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Reviews the dynamic operation of supply chains and reaches some simple conclusions for reducing demand amplification, which consequently attenuates swings in both production rates and stock levels. The results are based on one particular supply chain, for which the use of systems simplification techniques has generated valuable insight into supply chain design. Although different strategies are compared for reducing demand amplification as witnessed by one particular supply chain model, the conclusions are nevertheless thought to have wide application and, indeed, implication. Comments in depth on the significance of the simulation results for the demand chain as a whole, and for the role of an individual business within the chain. In the first instance, supply chain integration, and in particular free exchange of information, is a prerequisite for progress. In the second case, shows that reduction in lead times throughout the supply chain via JIT is similarly beneficial. Clearly pinpoints the limitation to supply chain improvement which can be obtained as a result of using JIT alone. This can be an expensive and ongoing process of improvement with many spin‐off benefits. Nevertheless, shows that the improvement possible by JIT operation of an individual business can be negated by the failure to design and manage the supply chain dynamics as a total system. The message for an individual business is thus quite specific. Not only must lead times be reduced via JIT, but also the business must seek to be part of the right supply chain, if it is to remain competitive and stable.

Aims to discuss the basic strategy taken by a specific manufacturer. States supply chain structures influence, directly, the supply chain inventory as a measure of performance. Examines the difference in the supply chain in relation to the manufacturer’s strategy to the product.

This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO).

The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation.

The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions.

This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level.

PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

The materials planning (MP) environment sets the prerequisites for the MP process. Before and during production transfer and start-up (PTS) supply chain uncertainty of the MP environment increases, as the company goes from a known to an unknown situation. The purpose of this paper is to describe the impact of the MP environment on the MP process before and during PTS.

A conceptual framework describing the MP environment before and during PTS is developed and applied to one case of outsourcing from Sweden to China. The framework is based on a literature review and further evaluated by both researchers and managers.

A conceptual framework describing the dynamic MP environment before and during PTS has been developed compared to previously static MP environments descriptions. In addition, this framework proved to be useful in analysing the importance of various characteristics of the MP environment before and during PTS.

The study highlights the importance of a proactive approach to materials availability when transferring production. The conceptual framework developed here can be used as a checklist to identify the characteristics of the MP environment that are most important to ensuring materials availability.

The paper highlights the PTS when outsourcing, a substantial time frame with a large impact on success. This is an important contribution, given the focus of previous outsourcing research on strategic issues. Further, the paper demonstrates the differences between static and dynamic MP environments.

The purpose of this study is to propose a new dynamic model of a production-inventory control system. The objective of the new model is to maximise the flexibility of the system so that it can be used by decision makers to design inventory systems that adopt various strategies that provide a balance between reducing the bullwhip effect and improving the responsiveness of inventory performance.

The proposed production-inventory control system is modelled and analysed via control theory and simulations. The production-inventory feedback control system is modelled through continuous time differential equations. The simulation experiments design is conducted by using the state-space model of the system. The Automatic Pipeline Inventory and Order-Based Production Control System (APIOBPCS) model is used as a benchmark production-inventory control system.

The results showed that the Two Automatic Pipelines, Inventory and Order-Based Production Control System (2APIOBPCS) model outperforms APIOBPCS in terms of reducing the bullwhip effect. However, the 2APIOBPCS model has a negative impact on Customer Service Level. Therefore, with careful parameter setting, it is possible to design control decisions to be suitably responsive while generating smooth order patterns and obtain the best trade-off of the two objectives.

This research is limited to the dynamics of single-echelon production-inventory control systems with zero desired inventory level.

This present model is an extension and improvement to Towill’s (1982) and John et al.’s (1994) work, since it presents a new dynamic model of a production-inventory control system which utilises an additional flow of information to improve the efficiency of order rate decisions.

A production‐inventory system based on a model proposed by Axsäter is examined with the purpose of understanding the dynamic properties of the model.

The information flow concept is discussed and a dynamic analysis using a system simplification approach is carried out to achieve an understanding of the dynamic behaviour of the system. Finally, the information flow is examined and analysed from a hierarchical perspective.

The model is extended to include an order decision rule and a production unit and it is shown that the extended model has the capability to represent the dynamics of a number of different system management principles. The three different model instances of base stock, kanban and material requirements planning character are analysed.

Dynamic modelling of production‐inventory and supply chain models are usually analysed at an aggregate level not involving any complex relations of materials or capacities. In this paper, this line of research is merged with an approach based on multiple information channels using matrix representation and it is shown how a system simplification approach can be used for this purpose.

The purpose of the study is to describe the implications of strategic lead times (SLTs) for return on investment (ROI).

This study was part of an interactive research project and is based on the logic of theory application leading to theory building. It uses a multiple case study with five holistic single cases. Empirical data (ED) have mainly been collected from interviews and focus groups.

The length of and uncertainty in SLTs have implications for companies' financial performance. These implications vary in strength and can be either direct or indirect. These findings are incorporated into a framework on SLTs' implications for ROI.

The presented array of SLTs' implications for ROI could be further investigated, focussing on their strength. Additionally, it would be interesting to substantiate the findings in the context of environmental and social sustainability (i.e. the triple bottom line).

The findings offer practitioners a rich description and understanding of SLTs' actual implications for financial performance in terms of ROI. This knowledge can support practitioners in analysing supply chain designs based on financial performance.

Using a combination of a relative financial performance measure (ROI) and a set of SLTs (systems perspective), this study focuses on SLTs' actual implications for ROI. The findings provide evidence that different sections of a supply chain can have different implications for revenue, cost and investment (i.e. the three absolute measures related to ROI).

The integration of supply chains together with the disintegration of individual actors in the supply chain shifts the focus from actors to challenges in the interaction between actors. This paper aims to identify risk strategies for different supplier interactions in triadic configurations to outline supply strategies.

Companies participating in a research project recounted the challenges they faced regarding the integration of customer order-based management and supply from a triad perspective. Six triad configurations were identified, based on the literature, resulting in three risk strategies, which were empirically illustrated in practice by the participating companies.

A key finding is that a triad perspective for a customer-differentiated approach to supplier interaction results in a material classification that highlights the circumstances in which to apply “balance efficiency”, “postpone”, “balance responsiveness” and “speculate” supply strategies.

The research has focused on process drivers and controllability, and the results may require careful interpretation when there is a mix of standardized and customized products because further interaction differentiation may then be required.

The strategies developed herein provide guidelines for differentiated supplier interaction with explicit focus on triads where customer actors directly influence supplier actors. This approach highlights how outsourcing must be carefully executed when supplier actors are involved in delivery to customer orders.

The paper sheds new light on how customer requirements impact supplier interaction in terms of decoupling points related to both delivery strategy and control strategy. The study also presents a novel application of the Kraljic matrix in in terms of risk strategies in different triad configurations.

The purpose of the paper is to describe ambidextrous learning in organizations within the customer order-based context (COBC), here based on a dynamic view of work processes. The study focuses on how organizations can learn while working with customer orders, considering learning in organizations as both a process and an outcome.

This conceptual article focuses on learning in the COBC, where the individual customer requirements represent a key input into the organization’s work processes, thus limiting the possibilities to plan and standardize. The COBC brings about challenges and potentials for learning in organizations where task variety and complexity are high and in which the contradictory interplay between efficiency and responsiveness is apparent not only at a strategic level but also at an operative level in the customer order fulfillment processes. Depending on the variations in tasks and parallel complex work processes between different units in the organization, the ambidextrous learning dynamic can appear in the COBC.

Five propositions were made from the analysis: Proposition 1: Learning in the COBC can occur both in real-time but also in retrospect and with sporadic and recurrent interventions. Proposition 2: Learning in the COBC can occur for, as well as from, customer order processes. Proposition 3: Learning in the COBC varies and will depend on the delivery strategy. Proposition 4: Learning can be stimulated by the variation in priorities among customer orders in the COBC because the work characteristics for the back office and front office differ between customer order fulfillment processes. Proposition 5: Learning in the COBC can occur both within the back office and front office but also between these organizational units. The paper discusses the importance of building learning infrastructure in COBC and how that can be supported by a suggested learning office.

The present study demonstrates the importance of functions being able to act both as back office and front office in relation to delivery strategy. It also shows the ambidextrous learning process for the sake of improving both the internal efficiency and external effectiveness across the organization.

The customer order decoupling point (CODP) concept addresses the issue of customer engagement in the manufacturing process. This has traditionally been applied to material flows, but has more recently been applied to engineering activities. This later subject becomes of particular importance to companies operating in “engineer-to-order” (ETO) supply chains, where each order is potentially unique. Existing conceptualisations of ETO are too generic for practical purposes, so there is a need to better understand order penetration in the context of engineering activities, especially design. Hence, the purpose of this paper is to address the question “how do customer penetration concepts apply to engineering design activities?”

A collaborative form of inquiry is adopted, whereby academics and practitioners co-operated to develop a conceptual framework. Within this overarching research design, a focus group of senior practitioners and multiple case studies principally from complex civil and structural engineering as well as scientific equipment projects are used to explore the framework.

The framework results in a classification of nine potential engineering subclasses, and insight is given into order penetration points, major uncertainties and enablers via the case studies. Focus group findings indicate that different managerial approaches are needed across subclasses.

The findings give insight for companies that engage directly with customers on a one-to-one basis, outlining the extent of customer penetration in engineering activities, associated operational strategies and choices regarding the co-creation of products with customers. Care should be taken in generalising beyond the sectors addressed in the study.

The paper refines the definition of the ETO concept, and gives a more complete understanding of customer penetration concepts. It provides a comprehensive reconceptualization of the ETO category, supported by exploratory empirical research.