We study the problem of how to design a sparse flexible process structure in a balanced and symmetrical production system to match supply with random demand more effectively. Our goal is to provide an optimal design, i.e., the sparsest design, to achieve (1-ε)-optimality relative to the fully...

This study takes a contingent perspective regarding the relationships among a firm's technological search depth, the characteristics of its knowledge, and its product innovation performance. While a firm's search patterns directly influence innovative output, their effectiveness is moderated by...

Stochastic gradient descent (SGD) has proven effective in solving many inventory control problems with demand learning. However, it often faces the pitfall of an infeasible target inventory level that is lower than the current inventory level. Several recent works (e.g., (Huh and...

Process flexibility has been widely adopted as an effective strategy to improve responsiveness to demand uncertainty. Many algorithms for constructing sparse flexibility designs with good theoretical guarantees have been developed for balanced and symmetrical production systems, which assume...

We consider the periodic review dynamic pricing and inventory control problem with fixed ordering cost. Demand is random and price dependent, and unsatisfied demand is backlogged. With complete demand information, the celebrated (s,S,p) policy is proved to be optimal, where s and S are the...

This paper employs real option analysis to evaluate the investment project to adopt energy saving and carbon emission reduction technology. Sensitivity analysis and simulation outcomes highlight the respective roles of carbon price level and government support in the investment decision. That...