Fuzzy-Based Trust Model to Evaluate Customer Trust towards Online SNSs Sellers

Ramona Ramli Et.Al

doi:10.17762/turcomat.v12i3.1025

Abstract

The rapid growth of Social Networking Sites (SNSs) as business platforms for individual or small sellers recognised trust as the main important role in determining the successful execution of their business operation.Current trust modelfocused in business sellers by considering website as one of the trust factors. However, these model are not applicable for SNSs environment. Based on the identified factors affecting trust in SNSs environment, this paper proposeda fuzzy-based trust model to evaluate customers‘ trust based on their perception and experiences.The evaluation model was then tested to validate its efficiency in evaluating trust level.

Highlights

The Social Networking Sites (SNSs) are a kind of disruptive technology for communication that has gone beyond conventional means of social interaction (Noordin et al, 2018)
The increasing number of cases of scams reported by the Australian Competition and Consumer Commission shows that consumers in that country have lost over $500 thousands in 2019 to scams on online shopping via social media platforms (Australia Competition and Consumer Comission, 2019)
Based on the levels obtained in first layer, the trust level is evaluated in the second level that consists of the four modules which is ElectronicWord of Mouth (E-WoM), Social Commerce Construct, Information Quality and People

Summary

Introduction

The Social Networking Sites (SNSs) are a kind of disruptive technology for communication that has gone beyond conventional means of social interaction (Noordin et al, 2018). Majority of the study on trust focus on business sellers (B2C) where businesses sell products to consumers with the aid of user ratings and reviews (Hawkins, 2019) This is due to the development of business models and technologies shift is not parallel with the enforcement of consumer law, for individual businesses who are sellers and consumers (i.e., C2C) at the same time over SNSs. Little studies focus on C2C on SNSs despite the growing concern towards trust, resulting customers having less trust toward individual sellers than toward large established firms (Wongkitrungrueng and Assarut, 2018). The increasing number of cases of scams reported by the Australian Competition and Consumer Commission shows that consumers in that country have lost over $500 thousands in 2019 to scams on online shopping via social media platforms (Australia Competition and Consumer Comission, 2019) This statistic reveals that transactions via SNSs are prone to risks and the current law enforcement is inadequate in protecting consumers (Lee, 2016; Riefa, 2019). Result from the validation will indicates the accuracy and effectiveness of the proposed model

Fuzzy Based Trust Model

Formation of Fuzzy Rules

Simulation of Fuzzy Logic Controller

Validation Of The Fuzzy Based Model

Findings

Conclusion