the keywords; other important keywords that appeared in the study, such as “social media”, “trust”, and “e-commerce” should also be included in further research. According to most cited works, researchers from China contributed most to the field; this finding and the underlying reasons behind it can also be analyzed in future research. The bibliometric analysis shows the growing interest in s-commerce and the importance of purchase intention in this new environment, presents the keywords related to the field, and highlights the important authors, countries, journals, and trends related to the field. The analysis points out the importance of the domain for professionals aiming to have a sustainable s-commerce business, as the papers and the keywords “trust”, “social media”, and “e-commerce” indicate the directions where they should focus their efforts. For researchers, it is helpful in understanding the trends in this research area, and in choosing an appropriate approach and the right direction to advance the field. Although bibliometric analysis is an analysis that can cover a wide field, in this first work, we narrowed our focus on the intersection of two keywords to have an accurate image of the domain as it advances at a rapid pace. Thus, this work will be a good starting point for future papers. This point of view could also be a new contribution to bibliometric analysis. Future studies should use multiple databases to extract data for analysis. Finally, this work did not analyze the reviewers or top editors in this field. This information should also be used in the future.
Some limitations should be considered in this study. Firstly, the database of scientific articles used in our work was ScienceDirect, one of the most important academic databases. However, in order to limit the work and have a more comprehensive perspective, other major databases were excluded. Thus, the quality of the articles used in the analysis is ensured at some level and the bibliometric analysis indicators are strengthened with the citation index. Secondly, to focus on the purchase intention in s-commerce, the keywords used to explore the research articles in the area were only these two words. These two words were chosen to keep the analysis simple, but as the analysis revealed, the words “social media”, “e-commerce”, and “trust” can cover more facets of s-commerce. Finally, a similar field could be investigated by using these words or interchanging them to advance the field.
All authors equally contributed to the preparation of the paper. Conceptualization, B.D. and C.D.; Formal analysis, B.D. and C.D.; Investigation, B.D. and C.D.; Methodology, B.D. and C.D.; Writing—original draft, B.D. and C.D.; Writing—review and editing, B.D. and C.D. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Data can be found in ScienceDirect Database, keywords “purchase intention” and “social commerce”, as of February 2022.
The authors declare no conflict of interest.
Footnotes
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Enlarge this image.Figure 2. Ranking of the top 10 journals with the most articles on social commerce and purchase intention by number of articles published between 2013 and 2022.
Enlarge this image.Figure 3. Top 10 authors with the highest numbers of social commerce and purchase intention-related articles.
Top 10 most cited articles and their citation frequency.
| Author(s) and Year | Journal | Article | Number of Citations |
|---|---|---|---|
| Lu et al. (2016) [ |
Computers in Human Behavior | Social presence, trust, and social commerce purchase intention: An empirical research | 406 |
| Ng (2013) [ |
Information & Management | Intention to purchase on social commerce websites across cultures: A cross-regional study | 260 |
| Chen and Shen (2015) [ |
Decision Support Systems | Consumers’ decisions in social commerce context: An empirical investigation | 238 |
| Pöyry et al. (2013) [ |
Electronic Commerce Research and Applications | Can we get from liking to buying? Behavioral differences in hedonic and utilitarian Facebook usage | 187 |
| Alalwan (2018) [ |
International Journal of Information Management | Investigating the impact of social media advertising features on customer purchase intention | 169 |
| Wang and Yu (2017) [ |
International Journal of Information Management | Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning | 146 |
| Bai et al. (2015) [ |
International Journal of Information Management | Effect of social commerce factors on user purchase behavior: An empirical investigation from renren.com | 142 |
| Liu et al. (2016) [ |
Computers in Human Behavior | Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce | 138 |
| Wang et al. (2013) [ |
Electronic Commerce Research and Applications | How online social ties and product-related risks influence purchase intentions: A Facebook experiment | 136 |
| Filieri et al. (2018) [ |
Information & Management | Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services | 120 |
Appendix A
General theme, method, and number of citations of 71 articles in the used database.
| Author(s) and Year | Title | Publisher | Key Words | Methodology | Citations | Theme |
|---|---|---|---|---|---|---|
| Akram et al., 2021 [ |
Online purchase intention in Chinese social commerce platforms: Being emotional or rational? | Journal of Retailing and Consumer Services | Online purchase intention | Questionnaire survey/online and face to face | 12 | Utilitarian and hedonic motivations positively affect Online Purchase Intention. |
| Hedonic motivations | ||||||
| Utilitarian motivations | ||||||
| Social value | ||||||
| Customer engagement | ||||||
| Social learning theory | ||||||
| Ghahtarani et al., 2020 [ |
The impact of social capital and social interaction on customers’ purchase intention, considering knowledge sharing in social commerce context | Journal of Innovation & Knowledge | Purchase intention | Questionnaire survey | 33 | Social capital theory and social interaction theory have a significant relationship with knowledge/information sharing. |
| Knowledge sharing behavior | ||||||
| Social capital | ||||||
| Social commerce | ||||||
| Social interaction theory | ||||||
| Lu et al., 2016 [ |
Social presence, trust, and social commerce purchase intention: An empirical research | Computers in Human Behavior | Social commerce | Simulation experiment | 406 | This paper confirms the positive role of social aspect in shaping online purchase behaviors. |
| Social presence | ||||||
| S-commerce marketplaces | ||||||
| Online trust | ||||||
| Purchase intention | ||||||
| Chen et al., 2021 [ |
The impact of imitation on Chinese social commerce buyers’ purchase behavior: The moderating role of uncertainty | International Journal of Information Management | Social commerce | Survey | 6 | Imitation has a positive impact on purchase intention. Purchase intention positively affects actual purchase behavior. |
| Imitation | ||||||
| Uncertainty | ||||||
| Purchase intention | ||||||
| Purchase behavior | ||||||
| Liu et al., 2021 [ |
The effects of social commerce environmental characteristics on customers’ purchase intentions: The chain mediating effect of customer-to-customer interaction and customer-perceived value | Electronic Commerce Research and Applications | Social commerce environmental characteristic | Questionnaire survey/online and face to face | 5 | Empirical analyses show that four technical environmental characteristics increase customers’ purchase intentions through customer-to-customer interaction and perceived value. |
| Stimulus-organism-response model | ||||||
| Customer-to-customer interaction | ||||||
| Customer-perceived value | ||||||
| Purchase intention | ||||||
| Onofrei et al., 2022 |
Social media interactions, purchase intention, and behavioural engagement: The mediating role of source and content factors | Journal of Business Research | Social media | Online questionnaire | 1 | Interaction influences perceived source credibility, source homophily, content quality, and consumers’ purchase intention. |
| Social media interactions | ||||||
| Information adoption model | ||||||
| Value co-creation | ||||||
| Purchase intention | ||||||
| Behavioral engagement | ||||||
| Lin et al., 2021 [ |
Factors influencing consumers’ continuous purchase intention on fresh food e-commerce platforms: An organic foods-centric empirical investigation | Electronic Commerce Research and Applications | Fresh food e-commerce platforms | Online questionnaire on e-commerce platform | 2 | Companies should focus on product characteristics and platform characteristics to enhance consumers’ perceived value, thus increasing their continuous purchase intention. |
| Organic foods’ perceived utilitarian value | ||||||
| Perceived hedonic value | ||||||
| Continuous purchase intention | ||||||
| Ng, 2013 [ |
Intention to purchase on social commerce websites across cultures: A cross-regional study | Information & Management | Social commerce | Convenience sampling method | 260 | Trust in a social network community may be attributed to the closeness and familiarity developed among its members resulting from social interactions. |
| Cross-cultural study | ||||||
| Social interactions | ||||||
| Trust transference | ||||||
| Social network site | ||||||
| Subgroup analysis | ||||||
| Sun et al., 2019 [ |
How live streaming influences purchase intentions in social commerce: An IT affordance perspective | Electronic Commerce Research and Applications | IT affordance | Survey | 90 | Visibility affordance, meta voicing affordance, and guidance shopping affordance can influence customer purchase intention through live streaming engagement. |
| Customer engagement | ||||||
| Live streaming | ||||||
| Purchase intention | ||||||
| Chinese social commerce | ||||||
| Zhou et al., 2022 [ |
What drives consumers’ purchase intention of online paid knowledge? A stimulus-organism-response perspective | Electronic Commerce Research and Applications | Online paid knowledge | Questionnaire survey | 0 | Knowledge platform interactivity and information quality, knowledge rareness, knowledge contributor professionalism and charisma positively influence consumers’ knowledge payment intention through the mediation of consumer perceived value. |
| Stimulus-organism-response | ||||||
| Perceived value | ||||||
| Purchase intention | ||||||
| Neural network analysis | ||||||
| Peng et al., 2019 [ |
Moderating effects of time pressure on the relationship between perceived value and purchase intention in social E-commerce sales promotion: Considering the impact of product involvement | Information & Management | Online flash sales | Questionnaire survey | 52 | Perceived value is positively related to purchase intention. Time pressure negatively moderates the effect of emotional/social value on purchase intention. |
| Perceived value | ||||||
| Time pressure | ||||||
| Product involvement | ||||||
| Purchase intention | ||||||
| Chen et al., 2018 [ |
What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness | Telematics and Informatics | Sharing economy | Questionnaire survey | 98 | Ratings have an insignificant impact on purchase intention, but a significant impact on perceived value. |
| Consumer review | ||||||
| Information quality | ||||||
| Media richness | ||||||
| Purchase intention | ||||||
| Alalwan, 2018 [ |
Investigating the impact of social media advertising features on customer purchase intention | International Journal of Information Management | Social media | A self-administrative questionnaire | 169 | Significant impact of performance expectancy, hedonic motivation, interactivity, informativeness, and perceived relevance on purchase intentions. |
| Marketing | ||||||
| Advertising | ||||||
| Customers | ||||||
| Purchase intention | ||||||
| Filieri et al., 2018 [ |
Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services | Information & Management | Electronic word of mouth | Questionnaire survey | 120 | Popularity signals, two-sided reviews, and expert sources are perceived as helpful by consumers to assess service quality and performance. |
| Services | ||||||
| Dual process theory | ||||||
| Perceived information helpfulness | ||||||
| Purchase intention | ||||||
| Liu et al., 2016 [ |
Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce | Computers in Human Behavior | Social commerce | Questionnaire survey | 138 | Interpersonal interaction factors positively relate to flow experience and subsequently influence purchase intention. |
| Interpersonal interaction | ||||||
| Flow experience | ||||||
| Purchase intention | ||||||
| Chang et al., 2019 [ |
Effect of tangibilization cues on consumer purchase intention in the social media context: Regulatory focus perspective and the moderating role of perceived trust | Telematics and Informatics | Mobile community | Experimental survey | 6 | The results suggest that affective trust information is more effective than cognitive trust information in facilitating consumer purchase behavior. |
| Tangibilization cues | ||||||
| Regulatory focus | ||||||
| Perceived trust | ||||||
| Purchase intention | ||||||
| Erdoğmuş et al., 2015 [ |
Drivers of Social Commerce through Brand Engagement | Procedia—Social and Behavioral Sciences | Social commerce | S-O-R model | 5 | The social commerce stimuli include sales campaigns, personalization, interactivity, UGC, and reviews. |
| Online brand engagement | ||||||
| Relationship marketing | ||||||
| Online purchase intention | ||||||
| Hu et al., 2016 [ |
The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention | International Journal of Information Management | Social shopping website | S-O-R model—Questionnaire survey | 100 | Similarity and expertise of peer members in the community and the website’s support for recommendations positively impact shoppers’ perceived utilitarian value of the SSW. |
| Social commerce | ||||||
| Stimulus-organism-response model | ||||||
| Purchase intention | ||||||
| Shopping values | ||||||
| Tuncer, 2021 [ |
The relationship between IT affordance, flow experience, trust, and social commerce intention: An exploration using the S-O-R paradigm | Technology in Society | Online social commerce | Questionnaire survey | 5 | Visibility affordance influences customer purchase intention through trust in the seller and trust in the social media platform; meta voicing affordance influences social commerce intention. |
| IT affordance | ||||||
| Flow experience | ||||||
| Trust | ||||||
| Social commerce intention | ||||||
| Stimulus-organism-response (S-O-R) theory | ||||||
| Fu et al., 2018 [ |
Who will attract you? Similarity effect among users on online purchase intention of movie tickets in the social shopping context | International Journal of Information Management | Perceived usefulness | Questionnaire survey | 65 | External and internal similarity significantly affected users’ perceived usefulness, enjoyment, and trust transfer. |
| Perceived enjoyment | ||||||
| Trust transfer | ||||||
| Purchase intention | ||||||
| Lin et al., 2020 [ |
Purchasing organic food with social commerce: An integrated food-technology consumption values perspective | International Journal of Information Management | Social commerce | Questionnaire survey | 26 | Functional value is more instrumental and there is a significant difference between males and females in the formation of purchase intention. |
| Social networking sites | ||||||
| Organic foods | ||||||
| Theory of consumption values | ||||||
| Functional value | ||||||
| Emotional value | ||||||
| İslam et al., 2021 [ |
Determinants of purchase luxury counterfeit products in social commerce: The mediating role of compulsive internet use | Journal of Retailing and Consumer Services | Materialism | Questionnaire survey | 3 | The mediating CIU and moderating factors that played a significant role in promoting counterfeit purchase intention. |
| Novelty seeking | ||||||
| Hedonic benefits | ||||||
| Counterfeit luxury products | ||||||
| Attitude toward luxury counterfeit | ||||||
| Product conspicuousness | ||||||
| Positive online reviews | ||||||
| Lin, et al., 2019 [ |
Understanding the interplay of social commerce affordances and swift guanxi: An empirical study | Information & Management | Social commerce | Questionnaire survey | 64 | Interactivity and word of mouth exert positive effects on mutual understanding, reciprocal favor, and relationship harmony to various degrees. |
| Swift guanxi | ||||||
| Mutual understanding | ||||||
| Reciprocal favor | ||||||
| Relationship harmony | ||||||
| Meilatinova, 2021 [ |
Social commerce: Factors affecting customer repurchase and word-of-mouth intentions | International Journal of Information Management | WOM intention | Questionnaire survey | 25 | The results indicate that repurchase and WOM intentions are positively affected by trust and satisfaction. |
| Trust | ||||||
| Satisfaction | ||||||
| Reputation | ||||||
| Information quality | ||||||
| Zhu et al., 2016 [ |
Exploring factors of user’s peer-influence behavior in social media on purchase intention: Evidence from QQ | Computers in Human Behavior | Social media | Questionnaire survey | 27 | Peer-influence purchase is less likely to be due to the influence of higher degree users but is more related to the number of prior adoptions in the user’s social neighborhood. |
| Social marketing | ||||||
| Peer-influence behavior | ||||||
| Purchase intention | ||||||
| Leong et al., 2020 [ |
Predicting the antecedents of trust in social commerce—A hybrid structural equation modeling with neural network approach | Journal of Business Research | Trust | Mall intercept technique | 47 | Information support has the strongest effect, followed by the social presence of interaction with the sellers, income, and social presence of others. |
| Social commerce | ||||||
| Social Presence Theory | ||||||
| Social Support Theory | ||||||
| Artificial neural network | ||||||
| Wang et al., 2019 [ |
Does privacy assurance on social commerce sites matter to millennials? | International Journal of Information Management | Social commerce | Questionnaire survey | 63 | Institutional privacy assurance positively influences institutional-based trust, which, in turn, affects online social interactions and increases purchases on s-commerce sites. |
| Institutional privacy assurance | ||||||
| Institutional-Based trust | ||||||
| Word-of-mouth | ||||||
| Bai et al., 2015 [ |
Effect of social commerce factors on user purchase behavior: An empirical investigation from renren.com | International Journal of Information Management | Social commerce | Questionnaire survey | 142 | Social factors can significantly enhance users’ purchase intentions in social shopping. |
| Consumer purchasing intentions | ||||||
| Social support | ||||||
| Seller uncertainty | ||||||
| Product uncertainty | ||||||
| Third-party infomediaries | ||||||
| Chen et al., 2017 [ |
Customers’ purchase decision-making process in social commerce: A social learning perspective | International Journal of Information Management | Social commerce components | Questionnaire survey | 96 | Cognitive appraisal has a higher predictive power on purchase behavior than affective appraisal. |
| Social learning theory | ||||||
| Forums and communities | ||||||
| Ratings and reviews | ||||||
| Wang et al., 2017 [ |
Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning | International Journal of Information Management | Social commerce | Secondary data from the literature | 146 | Positive and negative valence WOM, WOM content, and observing other consumers’ purchases significantly affect consumers’ intention to buy a product. |
| E-commerce | ||||||
| Social interaction | ||||||
| Consumer decision-making process | ||||||
| Word of mouth (WOM) communication | ||||||
| Observational learning | ||||||
| Doha et al., 2017 [ |
Social bundling: A novel method to enhance consumers’ intention to purchase online bundles | Journal of Retailing and Consumer Services | Bundling | Questionnaire survey | 7 | Social bundling outperforms traditional bundling in driving intention to purchase in bundles. |
| Consumer control | ||||||
| Intention to purchase | ||||||
| Field experiment | ||||||
| Anderson et al., 2014 [ |
Influence of hedonic and utilitarian motivations on retailer loyalty and purchase intention: a facebook perspective | Journal of Retailing and Consumer Services | Retailing | Secondary data—National online consumer panel | 118 | Experiential shopping influences loyalty but not purchase intention. |
| Consumers | ||||||
| Motivations | ||||||
| Hedonic | ||||||
| Utilitarian | ||||||
| Aladwani, 2018 [ |
A quality-facilitated socialization model of social commerce decisions | International Journal of Information Management | Social commerce | Secondary data from the literature | 27 | Social commerce process followed a causal path, linking an individual consumer’s initial attention to interaction experience to intuitive evaluation to intention to buy. |
| Social media quality | ||||||
| Social support quality | ||||||
| E-commerce | ||||||
| Website quality | ||||||
| Li, 2019 [ |
How social commerce constructs influence customers’ social shopping intention? An empirical study of a social commerce website | Technological Forecasting and Social Change | Social commerce constructs | Questionnaire survey | 70 | Familiarity exerted a positive and significant effect on trust in product recommendations. Trust in product recommendations exerted a significant effect on social shopping intention. |
| Social presence | ||||||
| Social support | ||||||
| Closeness | ||||||
| Familiarity | ||||||
| Trust | ||||||
| Sun et al., 2016 [ |
Does social climate matter? On friendship groups in social commerce | Electronic Commerce Research and Applications | Collaborative shopping | Online survey | 45 | Proximal social networks in voluntary settings show that social climate influences friendship group members’ purchase behavior. |
| Friendship group | ||||||
| Member intention | ||||||
| Purchase behavior | ||||||
| Social commerce | ||||||
| Yeon et al., 2019 [ |
What creates trust and who gets loyalty in social commerce? | Journal of Retailing and Consumer Services | S-commerce | Questionnaire survey | 29 | The individual vendor’s trust has no significant effect but customer loyalty is accumulated by individual vendors. |
| Online purchase process | ||||||
| Social network service | ||||||
| Heuristic factor | ||||||
| Systematic factor | ||||||
| Li et al., 2018 [ |
The power of a thumbs-up: Will e-commerce switch to social commerce? | Information & Management | Switching intention | Questionnaire survey | 67 | Push effect, in terms of low transaction efficiency, drives customers away from e-commerce sites, whereas the pull effects, including social presence, social support, social benefit, and self-presentation, attract customers to social commerce sites. |
| Push–pull–mooring framework | ||||||
| Social commerce | ||||||
| E-commerce | ||||||
| Ahmad et al., 2017 [ |
Analyzing electronic word of mouth: A social commerce construct | International Journal of Information Management | Social commerce | Online reviews | 73 | Potential customers find the negative reviews containing service failure information and the positive reviews containing information on core functionalities to be more helpful. |
| Reviews | ||||||
| Informational support | ||||||
| e-WOM | ||||||
| Latent semantic analysis | ||||||
| Chen et al., 2015 [ |
Consumers’ decisions in social commerce context: An empirical investigation | Decision Support Systems | Social commerce | Questionnaire survey | 238 | Both emotional and informational social support significantly affected consumers’ trust and community commitment, which in turn exerted profound impacts on both social shopping and social sharing intention. |
| Trust transfer | ||||||
| Community commitment | ||||||
| Social support | ||||||
| Zhao et al., 2020 [ |
Electronic word-of-mouth and consumer purchase intentions in social e-commerce | Electronic Commerce Research and Applications | Electronic word-of-mouth | Questionnaire survey | 21 | Information is very important for trust, which has a positive effect on purchase intention. |
| Information quality | ||||||
| Social psychological distance | ||||||
| Purchase intention | ||||||
| Tandon et al., 2021 [ |
Why do people purchase from food delivery apps? A consumer value perspective | Journal of Retailing and Consumer Services | Consumption values | Questionnaire survey | 8 | Visibility and attitude acted as an antecedent of all consumption values and significantly influenced purchase intentions. |
| Food delivery apps | ||||||
| Hospitality | ||||||
| Purchase intention | ||||||
| Visibility | ||||||
| Masuda et al., 2022 [ |
Impacts of influencer attributes on purchase intentions in social media influencer marketing: Mediating roles of characterizations | Technological Forecasting and Social Change | Influencer marketing | Questionnaire survey | 1 | PSR had a significantly positive impact on purchase intentions relative to other characterizations and PSR was significantly related to the three personal attributes. |
| social media | ||||||
| Purchase intention | ||||||
| Theory of persuasion | ||||||
| Parasocial relationship | ||||||
| YouTube | ||||||
| Özkara et al., 2017 [ |
Examining the effect of flow experience on online purchase: A novel approach to the flow theory based on hedonic and utilitarian value | Journal of Retailing and Consumer Services | Online purchase intention | Web-based survey | 51 | The results indicates that the flow’s most valuable antecedent is feedback in the context of online purchase. |
| Human computer interaction | ||||||
| Hedonic value | ||||||
| Utilitarian value | ||||||
| Zhang et al., 2018 [ |
Social media, information presentation, consumer involvement, and cross-border adoption of pop culture products | Electronic Commerce Research and Applications | Argument adoption | Questionnaire survey | 8 | Presence of the country-of-cultural-origin effect. |
| Consumer involvement | ||||||
| Cultural products | ||||||
| Social media | ||||||
| Social network | ||||||
| Purchase intention | ||||||
| Qin et al., 2021 [ |
How mobile augmented reality applications affect continuous use and purchase intentions: A cognition-affect-conation perspective | Journal of Retailing and Consumer Services | Mobile augmented reality | Questionnaire survey | 1 | The relationships proposed in the cognition-affect-conation framework support the direct and indirect influence of perceived value on conative efforts in the MAR context. |
| Perceived value | ||||||
| Cognition-affect-conation | ||||||
| Continuous use intention | ||||||
| Purchase intention | ||||||
| Zhu et al., 2019 [ |
No trespassing: exploring privacy boundaries in personalized advertisement and its effects on ad attitude and purchase intentions on social media | Information & Management | Personalized Advertisement | Questionnaire survey | 12 | Facebook ads are positively related to perceived privacy, which leads to better ad attitude and higher purchase intentions. |
| Online purchase intention | ||||||
| Information Boundary | ||||||
| Perceived Privacy | ||||||
| Ad attitude | ||||||
| Kao et al., 2020 [ |
Modeling Airline Crisis Management Capability: Brand attitude, brand credibility and intention | Journal of Air Transport Management | Crisis management | Questionnaire survey | 6 | Conceptual and methodological contributions to crisis management and purchase intention research; provides practical insights into effective airline crisis management and brand management for the airline industry. |
| Strike | ||||||
| Airline | ||||||
| Brand attitude | ||||||
| Brand credibility | ||||||
| Intention to purchase | ||||||
| Wang et al., 2013 [ |
How online social ties and product-related risks influence purchase intentions: A Facebook experiment | Electronic Commerce Research and Applications | Social networking sites | Field experiment | 136 | Product information and recommendations provided by friends are perceived as having a high level of diagnosticity. |
| Information diagnosticity | ||||||
| Tie strength | ||||||
| Purchase intention | ||||||
| Product-related risks | ||||||
| Wang et al., 2022 [ |
Effect of sponsorship disclosure on online consumer responses to positive reviews: The moderating role of emotional intensity and tie strength | Decision Support Systems | Online reviews | 0 | In an online scenario-based experiment, sponsorship disclosure of positive reviews negatively influences consumers’ purchase intention, and review credibility mediates the relationship. | |
| Sponsorship disclosure | ||||||
| Emotional intensity | ||||||
| Tie strength | ||||||
| Language expectancy theory | ||||||
| Wang et al., 2021 [ |
The dual concept of consumer value in social media brand community: A trust transfer perspective | International Journal of Information Management | Business value | Survey | 9 | This study examines the effects of three types of perceived values on consumer behaviors. |
| Consumer value | ||||||
| Trust | ||||||
| Social media brand community | ||||||
| Lu et al., 2020 [ |
Is user-generated content always helpful? The effects of online forum browsing on consumers’ travel purchase decisions | Decision Support Systems | Online forums | Questionnaire survey | 4 | The findings of this study provide insights into how online forum browsing behavior affects consumers’ purchase decisions. |
| S-commerce | ||||||
| Purchase intention | ||||||
| Guo et al., 2022 [ |
Way to success: Understanding top streamer’s popularity and influence from the perspective of source characteristics | Journal of Retailing and Consumer Services | E-commerce live streaming | Survey | 2 | Beauty, expertise, humor, and passion are all proved to be positively related to hedonic value, and both warmth and expertise are positively related to utilitarian value. |
| Streamer characteristics | ||||||
| Perceived value | ||||||
| Popularity | ||||||
| Le et al., 2021 [ |
Effects of negative reviews and managerial responses on consumer attitude and subsequent purchase behavior: An experimental design | Computers in Human Behavior | Negative reviews | Subject design | 4 | Findings provide managerial implications for the sellers in the shopping environment. |
| Review impression | ||||||
| Review diagnosticity | ||||||
| Managerial responses | ||||||
| Attitude-behavior relations | ||||||
| Category diagnosticity theory | ||||||
| Cabanillas et al., 2017 [ |
Factors that determine the adoption of Facebook commerce: The moderating effect of age | Journal of Engineering and Technology Management | Social networks | Online questionnaire | 52 | The results demonstrate that the social image, subjective norms, and usefulness determine the final intention of the users. |
| E-commerce | ||||||
| S-commerce | ||||||
| Digital marketing | ||||||
| Shi et al., 2022 [ |
Gamification in OTA platforms: A mixed-methods research involving online shopping carnival | Tourism Management | Gamification | Mixed-methods design | 4 | Four key gamification affordances contribute to tourists’ diverse value perceptions on the OTA platform, which impact their purchase intention. |
| Online travel agency (OTA) | ||||||
| Customer value | ||||||
| Online shopping carnival | ||||||
| Mixed-methods design | ||||||
| Aw et al., 2021 [ |
“Stop the unattainable ideal for an ordinary me!” fostering parasocial relationships with social media influencers: The role of self-discrepancy | Journal of Business Research | Social media influencers | Purposive sampling technique | 6 | Influence attempts, attractiveness, prestige, and expertise positively influence parasocial relationships, whereas parasocial relationships negatively influence perceived endorser motive, which in turn reduces purchase intention. |
| Parasocial relationships | ||||||
| Self-serving motive | ||||||
| Self-discrepancy | ||||||
| Gender | ||||||
| Number of followers | ||||||
| Pöyry et al., 2013 [ |
Can we get from liking to buying? Behavioral differences in hedonic and utilitarian Facebook usage | Electronic Commerce Research and Applications | Brand community | Literature reviews | 187 | The effects on variables closely linked to business performance are examined. |
| Online community | ||||||
| Social media | ||||||
| Social commerce | ||||||
| Hedonism | ||||||
| Utilitarianism | ||||||
| Chang et al., 2020 [ |
An elaboration likelihood model of consumer respond action to facebook second-hand marketplace: Impulsiveness as a moderator | Information & Management | Elaboration likelihood model | Questionnaire survey | 21 | The results of the data analysis indicated that consumers who process messages through the central route tend to respond to the post before initiating purchase intention. |
| Facebook second-hand marketplace | ||||||
| Impulsiveness | ||||||
| Product types | ||||||
| Yadav et al., 2017 [ |
Measuring consumer perception of social media marketing activities in e-commerce industry: Scale development & validation | Telematics and Informatics | Social media | Questionnaire survey | 83 | The study offers implications of perceived SMMA of e-commerce for academics and managers. |
| Social media marketing | ||||||
| Scale development | ||||||
| E-Commerce | ||||||
| E-Shopping | ||||||
| Zhang et al., 2021 [ |
Gamification and online impulse buying: The moderating effect of gender and age | International Journal of Information Management | Gamification | Online survey | 18 | The study provides new insights into the role of gamification in influencing consumer buying behavior in the online marketplace. |
| Impulse buying | ||||||
| Gender | ||||||
| Digital natives | ||||||
| Digital immigrants | ||||||
| Brand et al., 2022 [ |
Cultural differences in the perception of credible online reviews—The influence of presentation format | Decision Support Systems | Online reviews | Questionnaire survey | 12 | Differences occurred based on nationality, gender, and online shopping frequency. |
| Intercultural comparison | ||||||
| Presentation format | ||||||
| Review credibility | ||||||
| Benson et al., 2015 [ |
The role of security notices and online consumer behaviour: An empirical study of social networking users | International Journal of Human-Computer | Social media | Web-based research | 29 | No association between purchase experience, user victimization, and perception of security notices/features. |
| Security notices | ||||||
| Personal information privacy | ||||||
| Information security | ||||||
| Social learning | ||||||
| Jiao et al., 2020 [ |
Understanding users’ dynamic behavior in a free trial of IT services: A three-stage model | Information & Management | Free trial | Questionnaire survey | 1 | The perceived trial benefit and social influence strongly motivate user’s willingness to trial. |
| IT services | ||||||
| Learning motivation theory | ||||||
| Reference-dependent theory | ||||||
| Three-stage model | ||||||
| User behavior dynamics | ||||||
| Petcharat et al., 2021 [ |
A retentive consumer behavior assessment model of the online purchase decision-making process | Heliyon | Technology acceptance model | Questionnaire survey | 54 | The proposed model can be explained for the relationship with consistent E-Business platforms affecting purchase and re-purchase or recommend behaviors of online trading users on E-commerce, M-commerce, and S-commerce. |
| Online purchase decision | ||||||
| E-Business, E-commerce | ||||||
| M-commerce, S-commerce | ||||||
| Trust, Quality, Re-purchase | ||||||
| Recommend | ||||||
| Timoumi et al., 2022 [ |
Cross-channel effects of omnichannel retail marketing strategies: A review of extant data-driven research | Journal of Retailing | Retailing | Literature review | 2 | Adding an online channel may lead to cannibalization of offline sales. Offline channel has a complimentary effect. Mobile channel has a positive effect on the retailer’s overall performance. |
| Omnichannel | ||||||
| Cross-channel effects | ||||||
| Luceri et al., 2022 [ |
What drives consumers to shop on mobile devices? Insights from a Meta-Analysis | Journal of Retailing | Mobile shopping | Literature reviews | 1 | Companies should focus on both utilitarian and hedonic variables to stimulate the intention to use the mobile for the first time. |
| Retailing | ||||||
| Customer journey | ||||||
| Customer purchase behavior | ||||||
| Meta-analysis | ||||||
| Structural equation model | ||||||
| Fu et al., 2020 [ |
Investigating consumers’ online social shopping intention: An information processing perspective | International Journal of Information Management | Social shopping intention | Structural equation modeling (SEM) | 15 | The multiple-group analysis suggests that high product-involved consumers are motivated to exert more cognitive effort to evaluate the product information. |
| Informational social influence | ||||||
| Normative social influence | ||||||
| Heuristic-systematic model | ||||||
| Social interaction | ||||||
| Chopdar et al., 2022 [ |
Examining the role of consumer impulsiveness in multiple app usage behavior among mobile shoppers | Journal of Business Research | Stimulus-Organism-Response | Questionnaire survey | 1 | The findings apprise managers of the role of impulsiveness in encouraging split loyalty among mobile shoppers and prescribe new strategies for sustained use of shopping platforms. |
| Mobile shopping | ||||||
| Personalization | ||||||
| Hedonic | ||||||
| Motivation | ||||||
| Switching behavior | ||||||
| Hew et al., 2017 [ |
Crafting a smartphone repurchase decision making process: Do brand attachment and gender matter? | Telematics and Informatics | Smartphone repurchase intention | Quota sampling | 43 | Brand attachment is the most influential and relevant driver of consumers’ intention to repurchase smartphones from current brand. |
| Brand attachment | ||||||
| Gender differences | ||||||
| Gunawan et al., 2022 [ |
Examining the effect of radical innovation and incremental innovation on leading e-commerce startups by using expectation confirmation model | Procedia Computer Science | Strategic entrepreneurship | Electronic survey | 0 | The results show that perceived enjoyment and satisfaction engagement positively impact continuance intention |
| Radical innovation | ||||||
| Incremental innovation | ||||||
| Confirmation perceived | ||||||
| engagement continuance intention | ||||||
| Multi-sided platform | ||||||
| Goel et al., 2022 [ |
A moderated mediation model for e-impulse buying tendency, customer satisfaction and intention to continue e-shopping | Journal of Business Research | Customer satisfaction | Questionnaire survey | 0 | The findings show that the e-IB interacts with the website (first moderator) and stimulants and promotions (second moderator) to significantly influence the e-IB. |
| E-shopping | ||||||
| E-impulse buying | ||||||
| India | ||||||
| COVID-19 | ||||||
| Intention to continue |
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