Identifying desirable product specifications from target customers' Chinese eWOM

Yuh Jen Chen, Yuh Min Chen, Chien Wei Fu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In a fiercely competitive business environment, understanding target customers' product preferences and demands has become the basis for improving competitive advantage. In the past, an enterprise would understand its consumers' preferences and demands through interactions between salespersons and consumers or questionnaire surveys. As Internet technology and the popularity of virtual communities have grown, more consumers are commenting about products on the Internet, enabling enterprises to understand more objectively consumers' preferences and demands. Therefore, the extraction and analysis of valuable decision-supporting information from extensive target customers' Chinese electronic word-of-mouth (eWOM) is critical to improving an enterprise's competitiveness. This work develops a mechanism for identifying desirable product specifications from target customers' Chinese eWOM to provide enterprises with reference specifications in product planning, and thereby reduce the time to market and improve the target customers' satisfaction. This goal can be achieved by performing the following tasks: (i) designing a process for identifying desirable product specifications from target customers' Chinese eWOM, (ii) developing techniques related to desirable product specification identifi-cation from target customers' Chinese eWOM, and (iii) implementing a mechanism for identifying desirable product specifications from target customers' Chinese eWOM. Developing techniques associated with identifying desirable product specifications from target customers' Chinese eWOM involves the selection and analysis of the target customers' Chinese eWOM and the evaluation of the desirable product specifications.

Original languageEnglish
Pages (from-to)545-572
Number of pages28
JournalInternational Journal of Information Technology and Decision Making
Volume16
Issue number2
DOIs
Publication statusPublished - 2017 Mar 1

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)

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