The Journal of Society for e-Business Studies (한국전자거래학회지)

Society for e-Business Studies (한국전자거래학회)
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Development of an Agent-based Simulator for Shopping Path Analysis in Retail Stores

유통매장 내 쇼핑 동선 분석을 위한 에이전트 기반 시뮬레이터 개발

  • 김상희 (동국대학교 서울캠퍼스 산업시스템공학과) ;
  • 메디 케사바즈 (동국대학교 서울캠퍼스 산업시스템공학과) ;
  • 이용한 (동국대학교 서울캠퍼스 산업시스템공학과)
  • Received : 2012.01.05
  • Accepted : 2012.01.26
  • Published : 2012.02.28
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Abstract

Recently the effort of retailers improving the efficiency of store operations by using the information technology (IT) is increasing. Among them, the analysis of the shoppers' flow in retail stores is one of the critical tasks since it is an essential part in optimizing store layout and item grouping, and in developing the customized services specialized to shoppers' classification. Agent-Based Modeling and Simulation (ABMS) is one of the most promising methods which support analyzing the shoppers' flow. In this paper, we suggested a shopper's behavior model and developed an agent-based simulator for optimizing the operations of retail stores. In order to model the shoppers' behavior, we analyzed the behavioral characteristics of shoppers based on their shopping lists, suggesting BDI-based agent models of the shoppers' behavior. The shopping agent model were suggested, which has an additional mental state, the shopper's behavioral characteristic, as well as the original mental states of the BDI theory which has beliefs, desires and Intentions. The result of this study can be used in as a preliminary study for modeling and simulation of retail stores congestion and in the end the optimization of item grouping and store layout.

최근 유통업체의 운영 효율화를 위한 IT 활용 노력이 증대되고 있다. 이 가운데 유통매장 내 고객 흐름에 대한 분석은, 매대 배치와 상품 그룹핑의 최적화 및 매대별, 지역고객 특성별 서비스 개발에 있어서 핵심적인 부분이다. 에이전트 기반 모델링 및 시뮬레이션(ABMS)은 유통매장 내 고객 흐름을 분석하는데 가장 유망한 방법 중 하나이다. 본 논문에서는 고객 흐름 분석 기반의 유통매장운영 최적화를 위한 ABMS의 기초 연구로서 고객들의 행동을 분석하여 모델링하고 시뮬레이션 하였다. 고객 행동 모델링을 위하여 구매 물품 리스트에 따른 실제 고객의 행동 특성을 조사하였고, 이를 바탕으로 BDI 기반의 고객 에이전트 모델을 제시하였다. 고객 모델은 BDI 이론의 구성요소인 믿음(Beliefs), 소망(Desires), 그리고 의도(Intentions)와 고객의 특성(Characteristics)을 포함하고 있다. 본 연구 결과는, 향후 매장 내 혼잡도 분석을 위한 모델링 및 시뮬레이션, 그리고 이를 바탕으로 한 상품 그룹핑 및 매대 배치 최적화에 활용될 수 있을 것이다.

Keywords

References

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