Research examines how online social networking and social media improve business performance
Dr. Shan Wang (PhD) is an Associate Professor of Finance and Management Science at the Edwards School of Business. Her research explores the relationship between online social networking and business performance in the areas of electronic and social commerce, and digital innovation and transformation. She was a recipient of the Social Sciences and Humanities Research Council of Canada (SSHRC) Insight grant for her research project entitled: “Online social networking and social commerce performance: an ego network perspective.”
Q: What is the big question you are trying to answer?
My big question asks: how does online social networking and social media improve business performance?
Studying the relationship between online social networking and business performance is my major research area of interest. I have several ongoing projects in this stream including a project studying how social networking functionalities in online product communities can help improve small and medium sized sellers’ performance in social marketplaces. Social marketplaces are electronic marketplaces that offer rich social IT artefacts and functionalities to enrich customer experience and enhance social enjoyment while shopping online.
In a second project, I am studying how social networking in a merchants’ online community enhances sellers’ performance in business-to-business electronic marketplaces. I recently launched another project to study how social networking improves the performance of users in a 3D printing community. In this research I try to answer whether and how online social networking improves users’ innovation performance in the community.
Q: What drew your interest to this research area?
A: This current research area is a natural extension of the research that I have done for the past decade. Previously my main research interest was electronic and social commerce and grew into understanding how electronic commerce is enriched by social IT artefacts. There are many network analyses of online social networks in the fields of social science, computer science, and communications, however, this is underexplored in the field of electronic commerce despite the rise of online sellers using social networking. Uncovering managerial knowledge through the analysis of online social network structures is important and offers practical value to organizations.
Q: What are the key findings and outcomes of your research?
A: There are some interesting findings and outcomes from my research. For example, I have studied the following behavior of sellers in online product communities. While we observed robust results from the literature which indicate that following others in an online product community hurts sellers’ performance in social marketplaces, our research suggests otherwise. Our findings show that when we create gaps or disconnections which are called “structural holes” between groups (sellers and buyers or “followees”) in an online social networking selling community, it can positively contribute to a seller’s performance. This result occurs because gaps enable sellers to access new (non-redundant) information in the social network efficiently. The impact is stronger for sellers who have greater product diversity, more prominent followees, and when sellers and buyers in the seller’s followee network are less connected. I have one paper in progress in collaboration with Dr. Fang Wang from Wilfrid Laurier University that report on this research.
In another work in progress, we studied the follower network of sellers. The follower network is considered a seller’s most important digital asset in an online community since it is easy to convert followers into real customers and the number of followers a seller has is also found to positively contribute to a seller’s performance. Our research went one step further to investigate the structure of a seller’s follower ego network, referring to local networks with one central node, and we found that ego networks with certain structures such as high density and high centralization actually create a structural liability for sellers. This shows that sellers should avoid building and maintaining online follower networks with these structural properties.
Q: How can your research results inform best practices for online selling communities?
A: My research offers important social intelligence for e-commerce sellers, social media marketing practitioners, and individuals involved with social commerce platforms. For instance, one main recommendation is that e-commerce sellers and social media marketing practitioners should add social network structure metrics into their dashboards. Similarly, social commerce platforms could be enhanced by providing key social network structure metrics such as structural hole, density, and centralization as part of their data analysis service to sellers that could improve business performance. The platforms can provide these metrics either in the form of summary statistics of network metrics or network visualization. As far as we know, few platforms to date provide business intelligence embedded in the social network structure and would be of great value to online selling communities.
Q: Do you have any research collaborations on this topic?
A: Research collaboration is very important. The research projects in this area require a long chain of data collection, cleaning, storage, transformation, and analysis. I work with two students from the department of computer science at the University of Saskatchewan who are helping me with the data collection and storage. I also collaborate with Dr. Fang Wang from Wilfrid Laurier University who has expertise in both information system and marketing research. We plan to extend our research team by collaborating with additional researchers with relevant expertise and aim to train more students in this emerging and exciting area of research.
Q: Were there any challenges you encountered with researching this emerging area?
A: The challenge of this research is from data collection and data analysis. This research requires tracking both e-commerce operational data and users’ social networking behavior data. The two types of data are extremely discrete and dynamic, which make it hard to collect, store and process. I would like to take this opportunity to thank Edwards IT support for their great help in supporting my computing needs during this research process. For my current SSHRC funded project on online product communities, once the dataset is built, it will enable nice outcomes.
Q: How has COVID-19 impacted your research?
A: COVID-19 brings both opportunities and challenges to my research. With COVID-19, people increasingly relied on electronic commerce for shopping and social media for information acquisition and socialization which allowed for more research in this area. There are also innovative uses of IT. For example, in one of our research projects on open innovation, we studied a case of a large-scale hackathon that aimed to generate and discover new ideas in combating COVID-19. This phenomenon is significant both in terms of the number of people involved, and the innovative use of free, cloud based social IT artefacts to support the event. Our paper, Learnings and Implications of Virtual Hackathon, on this research is currently published in Journal of Computer Information Systems.
COVID-19 also disrupted my research routine to some degree. I found that if a research computer needs to be fixed, it can take much longer to recover it due to restrictions and increased wait times. With the majority of conferences being held virtually there has been less direct interaction with peers, and site visits to companies are not feasible due to travel restrictions.
Q: What is your research “success story” and what contributions are you most proud of?
A: For my research on electronic and social commerce, I have won four major national research grants, worked with giant e-commerce companies in China such as Alibaba and JingDong as well as many small and medium sized e-commerce companies, and published in A* level journals. Beyond these achievements, I am proud to have developed the ability to use multi-methods to probe the phenomenon of e-commerce and social commerce, including case research, survey research, content analysis, textual analysis and network analysis, and enhanced my ability to organize research projects. It is hard to say “success story” but good research takes time to cultivate, and so does “success”. From my perspective, learning how to develop a successful project is the most important thing and no two projects are the same.
Funding acknowledgment: Social Sciences and Humanities Research Council (SSHRC) and National Natural Science foundation of China (NSFC)
To learn more about Shan Wang’s work, check out her profile page!
Publication highlights
Wang, S., William, Y., Jie, R., & Alvin, L. (2021). Learnings and Implications of Virtual Hackathon. Journal of Computer Information Systems, pp1-13, DOI: 10.1080/08874417.2020.1864679.
Pei, Y., Wang, S., & Archer, N. (2021). Reputation, Familiarity, and Use Intention for E-payment Services: A Comparison of Pure-Play and Click-and-Mortar E-payment Services. International Journal of Services Technology and Management; 27 (1/2): 72-103.
Wang, S., & Wang, F. (2020). Network prominence in social marketplace and e-store performance: A nuanced typology and empirical evidence. Electronic Commerce Research and Applications, 43 (September–October), 1-12.
Lee, A. S.-H., Wang, S., Yeoh, W., & Ikasarid, N. (2020). Understanding the Use of Knowledge Sharing Tools. Journal of Computer Information Systems, pp. 1-12.
Wang, S., Yeoh, W., Richards, G., Fan, W. S., & Chang, Y. H. (2019). Harnessing business analytics value through organizational absorptive capacity. Information & Management, 56(7), 103152.
Wang, S., Wang, Y., & Archer, N. (2018). The co-evolution of IT competence, organisational agility and entrepreneurial action: a case study of entrepreneurial e-tailers. International Journal of Networking and Virtual Organisations, 18(1), 1-29.
*Wang, S., Cavusoglu, H., & Deng, Z. (2016). Early mover advantage in an industry with low entry barrier: Evidence from e-tailers on third party e-commerce platforms. Information & Management, 53(2), 197-206.
*Wang, S. & Cavusouglu, H. (2015). Small and medium sized manufacturer performance on third-party B2b electronic marketplaces: The role of enabling and IT capabilities. Decision Support Systems, 79(November), 184-194.
Wang, Y., *Wang, S., Fang, Y., & Chau, P. (2013). Store survival in online marketplaces: An empirical investigation. Decision Support Systems, 56(December), 482–493.
Wang, Y., Qu, Z., *Wang, S., & Zhang, Y. (2013). Implications of online social activities for e-tailers’ business performance. European Journal of Marketing, 47(8), 1190-1212.