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Drum‐Buffer‐Rope (DBR) is a relatively new approach to inventory and logistics management that effectively supports reduced manufacturing lead‐time. Previous studies have not emphasized this fact nor explained how it is accomplished. This paper describes DBR mechanics, proposes appropriate implementation steps, identifies key ideas, and reports experience with one DBR application. Key ideas identified include the use of input control and excess capacity. Input control is readily implemented within DBR while excess capacity permits DBR flow to be maintained. The reported application demonstrates both the effectiveness of DBR in reducing lead‐time and its vulnerability to misunderstanding.

The purpose of this paper is to examine to what extent the factors of the operating environment influence the structural dimensions and subsequent performance of a firm's recovery system.

Using contingency theory and a sample of 158 service firms, this research tests for structural differences in service recovery systems based on Schmenner's widely‐cited taxonomy, the service process matrix. To conduct the analysis, both multiple analysis of variance (MANOVA) and analysis of variance (ANOVA) models were tested to assess overall system differences and to detect individual dimensional differences.

The results indicate that differences in the structure of service recovery systems do exist across divergent operating environments. Additionally, differences in performance measures were found only in capability improvements, while customer‐oriented performance did not vary across operating environments.

The paper is believed to be the first to empirically investigate how differences in operating environments increase the likelihood that firms will employ divergent recovery system configurations. This work yields valuable insights into how organizations can design their systems to more appropriately respond to the demands of the environments in which they operate. The results also lend credence to the concept of equifinality, which suggests similar ends are attainable through multiple means.

Much of the earlier empirical work in service management has suggested that the dimensions of service quality may be stable in terms of their relative importance. In particular, the works of Zeithaml et al. postulate that service reliability matters most to customers and that empathy and the tangible aspects of services matter the least. Shows arguments, both conceptually and empirically, so that this observation is not based on strategic thinking nor on a particularly sound set of experiments. The relative priorities of service organizations must be established through the strategy formulation process and are likely to vary, quite logically, according to market choices and operations process characteristics.

The purpose of this paper is to explore whether and how the bullwhip effect, as found in product supply chains, might also manifest itself in services, as well as what policies can be successful for mitigating it.

A combination of analytic methods was used – inductive case analysis and analysis of data from two service supply chains in the telecom industry.

Empirical evidence from two cases was examined and provides support for the presence of a service bullwhip effect. Quantitative and qualitative case data were used to explore how this effect manifests itself in services, the distinctive drivers of the bullwhip effect in services, and the managerial actions that can either trigger or mitigate these bullwhip effects. In total, eight propositions are developed and three types of characteristics that potentially make the bullwhip effect worse in services than in manufacturing are identified: the destabilizing effects of manual rework in otherwise automated service processes; the omission of accurate and timely data on rework volumes upstream in the chain, pointing at future bullwhip effects downstream; and the lack of a supply‐chain mindset within the various departments jointly responsible for delivering the service, leading to longer delays in reacting to service bullwhips as they develop over time.

The research is based on two cases within a single industry, limiting generalizability. The propositions developed need testing in a wider set of contexts, including hybrid service and product supply chains.

The implications of this research can help organizations prevent or reduce the negative impact of planned and unplanned fluctuations in their service supply chains.

This paper explores an area that has been well researched in manufacturing, but not in services, and it contributes to both the theory and practice of service supply chains.