Elsevier

Decision Support Systems

Volume 138, November 2020, 113383
Decision Support Systems

S-commerce: Influence of Facebook likes on purchases and recommendations on a linked e-commerce site

https://doi.org/10.1016/j.dss.2020.113383Get rights and content

Highlights

  • Facebook likes influence customers' purchases and recommendations on a linked e-commerce site.

  • Facebook-driven social commerce benefits from a high volume of likes.

  • Likes act as social proof, and attitude transfer hypothesis explains their inter-site impact.

  • A controlled laboratory experiment confirms the observed effect.

  • The volume of Facebook likes needs to be high to impact social commerce.

Abstract

Social networking site (SNS) driven e-commerce, the latest social commerce (s-commerce) phenomenon, gains prominence with the introduction of the call-to-action feature. The call-to-action feature on any sponsored post or advertisement on SNS redirects the user to a linked e-commerce website that offers the product. Information cues available on the SNS are expected to influence user decision making on the linked e-commerce site. Set in the context of Facebook driven e-commerce, this study explores how likes on Facebook influence user's purchase and recommendation decisions on a linked e-commerce website. Using controlled experiments we find that a higher volume of likes on Facebook leads to a higher likelihood of purchasing and recommending a product on the linked e-commerce site. This effect is found to be mediated by the user's initial product attitude formed on Facebook. An additional analysis examining the strength of the influence reveals that the mere presence of likes is not sufficient to impact the user's decision making. In fact, a low volume of likes elicits user behavior similar to absence of likes. The influence is effective only if the number of likes is substantially high. The findings of the study add to the s-commerce literature by establishing the inter-site influence of Facebook likes on user's purchase and post-purchase decisions and providing empirical evidence of the efficacy of SNS-driven e-commerce.

Introduction

Recently marketers have started leveraging social networking sites (SNSs) not only to promote their products but also to facilitate commercial transactions through the channel, giving a boost to social commerce (s-commerce). S-commerce, the newest paradigm of e-commerce, refers to the convergence of e-commerce and social networking sites that facilitates “the delivery of e-commerce activities and transactions via social media environment” [1]. SNSs such as Facebook, Pinterest, Instagram, etc., have extended their capabilities from merely hosting advertisements to providing avenues to carry out commercial transactions through their sites. The latest call-to-action (e.g., shop now, subscribe now) feature on sponsored posts and advertisements on SNSs is an example of the extended capabilities in this regard. The call-to-action feature redirects users from SNSs to a linked e-commerce site that sells the product, giving rise to SNS-driven e-commerce purchases. Users browsing their accounts on SNSs get exposed to advertisements or sponsored posts about products and services. After an initial evaluation of the products on the SNS they may choose to click on the call-to-action button to visit the linked e-commerce site where they can finally evaluate the product. The initial evaluation of the product on the SNS and the final evaluation of the product on the e-commerce site are expected to be impacted by the information cues available on the SNS.

One of the most common information cues on SNSs is one-click social cue such as like (on Facebook) or love (on Instagram).1 Although non-lexical or symbolic in nature [2], such one-click social cues convey positively connoted user opinion [3,4] and indicate user preference or interest [5] for the ‘liked’ item. Thus, it can serve as an indirect form of recommendation and act as a source of social influence [6,7]. Facebook like, a common form of one-click social cue, has gained a considerable amount of attention in the academic research recently. This is due to the fact that Facebook is the most popular SNS among individuals and organizations [8,9]. As of 2020, Facebook has more than 1.7 billion daily active users accounting for 37% of global internet users.2 It is also a popular medium among marketers with more than 86% of marketers in the US using Facebook for advertising in 2019.3 Due to its popularity in practice, academic research has started showing interest in understanding the role of Facebook likes in users' perceptions and actions, particularly in users' consumption decisions [6,[10], [11], [12], [13], [14], [15], [16]]. However, several gaps still exist in this field of knowledge.

First, the role of Facebook likes in user decision making in inter-site setting such as SNS-driven e-commerce has not been investigated. Most of the existing studies have investigated the effects of likes for intra-site purchases only, i.e., display of likes and users' purchasing decisions are restricted to the same platform, e.g., a retailer's website [10], or a group buying website [6]. However, in reality, users often come across likes on a product on Facebook but make the final purchase decision on a different site. Therefore, it is important to examine whether Facebook likes exert any influence in inter-site settings. Second, the findings of prior studies are contradictory with some claiming significant positive effect of likes on users' consumption decisions [6,10,13,17], while some questioning its effectiveness in persuading users (e.g., [14]). Third, most of the previous studies have merely established association between the number of likes and sales [6,15], without providing any evidence about the causal effects of likes on the outcomes. Finally, studies have primarily looked into the influence of likes on individuals' purchasing behavior only [6,12,15,17], overlooking individuals' social sharing behavior (e.g., spreading word of mouth, recommending a product to others, etc.) which is an important aspect of s-commerce [18,19]. To address these gaps, in this study we investigate the causal effects of likes on Facebook on purchases and product recommendations on a linked e-commerce site, delineating the inter-site influence of likes on user decision making. Thus, this becomes one of the few studies to empirically examine the causal influence of social cues on e-commerce purchases, thereby assessing the value of s-commerce. Also, to the best of our knowledge, this study is a novel attempt to identify the inter-site influence of social cues by simulating the real s-commerce phenomenon of Facebook-driven e-commerce. Specifically, we seek to answer the following research questions:

In SNS driven e-commerce, how do likes on SNS influence user's product evaluation on the SNS itself? How do likes on SNS influence a user's decision to visit the linked e-commerce site that offers the product? In SNS driven e-commerce, how do likes on SNS influence a user's final decision to purchase and recommend4 a product on a linked e-commerce site that offers the product?

We theorize our study based on the social proof heuristic, a psychological phenomenon in which individuals' decisions are impacted by preferences and behaviors of peers [20,21], and the attitude transfer hypothesis [22], a theory that expounds how individuals' attitudes get transferred from one entity to another related entity. Combining the concepts of social proof and attitude transfer we posit that users' initial product attitude on Facebook, their intention to visit the linked e-commerce site, and their final purchase and recommendation decisions on the e-commerce site will be positively shaped by Facebook likes. The conceptual model of our research is presented in Fig. 1.

Using controlled experiments, we substantiate the findings of extant research by establishing a positive causal influence of Facebook likes and the outcomes. We find that likes on Facebook exert a significant and positive inter-site influence on users' likelihood to purchase and recommend a product on the linked e-commerce site. The influence of likes on users' final decisions (to purchase and to recommend) on the e-commerce site are found to be mediated by the initial product attitude formed on Facebook. Additionally, we conduct a post-hoc study to determine whether SNS driven e-commerce provide any considerable leverage to the marketers as compared to direct e-commerce.5 Hence, we compare the results of our main experiment with the results of a baseline experiment that captures users' likelihood of purchase and likelihood of recommendation when visiting the e-commerce site directly. We find that both outcomes are significantly higher in case of SNS driven e-commerce transactions than direct e-commerce transactions if the volume of likes is substantially high. In case of a low volume of likes, there is no significant difference between SNS driven e-commerce and direct e-commerce.

In terms of theoretical contributions, our study establishes the inter-site influence of Facebook likes in shaping users' decision to purchase and recommend a product on a different site. Specifically, it demonstrates the causal impact of Facebook likes on users' attitude towards a product not only on the same website (i.e., Facebook), but also on a separate yet related website (i.e., the linked e-commerce site). It also contributes to the literature by combining the concepts of attitude transfer and social proof to explain the inter-site influence of social cues. Further, by comparing SNS driven e-commerce to direct e-commerce purchases, the study provides empirical evidence about the role of s-commerce. It offers insights on the strength of Facebook likes and add to the literature on likes and other types of one-click social cues. From a practitioner's point of view, our study examines the effectiveness of likes in SNS driven e-commerce and provides implementable insights to marketers who are contemplating to advertise their offerings on SNSs. The findings of the research can help them devise effective means of attracting more traffic to the linked e-commerce sites and maximizing sales.

Section snippets

Literature review

A thorough review of existing literature reveals the relationship between Facebook likes and users' product evaluation and consumption decisions in different online settings. Prior studies have reported a positive association between Facebook likes received on deals on group buying websites and their quantity of sales [6,15], a positive effect of likes on product's quality perception [10], brand evaluation and purchase likelihood [23,24], also and a positive effect of likes on consumers'

Theoretical background

The theoretical foundation of our study is based on the concepts of social proof [21] and attitude transfer [22]. The central tenet of this study is that a social cue such as Facebook like acts as a social proof that positively impacts users' perceptions and actions including their inter-site purchase and recommendation decisions. Further the transference of this influence of likes from Facebook to another site (the linked e-commerce site) is mediated by the initial product attitude formed on

Effect of likes on product attitude on Facebook and likelihood of purchase on a linked e-commerce site

According to the social proof heuristic, individual's perceptions and actions are influenced by the opinions and actions of others [20,21]. For example, the effect of e-WoM on sales of movie tickets [37], sales of digital microproducts [38], etc. Facebook likes being a form of peer opinion [6] can act as social proof and influence prospective buyers. The fact that likes are provided by real users, some of them being familiar sources such as friends and acquaintances, further strengthens the

Research methodology

Existing research has predominantly used secondary data for examining the influence of likes (e.g., [6,15,17]), that has weaker causal claims. To establish causality and increase the accuracy of conceptualization of constructs, we conducted scenario-based controlled experiments, as used in many previous studies (e.g., [43,44]). A randomized controlled experiment is the best method to establish causality as it minimizes the problems created by confounding variables and self-selection bias6

Manipulation checks

To check whether our manipulation had worked as intended, we asked the participants questions regarding their perception about the number of Facebook likes: “According to you the number of likes the product got on Facebook is:” (1 = “Extremely low” to 7 = “Extremely high”). The perception about aggregated product rating was also captured using the question: “According to you the rating of the product is:” (1 = “Extremely low” to 7 = “Extremely high”). A comparison of mean values using a t-test

Additional analysis

As an extension to our main study we verified whether individuals showed any differences in their decision making about e-commerce facilitated by Facebook and e-commerce by visiting the site directly. To accomplish this, we needed to measure likelihood of purchase and likelihood of recommendation in case of a direct visit to an e-commerce site, which constituted the baseline condition. In a separate experimental setting, a group of 24 respondents were randomly assigned to one of the two

Summary of results

SNS driven e-commerce has given rise to the possibility of users' purchase decisions getting impacted by likes on the SNS. In this study, we theorize and test the effect of likes on Facebook on users' product attitude on Facebook, and purchase and recommendation decisions in a linked e-commerce site. The results indicate that Facebook likes exert a positive inter-site influence on users' likelihood of purchase and recommendation on the linked e-commerce site, through the initial product

Authors contribution

The authors do not wish to include any author contribution statement for the paper.

Acknowledgments

The second author gratefully acknowledges the support received from the Indian Institute of Management Calcutta in the form of a Category I grant with work order number RP:ITRRLROCC/3809/2019-20 for conducting this research.

Samadrita Bhattacharyya holds a PhD in Management Information Systems from the Indian Institute of Management Calcutta. She holds B.Tech in Electronics and Communication Engineering from West Bengal University of Technology and M.Tech in VLSI Design from Indian Institute of Engineering Science and Technology Shibpur. Her research interests include social commerce, online reviews, online communities, and data analytics. Her research articles have appeared in Journal of Management Information

References (64)

  • N. Hajli et al.

    A social commerce investigation of the role of trust in a social networking site on purchase intentions

    J. Bus. Res.

    (2017)
  • C. Oh et al.

    Beyond likes and tweets: consumer engagement behavior and movie box office in social media

    Inf. Manag.

    (2017)
  • J. Braojos et al.

    How do social commerce-IT capabilities influence firm performance? Theory and empirical evidence

    Inf. Manag.

    (2019)
  • X. Zheng et al.

    Capturing the essence of word-of-mouth for social commerce: assessing the quality of online e-commerce reviews by a semi-supervised approach

    Decis. Support. Syst.

    (2013)
  • S. Wang et al.

    Congruity’s role in website attitude formation

    J. Bus. Res.

    (2009)
  • G.C.C. Shen et al.

    Effective marketing communication via social networking site: the moderating role of the social tie

    J. Bus. Res.

    (2016)
  • L. Qiu et al.

    Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: the moderating role of review valence

    Decis. Support. Syst.

    (2012)
  • N. Hu et al.

    Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales

    Decis. Support. Syst.

    (2014)
  • V. Sadovykh et al.

    Do online social networks support decision-making?

    Decis. Support. Syst.

    (2015)
  • V. Sadovykh et al.

    Do decision-making structure and sequence exist in health online social networks?

    Decis. Support. Syst.

    (2015)
  • C.M.K. Cheung et al.

    Do actions speak louder than voices ? The signaling role of social information cues in in fl uencing consumer purchase decisions

    Decis. Support. Syst.

    (2014)
  • S. Piramuthu et al.

    Input online review data and related bias in recommender systems

    Decis. Support. Syst.

    (2012)
  • J. Benitez et al.

    IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: the moderator role of social media capability

    Inf. Manag.

    (2018)
  • T. Liang et al.

    Introduction to the special issue social commerce: a research framework for social commerce

    Int. J. Electron. Commer.

    (2011)
  • J. Xu et al.

    Effects of symbol sets and needs gratifications on audience engagement: contextualizing police social media communication

    J. Assoc. Inf. Syst.

    (2019)
  • I. Heimbach et al.

    The impact of sharing mechanism design on content sharing in online social networks

    Inf. Syst. Res.

    (2018)
  • K. Lee et al.

    Thumbs up, sales up? The contingent effect of Facebook likes on sales performance in social commerce

    J. Manag. Inf. Syst.

    (2015)
  • V. Schöndienst et al.

    Like versus dislike: how Facebook’s like-button influences people’s perception of product and service quality

  • J.C. Wang et al.

    The impacts of online lightweight interactions as signals

  • S. Dewan et al.

    Popularity or proximity: characterizing the nature of social influence in an online music community

    Inf. Syst. Res.

    (2017)
  • L. John et al.

    Does “liking” lead to loving? The impact of joining a brand’s social network on marketing outcomes

    J. Mark. Res.

    (2017)
  • X. Li et al.

    Measuring effects of observational learning and social-network word-of-mouth (WOM) on the sales of daily-deal vouchers

  • Cited by (45)

    View all citing articles on Scopus

    Samadrita Bhattacharyya holds a PhD in Management Information Systems from the Indian Institute of Management Calcutta. She holds B.Tech in Electronics and Communication Engineering from West Bengal University of Technology and M.Tech in VLSI Design from Indian Institute of Engineering Science and Technology Shibpur. Her research interests include social commerce, online reviews, online communities, and data analytics. Her research articles have appeared in Journal of Management Information Systems, Decision Support Systems, and Information & Management. She presented her work in reputed conferences such as Hawaii International Conference on System Sciences, Australasian Conference on Information Systems, and Workshop of e-Business. At present she is Assistant Professor of IS & Analytics in Jindal Global Business School of O.P. Jindal Global University.

    Indranil Bose is Professor of Management Information Systems at the Indian Institute of Management, Calcutta (IIMC). He acts as the Chairperson of Doctoral Programs at IIMC He was the Founder and Co-ordinator of IIMC Case Research Centre from 2012-2020. He holds a BTech from the Indian Institute of Technology Kharagpur, MS from the University of Iowa, and MS and PhD from Purdue University. His research interests are in business analytics, digital transformation, information security, and management of innovation. His publications have appeared in MIS Quarterly, Journal of MIS, Communications of the ACM, Communications of AIS, Computers and Operations Research, Decision Support Systems, Electronic Markets, Ergonomics, European Journal of Operational Research, Information & Management, International Journal of Production Economics, Journal of Organizational Computing and Electronic Commerce, Journal of the American Society for Information Science and Technology, Operations Research Letters, Technological Forecasting and Social Change, etc. He serves as Senior Editor of Decision Support Systems and Pacific Asia Journal of AIS, and as Associate Editor of Communications of AIS, Information & Management, and Journal of AIS.

    View full text