Guo Chen, Mohamed Wahab Mohamed Ismail and Liping Fang
The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively…
Abstract
Purpose
The single-supplier multi-retailer cold chain is a widely adopted type of supply chain in the real-world food industry. This paper aims to consider the problem of effectively designing and managing a single-supplier multi-retailer cold chain for fresh produce with deterministic demand to minimize the total cost, which includes cooling, loss of value and carbon emission costs.
Design/methodology/approach
The global stability index (GSI) method and the non-Arrhenius model are integrated to describe the behavior of food quality degradation. The power-of-two (PoT) policy is adopted in determining the coordinated replenishment policies for the suppliers and retailers, and an appropriate wholesale price structure that can achieve the coordination of the chain is presented.
Findings
The properties of the cold chain are uncovered, and an appropriate wholesale price scheme that achieves chain coordination with the optimal PoT decision is provided. In the numerical examples, different scenarios are investigated, and it is found that the cold chain parameters influence the optimal decisions in certain ways.
Originality/value
The PoT policy – an efficient policy to determine the replenishment strategy – has not been adopted in finding the solution of a single-supplier multi-retailer cold chain in the literature. Also, no study has compared the uncoordinated and coordinated cold chain. Moreover, in the existing literature, the wholesale price is usually a constant rather than having a coordinated scheme. This research aims to fill these research gaps.
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Raaid Batarfi, Aziz Guergachi and M.I.M. Wahab
Studies have suggested that attributes are dynamic and a life cycle of product and service attributes exists. When an innovative feature is introduced, the feature might attract…
Abstract
Purpose
Studies have suggested that attributes are dynamic and a life cycle of product and service attributes exists. When an innovative feature is introduced, the feature might attract and delight customers. However, with the passage of time the state of the attractiveness of this feature may change, for better or for worse. The purpose of this paper is to provide a detailed model that shows the factors and related sub-factors that affect the life cycle of a feature and thereby explain the changes that may happen to a feature over time.
Design/methodology/approach
This model provide detailed explanations of the direct and indirect factors that affect the states of a feature, the ones that affect the rate of adoption, and the ones that trigger the changes between states. The model uses a current-market product’s feature to discuss the effects of these factors on the life cycle of this feature in detail.
Findings
This paper extends the theory of attractive quality attributes by identified seven states of the feature in its life cycle. These states are as follows: unknown/unimportant state, honey pot state, racing state, required state, standard state, core state, and dead state. This paper also identified eight major factors that affect the transition of the feature from one state to another. These factors include demographic, socioeconomic, behavioural, psychological, geographical, environmental, organisational, and technological factors.
Originality/value
The findings of this paper provide additional evidence that product and service attributes are dynamic. This paper also increases the validity of the attractive quality attributes theory and the factors that affect the state of the feature in its life cycle. The understanding of the state of the feature in its life cycle, and the factors that influence this change, helps not only in the introduction of completely new features but also in knowing when to remove obsolescent ones.
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Bangdong Zhi, Xiaohong Liu, Junlin Chen and Fu Jia
The purpose of this paper is to employ an emerging phenomenon in China concerning collaborative carbon emission reduction (CCER) to investigate: first, the coordination of…
Abstract
Purpose
The purpose of this paper is to employ an emerging phenomenon in China concerning collaborative carbon emission reduction (CCER) to investigate: first, the coordination of suppliers and manufacturers within supply chains to reduce carbon emissions, and second, the role of governmental policy in facilitating this process.
Design/methodology/approach
This paper draws upon evolutionary game theory to develop an evolutionary game model for CCER for suppliers and manufacturers within supply chains. This includes a detailed analysis of the evolutionary direction and process in different areas, both with, and in the absence of, governmental subsidies.
Findings
The results demonstrate that CCER is path dependent and that its evolutionary process is influenced by the following four factors: the initial status within supply chains; the cost; the additional benefit; and the investment risk related to CCER. The research also reveals that the reward provided by manufacturers is rational over the long term, due to the excessive cost of incentives potentially preventing the implementation of CCER.
Originality/value
This study represents the first attempt to investigate CCER within supply chains through the application of an evolutionary game-theoretic model. The investigation of multiple factors in the model will deepen understanding of the collaborative role required for the carbon emission reduction.
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Kelly Weeks, Alfred Guiffrida and Mahdi Safa
The purpose of this paper is to extend the developing body of knowledge on supply chain performance by addressing the impact of resource commitment (RC), product route efficiency…
Abstract
Purpose
The purpose of this paper is to extend the developing body of knowledge on supply chain performance by addressing the impact of resource commitment (RC), product route efficiency (PRE), and manufacturing flexibility (MF) on a firm’s financial performance (FP) has a direct impact on supply chain operations.
Design/methodology/approach
Survey questionnaires were developed in conjunction with literature guidance. Exploratory and confirmatory factor analysis was used in conjunction with structural equation modeling to give a robust analysis of the problem setting.
Findings
Discoveries herein indicate that committing resources in itself is insufficient to adequately increase FP over the long term. However, the mediating variables of MF and PRE were found to significantly improve a firm’s bottom line.
Originality/value
Prior research has been somewhat lacking and inconsistent with regards to the nature of causal and mediating relationships found between RC, PRE, MF, and a firm’s financial performance. Given the increasing global nature of competition, understanding the relationships between potential factors that could positively impact a firm’s FP has a large potential direct impact and benefit on supply chain operations.
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The yield of defective items and emissions of greenhouse gases in supply chains are areas of concern. Organizations try to reduce the yield defective items and emissions. In this…
Abstract
Purpose
The yield of defective items and emissions of greenhouse gases in supply chains are areas of concern. Organizations try to reduce the yield defective items and emissions. In this paper, a constrained optimization model is developed with consideration of the yield of defective items and strict carbon cap policy simultaneously and then optimized. Further, sensitivity analyses have been carried out to draw different managerial insights. Precisely, we have tried to address the following research questions: (1) how to optimize the cost for a two-echelon supply chain considering yield of defective items and strict carbon cap policy, (2) how the total expected cost and total expected emissions act with changing parameters.
Design/methodology/approach
The mathematical modeling approach has been adopted to develop a model and further optimized it with optimization software. Costs and emissions from different areas of a supply chain have been derived and then the total cost and total emissions have been formulated mathematically. One constrained mixed-integer nonlinear programming (MINLP) problem has been formulated and solved considering emissions-related, velocity and production related-constraints. Further, different sensitivity analyses have been derived to draw some managerial insights.
Findings
In this paper, many decision variables have been calculated with a set of basic values of other parameters. It has been found that both cost and emissions can be controlled by controlling different parameters. It has been also found that some parameters have very little or no influence either on cost or emissions. In most cases, originations may exhaust the given limit of carbon cap to optimize their costs.
Originality/value
In spite of my sincere efforts, no paper has been found that has considered the yield of defective items and strict carbon cap policy simultaneously. In this paper, it is assumed that both demand and defect rates are random in nature. The model, presented in this paper may give insights to develop different supply chain models with consideration of both defective items and strict carbon cap policy. Sensitivity analyses, drawn in this paper may give deep insights to managers and carbon regulatory bodies.
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Piyal Sarkar, Mohamed Wahab Mohamed Ismail and Timur Tkachev
In light of the COVID-19 pandemic, all business sectors have critical needs. They face multiple challenges to restructuring their operations to build a resilient, cost-effective…
Abstract
Purpose
In light of the COVID-19 pandemic, all business sectors have critical needs. They face multiple challenges to restructuring their operations to build a resilient, cost-effective and sustainable supply chain. Therefore, this paper aims to investigate the practice and the research gaps related to supply chains.
Design/methodology/approach
This research paper is influenced by a literature review of the past decade. This review paper incorporates industry challenges of the COVID-19 pandemic, including future steps toward developing resilient supply chains in the new normal economy. The research provides a detailed framework for designing cost-effective survivable supply chains that withstand disruptions for the long term.
Findings
The proposed research focuses on the effects of the COVID-19 pandemic on supply chains and attempts to bridge pre and post COVID-19 research and practice gaps. Post-COVID-19 resilient supply chains need to be transformed into survivable supply chains. The survivability of the supply chain can be achieved by combining both supply chain resilience and supply chain viability measures. To the best of the authors’ belief, this is the first study that grounds a theory to provide interconnection of five critical supply chain concepts to manage supply chain risk. This study is uniquely positioned to develop a theoretical framework to design a cost-effective, resilient and sustainable supply chain by establishing the interconnection among these concepts in supply chains. This framework helps practitioners to implement the key strategies at the operational, tactical and strategic levels that enhance maturity in supply chains.
Research limitations/implications
The research findings are based on secondary reports such as industry reports, cases, research papers and expert opinions. The authors tried to consult with many companies. However, they were reluctant to share the recovery plan information from COVID. Also, as COVID still exists in many places in Canada, the authors could not gather every intended information from the companies. However, the authors have successfully shared the outcomes of this research with a reputed retail company in Canada. They recognized the importance of survivability in supply chains. Going forward, business organizations need to design cost-effective, sustainable and survivable supply chains.
Originality/value
The study attempts to unify current research dealing with supply chain resilience. The study concludes with the limitations of the current research. It highlights the prospects of future research and bridges the supply chain practice gaps from the challenges faced by industries due to COVID-19. The study contributes to the literature by identifying gaps to bridge the supply chain practice and reiterating new research directions to develop a cost-effective, survivable and sustainable supply chain.
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Christoph H Glock and Taebok Kim
This paper studies a supply chain consisting of multiple suppliers and a single buyer. It considers the case where a set of heterogeneous trucks is used for transporting products…
Abstract
Purpose
This paper studies a supply chain consisting of multiple suppliers and a single buyer. It considers the case where a set of heterogeneous trucks is used for transporting products, and develops a mathematical model that coordinates the supply chain. The purpose of this paper is to minimise the costs of producing and delivering a product as well as carbon emissions resulting from transportation. In addition, the authors analyse how imposing a tax on carbon emissions impacts the delivery of products from the suppliers to the buyer.
Design/methodology/approach
It is assumed that heterogeneous vehicles are used for transporting products, which have different performance and cost attributes. A mathematical model that considers both operating costs and carbon emissions from transportation is developed. The impact of vehicle attributes on lot sizing and routing decisions is studied with the help of numerical examples and a sensitivity analysis.
Findings
The analysis shows that considering carbon emissions in coordinating a supply chain leads to changes in the routing of vehicles. It is further shown that if carbon emissions lead to costs, routes are changed in such a way that vehicles travel long distances empty or with a low vehicle load to reduce fuel consumption and therewith emissions.
Research limitations/implications
Several areas for future work are highlighted. The study of alternative supply chain structures, for example structures which include logistics service providers, or the investigation of different functional relationships between vehicle load and emission generation offer possibilities for extending the model.
Originality/value
The paper is one of the first to study the use of heterogeneous vehicles in an inventory model of a supply chain, and one of the few supply chain inventory models that consider ecological aspects.
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Ruchi Mishra, Ashok K. Pundir and L. Ganapathy
The purpose of this paper is to propose a novel integrated approach using analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution…
Abstract
Purpose
The purpose of this paper is to propose a novel integrated approach using analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods for evaluation and prioritization of appropriate manufacturing flexibility type required in the face of multiple environmental uncertainties.
Design/methodology/approach
Using a case study of an Indian fashion apparel firm, the study demonstrates the application of the proposed integrated framework for evaluation and prioritization of manufacturing flexibility. The study uses AHP method to determine importance weight of environmental uncertainty criteria and subcriteria and then employs TOPSIS method to determine the final ranking of manufacturing flexibility types required to cope up with these uncertainties.
Findings
The findings of the case suggest that the proposed integrated approach is feasible and practically implementable for manufacturing flexibility assessment.
Research limitations/implications
AHP has been extensively studied and used, but the major limitation of this proposed approach is the involvement of large number of pairwise comparisons leading to difficulty in maintaining consistency in pairwise comparisons.
Practical implications
The proposed approach can work as a benchmarking tool to practitioners in evaluating and prioritizing manufacturing flexibility alternatives and to suggest strategic allocation of resource by prioritizing different manufacturing flexibilities types.
Originality/value
Unlike conventional approaches, the study provides meaningful knowledge to decision makers by demonstrating a simple, flexible, and efficient method to evaluate and rank the appropriate manufacturing flexibility types.
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Shikha Yadav, Aman Borkar and Aditi Khanna
With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for…
Abstract
Purpose
With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).
Design/methodology/approach
The current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.
Findings
The research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.
Originality/value
The proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.
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Yan Li, Ming K. Lim, Weiqing Xiong, Xingjun Huang, Yuhe Shi and Songyi Wang
Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental…
Abstract
Purpose
Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.
Design/methodology/approach
This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.
Findings
The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.
Research limitations/implications
The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.
Originality/value
In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.