RESOURCE ALLOCATION TO IMPROVE SERVICE QUALITY PERCEPTIONS IN MULTISTAGE SERVICE SYSTEMS

Service quality improvement has become an imperative in today's service firms. In this paper, we present a modeling framework that combines marketing and operations viewpoints for resource allocation. The framework can be used to allocate resources to the different stages of a multistage service system, where the manager's goal is to improve customers' perceptions of service quality, given some budget. Optimal allocation guidelines are provided, and the interplay of three factors on the resulting allocation scheme is captured. These factors are the current level of customers' perceptions of service quality at each stage, the cost of implementing a service quality improvement at each stage, and the importance placed by customers at each stage. Sensitivity analysis to provide additional managerial insights is also performed. We demonstrate the applicability of the modeling framework, using data from a real life health care environment. Model limitations and future research are also discussed.     

ALLOCATING AND SCHEDULING MOBILE DIAGNOSTIC IMAGING EQUIPMENT AMONG HOSPITALS

The allocation and weekly scheduling of mobile magnetic resonance imaging (MRI) units leased to a group of hospitals that share the equipment can be a complex problem. Similar problems occur in other domains where expensive equipment or facilities such as video conference facilities, aircraft, and supercomputers are leased. The crux of the problem was determining the number of days and which days of the week various types of equipment types should be leased to hospitals, so as to maximize the rental revenues and satisfy client preferences for days of the week and equipment types. We found rental revenues were a decreasing function of the number of days allocated to a hospital. We considered two sub-problems linked by a set of variables to model the problem. We show that one of these subproblems is a minimum cost network flow problem and the other is an integer multi-commodity transportation problem. We developed a procedure for solving the latter problem by exploiting earlier results for specialized networks. We conducted a computational study to evaluate the performance of this procedure and showed that it generally provides near-optimal integer solutions. We describe the development and implementation of a spreadsheet-based decision support system based on this model. This system was successfully implemented by a small firm with no expertise or prior experience using models.     

A COMPARISON OF RULES FOR ALLOCATING SETUP-REDUCTION INVESTMENTS IN A CAPACITATED ENVIRONMENT

This paper builds on a recent empirical study of the setup-reduction process that suggests setup-reduction proceeds through three major stages and that each stage is dominated by a particular type of investment function. Specifically, it examines the question of how to best prioritize investments during the stage that emphasizes standardizing setups across a work center. We compare different investment-allocation rules in a multi-item, capacity-constrained, dynamic demand environment under a variety of cost, demand, and investment assumptions. This analysis shows that significant differences in benefits can be achieved depending on the way setup-reduction investments are prioritized.     

MADE IN THE WORLD: THE GLOBAL SPREAD OF PRODUCTION

We are moving rapidly into an age of transnational manufacturing, where things made in one country are shipped across national borders for further work, storage, sales, repair, remanufacture, recycle, or disposal; but our laws, policies, and management practices are slow in adjusting to this reality. They are often based on inaccurate premises. This article examines these premises and suggests what they imply for management of manufacturing. First, a common view is that manufacturing investment in the industrialized nations is declining and shifting to the developing countries. This is not true. Investment in manufacturing in both industrialized and developing nations is increasing and, in absolute value, there is a lot more investment in industrialized countries than in developing countries. Second, a related view argued by many is that manufacturing does not have a bright future in the rich countries. I argue that manufacturers can thrive in the industrialized countries if they learn how to add more value for the end users. They must go beyond productivity improvement to producing more technologically advanced and customized products, responding faster to changing customer demands, and appending more services to their products. Doing all this is easier in the industrialized countries because the needed skills and infrastructure are more readily available there. Third, another potentially misleading notion is related to why companies invest in manufacturing abroad. Access to low-cost production is not the main motivation in most cases; rather it is access to market. Superior global manufacturers use their foreign factories for much more: to serve their worldwide customers better, preempt competitors, work with sophisticated suppliers, collect critical marketing, technological, and competitive intelligence, and attract talented individuals into the company. They build integrated global production networks, not collections of disjointed factories that are spread internationally. Thus their investment in manufacturing abroad is not a substitute for investment at home, it is a complement. Building and managing such integrated global factor networks is the next challenge in manufacturing.     

OPTIMAL PROJECT SEQUENCING WITH RECOURSE AT A SCARCE RESOURCE

We develop a dynamic prioritization policy to optimally allocate a scarce resource among K projects, only one of which can be worked on at a time. When the projects' delay costs differ, the problem (a “restless bandit”) has not been solved in general. We consider the policy of working on the project with the highest expected delay loss as if the other project was completely finished first (although recourse is allowed). This policy is optimal if: (1) the delay cost increases with the delay regardless of the performance state, (2) costs are not discounted (or, discounting is dominated by delay costs), (3) projects are not abandoned based on their performance state during processing at the scarce resource, and (4) there are no stochastic delays. These assumptions are often fulfilled for processing at specialized resources, such as tests or one‐off analyses.     

OPTIMAL AND HEURISTIC SOLUTIONS FOR THE MULTI‐ITEM NEWSVENDOR PROBLEM WITH A SINGLE CAPACITY CONSTRAINT

This research considers a multi‐item newsvendor problem with a single capacity constraint. While this problem has been addressed in the literature, the focus here is on developing simple, closed‐form expressions for the order quantities. The benefit of such an approach is that the solutions are straightforward to calculate and have managerial appeal. Additionally, we show these expressions to be optimal under a variety of conditions. For more general cases when these optimality conditions do not hold, we use these expressions as heuristic solutions. Via computational studies, we demonstrate that these heuristics are extremely effective when the optimality conditions are not satisfied.