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Title: Impact of Online Social Information on Consumer Behavior in Social Commerce Environment
Authors: Bhattacharyya, Samadrita
Bose, Indranil (Supervisor)
Keywords: E-retailers
Social commerce
Social behaviour
Consumer behaviour
Management Information System
Issue Date: 2020
Publisher: Indian Institutte of Management Calcutta
Abstract: Widespread adoption and popularity of social media and social networking sites, along with their immense commercial potential, are changing the ways of conducting businesses. At present e-commerce is going through an evolution where e-retailers are harnessing the advantages of social media to move beyond just selling their products and services. They are using social media and social networking sites to have wider reach to their consumer base, promote and advertise their offerings, receive feedback from customers, and co-create products and services. Consumers are also enjoying greater sense of empowerment with the shift of bargaining power from sellers to buyers (Hajli & Sims, 2015). They have access to opinions and actions of other consumers including their friends and acquaintances. Along with that, being able to share their own opinions, recommendations and referrals, provides them a sense of belongingness to a community. It also provides gratification from heightened social presence. These opportunities have led to social commerce (s-commerce), the newest paradigm of e-business that marks the convergence of e-commerce and social networks. E-commerce giants such as Amazon and e-Bay have enabled their websites with social elements such as likes, reviews, referrals, facilities to create and share wish-lists, share purchase information, etc. They allow consumer interaction and networking (Wang & Zhang, 2012). On the other hand, leading social networking sites such as Facebook, Instagram and Pinterest are augmenting their capabilities to enable commercial transactions: from retailers launching their social media pages (Busalim & Hussin, 2016) to the latest feature of ‘direct buying’ (e.g., ‘buy’ pins in Pinterest, ‘shop now’ in Facebook) for direct purchase of products from social media platforms. These are typical examples of s-commerce. With its growing popularity, s-commerce has drawn significant attention of academic research (especially in Information Systems and Marketing) in the recent past. Researchers have concentrated on a wide variety of themes, such as adoption of s-commerce, economic value of s-commerce, website design and technological features of s-commerce, user behavior in s-commerce, electronic word of mouth, implications of s-commerce activities, risk and security issues in s-commerce, etc. (Busalim & Hussin, 2016). There are several competing definitions of s-commerce in literature. However, it essentially refers to the “exchange-related activities taking place between and are influenced by social network users in a computer-mediated environment, where activities correspond to need-recognition, pre-purchase, purchase and post-purchase stages of a focal exchange” (Yadav et al. 2013). Despite its recent growth, research in this field is still fragmented with several avenues yet to be explored. What demarcates s-commerce from classical e-commerce is the social element of s-commerce. In an s-commerce environment social interaction is of paramount importance and the information shared through the social exchange plays a pivotal role in the sustenance and success of the ecosystem (Hajli, 2015). Information that results from the social interactions in s-commerce context are referred to as online social information. Marketers heavily bank on online social information to influence consumers’ commercial and social behavior on s-commerce platforms. To receive user feedback and facilitate active users’ social interaction and communication, s-commerce platforms provide various features such as review and rating tools, comment and chat boxes, ‘like’, ‘share’ and ‘favorite’ buttons, etc (Gonçalves Curty & Zhang, 2013; Huang & Benyoucef, 2013). Furthermore, in some cases s-commerce websites have features for tracking user activities on the platform to gather insights about user behavior and projecting market trends. They also display the information related to user behavior on websites to influence other users (Gonçalves Curty & Zhang, 2013). Thus, s-commerce witnesses a plethora of social information cues, independently or simultaneously influencing user decision making. Despite a considerable amount of research in the specific area of online social information in s-commerce, it is quite nascent with different studies concentrating on bits and pieces of different s-commerce information. Thus, there exists a gap in the holistic understanding of the domain, including its definition, scope, and boundaries. Furthermore, major portion of the existing research is confined to the conventional type of e-WOM, i.e., ratings and online reviews. Research on ratings and online reviews in s-commerce is further supplemented by a voluminous body of research on the same under the purview of traditional e-commerce making it an over-studied area. Only a few studies have discretely focused on alternate sources of social information, such as social media cues (Facebook likes, Google+ +1, etc.) and information generated by fellow consumers’ actions or behaviors. In this dissertation we try to address the gaps by first defining the term online social information in s-commerce and then investigating the effects of different types of online social information on users’ purchase decisions under different s-commerce settings. The dissertation is divided into three parts. In the first part, we define online social information in s-commerce ecosystem based on review of past literature. Next, we identify and classify prevalent online social information into two groups depending on their mode of creation: peer opinion-based and peer behavior-based. We further divide each class into two subclasses according to their relationship with actual s-commerce sales: direct and indirect. We also map real s-commerce social cues to each of these classes and compare them based on their advantages and limitations. Thus, we contribute to s-commerce literature by providing a comprehensive understanding of the area. In the second part of the dissertation, we investigate the impact of Facebook likes on s-commerce users’ purchase and recommendation decisions using controlled experiments. We use the context of our study as social network driven e-commerce transactions. We find that Facebook likes exert positive influence on users’ purchase and recommendation likelihood on a linked e-commerce site. The effect of likes is mediated by the product attitude formed on Facebook, indicating a transfer of attitude across websites. We also find that like acts as an effective information cue when its number is sufficiently high, underscoring the significance of not only the presence but also the volume of Facebook likes. In the third part, we investigate the joint role of two behavior-based social information cues (i.e., peer purchase information and peer bookmarking information) on a product’s purchase likelihood. The timing of the purchase sets the context. We find that concurrent information involving high peer purchase volume and low peer bookmarking volume leads to higher purchase likelihood of a product in case of immediate purchases than distant purchases. However, concurrent information involving low peer purchase volume and high peer bookmarking volume leads to similar purchase likelihood both immediate and distant purchases. The results indicate differential preference of information cues based on purchase temporality in s-commerce. This study also explicates the signalling role of behavior-based information cues. This dissertation contributes to the expanding body of research on s-commerce by defining and classifying online social information in s-commerce, and then examining the impact of different types (opinion-based and behavior-based) online social information cues on two most important s-commerce outcomes: social buying and social sharing. The findings emphasize the importance of alternate types of social information cues, such as social media cues (e.g. Facebook likes) and users’ behavior-based information cues (e.g., purchases and wishlists) on s-commerce purchase decisions and expand our understanding beyond conventional forms of e-WOM, i.e., ratings and online reviews. The dissertation also provides practical insights to the marketers and s-commerce website managers to harness the power of online social information, and accordingly devise strategies to increase footfalls to their websites and thus increase sales.
Description: Call No: 658.4038 BHA
Accession No. TH245
Physical Description: xviii, 190p. ; 30cm
Subject Area/Academic Groups: Management Information System
Members, DPR Committee: Indranil Bose, Somprakash Bandhopadhyay, Sipra DasBit, Shubhamoy Dey
Chairperson: Bodhibrata Nag
Appears in Collections:Management Information Systems

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