Customer engagement behaviour on social commerce platforms: An empirical study

2021 ◽  
Vol 64 ◽  
pp. 101437 ◽  
Author(s):  
Abdelsalam H. Busalim ◽  
Fahad Ghabban ◽  
Ab Razak Che Hussin
2021 ◽  
pp. 1-27
Author(s):  
Robert Cutshall ◽  
Chuleeporn Changchit ◽  
Huong Pham ◽  
Dung Pham

2020 ◽  
Vol 7 (12) ◽  
pp. 711-720
Author(s):  
Arief RAHMAN ◽  
Refika Nurliani FAUZIA ◽  
Sigit PAMUNGKAS

Author(s):  
Zhenyuan Liu ◽  
Shuihua Han ◽  
Chao Li ◽  
Shivam Gupta ◽  
Uthayasankar Sivarajah

Author(s):  
Robin Cheng

This chapter focused on exploring the engagement in which consumers interact with each other while conducting online shopping activities, such as discovering products, sharing product information, and/or collaboratively making shopping decisions. At the core of the product/service offering, successful shopping models will be able to meet the needs of highly engaged shoppers. In order to develop sustainable shopping model for this group of shoppers, social support theory could explain the current phenomenon of the use of social media for shopping. The social media technologies facilitated collaborative learning and collaborative improvement on the sale of unconventional and innovative products. The chapter contributes in social commerce innovations and provides managerial implications for understanding the overall interactions of social commerce.


2018 ◽  
Vol 31 (2) ◽  
pp. 595-614 ◽  
Author(s):  
Vidyasagar Potdar ◽  
Sujata Joshi ◽  
Rahul Harish ◽  
Richard Baskerville ◽  
Pornpit Wongthongtham

Purpose The purpose of this paper is to develop and empirically test a process model (comprising of seven dimensions), for identifying online customer engagement patterns leading to recommendation. These seven dimensions are communication, interaction, experience, satisfaction, continued involvement, bonding, and recommendation. Design/methodology/approach The authors used a non-participant form of netnography for analyzing 849 comments from Australian banks Facebook pages. High levels of inter-coder reliability strengthen the study’s empirical validity and ensure minimum researcher bias and maximum reliability and replicability. Findings The authors identified 22 unique pattern of customer engagement, out of which nine patterns resulted in recommendation/advocacy. Engagement pattern communication-interaction-recommendation was the fastest route to recommendation, observed in nine instances (or 2 percent). In comparison, C-I-E-S-CI-B-R was the longest route to recommendation observed in ninety-six instances (or 18 percent). Of the eight patterns that resulted in recommendation, five patterns (or 62.5 percent) showed bonding happening before recommendation. Research limitations/implications The authors limited the data collection to Facebook pages of major banks in Australia. The authors did not assess customer demography and did not share the findings with the banks. Practical implications The findings will guide e-marketers on how to best engage with customers to enhance brand loyalty and continuously be in touch with their clients. Originality/value Most models are conceptual and assume that customers typically journey through all the stages in the model. The work is interesting because the empirical study found that customers travel in multiple different ways through this process. It is significant because it changes the way the authors understand patterns of online customer engagement.


2021 ◽  
Vol 1 (3) ◽  
pp. 8-13
Author(s):  
Saisai Qiao ◽  
Jie Wei

As a new type of business model, social commerce has attracted more attention. we propose a model to explore the factors influencing customer engagement by using the two-factor theory, as well as the effect of customer engagement on subsequent participation behavior. The results show that both social support and self-congruence have a positive impact on customer engagement, while perceived engagement risk and perceived commerce risk have a significant negative impact on customer engagement, moreover, customer engagement is positively related to social sharing and purchase intention. In addition, this paper verifies the comparative effect of social commerce platforms. The results show that there are significant differences in social support and self-congruence between e-commerce and social media platforms.


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