Showing 93 results for Supply Chain
Leila Rezaei, Reza Babazadeh,
Volume 33, Issue 4 (12-2022)
Abstract
The introduction of blockchain technology into the food supply chain represents a digital revolution that has led to widespread advances in tracking food security. This article presents a comprehensive review of the literature on the use of blockchain in the food supply chain. This article is a review of the synthesis evidence Best group. We have focused on the supply chains of meat, fruits and vegetables. The Literature review has been conducted from seven different databases. For more insight, we categorized meat, fruit, and vegetable articles into four groups: descriptive, prescriptive, conceptual, and predictive. Due to the small number of case studies in research, the theoretical and conceptual frameworks proposed in most food supply chain articles, including the supply chain of meat, fruits and vegetables, have been less tested in reality. These surveys and small-scale case studies do not clearly and completely identify the impact of blockchain on the meat, fruit and vegetable supply chain and the challenges that blockchain implementation may pose to these supply chains. Findings indicate that little valid and quality research has been done in this field and more research is needed on the use of blockchain in the supply chain of fresh products.
Seyed Mohamad Hamidzadeh, Mohsen Rezaei, Mehdi Ranjbar-Buorani,
Volume 33, Issue 4 (12-2022)
Abstract
In this paper, a closed-loop supply chain is modeled based on hyperchaotic dynamics. Then, synchronization of the two hyperchaotic closed loop supply chains is performed with a proportional integral (PI) sliding mode controller design method. Using Lyapunov stability theory, it has been proved that the PI sliding mode controller can converge the synchronization error to zero in a limited time. The most important issue in the design of control strategies is the behavior of the control signal. In other words, it affects the cost of design and implementation. Numerical simulation results show that the control signal has low amplitude and fluctuations. so, the PI sliding mode control method can be implemented in the real world. Based on the numerical simulation results, the use of two controllers is proposed to reduce design costs.
Fatemeh Hajisoltani, Mehdi Seifbarghy, Davar Pishva,
Volume 34, Issue 1 (3-2023)
Abstract
The main objective of this research is effective planning as well as greener production and distribution of mineral products in supply chain network. Through a case study in cement industry, it considers the design of the mining supply chain network including several factories with a number of production lines and multiple distribution centers. It leaves part of the transportation operation to contractor companies so as to enable the core company to better focus on its products’ quality and also create job opportunities to local people. It employs a multi-period and multi-product mixed integer linear programming model to both maximize the profit of the factory as well as minimize its carbon dioxide gas emissions which are released during cement production and transportation process. Due to the uncertainty of its cost parameters, fuzzy logic has been used for the modeling and solved via a novel fuzzy multi-choice goal programming approach. Sensitivity analysis has also been done on some key parameters. Comparing results of the model with those from the single-objective models, shows that the model has good efficiency and can be used by managers of mining industries such as cement. Although leaving part of the transportation operations to contractor companies increases the number of vehicles used by the contractor companies, its associated decrease in the number of required factory vehicles, improves both objectives of the model. This should be considered by the managers since on top of profit maximization, it can help them build an eco-friendly image. Mining industries generally generate significant amount of pollutions and companies that pay attention to different dimensions of their social responsibilities can remain stable in the competitive market.
Nur Afni Kutanga, Annisa Kesy Garside, Dana Marsetiya Utama,
Volume 34, Issue 1 (3-2023)
Abstract
Palm oil is a commodity whose demand continues to increase, requiring proper risk management in the supply chain. This study aims to develop a hybrid method that integrates probability impact matrix, analytical network process, and house of risk to mitigate strategies in the palm oil supply chain. The Probability Impact Matrix (PIM) method is used to map the priority risk agents and determine the occurrence value of the risk agents, and Analytical Network Process (ANP) is used to determine the severity value of the risk event. Furthermore, the House of Risk (HOR) is proposed to determine the priority of the mitigation strategy. The proposed method was applied in a case study on the palm oil supply chain in Indonesia. The research results show that ten priority risk agents and 6 mitigation strategies were obtained based on the proposed method to overcome risk agents in palm oil supply chain
Hamed Fazlollahtabar, Sepide Ebadi,
Volume 34, Issue 1 (3-2023)
Abstract
Providing skills training is an essential need of different societies. Considering the significance of the role of skill training in empowerment and employment of individuals through the training of skilled labor required by the labor market and industry, in this study the supply chain of skills training has been designed. In the proposed supply chain, according to the skill training aspects, a network structure is conceptualized to include appropriate factors in different layers of the supply chain. Evaluating the performance of the supply chain is handled applying a network data envelopment analysis. Network Data Envelopment Analysis (NDEA) is an efficient method analyzing all the factors included in the evaluation network. Among the NDEA models, the output-oriented BCC model was selected due to the importance of the output of the supply chains of the skills training. In addition to efficiency, the concept of complementary loss is also introduced to validate the results. The research findings show the efficiency of various factors in the stages of the designed network. On the other hand, unlike the classic DEA method, which shows the maximum efficiency of a factor, in the proposed network model, the efficiency priority is calculated and the efficiency is determined at each stage of the supply chain.
Harwati Harwati, Anna Maria Sri Asih, Bertha Maya Sopha,
Volume 34, Issue 3 (9-2023)
Abstract
In recent years, research on halal supply chain resilience (HSCRES) has been growing to deal with the vulnerabilities caused by halal risks that disrupt global halal supply chains. However, empirical studies in this field have been hindered by the lack of identifying halal capabilities that represent the strength of HSCRES. This study aimed to determine and prioritize halal resilience capability. In the first step, extant literature is reviewed to identify capability factors in the context of the halal supply chain. In the second step, the fuzzy analytical hierarchy process (FAHP) approach was used to rank the halal capability indicators. The results of this study indicate that halal integrity is the most important capability factor in enhancing a resilient halal supply chain. The results also reveal that mandatory regulation is the most significant indicator in HSCRES, followed by halal teams, official halal logos, internal halal audits, and communication channels. This finding offers stakeholder recommendations on which capabilities should be prioritized to reduce the impact of halal risks that disrupt supply chains’ resilience
Muhammad Asrol, Muchammad Arief, Hendra Gunawan,
Volume 34, Issue 3 (9-2023)
Abstract
The food industry's supply chain primarily relies on materials that are not environmentally friendly. To address this issue and improve overall performance, the implementation of Green Supply Chain Management (GSCM) becomes crucial. The objective of this research is to analyze the factors influencing the adoption of GSCM and its impact on the performance of the food industry, particularly in Indonesia where there is a high potential for waste production and environmental impact. The study targeted 83 food industry companies as respondents, achieving a response rate of 76.82%. The research employed a Partial Least Squares (PLS) and statistical analysis approach to test hypotheses regarding food industry performance. The findings indicate that GSCM does not directly affect food industry performance. However, GSCM has a positive influence on Green Innovation, which in turn has a positive impact on Company Performance. Green Innovation acts as a mediator between GSCM and Corporate Performance. The implementation of a GSCM at the food industry not only enhances environmental performance but also to improved economic performance. It is emphasized that renewable company innovations should be integrated alongside the adoption of green supply chains. The study highlights that the positive effects of the GSCM are more significant when mediated by green innovation.
Mehdi Seifbarghy, Mehri Nasrabadi,
Volume 34, Issue 3 (9-2023)
Abstract
One of the most key parts of a health system is the blood supply chain whose design is challenging due to the perishability of blood. In this research, an optimization model for multi-product blood supply chain network design is presented by considering blood deterioration. We consider a four-echelon blood supply chain that consists of blood donation centers, blood processing centers, blood products storage centers and hospitals as the user of the blood products. The locations of blood processing centers and blood products storage centers should be determined. Furthermore, considering different levels of technologies for blood processing, the suitable level for each opened center should be determined. In addition, different types of vehicle are also considered for blood transfer between different levels of the network. The objective is minimizing the total logistical costs including the costs of opening and running the blood processing centers and blood product storage centers and blood products transfer costs between different levels of the supply chain. Finally, we apply the given model to a real case study in Iranian blood supply chain, and sensitivity analysis is performed on some parameters. In the end, some managerial insights are given
Zohre Farmani, Gholamreza Nasiri, Gholamreza Zandesh,
Volume 34, Issue 3 (9-2023)
Abstract
Today, the use of electrical energy storage has a significant role in flatting the load curve, peak shaving, increasing reliability and also increasing the penetration of distributed generation, reducing carbon emissions, and reducing network losses. In this article, a three-echelon power supply chain is investigated considering energy storage as a new level in the power supply chain. The model in this article is an integrated model of locating and capacity planning of distributed energy storage with the aim of maximizing profit and reliability, which is modeled with two different approaches. The first model is modeled from the point of view of the distribution network as the owner of the energy storage and the second model is modeled from the perspective of the electricity subscribers as the owner of the energy storage. Finally, the model is solved by GAMS software and the results of sensitivity analysis are presented. According to the obtained results, the presented model is the most sensitive to the changes in demand and production, and the owners of energy storage should be sensitive to the changes in production and demand in different seasons of the year in order to get the maximum profit.
Ahmad Lotfi, Parvaneh Samouei,
Volume 34, Issue 3 (9-2023)
Abstract
As efficient instruments, there have been increasing studies on contract optimization in the supply chain field over the recent two decades. The lack of review papers is one of the gaps in contract optimization studies. Hence, the extant study aimed to provide researchers with an attitude to direct future studies on this topic. Therefore, the collected studies on contract optimization were reviewed and analyzed primarily. Then papers were classified based on the selected categories and themes. Finally, evaluation and results were presented based on the classified topics. They conducted studies, then achievements and limitations of the literature and future research opportunities were introduced to pave the way for researchers’ further studies.
Mohammad Reza Ghatreh Samani, Jafar Gheidar-Kheljani,
Volume 34, Issue 3 (9-2023)
Abstract
In this paper, a brief review of the recently developed blood supply chain (BSC) management studies is firstly presented. Then, a first-ever multi-objective robust BSC model is proposed, which is inspired by the need for an integrated approach towards improving the performance of BSC networks under uncertain conditions. The network efficiency by minimizing cost, adequacy by providing reliable and sufficient blood supply, and effectiveness by controlling blood freshness are aimed at the proposed model. A two-phase approach based on robust programming and an augmented epsilon-constraint method is devised to model the uncertainty in parameters and provides a single-objective counterpart of the original multi-objective robust model. We investigate a case to illustrate the real-world applicability of the problem. The research comes to an end by performing some sensitivity analyses on critical parameters, and the results imply the capability of the model and its solution technique.
Mahdi Rezaei, Ali Salmasnia, Mohammad Reza Maleki,
Volume 34, Issue 3 (9-2023)
Abstract
This article develops an integrated model of transmitting strategies and operational activities to enhance the efficiency of supply chain management. As the second objective, this paper aims to improve supply chain performance management (SCPM) by employing proper decision-making approaches. The proposed model optimizes the performance indicator based on SCOR metrics. A process-based method is utilized for high-level decisions, while a mathematical programming method is proposed for low-level decisions. The suggested operational model takes some major supply chain properties such as multiple suppliers, multiple plants, multiple materials, and multiple produced items over several time periods into account. To solve the operational multi-objective optimization model, a goal programming approach is applied. The computational results are explained in terms of a numerical example, and a sensitivity analysis is performed to investigate how the performance of the supply chain is influenced by strategic scenario planning.
Shahla Zandi, Reza Samizadeh, Maryam Esmaeili,
Volume 34, Issue 3 (9-2023)
Abstract
A coalition loyalty program (CLP) is a business strategy adopted by companies to increase and retain their customers. An operational challenge in this regard is to determine the coordination mechanism with business partners. This study investigated the role of revenue-sharing contracts (RSCs) considering customer satisfaction in coalition loyalty reward supply chain planning. A two-stage stochastic programming approach was considered for the solution considering the demand uncertainty. We aimed to investigate the impact of RSCs on the decision-making and profitability of the host firm of this supply chain taking into account the maximization of the profit coming from the CLP compared to the more common wholesale price contract (WPC). After the model was solved, computational experiments were performed to evaluate and compare the effects of RSCs and WPCs on the performance of the loyalty program (LP). The results revealed that RSC is an effective incentive to increase the host’s profit and reduce its cost. These findings add new insights to the management literature, which can be used by business decision makers.
Seyed Mahdi Aghazadeh, Hamid Farvaresh,
Volume 34, Issue 4 (12-2023)
Abstract
The growing online marketplace has opened a plethora of opportunities for businesses across various industries. Manufacturers, seeking to bypass intermediaries and directly reach end-users, have been increasingly adopting online sales channels in addition to their traditional retail sales. A key challenge, however, lies in determining optimal pricing strategies and advertising investments for both manufacturers and retailers while considering various constraints. This study contemplates a two-echelon supply chain model involving one manufacturer and two retailers. The manufacturer sells its product both through retailers (offline channel) and directly to consumers via an online channel. The model features both global and local advertising. The influence of global advertising is realized through distinct advertising channels, each with a unique impact on demand. To further motivate retailers, the manufacturer contributes to the cost of local advertising. In response to these challenges, this research formulates a bi-level model and employs the concept of Variational Inequalities to solve it. The model also contends with production capacity and budget constraints, leading to a Generalized Nash-Stackelberg game. The validity of the model and the efficacy of the solution method are assessed through numerical experiments performed. Finally, a set of valuable managerial insights are provided.
Simin Dargahi Darabad, Maryam Izadbakhsh, Seyed Farid Ghannadpour, Siamak Noori, Mohammad Mahdavi Mazdeh,
Volume 35, Issue 1 (3-2024)
Abstract
The construction supply chain is presently the focus of considerable interest among numerous project-related businesses. Strong project management is essential for the effective completion of a project, since restricted budgets and time constraints are considered for each project. The research uses multi-objective linear programming to create a mathematical model of the building supply chain. The primary aims of the present investigation are to limit the expenses associated with logistics and to diminish the release of greenhouse gases caused by transportation. Given the reality of managing several projects concurrently, the model provided comprises a network of projects. Following the completion of each project, an inspection is arranged to assess its level of success. Estimating the costs of a project relies on several variables. In reality, there are always uncertainties highlighted in several studies about the uncertainty of cost and time parameters. This research incorporates many characteristics concurrently to simulate real-world settings and address the issue of uncertainty. The expression of uncertainty for all costs, activity length, inspection, supplier capacity, and resource demand are represented by triangular fuzzy numbers. Ultimately, the precision of the model's performance has been verified using a numerical illustration.
Dian Dewi, Yustinus Hermanto, Martinus Sianto, Jaka Mulyana, Dian Trihastuti, Ivan Gunawan,
Volume 35, Issue 2 (6-2024)
Abstract
Supply chain agility (SCA) has emerged as a significant focus for industries and businesses, serving as a cornerstone for gaining a competitive edge and playing a pivotal role in supply chain management. This importance is further underscored in the context of Product–Service Systems (PSS), which involve the development of both products and services. Despite the existing body of research on SCA and PSS, there has been a notable dearth of empirical studies examining the readiness of PSS SCA. This study makes a substantial contribution by developing a valid and reliable framework to assess the readiness of PSS for supply chain agility. The process involves defining domains, generating items, analyzing agreement among raters, testing for response bias, and conducting exploratory and confirmatory factor analyses. Using structural equation modeling, the model's validity and reliability were evaluated through an online survey with 405 participants from official motorcycle service partners. The findings identify six key capability constructs: collaboration, knowledge transfer, service partner development, information sharing, logistic integration and supply chain agility. This examination of PSS SCA readiness and its constructs provides a validated tool for industry practitioners to enhance their supply chain agility.
Daniel Atnafu, Shimelis Zewdie Werke,
Volume 35, Issue 2 (6-2024)
Abstract
The incorporation of sustainable practices becomes crucial as firms transition from Industry 4.0 to Industry 5.0. Therefore, this systematic review explores the relationship between the two sustainability approaches; Green Human Resource Management (GHRM) and Green Supply Chain Management (GSCM) using peer-reviewed studies from 2016-2023, retrieved from Scopus and Web of Science databases. 2016 marks the starting point as the first relevant paper emerged in the literature in that year. The PRISMA approach was used to identify relevant studies, resulting in the inclusion of 30 studies for analysis purposes. The study reveals a growing interest in understanding the relationship between GHRM and GSCM practices and their impact on sustainable performance. The majority of reviewed studies utilized quantitative survey methods, suggesting the need for future research utilizing qualitative and mixed methods for gaining deeper insights. The review indicates that most studies are conducted in emerging countries, and there is a significant gap in research on the relationship between GHRM and GSCM practices in other context. Finally, the study provides valuable insights for practitioners and researchers, emphasising the importance of integrating GHRM and GSCM practices for a sustainable competitive advantage.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (6-2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (6-2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
Zahrasadat Hasheminasab, Esmaeil Mazroui Nasrabadi, Zahra Sadeqi-Arani,
Volume 35, Issue 3 (9-2024)
Abstract
In today’s world, supply chains must adopt new and intelligent technologies to achieve objectives such as enhancing productivity and performance, competitiveness, and overcoming challenges. The Internet of Things (IoT), as an emerging and transformative technology, is considered one of the most significant technology areas today and has garnered considerable attention across various industries. However, the implementation of IoT at the supply chain (SC) level faces numerous challenges and obstacles, and its acceptance at this level requires specific drivers. To date, no specific classification has been provided for drivers at the SC level, and existing classifications for challenges also need to be reviewed and updated. Given the importance of IoT in SC management, a systematic review at this level is necessary. This article provides a systematic literature review to identify and classify the challenges and drivers of IoT at the SC level. The study reviewed articles published from 2004 to 2023, ultimately identifying and categorizing 92 challenges into 16 categories: financial, standards and government regulations, privacy and security, energy consumption, health issues, hardware and software issues, culture in the SC, lack of knowledge and awareness, poor IT management, coordination in the SC, perception, the Challenge of uncertainty, lack of Plan and Strategy, incompatibility with existing technology, supply Problems, and user acceptance and trust in technology. Additionally, the study identified 4 antecedent drivers (pressures, understanding the benefits, government regulations, government incentives) and 10 consequent drivers (production benefits, improving competitive advantage, inventory management, cost management, improving transparency, efficiency of information flow, development of responsiveness and agility, sustainable development, facilitation of management, and development of cooperation and coordination). Finally, a model for implementing IoT technology in the SC is presented. This model synthesizes the findings from the literature review and offers a practical roadmap for organizations seeking to leverage IoT in their supply chains. By addressing the identified challenges and utilizing the drivers, organizations can effectively integrate IoT technology, thereby enhancing the efficiency, transparency, and overall performance of their SC operations.
