ABSTRACT
Manufacturers in competitive markets can enhance profit opportunities by transforming their business model to own branding and manufacture (OBM). Note however that in situations involving limited storage and production capacity, OBM groups must determine the optimal preparation quantity and frequently evaluate profitability in all channels. This is particularly important when dealing with newsboy-type (i.e. single-period) products. The achievable capacity index (ACI) can effectively measure and estimate the profitability of a newsboy-type product. However, the ACI is applicable only to measure a single product in a single retail point. In the current study, we developed an integrated achievable capacity index (IACI) to enable OBM groups with owned channels to measure the overall profitability with multiple independent normal demands. To estimate the true IACI, we derived the statistical properties of the IACI estimator based on the historical demand data. The lower confidence bound on IACI (LCBIA) was also presented to prevent overestimation due to sampling error. The LCBIA values for various values of parameters were summarized as the generic tables for the manager’s convenience pertaining to decision-making in conservative profitability evaluation. Finally, the applicability of the proposed scheme was assessed by applying numerical and sensitivity analyses to a real-world OBM example.
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Correction Statement
This article has been corrected with minor changes. These changes do not impact the academic content of the article.
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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 Associate 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, Annals of Operations Research, European Journal of Industrial Engineering, Journal of Statistical Computation and Simulation, Quality Technology & Quantitative Management, and Central European Journal of Operations Research, etc.
Jun-Jie Chen
Jun-Jie Chen received his master’s degree in the Department of Statistics and Information Science from Fu-Jen Catholic University, New Taipei City, Taiwan. He is currently a business manager at Taiwan Oriental Motor Corporation.