Showing 109 results for Supply
Shereen Abdelaziz, Munjiati Munawaroh,
Volume 0, Issue 0 (10-2025)
Abstract
This study investigates the intersection of sustainable logistics and supply chain resilience, emphasizing their role in mitigating global disruptions such as natural disasters, pandemics, and geopolitical tensions. It identifies key trends, critical gaps, and actionable insights to guide the development of robust, adaptable, and sustainable supply chains. A bibliometric analysis of 480 scholarly works systematically maps the academic landscape, uncovering key themes, emerging trends, and knowledge gaps. The analysis focuses on sustainable logistics practices, such as green logistics, circular economy principles, and reverse logistics, alongside digital transformation technologies, including IoT, blockchain, and predictive analytics, to assess their integration into resilience strategies. The analysis reveals a fragmented approach to integrating sustainability and resilience, with practices often treated in isolation. Sustainable logistics practices enhance resource efficiency and adaptability but are constrained by the lack of holistic frameworks that integrate diverse sustainability practices with resilience strategies. While environmental dimensions and digital technologies, such as IoT and blockchain, are recognized as critical enablers, social and governance dimensions remain underexplored. Adoption disparities further hinder progress, particularly among SMEs, resource-constrained sectors, and underrepresented regions like Africa and South Asia. Inclusive frameworks, sector-specific applications, and empirical research—incorporating mixed methods, longitudinal studies, and real-world case studies—are essential to address these gaps and operationalize sustainability-resilience integration across diverse contexts. This research bridges a critical gap in the literature by presenting a comprehensive bibliometric analysis of sustainable logistics and supply chain resilience, emphasizing holistic, sector-specific, and integrative frameworks and highlighting the transformative role of digital technologies in achieving operational and strategic resilience.
Zahwa Fitria Gumilang, Rakhmat Ceha, Vera Septiawati,
Volume 0, Issue 0 (10-2025)
Abstract
The imperative to align supply chains with sustainability objectives has intensified interest in the technological dimensions of sustainable supply chain management (SSCM). To provide a systematic overview of how this research area has evolved, this study conducts a bibliometric analysis of publications from 2005 to 2025, drawing on data from Scopus and Web of Science (WoS). The results demonstrate that technologies such as blockchain, artificial intelligence, big data analytics, and the Internet of Things have received the most attention, shaping the trajectory of SSCM research. Publication and citation trends show exponential growth after 2016, reflecting both global policy shifts and accelerated digital adoption during the COVID-19 pandemic. The United Kingdom and China lead in research output, while the United States demonstrates high citation impact. Several highly cited publications serve as intellectual anchors, shaping theoretical and methodological development. Keyword analysis and bibliographic coupling further reveal five dominant knowledge clusters: digital transformation for SSCM, life cycle thinking, policy in SSCM, blockchain for food sustainability, and sustainable product design. Overall, the study highlights technological trajectories, underexplored research areas, and regional disparities, providing theoretical and practical guidance for future interdisciplinary research, policy design, and technology adoption aimed at advancing sustainable and resilient supply chains.
Vembri Noor Helia, Anna Maria Sri Asih, Nur Mayke Eka Normasari, Elisa Kusrini,
Volume 0, Issue 0 (10-2025)
Abstract
The development of literature reviews on Supply Chain Performance Measurement Systems (SCPMS) has been extensive. However, studies focusing on the roles of various actors within the supply chain, as well as research covering the period beyond 2020, remain limited. Therefore, we conducted a study to explore the evolution of SCPMS using the Scopus and Web of Science databases, covering the years 2004 to 2024. We began by identifying the limitations of previous literature reviews. Subsequently, we performed a systematic literature review of academic articles published in internationally accredited journals, primarily within the domains of supply chain management and performance measurement. The final sample consisted of 78 articles. The findings reveal publication trends over time and provide insights into the evolution and research opportunities of SCPMS. The evolution of SCPMS over the past two decades reflects a significant transformation driven by shifts in the global business environment, advancements in technology, and the growing emphasis on sustainability and resilience. The research opportunities are categorized into nine key areas. These include the comprehensive SCPMS framework, dynamic evaluation, generalization of SCPMS models, the integration of green, sustainability, and circular economy principles into SCPMS, the analytical methods, and the development of specialized metrics.
Maria Moghadam, Iraj Mahdavi, Ali Tajdin, Babak Shirazi,
Volume 0, Issue 0 (10-2025)
Abstract
Addressing the complex challenges of supply chain management requires integrating sustainable practices, advanced technologies, and innovative solutions. This review article explores the concept of sustainable closed-loop supply chains as a means to balance economic, social, and environmental goals. We examine the relationship between sustainable closed-loop supply chains and advanced technologies such as artificial intelligence, machine learning, game theory, and metaheuristic algorithms. Various aspects of supply chain models, sustainability, and the integration of innovative solutions are analyzed to identify key challenges and opportunities in the implementation of sustainable closed-loop supply chains. We highlight the potential benefits of adopting such practices, including cost savings, enhanced brand reputation, and increased customer loyalty. The article also discusses the importance of managing risks associated with cost, environment, social issues, and operations. Our review emphasizes the need for ongoing research and collaboration among stakeholders to address existing research gaps and foster a comprehensive understanding of sustainable closed-loop supply chains. This includes empirical studies on real-world implementation, advanced optimization techniques, sustainable business models, and policy frameworks. Ultimately, this article aims to contribute to the development of more resilient, efficient, and sustainable supply chains that benefit businesses and society alike.
A. Amid, S.h. Ghodsypour,
Volume 19, Issue 4 (12-2008)
Abstract
Supplier selection is one of the most important activities of purchasing departments. This importance is increased even more by new strategies in a supply chain, because of the key role suppliers perform in terms of quality, costs and services which affect the outcome in the buyer’s company. Supplier selection is a multiple criteria decision making problem in which the objectives are not equally important. In practice, vagueness and imprecision of the goals, constraints and parameters in this problem make the decision making complicated. Simultaneously, in this model, vagueness of input data and varying importance of criteria are considered. In real cases, where Decision- Makers (DMs) face up to uncertain data and situations, the proposed model can help DMs to find out the appropriate ordering from each supplier, and allows purchasing manager(s) to manage supply chain performance on cost, quality, on time delivery, etc. An additive weighted model is presented for fuzzy multi objective supplier selection problem with fuzzy weights. The model is explained by an illustrative example.
S.k. Charsoghi, A. Sadeghi,
Volume 19, Issue 4 (12-2008)
Abstract
In this paper, a two-echelon supply chain, which includes two products based on the following considerations, has been studied and the bullwhip effect is quantified. Providing a measure for bullwhip effect that enables us to analyze and reduce this phenomenon in supply chains with two products is the basic purpose of this paper. Demand of products is presented by the first order vector autoregressive time series and ordering system is established according to order up to policy. Moreover, lead-time demand forecasting is based on moving average method because this forecasting method is used widely in real world. Based on these assumptions, a general equation for bullwhip effect measure is derived and there is a discussion about non-existence of an explicit expression for bullwhip effect measure according to the present approach on the bullwhip effect measure. However, bullwhip effect equation is presented for some limited cases. Finally, bullwhip effect in a two-product supply chain is analyzed by a numerical example.
H. Teimory, H. Mirzahosseinian, A. Kaboli,
Volume 19, Issue 4 (12-2008)
Abstract
The advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. In this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. The system receives stochastic demand from the both channel which each channel has an independent demand arrival rate. A lost-sales model which no backorder is allowed is supposed. The replenishment lead times are assumed independent exponential random variables for both warehouse and the retail store. Under the replenishment inventory policy, the inventory position is kept constant at a base-stock level. To analyze the chain performance, an objective function included holding and lost sales costs is defined. At the end, a proposed algorithm named, Best Neighborhood (BN) is used to find a good solution for inventory and the results are compared with Simulated Annealing (SA) solutions.
J. Jassbi, S.m. Seyedhosseini , N. Pilevari,
Volume 20, Issue 4 (4-2010)
Abstract
Nowadays, in turbulent and violate global markets, agility has been considered as a fundamental characteristic of a supply chain needed for survival. To achieve the competitive edge, companies must align with suppliers and customers to streamline operations, as well as agility beyond individual companies. Consequently Agile Supply Chain (ASC) is considered as a dominant competitive advantage. However, so far a little effort has been made for designing, operating and evaluating agile supply chain in recent years. Therefore, in this study a new approach has been developed based on Adaptive Neuro Fuzzy Inference System (ANFIS) for evaluating agility in supply chain considering agility capabilities such as Flexibility, Competency, Cost, Responsiveness and Quickness. This evaluation helps managers to perform gap analysis between existent agility level and the desired one and also provides more informative and reliable information for decision making. Finally the proposed model has been applied to a leading car manufacturing company in Iran to prove the applicability of the model.
F. Bagheri , M. J. Tarokh,
Volume 21, Issue 1 (6-2010)
Abstract
Assessment and selection of suppliers are two most important tasks in the purchasing part in supply chain management. Supplier selection can be considered to be a single or multi-objective problem. From another point of view, it can be a single or multi-sourcing problem. In this paper, an integrated AHP and Fuzzy TOPSIS model is proposed to solve the supplier selection problem. This model makes the decision-maker to be able to solve this problem with different criteria and different weight for each criterion with respect to the purchasing strategy. Finally, the proposed model is illustrated by an example.
Mohammad Najafi Nobar, Mostafa Setak,
Volume 21, Issue 1 (6-2010)
Abstract
In nowadays world competitive market, on account of the development of electronic media and its influence on shortening distances, companies require some core competencies in order to be able to compete with numerous competitors in industry and sustain their situation in such a market. In addition companies achieve this target are those which their processes perform great and exploit from competitive price, quality, guarantee, etc. Since some parameters such as price and quality are so dependent on the performance of company supply chain management, so the results can highly impress the final price and quality of products. One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article two layers of suppliers have been considered as a chain of suppliers. First layer suppliers are evaluated by two groups of criteria which the first one encompasses criteria belongs to first layer suppliers features and the second group contains criteria belong to the characteristics of second layer suppliers. One of the criteria is the performance of second layer suppliers against environmental issues. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second layer suppliers features as a criteria for selecting the best supplier.
Jafar Mahmodi , Mohamad Hosein Minaee,
Volume 21, Issue 3 (9-2010)
Abstract
Steel market and particularly rod bar market play important roles in economy of countries. Economic systems are considered as complex systems which are sophisticated to be modeled mathematically. One way to model these systems is simulation and use of system dynamics. This paper models rod bar supply chain in Iran using system dynamics. Data of this research is gathered from first hand materials published by governmental sector. In order to modeling relationships between variables, interviews were conducted with experts in Iran Ministry of Commerce. Proposed model explains turbulence of rod bar market during 5 years ago and the fluctuations of its price. In addition, it is examined and confirmed by experts of this market in Iran Ministry of Commerce. Although proposed model may not offer an exact prediction of future market, but could be used as an applicable tool for analyzing and adjusting the market in Iran Ministry of Commerce .
Rasoul Haji, Mohammadmohsen Moarefdoost, Seyed Babak Ebrahimi,
Volume 21, Issue 4 (12-2010)
Abstract
This paper aims to evaluate inventory cost of a Two-echelon serial supply chain system under vendor managed inventory program with stochastic demand, and examine the effect of environmental factors on the cost of overall system. For this purpose, we consider a two-echelon serial supply chain with a manufacturer and a retailer. Under Vendor managed inventory program, the decision on inventory levels are made by manufacturer centrally. In this paper, we assume that the manufacturer monitors inventory levels at the retailer location and replenishes retailer's stock under (r, n, q) policy moreover, the manufacturer follows make-to-order strategy in order to respond retailer's orders. In the other word, when the inventory position at the retailer reaches reorder point, r, the manufacturer initiates production of Q=nq units with finite production rate, p. The manufacturer replenishes the retailer's stock with replenishment frequency n, and the complete batch of q units to the retailer during the production time. We develop a renewal reward model for the case of Poisson demand, and drive the mathematical formula of the long run average total inventory cost of system under VMI. Then, by using Monte Carlo simulation, we examine the effect of environmental factors on the cost of overall system under VMI .
M. S Jabalameli, B. Bankian Tabrizi, M. Moshref Javadi ,
Volume 21, Issue 4 (12-2010)
Abstract
The problem of locating distribution centers (DCs) is one of the most important issues in design of supply chain. In previous researches on this problem, each DC could supply products for all of the customers. But in many real word problems, DCs can only supply products for customers who are in a certain distance from the facility, coverage radius. Thus, in this paper a multi-objective integer linear programming (MOILP) model is proposed to locate DCs in a two-echelon distribution system. In this problem, customers who are in the coverage radius of the DCs can be supplied. Moreover, we suppose that the coverage radius of each DC can be controlled by decision maker and it is a function of the amount of money invested on the DC. Finally, a random generated problem is used to verify the model and the computational results are presented .
E. Teimoury, H. Ansari , M. Fathi ,
Volume 22, Issue 1 (3-2011)
Abstract
The importance of reliable supply is increasing with supply chain network extension and just-in-time (JIT) production. Just in time implications motivate manufacturers towards single sourcing, which often involves problems with unreliable suppliers. If a single and reliable vendor is not available, manufacturer can split the order among the vendors in order to simultaneously decrease the supply chain uncertainty and increase supply reliability. In this paper we discuss with the aim of minimizing the shortage cost how we can split orders among suppliers with different lead times. The (s,S) policy is the basis of our inventory control system and for analyzing the system performance we use the fuzzy queuing methodology. After applying the model for the case study (SAPCO), the result of the developed model will be compared in the single and multiple cases and finally we will find that order splitting in optimized condition will conclude in the least supply risk and minimized shortage cost in comparison to other cases .
F Etebari, M. Abedzadeh , F. Khoshalhan,
Volume 22, Issue 1 (3-2011)
Abstract
Improvement in supply chain performance is one of the major issues in the current world. Lack of coordination in the supply chain is the main drawback of supply chain that many researchers have proposed different methodologies to overcome it. VMI (Vendor-managed inventory) is one of these methodologies that implementing it has some obstacles. This paper proposes new model that is agent-managed SC. This paper is trying to use intelligent agent technology in the supply chain. In this paper supply chain assessment performance measure indicators have been divided into three categories cost, flexibility and customer responsiveness indicators. In the first category we use holding and backordered inventory costs, for second category, bullwhip effect are used and for the last one customer responsiveness indicator has been applied. Bullwhip effect is one of the main phenomena’s that has been tried to reduce it with the agent-based systems.
Behin Elahi, Seyed Mohammad Seyed-Hosseini, Ahmad Makui,
Volume 22, Issue 2 (6-2011)
Abstract
Supplier selection, Multi-objective decision making, Fuzzy Compromise programming, Supply chain management, Quantity discount . |
Supplier selection is naturally a complex multi-objective problem including both quantitative and qualitative factors. This paper deals with this issue from a new view point. A quantity discount situation, which plays a role of motivator for buyer, is considered. Moreover, in order to find a reasonable compromise solution for this problem, at first a multi-objective modeling is presented. Then a proposed fuzzy compromise programming is utilized to determine marginal utility function for each criterion. Also, group decision makers’ preferences have taken into account and the weight of each criterion has been measured by forming pair-wise comparison matrixes. Finally the proposed approach is conducted for a numerical example and its efficacy and efficiency are verified via this section. The results indicate that the proposed method expedites the generation of compromise solution .
M. Miranbeigi, A.a. Jalali, A. Miranbeigi ,
Volume 22, Issue 3 (9-2011)
Abstract
supply chain network receding horizon control demand move suppression term |
Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system , we added a move suppression term to cost function .
M Karbasian, M Bashiri, M Safaei,
Volume 22, Issue 3 (9-2011)
Abstract
Strategic programming, Complex supply chain, Lean, Production programming, Suppliers selection, ELECTRE |
This paper represents a model of strategic programming with limited resources in a complex supply chain. The main goal of the proposed model is to increase efficiency and effectiveness of the supply chain with respect to income increases and cost decreases. Using special objective functions, has guaranteed the lean supply, production, distribution and suppliers' selection strategies. Furthermore, it can use for production programming in the supply chain. Moreover, customer satisfaction has also been perceived, by using minimization objective functions of shortage amount and restrictions of maximum allowed shortage. In this model, objective functions have been defined in a way, which directs the supply chain to the lean. Finally, after determining strategies according to objective functions and constraints, the optimal strategies using multi-criteria decision making - ELECTRE process- have been chosen .
Maghsoud Amiri, Mehdi Seif Barghy, Laaya Olfat, Seyed Hossein Razavi Hajiagha ,
Volume 23, Issue 1 (3-2012)
Abstract
Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumers' demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.
, , ,
Volume 23, Issue 2 (6-2012)
Abstract
Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then, the stochastic counterpart of the proposed MILP model is used to measure the conditional value at risk (CVaR) criterion, as a risk measure, that can control the risk level of the proposed model. The computational results show the power of the proposed stochastic model with CVaR criteria in handling data uncertainty and controlling risk levels.
