Azam Tariyan; Hessam ZandHessami; Abbas khamseh
Abstract
The construction industry has always had significant destructive effects on the environment. Utilizing green supply chain management strategies to achieve sustainable construction is an effective approach to reducing environmental damage. In this research, the qualitative approach and interpretive paradigm, ...
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The construction industry has always had significant destructive effects on the environment. Utilizing green supply chain management strategies to achieve sustainable construction is an effective approach to reducing environmental damage. In this research, the qualitative approach and interpretive paradigm, along with the seven-step meta-synthesis method, were employed to explain the influential components in establishing green supply chain management in the construction industry. A total of 728 relevant studies in the field of supply chain management, particularly with a focus on sustainability, green practices, and reverse logistics, were identified, reviewed, evaluated, and screened. Based on the entry and exit protocol, 37 studies were included in the research portfolio, resulting in the extraction of 73 primary codes that were categorized into 13 concepts and 4 categories. The reliability of the classification was confirmed using the Kappa coefficient. The research findings revealed that the components influencing green supply chain management were identified across four main categories: main factors of green supply chain management, facilitating factors, internal and external drivers and barriers. Finally, suggestions based on the extracted results from this research were presented for future researchers. IntroductionThe construction industry is the primary consumer of resources and energy worldwide and has significant detrimental effects on the environment. Environmental protection and sustainability have become global concerns across various industries in the past two decades. Companies and governments in many countries are recognizing the importance of green supply chains, and this awareness is rapidly growing within the construction industry. Currently, competition between companies has shifted towards competition between their supply chains. Therefore, expanding the concept of sustainability in supply chain management is considered a strategy to enhance performance and improve a company's competitiveness. Green supply chain management is highly regarded among academics and industry professionals as it aims to preserve product quality, conserve resources, and minimize production waste. In the construction industry, green supply chain management involves managing all activities throughout the supply chain that contribute to the final product (building) to minimize environmental impacts. Hence, a holistic approach is required to manage all construction project activities and ensure sustainability across social, economic, and environmental dimensions. While extensive studies have been conducted on green supply chain management in various industries, the number of studies in the construction industry is relatively limited and fragmented, lacking a cohesive understanding of scientific findings in this field. To address this research gap and considering the importance of the topic and the lack of a comprehensive method in this field, the current research aims to present a model and identify the factors influencing green supply chain management in the construction industry, particularly in Iran. Materials and MethodsAccording to the nature of the research, the current study adopts a meta-synthesis approach, which is qualitative in nature with an interpretive paradigm. Meta-synthesis is a type of systematic qualitative approach that combines and integrates qualitative findings from different but related studies. By providing a systematic perspective to researchers, meta-synthesis allows for the discovery of new and fundamental themes and insights by synthesizing various qualitative studies. This approach enhances the existing knowledge and provides a broader understanding of the issues at hand. The seven-step method developed by Sandelowski has been employed to conduct the meta-synthesis. The data collected for this research have been coded and summarized using content analysis with the assistance of the MAXQDA qualitative data analysis software.ConclusionsThis research aimed to identify the factors influencing green supply chain management in the construction industry. After conducting keyword searches, the identified documents were screened and evaluated, resulting in a set of documents that were coded and summarized using content analysis. These codes were then evaluated by experts. The findings were categorized and presented in a table, and a visual model was proposed for better comprehension. The research findings revealed four categories of factors influencing green supply chain management: main factors, facilitating factors, internal and external drivers, and barriers. The main factors identified in this research include green purchasing, green design, green construction, and reverse logistics. Facilitating factors include human resource management, green technology, internal environmental management, and green marketing. Additionally, the research identified important drivers and barriers for the implementation of green supply chain management. Internal drivers include the desire to enhance reputation, credibility, and business image; cost reduction; the desire to enter foreign markets; and societal pressure
quality management
amir mohammad khani; Abolfazl Kazzazi; Soraya birami
Abstract
The aim of this study was to investigate the relationship between comprehensive productive maintenance, TQM, supply chain management, learning organization characteristics and operational performance. In order to conduct research operations, the conceptual framework of the research was first presented ...
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The aim of this study was to investigate the relationship between comprehensive productive maintenance, TQM, supply chain management, learning organization characteristics and operational performance. In order to conduct research operations, the conceptual framework of the research was first presented by studying the theoretical foundations. In the next stage, by compiling and distributing a questionnaire among 180 people from the statistical population of the research consisting of senior, middle and operational managers aware of the subject under study, export companies of Golestan province were distributed randomly, the information needed to test research hypotheses was collected. Finally, 146 completed return questionnaires were covered by the structural equation modeling technique based on the partial least squares method. The results obtained based on this technique showed that the maintenance and repair of comprehensive productivity has a positive effect on total quality management, while the maintenance and repair of comprehensive productivity alone could not achieve an acceptable result to achieve operational performance and requires comprehensive quality management. . Another result obtained indicates the positive effect of total quality management and supply chain management and the mediating role of supply chain management in achieving operational performance between the two variables of total quality management and operational performance. In addition to these results, it was found that total quality management has a positive effect on the learning organization and the learning organization has an important role between total quality management and operational performance of export companies in Golestan province.
Mahdi Haghighi Kaffash; Zhre Dehdashtishahrokh; Vahid Khashei; Reza Hajari
Abstract
This study is conducted to identify and analysis the relationship between the factors affecting the distribution network design (DND) in the food distribution industry in Iran. In this paper, the distribution network design has been classified into two main areas of the strategic structure of the distribution ...
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This study is conducted to identify and analysis the relationship between the factors affecting the distribution network design (DND) in the food distribution industry in Iran. In this paper, the distribution network design has been classified into two main areas of the strategic structure of the distribution network and the distribution management policies and the impact of the key variables on distribution network design has been investigated. This study is descriptive, exploratory and using quantitative research method. The statistical population of this research is all 54 food distribution companies in Iran. Using a census method, a questionnaire was sent to all general and marketing managers of these companies (108 people). 92 questionnaires were completed, according to the established criteria, only 81 questionnaires could be used, which also covers the standards of Cochran formula. The partial least squares (PLS) method is used to analyze the data and the results show that product characteristics, service requirements, demand characteristics, supply characteristics, and economic variables are the key variables that affect the distribution network design. Given the lack of research on the distribution network design and the study of the factors affecting the formation of strategic distribution structures and policies, it can be argued that this article provides valuable insights for academics and professionals, because in many studies the various components of distribution network design, the decisions related to the design of the distribution network and the analysis of the main factors affecting the distribution network structure are presented
Mehdi Seifbarghy; Shima Zangeneh
Abstract
In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. ...
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In the classic models of facility location, it is assumed that the selected facilities always work based on the schedule while, in the real world, facilities are always exposed to disruption risk and sometimes these disruptions have long-term effects on the supply chain network and cause a lot of problems. In this paper, a mixed integer programing (MIP) model presented in order to determine how to serve the customers at the time of disruption in distribution centers in a two-echelon supply chain, including distribution centers and customers. This model selects potential places that minimize traditionally supply chain costs and also the transportation cost after distribution centers disruptions. In fact, the model tries to choose the distribution centers facilities with lowest cost and highest reliability and also allocate them to customers. The problem divided into two sub-problems using Lagrangian relaxation approach. By examining sub-problems optimal conditions, a heuristic solution is used for the first sub-problem and a genetic algorithm is used for the second sub-problem to solve large-scale problems. Finally, numerical examples are presented to examine the performance and efficiency of the proposed model and approach
Parham Azimi; Farzaneh Goldar; Esmaeil Mehdizadeh
Volume 13, Issue 36 , April 2015, , Pages 115-142
Abstract
Supply chain management (SCM) is one of the most important competitive strategies used by modern companies. The main goal of supply chain management is integration different suppliers to fulfill market demand. Therefore, evaluation and selection of suppliers has critical role and significant effect on ...
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Supply chain management (SCM) is one of the most important competitive strategies used by modern companies. The main goal of supply chain management is integration different suppliers to fulfill market demand. Therefore, evaluation and selection of suppliers has critical role and significant effect on supply chain management. This paper presents hybrid model based on clustering approach and suppliers' selection. At first, K-harmonic means clustering method which is one of the most popular methods in clustering analysis is used for clustering suppliers. Then, according to theoutput of clustering, a multi-objective model is considered to select the best supplier. Since the model belongs to the class of NP-hard optimization problems, two meta-heuristic algorithms named Non-dominated Sorting Genetic Algorithm (NSGAII) and Non-dominated Ranked Genetic Algorithm (NRGA) is used for solving model in reasonable time. Computational results show that the clustering analysis can be considered as an effective way to the suppliers' selection. Also, several data sets are applied to evaluate the effect of clustering analysis on suppliers' selection
Ali Mohtashami; Ali Fallahian-Najafabadi
Volume 11, Issue 31 , January 2014, , Pages 55-84
Abstract
In today’s competitive world, the organizations decide to establish competitive benefits by making benefit from management sciences. One of the most important management sciences arisen lots of so useful matters is the supply chain. The supply chain management is the evolved result of warehousing ...
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In today’s competitive world, the organizations decide to establish competitive benefits by making benefit from management sciences. One of the most important management sciences arisen lots of so useful matters is the supply chain. The supply chain management is the evolved result of warehousing management and is regarded as one of the infrastructure and important concepts for implementing the career so that in many of them it is essentially tried to shorten the time between the customer’s order and the real time of delivering the goods. Cross docking is one of the most important alternatives for lowering the time in supply chain. The central aim of this paper is to focus on optimizing the planning of the trucks input and output aiming to minimize total time of operation inside the supply chain in designed model. Timing the transportation in this paper makes the time between sources and destinations, time of unloading and transferring the products minimized. To find the optimum answers to the question, genetic algorithms and the particle swarm optimization have been used. Then, these algorithms have been compared with the standards such as the implementation time and quality of answers with each other and then better algorithms in each standard identified.
Haidar Mirfakhroddini; Davood Andalib Ardakani; Morteza Rezaei Asl
Volume 8, Issue 21 , June 2011, , Pages 107-130
Abstract
Supply chain is a network of independent organizations that cooperate with each other, in order to control, manage and improve material and information flow from suppliers to final consumers to meet customer satisfaction. In Industry, especially industries that are moving towards the longer supply chain, ...
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Supply chain is a network of independent organizations that cooperate with each other, in order to control, manage and improve material and information flow from suppliers to final consumers to meet customer satisfaction. In Industry, especially industries that are moving towards the longer supply chain, the issue of supply chain risk management is important.
The risk management process focuses on the identification of risks and reduction of theirs adverse effects. Risk management process in supply chain includes four-phase identification, assessment, control or management and tracking of risky events. The aim of risk assessment is risk measurement based on various attributes. A key part of this process is risk rating; in this article first, with study of multi criteria decision making, it was tried to recognize the appropriate model for ranking of risk factors in order to determine their priority and allocate resources to deal with each of them. More, the field of information technology in small and medium enterprises was studied and after recognizing of risk factors of field of information technology in small and medium enterprises, Electre, Topsis and Taxonomy techniques to rank these factors were used.
More and also with calculating the Spearman correlation coefficient for detecting convergence of ratings, using the mean method, the final ranking risk factors in the supply chain field were acquired.
Mostafa Ekhtiari
Volume 8, Issue 18 , September 2010, , Pages 123-160
Abstract
In this paper, a single-product three-echelon supply chain with the loops of manufactures-distributors-customers has been considered where the customers demand, the percent of rejected product from customers and the shipping time of product from distributors to customers are considered as fuzzy variables. ...
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In this paper, a single-product three-echelon supply chain with the loops of manufactures-distributors-customers has been considered where the customers demand, the percent of rejected product from customers and the shipping time of product from distributors to customers are considered as fuzzy variables. The main approach in this paper is simultaneously consideration of suppliers and distributors selection problems and to determine effective customers in the system under uncertainty. The purpose of this paper is to present a model which aggregates conflicting objectives between loops of this chain, increases the number of uncertainty parameters of the model as well. Hence, the objectives of the proposed model are: to maximize quality of products, to minimize total cost, to minimize product shipping time from distributors to customers and to maximize obtained earning from product selling to customers. Also in the proposed model, some constraints are considered such as the orders shortage, the production capacity and demand of customers. The proposed model will be illustrated by a numerical example for the three-echelon supply chain problem and will be analyzed based on a-cut levels.
