Journal of Fashion Business (패션비즈니스)

The Korean Society of Fashion Business (한국패션비즈니스학회)
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The Effect of Big Data-based Fashion Shopping Applications on App Users' Continuous Usage Intention

  • Received : 2018.11.05
  • Accepted : 2018.12.17
  • Published : 2018.12.30
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Abstract

The purpose of this research is to investigate the characteristics of big data-based fashion shopping (BDFS) application, perceived usefulness, and expectation confirmation that influence the continuous usage intention of BDFS application users based on the expectation-confirmation model. A survey was conducted with female consumers in their 20s, who are living in Seoul and Incheon area and have used BDFS applications, A total of 182 responses were used for the data analysis. Five hypotheses were proposed, and regression analyses were conducted to test those hypotheses. The results indicated that the users' perceived usefulness increased with the increase of accuracy and personalization characteristics of the app and the expectation confirmation. The result suggested that it is essential to provide accurate information for users to feel useful and to develop the personalized offerings and services which can be the biggest strength of the big-data based mobile fashion store. It was also found that continuous usage intention increases with increased perceived usefulness and expectation confirmation. This result suggests that expectations can play a critical role in perceiving the usefulness of BDFS applications and the user's expectation confirmation also significantly affected the users' continuous usage intention.

Keywords

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Figure 1. Proposed Model

Table 1. Sources of Measurement

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Table 2. Result of Factor Analysis and Reliability Tests

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Table 3. Effect of BDFS Apps’ Characteristics and PEU on PU of BDFS Apps

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Table 4. Effect of BDFS apps’ PU and Expectation Confirmation on Continuous Usage Intention regarding BDFS Apps

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