Purpose The purpose of this paper is to determine if internal integration, information sharing, and training constitute direct antecedents to organizations’ warning and recovery capabilities. Assuming that organizations periodically face various supply chain risks, the authors intend to show that managers can develop these antecedent competencies in ways that bolster their supply chain risk management (SCRM) capabilities. Design/methodology/approach To understand the relationships between the antecedents and SCRM capabilities, the authors used Q-sorts and confirmatory factor analysis to develop new warning and recovery measures. The authors then collected survey data from 231 hospital supply managers and analyzed these records using structural equation modeling. Findings The results indicate that internal integration and training positively affect organizations’ warning and recovery capabilities, in both a direct and indirect manner. The authors also illustrate how managers can leverage their SCRM capabilities to affect operational performance. Research limitations/implications These results suggest that by developing antecedent competencies like internal integration and training, firms may bolster their warning and recovery capabilities, and ultimately operational performance of the organization. Originality/value The findings provide hospital supply organizations and other inventory management teams with a novel approach to managing an evolving array of supply chain risks. Rather than investing in costly risk management techniques, like inventory stocks, organizations can use internal integration and training to improve their SCRM capabilities.

The stability of the Master Production Schedule (MPS) is a critical issue in managing production operations with a Material Requirements Planning System. One method of achieving stability is to freeze some portion or all of the MPS. While freezing the MPS can limit the number of schedule changes, it can also produce an increase in production and inventory costs. This paper examines three decision variables in freezing the MPS: the freezing method, the freeze interval length, and the planning horizon length. Simulation experiment results are reported which suggest that freezing up to 50% of the planning horizon has a marginal effect on production and inventory cost under a wide range of operating conditions. These results also suggest that an order based freezing method produces superior results in comparison with a period based method.production/scheduling: material requirements planning, simulation: applications, inventory/production: planning horizons

In the context of production scheduling, inserted idle time (IIT) occurs whenever a resource is deliberately kept idle in the face of waiting jobs. IIT schedules are particularly relevant in multimachine industrial situations where earliness costs and=or dynamically arriving jobs with due dates come into play. We provide a taxonomy of environments in which IIT scheduling is relevant, review the extant literature on IIT scheduling, and identify areas of opportunity for future research.

A substantial amount of behavioral research in business has attempted to uncover the relative importance decision makers attach to different decision variables (cues) used in their decision processes. This paper reports on two experiments that examine methodological issues concerning the assessment of cue importance. The first experiment examined whether the categorical descriptions given to cues in many modeling studies affect the importance decision makers attach to those cues. Results revealed that the importance attributed was significantly affected by the categories used to define cues. Additionally, because different techniques have been utilized to model cue importance, the second experiment examined the level of agreement between importance measures derived from two commonly used modeling techniques (ANOVA and information boards) under varying levels of task complexity. Results indicated that cue importance measures generally exhibited a moderate level of agreement. However, the use of different modeling techniques appears to affect the importance attributed to cues for some decision makers. In addition, the level of agreement was not affected by changes in task complexity. Implications of these results for future research studies that model decision behavior are discussed.

This article investigates the effectiveness of a tactical demand-capacity management policy to guide operational decisions in order-driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first-come-first-served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order-processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order-processing approach.

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Schedule nervousness caused by uncertainty in demand or supply or by dynamic lot-sizing can be an obstacle to effective execution of material requirements planning (MRP) systems. Previous studies on the effectiveness of alternative approaches for dampening nervousness almost always considered single-level product structures and deterministic demand conditions. This study evaluates the effectiveness of three strategies for reducing nervousness in multi-level MRP systems under demand uncertainty: (1) freezing, (2) end-item safety stock, and (3) lot-for-lot scheduling below level 0. The strategies are evaluated under a wide range of operating conditions characterized by variations in item cost structure, product structure, demand uncertainty, and lot-sizing methods used. A multi-level MRP system is simulated to study the relative performance of the three strategies. Results indicate that freezing the master production schedule is the most effective approach in terms of reducing both instability and cost as the freeze length covers the cumulative lead time. It is also the least sensitive to changes in operating conditions.