Inventory decision-making models for a closed-loop supply chain system

In this paper, we investigate how buyers’ and suppliers’ distinct perceptions of technology uncertainty affect the relationship between communication frequency and supplier performance. Information processing theory suggests that a fit is desirable between perceived environmental uncertainty and the communication processes between organisations. However, if partners in a buyer-supplier relationship do not concur on the high level of technology uncertainty, it is highly questionable whether increased communication will be effective in increasing supplier performance. Using dyadic data from 86 buyer-supplier relationships, involving 388 respondents, we found that communication frequency was positively related to supplier performance only when both suppliers and buyers perceived high levels of technology uncertainty. When buyers perceived greater technology uncertainty than their suppliers, communication frequency was negatively related to supplier performance. The findings in this study show that it is important to take the distinct perceptions of buyers and suppliers of technology uncertainty into account when assessing the effects of communication frequency. It appears that increased communication is only effective when both parties acknowledge the need to communicate, and can be unfavourable when only one party sees the benefits of it.     

The impact of collaborative transportation management on demand disruption of manufacturing supply chains

This paper describes the impact of collaborative transportation management (CTM) on the performance of manufacturing supply chains using a multi-agent approach. Two supply chain models (with and without CTM) are proposed to show how it realises the real operational interactions between different supply chain partners under demand disruption. Simulation results of the proposed models reveal the evolution of the CTM supply chain with demand disruption. The dynamic delivery ability and order point which are caused by demand disruption in the CTM supply chain are investigated. The results indicate that CTM can significantly reduce costs and improve the flexibility of companies in handling demand disruption problems. It is suggested that CTM is an efficient mechanism to manage supply chains, especially under a demand disruption environment.     

Revealing interfaces of supply chain resilience and sustainability: a simulation study

Dynamics of structures and processes is one of the underlying challenges in supply chain management, where multiple dimensions of economic efficiency, risk management and sustainability are interconnected. One of the substantiated issues in supply chain dynamics is resilience. Resilience has a number of intersections with supply chain sustainability. This paper aims at analysing disruption propagation in the supply chain with consideration of sustainability factors in order to design resilient supply chain structure in regard to ripple effect mitigation and sustainability increase. Ripple effect in the supply chain occurs if a disruption at a supplier cannot be localised and cascades downstream impacting supply chain performance. This simulation-based study helps to identify what sustainability factors mitigate the ripple effect in the supply chain and what sustainability factors enhance this effect. The results indicate that (i) sustainable single sourcing enhances the ripple effect; (ii) facility fortification at major employers in regions mitigates the ripple effect and enhances sustainability; and (iii) a reduction in storage facilities in the supply chain downstream of a disruption-risky facility increases sustainability but causes the ripple effect.     

Additive manufacturing technology in spare parts supply chain: a comparative study

Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains.     

Mapping the future of supply chain management: a Delphi study

Supply chain management, a field that developed from business practice and research, is undergoing a major transformation. It is changing from tactical in nature (where the major focus is on cost and delivery) to a field that is strategic in nature. However, the future issues and challenges facing managers and executives are just now becoming understood. This paper reports these issues by drawing on the findings generated by a three-phase study consisting of a literature review, a two-round Delphi study, and a workshop. Unique in this Delphi study is that it brings together leading practitioners in supply chain management with leading supply chain management researchers. The findings show that while the focus of the current tactical supply chain view is relatively limited to issues of delivery, risk, and leadership, the supply chain view of the future (i.e., five years from now) is more complex and demanding. The findings also show that there is generally no difference between researchers and practitioners in terms of how they view the issues. Finally, the study uncovers major obstacles that must be resolved before the strategic potential of future-state supply chains can be realised.     

New flexibility drivers for manufacturing,supply chain and service operations

Increasing product proliferation, customisation, competition and customer expectations, as well as supply side disruptions, pose significant challenges to firm operations. Such challenges require improved efficiency and resilience in manufacturing, service and supply chain systems. New and innovative flexibility concepts and models offer a prospective route to such operational improvements. Several emerging issues in flexibility, such as risk and uncertainty management, environmental sustainability, optimal strategies under competition, optimal operations with strategic consumer behaviours are being examined in this regard. This overview provides a concise review of these critical research issues, and discusses related papers featured in this special issue. Four major flexibility drivers are classified: disruption risks, resilience and the ripple effect in the supply chain; digitalisation, smart operations and e-supply chains; sustainability and closed-loop supply chains; and supplier integration and behavioural flexibility.     

Inventory performance of some supply chain inventory policies under impulse demands

This paper attempts to study the impact of impulsive demand disturbances on the inventory-based performance of some inventory control policies. The supply chain is modelled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). Under this setting, the behaviour of each inventory policy is analysed for inventory performance of each node. It is found that the independent decision-making by each node leads to a bullwhip effect in the supply chain whereby demand information is amplified and distorted. However, under a scenario where the retailer places a constant order irrespective of the end customer demand, the inventory variance was actually found to decrease along the supply chain. The variance of the inventory remained constant along the chain when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes. The results have significant industrial implications.     

Determinants of mobile supply chain management system diffusion: a structural equation analysis of manufacturing firms

Mobile supply chain management (SCM) is gaining recognition as a major source of cost reduction and supply chain performance improvement. The current literature related to mobile SCM needs to be extended further in order to provide insights into how manufacturing firms can implement mobile SCM successfully. Specifically, there is a need to provide empirical and systematic analysis of the variables that can explain the various stages of mobile SCM diffusion. A review of recent literature suggests that existing e-supply chain technology adoption literature is not strongly grounded in theory. A theoretical model with six hypotheses was proposed based on the technology–organisation–environment (TOE) framework and innovation diffusion theory (IDT). This study draws its survey responses from a group of manufacturing firms in order to investigate the factors that affect the diffusion of mobile SCM. The results show that the variables derived from TOE and IDT can explain mobile SCM diffusion well. However, interorganisational relationships (IORs) play a crucial role in determining the success of mobile SCM routinisation. This is one of the first known empirical studies on the factors influencing the diffusion of mobile SCM. The results of this study will help decision makers better understand the implementation process of mobile SCM and formulate strategies for successful diffusion of mobile SCM.     

A technology selection framework for integrating manufacturing within a supply chain

This paper describes a structured analytical approach for selecting a manufacturing technology. A framework consisting of six integrated steps is proposed by considering the growing importance of supply chains in manufacturing organisations. The framework makes use of the analytical hierarchy process (AHP) approach combined with strategic assessment model (SAM) to evaluate and select the technologies appropriate for providing overall competitive advantage. The framework is intended to assist industrial managers in promoting manufacturing and supply chain collaboration and co-ordination by including intra-organisational perspective in their organisational technology selection decision making process.     

绿色供应链管理的基本原理

人口、资源与环境三者之间的矛盾日益突显，要求制造业提高其活动与环境的相容性。绿色供应链管理是从系统的观点与集成的思想出发解决制造业与环境之间冲突的有效方式。从可持续发展的思想出发建立了绿色供应链的概念模型，分析了绿色供应链管理的目标，在此基础上探讨了绿色供应链管理的基本原理，认为共生原理、循环原理、替代转换原理与系统开放原理是实施绿色供应链管理应该遵循的基本原理。     

Traceability as a means to investigate supply chain sustainability: the real case of a leather shoe supply chain

In recent years, the growing attention to environmental challenges has shown that these issues are becoming of more and more interest to both research and industry. Companies are expected to ensure their products are fully traceable and more sustainable, which requires the involvement of all of the actors in the production network. According to this aim, this study proposes a structured approach that uses the traditional traceability concept as a means to identify the main information needed to assess environmental impacts along the whole supply chain (SC). The proposed approach is composed of four main steps: (i) SC modelling to identify all stakeholders and their inter-relations, (ii) data sharing to collect all relevant data, (iii) data elaboration to calculate performance at different levels of detail and (iv) result interpretation to optimise the SC. The distributed implementation of the approach at different SC steps represents a useful means to practically realise a sustainable SC management. A case study involving a leather shoe SC is used to demonstrate the effectiveness of the approach in identifying criticalities, supporting the selection of the most appropriate suppliers and correctly setting a management strategy towards the optimisation of internal and external traceability and environmental sustainability performances.     

How will the diffusion of additive manufacturing impact the raw material supply chain process?

This study investigates the potential of additive manufacturing (i.e. 3D printing) to alter established manufacturing and supply chain processes, complementing previous research work that deals with additive manufacturing and rapid prototyping. Additive manufacturing is a manufacturing technique, which allows the direct fabrication of three-dimensional design models using an additive approach by adding layer after layer. As additive manufacturing is inherently less wasteful and only applies raw material where needed, it constitutes a chance to reduce materials usage and related inventories. Even though the technology has faced considerable hype, its adoption still does not match the high expectations. The aim of this study is to overcome limitations of state-of-the-art impact assessments by integrating the potential reduction of materials inventories through the adoption of additive manufacturing in manufacturing and to point out possible implications for supply chain processes. For this purpose, a dynamic evaluation model was developed analysing the adoption of additive manufacturing by integrating the Bass Diffusion Model to provide interesting and novel results for both practitioners and researchers. The study shows that additive manufacturing can indeed reduce raw materials inventory by approximately 4% and that the diffusion rate is likely to be affected by the utility of the technology.     

Information management strategies and supply chain performance under demand disruptions

The operations management literature presents inadequate comprehensive understanding on information management strategies of mitigating supply chain disruption risks. By using control theory modelling and simulation, this study compares the disruption mitigation effects of three information management strategies. From the aspect of stability, the existing stability boundaries are revised by a new method in a two-echelon case. It shows that supply chains (SC) with popular information management strategies are not evidently more stable than traditional ones. From the aspect of disruption recovery time, an innovative two-echelon swiftest response problem under these information management strategies is formulated and solved. Results show that a collaborative planning, forecasting and replenishment (CPFR) SC with complete SC information performs the best. However, in a later operational risk mitigation test, an information sharing (IS) SC with partial information has the smallest bullwhip effect. From the aspect of demand amplification and frequency response, an innovative frequency–response plot of order amplification is proposed in a time-continuous SC with moving average forecasts. It implies the best frequency response for concurrently mitigating both operational and disruption risks coming from a CPFR SC. But for a certain SC structure there is still a balance between mitigating bullwhip effect and quick response. Moreover, it also implies that anti-bullwhip should exist in a certain condition, as realised in our numerical experiments.     

An object-oriented simulation meta-model to analyse supply chain performance

This paper proposes a meta-model, which allows automatic building of simulation models of supply chains. The proposed meta-model is made up from a user interface (to define the characteristics of the supply chain), an ad hoc objects library and a software application, to build the simulation model. The meta-model can dramatically reduce to a few minutes or even seconds the time required to test a specific configuration of a supply chain and/or a specific management policy and, since the simulation model is automatically built, neither the personnel skills nor the time available to build the simulation model represent significant hurdles anymore. The meta-model has been applied to represent a simplified supply chain according to six different scenarios, where demand is deterministic. For each scenario a simulation campaign has been performed and the outputs of the model (built through the proposed meta-model) correspond to the predicted results.     

A matrix-based Bayesian approach for manufacturing resource allocation planning in supply chain management

Nowadays, the supply chain of manufacturing resources is typically a large complex network, whose management requires network-based resource allocation planning. This paper presents a novel matrix-based Bayesian approach for recommending the optimal resource allocation plan that has the largest probability as the optimal selection within the context specified by the user. A proposed matrix-based representation of the resource allocation plan provides supply chain modelling with a good basis to understand problem complexity, support computer reasoning, facilitate resource re-allocation, and add quantitative information. The proposed Bayesian approach produces the optimal, robust manufacturing resource allocation plan by solving a multi-criteria decision-making problem that addresses not only the ontology-based static manufacturing resource capabilities, but also the statistical nature of the manufacturing supply chain, i.e. probabilities of resource execution and resource interaction execution. A genetic algorithm is employed to solve the multi-criteria decision-making problem efficiently. We use a case study from manufacturing domain to demonstrate the applicability of the proposed approach to optimal manufacturing resource allocation planning.     

供应链协同库存策略分析

采用形式化描述的方式,对不同的协同库存策略进行了统一和完整的分类,从产品交付、信息传递和库存决策3个方面得到了9种原子形式的协同库存策略及策略集合,同时在分类的基础上对协同策略的集成度进行了分析.采用案例分析的方法分析了多个企业实际应用协同库存策略的情况,对文中提出的模型和分类进行了验证.研究结果使得企业对各种协同库存策略能够有清晰的认识,在明确企业集成意向的情况下,可以对比文章给出的模型选择相应的库存策略.     

Integrated supply chain risk management via operational methods and financial instruments

Supply chain risk management (SCRM) is an emerging field that generally lacks integrative approaches across different disciplines. This study contributes to narrowing this gap by developing an integrated approach to SCRM using operational methods and financial instruments. We study a supply chain composed of an aluminium can supplier, a brewery and a distributor. The supply chain is exposed to aluminium price fluctuation and beer demand uncertainty. A stochastic optimisation model is developed for managing operational and financial risks along the supply chain. Using this model as a base, we compare the performance of an integrated risk management model (under which operational and financial risk management decisions are made simultaneously) to a sequential model (under which the financial risk management decisions are made after the operational risk management decisions are finalised). Through simulation-based optimisation and using experimental designs and statistical analyses, we analyse the performance of the two models in minimising the expected total opportunity cost of the supply chain. We examine the supply chain performance as a function of three factors, each at three levels: risk aversion, demand variability and aluminium price volatility. We find that the integrated model outperforms the sequential model in most but not in all cases. Furthermore, while the results indicate that the supply chain improves its performance by being less risk averse, there exists a threshold beyond which accepting a higher risk level is not justified. Managerial insights are provided for various business scenarios experimented with.     

The impact of supply chain analytics on operational performance: a resource-based view

This study seeks to better understand the role of supply chain analytics (SCA) on supply chain planning satisfaction and operational performance. We define the architecture of SCA as the integration of three sets of resources, data management resources (DMR), IT-enabled planning resources and performance management resources (PMR), from the perspective of a resource-based view. Based on the data collected from 537 manufacturing plants, we test hypotheses exploring the relationships among these resources, supply chain planning satisfaction, and operational performance. Our analysis supports that DMR should be considered a key building block of manufacturers’ business analytics initiatives for supply chains. The value of data is transmitted to outcome values through increasing supply chain planning and performance capabilities. Additionally, the deployment of advanced IT-enabled planning resources occurs after acquisition of DMR. Manufacturers with sophisticated planning technologies are likely to take advantage of data-driven processes and quality control practices. DMR are found to be a stronger predictor of PMR than IT planning resources. All three sets of resources are related to supply chain planning satisfaction and operational performance. The paper concludes by reviewing research limitations and suggesting further SCA research issues.     

Structural-aware simulation analysis of supply chain resilience

Supply chain resilience (SCRES) refers to the ability of a supply chain (SC) to both resist disruptions and recover its operational capability after disruptions. This paper presents a simulation model that includes network structural properties in the analysis of SCRES. This simulation model extends an existing graph model to consider operational behaviours in order to capture disruption-recovery dynamics. Through structural analysis of a supply chain network (SCN), mitigation strategies are designed to build redundancy, while contingency strategies are developed to prioritise recovery of the affected SCN. SCRES indexes are proposed by sampling SC performance measures of disruption for each plant and aggregating the measures based on the criticality of the plants in the SCN. The applicability of this simulation model is demonstrated in a real-world case study of different disruption scenarios. The application of mitigation and contingency strategies is shown to both improve recovery and reduce the total costs associated with disruptions. Through such simulation-based analysis, firms can gain insight into the SCRES of their existing SCNs and identify suitable strategies to improve SCRES by considering recovery time and costs.     

On measuring company performance within a supply chain

Emerging research strengthens the connection between supply chain performance and a company's financial performance (D’Avanzo, R., Von Lewinski, H. and Van Wassenhove, L. N., 2003. The link between supply chain and financial performance. Supply Chain Management Review, November/December, 40–47). The focus on integrating functional internal processes has expanded to include the need for integrating these with external processes of business partners (Edwards, P., Peters, M. and Sharman, G., 2001. The effectiveness of information systems in supporting the extended supply chain. Journal of Business Logistics, 22(1), 1–27). This need for enterprise efficiency is compelling companies to review, to identify, and to adopt supply chain initiatives. This research investigates the use of common measurement metrics in an attempt to determine which one(s) are most useful for measuring performance as companies implement SCM practices. For firms that were engaged in SCM we found inventory and cycle time to be the most significant metrics.