Asia pacific journal of information systems

  • 제34권1호
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  • Pages.226-247
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  • 2024
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  • 2288-5404(pISSN)
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  • 2288-6818(eISSN)
한국경영정보학회 (The Korea Society of Management Information Systems)
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Empirical Comparison of the Effects of Online and Offline Recommendation Duration on Purchasing Decisions: Case of Korea Food E-commerce Company

  • Qinglong Li (Department of Big Data Analytics, Kyung Hee University) ;
  • Jaeho Jeong (Department of Business Administration, Kyung Hee University) ;
  • Dongeon Kim (Department of Big Data Analytics, Kyung Hee University) ;
  • Xinzhe Li (Department of Big Data Analytics, Kyung Hee University) ;
  • Ilyoung Choi (Division of Business Administration, Seo Kyeong University) ;
  • Jaekyeong Kim (Department of Big Data Analytics and School of Management, Kyung Hee University)
  • 투고 : 2023.07.18
  • 심사 : 2023.12.26
  • 발행 : 2024.03.31
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초록

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

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참고문헌

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