A blockchain-based approach for a multi-echelon sustainable supply chain

Blockchain technology is destined to revolutionise supply chain processes. At the same time, governmental and regulatory policies are forcing firms to adjust their supply chains in response to environmental concerns. The objective of this study is therefore to develop a distributed ledger-based blockchain approach for monitoring supply chain performance and optimising both emission levels and operational costs in a synchronised fashion, producing a better outcome for the supply chain. We propose the blockchain approach for different production allocation problems within a multi-echelon supply chain (MESC) under a carbon taxation policy. As such, we couple recent advances in digitalisation of operations with increasingly stringent regulatory environmental policies. Specifically, with lead time considerations under emission rate constraints (imposed by a carbon taxation policy), we simultaneously consider the production, distribution and inventory control decisions in a production allocation-based MESC problem. The problem is then formulated as a Mixed Integer Non-Linear Programming (MINLP) model. We show that the distributed ledger-based blockchain approach minimises both total cost and carbon emissions. We then validate the feasibility of the proposed approach by comparing the results with a non-dominated sorting genetic algorithm (NSGA-II). The findings provide support for policymakers and supply chain executives alike.     

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.     

Impacts of using a performance measurement system in supply chain management: a case study

The study examines how the utilisation of a new performance measurement system (PMS) influences supply chain management (SCM) and what kind of impacts the new system has on the performance of the supply chain. The paper utilises a longitudinal research setting where the data was gathered in two semi-structured interview studies after an action research project in which a new measurement system was designed and developed. The findings show how a PMS serves as a catalyst of inter-organisational knowledge transfer and promotes shared learning. The results also show how knowledge transfer and shared learning led to improved performance of the supply chain. The paper contributes by opening up the practical mechanisms through which performance measurement provides value for SCM and by showing how inter-organisational transfer of performance information catalyses learning and performance improvement. The paper looks beyond the design of performance measures and provides a view on the practice of supply chain performance management. The paper illustrates how sharing performance information amongst supply chain companies improves managers’ awareness of shared targets and the status of network operations. This also resulted in improved performance in the studied case network. Overall, the results encourage organisations to engage in network-level performance measurement and share performance information with their network partners.     

Applying performance measures to support decision-making in supply chain operations: a case of beverage industry

Performance measurement systems (PMS) have commonly been applied to evaluate and reward performances at managerial levels, especially in the context of supply chain management. However, evidence suggests that the effective use of PMS can also positively influence the behaviour and improve performance at an operational level. The motivation is to accomplish organisational goals, namely to increase supply chain flexibility by responding to evermore-varying customer demands in a timely manner. The purpose of the study described in this paper was to develop a conceptual framework that adopts performance measures for ex-ante decision-making at an operational level within the supply chain. To guide the research, five questions were asked and subsequently key gaps have been identified. In an attempt to fill the gaps, a case study at a major global brand beverage company has been carried out, and as a result, a conceptual framework of the PMS has been developed. Overall, the research offers a foundation of the applicability and impact of PMS in the supply chain and provides a framework that attends to some of the potential uses of PMS that so far have not been practically applied. The outcomes from the testing indicate that the initial gaps identified in the literature have been addressed and that the framework is judicious with scope for practical applicability. The framework is deemed worthy of further testing in different operational contexts of the supply chain.     

The performance impact of supply chain agility and supply chain adaptability: the moderating effect of product complexity

Even though research has suggested that supply chain agility and supply chain adaptability are distinct capabilities, little is known about their performance effects and about the contextual conditions under which they are effective. Based on a sample of 143 German firms, we empirically investigate the effects of supply chain agility and supply chain adaptability on cost performance and operational performance using hierarchical regression analysis. We ground our investigation in the dynamic capabilities view and contingency theory. We find that supply chain agility and supply chain adaptability positively affect both cost performance and operational performance. We further find evidence for a mediating role of supply chain agility in the links between supply chain adaptability and performance. Product complexity positively moderates the links between supply chain adaptability and cost performance, and supply chain adaptability and operational performance. The results contribute to the literature by offering a more nuanced understanding of the performance implications of supply chain agility and supply chain adaptability, thereby addressing the crucial question of why their benefits may or may not materialise under varying levels of product complexity.     

Coordination and performance analysis for a three-echelon supply chain with a revenue sharing contract

This paper focuses on a three-echelon supply chain composed of a manufacturer, a distributor and a retailer for a single selling period. Based on a revenue sharing contract, the coordination of the decentralised supply chain with the simultaneous move game or the leader–follower game is analysed. It is determined that the revenue sharing contract can coordinate the decentralised supply chain with the simultaneous move game. Our analysis reveals that the revenue sharing contract cannot coordinate the decentralised three-echelon supply chain with the leader–follower game except for a special situation. However, this result provides an opportunity to develop methodology and results that measure the potential improvement in supply chain performance that can be gained from utilising the revenue sharing contract. This is an important aspect of this paper.     

A simulation-optimisation approach for supply chain network design under supply and demand uncertainties

We investigate a three-echelon stochastic supply chain network design problem. The problem requires selecting suppliers, determining warehouses locations and sizing, as well as the material flows. The objective is to minimise the total expected cost. An important feature of the investigated problem is that both the supply and the demand are uncertain. We solve this problem using a simulation-optimisation approach that is based on a novel hedging strategy that aims at capturing the randomness of the uncertain parameters. To determine the optimal hedging parameters, the search process is guided by particle swarm optimisation procedure. We present the results of extensive computational experiments that were conducted on a large set of instances and that provide evidence that the proposed hedging strategy constitutes an effective viable solution approach.     

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.     

The effect of human factors on the performance of a two level supply chain

Many studies have addressed the issue of coordination in a supply chain. Coordinating mechanisms such as joint lot sizing models, quantity discounts and delay in payments have been used to achieve coordination in a supply chain. An important omission in this literature is the role of human factors, in particular inspection errors and learning, as a tool to improve coordination in a supply chain. In this paper, two coordination mechanisms found in the literature are integrated into a model for a two-level supply chain in which the incoming quality level of raw materials provided to a vendor by a set of suppliers is not perfect. The model addresses supply chain coordination by specifically investigating the role of different human factors on the total cost of the supply chain. These factors are: (a) type I and type II inspection errors; (b) learning in the production process; and (c) learning in quality at the suppliers’ end. Numerical examples are used to compare the costs of the three extensions with the base model (with no defectives).     

Analytical foundations for development of real-time supply chain capabilities

The emergence of real-time supply chain visibility technologies has raised challenges for organisations in developing the required management capabilities required to exploit enhanced visibility. The convergence of cloud computing, mobile technology, distributed computing, and data integration technologies has enabled managers for the first time to have real-time visibility of material flows in end to end supply chains, enhancing their ability to identify bottlenecks and disruptions of material flows anywhere in their network. To effectively harness these technologies, a new set of managerial decision-making capabilities as well as enhanced data governance disciplines will be required. In this research, we employ organisational information processing theory to explore the relationship of analytical capabilities, data quality, reporting quality, and real-time data capabilities on supply chain performance. Our research model suggests that the benefits of real-time information technologies are dependent on quality reporting and managerial analytical strengths to derive supply chain benefits. The implications for managerial applications and research are further described based on these findings.     

Examining the effects of green supply chain management practices and their mediations on performance improvements

Environmental pressures have caused green supply chain management (GSCM) to emerge as an important corporate environmental strategy for manufacturing enterprises. For manufacturers to fully realise the performance potentials of GSCM, they need to integrate internal GSCM practices emphasising functional coordination with external GSCM practices such as cooperation with suppliers and customers in the implementation. Using coordination theory, this article examines three models used to evaluate the mediation relationships between the external and internal practices of GSCM with respect to environmental, economic, and operational performance. We posit that the strategic stance of manufacturing enterprises in improving their overall performance and competitive position requires a joint coordination of internal and external GSCM practices. Survey data collected from 396 Chinese manufacturing enterprises are used to validate our arguments by testing the mediation effects of two categories of GSCM practices. Our empirical results show support for the mediation effects, which indicates the importance for manufacturers to coordinate between the internal and external aspects of implementing GSCM practices to reap the performance benefits. Coordinating internal and external GSCM practices to seek performance improvements is an important aspect of the manufacturing operations strategy. The dynamics of implementing GSCM practices and the performance contingencies are worthwhile topics to pursue in future research.     

A control engineering approach to the assessment of supply chain resilience

There is no consensus on the supply chain management definition of resilience. To aid in evaluating the dynamic behaviour of such systems we need to establish clearly elucidated performance criteria that encapsulate the attributes of resilience. A literature review establishes the latter as readiness, responsiveness and recovery. We also identify robustness as a necessary condition that would complement resilience. We find that the Integral of the Time Absolute Error (ITAE) is an appropriate control engineering measure of resilience when it is applied to inventory levels and shipment rates. We use the ITAE to evaluate an often used benchmark model of make-to-stock supply chains consisting of three decision parameters. We use both linear and nonlinear forms of the model in our evaluation. Our findings suggest that optimum solutions for resilience do not yield a system that is robust to uncertainties in lead-time. Hence supply chains will experience drastic changes in their resilience performance when lead-time changes.     

Approximate analysis of serial flow lines with multiple parallel-machine stations

This paper studies serial flow lines, in which each station consists of multiple identical reliable parallel machines. The parallel machines of different work stations are not necessarily identical, viz., station processing times are assumed to be exponentially distributed with non-identical mean service rates. Initially, a model consisting of two stations with multiple parallel machines and an intermediate buffer is solved analytically, by developing a recursive algorithm that generates the transition matrix for any value of the intermediate buffer capacity. This model is used as a decomposition block for solving larger lines. More specifically, the decomposition block is solved via exact Markovian analysis and then the decomposition equations and an algorithm that simultaneously solves them are derived in order to evaluate the performance measures of large production systems with multiple parallel-machine stations. Numerical results are provided for large production lines with up to 1000 workstations. These results are compared against simulation and the average percentage error is found to be very small.     

Effects of information transparency and cooperation on supply chain performance: a simulation study

This research explores the effect of information transparency and cooperation among the front nodes of supply chains. Although published works in the supply chain (SC) domain underline the need for information transparency and cooperation for competitiveness of firms, the majority among these are conceptual or empirical. As such, the domain requires fresh effort towards analytical and simulation based research for validation. In the present work, simulation is used as the research methodology. The simulation platform is developed in ARENA®, which is based on simulation language SIMAN. It has the capability to model multi-product, multi-echelon supply chains. Cooperation is depicted in the form of demand pooling and accelerated delivery of consignments from cooperating SC nodes, when stock-out contingency occurs at a particular node. The modelling also explores the effects of full, partial and zero level of information transparency on the SC performance. The simulation results suggest that these initiatives improve SC service time performance. It is also observed that more advantages from cooperation and information transparency are obtainable when the SC is leaner. The studies also highlight that such SC initiative that motivates local optimisation at the nodes is counter-productive to SC wide performance.     

Quick response strategy with cleaner technology in a supply chain: coordination and win-win situation analysis

Quick response strategy (QRS) has been widely adopted in a supply chain where members collect timely market information for better forecasting, and then respond promptly to the market changes by adjusting initial inventory decision. After adopting the QRS, sustainability issues such as greenhouse gas emission and energy waste may be more serious as production lead time is shorter. In this study, due to this dilemma, we develop a two-stage quick response supply chain with cleaner technology, where the manufacturer determines the cleaner technology investment and afterwards the retailer decides the ordering quantity. Based on Bayesian theory, we depict an information updating process for the QRS with cleaner technology. First, we find that the inventory service level significantly affects both manufacturer’s and retailer’s performance under the QRS with cleaner technology. Moreover, our analytical results indicate that the performance of centralised supply chain system is always better than the decentralised one. As a result, we propose two supply chain contracts, minimum ordering quantity (MOQ) and MOQ with buyback (MOQ-BB) to achieve supply chain coordination. Comparing with the MOQ, the MOQ-BB is more flexible to allow better allocation of the ‘additional’ expected profit between the channel members through the buyback price negotiation.     

A dynamic model for serial supply chain with periodic delivery policy

A three-echelon, dynamic lot-sizing model is presented for computing the parameters of a serial supply chain, which consists of integrated material replenishment, production at a capacity constraint, and outbound dispatching with a periodic delivery policy. The model is applicable in the general context of a three-echelon model with capacity constraint at the middle echelon of the serial supply chain which was not considered in most of the literature. This paper addresses a number of structural properties of the model and proposes a polynomial-time algorithm for deriving the optimal solution of minimising the total system costs over the planning horizon. Examples are provided to describe the algorithm.     

Disruption risks in supply chain management: a literature review based on bibliometric analysis

Disruption risks in supply chain management have a great negative influence on the performance of supply chain members. Therefore, the field of supply chain disruption (SCD) has received increasing attention on mitigating the risks and improving the supply chain performance. This paper presents a comprehensive bibliometric overview and visualisation of the field of SCD based on 1,310 publications derived from the core collection of the Web of Science. The influential authors, organisations, and SCD keywords are discussed in detail based on some visualisation tools. Then, the leading publications and main clusters of SCD are identified to find out the key research topics based on citation analysis and reference co-citation analysis. The paper will be a helpful resource for researchers and practitioners who are interested in the field of SCD to capture the current research hotspots and potential research directions.     

Game-theoretical analysis for supply chain with consumer preference to low carbon

This paper focuses on the impact of consumers’ preference to low carbon in the emission-concerned supply chain. In an emission-concerned supply chain, the consumers are assumed to prefer to low-carbon products. In an emission sensitive market, emission reduction not only brings the higher production costs but also stimulates the inverse demand function. Therefore, this may be an opportunity for players of the supply chain to coordinate their two objectives: environmental pressure (to reduce carbon emissions for environment protection) and profit-seeking, which intuitively seem to be contradictory. In order to address this research focus, a novel emission-sensitive demand function is adopted, and an emission -sensitive cost function is introduced explicitly to capture the deviation production cost caused by emission reduction. Then the decision-making of each member in the emission-concerned supply chain is investigated. We find that the decision-maker of the supply chain will choose different emission reduction strategies for different cases. An inspiring result shows that the channel profit as well as the emission reduction increase in the consumers’ preference to low-carbon consumption simultaneously in particular cases. Moreover, several emission-concerned contracts are designed to coordinate the channel. Another finding is that the manufacturer’s optimal carbon emissions per unit product keeps the same as the centralised channel, no matter whether the supply chain is coordinated or not. Furthermore, the further discussion reveals that less eco-friendly production than the traditional, if lack of external regulation as well as internal moral self-discipline, might be chosen under some specific conditions.     

Multi-period hedging and coordination in a prefabricated construction supply chain

In this paper, a multi-period buffer space hedging coordination between a building contractor (BC) and a logistics provider (LP) is investigated. In order to facilitate the application of the construction lead-time hedging (CLTH) strategy, adopted by the BC, extra buffer space needs to be reserved at LP’s intermediate warehouse for contingency usage. This strategy is defined as ‘buffer space hedging (BSH)’ and it increases the pressure of LP on involving extra storage and maintenance cost. Two coordination mechanisms are adopted for solving this BSH problem. One scheme is by introducing a cost-sharing term. A Nash game model is studied to find the individual optimal decisions. Another scheme is a cooperative game model with proper side-payments. We show that adjusting the BSH amount for each review period benefits the supply chain. Both coordination mechanisms enable a win–win outcome. Especially, if system resources are sufficient, the cooperative game outperforms the Nash game. Numerical experiments further demonstrate that the benefit of the proposed model is more significant under the case with lower unit enlarging/rearrangement cost, higher tardiness penalty and unpredictable and uncontrollable construction process-determined assembled and installed prefabs.     

A green supply chain is a requirement for profitability

Many companies are not dramatically changing to more sustainable environmental practices despite pressure from the investment community, the government and consumers. This study explores a simple model that companies can use to understand and improve supply chain sustainability practices. It applies this model in two case studies, Coca-Cola, a leader in global sustainability, and Apple, a company that has only recently started to develop a sustainability strategy. The model was developed through a review of existing research and an application of supply chain principles. The results of this study demonstrate that following this model to eliminate waste throughout the supply chain will make the supply chain more profitable. The outcomes from this study highlight the importance for every company to do so in order to stay competitive. This study is unique in the relative simplicity of its model, combined with the supporting evidence that a sustainable supply chain is the same as a supply chain that is using best practices to reduce waste.