supply chain management
Mehdi Keshavarz-Ghorabaee
Abstract
Supplier selection and order allocation are two of the most important issues in supply chain management, which can have a significant impact on the overall performance and efficiency of an organization. This research presents a new approach based on group decision-making to address this problem. Firstly, ...
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Supplier selection and order allocation are two of the most important issues in supply chain management, which can have a significant impact on the overall performance and efficiency of an organization. This research presents a new approach based on group decision-making to address this problem. Firstly, the evaluation outputs of decision-makers are converted into interval-valued Pythagorean fuzzy sets using a quantitative procedure. Then, based on these fuzzy elements, the CRITIC method is employed to determine the weights of the criteria. Using the Einstein weighted geometric aggregation operator and the extracted weights, the final performance of each supplier is calculated as an interval-valued Pythagorean fuzzy set. In the next step, a multi-objective model is formulated considering the order allocation parameters and the obtained performances from the suppliers. Finally, the fuzzy programming technique is used to solve the multi-objective model. To analyze the efficiency of the proposed approach, a practical example based on environmental criteria is considered, and a sensitivity analysis is performed on the criteria weights to evaluate the reasonableness and efficiency of the results. The obtained results indicate the performance of the proposed approach in solving the supplier selection and order allocation problem.
supply chain management
Parisa Hosseini; Mehdi Seifbarghy
Abstract
One of the most critical decisions in the supply chain is pricing, playing a vital role in the profitability of the entire supply chain. In this research, a two-tier green supply chain is considered, comprising a producer and a retailer, where two types of products, standard and green, are produced. ...
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One of the most critical decisions in the supply chain is pricing, playing a vital role in the profitability of the entire supply chain. In this research, a two-tier green supply chain is considered, comprising a producer and a retailer, where two types of products, standard and green, are produced. The demand for products is determined as a certain linear function of product prices, delivery time in the online channel, the level of green quality, advertising intensity, and information tracing level. Green products are sold through the online channel, while standard products are distributed through traditional retail channels. The government provides subsidies for the production of green products and the implementation of blockchain technology. The decision-making problem is approached through two centralized and decentralized models. In the decentralized model, a Stackelberg game is employed, with the producer leading the decision-making process. In the centralized model, all supply chain members make decisions in a unified manner. The results indicate that the centralized model yields the highest profitability for the supply chain. Additionally, in the centralized model, all products are observed to have the lowest prices.
supply chain management
Abolfazl Sadeghian; Seyed Mohammad Ali Khatami Firouzabadi; Laya Olfat; maghsoud Amiri
Abstract
Nowadays attending to closed-loop supply chain matter for survival in competitive circumstances not only has been become a controversial topic but also has been considered as a critical topic too. Close loop supply chain has combined to direct and reverse flow (method/ manner). This paper’s goal ...
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Nowadays attending to closed-loop supply chain matter for survival in competitive circumstances not only has been become a controversial topic but also has been considered as a critical topic too. Close loop supply chain has combined to direct and reverse flow (method/ manner). This paper’s goal is presenting a model for inventory control in closed loop supply chain by multiple objective approach. This research intends to reach it's main goal including reduce expenses such as production, maintenance, transportation in direct flow also decrease the waste material and defective in reverse flow and in conclusion increase the company’s profit by desingning and optimizing multiple objective model. Hence a double purpose model in closed-loop supply chain consists three classes direct flow in which conclude suppliers, manufactures and customers. Furthermore this consists four classes in reverse flow that concludes: collection centers, inspection, repair centers, recycling centers and disposal centers. According to the article’s model, which is multipurpose, linear and integer, At the beginning the model convert to single objective by Weighting and Constraint method and then is solved by using Branch and bound algorithm and Lingo software. Finally, the model extended in Iran Khodro Company as a study case and its function validated. Results and output of model solving demonstrate its capability to be useful for planning and inventory control in closed-loop supply chain.
supply chain management
Mohammad Ali Razaghi Heris; Habibollah Javanmard; Iraj Nouri
Abstract
Considering the importance of the home appliances industry in generating employment and promoting economic prosperity, this research identifies the key factors that improve the performance of the financing chain within this sector. A mixed-method approach (qualitative and quantitative) was utilized to ...
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Considering the importance of the home appliances industry in generating employment and promoting economic prosperity, this research identifies the key factors that improve the performance of the financing chain within this sector. A mixed-method approach (qualitative and quantitative) was utilized to achieve this goal. The qualitative phase drew from library resources related to the financing chain, while the quantitative phase included 183 senior managers and experts involved in the financing chain of the home appliances industry in Alborz province. Sampling was conducted using simple random sampling, and data were collected through a field questionnaire. To validate and assess the fit of the research model, confirmatory factor analysis and structural equation modeling were employed using SPSS 19 and Smart PLS 3 software. The results indicated that 13 overarching themes were identified, including four themes related to background requirements (structure), five themes related to strategies and processes within the financing chain (content), and four themes related to the outcomes of the financing chain. All factor loadings were significant at the 95% confidence level, confirming the model’s fit and validating the research hypotheses. The findings suggest that contextual components are crucial in shaping the actions and strategies within the financing chain, while the content components play an essential role in achieving the goals of this chain in the home appliance industry.
supply chain management
Mehdi Seifbarghy; Morvarid Yousefi
Abstract
The evaluation and selection of suppliers is a crucial issue in supply chain management. This problem has grown increasingly uncertain due to the influence of imprecise parameters, and various tools have been proposed for weighting criteria and evaluating supplier scores for each criterion. Neutrosophic ...
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The evaluation and selection of suppliers is a crucial issue in supply chain management. This problem has grown increasingly uncertain due to the influence of imprecise parameters, and various tools have been proposed for weighting criteria and evaluating supplier scores for each criterion. Neutrosophic numbers, a modern tool for handling uncertainty, ambiguity, and inconsistency, are introduced to tackle such challenges. As the most comprehensive form of non-classical logic after fuzzy and intuitionistic fuzzy logic, Neutrosophic logic assigns degrees of membership, non-membership, and hesitation independently between zero and one. In this research, the quality function deployment (QFD) technique is developed in a Neutrosophic environment to identify and weigh supplier evaluation criteria. Additionally, the Neutrosophic EDAS approach is proposed for selecting top suppliers. A numerical study of the pharmaceutical industry demonstrates that geographical location and supplier experience are the two most critical criteria, and the second supplier is chosen as the best.
supply chain management
poorya naseri; morteza abbasi; karim atashgar
Abstract
This article investigates the selection of a cooperation model with suppliers and the continuous monitoring of the collaboration strategy over time by tracking the supplier's performance. A multiple fuzzy profile monitoring model is proposed and implemented in two stages to oversee the supplier’s ...
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This article investigates the selection of a cooperation model with suppliers and the continuous monitoring of the collaboration strategy over time by tracking the supplier's performance. A multiple fuzzy profile monitoring model is proposed and implemented in two stages to oversee the supplier’s unforeseen costs. In the first stage, criteria and indicators for evaluating the delivery process and quality are identified based on literature reviews and expert opinions from industry leaders. In the second stage, a two-phase monitoring approach is adopted. First, using the T² method, the model’s parameters based on successive differences are calculated and separately monitored for the multiple fuzzy profiles of delivery and quality processes. In the second phase, the likelihood ratio method is applied to track the profiles over time, enabling the control chart to signal any warning in the shortest possible time. In the final stage, the results from the fuzzy profiles of delivery and quality processes, combined with artificial intelligence and the fuzzy inference system tool, are used to monitor unforeseen costs, make decisions regarding the supplier, and assess the adopted strategy. This model has been implemented in Iran's automotive industry, specifically within Iran Khodro Company and its gearbox parts supplier, Niromoharkeh Company.
supply chain management
salim karimi takalo; Hamid Sharifi; ehsan bakhshi khorde blagh
Abstract
The purpose of this research was to identify and analyze the drivers of the smart sustainable circular supply chain. Twelve samples were selected by the snowball method from among industry experts in the edible oil sector. Drivers were finalized with expert opinions and analyzed using the DEMATEL and ...
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The purpose of this research was to identify and analyze the drivers of the smart sustainable circular supply chain. Twelve samples were selected by the snowball method from among industry experts in the edible oil sector. Drivers were finalized with expert opinions and analyzed using the DEMATEL and AISM methods. The results showed that organizational competence and human resource competence are the most effective drivers, while economic sustainability and environmental sustainability drivers have the highest levels of effectiveness compared to other drivers. According to the results of the research, officials in the edible oil industry should pay special attention to organizational competence to advance towards a sustainable and smart circular supply chain, as this driver has the greatest impact compared to others.
supply chain management
Akbar Rahimi; mohamad hossein karimi govareshki; Amirreza zareei
Abstract
The competitive landscape among companies and their supply chains necessitates a heightened focus on collaborating with the best suppliers. The appropriate selection of suppliers presents an opportunity for organizations to gain a sustainable competitive advantage while enhancing profitability. The Etka ...
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The competitive landscape among companies and their supply chains necessitates a heightened focus on collaborating with the best suppliers. The appropriate selection of suppliers presents an opportunity for organizations to gain a sustainable competitive advantage while enhancing profitability. The Etka organization, responsible for meeting the consumption and general needs of the armed forces, is no exception. Consequently, it requires establishing partnerships with suppliers across industries. To address this need, this research aims to provide a framework for selecting suppliers with lean, agile, and resilient approaches within the supply chain of the Etka organization. To achieve this objective, an extensive review of the relevant literature on lean, agile, and resilient supplier selection was undertaken. Through this process, key selection criteria were identified, and the fuzzy screening method was employed to localize and refine these criteria. Furthermore, the combined rough best-worst method was utilized to assign weights to each criterion, reducing uncertainties associated with expert opinions. "Cooperation and coordination" emerged as the most critical criterion from the resilient supply perspective, "trust development" from the agile supply approach, and "product quality" from the lean supply approach. The application of the rough VIKOR method then facilitated the ranking of selected suppliers, resulting in the Qaemshahr canning company being identified as the most desirable supplier in the related industry. This study presents a comprehensive framework for selecting lean, agile, and resilient suppliers within the supply chain of the Etka organization, enabling fruitful partnerships that contribute to competitive advantage and overall profitability.IntroductionThe foundational importance of ensuring the timely provision of high-quality sustenance to the armed forces at reasonable costs stands as a cornerstone in bolstering a nation's defense preparedness. The Etka organization, entrenched in the responsibility of orchestrating the seamless delivery of top-tier nourishment to military personnel from farm to table, grapples with the imperative of devising astute supply chain management strategies. As global challenges, such as the ramifications of the COVID-19 pandemic, underscore the criticality of resilient supply chains, Etka's commitment to fortifying its procurement infrastructure gains newfound significance. While Etka cultivates a portion of its food internally, strategic partnerships play a pivotal role in ensuring the efficient fulfillment of diverse demands. In tandem, industry-wide strategies like adopting lean, agile, and resilient supply chain methodologies could guide organizations toward operational efficiency, profitability, and customer-centricity. The nimble nature of the agile approach, coupled with the waste-reducing prowess of the lean strategy, and the resilience to rebound after disruptions embody the ethos underpinning modern supply chain excellence. Effective supplier selection emerges as a linchpin in the quest for operational optimization and enhanced competitiveness, particularly manifesting as an imperative facet in Etka's role as a custodian of the armed forces' nutritional sustenance. This necessitates meticulous scrutiny, evaluation, and collaboration with suppliers aligned with the organization's criteria to ensure streamlined procurement processes. This scholarly endeavor embarks on architecting a comprehensive roadmap for selecting suppliers harmonized with Etka's requisites through the delineation of precise procurement criteria and strategic imperatives.Literature ReviewIn the area of supplier selection, various studies have been conducted. Among these, there are studies that have selected suppliers based on one, two, or all of the essential, agile, and resilient approaches. These three approaches are of significant importance in the matter of selecting suppliers, to the extent that almost all recent research in the field of supplier selection has examined at least one of these approaches. Therefore, in this study, after reviewing and studying the literature on the subject, we proceed to identify the criteria for selecting essential, agile, and resilient suppliers. The identified criteria for selecting essential suppliers include: cost, quality, lead time, collaborative relationships with suppliers, level of service and customer satisfaction, flexibility, just in time, information sharing, implementation of quality management systems, waste management, automatic inventory replenishment, and inventory management. The identified criteria for selecting agile suppliers include: production flexibility, delivery flexibility and speed, resource flexibility, market sensitivity, information sharing, reliability, responsiveness, capacity to create new production lines, process integration through IT, quality improvement, minimizing uncertainty, innovation capability, cost flexibility and reduction, trust development, reducing resistance to change, and improving after-sales services. The identified criteria for selecting resilient suppliers include: excess inventory, reliability, adaptability, multiple sourcing, collaboration and coordination, identifying vulnerable points, awareness of risks and their management, redundancy in production equipment, having a list of alternative materials, technological capability, demand-driven management, and warehouse location flexibility.MethodologyThe current study is characterized by an applied research type with a descriptive methodological approach. The nature of this research as a questionnaire-based inquiry categorizes it as a descriptive-survey study. The statistical population targeted in this investigation comprises experts and managers from the business department of the Etka organization. Data collection methods employed in this study encompass both library research for theoretical foundations and field research for practical investigations. The foundational knowledge and background were cultivated through a meticulous examination of authoritative texts and articles, aligning with the library research method. Conversely, the actual data collection process involved direct engagement with the subjects through the distribution of a questionnaire, reflecting the field research method. Upon establishing the supplier selection criteria derived from existing literature, a questionnaire was formulated to screen these criteria, which was subsequently shared with the experts at Etka organization. Through expert consultation, certain identified criteria deemed less critical for the organization were eliminated following a fuzzy screening process. Subsequently, the best and worst criteria were identified through a second questionnaire distributed among the experts. Using the rough Best-Worst Method (BWM), expert-valued criteria were quantified and prioritized within the lean, agile, and resilient frameworks. Subsequently, a final questionnaire was administered to experts, aiming to evaluate suppliers from the Etka Organization based on the weighted criteria determined in the previous stages. These supplier evaluations were quantified using Raff's numbers, supported by Raff's theory relationships. Finally, a comparative analysis was conducted to rank the selected suppliers utilizing the VIKOR method relationships. This methodological approach employed a systematic process of refining criteria, expert consultation, and quantitative analysis to effectively evaluate and rank suppliers within the organizational context of the Etka organization.ResultsThe findings of this research indicate that when selecting a supplier for the Etka organization, the most critical approaches in order of importance are resilience, agility, and lastly, the lean approach. Consequently, a framework was developed for the selection of suppliers optimized for Lean, Agile, and Resilient (LAR) characteristics within this organization. The key criteria for supplier selection across lean, agile, and resilient approaches were identified as product quality criteria, trust development, and cooperation and coordination, respectively. Moreover, through a comparative analysis of the weight and significance of these criteria, it is evident that among the top five essential criteria recognized, three fall within the realm of resilience. This reaffirms the significance of prioritizing resilient suppliers in the selection process. Lastly, the research findings highlight that the Qaemshahr cannery demonstrates exemplary performance concerning Lean, Agile, and Resilient approaches.Conclusion and DiscussionThe framework devised for selecting suppliers using Lean, Agile, and Resilient (LAR) approaches offers several practical applications for the Etka organization. A comprehensive assessment of the prevailing supply conditions within the organization revealed a minimal adoption of the key criteria outlined in this research in the practical supplier selection processes at Etka. With attention to these findings, the Etka organization stands to enhance its supply chain operations within the food industry significantly by revisiting and fine-tuning its supply policies in alignment with the framework established in this study. The suggested course of action entails the organization reconsidering its supplier selection criteria to prioritize suppliers who align with the identified criteria, fostering improved operational performance. By recalibrating its supplier selection practices in accordance with the research framework, the Etka organization can strive towards optimizing its supply chain operations, enhancing efficiency, and fostering resilience in the face of challenges. Therefore, leveraging the insights gleaned from this research framework presents an opportunity for the Etka organization to refine its supplier selection strategies, bolster operational efficacy, and cultivate relationships with suppliers that align closely with the organization's objectives and requirements.
supply chain management
Ali Mirzaei; Esmaeil Mazroui Nasrabadi
Abstract
The supply chain of the food industry is crucial for countries, yet it is vulnerable to disruptions caused by natural disasters like floods, frost, and heatwaves, as well as operational shutdowns. These disruptions can trigger a ripple effect throughout the food supply chain, posing significant challenges ...
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The supply chain of the food industry is crucial for countries, yet it is vulnerable to disruptions caused by natural disasters like floods, frost, and heatwaves, as well as operational shutdowns. These disruptions can trigger a ripple effect throughout the food supply chain, posing significant challenges for the country. Therefore, it is imperative to identify and analyze strategies to mitigate the ripple effect. This research has been conducted in two stages: qualitative and quantitative. The qualitative stage aimed to identify coping strategies, employing thematic analysis. The quantitative stage involved scenario modeling and analysis using fuzzy cognitive maps. The findings revealed 84 primary codes grouped into 21 sub-categories and 4 main categories: "Strategic Management," "Operations Management," "Compilation and Correct Implementation of Laws," and "Supply Chain Management." Analysis of backward scenarios underscored the importance of "supplier relationship management," "cooperation and coordination in the supply chain," and "contingency plans." Conversely, analysis of forward scenarios highlighted the significance of "monitoring environmental changes" and "strategic planning." Focusing on short-term plans, enhancing managers' decision-making and problem-solving skills, refining supplier selection criteria, optimizing supply network design with backup locations, and maintaining safety stock for critical goods are recommended actions for industry stakeholders.IntroductionThe growth of supply chains and their increasing interdependence raise concerns about vulnerability and the likelihood of supply chain failure (Kek et al., 2022). One significant contributor to supply chain failure is the propagation of disruption, commonly known as the ripple effect (Ghadge et al., 2022). The ripple effect exerts various negative impacts on the agricultural supply chain (Wei & Chen, 2010), with factors such as climate change exacerbating these effects on the agricultural sector and food supply chain (Galli et al., 2023). A prominent example of the ripple effect is the COVID-19 pandemic, which led to crises in the food supply chain, including human resource shortages, transportation disruptions, and input cost escalations (Waris et al., 2022). In Iran, the pandemic significantly disrupted the food supply chain, resulting in decreased profitability, sales rates, flexibility, and investment returns (Afzali and Zare Mehrjardi, 2020). Thus, investigating this issue in Iran's food supply is imperative. The objectives of the research are:Identifying strategies to cope with the ripple effect in Iran's food product supply chain.Presenting a fuzzy cognitive map of strategies to cope with the ripple effect in Iran's food product supply chain.Conducting scenario analysis of strategies to cope with the ripple effect in Iran's food product supply chain.Materials and MethodsThis research adopts a mixed-method approach, comprising qualitative and quantitative stages. In the qualitative stage, participants include experts and managers with a minimum of 10 years of experience in the food processing supply chain, possessing academic qualifications, and experience with supply chain disruptions. The statistical population for the quantitative stage encompasses the participants from the qualitative stage, supplemented by university professors with publications in the field of supply chain ripple effects. Thematic analysis is employed in the qualitative part to analyze the data. Subsequently, based on the qualitative findings, a researcher-designed questionnaire is developed for the quantitative phase. The fuzzy cognitive map method is then utilized to analyze the quantitative data gathered.ResultsSemi-structured interviews were conducted with experts to identify strategies for coping with the ripple effect in Iran's food supply chain. From these interviews, 84 primary codes were identified, which were then organized into 21 sub-categories and 4 main categories: "strategic management," "operations management," "drafting and correct implementation of laws," and "supply chain management." Notably, nearly half of the obtained codes were attributed to the "supply chain management" category, indicating its significant importance in addressing the ripple effect. In the second stage of the research, a questionnaire was designed based on the findings of the previous stage and administered to 10 experts for completion. In this questionnaire, experts were asked to assess the importance of each of the 21 sub-categories. Subsequently, FCMapper software was employed to construct a fuzzy cognitive map depicting coping strategies.Table 1: Analysis of strategies to cope with the ripple effectTypeCentralityOutdegreeIndegreeStrategyTotal Componentsordinary17٫295٫7311٫56121ordinary12٫32٫459٫852Total Connectionsdriver10٫1110٫1103191ordinary11٫128٫972٫154Densityreceiver9٫6409٫6450.45ordinary8٫282٫985٫36Connections per Componentordinary16٫914٫8712٫0479.09ordinary10٫278٫911٫368Number of Driver Componentsordinary17٫646٫9110٫7393ordinary10٫586٫434٫1510Number of Receiver Componentsordinary5٫192٫552٫64111driver5٫815٫81012Number of Ordinary Componentsdriver8٫98٫901317ordinary16٫336٫331014Complexity Scoreordinary16٫397٫379٫02150.33ordinary8٫897٫641٫2516ordinary15٫816٫369٫4517ordinary14٫184٫849٫3418ordinary11٫644٫197٫4519ordinary4٫723٫261٫4620ordinary11٫487٫134٫3521As shown in Table 1, 'Environmental change monitoring,' 'Strategic planning,' and 'Technology upgrade' strategies have the highest degree of effectiveness, while 'Inventory management,' 'Contingency programs,' and 'Production flexibility' strategies also exhibit high effectiveness. Furthermore, 'Production flexibility,' 'Contingency plans,' and 'Inventory management' demonstrate the highest degree of centrality. Figure 1 depicts the fuzzy cognitive mapping of strategies to cope with the ripple effect in the supply chain of Iran's food products.Figure 1: Fuzzy cognitive mapping of strategies to cope with the ripple effect To examine the scenarios, three backward and three forward scenarios were designed. In the backward scenario, the most effective variables were selected. Figure 2: The first backward scenario of coping strategiesCooperation and CoordinationSupplier Relationship ManagementContingency PlanningInventory ManagementFigure 3: Second backward scenario of coping strategiesSupplier Relationship ManagementCooperation and CoordinationContingency PlanningFigure 4: The third scenario backward coping strategiesCooperation and CoordinationSupplier Relationship ManagementContingency PlanningProduction FlexibilityFigure 5: Overlap of the backward scenarios of coping strategiesCooperation and Coordination Supplier Relationship Management Production Flexibility Contingency Planning Inventory Management To draw forward scenarios, strategies No. 3, 4, and 8, which represent 'monitoring environmental changes,' 'strategic program,' and 'technology improvement,' respectively, were selected.Figure 6: First forward scenario of coping strategiesMulti-Skilled WorkforceShort Term PlanningHRMTechnology UpgradeMonitoring Environmental Changes Figure 7: Second forward scenario of coping strategiesHRMMulti-skilled WorkforceShort Term Planning Horizontal IntegrationStrategic Planning Figure 8: The third forward scenario of coping strategiesMulti-Skilled Workforce Short Term PlanningHRMTechnology Upgrade Figure 9: Overlap of the forward scenario of coping strategiesMulti-skilled Workforce Short Term Planning HRMTechnology Upgrade Monitoring Environmental changes Horizontal IntegrationStrategic PlanningConclusionsFood product supply chain managers should consider long-term factors, price flexibility, and contract support clauses in contracts with suppliers. For foreign products, it is recommended to contract with companies that have active agencies in the country, as other companies may quickly cease their services due to new sanctions. The purchase of critical parts of the supply chain, known as vertical integration, is recommended to reduce risk. Contingency plans are necessary to cope with the ripple effect, but to develop suitable contingency plans, environmental and political issues must be carefully monitored. As a result, it is necessary to create management teams in food products to investigate environmental issues.
supply chain management
Allahyar Beigi Firoozi; Mohammad Bashokouh Ajirlou; Naser Seffollahi; Ghasem Zarei
Abstract
The current study aimed to cluster the application of digital technologies from Industry 4.0 in the agricultural food distribution network. To achieve this goal, a bibliometric technique was employed to identify prominent trends and themes in this field through the analysis of articles, authors, countries, ...
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The current study aimed to cluster the application of digital technologies from Industry 4.0 in the agricultural food distribution network. To achieve this goal, a bibliometric technique was employed to identify prominent trends and themes in this field through the analysis of articles, authors, countries, and co-citations of authors and bibliographic pairs. Through an extensive search in the Scopus scientific database, bibliographic information for 331 valid and relevant scientific articles was acquired. This information was inputted into the bibliometric package in R software, and the most influential journal, author, university, country, and most cited authors were determined. To visualize the information, Vosviewer software was utilized for co-citation analysis of authors, cited references, and bibliographic pairs. The findings from the network analysis revealed that the studies on the application of digital technologies in the agricultural food distribution network can be categorized into five main clusters.IntroductionIndustry 4.0, viewed as a new industrial stage, has introduced complex information and communication technologies that facilitate comprehensive connections across different parts of the supply chain. The digital technologies associated with Industry 4.0 allow production lines, business processes, and teams within a supply chain to collaborate seamlessly, irrespective of location, time zone, network constraints, or any other factors. Researchers highlight that the advent of digital technologies from the fourth industrial revolution, including radio frequency identification, big data, cloud computing, smart sensors, machine learning, robotics, augmented production, artificial intelligence, augmented reality, the Internet of Things, blockchain, and similar technologies, holds immense potential for significantly enhancing production productivity. These technologies could lead to substantial innovation, competitive growth, and may contribute to improving the sustainability of the current industrial system. To meet the escalating demand for food, agricultural marketing professionals and managers globally must maximize the efficiency of the agricultural distribution network, given the widespread adoption of digital technologies. The increasing significance of this goal has prompted marketing researchers to explore the use of digital technologies in the agricultural food distribution network, leading to a substantial number of studies in this research field since 2011. In this context, the present study aimed to cluster the utilization of digital technologies in Industry 4.0 within the agricultural food distribution network. A bibliometric study was conducted to identify existing gaps in research and propose future directions. The research focuses on the application of digital technologies in the distribution network.Aligned with the research objective, fundamental questions are posed: Which publications, authors, and countries are most influential in the application of Industry 4.0 digital technologies in the agricultural food distribution network? Additionally, what scientific clusters exist in this domain?MethodologyThe objective of the current research is to conduct a bibliographic analysis of studies related to the application of digital technologies in Industry 4.0 within the agricultural food distribution network. Utilizing bibliometric techniques, a crucial measure for evaluating scientific output, a comprehensive examination of scientific literature was carried out concerning the application of digital technologies in Industry 4.0 within the agricultural food distribution network.The search was conducted within the Scopus scientific database, which encompasses a significant array of diverse journals and authoritative articles globally. The search covered three sections: title, abstract, and keywords, yielding a list of studies that exclusively included English-language articles from journals (excluding conference studies and book chapters) published between 2011 (the inception year of Industry 4.0) and 2023. By imposing these criteria, 352 original pieces of data containing bibliographic information were obtained. Subsequently, the title and abstract of each article were meticulously scrutinized to identify information relevant to the agricultural food distribution networks. Among these, 6 articles pertaining to the halal supply chain and 15 articles conducted as systematic reviews were excluded from the bibliographic information collection. The final portfolio for analysis consisted of bibliographic information from 331 articles, which was then entered into the bibliometric software package. This analysis was carried out using R software and VOSviewer software. The bibliometric software package facilitated quantitative bibliographic analysis, while the VOSviewer software was employed for visualizing and analyzing citation networks.ResultsThe quantitative findings indicate a significant increase in studies related to the adoption of digital technologies in the agricultural food distribution network, particularly after 2017. The most widely utilized digital technologies in the food distribution network include blockchain, the Internet of Things, simulation, artificial intelligence, big data, machine learning, 3D printers, sensors, and digital twins.Through the analysis of bibliographic pairs, five primary clusters were identified concerning the application of digital technologies in the agricultural food distribution network. These clusters are associated with the use of digital technologies in ensuring food quality, enhancing distribution network flexibility, establishing modular architecture within the distribution network, implementing intelligent logistics systems, and promoting sustainable distribution networks.ConclusionBased on the themes of the clusters identified in Table 7, it can be concluded that the Internet of Things and blockchain play crucial roles in real-time tracking, tracing, and monitoring of food throughout the supply chain, thereby reducing wastage. RFID technologies and digital twins are highly effective in ensuring food safety and facilitating delivery to consumers, especially in the face of environmental changes and crises such as epidemics. Another application of digital technologies lies in the modular architecture of the food distribution network. Through the use of modular architecture, various technologies can modularize tasks and extensive operations within the food distribution network. Ultimately, all these components can be centralized under blockchain technology, with diverse data stored in a vast cloud space. Consistent implementation of digital technologies in the food distribution network has the potential to establish regional warehouses, resulting in reduced distribution and delivery costs, enhanced food safety and sustainability, and the possibility of customizing food for end consumers. This, in turn, will contribute to the stability of the food network.
supply chain management
Mahsa Pishdar; Atefeh Habibi
Abstract
To explain a framework for managing the risk of transportation in the food industry supply chain, the initial step involves identifying 12 risks that can potentially lead to transportation disruptions, based on the research background. Utilizing the Delphi method and gathering opinions from 15 academic ...
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To explain a framework for managing the risk of transportation in the food industry supply chain, the initial step involves identifying 12 risks that can potentially lead to transportation disruptions, based on the research background. Utilizing the Delphi method and gathering opinions from 15 academic and industrial experts across 3 stages, the risks were ultimately defined. Furthermore, expert opinions were sought to determine solutions to address the identified risks. The grey DEMATEL method was employed to investigate the interaction of risks. The findings revealed that weather problems, natural disasters, insufficient skilled labor/labor strikes, infrastructure capacity, and inflation and exchange rate changes are among the risks that exert a more significant influence on other risks than they are influenced by them. Subsequently, using the grey COPRAS method, the prioritization of solutions to mitigate the identified risks, based on expert opinions, was undertaken. The results indicated that the top-ranked solution is the definition of key performance indicators. Therefore, it is recommended to managers that, in order to establish a robust supply chain and proactively manage risks, they should identify stakeholders and critical processes. Afterward, an agreement on the financial flow in each situation should be obtained, and a value flow map drawn. This approach enables the implementation of preventive measures to reduce supply chain risk and facilitates the preparation of an emergency plan for unforeseen conditions, thereby enhancing resilience.IntroductionDisruption in transportation stands as the pivotal factor undermining the efficiency of the supply chain. Any significant interruption can result in delays or business flow cessation, leading to consequential impacts (Ali et al., 2021). The transportation supply network is susceptible to various technical, economic, and environmental factors (Tan et al., 2023). Simultaneously, research indicates that factors such as a workforce lacking sufficient skills, suboptimal selection of service providers, traffic accidents, and the inability to predict the systemic impact of these risks play a crucial role in transportation, causing disruptions in the flow. In addition to these factors, it is noteworthy that supply chain management in the food industry introduces its own complexities. Unlike other industries, the quality of products in this type of supply chain consistently diminishes during product movement and this issue of perishability intensifying the need for transportation risk management (Hosseini-Motlagh et al., 2019; Choe et al., 2021). Given this context, emphasis should be placed on establishing distribution channels with lower costs and implementing change management to enhance efficiency. However, existing studies have predominantly focused solely on analyzing transportation disruption within companies' supply chains. Clearly, it is insufficient to only address disorders or the risks that may lead to their occurrence. A comprehensive examination of the cause-and-effect relationships among these risks facilitates a systematic understanding of the risk network. This approach enables the development of a more effective program to enhance the resilience of the transportation system. Even in the face of risks and disruptions, this ensures minimal damage, a swift return to normal operational levels in the supply chain, or the application of knowledge management to learn from experiences and prevent the recurrence of disruptions through appropriate implementation solutions. Consequently, the overall performance of the supply chain can be improved. In consideration of these elements, this study aims to address the following main questions:- What are the risks associated with transportation in the food supply chain?- What are the pertinent solutions, according to expert opinions, and what is their prioritization?MethodologyIn terms of its objective, the current study falls within the domain of applied research as it aims to discover practical solutions to address a real-world problem. Regarding information collection, the study is categorized as survey research, wherein data is gathered based on the opinions of 15 experts. Among these experts, 9 are drawn from the industrial community, each possessing over 10 years of experience in the commercial sector and raw material procurement within the food industry. The remaining 6 experts are affiliated with the academic community and have published numerous articles in the field. The study unfolds in several stages. Initially, a compilation of transportation risks causing disruptions in the food supply chain is accomplished through a literature review. Subsequently, the Delphi method is employed to screen and refine these disruptions. The cause-and-effect relationships among the identified disruptions are then scrutinized using the Grey DEMATEL method. Experts are engaged to contribute not only by assessing the risks but also by providing their insights into coping strategies based on their experience. Finally, the coping strategies are prioritized using the Grey COPRAS method.Results and DiscussionAccording to the obtained results, it is evident that the climate problems risks of failure to choose logistics service providers that care about sustainability principles (C6) and frequent change of product delivery time (C9) exhibit the highest degree of interconnectedness with other risks. The weights of these risks have also been determined. Notably, the failure to choose logistics service providers committed to sustainability principles has secured the top rank with a weight of 0.1443. Following closely, the frequent change of product delivery time holds the second position with a weight of 0.1384, while natural disasters rank third with a weight of 0.1039. Turning to coping strategies, it is noteworthy that the solution of "Definition of Key Performance Indicators (KPI)" has claimed the top position. In today's business landscape dominated by Logistics 4.0 and Omnichannel, simplifying processes can create significant added value for any business, particularly in minimizing transfer time. Concurrently, many manufacturing companies are leveraging various logistics transportation modes as a critical factor for promptly responding to demands, thereby enhancing service reliability and minimizing travel time (Foroozesh et al., 2022). The adoption of modern technologies such as the Internet of Things facilitates real-time inventory monitoring, contributing to dynamic pricing policies. As product quality diminishes along the chain, electronic labels enable adjusting product prices based on features (Kumar & Agrawal, 2023).ConclusionStudies indicate that supply chain managers, particularly in food supply chains, have demonstrated significant commitments to sustainability goals, leading to the pursuit of a diverse array of performance improvement projects. This study identifies various risks and corresponding coping strategies. Outsourcing logistics activities to 3PL allows leveraging their expertise in supply chain management, thereby enhancing stability and efficiency. This approach can contribute to reducing the carbon footprint, increasing order fulfillment, and lowering energy consumption throughout the supply chain.For future research endeavors, it is recommended to prioritize strategies related to realizing the circular economy within the logistics system of the food industry. Providing a roadmap for the sustainable development of logistics clusters can enhance supply chain performance, minimize waste, and boost the social credibility of the supply chain. Additionally, attention to the concept of greenwashing in sustainable logistics, particularly concerning the fulfillment of social responsibility, can prove beneficial in improving overall supply chain performance
supply chain management
Mehrdad kiani; davood andalib ardakani; Habib Zare Ahmadabadi; Seid Heydar Mirfakhraddini
Abstract
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society ...
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Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.
Introduction
The concept of the circular economy can be regarded as a solution to reduce production costs within a sustainable supply chain. In this context, the integration of cyber-physical systems, big data, data mining, data analytics, the Internet of Things, and novel business models can offer significant opportunities for the creation of sustainable industrial value, value capture, and the promotion of the circular economy (Antikainen et al., 2018). Industry 4.0, often referred to as the future of supply chains, can have numerous implications for sustainability, including the optimal utilization of resources and technology (Quezada et al., 2017). Based on the sustainability axis, the concept of Industry 4.0 aids industrial managers in encompassing not only environmental protection and control initiatives but also aspects of process safety, such as resource efficiency, human resource and societal well-being, and the development of smarter and more flexible supply chain processes (Luthra & Mangla, 2018). Numerous studies have explored the factors that impact the implementation of circular economy and Industry 4.0, and these factors have been broadly classified into categories such as barriers, challenges, drivers, and enablers (Fedotkina et al., 2019). Identifying the enablers that are effective in implementation is a crucial step in enhancing the performance of a circular and intelligent supply chain. Until these enablers are identified, it is impossible to determine their relative importance. Following their identification, industry practitioners and policymakers can develop appropriate strategies for their implementation. As such, this current research aims to identify, categorize, and analyze the effective enablers for implementing circular economy and Industry 4.0 at the Ardakan Glass Factory in Yazd, which is the largest glass factory in West Asia. To achieve this, both a qualitative method for enabler identification and the technical Dimtel method using fuzzy logic for establishing cause-and-effect relationships between enablers are employed. What sets this research apart from others is its focus on identifying the combined enablers for implementing the circular economy and Industry 4.0 at the Ardakan Glass Factory Group of Yazd, as well as the network approach that examines the relationships and interactions between these enablers. Given these key elements, this research aims to address the following questions:
-What are the effective enablers for implementing the circular economy and Industry 4.0 at the Ardakan glass factories in Yazd?
-What is the effectiveness and influence, including cause-and-effect relationships, of these enablers?
Materials and Methods
This research is categorized as applied-developmental research in terms of its purpose and is classified as a field-library study in terms of its methodology. Its objective is to formulate a novel scientific model of enablers for implementing circular economy and Industry 4.0 within organizational supply chains. Given the significant number of qualitative articles that have explored the enablers of Industry 4.0 and the circular economy across various industries and the need to establish a shared understanding of these enablers, the first stage of this research involved identifying effective enablers using the meta-synthesis qualitative method. Their validity was assessed through content validity, which involved obtaining opinions from 15 organizational experts. In the second phase of the research, the researchers evaluated the effectiveness and impact of these enablers using the Fuzzy DEMATEL method. The statistical population for the first stage of the research comprised all studies published in the Scopus database, the largest text database, related to the enablers that influence the implementation of circular economy and Industry 4.0 within organizational supply chains up until the commencement of this research. In the second stage of the research, the statistical population included all professors and managers with expertise in sustainability, familiar with circular economy, and knowledgeable about Industry 4.0 technologies at Ardakan Glass Factories in Yazd. For this phase, a purposeful sampling method was used to select ten participants.
Discussion and Results
The purpose of the current research is to analyze the enablers that are effective in implementing the circular economy and Industry 4.0 within the supply chain of Ardakan Glass Factories in Yazd. In the first stage of the research, various articles were reviewed, and the meta-combination method was employed to identify and categorize relevant enablers. This process led to the identification of 15 enablers across four dimensions: economic, human resources, organizational management, and infrastructure. In the second stage, the Fuzzy DEMATEL technique was utilized to investigate the cause-and-effect relationships between these enablers. The research results revealed that the economic and infrastructural enablers are considered influential dimensions that affect human resources and organizational management dimensions. Within the economic dimension, "budget allocation for the implementation of the circular economy and Industry 4.0" and "stimulation of demand for circular products" emerged as the most effective enablers. Additionally, in the infrastructure dimension, "development of IT standards and infrastructure" was identified as the most influential enabler for the implementation of the circular economy and Industry 4.0 within the supply chain. In the organizational management dimension, "the support and commitment of senior management" was recognized as the most influential enabler.
Conclusion
While the enablers mentioned are considered among the most effective ones in implementing circular economy and Industry 4.0 in the Ardakan Glass Factories of Yazd, it's crucial for the glass industry to prioritize the most important enablers. It's essential to pay adequate attention to all identified enablers. Using specific guidelines and a checklist of effective enablers during decision-making can facilitate the decision-making process and enhance decision-making capabilities. Therefore, based on the identified enablers and their importance in this research, it's recommended to develop and provide guidelines and checklists for executive managers. Among the significant limitations of this research is the reliance on a single scientific database, Scopus, for sourcing research. It's advisable to supplement this by utilizing other databases such as Google Scholar and Web of Science. Additionally, the classification of enablers was conducted using a qualitative approach. Researchers are encouraged to name and categorize enablers using survey and quantitative methods, such as cluster analysis, to expand their research scope. Another limitation pertains to the research's statistical population, which was restricted to Ardakan Glass Factories in Yazd due to time and cost constraints. To generalize the research results, it's advisable to investigate the same research topic in other glass factories across the country. Future researchers could employ methods like fuzzy cognitive mapping and systems dynamics to examine relationships and interactions between enablers. Moreover, the enablers identified and analyzed in this research were primarily based on international studies. To adapt these enablers to the specific conditions of Iran's industries, it's suggested that in-depth interviews be conducted with industry owners. This way, certain enablers that may be unique to Iran's circumstances or require different interpretations can be revised.
supply chain management
Fatemeh Arjmandi; Parvaneh Samouei
Abstract
Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive ...
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Planning and scheduling operating rooms and required equipment is very important for hospital managers from the perspective of cost, social, and health principles. Because operating rooms are one of the sources of income for hospitals that can provide the services needed by emergency patients who arrive randomly and elective patients whose surgery is preplanned. Since some tools used in operating rooms need to be sterilized each time, and in the real world, due to various reasons such as the physical condition of each patient, the duration of surgeries is uncertain, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. Solving several problems and different sensitivity analyses confirmed the validation of the presented model from the viewpoint of the hospital managers.
Introduction
The healthcare system is one of the most important topics that has attracted the attention of researchers and hospital managers. Two significant elements of healthcare systems are patients and hospitals, and their planning and scheduling are necessary for providing better services. Hospital managers aim to minimize costs or maximize profits while considering service times. Operating rooms are often the most critical sections of the hospital. Since life and death issues are at stake in the operating rooms, even the slightest delay or lack of resources can endanger human lives. Therefore, careful planning and scheduling of operating rooms and their resources is especially important. Additionally, to prevent potential hospital infections, the sterilization of reusable medical instruments is essential for every operation. Furthermore, patients can be broadly categorized into two groups: emergency patients who arrive randomly, and elective patients whose surgeries are preplanned. Planning and scheduling operating rooms, along with the required equipment, is of utmost importance for hospital managers, taking into account cost, social factors, and health considerations. Some items used in operating rooms need to be sterilized after each use, which incurs both time and cost.
Methodology
Due to high fluctuations of the duration of surgery, the different condition of each patient, and in order to get as close as possible to the real conditions, the duration of each surgery is considered uncertain. In this research, in addition to considering selected patients, considering the uncertainty of the duration of surgery, emergency patients have also been investigated, and dealing with uncertainties, the robust optimization approach is used. This approach is stable against changes, and minimizes the fluctuation of changes and maintains optimal and feasible. Therefore, in this research, as well as considering the uncertainty of surgery times for emergency and elective patients, a robust scenario-based integrated mathematical model with two objective functions is presented. In this model, in addition to minimizing the cost of operating rooms, sterile section, and penalties for delay in surgery, the competition time of the last operation is minimized. There are costs for performing elective and emergency operations, and in order to give priority to emergency patients, the cost of performing the operation of these patients is lower than the cost of performing elective operations surgeries of emergency patients, such as those injured in accidents, must be performed as soon as possible and these patients should be paid less. Also, for emergency patients, a maximum waiting time is considered, which they should not wait more than it. Obviously, surgeries that cannot be scheduled during the working hours of the operating room are postponed. Every patient needs a number of reusable medical tools that require sterilization. The sterile duration of reusable tools and the capacity of each sterile machine are known.
There are various techniques for solving multi-objective problems, one of which is the epsilon constraint method. In this method, one of the objective functions is considered as the main objective function and other objective functions are applied as constraints to the problem. Various developments for the epsilon constraint method have been presented to make it more efficient, among which we can mention the Augmented Epsilon Constrain (AEC) method. Moreover, in order to solve the bi-objective integrated mathematical model, Mulvey's robust method is implemented on the model, and its validation is carried out in the GAMS software with the AEC method.
Results and Conclusion
Different sensitivities all confirm the validity and accuracy of the model from the point of view of hospital managers. According to the obtained results, the changes of the three parameters of surgery delay cost, duration of surgery and sterile duration times have more effects on the both objective functions of the mathematical model than other parameters of the problem. Furthermore, the obtained results show that the first objective function, which includes the total cost, will have the highest value when the delay cost parameters and the duration of the surgical operations increase. For the second objective function, which shows the complete time of the last operation, the most challenging situation occurs when the parameters of the duration of surgical operations and the sterile duration increase. Therefore, the most ideal situation from the point of view of the hospital manager is to reduce all three parameters, which will reduce, the total cost and the completion time of the last operation; Moreover, the results show, the separate costs of planning and scheduling of the operating room and the sterile department are more than when the planning and scheduling of the operating rooms and the sterile department were examined in an integrated manner. The results of this research can be used for the integrated planning and scheduling of the operating rooms and sterilization department in all hospitals as a suitable management tool.
supply chain management
shahryar marzban; Morteza Shafiee; Mohammad Reza Mozaffari
Abstract
There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, ...
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There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, we aim to assess the sustainability of the supply chain for perishable products in the food industry. After examining both external and internal factors and identifying a research gap, the structure of the present study involves a four-stage supply chain. Input and output variables were selected based on perishable products and the three dimensions of sustainability. To achieve this goal, we conducted field and library studies to identify and extract relevant input, output, and intermediary indicators for evaluating the relative efficiency of supply chains in various sectors. Subsequently, we examined the supply chain's efficiency and ranked the efficient units. Given the primary focus on perishable materials, our study involved 18 dairy and meat factories in Fars province as the statistical population. We utilized WinQSB software to analyze network downtime and to model and solve the data. The results highlight that the most significant challenges faced by the companies are in the supply sector. Based on these findings, we provide recommendations for companies to enhance their performance.IntroductionIn the food industry, there are numerous inventory systems that deal with perishable items, which have a limited shelf life. These perishable items encompass a wide range of products, including food, fruits, and medicine. Given the extensive use of these products, it is crucial to model perishable products within a supply chain context. Furthermore, reviewing the contracts and regulations among the supply chain members is of great importance for decision-making in interactive conditions. This study aims to determine the most effective ordering policies at different levels of the perishable food supply chain. The goal is to maximize the overall profit of the chain while minimizing social and environmental negative impacts. Our supply chain consists of four levels, including suppliers, manufacturers, distributors, and retailers. We have thoroughly investigated the dimensions of sustainable development, ultimately leading to an assessment of the overall performance of the chain. The primary research question we seek to answer is: 'How does the performance of the perishable product supply chain align with a sustainable development approach?MethodologyIn this section, we employed the network data overlay analysis model to assess the performance of the research supply chain and determine the efficiency of the research units, with a particular focus on perishable products. Conventional Data Envelopment Analysis (DEA) models typically overlook the steps and internal processes within Decision-Making Units (DMUs). These conventional DEA models treat each company as a DMU and limit their calculations to initial inputs and final outputs. Given that DEA has been increasingly used in recent years for buyer-seller relationships, production-distribution processes, and performance evaluations in supply chains, and recognizing that a supply chain is a unique decision-making unit with not only input and output indicators but also intermediary indicators that flow from one stage to the next, traditional data envelopment analysis models may fall short in accurately and comprehensively evaluating supply chain performance due to the network or multi-stage nature of the supply chain. Hence, this study adopts the NDEA model with a fresh approach, calculating efficiency based on sustainability indicators related to perishable products in 18 manufacturing supply chains of dairy, meat, and protein products. Conducting an in-depth study to identify the significant parameters in the research field is a prerequisite for any applied research. To this end, we conducted extensive field and library research to investigate variables and indicators across various supply chain activities. This allowed us to identify and extract meaningful input, output, and intermediate indicators for evaluating supply chain performance in the supplier's sector. After reviewing existing literature, we identified 51 specific indicators that play a crucial role in the research.ResultsAccording to research findings, it is shown that the average efficiency of the supply chain for the production and distribution of perishable products in the financial year studied by the research was 0.9634% in the suppliers' sector. This average was 0.9899 in the producers' sector, 0.9903 in the distributors' sector, and 0.9707 in the retailers' sector. Therefore, the average efficiency indicates that the most significant inefficiency problems of the studied companies are related to the supplier sector. Furthermore, the overall average efficiency is 0.9950. According to the results obtained from the Anderson-Piterson Method for Employer Units Ranking, DMU3's Supply Chain demonstrates strong efficiency, and the supply chains of DMU7, DMU2, and DMU4 followed in the subsequent rankings. All supply chains were rated based on efficiency.ConclusionAmong the supply chains of the 18 companies studied in the research that deal with perishable products, the supplier process exhibits lower efficiency scores compared to the production, distribution, and sales processes. Consequently, it is recommended that inefficient companies at each stage take action to identify the factors causing inefficiency in the production, distribution, and sale processes of perishable products. This can be achieved by modeling the performance of efficient companies, with the goal of improving the efficiency at each stage and overall efficiency. Based on the model and research results, the following topics are suggested for future research: Given that most of the inefficiency is associated with the first stage of the model, it is advisable to pay greater attention to the supply of raw materials and transportation, or to select different input indicators. The supply of raw materials for factories emerged as one of the major challenges in this research, highlighting the inefficiency at the first stage. It is recommended that separate modeling be conducted to address the supply of raw materials in the food industry. The highest inefficiency in the fourth stage of the model is attributed to the limited consideration of the social dimension in sustainable development. For future research, it is suggested to focus more on social dimension indicators, such as satisfaction, motivation, empowerment, respect, mutual trust, social commitment, and the creation of suitable working conditions, as well as workers' health and safety. Regarding the inefficiency in the second stage (manufacturers), future research could explore strategies to enhance the freshness of raw materials and the shelf life of perishable products. For the inefficiency in the third stage (distributors), future research should concentrate on modeling and designing innovative distribution systems and routing for perishable products.
supply chain management
Mina Kazemi Miyangaskari; Mohammad Reza Mehrregan; Hossein Safari; samira keivanpour; Mahmoud Dehghan Nayer
Abstract
In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, ...
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In today's competitive business landscape, the efficient management of supply chains has become a cornerstone of success for economic enterprises. Supplier selection, as the initial link in the supply chain, holds significant sway over various critical factors, such as product quality, return rates, and production costs. However, the real world is rife with uncertainties, making the application of a fuzzy approach highly advisable. This study's primary objective is to develop a model for supplier selection and order quantity determination for perishable protein products in a retail setting under uncertain conditions. Initially, a comprehensive fuzzy multi-objective model is designed for Kourosh Protein, a company in the closed-loop supply chain, aiming to minimize costs, waste, and maximize profit, customer satisfaction, quality, and profit margin in the face of uncertainty. Subsequently, this full-fledged fuzzy multi-objective model is transformed into a deterministic single-objective model using the Sharma and Agarwal method (2018), yielding optimal order quantities from each supplier. The model's practical implementation in an Iranian retail store for protein products, such as sausages, bologna, hamburgers, etc., demonstrates its potential to reduce costs and boost profits.IntroductionThe global population's rapid expansion and shifts in lifestyle have significantly elevated the food sector's importance in the global economy, specifically in Sustainable Food Supply Chain Management (SFSCM). SFSCM plays a pivotal role in balancing economic, social, and environmental criteria to optimize supply chain performance. Within the complex food supply chain, suppliers wield considerable influence due to their impact on product attributes, safety, quality, and perishability. Supplier selection, a critical facet of SFSCM, substantially affects a company's strategic and operational performance, product pricing, and quality. In this context, this research introduces a fully fuzzy multi-objective model (FFMOP) to enhance the sustainable supply chain performance of a retail company's protein products. Given the inherent uncertainties associated with supplier selection, the proposed model incorporates an extensive array of variables to simulate real-world scenarios. This innovative approach aims to address identified gaps in existing literature, providing a more robust and realistic tool for bolstering supply chain sustainability.Materials and MethodsThis study constructs a full fuzzy multi-objective model with the objective of determining optimal order quantities within the food supply chain while integrating sustainability criteria. The analyzed supply chain network encompasses multiple suppliers, a single retailer, and end consumers, characterized by multi-product and multi-level interactions. The model seeks to optimize profit, customer satisfaction, brand acceptance, quality, profit margin, and minimize waste production while determining the optimal order volume for each product from each supplier. Reviewing the existing literature reveals various approaches to tackle Full Fuzzy Multi-Objective Problems. This research employs the methodology proposed by Sharma & Aggarwal in 2018 to solve the FFMOP model. After defuzzification, the final model is solved using GAMS software to determine the optimal values of decision variables.ResultsThis research utilizes a case study of an Iranian retail company with eight main suppliers providing 15 protein food products. However, the focus is primarily on four key products: sausages, bologna, hamburgers, and pizza cheese, which are examined. Data for the study was collected from historical company records and interviews with experts from June 2021 to 2022. Model parameters are defined using trapezoidal fuzzy numbers. A comparison of optimal order quantities with the company's actual orders and sales reveals that the proposed model for order allocation leads to reduced ordering, maintenance, and procurement costs for the company. Additionally, the model mitigates waste resulting from unsold products.ConclusionSupplier selection stands as a pivotal process in an effective supply chain, exerting substantial influence on a company's strategic outcomes and performance metrics. This study employs a full fuzzy multi-objective model to identify the most suitable supplier and determine optimal orders within a sustainable food supply chain context. To better mimic real-world conditions, variables and parameters are treated as trapezoidal fuzzy numbers. A comparison of the model's outputs with actual sales data indicates that this methodology aligns more accurately with sales figures. Consequently, applying this model has the potential to reduce waste production and economic consequences. The study's achievement lies in selecting a supplier through a methodology that simultaneously considers sustainability criteria within a fully fuzzy environment while determining optimal order quantities from various suppliers. Moreover, the model's flexibility allows for its application across diverse industries, including dairy and dried fruit, for procuring and selling an array of products from potential suppliers.
supply chain management
S.Ali Torabi; Yasin Heidari
Abstract
In a competitive world, one of the most crucial ways to enhance the supply chain performance of manufacturing companies is through integrated scheduling of production and distribution activities. Two significant concerns for dentists and patients include delayed denture deliveries and the multiple production ...
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In a competitive world, one of the most crucial ways to enhance the supply chain performance of manufacturing companies is through integrated scheduling of production and distribution activities. Two significant concerns for dentists and patients include delayed denture deliveries and the multiple production and correction processes for dentures. This research addresses these concerns by developing a mixed-integer linear programming model for solving the integrated production and distribution scheduling problem in a fixed denture supply chain operating under an additive manufacturing environment. The objective functions of this model aim to minimize the cost of production and distribution orders while reducing weighted delays. The Augmented Epsilon Constraint Method is employed to identify Pareto-optimal solutions. To validate the mathematical model, a numerical example and a case study are presented, and various sensitivity analyses are conducted on key model parameters. The numerical results demonstrate substantial improvements in total costs and customer satisfaction levels.IntroductionA supply chain (SC) comprises several interconnected echelons and processes, where an integrated perspective can lead to optimal overall SC performance. Simply improving an organization's internal processes is insufficient for competitiveness in the market; establishing effective relationships with suppliers, distributors, and other SC stakeholders is essential. Achieving maximum value along the SC involves focusing on cost reduction through cost-effective decision-making. In the past decade, the rising adoption of 3-D printing and additive manufacturing technologies in SCs, as a prominent disruptive technology in the Industry 4.0 era, has created numerous opportunities for improving manufacturing SCs compared to traditional production methods. These opportunities include reduced setup and production times, lower safety stock levels, and fewer processing steps. Additive manufacturing has found applications in various fields, particularly in denture production. This research addresses two primary concerns in the field: timely denture delivery and the multiple production and correction processes associated with dentures. A novel mathematical model is developed to tackle these issues, aiming to solve the integrated production and distribution scheduling problem in a fixed denture supply chain operating within an additive manufacturing environment. The objective functions of this model aim to minimize the costs associated with production and order distribution while minimizing the weighted total delays.Materials and MethodsA mixed-integer linear programming model is devised to address the problem outlined in this paper. The Augmented Epsilon Constraint Method is applied to identify Pareto-optimal solutions. To validate the mathematical model, a numerical example and a case study are presented, and several sensitivity analyses are conducted on key model parameters to elucidate their critical roles in the final solutions.Discussion and ResultsA case study is provided to demonstrate the practical applicability of the developed model. Sensitivity analyses on demand data highlight the substantial impact of demand management on final solutions. This research presents a two-objective optimization model to address the simultaneous scheduling of production and order delivery in a three-tier dental prosthesis supply chain. The first tier comprises a dental prosthesis production laboratory, while the second and third tiers include distributors and dentists (final customers). The objective functions include the minimization of total order delivery costs and the average weighted lateness of delivered products from a fixed dental prosthesis production laboratory. Constraints encompass delivery time delays, order allocation to customers, capacity limitations, calculations of time to reach each customer, and vehicle routing. Given that this research problem falls into the category of multi-objective problems, the Augmented Epsilon Constraint Method is employed to obtain Pareto-optimal solutions. To investigate and implement the proposed model, a fixed dental prosthesis production laboratory in Neka City is examined. The numerical results indicate the existence of a trade-off between the problem's objectives.ConclusionsThis paper presents a bi-objective model to address the integrated production and distribution scheduling problem in a three-tier dentures supply chain, aiming to minimize total delivery costs and the average weighted tardiness. The first tier includes a dentures production laboratory, while the second and third tiers comprise distributors and dentists, respectively. Numerical results based on a real case study demonstrate the practical applicability of the model. Several avenues for future research include considering uncertainty in input data and developing efficient meta-heuristic algorithms for solving large-scale instances.
supply chain management
hossein karimi; MohhamadJavad Jamshidi; Milad Bakhsham
Abstract
This research aims to identify key components and indicators for managing green supply chains utilizing the Internet of Things (IoT). The methodology employed is a mixed approach consisting of two stages. First, through qualitative content analysis, this study reviews theoretical foundations and previous ...
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This research aims to identify key components and indicators for managing green supply chains utilizing the Internet of Things (IoT). The methodology employed is a mixed approach consisting of two stages. First, through qualitative content analysis, this study reviews theoretical foundations and previous research to identify indicators associated with drivers for green supply chain management based on IoT. Subsequently, these indicators were presented to 22 experts in management and information technology to validate and verify them. The research findings reveal that the IoT-based green supply chain model encompasses nine components and 66 indicators. These components include intelligent supply chain management, real-time monitoring of object statuses in the supply chain, intelligent object transfer along the supply chain, intelligent object location in the supply chain, information transparency within the supply chain, corruption reduction, intelligent quality management within the supply chain, intelligent sourcing in the supply chain, intelligent distribution management, and intelligent inventory management. The comprehensive drivers in the proposed model emphasize the importance of incorporating IoT in supply chain management to enhance overall supply chain performance while addressing environmental concerns.IntroductionAs technology continues to advance rapidly across various industries, mankind has enjoyed an improved quality of life. However, the environmental toll of recent decades, such as global warming, water scarcity, polar ice melting, habitat destruction, and deforestation, has raised significant environmental concerns. Modern human activities have contributed to these environmental issues. Consequently, there is mounting pressure on companies to integrate environmentally responsible practices into their operations and supply chains. Recognizing the pivotal role of green supply chain management in sustainable job creation, environmental problem reduction, improved public health through safer food consumption, and enhanced agricultural land productivity, recent years have witnessed increased interest and research into the determinants of green supply chain management.MethodologyThis research adopts a mixed-method approach conducted in two stages. Firstly, qualitative content analysis is employed to review theoretical foundations and prior studies, facilitating the identification of indicators associated with drivers for green supply chain management using IoT. Subsequently, these identified indicators are validated and verified by 22 experts specializing in management and information technology.ResultsThe research findings indicate that green supply chain management, with an IoT approach, comprises nine components: intelligent supply chain management, real-time monitoring of object statuses, intelligent object transfer, intelligent object location, information transparency, corruption reduction, intelligent quality management, intelligent sourcing, intelligent distribution management, and intelligent inventory management.ConclusionsThis study highlights the presence of nine components and 66 indicators within the IoT-based green supply chain model. These components encompass various aspects of supply chain management, emphasizing the importance of incorporating IoT technology to enhance overall supply chain performance while addressing environmental considerations. Due to the growing concerns surrounding environmental issues and the emission of harmful substances by companies, it is highly recommended to incorporate the IoT into supply chain management. This integration serves to monitor and control the quantity of waste generated, and encourages the use of environmentally-friendly 3D printing for creating IoT sensors instead of traditional plastic materials. Furthermore, it is advisable to optimize waste collection schedules and routes for garbage trucks, as these measures can significantly reduce the time and resources spent on waste management. To facilitate this transition, managers should organize in-service training programs to educate employees about IoT technology and communication equipment, emphasizing the positive impact of these advancements on green supply chain management. Additionally, adopting state-of-the-art technologies like Radio-Frequency Identification (RFID) in supply chain systems can contribute to the development of a sustainable and environmentally-conscious supply chain. Legislative bodies should also play a crucial role in promoting green supply chain practices by identifying and addressing legal loopholes in existing supply chain-related laws. This can be achieved through the implementation of incentives, such as tax reductions for eco-friendly companies, or penalties, including tax hikes, financial fines, and even legal repercussions, to encourage the adoption of smoother and more environmentally responsible supply chain management practices. It's worth noting that this research has certain limitations. It primarily relied on articles within specific databases during a defined timeframe, excluding other valuable sources like foreign books and theses due to accessibility constraints. Furthermore, qualitative research inherently depends on the researcher's interpretation and perspective, potentially affecting the reliability of the results. Lastly, challenges related to the COVID-19 pandemic and respondent reluctance posed difficulties during the research process.
supply chain management
mona mousavie; Mahmoud Moradi; Mostafa Ebrahimpour Azbari
Abstract
In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, ...
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In light of the continuous and rapid changes in global competition, companies face the imperative of consistently introducing new products or expanding their existing product lines to maintain their competitive edge. Recognizing that numerous factors within the supply chain influence the production, design, distribution, and introduction of new products, understanding supply chain risks is crucial, spanning from the procurement of raw materials to the delivery of products to the market. Consequently, risk management stands as one of the most critical challenges within the supply chain, significantly impacting New Product Development (NPD) performance. This research seeks to answer the primary question: "How and to what extent do various supply chain risks affect newly developed products?" While prior research has employed various methods to evaluate and manage supply chain risks, few models have explored the interplay of these risks on each other and their influence on performance dimensions. In this study, based on a review of theoretical foundations and prior research within the clothing manufacturing sector, we identified dimensions of newly developed products and supply chain risks. We employed the Delphi technique through interviews to identify the most significant risks. Subsequently, we employed the Cross-Impact Analysis method to elucidate relationships between these factors. Finally, we utilized Bayesian networks to analyze the impact of identified risks on the performance of the selected new product, conducting sensitivity and scenario analyses. The findings indicate that environmental and supply risks are more likely to manifest than other risks, with three operational, distribution, and demand risks, influenced by environmental and supply risks, exerting the most direct impact on new product performance, particularly in the dimension of quality.IntroductionModern organizations recognize that traditional competitive strategies, such as improving quality and reducing costs, no longer suffice to remain competitive. Research has demonstrated that numerous new product development NPD projects face failure for various reasons. Effective risk identification and management, particularly concerning supply chain risks in NPD projects marked by a high degree of uncertainty, emerge as pivotal factors for NPD success. In this context, the clothing sector, characterized by a complex supply chain structure, has been extensively studied. However, prior research has predominantly examined existing risks individually, overlooking the interactions between risk components and their simultaneous effects on one or more project objectives. In this research, we not only assess the simultaneous impact of risks on product performance using the Bayesian network method, an effective approach in supply chain risk analysis, but also investigate the severity of risk impacts under different scenarios. This research addresses three primary objectives:Identification of supply chain risks in the clothing industry based on background research and case studies.Determination of interdependencies among variables using conditional modeling.Evaluation of the influence of supply chain risks on new product performance using the Bayesian network method under varying scenarios.Literature reviewNumerous researchers have investigated supply chain risks and their repercussions on product and organizational performance. Asgharenjad Nouri et al. (2021), in their article titled "The Effect of Risk Management on New Product Development in the Banking Industry," explored the impact of various risk indicators on new product development. Their results underscore the significant positive influence of managing all risk indicators, including technology, market, environment, finance, organizational resources, and commercialization, on new product development. Qazi et al. (2017), in their article titled “Supply Chain Risk Network Management,” prioritized risks and corresponding strategies through a case study involving semi-structured interviews. They initially identified organizational performance criteria and then linked them to relevant risks, using a matrix of expected profit to investigate the impact of risks on specified performance criteria. Subsequently, they employed the "weighted net evaluation" method to assess practical strategies.MethodologyIn conducting this research, we initially extracted supply chain risks and product performance dimensions from the existing literature. Subsequently, we employed the Delphi technique to select the most significant supply chain risks, providing indicators to participating experts through questionnaires with a 5-point Likert scale. We then used the Content Validity Ratio (CVR) index to confirm or reject the components derived from the questionnaires. In the next step, we used the Cross-Impact Analysis method, employing pairwise comparisons via questionnaires, to reveal relationships between the key risk criteria. Finally, we investigated the impact of identified risks on the performance of the selected new product within the supply chain of Happy Land factory using the Bayesian network method under various scenarios.Discussion and ResultsThe results from the Bayesian network analysis in this research demonstrate that environmental risk, as an external risk within Happy Land’s supply chain, exerts the most significant influence at the highest level of the Bayesian map. Subsequently, other risks, including economic risks, supplier risks, distribution risks, operational risks, and demand risks, are categorized in subsequent levels. Additionally, sensitivity analysis scenarios, depicted in the Tornado chart, reveal that supply chain risks have a substantial impact on performance criteria. According to this scenario analysis, the primary risk affecting quality and cost target nodes is operational risk, while the major risk affecting the product delivery time node is distribution risk, and the primary risk influencing profitability is demand risk. Results from both pessimistic and optimistic scenario analyses under the second scenario of the research indicate that in the pessimistic state, the presence of a high percentage of these risks significantly negatively impacts quality performance. Conversely, in optimistic scenarios, where these risk factors are not present, improvements in quality's functional dimension exhibit the most substantial impact.ConclusionWhen introducing a new product to the market, evaluating and managing supply chain uncertainties is essential due to the mutual influence of new product development and the supply chain. Supply chain risk management, which commences with the accurate identification and assessment of risks and proceeds with appropriate responses, is crucial for providing efficient and effective new products to the market. In addition to employing the Bayesian network method, a highly effective tool in supply chain risk analysis, we have endeavored to evaluate the simultaneous impact of risks on product performance and assess the severity of risk impacts under various scenarios, including optimistic, pessimistic, and sensitivity analyses. Scenario building proves to be an effective method for validating a developed model to measure the impact of risks under different conditions on target criteria.
supply chain management
Homa Abedi Dehkordi; Ghasem Tohidi; Shabnam Razavyan; Mohammad Ali Keramati
Abstract
Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs ...
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Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs and outputs assume significance in each production technology, resulting in non-homogeneity among cement factories. Despite these differences, all these facilities are engaged in cement production, warranting a comparative analysis of their efficiency. This study examines the operational processes of five different cement production technologies—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies comprising a total of nine factories. The study evaluates their efficiency between 2017 and 2020 using network data envelopment analysis under non-homogeneous conditions across three modeling stages. An important aspect of this study is its focus on the entire supply chain, from raw materials to the final product. Although the raw materials employed vary among different cement production technologies, the end product remains largely consistent.IntroductionIn certain real-world scenarios, even with similar production technologies, the assumption of homogeneous decision-making units may not hold true. Practical applications often involve supply chain structures that differ significantly from others. For instance, some supply chains may, at certain stages, eject intermediate products to meet specific needs, a phenomenon not universal to all supply chains, resulting in non-homogeneous chains. The cement industry, including Iran, constitutes one of the pivotal economic sectors. Therefore, mitigating shortcomings, including resource and material waste reduction, can have a substantial impact on this industry and consequently on the broader economy. Due to varying climatic conditions, cement production employs diverse technologies, primarily categorized as dry or wet processes. This study investigates the operational processes of five different cement production methods—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies with a total of nine factories. Their performance between 2017 and 2020 is evaluated using network DEA under non-homogeneous conditions, encompassing three modeling stages.Materials and MethodsIn novel approaches, DEA is utilized to assess the performance of network decision-making units. The models typically assume homogeneity among decision-making units, which may not always align with real-world conditions. Practical situations often violate assumptions of unit homogeneity and uniformity in input and output parameters. Consequently, it is imperative to present and employ methods and models capable of accommodating non-homogeneous units. This study employs a scientific library research approach and practical purposive data collection to gather relevant information. This information informs specific adjustments to operational processes. Consequently, the development of a robust system for evaluating supply chain performance becomes essential. The study utilizes common models to evaluate efficiency under non-homogeneous conditions. Classification of operational processes and related data, followed by modeling using Lingo software, is employed in this research.Discussion and Result:This article consists of two parts. Initially, it introduces the fundamental performance evaluation model and subsequently delves into the three-stage model of data envelopment analysis (DEA) within the supply chain context. In the second part, the production processes of Portland cement are examined, covering dry, semi-dry, humid, semi-humid, and wet slurry processes. The proposed approach assesses the performance of four cement production companies over a four-year period. Efficiency calculations for nine factories are conducted in three stages:The first stage consists of three steps as follows:First step: Input and output parameters used across the entire production process are categorized based on the different production methods.Second step: Processes utilizing similar production steps, as determined in the first stage, are grouped into four categories.Third step: Efficiency assessments for factories sharing similar production stages from the previous step are conducted, resulting in the identification of nine categories.Second stage: The efficiency of each category, characterized by a common feature from the previous step, is calculated.Third stage: To determine the overall efficiency of each factory, the efficiencies of individual processes are multiplied.ConclusionsThe results indicate that the fourth cement production company exhibits the highest efficiency, while the first company has the lowest efficiency. Notably, the lowest efficiency for the years 2017 to 2020 was recorded by the first company in 2020, while the fourth company achieved the highest efficiency in the same year. Among the factories, the lowest efficiency was observed in 2017 for the first company's five semi-dry factories, the fourth company's four semi-humid factories in 2018, the fourth company's nine wet slurry factories in 2018, the third company's seven semi-humid factories in 2020, and the fourth company's four semi-humid factories in 2020, which recorded the highest efficiency. Further examination and identification of suitable solutions to enhance efficiency in cases with lower efficiency levels can follow this study.
supply chain management
fateme khanzadi; Reza Radfar; nazanini pilevari salmasi
Abstract
Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the ...
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Nowdays, supply chain specialists are looking for the integrated development of the supply chain model in order to increase the competitiveness, effectiveness and reduce the problems in the supply chain. They always seek to identify and develop this process so that they can cover more aspects of the chain. Adding effectiveness indicators along with LARG indicators and using the basics of the dynamic system to improve the efficiency of the supply chain is one of the innovations of this study. At first, by using research literature and studies, 12 headings of indicators were selected as LARG-E indicators. Then, with the Fuzzy Delphi method, the relationships and importance of each of these components were determined, and more important variables were modeled for further investigation. With using the concepts of dynamic systems, causal loops were drawn. Then, to check the function of the model, dynamic hypotheses were developed with the opinion of experts. In the next step, the flow diagram of the model and also the validation tests of the proposed model were done. Finally, by examining the outputs obtained from the proposed scenarios, it was found that most of variables have better behavior in LARG-E approach.IntroductionIn recent years, with the addition of various competitions in the world markets, many researches have been conducted to use new technologies and researches in order to improve the production process and increase the effectiveness of these competitions as much as possible (Mohghar et al., 2017). All the goals that work in this field increase the competitiveness of the organization. This competition is by reducing costs, being present in the market and satisfying the customer. To increase profits, protect the environment, keep the markets stable and meet the expectations of customers, organizations should be provided using the existing environments in a set of customers (Pisha et al., 2016). Use chain management requires the use of new facilities and improvements to previous findings such as lean, agile, resilience and green to increase speed and competitiveness, selection and decision-making to achieve the organization and maximum effectiveness.Today, supply chain specialists are looking for the integrated development of the supply chain model to increase the effectiveness and efficiency of the supply chain in order to increase competitiveness and reduce supply chain problems. In this case, there is a consensus among experts that there is no comprehensive model. All the mentioned cases make it inevitable to design a comprehensive and effective model for the supply chain. The verifiable issue is the conflicts and the non-alignment of all the indicators of the paradigms with each other. LARG paradigms, without considering the spirit of effectiveness in each supply chain, cannot fully protect it against continuous changes in the competitive market arena. A comprehensive model that pays particular attention to effectiveness while implementing LARG paradigms has not been examined in the literature review and the consensus of experts. Therefore, in this research, we are looking to design a comprehensive model in a LARG-effective manner so that the effect of various LARG-effective indicators on the performance of the supply chain can be investigated. The integration of LARG paradigms has been studied a lot so far, but its development is based on the concepts of innovation effectiveness of this research, and in this way, the dynamic system approach was used.Materials and MethodsTo formulate a LARG supply chain, first the framework, indicators and variables of each LARG paradigm were extracted from the research literature, then in order to develop them with effective concepts, the effective supply chain was studied. In order to implement the fuzzy Delphi approach, based on the effectiveness indicators extracted from the subject literature and LARG supply chain approaches, operational indicators were provided to the experts participating in the research in the form of a questionnaire via email and after initial coordination. After collecting the completed questionnaires, fuzzification operations, fuzzy averaging and then de-fuzzification were performed. The results were brought to the attention of the participants and they were asked to apply their desired changes according to the obtained results. This approach reached the saturation stage in the third round and there was no change in the opinions of the participants and the consensus of the panel experts was the final and trusted output of the Delphi method. Finally, according to these weights, 9 quantitative variables had the highest importance and were used for dynamic modeling. The simulation stage is done with the help of software and Nasim. According to the features of modeling based on system dynamics, this approach was chosen as the main research tool in this study because there are linear relationships between the variables and there are nested feedbacks between the variables of the subsystems, the importance of simultaneously improving the performance in different layers of the producer, supplier and distributor. Which is one of the goals of this research, with this approach, it can be a very suitable tool for decision-making by the senior managers of the organization.Discussion and ResultsOrganizations are trying to improve their competitiveness by adopting Lean, Resilient, Green and Agile strategies; But as it was said, the implementation of these paradigms, which sometimes have conflicting results, requires a new integration and index to align the goals. So far, many researches have been done by merging two or more paradigms, the combination of all 4 paradigms called LARG has greatly helped to improve the performance of supply chains, but in this research, in order to improve the conflicts between paradigms, a new concept of spiritual effectiveness was given to the supply chain. Understanding the dynamics of applying the above four strategies and their effectiveness was done using the dynamic systems approach. In this research, the indicators of the LARG supply chain were defined based on theoretical foundations and interviews with experts; then the effectiveness indicators were placed next to them. These indicators were implemented in the printing and ink industry. In this way, an effective LARG integrated system was defined; then, using a dynamic model, dynamic hypotheses were first defined and state and flow diagrams were drawn. After correctness of the model and validation of the model, two scenarios were examined for 8 important variables. After applying the scenarios, the performance of LARG and effective LARG was compared. By applying each scenario in the designed model, it was possible to check the effect of new indicators on the variables and their behavior.ConclusionsAs a result, if the components of the effective supply chain are properly integrated with the LARG concepts, they integrate the conflict that may exist between the LARG paradigms and play the role of synchronization and improvement as a ruler and standard. The effective management of the LARG supply chain may not be defined as an independent variable, but it is a result of variables and indicators that improved performance in most cases.
supply chain management
Ali Mahmoodirad; Ali Tahmasebi Notareki; Sadegh Niroomand
Abstract
The closed-loop supply chain is used in practice for several reasons. Firstly, returning products to the production cycle is important for its operation. Secondly, sustainability in the supply chain is a topic of interest for researchers, as the environmental impacts of industries are significant. In ...
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The closed-loop supply chain is used in practice for several reasons. Firstly, returning products to the production cycle is important for its operation. Secondly, sustainability in the supply chain is a topic of interest for researchers, as the environmental impacts of industries are significant. In this paper, a multi-objective integer fuzzy mathematical programming model is presented to design a sustainable closed-loop supply chain under uncertain conditions. The proposed model aims to maximize profit and social impacts, while minimizing gas emissions into the environment. Since decision makers face uncertainty and doubt, trapezoidal intuitionistic fuzzy numbers are employed to determine the parameter values in the model. To convert the objective functions and model constraints into crisp forms, the expected value and the intuitionistic credibility measure are developed for the objectives and constraints, respectively. Finally, an interactive fuzzy programming approach is utilized to solve the crisp multi-objective problem. Three numerical examples are designed and solved to validate the model and assess the efficiency of the proposed solution method.IntroductionSupply chain management encompasses techniques aimed at coordinating all aspects of the supply chain, from raw material procurement to product delivery or recovery, with the objective of minimizing total costs while addressing conflicts among chain partners. Once raw materials have traversed the forward chain and been transformed into products or services, they may require repair, transformation, or proper disposal, which occurs within the reverse chain. The integration of forward and reverse supply chain methods gives rise to a closed-loop supply chain.Today, one of the primary concerns for organizational managers in supply chain network design is the presence of uncertainties, such as disruptions and uncertain input parameters. Uncertainties can have adverse effects on supply chain performance and decision-making at various network levels, including tactical, strategic, and operational decisions. As probabilistic planning necessitates historical data, which may not always be available or accurate, the theory of fuzzy sets can serve as a suitable option for expressing ambiguity and lack of certainty in parameters. In recent years, environmental factors have received increasing attention. There has been a growing recognition of the importance of environmental effects and the need to incorporate these effects alongside traditional indicators in supply chain design. Environmental considerations are crucial not only for compliance with government regulations but also for improving the organization's social standing from the customers' perspective. Moreover, with the rise of global warming and the accumulation of waste (both renewable and non-renewable, as well as electronic waste and ozone-depleting gases), the importance of managing and controlling these factors has become even more prominent. Despite the significance of environmental issues, there remains a noticeable gap in the supply chain literature concerning the provision of mathematical models based on real-world conditions and efficient solution methods for this problem. This paper focuses on the design of a sustainable closed-loop logistics network that aims to maximize profitability and social factors while minimizing environmental factors. The proposed integrated network considers multi-product and multi-state customer demand under conditions of uncertainty. The significance of this research lies in simultaneously addressing economic, environmental, and social considerations in the modeling process, as previous studies have mostly focused on single or dual objectives. Another innovative aspect of this article is the consideration of parameters in the form of intuitive fuzzy numbers for the design of a sustainable supply chain network.Materials and MethodsIn this research, a comprehensive model addressing the problem of sustainable closed-loop supply chain under intuitionistic fuzzy uncertainty is selected through library studies and internet research. Subsequently, the model is transformed into a deterministic multi-objective model utilizing the intuitionistic credibility measure. Recognizing that decision makers face not only uncertainty but also doubts, trapezoidal intuitionistic fuzzy numbers are employed to determine parameter values within the proposed model. To convert the objective functions and model constraints into their crisp equivalents, the expected value and intuitionistic credibility measure are respectively developed for the objective functions and constraints.FindingsBased on the selected confidence levels and numerical examples, the following observations can be made: In numerical example 1, the first objective function demonstrated that the ABS, SO, and TH methods performed best, respectively. However, in the second objective function, the order shifted to SO, ABS, and TH. Interestingly, all three methods performed equally in the third objective function. The performance of the solution methods in numerical example 2 mirrored that of numerical example 1. Moving on to numerical example 3, the first objective function indicated that the SO, TH, and ABS methods were the most effective, respectively. The order remained similar in the second objective function, and once again, all three methods performed equally in the third objective function. These results indicate the relative superiority of the SO solution method compared to the other methods employed. Additionally, concerning the execution time of the solution methods, numerical examples 1 and 2 exhibited nearly equal execution times for the methods. However, in numerical example 3, the SO, TH, and ABS methods displayed the best performance in terms of execution time, respectively. These findings further emphasize the relative superiority of the SO solution method compared to the others in terms of execution time. It is worth noting that the execution time of each method alone increases significantly with the problem's dimensions across all numerical examples.ConclusionsThis paper presents a multi-objective fuzzy optimization model for the design problem of a sustainable closed-loop supply chain. The model takes into account the concept of sustainability and aims to maximize the income and minimize the costs of the entire supply chain, while also minimizing environmental effects and maximizing social effects. The parameters are considered uncertain and are represented by intuitionistic trapezoidal fuzzy numbers. To handle this uncertainty, the model is transformed into a deterministic multi-objective optimization model using the expected value definition and a chance constraint based on the size of intuitionistic. The obtained deterministic multi-objective model is then solved using the interactive fuzzy mathematical programming method.
supply chain management
Mehdi Seifbarghy; Nastaran Bakhshizadeh
Abstract
Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other ...
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Closed loop supply chain network design is of great important due to the legal requirements and economic benefits. Raw material suppliers are of the most important players of this supply chain. Most of the previous researchers studied the design problem separated from the supplier assessment. Some other criteria except for price, like the production process, the features of parts and reliability of supply have long term effects on the performance of supply chains. In this research a general closed loop supply chain network including production centres, disassembly, refurbishing, and disposal sites is considered. An integrated two-phase model is given so that in the first phase, the proposed fuzzy-MOORA-reference point method is applied to suppliers’ assessment and the results from this phase is used in the second phase. In the second phase, a three-objective mixed integer linear programming model is proposed in order to determine the eligible suppliers, the locations of refurbishing sites and the material flows between the supply chain members. The objective functions are maximizing profit, suppliers’ evaluation and resiliency scores. Unsatisfied demand of customers is lost. The numerical results show the validity of the model and the role of stockout option in reaching better solutions based on the LP-Metric method.
supply chain management
Shaghayegh Vaziri; Farhad Etebari; Behnam Vahdani
Abstract
In this paper, we study a novel pickup and delivery problem called carrier collaboration (CC). This problem includes a set of heterogenous (refrigerated and general type) vehicles with specific capacities for serving perishable products to several pickup and delivery nodes. Each carrier can have reserved ...
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In this paper, we study a novel pickup and delivery problem called carrier collaboration (CC). This problem includes a set of heterogenous (refrigerated and general type) vehicles with specific capacities for serving perishable products to several pickup and delivery nodes. Each carrier can have reserved and selective requests which can be delivered before the products are corrupted. The fleet of vehicles must serve reserved requests, but the selective requests can be served or not. Products are corrupted at a constant rate and a rate of corrosion in general type vehicles is greater than referigrated type veicles and the cost of using general one is less than referegireted. For the mentioned features, we develop a nonlinear mathematical model. The purpose is to find routes to maximize profits and reduce costs while at the same time, enhance customer satisfaction which is dependent on the freshness of delivered products. A Gnetic Algorithm (GA) is proposed to solve this problem due to its NP-hard nature. In this study, Variable Neighborhood Search (VNS) method is developed for improving the quality of initial solutions. Several instances are generated at different scales to evaluate the algorithm performance by comparing the results of an exact optimal solution wih that of the proposed algorithm. The obtained results demonstrate the efficiency of the proposed algorithm in providing reasonable solutions within an acceptable computational time.
supply chain management
Mohammad ali Enayati shiraz; Seyed Abdollah Heydariyeh; Mohammad Ali Afshar kazemi
Abstract
Supply chain management can lead to a sustainable competitive advantage. The present study is in search of paper industry supply chain strategies with respect to supply chain dynamics and lean supply chain using dynamics in order to gain a competitive advantage in Iran Wood and Paper Industries Company ...
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Supply chain management can lead to a sustainable competitive advantage. The present study is in search of paper industry supply chain strategies with respect to supply chain dynamics and lean supply chain using dynamics in order to gain a competitive advantage in Iran Wood and Paper Industries Company (Chooka). For this purpose, first, using organizational data and decision makers' participation, the system dynamics model was designed and after validation, the model was simulated in a ten-year horizon. According to the behavior of target variables and model sensitivity analysis in the simulation horizon, policies in line with lean supply chain strategy and sustainable profitability strategy of Chooka business were designed and applied separately and in combination to the model. And analyzed. According to the findings of the model simulation, productivity promotion policies through the use of lean methods in internal processes, increasing the quality of paper products, increasing innovation in the production and supply of paper products, improving raw material supply management And strategic partnership with suppliers of raw materials, industrial waste management, waste and solid waste management and staff empowerment have been presented as the best combined policies of the supply chain strategy of Iran's wood and paper industries.
supply chain management
Maedeh Fasihi; Seyed Esmaeil Najafi; Reza Tavakkoli-Moghaddam; Mostafa Hahiaghaei-Keshteli
Abstract
The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development ...
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The supply chain management is an important factor in current competitive market. In recent years, the shortage of resources for answering an increasing food demand has increased researchers’ attention to the food supply chain. Given the importance of fish in the Household Food Basket, the development of aquaculture and recycling of returned goods in reverse logistics would significantly help with preserving water resources, as well as sustainable development. Therefore, government agencies and aquaculture industry beneficiaries are interested in reverse logistics. This study is focused on the optimization of a closed-loop supply chain of fish. To this end, a new bi-objective mathematical model is proposed that both minimizes total costs and maximizes fulfilling customers demand in uncertainty situation. Several well-known multi-objective meta-heuristic algorithms and a proposed hybrid meta-heuristic algorithm are applied to identify Pareto solutions. The solutions are then compared in terms of performance metrics. Also, the epsilon-constraint method and sensitivity analysis are used to validate the algorithms and evaluate the performance of the model. Lastly, the VIKOR method is used to select the superior method. To demonstrate the capability of the proposed model, a closed-loop supply chain of trout in northern Iran is investigated as a case study. The results show that the developed model could be effective in reducing the costs and increasing customer satisfaction.
