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.
Vahid Hajipour; Sina Salimian
Abstract
Given the increase of natural disasters, the community's need for health services has increased dramatically. Firstly, the condition of the injured people should be determined and then the treatment should be start, and in the event of increasing in the severity of the injured, these people should be ...
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Given the increase of natural disasters, the community's need for health services has increased dramatically. Firstly, the condition of the injured people should be determined and then the treatment should be start, and in the event of increasing in the severity of the injured, these people should be transfer to the hospitals in the shortest possible time. On the other hand, another essential measure at the time of the accident is to send medicines and medical items at the appropriate time for treatment of injured. In this regard, we follow to design an emergency relief supply chain network including suppliers of medical items, treatment center, warehouses, and disaster points. Therefore, a location and inventory mathematical modeling is proposed to provide better services with the goal of minimizing the costs associated with locating and inventory of health systems. Thenو, to analyze and optimize the problem, proposed some numerical example and genetic algorithm.
Maryam Azizi; Abolfazl Kazemi; Alireza Alinezhad
Abstract
Reverse logistics as a new approach and attitude in the area of logistics is one of the new trends in logistics management, recycling, and or reuse of products. Logistics network design in the forward and reverse mode is one of the most important issues that forms the strategic dimension of supply chain ...
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Reverse logistics as a new approach and attitude in the area of logistics is one of the new trends in logistics management, recycling, and or reuse of products. Logistics network design in the forward and reverse mode is one of the most important issues that forms the strategic dimension of supply chain design. In this paper we propose a mixed integer linear programming (MILP) model for reverse logistics problem. In the proposed model costs of facilities construction, transportation and procurement from suppliers are minimized and importance of suppliers are maximized. Since the proposed model is NP-hard, we use NSGA-II and NRGA algorithms to solve the problem.
Adel Azar; Mahdi Abedini Naeini; Amir Afsar; Mohammad Sabet Motlagh
Volume 14, Issue 42 , October 2016, , Pages 1-30
Abstract
Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan ...
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Supplier selection and quota allocation is an important decision in supplychains. This decision can be considered as a complex multi-criteria groupdecision making problem. This decision in many practical situations is verydifficult for vague and uncertain environment. This vagueness and uncertaintycan be handled by using fuzzy set theory. Therefore, this paper proposed afuzzy MCDM model to evaluate candidate suppliers and quota allocation. Ahybrid ANP-VIKOR method in fuzzy environment applied first with 16criteria to evaluate suppliers. Then, a fuzzy multi-objective mathematicalmodel is used to quota allocation. Finally, the fuzzy model is solved by Tiwarimethod. An illustration with a data set from a realistic situation is presented todemonstrate the effectiveness of the proposed model.
Mohammad Hoseyn Karimi; Nima Esfandiari; Mahmoud Moradi
Volume 13, Issue 39 , January 2016, , Pages 145-170
Abstract
Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order ...
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Many companies are pursuing agile manufacturing in order to reduce costs, improve customer service and attaining competitive advantage. After reviewing theoretical background and literature on agility, this paper presents agility attributes, criteria and enablers. Then a framework developed in order to prioritize and analyze agility indices with considering major competitive advantage. Hybrid Fuzzy Quality Function Deployment (FQFD) and Gap Analysis (GA) approach used to prioritize indices based on experts in an organization. Findings point out that “manufacturing management agility” has lowest maturity among agility enablers that lead this enabler to takes maximum importance. Furthermore, “manufacturing management agility” obtained most weight by FQFD, meaning this enabler has maximum priority and importance for organization. Interestingly, “knowledge management criterion” got first priority among all criteria by regarding maximum gap in gap analysis approach
