Hidden Semi-Markov Model-Based Reputation Management System for Online to Offline (O2O) E-Commerce Markets

Published at Decision Support Systems

36 Pages Posted: 2 Aug 2018

See all articles by Shengsheng Xiao

Shengsheng Xiao

Shanghai University of Finance and Economics

Ming Dong

Goethe University Frankfurt

Date Written: July 1, 2012

Abstract

The rapid development of information technology enables an increasing number of consumers to search and book products/services online first and then to consume them in brick-and-mortar stores. This new e-commerce model is called Online to Offline (O2O) e-commerce and has received significant managerial and academic attention. Compared with many extant e-commerce models (i.e., B2B, B2C and C2C), reputation management in this emerging model needs some improvement. It has to collect more raw reputation-related data, consider more reputation-related factors and show more comprehensive reputation evaluation results. As a stepping-stone in the research in O2O e-commerce, a new reputation management system (HSMM-RMS) has been developed based on a probabilistic model called the Hidden Semi-Markov Model. By combining observable online and offline raw reputation information, the proposed system can accurately, promptly and dynamically provide O2O e-commerce participants with offline merchants’ historical and predictive reputation information. Our Monte-Carlo simulation experiments indicate that the proposed system performs significantly better than the extant Hidden Markov Model-based reputation management system. A case study based on a real O2O e-commerce platform demonstrates the real application of HSMM-RMS. It also shows that the proposed system can provide a realistic solution for reputation management in the O2O e-commerce market.

Keywords: Online to Offline E-commerce; Reputation Management System; Hidden Semi-Markov Model

Suggested Citation

Xiao, Shengsheng and Dong, Ming, Hidden Semi-Markov Model-Based Reputation Management System for Online to Offline (O2O) E-Commerce Markets (July 1, 2012). Published at Decision Support Systems, Available at SSRN: https://ssrn.com/abstract=3213822

Shengsheng Xiao (Contact Author)

Shanghai University of Finance and Economics ( email )

No. 100 Wudong Road
Shanghai, Shanghai 200433
China

Ming Dong

Goethe University Frankfurt ( email )

Grüneburgplatz 1
Frankfurt am Main, 60323
Germany

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