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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Predicting Online Customer Shopping Behavior

Predicting Online Customer Shopping Behavior
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Author(s): Fan Zhao (University of Nebraska, USA) and Sagar S. Kulkarni (MedPlus a Quest Diagnostics Company, USA)
Copyright: 2006
Pages: 4
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch233
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

Business-to-consumer (B2C) is the most common online business type, which attempts to reach individual consumers. Compared to the brickand- mortar environment, the use of the Internet for business-to consumer transactions presents obvious advantages. The openness of the Internet creates opportunities for virtually all companies ranging from small start-ups to Fortune 100 companies. In particular, it allows companies to offer direct sales to their customers through an electronic channel (Hoffman, et al, 1996). In the bricks-and-mortar stores, sales people are hired to distinguish shoppers and to stimulate their maximum consuming desire based on their in-store behavior. When shoppers show special interest in some specific product, sales people will help them find what they are looking for. In other cases, for shoppers who are merely window shopping, sales person can recommend some product to entice their shopping appetence. However, in the virtual shopping environment, there is no sales person to perform this role. Therefore, to understand consumer behavior in virtual stores is very important for online business. This research aims to provide theoretical analysis to explain consumers’ shopping behavior in virtual stores. We first review literatures on aspects of customers’ online purchasing behavior, and then propose a model for customer online behavior.

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