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Distribution requirements planning (DRP) is one of the scheduling methods used in logistics systems. A generalised version is presented of a DRP system designed to enhance scheduling flexibility of currently used DRP systems and to deal with multi‐sourcing trans‐shipment problems in a multi‐echelon logistics system. The required information inputs, capabilities and advantages of this generalised DRP system are described in detail. Finally, the future research direction to improve the adaptability of DRP in distribution systems is discussed.

A framework is presented based on the MRP Evolution‐Information System Evolution (MEISE) grid to classify MRP users in terms of the diagonal band along the dimension of information processing system development. The classification scheme provides a guideline for the information system specialist to make necessary adjustments of information systems when they decide to upgrade their MRP systems. Furthermore, the MEISE grid also facilitates the organisation of information and production functions while maintaining overall co‐ordination. Finally, the operational implications of deviating from the diagonal band are discussed.

Safety stock, safety lead time, and safety capacity are the conventional methods used to deal with operational uncertainty. With the advent of material requirements planning (MRP) systems, the rescheduling capability can be viewed as an alternative to buffer production systems against uncertainty. Logistics systems have characteristics similar to production systems in the face of uncertain events occurred in the operating environments. After presenting the rescheduling capability of a counterpart of MRP in logistics systems, distribution resource planning (DRP), as a viable uncertainty buffering method, we discuss the operational implications of these buffering methods from the perspectives of (1) the nature of the business, (2) the decision‐making hierarchy, (3) the cost of implementation, and (4) the impact of operating environments in logistics systems. The discussion on operational implications should lead to a better understanding regarding how to evaluate these buffering methods in logistics systems.

There are several alternatives suggested in the literature to deal with material requirements planning (MRP) system nervousness. Conventional uncertainty buffering techniques, such as safety stock, excess capacity, and safety lead time, can be used to cope with unplanned events and to reduce the impact of system nervousness. However, inappropriate use of safety stock could result in significant work‐in‐process inventory and using safety lead time could distort priorities and increase inventories. Safety capacity is another buffering mechanism which has been used to deal with uncertainty. Dampening procedures to cope with system nervousness have recently received some attention. Here a classification framework is presented which provides a basis for investigating the relative performance of dampening procedures to cope with MRP system nervousness. Operating characteristics are identified and future research directions are suggested.

The general practice in implementing an appointment scheduling rule (ASR) is to enforce a certain rule, such as “block appointment”, to schedule customer arrivals in service systems. There are several commonly used ASRs that have been used in such service systems as public and private clinics and restaurant reservations, most of which tend to minimize the idle time or optimize the utilization rate of the service facility while neglecting customers′ waiting times. One commonly used ASR in real‐world service systems, which schedules several customers to arrive at the start of each service session, tends to induce long customer waiting time, but manages to keep the facility idle time fairly low. Introduces an ASR to reduce customers′ waiting time considerably while increasing the facility idle time at a manageable minimum. Evaluates environmental factors that may affect the performance of ASRs, such as the probability of no‐shows, the coefficient of variation of service times, and the number of customers per service session. Discusses several exceptional situations such as walk‐ins, seasonality of customer arrivals, and multiple‐priority/queues.

Past research in examining the performance of alternative lot‐sizing rules has focused on the total cost of inventory carrying cost and set‐up cost. Although this cost‐related performance measure is significant for evaluating the overall efficiency of production systems, there are other variations such as frequent rescheduling, generally referred to as system nervousness, occurring that would affect the production scheduling and subsequently the system performance. Expands the performance criteria to re‐evaluate the effectiveness of using several commonly tested lot‐sizing rules in a multi‐level MRP system under stochastic operating environments by means of a simulation study. Results indicate that the Silver‐Meal algorithm seem to perform very well under most operating environments tested. Also, the operating environments play a significant role in the relative performance of lot‐sizing rules tested.

The purpose of the paper is to present an empirical study on the logistics innovation capability and its impacts on the supply chain risk in the Australian courier firms. Based on the resource-based review, logistics innovation capability provides valuable insight into mitigating supply chain risks in the Industry 4.0 era.

The research model focuses on the relationships between logistics innovation capability and supply chain risk. Partial least squares approach for structural equation modelling is used to validate the research model by empirically analysing survey data.

The empirical result shows negative relationships between logistics innovation capability and supply chain risks. These relationships may imply that firms can mitigate the negative impacts of supply chain risks by developing logistics innovation capabilities. The findings demonstrate the applicability of logistics innovation capability for mitigating supply chain risks in the Australian courier firms.

There are very few empirical studies on the mitigating supply chain risk through logistics innovation capability. The empirical results provide an insight into innovation management and risk management in logistics and supply chain. This insight offers practical guidance for developing and deploying logistics innovation capability to support and enable supply chain risk management strategies in the Industry 4.0 era.