Supply process improvement decisions for a newsvendor with random capacity. (March 2020)

• Record Type: Journal Article
• Authors: Shi, Zhenyang; Li, Bo; Liu, Shaoxuan
• Is Part Of: Computers & industrial engineering. Volume 141(2020)
• Publication Date: 2020-03
• Subjects: Random capacity -- Newsvendor model -- Process improvement -- Procurement -- Supply chain management; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106289
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Study a newsvendor's supply process improvement with random capacity. A firm benefit from increases in mean and decreases in variance of the capacity, despite diminishing returns. Similar results hold when capacity follows distributions with the mean and variance jointly parame­terized. The optimal capacity mean level increases in profit margin but is non­monotone in demand variability. The optimal capacity variability level decreases in profit margin and increases in demand variability. Abstract: This paper considers a firm with random capacity that makes decisions on supply process improvement in a newsvendor setting. We find that the firm benefits from increased mean capacity, from reduced variance in capacity, and from monotonicity in the increasing concave order of capacity, despite diminishing returns. Moreover, we identify positive moderating effects on process improvements of profit margin and demand magnitude. When the capacity follows specific distributions whose mean and variance are jointly parameterized, we investigate comparative statics via analytical derivation and numerical experiments. The results are consistent with those obtained under a general distribution, where process improvement is more effective when initiated earlier rather than later. Analyzing various capacity distributions reveals that the random capacity's optimal parameters related to its mean increase with the firm's profit margin. However, the associations between these parameters and demand variability are subtle and may change under different procurement costs. The capacity's optimal parameters related to its variance decrease with higher profit margins but increase with greater demand variability. Our findings yield several managerial insights.