What is the role of value-added service in a remanufacturing closed-loop supply chain?

While the previous literature overlooks value-added service in a closed-loop supply chain (CLSC), we consider new research problems with embedding value-added service into remanufacturing models. In this paper, we mainly study the role of value-added service in a CLSC and investigate how the value-added service influences profits and other decision variables. Then, we evaluate the performance of the CLSC in different service structures, where a manufacturer or a retailer provide the value-added service. Systematic comparisons and numerical studies show that the supply chain is more effective when service is provided by a manufacturer rather than by a retailer. Also, value-added service improves the whole supply chain performance and plays a regulatory role in a CLSC and influences the decisions of supply chain members. We also show that while a service cost-sharing mechanism can only optimise rather than achieve the supply chain coordination, and the degree of optimisation depends on cost-sharing percentage, the two-part tariff contract can be an effective mechanism to coordinate decentralised service scenarios by generating the same supply chain performance in a centralised service architecture model.     

Distributed supply‐chain project rescheduling: Part I—impacts of information‐sharing strategies

A supply‐chain project normally involves a number of independent and autonomous enterprises that share information to varying levels. The initial project schedule (preschedule) established at the time of forming the supply‐chain often requires a series of amendments due to unexpected or abrupt disturbances such as temporary resource outage (e.g. machine break), arrival or cancellation of orders from customers, and change in an operation's processing time (e.g. rework). Rescheduling or adaptive scheduling is a process of updating/repairing the preschedule to adapt to the disturbances. Appropriate rescheduling methods must be chosen and applied depending on the specific protocol of sharing information agreed between the enterprises in the supply chain. This paper is concerned with the impacts of different levels of information sharing on the performance of supply‐chain project rescheduling problems. Three rescheduling methods are examined in the research. They are distributed AOR (Affected Operations Rescheduling), negotiation‐based rescheduling (NEG), and centralized total rescheduling (TR). These three rescheduling algorithms represent three typical information‐sharing scenarios: little information sharing, limited information sharing and complete information sharing, respectively. A comprehensive computational study is conducted under different experimental settings. The results show that NEG and distAOR outperforms the TR rescheduling in terms of total cost minimization and stability of schedule and contractual relationship. NEG is superior in both rescheduling efficiency and effectiveness due to the effect of a moderate level of information sharing.     

Analysis of retailers’ coalition stability for supply chain based on LCS and stable set

To attain the general form of stable coalition structure, this paper addressed the problem of retailers’ coalition stability in a two-stage supply chain consisting of one supplier and multiple retailers. A profit gain function was established via introducing market gain coefficient and coalition cost coefficient for different coalition structures. Based on the function, the profit of each retailer in all kinds of coalition structures was analysed, and the general feature of a stable coalition structure was attained by the largest consistent set method and the stable set method. Furthermore, some insights were obtained. For example, stable coalition structures are equidistributed or approximate equidistributed; with supplier’s cost increasing, the size of the retailers’ coalition increases. Finally, the above conclusions are verified by numerical simulation. The results of this paper provide a reference for retailers’ coalition in a supply chain, such as automobile or Information Technology supply chain.     

Impact of modelling approximations in supply chain analysis – an experimental study

This paper presents a study of the comparison of the quality of results obtained at different levels of detail using a supply chain simulation. Analysis of supply chain is typically carried out using aggregated information to maintain the level of complexity of the simulation model at a manageable level. Advances in simulation have provided the ability to build comprehensive (detailed), modular models. The quantitative effect of detailed modelling on the corresponding analysis is investigated in this paper. A three-echelon supply chain is analysed using simulation models of varying levels of detail. Using each of these models, four sets of intensive experiments are performed. The first experiment intends to test whether the supply chain dynamics themselves depend on the modelling accuracy that represents the supply chain. The second and third experiments are conducted to test whether the effectiveness of the strategies employed to reduce the supply chain dynamics vary depending on the type (different detail) of model representing the supply chain. In the fourth experiment, statistical techniques are employed to identify which modelling aspect has the most influence on the supply chain dynamics. It is found that the approximations used in modelling, such as delays and capacity, have more impact on the outcome of supply chain analysis than end customer demand. Evidence that both the basic problem (supply chain dynamics) and the solution (strategy to reduce the dynamics) are greatly influenced by the modelling accuracy are presented.     

Antecedents of proactive supply chain risk management – a contingency theory perspective

Since supplier insolvencies are a major source of supply chain disruptions, scholars have continuously suggested managing supply chain risk management (SCRM) proactively in order to avoid their occurrence. However, business practice seems to fail with this task. This paper investigates antecedents which foster proactive SCRM implementation from a contingency theory perspective. As a major contingency we choose past supplier insolvencies as an indicator for the level of vulnerability of organisations and investigate inter-organisational, intra-organisational, and individual antecedents. By consulting supply chain management and management accounting literature, hypotheses are developed and tested via content analysis in 63 interviews with representatives from the automotive industry. The findings demonstrate that a mechanistic management control system, a rational cognitive style and relational buyer–supplier relationships have positive impacts on proactively managing supplier insolvency risks. Furthermore, past experience with supplier insolvencies has a moderating, though not a direct, effect on proactiveness. This research suggests that a holistic risk management approach is required to proactively mitigate supplier insolvency risk.     

Impact of the pull and push‐pull policies on the performance of a three‐stage supply chain

We investigate the performance of two common operating policies (i.e., pull and push‐pull) for a make‐to‐stock product in an un‐capacitated, three‐stage supply chain. The pull policy operates based on periodic orders received from the immediate downstream facility. However, in the push‐pull policy, while processes upstream of the order decoupling point are managed by the push policy, the downstream processes are managed by the pull policy. Simulation experiments are conducted to examine the impact of each operating policy under a variety of experimental conditions, characterised by demand uncertainty and lead‐time variability. Our results indicate that the relative advantage of the two policies is dependent on the type of uncertainty, the level of uncertainty, the inventory control policy and the performance measures of interest. More specifically, while the push‐pull policy results in lower inventory, the pull policy yields a better fill rate. This is in contrast to the notion that the pull policy generally results in superior inventory performance. Our findings suggest that firms should carefully consider the level of uncertainty, the inventory control policy and the performance measures of interest when determining the operating policy.     

Formulation of H2 and H8 optimal control problems – a variational approach

Abstract

In this paper, the full state and output feedback controllers with gains determined using either an H₂ or an H₈ – norm optimality criterion are presented. The problem is approached by transforming the frequency domain optimality criteria to the corresponding variational forms in the time domain. The variational approach allows formulation of the H₈ – optimal control problem without the limitations placed by the orthogonality assumptions. The state feedback gains and the observer gains are determined by solving two special Riccati equations. The tracking and the regulation problems are presented, and a computer algorithm is proposed for determining both the controller gains and the observer gains. The theoretical developments are applied to two examples for illustrative purposes.     

Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?

The purpose of this research is to develop a better understanding of smart systems and autonomous processes of the Industry 4.0 era. Does the implementation of Industry 4.0 processes and systems expose firms to higher levels of risk in the supply chain through capability loss or does Industry 4.0 spur capability enhancement and thereby increase supply chain resilience? Industry 4.0 is centred on the idea that certain tasks and decisions can be automated through smart systems and autonomous processes. However, is there a risk of losing critical capabilities and the ability to be flexible, agile and resilient to unexpected disruptions in the supply chain? In order to address these questions, this research presents results from semi-structured interviews across multiple industries to provide findings on firms’ uses of smart systems and capability development associated with these systems. Results from this exploratory study may be classified into two primary insights. First, although Industry 4.0 systems are new and, in many cases untested, firms are eager regarding the potential of smart systems to positively impact firm performance and to leverage Industry 4.0 processes for a competitive supply chain advantage. Second, companies did not claim any human capability loss associated with Industry 4.0. In fact, these smart systems may lead to increased supply chain resilience because of capability enhancement and new skill development.     

Robust H∞ non-fragile control with memory state feedback for a class of singular time-delay systems

The problem of delay-dependent robust H_∞ non-fragile control for a class of singular systems with state-delay and parameter uncertainties is investigated in this article. A delay-dependent sufficient condition for the problem of H_∞ control for a class of singular systems is proposed by constructing the generalized Lyapunov–Krasovskii function, combining with linear matrix inequality approach. A memory state feedback controller under controller gain perturbations is obtained, which guarantees that, for all admissible uncertainties, the resulting closed-loop system is regular, impulse free, and stable with an H_∞ disturbance attenuation level. Numerical examples show that the proposed methods are less conservative than existing ones.     

Composition control of co-electroplating Au–Sn deposits using experimental strategies

The optimal electroplating parameters for a pulse-current co-electroplating system of Au–Sn deposits in a non-cyanide electrolyte were investigated using experimental strategies, including fractional factorial design (FFD) and central composite design (CCD) coupled with the response surface methodology. pH value, ethylene diamine tetraacetic acid (EDTA) concentration, catechol concentration and metallic ions molar ratio (i.e., [Au]/[Sn]) were identified as the key factors affecting the composition of Au–Sn deposits in the FFD study. A reliable model between the response variable and the key factors of pH value, EDTA concentration and catechol concentration was established for the composition control of Au–Sn alloys in the CCD study. The standard deviation of the response variable (tin content) was set at the minimum level to determine the optimal co-electroplating parameters for the predicted composition value of Au–Sn deposits. Pair T test was conducted to validate both predicted and observed composition values under the optimal electroplating parameters, and the composition of Au–Sn deposits can be precisely controlled based on the established model. Scanning electron microscope observation and X-ray diffractometer analysis revealed that the morphology and crystalline of the Au–Sn deposits were composition-dependent.     

Decarbonising product supply chains: design and development of an integrated evidence-based decision support system – the supply chain environmental analysis tool (SCEnAT)

Based upon an increasing academic and business interest in greening the industrial supply chains, this paper establishes the need for a state-of-the-art decision support system (DSS) for carbon emissions accounting and management, mainly across the product supply chains by identifying methodological shortcomings in existing tools, and proposing a supply chain (SC) framework which provide businesses with a holistic understanding of their supply chains and ensuring partners within supply chain collaborative networks have a shared understanding of their emissions. It describes the design and development of a DSS now known as supply chain environmental analysis tool (SCEnAT) in detail, putting its unique and innovative features into a comparative perspective vis-à-vis existing tools and software of different types. The methodological framework used to design and develop SCEnAT integrates different individual techniques/methods of supply chain (SC) mapping, SC carbon accounting, SC interventions and SC interventions evaluation on a range of key performance indicators (KPIs). These individual methods have been used and applied innovatively to the challenge of designing SCEnAT within the desired framework. Finally, we demonstrate the application of SCEnAT, especially the advantage of using a robust carbon accounting methodology, to a SC case study. The SCEnAT framework pushes the theoretical boundary by addressing the problems of intra-organisational approach in decision making for lowering carbon along the supply chain; with an open innovation, cutting edge, hybridised framework that considers the supply chain as a whole in co-decision making for lowering carbon along the supply chain with the most robust methodology of hybrid life cycle analysis (LCA) that considers direct and indirect emissions and interventional performance evaluation for low carbon technology investment and business case building in order to adapt and mitigate climate change problems. This research has implications for future sustainability research in SC, decisions science, management theory, practice and policy.     

A technical note on ‘Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation’

This study analyses the mixed-integer linear program (MILP) proposed by Kannan et al. [Kannan, G., Noorul Hag, A., and Devika, M., 2009. Analysis of closed loop supply chain using genetic algorithm and particle swarm optimization. International Journal of Production Research, 47 (5), 1175–1200] in their paper entitled ‘Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation’. Since we find inconsistencies in the model, we propose modifications to rectify the flaws. The revised model is presented and tested using a hypothetical problem.     

Decentralized robust control of multi‐machine power systems with a prescribed degree of stability

Abstract

This paper presents a completely decentralized scheme for the robust control of multi‐machine power systems with a prescribed degree of stability. By applying the optimal control technique to the nominal dynamics of each decomposed machine, the calculated optimal gains are multiplied by appropriate factors to account for the intrinsic uncertainties and nonlinear interactions among the machines. This subsystem‐based method can give the overall system an arbitrarily chosen degree of stability, where no state information is transferred. An example of a three‐machine power system is given below.     

Effects of human resource management practices on logistics and supply chain competencies – evidence from China logistics service market

The Chinese logistics service market is a vibrant and highly contested arena. The industry, however, has been characterised as operationally inefficient in comparison with those of the developed economies. Shortage of logistics human resources and lack of logistics expertise have been identified as two of the key contributory factors. Based on responses from 76 Chinese logistics service providers to a survey conducted in 2010, this study explores whether, and how, four sets of human resource management (HRM) practices contribute to nurturing three logistics and supply chain (L&SC) competencies in the Chinese logistics service market. Results from a hierarchical multiple regression analysis show that not all HRM practices were equally effective in building L&SC competencies. While training and development, and recruitment and selection were significant in contributing to nurturing the three L&SC competencies, both performance management and reward management did not. These findings suggest that conventional HRM practices designed to reward individual performance may not be suited to nurturing team-based L&SC competencies in the Chinese context. The implications of these findings were discussed and directions for further studies offered.     

Dynamic and fluid–structure interaction simulations of bioprosthetic heart valves using parametric design with T-splines and Fung-type material models

This paper builds on a recently developed immersogeometric fluid–structure interaction (FSI) methodology for bioprosthetic heart valve (BHV) modeling and simulation. It enhances the proposed framework in the areas of geometry design and constitutive modeling. With these enhancements, BHV FSI simulations may be performed with greater levels of automation, robustness and physical realism. In addition, the paper presents a comparison between FSI analysis and standalone structural dynamics simulation driven by prescribed transvalvular pressure, the latter being a more common modeling choice for this class of problems. The FSI computation achieved better physiological realism in predicting the valve leaflet deformation than its standalone structural dynamics counterpart.     

A design model and a production–distribution and inventory planning model in multi-product supply chain networks

Supply chain network (SCN) design implicates decision-making at a strategic level. That includes selecting the right suppliers and determining the number and the location of plants, distribution centres and retailers. An apt design model of the supply chain is imperative for the proper function of the supply chain and consequently for making better operational decisions in an attempt of a continuous improvement. In this paper, we propose two models. The first model is a mixed-integer linear programming model which is concerned with the SCN design problem, whereas the second operational model is a mixed-integer non-linear programming model in respect to the production–distribution and inventory planning problem in a supply chain network. The number of customers and suppliers as well as their demand and capacities are assumed to be known in both models. Two steady-state genetic algorithms were implemented in MATLAB in order to solve both the design and the operational model. The results were compared with GAMS. Some examples were devised in order to demonstrate potential ways of use for the designer of the supply chain network, as well as for the supply chain manager.     

Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications

Performance measures and metrics are essential for effectively managing logistics operations, particularly in a competitive global economy. The global economy is featured with global operations, outsourcing and supply chain and e-commerce. The real challenge for managers of this new enterprise environment is to develop suitable performance measures and metrics to make right decisions that would contribute to an improved organizational competitiveness. Now the question is whether traditional performance measures can be used and out of them which ones should be given priority for measuring the performance in a new enterprise environment. Some of the traditional measures and metrics may not be suitable for the new environment wherein many activities are not easily identifiable. Measuring intangibles and nonfinancial performance measures pose the greater challenge in the so-called knowledge economy. Nevertheless, measuring them is so critical for the successful operations of companies in this environment. Considering the importance of nonfinancial measures and intangibles, an attempt has been made in this paper to determine the key performance measures and metrics in supply chain and logistics operations. This is based on a literature survey and some of the reported case experiences. Suggestions for future research directions are also indicated.     

A note on ‘Pricing and ordering decisions in a supply chain with imperfect quality items and inspection under buyback of defective items’

Taleizadeh, Noori-daryan, and Tavakkoli-Moghaddam consider pricing and ordering decisions in a three-level supply chain with defective items and inspection processes in their paper published in 2015. They examine three scenarios for defective items at the manufacturer: disposal, rework and selling at a lower price. Unfortunately, this interesting and innovative paper suffers from some shortcomings that are addressed in our note.     

Examining the influence of supply chain glitches on shareholder wealth: does the reason matter?

This paper investigates how different reasons for supply chain glitches influence shareholder wealth. Prior research indicated that supply chain glitches can decrease shareholder wealth by a staggering 10.28%. We argue that the reason for the supply chain glitch is an important moderator for understanding how supply chain glitches affect shareholder wealth. In this paper we re-assess the effect of supply chain glitches on shareholder wealth for a new time period (i.e. 2001–2012) whilst including the moderators from the original study (growth prospects, firm size, debt-equity ratio and timing) and adding the reason for the supply chain glitch as an important new moderator. Our results show that on average supply chain glitches decrease shareholder wealth by 1.94%. Further, our results indicate that supply chain glitches that arise due to regulatory, catastrophic and infrastructural reasons trigger more significant negative reactions in financial markets as compared with glitches that occur from the supply side. We discuss the implications of our findings both for theory building and for business practice, and end with limitations and suggestions for future research.     

Internet of Things (IoT)–blockchain-enabled pharmaceutical supply chain resilience in the post-pandemic era

During the COVID-19 pandemic, the current operating environment of pharmaceutical supply chain (PSC) has rapidly changed and faced increasing risks of disruption. The Internet of Things (IoT) and blockchain not only help enhance the efficiency of PSC operations in the information technology domain but also address complex related issues and improve the visibility, flexibility, and transparency of these operations. Although IoT and blockchain have been widely examined in the areas of supply chain and logistics management, further work on PSC is expected by the public to enhance its resilience. To respond to this call, this paper combines a literature review with semi-structured interviews to investigate the characteristics of PSC, the key aspects affecting PSC, and the challenges faced by PSC in the post-pandemic era. An IoT–blockchain-integrated hospital-side oriented PSC management model is also developed. This paper highlights how IoT and blockchain technology can enhance supply chain resilience and provides a reference on how PSC members can cope with the associated risks.