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How to Recommend Online Shopping Consumers the Best of Many Sellers? : Online Seller Recommendation System Using DEA Method

DEA 방법론을 이용한 온라인 판매자 추천 시스템의 구축

  • 안정남 (KAIM 수학전문학원) ;
  • 노상규 (서울대학교 경영전문대학원) ;
  • 유병준 (서울대학교 경영전문대학원)
  • Received : 2011.05.18
  • Accepted : 2011.08.20
  • Published : 2011.08.31

Abstract

In a buyer-seller transaction process, 'value for money,' a measure of quality-price-ratio, is one of the most important criteria for buyers' purchasing decisions. The purpose of this paper is to suggest a method which helps online shoppers choose the best of several sellers offering homogeneous goods. We suggest FDH (free disposal hull) model, an applied model of data envelopment analysis (DEA), for online buyer-seller transactions and verify it with the data from an Internet comparison shopping site. For this purpose, we analyze consumer choice behaviors by examining how consumers respond to different sale conditions such as price, brand, or delivery time. Then, we implement a seller recommendation system to support buyers' purchasing decisions. We expect our FDH model to provide valuable information for rational buyers who want to pay the least price for high quality products/services and to be used in implementing automated evaluation processes in micro transactions. Moreover, we expect that our results can be utilized for sellers' benchmarking strategies which help sellers be more competitive by showing them how to attract buyers.

구매자와 판매자의 판매과정에서 '구매가치'는 구매자의 구매의사결정에 있어서 매우 중요한 가격대비 질의 중요한 측정치이다. 본 논문의 목적은 온라인 구매자들이 통일한 물건을 파는 판매자를 중에 최적 판매자를 선택하는 데 도움이 되는 방법론을 제안함에 있다. 이 방법론 수립을 위하여 DEA(data envelopment analysis) 방법론의 적용모형의 하나인 FDH(free disposal hull) 모형을 사용하고, 이 모형의 실효성을 질제 가격비교 사이트로부터 획득한 데이터를 이용하여 검증하였다. 모형 검증과정에서는 가격, 브랜드 배달 기간 등 거래 조건에 대하여 구매자들이 어떻게 반응하는지를 우선 분석하고, 이를 바탕으로 구매자의 구매 의사결정을 돕는 판매자 추천 시스템을 구축하였다. 본 연구를 통하여 검증된 FDH 모형은 구매자 측면에서 최적조건, 최저가로 좋은 제품과 서비스를 원하는 구매자에게 유용한 정보를 제공하고, 나아가 자동화된 소규모 거래에도 활용될 수 있을 것으로 기대된다. 판매자 측면에서는, 구매자의 선호도를 더욱 자세히 파악함으로써 타판매자 대비 경쟁력을 가지는 벤치마킹 전략을 수립하는 데에도 유용하게 이용될 수 있을 것으로 기대된다.

Keywords

Acknowledgement

Supported by : 서울대학교 경영대학 경영연구소

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