Knowledge that Transforms

Evidence on the impact of amplification effects on supply chain performance primarily has been derived from studies in manufacturing industries. In this article we reported on a case study from the telecommunication industry and aimed to analyze relevant root causes and associated countermeasures of the amplification phenomenon in service supply chains. Our case findings confirm the occurrence of upstream amplification of workload in the service supply chain, workload being a more appropriate measure for amplification effects in service supply chains than inventory levels. Not all of the root causes for amplification effects known from research in manufacturing environments were found to apply in this particular service context, especially those related to the use of inventory. In addition, our telecom case study highlighted a new root cause for amplification: interactions of high workloads and reduced process quality that start reinforcing each other once workloads pass a certain threshold. In this particular case, many of the known countermeasures to eliminate amplification did not apply, because of the specific characteristics of the service process, or yielded only limited results. A potentially very powerful countermeasure identified was to implement quality improvements throughout the service chain. This quality dimension links our research to the literature on service management in general, where service quality is on top of the research agenda.

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.

This paper provides a comprehensive survey of research on appointment scheduling in outpatient services. Effective scheduling systems have the goal of matching demand with capacity so that resources are better utilized and patient waiting times are minimized. Our goal is to present general problem formulation and modeling considerations, and to provide taxonomy of methodologies used in previous literature. Current literature fails to develop generally applicable guidelines to design appointment systems, as most studies have suggested highly situation‐specific solutions. We identify future research directions that provide opportunities to expand existing knowledge and close the gap between theory and practice.