Conservative Profitability Evaluation for Newsboy-type Products with Bootstrap Methods

ABSTRACT

In the field of inventory management, a profitability evaluation for ordered products is crucial to retailer revenue. Formulating such evaluations requires determining an appropriate order quantity, while ensuring that the product has high profitability potential. The achievable capacity index (ACI) provides a simple breakdown of profitability suitable for newsboy-type products with probabilistic distributed demand under the optimal order quantity. In this study, we investigated the lower confidence bound of ACI (LCBA) to obtain a conservative evaluation of profitability. Obtaining an explicit formula for the LCBA is difficult; therefore, we adopted parametric bootstrap methods to approximate the value for the LCBA. We also created a computational algorithm using R software to simulate the performances of various parametric bootstrap methods. Coverage rates and the corresponding ratios for various sample sizes and expected ACI values were tabulated to facilitate the selection of a suitable method and decide a required sample size with a conservative estimate. An illustrative example was presented to demonstrate the applicability of the proposed method and provide managerial insights.

KEYWORDS:

• Inventory control
• achievable capacity index
• conservative profitability evaluation
• parametric bootstrap method

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Rung-Hung Su

Rung-Hung Su received his PhD in Industrial Engineering and Management from National Chiao-Tung University, Hsinchu, Taiwan. He is currently an Assistant Professor at Fu-Jen Catholic University. His research interests include applied statistics, inventory management and operation research. He has published some papers on various SCI journals such as European Journal of Operational Research, International Journal of Production Economics, Computers and Industrial Engineering, European Journal of Industrial Engineering, Journal of Statistical Computation and Simulation, Quality Technology & Quantitative Management, and Central European Journal of Operations Research, etc.

Chia-Huang Wu

Chia-Huang Wu received a Ph.D. degree in Industrial Engineering and Management from National Chiao-Tung University, Hsinchu, Taiwan. He is currently an assistant professor at National Yang Ming Chiao-Tung University. His research interests include process capability analysis, applied statistics, queueing systems, and optimization theory. His research results have been published in various SCI journals such as Quality and Reliability Engineering International, European Journal of Industrial Engineering, Applied Mathematical Modelling, Computers and Operations Research, Computers and Industrial Engineering, Reliability Engineering and System Safety, etc.

Meng-Hsuan Lee

Meng-Hsuan Lee received her master's degree in the Department of Statistics and Information Science from Fu-Jen Catholic University, New Taipei City, Taiwan. She is currently a quality engineer at Unimicron Technology Corporation.