A shopping-path length estimation using Markov-chain-based shopper dynamics model

研究成果: Article

抜粋

We propose a framework of estimating shopping-path length, in which the floor is represented by the graph G(V,E) with a vertex set V and an arc set E and the shopping-path length is measured by the number of zones (vertices) shoppers visit. We used the Markov-chain to model the dynamics of distribution of shoppers on the vertecies in the graph. We derive the (discrete) probability distribution of shopping path length using the transition matrix in the Markov-chain, and derive the expected path length. We proposed the index called the improvement importance index to quantify how local changes in the transition probability affect the entire shopping path length. We have tested our framework to the test data from an industrial application and the estimated path-length is compared to the actual one. We have a result that the error of estimation is 0.2%.

元の言語English
ページ(範囲)68-73
ページ数6
ジャーナルOperations and Supply Chain Management
12
発行部数2
DOI
出版物ステータスPublished - 2019

ASJC Scopus subject areas

  • Management Information Systems
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Information Systems and Management

フィンガープリント A shopping-path length estimation using Markov-chain-based shopper dynamics model' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用