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A plethora of studies focused on the cause and solutions for the bullwhip effect, and consequently many have successfully experimented to dampen the effect. However, the feasibility of such studies and the actual contribution for supply chain performance are yet up for debate. This paper aims to fill this gap by providing a holistic system-based perspective and proposes a fuzzy logic decision-making implementation for a single-product, three-echelon and multi-period supply chain system to mitigate such effect.

This study uses system dynamics (SD) as the central modeling method for which Vensim® is used as a tool for hybrid simulation. Further, the authors used MATLAB for undertaking fuzzy logic modeling and constructing a fuzzy inference system that is later on incorporated into SD model for interaction with the main supply chain structure.

This research illustrated the usefulness of fuzzy estimations based on experts’ linguistically and logically defined parameters instead of relying merely on the traditional demand forecasting based on time series. Despite the increased complexity of the calculations and structure of the fuzzy model, the bullwhip effect has been considerably decreased resulting in an improved supply chain performance.

This dynamic modeling approach is not only useful in supply chain management but also the model developed for this study can be integrated into a corporate financial planning model. Further, this model enables optimization for an automated system in a company, where decision-makers can adjust the fuzzy variables according to various situations and inventory policies.

This study presents a systemic approach to deal with uncertainty and vagueness in dynamic models, which might be a major cause in generating the bullwhip effect. For this purpose, the combination between fuzzy set theory and system dynamics is a significant step forward.

This interdisciplinary investigation examines the topics of organizational climate and subcultures, which have received scant attention in the supply chain literature, highlighting the potential importance of these social dynamics to supply chain management phenomena.

The authors use a single-organization revelatory case study design, qualitatively analyzing coded interviews and observations of participants.

The authors’ findings indicate that a firm's organizational climate can contribute to the formation and strengthening of a subculture and that the subculture may desire to insert their own values and norms concerning supply chain management which could run counter to those of the overall company.

The authors theorize about the conditions under which strong subcultures emerge and that they may exert outsized influence on the way a company approaches supply chain management activities. Accounting for such influence may unearth important social dynamics occurring within supply chain phenomena that will better help researchers understand behavior and outcomes within that phenomenon.

Managers should be aware of the potential for subgroups to form strong subcultures and that subcultures may influence the way supply chain activities are performed. Climate dynamics can also affect employee perceptions and behaviors, and managers should monitor these dynamics and adapt their policies and messaging accordingly.

This study examines a phenomenon that has previously been underexamined in the supply chain management literature–the influence of culture and climate on subcultures and their subcultures' subsequent impact on how companies perform supply chain management activities.

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.

This study aims to examine the interrelationship between resilience, robustness and bullwhip effect using an inventory- and order-based production control system being subjected to operational disruption in the customer demand process.

Control engineering techniques and simulation are employed for the supply chain dynamics study.

The results show that resilience and robustness are two conflicting performance characteristics and therefore, a tradeoff can be established between them. It is also observed that improvement in resilience and reduction of bullwhip effect can be achieved simultaneously through a proper selection of control parameters.

The work establishes a relationship between the resilient behavior of a supply chain and bullwhip effect.

The purpose of this paper is to analyse health service supply chain systems. A great deal of literature is available on supply chain management in finished goods inventory situations; however, little research exists on managing service capacity when finished goods inventories are absent.

System dynamics models for a typical service‐oriented supply chain such as healthcare processes are developed, wherein three service stages are presented sequentially.

Just like supply chains with finished goods inventory, healthcare service supply chains also show dynamic behaviour. Comparing options, service reduction, and capacity adjustment delays showed that reducing capacity adjustment and service delays gives better results.

The study is confined to health service‐oriented supply chains. Further work includes extending the study to service‐oriented supply chains with parallel processing, i.e. having more than one stage to perform a similar operation and also to study the behaviour in service‐oriented supply chains that have re‐entrant orders and applications. Specific case studies can also be developed to reveal factors relevant to particular service‐oriented supply chains.

The paper explains the bullwhip effect in healthcare service‐oriented supply chains. Reducing stages and capacity adjustment are strategic options for service‐oriented supply chains.

The paper throws light on policy options for managing healthcare service‐oriented supply chain dynamics.

This paper offers a novel approach for conducting impactful research on emerging topics or practices. This method is particularly relevant in the face of emerging phenomena and new dynamics, such as the impact of the COVID-19 pandemic on supply chain risks. Because these new phenomena and dynamics are relatively unexplored, little prior knowledge exists in literature and industry, and they represent a large opportunity and/or challenge to practitioners.

The action principles research (APR) approach, as a newer version of critically engaged research (CER), offers comparison against more traditional empirical or intervention-based research. The authors illustrate the approach with a pandemic risk-management study.

The APR approach originated in the information technology field. It is highly applicable for researchers who are seeking to more expeditiously support decision making and actioning on new dynamics and emerging topics and practice in supply chain management than is allowed by traditional methods and longitudinal CER.

In the context of ongoing calls for relevance, impact and actionable findings on pandemic risk management, this paper describes an approach to developing timely findings that are actionable for practitioners and that advance science around dynamic and emerging topics or practices. We hope this will grow societal value of research, particularly in the face of the COVID-19 pandemic and the new dynamics and uncertainties that managers face in modern supply chains.

The purpose of this paper is to present how complexity on retail supply chains should be recognized and its relationship with the performance. Different supply chain structures and planning horizons have been analyzed to support practitioners taking action on the short, mid and long terms. Confronted complexity in the supply chain has been categorized as system, perceived and value adding. This would also help practitioners to understand the sources of the complexity and if the complexity is useful for the system or not.

Three different retail supply chain scenarios – each concentrating on different planning horizons – have been simulated on system dynamics software STELLA. Using the new classification scheme for complexity and suggested performance metrics, a multi-perspective analysis has been performed on the STELLA output.

The results and the methodology can be easily applicable in practice to support decision-making process and to answer “what-if” type scenario analysis on systems design and configuration. Using the selected complexity metrics, complexity of the system considering time factor – static and dynamic – and different information levels – system, perceived and value adding – has been evaluated. Used complexity metrics indicate the problematic areas in the systems to be distinguished.

This paper uses system dynamics modeling in retail supply chains to derive insight about dynamic behavior and to represent the complex interactions and a new classification scheme for system complexity.

The objective of the present study is to model the total supply chain cost (TSCC) of an Indian grain chain in order to understand and predict the future outcome of each supply chain model in different situations and to devise policies accordingly to reduce TSCC.

The system dynamics (SD) approach is used to model the TSCC model of an Indian grain chain, which takes care of the dynamic interaction of the cost variables.

The major findings of the paper are the reduced cost ratios in the different scenarios. A total of nine scenarios are evaluated, which are the cooperative model, contract farming and a collaborative supply chain based on optimistic, pessimistic and most likely views.

The practical implications are the action plans suggested to reduce TSCC in each of the future scenarios of the supply chain model that are developed in the paper.

The TSCC model is beneficial not only for organizations entering into the food business, but also for economic policy makers.

Poultry production supply chains produce substantial wastes that are transformable into favorable environmental outcomes and profitable products. While overwhelming evidence supports this conclusion, scant literature is available on how such transformations are doable. Using systems dynamics, this study addresses this research gap in a national (Bangladesh) context. This study aims to contribute an integrated model for poultry supply chains that incorporate reverse flows of wastes using system dynamics (SD) engineering with empirical simulations.

This study applies SD and simulations of alternative supply chains with versus without reverse loops that transform wastes into viable products in poultry production and downstream marketing operations. This research reports on an in-depth case study of systems thinking and use of the Massachusetts Institute of Technology systems dynamics software. Data for the study are longitudinal and come from written operation records and extensive, repeated, one-on-one Interview from a large poultry plant operation in Bangladesh.

This study finds that several current poultry waste production problems are solvable through an integrated approach that generates viable new marketable products with substantial profitable opportunities that also contributes to reductions in industrial pollution. This study confirms that forward, backward and reverse supply chains need to be under one umbrella system to achieve economic, social and environmental benefits.

This study’s SD model and outputs need additional applications in poultry supply chains in multiple countries. Applying the firm-level model that this study provides is a necessary but insufficient step toward empirical confirmation through replicating.

The purpose of this paper is to study the behaviour of a food supply chain possessing two originalities, i.e. a singular structure (40‐day upstream push and 24‐hour downstream pull) and one that suffers from simultaneous fluctuations in raw material supply capacities (due to epizooty) and customer demand (due to customer anxieties and fears) caused by a sanitary crisis.

A simulation model based on the system dynamics principles of Forrester is developed and applied to the French chicken meat supply chain suffering an Avian Influenza crisis.

This model first enables one us to study the regulation mechanisms of the chain that will improve understanding of the supply chain behaviour under environmental perturbations. A what‐if analysis is then implemented to examine the supply chain stability and the influence of flexibility adjustment times, inventory coverage time, slaughtered chicken buffer size and smoothing policies on the supply chain performance in different crisis fluctuation rate scenarios in order to propose necessary logistic policy enhancements.

This work will improve one's knowledge about the buffer inventory problem and the global stability of this multi‐echelon push‐pull supply chain.

The model can be used as a decision system support which aims to minimise the additional costs due to stock level increases as demand decreases as well as exceptional external purchasing sparked by the lack of available products when there is a sudden hike in demand. The research can help decision‐makers of fresh food push‐pull supply chains when they are facing such crises by using both cybernetic representation and computer simulation.

This study deals with a specific food supply chain within the context of a sanitary crisis. A system dynamics model is presented for studying the behaviour of the entire food supply chain threatened by high uncertainties in the supply capacity as well as in customer demand.