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1 – 10 of 138Xiaogang Cao, Cuiwei Zhang, Jie Liu, Hui Wen and Bowei Cao
The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.
Abstract
Purpose
The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.
Design/methodology/approach
This paper analyzes the impact of the bundling strategy of the retailer selling new products and remanufactured products on the closed-loop supply chain under the condition that the original manufacturer produces new products and the remanufacturer produces remanufacturing products.
Findings
The results show that alternative products can be bundled, and in many cases, the bundling of remanufactured products and new products is better than selling alone.
Originality/value
If the retailer chooses bundling, for the remanufacturer, when certain conditions are met, the benefits of bundling are greater than the separate sales at that time; for the original manufacturer, when the recycling price sensitivity coefficient is high, the bundling is better than separate sales.
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Pham Duc Tai, Krit Jinawat and Jirachai Buddhakulsomsiri
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a…
Abstract
Purpose
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.
Design/methodology/approach
The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.
Findings
For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.
Originality/value
The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.
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Weijie Zhou, Jianhua Zhu and Ce Zhang
This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon…
Abstract
Purpose
This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.
Design/methodology/approach
This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.
Findings
Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.
Originality/value
The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.
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Xiaoxi Zhu, Juan Liu, Meifei Gu and Changhui Yang
To examine how shareholding affects optimal profits, R&D innovation, NEV market scale and social welfare in two supply chain models with partial and cross ownership patterns.
Abstract
Purpose
To examine how shareholding affects optimal profits, R&D innovation, NEV market scale and social welfare in two supply chain models with partial and cross ownership patterns.
Design/methodology/approach
The gradual retreat of government subsidies has directly weakened the financial support available to the stakeholders of new energy vehicles (NEVs). In this context, upstream and downstream enterprises of NEV are constantly seeking new business models of cooperation to achieve possible win-wins. NEV supply chain shareholding is an emerging new practice for such explorations. However, its performance in the NEV supply chain is seldom investigated. In this paper, we employ a Stackelberg game model to investigate how partial and cross-ownership affect the optimal decisions in a NEV supply chain.
Findings
Results showed that: (1) Compared with the unilateral shareholding model, the battery supplier will benefit from cross-ownership in the supply chain, while the NEV manufacturer will not necessarily benefit from it. At the same time, cross-ownership will bring the greatest incentive for battery R&D (2) Supply chain downstream competition will not necessarily lead to the improvement of the total consumption of NEVs or the level of battery design. Pareto improvement can be brought only when one of the manufacturers holds less than a certain equity threshold. In addition, downstream competition will also not necessarily bring more benefits to the battery supplier.
Originality/value
At present, NEV supply chain management has attracted widespread attention from scholars from all walks of life. Previous studies have been carried out that covers topics such as pricing strategies and optimal profits and the role of NEV in the sustainable development of the automotive industry supply chain, or disparate impacts of government subsidies and carbon emission regulation on supply chain members. However, as far as the authors know, compared with the new emerging NEV corporate practice, the shareholding phenomenon between upstream and downstream in the supply chain of NEV has not been studied in the existing studies.
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Ryan Atkins, Kim Deranek and Robert Sroufe
Research and interest in food loss and waste (FLW) have increased, but barriers stand in the way of firms engaging in food recovery efforts. The purpose of this study is to gain a…
Abstract
Purpose
Research and interest in food loss and waste (FLW) have increased, but barriers stand in the way of firms engaging in food recovery efforts. The purpose of this study is to gain a better understanding of how firms overcome these barriers.
Design/methodology/approach
This study followed a qualitative, field-study-based research design in which 23 decision-makers at food-based organizations were interviewed. Quotes were extracted and categorized to develop a conceptual model of the food recovery process.
Findings
The conceptual model that evolved helps to explain decision-making related to FLW across the following dimensions: barriers to food recovery, incentives to overcome the barriers, internal processes for engaging in food recovery and external relationships influencing internal incentives and processes. In addition, the barriers and incentives were divided into operational and managerial issues.
Originality/value
Building on the barriers to food recovery in prior research, we explored the processes that help firms overcome these barriers. The model developed in this study is an important step toward addressing these processes and relationships. It can serve as a foundation for a variety of future studies of food recovery.
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Mohammad Mahdi Vali-Siar and Emad Roghanian
This study addresses resilient mixed supply chain network design (SCND) and aims to minimize the expected total cost of the supply chain (SC) considering disruptions. The capacity…
Abstract
Purpose
This study addresses resilient mixed supply chain network design (SCND) and aims to minimize the expected total cost of the supply chain (SC) considering disruptions. The capacity of facilities is considered uncertain. In order to get closer to real-world situations, competition between SCs is considered.
Design/methodology/approach
A two-stage stochastic programming model is developed for designing the SC network. The location of facilities and selection of suppliers are considered first-stage decisions, and the determination of materials and products flows are second-stage decisions. Some resilience strategies are applied to mitigate the negative impacts of disruptions.
Findings
The results indicate that considering resilience and applying the related strategies are vitally important, and resilience strategies can significantly improve the SC objective and maintain market share. Also, it is confirmed that unrealistic decisions will be made without considering the competition.
Originality/value
This study contributes to the literature by proposing a novel mathematical model for the resilient mixed SCND problem. The other contribution is considering the chain-to-chain competition in collecting returned products and selling recycled products to other SCs in a mixed SC under disruptions. Also, a novel hybrid metaheuristic is developed to cope with the complexity of the model.
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Seyed Mojtaba Taghavi, Vahidreza Ghezavati, Hadi Mohammadi Bidhandi and Seyed Mohammad Javad Mirzapour Al-e-Hashem
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of…
Abstract
Purpose
This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.
Design/methodology/approach
The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.
Findings
In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.
Originality/value
This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.
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Sheak Salman, Shah Murtoza Morshed, Md. Rezaul Karim, Rafat Rahman, Sadia Hasanat and Afia Ahsan
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular…
Abstract
Purpose
The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.
Findings
The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.
Research limitations/implications
The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.
Originality/value
This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.
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Ramin Rostamkhani and Thurasamy Ramayah
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of…
Abstract
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.
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Yanping Liu, Bo Yan and Xiaoxu Chen
This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of…
Abstract
Purpose
This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.
Design/methodology/approach
The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.
Findings
The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.
Practical implications
The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.
Originality/value
This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.
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