1. NCCU Academic Hub
  2. 學術產出
  3. College of Commerce
  4. Periodical Articles
  5. Item

學術產出-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

題名 Traffic-Based Labor Planning in Retail Stores
作者 Chuang, Howard Hao-Chun
莊皓鈞
貢獻者 資訊管理學系
關鍵詞 retail operations;staffing;store performance;data analytics
日期 2015
上傳時間 26-Oct-2015 17:42:14 (UTC+8)
摘要 Staffing decisions are crucial for retailers since staffing levels affect store performance and labor-related expenses constitute one of the largest components of retailers’ operating costs. With the goal of improving staffing decisions and store performance, we develop a labor-planning framework using proprietary data from an apparel retail chain. First, we propose a sales response function based on labor adequacy (the labor to traffic ratio) that exhibits variable elasticity of substitution between traffic and labor. When compared to a frequently used function with constant elasticity of substitution, our proposed function exploits information content from data more effectively and better predicts sales under extreme labor/traffic conditions. We use the validated sales response function to develop a data-driven staffing heuristic that incorporates the prediction loss function and uses past traffic to predict optimal labor. In counterfactual experimentation, we show that profits achieved by our heuristic are within 0.5% of the optimal (attainable if perfect traffic information was available) under stable traffic conditions, and within 2.5% of the optimal under extreme traffic variability. We conclude by discussing implications of our findings for researchers and practitioners.
關聯 Production and Operations Management, Vol.25, No.1, pp.96-113
資料類型 article
DOI http://dx.doi.org/10.1111/poms.12403
dc.contributor 資訊管理學系-
dc.creator (作者) Chuang, Howard Hao-Chun-
dc.creator (作者) 莊皓鈞-
dc.date (日期) 2015-
dc.date.accessioned 26-Oct-2015 17:42:14 (UTC+8)-
dc.date.available 26-Oct-2015 17:42:14 (UTC+8)-
dc.date.issued (上傳時間) 26-Oct-2015 17:42:14 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/79052-
dc.description.abstract (摘要) Staffing decisions are crucial for retailers since staffing levels affect store performance and labor-related expenses constitute one of the largest components of retailers’ operating costs. With the goal of improving staffing decisions and store performance, we develop a labor-planning framework using proprietary data from an apparel retail chain. First, we propose a sales response function based on labor adequacy (the labor to traffic ratio) that exhibits variable elasticity of substitution between traffic and labor. When compared to a frequently used function with constant elasticity of substitution, our proposed function exploits information content from data more effectively and better predicts sales under extreme labor/traffic conditions. We use the validated sales response function to develop a data-driven staffing heuristic that incorporates the prediction loss function and uses past traffic to predict optimal labor. In counterfactual experimentation, we show that profits achieved by our heuristic are within 0.5% of the optimal (attainable if perfect traffic information was available) under stable traffic conditions, and within 2.5% of the optimal under extreme traffic variability. We conclude by discussing implications of our findings for researchers and practitioners.-
dc.format.extent 618496 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Production and Operations Management, Vol.25, No.1, pp.96-113-
dc.subject (關鍵詞) retail operations;staffing;store performance;data analytics-
dc.title (題名) Traffic-Based Labor Planning in Retail Stores-
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1111/poms.12403-
dc.doi.uri (DOI) http://dx.doi.org/10.1111/poms.12403-