Earticle

초록

영어

Big data analytics has received wide attention by information technology industries. It has been done in quantitative and statistic viewpoints. Observing huge amount of data, it is possible without doubt to establish a model that may predict purchase behaviors of consumers. But this approach can neither explain what brings the consumers to such decisions nor predict future purchase behavior of other product categories. Furthermore, it is not possible to reason about consumers’ preferential differences that make choose or avoid certain places and shops. To answer this question, this paper argues that a qualitative analysis based on consumption values will be an alternative, and proposes a conceptual model of extracting consumption values from big data using clothing purchase as a case study.

목차

Abstract
 1. Introduction
 2. Basic Consumption Values
 3. Consumption Values from Big Data and Its Interpretation
  3.1. Big Data Analytics (BDA)
  3.2. Extracting Consumption Values: A Case Study on Clothing Purchase Decision Process
  3.3. Interpretation of Consumption Values
  3.4. Application
 4. Conclusion
 Acknowledgements
 References

키워드

저자

• Boeun Jung [ Hankuk University of Foreign Studies ]
• Sora Lim [ Hankuk University of Foreign Studies ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605