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Supporting the purchase decisions of consumers

Supporting the purchase decisions of consumers Online product ratings play an important role in the decision-making process of consumers, which are not only sources of information used by consumers to understand the function and quality of a product or service but also sources of information used to find desirable products. The purpose of this paper is to develop a decision-based method for supporting the purchase decisions of consumers based on not only the online product ratings but also the actual product attributes.Design/methodology/approachFirst, two types of utility values are designed to measure the preference of the consumer based on either online ratings or actual product attributes. Then, the traditional TOPSIS method is adopted to achieve a comprehensive value by integrating the two types of utility values so that all of the alternative products can be ranked. Further, a product selection support system prototype is designed and developed to support the purchase decisions of consumers.FindingsTo help consumers select desirable products efficiently, it is necessary to develop a product selection method based on the online ratings of alternative products and consumer expectations.Practical implicationsThe research shows that the proposed method can not only support consumers’ purchase decisions based on a large number of online product ratings but also help manufacturers to find out consumers’ demands or requirements on products so as to facilitate the design of new products or the improvement of products. On the basis of the proposed method, the developed system prototype is helpful for consumers to select desirable products.Originality/valueTo support the purchase decisions of consumers, a new decision-based method for selecting desirable online products is proposed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Supporting the purchase decisions of consumers

Fan, Zhi-Ping; Xi, Yang; Li, Yongli
Kybernetes , Volume 47 (4): 27 – Mar 16, 2018
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References (51)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0368-492X
DOI
10.1108/k-03-2017-0116
Publisher site
See Article on Publisher Site

Abstract

Online product ratings play an important role in the decision-making process of consumers, which are not only sources of information used by consumers to understand the function and quality of a product or service but also sources of information used to find desirable products. The purpose of this paper is to develop a decision-based method for supporting the purchase decisions of consumers based on not only the online product ratings but also the actual product attributes.Design/methodology/approachFirst, two types of utility values are designed to measure the preference of the consumer based on either online ratings or actual product attributes. Then, the traditional TOPSIS method is adopted to achieve a comprehensive value by integrating the two types of utility values so that all of the alternative products can be ranked. Further, a product selection support system prototype is designed and developed to support the purchase decisions of consumers.FindingsTo help consumers select desirable products efficiently, it is necessary to develop a product selection method based on the online ratings of alternative products and consumer expectations.Practical implicationsThe research shows that the proposed method can not only support consumers’ purchase decisions based on a large number of online product ratings but also help manufacturers to find out consumers’ demands or requirements on products so as to facilitate the design of new products or the improvement of products. On the basis of the proposed method, the developed system prototype is helpful for consumers to select desirable products.Originality/valueTo support the purchase decisions of consumers, a new decision-based method for selecting desirable online products is proposed.

Journal

Kybernetes – Emerald Publishing

Published: Mar 16, 2018

Keywords: Decision making; Decision support; Online product ratings; Product selection; Utility analysis

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