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Analyses the operational implications of marketing strategies that try to distinguish between high‐ and low‐priority customers. For a high‐priority customer, the distributor is willing to expedite an order from any emergency source. For a low‐priority customer, on the other hand, distributors will back‐order demand. Bases results on a normative model of dealer behaviour developed by the authors. The distributors are assumed to follow a periodic‐review, stochastic‐demand (s, S) inventory control policy. The principal constraint is a minimum level of service (fill rate) which reflects the objectives of the manufacturer. Bases the analysis on a complete experimental design where a distinction is made between exogenous (replenishment lead time and expedite cost) and endogenous (achieved service level and customer prioritization) variables. In addition, identifies small and large distributors as a function of the demand parameters. Results highlight policy options available to the manufacturer to increase the service level of the system, and these are dependent on the size and competitiveness of the market.

The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost.

In this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period.

The MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time.

Due to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight.

This research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits.

Despite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.

In this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.

The simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.

The findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

The purpose of this article is to start the process of exploring how to optimise connections between the strategic needs of an organisation as directed by top management and its learning management structures and strategies.

The article takes a broad brush approach to a complex and large subject area that is influenced by many internal and external variables. It highlights two of the main strands to be managed in the dynamic process of seeking to optimise performance and return on investment in organisational based demand‐led learning; learning that leads directly to decision making and resource allocation.

There are many treatises on the subject of organisation theory and practice and related platforms for change management. The condition of autopoesis, emphasising the dynamic of self production in shaping organisation states, has featured prominently in these concepts and ideas of management. Indications are, however, that the demands and perturbations of the external environment are playing an increasing role in shaping organisations and the medium of learning is the catalyst by which means this trend is accelerating.

More empirical research (available at: www.ecuanet.info) into the effect of learning process innovations and behaviours on business performance and organisational capability development is required to put real foundation into what are being revealed about the benefits of learning in the workplace.

Globalisation and global competition is placing greater emphasis on: releasing talent at all levels, the need for innovations in the creation and fulfilment of learning opportunities and the effective and efficient management of the firm's intellectual supply chain. The reactions at the learning supply‐demand interface are changing and this article outlines perspectives that map the areas where relationships are changing as a basis for demand‐led learning strategy formulation.

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands.

This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model.

The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain.

This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.

The purpose of this paper is to demonstrate, through the Delphi technique, how demand drivers and accommodation priorities for emerging knowledge‐intensive firms are understood and how corporate property and asset managers can respond to them.

This empirical paper discusses the results emerging from a Delphi study in four rounds with ten experts. This research focuses on the high growth, commercial sector in south‐east Queensland in Australia.

The accommodation priority demands of knowledge‐intensive firms varied depending on the stage of their lifecycle, that is, start‐up, established or mature. For start‐ups, accommodation cost was of primary importance; however, for the established and mature firms, their priorities were directly related to those supporting the progress of the firms itself and the productivity of its employers.

Many of the findings are likely to be applicable to commercial environments elsewhere and would provide a basis for investors, developers, asset owners and managers to better align their “old” assets, through better asset management, to these “new” firms within this rapidly changing environment.

The use of the Delphi technique in this multi‐faceted research topic captures the practical knowledge, wisdom and intuition of experts who deal with such issues on a day‐to‐day basis. Most real estate issues usually involve diverse specialities and perspectives – this paper illustrates how common ground through consensus can be achieved.

In today's quick‐response marketplace, it is becoming more and more difficult for business to react to the pressing demands of customers and consumers. Try as they might, they cannot achieve perfect knowledge of the market's actual demands. Instead, success depends upon making operations more flexible. In particular, management must work to build new flexibility into deployment—i.e., the allocation of available finished goods to meet immediate demands.

The purpose of this paper is to examine how US school leaders and teachers make sense of multiple accountability policies, including the Common Core State Standards and teacher evaluation, and how this process relates to school priorities and classroom practice.

This study uses a comparative case study approach to understand how principals and teachers in three high-poverty urban schools respond to policy.

Although principals and teachers viewed academic standards and the teacher evaluation framework as complementary, two of the three schools focused on meeting the expectations of the teacher evaluation framework at the expense of attention to academic standards. Without attention to the connections among policies and school priorities, the introduction of new policies may detract from rather than reinforce attention to academic standards.

Principals who are stronger instructional leaders may be better able to “craft coherence” among multiple standards-based policies and school priorities for instruction and student learning. Although their experiences are not generalizable, findings suggest that attending to standards for student and teacher performance without connecting to the implications for content and students’ learning may lead to superficial integration of accountability policies with school priorities.

Findings provide further evidence that principals play an essential role in responding to policy and suggest that districts and external support providers can assist their efforts by creating opportunities for professional learning about the connections among multiple policies and their implications for practice.

This paper extends Honig and Hatch’s conceptualization of “crafting coherence” to the work of teachers and the implications for classroom practice.

This paper aims to address a location-distribution-routing problem for distributing relief commodities during a disaster under uncertainty by creating a multi-stage model that can consider information updates during the disaster. This model aims to create a relief network that chooses distribution centers with the highest value while maximizing equity and minimizing response time.

A hybrid algorithm of adaptive large neighborhood search (ALNS) and multi-dimensional local search (MDLS) is introduced to solve the problem. Its results are compared to ALNS and an augmented epsilon constraint (AUGMECON) method.

The results show that the hybrid algorithm can obtain high-quality solutions within reasonable computation time compared to the exact solution. However, while it yields better solutions compared to ALNS, the solution is obtained in a little longer amount of time.

In this paper, the uncertain nature of some key features of the relief operations problem is not discussed. Moreover, some assumptions assumed to simplify the proposed model should be verified in future studies.

In order to verify the effectiveness of the designed model, a case study of the Sarpol Zahab earthquake in 2017 is illustrated and based on the results and the sensitivity analyses, some managerial insights are listed to help disaster managers make better decisions during disasters.

A novel robust multi-stage linear programming model is designed to address the location-distribution-routing problem during a disaster and to solve this model an efficient hybrid meta-heuristic model is developed.