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.
Yuvaraj M, Jothi Basu,
Volume 35, Issue 3 (9-2024)
Abstract
Refrigerated trucks in the cold chain enhance the shelf-life of food. In the fruit supply chain (FSC), if each different fruit necessitates its dedicated fleet of refrigerated vehicles, the total cost of the supply chain would increase. On the other hand, if there are several fruits in a single compartment, the quality and freshness of the fruits will be impacted since each fruit requires a different operating temperature. Therefore, partitions are necessary within the container. While the use of cold chain infrastructure will result in a reduction in food loss and an enhancement in food security, it will also incur an increase in the overall cost of the supply chain. Therefore, this paper aims to create a mixed integer non-linear programming (MINLP) mathematical model considering multi-compartment reefer trucks (MCRTs) to minimize the total cost in the FSC. To assess the efficiency of the model, a case study is carried out in India, and the formulated mathematical model is solved using a heuristic approach. The findings indicate that utilizing MCRTs leads to a reduction in the number of vehicles required and a drop in total supply chain cost. Three-compartment reefer trucks offer a more significant cost-saving advantage in the FSC compared to two-compartment reefer trucks. Furthermore, it is noted that operating three distribution centers (DCs) results in a reduction in the overall cost. The decrease in total supply chain costs enhances the affordability of fruits for low-income populations and contributes to the enhancement of food security. In addition to cost reduction, implementing MCRT has also beneficial environmental impacts such as decreased emissions due to a decrease in the number of trucks utilized and reduced food waste.
Sina Nayeri, Mahla Zhain Vamarzani, Zeinab Asadi, Zeinab Sazvar, Nikbakhsh Javadian,
Volume 35, Issue 3 (9-2024)
Abstract
This study focuses on evaluating potential raw material providers (RMPs) as one of the critical tasks of the logistics managers. In this regard, the literature showed that the simultaneous consideration of resilience, digitalization, and circular economy in the RMP selection problem (RMPSP) has been ignored by previous studies. Therefore, to cover the mentioned gap, this research attempts to study the RMPSP by considering other crucial concepts namely resilience and Circular Economy (CE). For this purpose, by considering a real-world case study in the steel industry, the current work first specifies the indicators of the research problem. Then, the indicators’ weights are measured using the stochastic Best-Worst Method (BWM). In the next step, the RMPs are prioritized by developing a novel approach called the stochastic Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In general, the main objective of this study is to evaluate the performance of the RMPs in the steel industry based on the CE, resilience, and digitalization aspects. According to the achieved results, “Reliability”, “Price”, “Quality”, “Reverse logistics and Waste management”, “Information systems usage”, and “Restorative Capacity”, are identified as the most desirable indicators. Moreover, the results confirm the effectiveness and validation of the developed method.
Mary Jiny D, G Navamani, Raman Kumar, Željko Stević, Darjan Karabašević, Rajender Kumar,
Volume 35, Issue 3 (9-2024)
Abstract
The increasing demand for food delivery services driven by technological innovations has led to a surge in online shopping and food ordering. Efficient logistics play a crucial role in connecting customers with restaurants seamlessly. In this context, the practical application of graphical networks is explored in this article to streamline food delivery operations. We introduce a novel parameter eternal m-certified domination number denoted by γmcer∞(G) , which represents the minimum number of guards needed to handle any sequence of single orders using multiple-guard movements, ensures that the guard arrangement consistently constitutes a certified dominating set. A case study is presented, illustrating how this concept can be employed to de-crease human resources in a food delivery start-up. This research contributes to optimizing food delivery logistics and reducing operational costs, thereby enhancing the efficiency of the food delivery industry.
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.
Rahma Fariza, Melinska Ayu Febrianti, Qurtubi Qurtubi, Hari Purnomo,
Volume 35, Issue 4 (12-2024)
Abstract
A business faces challenges in terms of product structuring, design, and space layout; it needs to adapt traditional design management models to scientific developments, like customer shopping behavior data. This article contains a systematic review of planograms and is essential because a similar complete literature review has yet to be found. Therefore, this research is necessary, especially for business actors such as retailers and suppliers. This research aims to analyze studies on shelf-space allocation and store layout and provide advice for future research. This study used the systematic review methodology to incorporate relevant literature, of which 50 articles were later obtained. The review protocol guides a comprehensive and systematic analysis of the articles. This study proposes potential avenues for future research to offer a thorough and precise examination of the impact of shelf-space allocation and store layout. The gaps in previous studies are opportunities to create more complex and comprehensive research results on similar topics. This article added scientific value by presenting an exhaustive literature review, and it can fill the theoretical gap by completing the previous literature review.
Agus Ristono,
Volume 35, Issue 4 (12-2024)
Abstract
This paper proposes a decision-support model for supplier selection based on integrating the step weight assessment ratio analysis (SWARA), the method based on the removal effects of a criterion (MEREC), and Additive Ratio Assessment (ARAS) using a case study of the leather industry in Indonesia. The model starts by identifying the main criteria using the opinions of leather industry experts using Delphi. The second stage is to weigh them based on the main criteria, using compromising of objective and subjective weighting methods, namely MEREC and SWARA. The suppliers are selected and ranked based on the main criteria. Lastly, a sensitivity analysis will be performed to check the robustness. Delphi methodology adopted in this study gives managers in Indonesia's leather industries insights into the factors that must be considered when selecting suppliers for their organizations. The selected approach also aids them in prioritizing the criterion. Managers can utilize the supplier selection methodology suggested in this study to rank the suppliers based on various factors/criteria. This study makes three novel contributions to the supplier selection area. First, Delphi is applied to the Indonesian leather industry and integrates MEREC, SWARA, and ARAS into supplier selection. Second, sensitivity analysis allows the determination of the impact of modifications in the primary criteria on the ranking of suppliers and assists decision-makers in assessing the resilience of the process. Last, we find it essential to develop a simple methodology for managers of the Indonesian leather industry to select the best suppliers. Moreover, this method will help managers divide complex decision-making problems into more straightforward methodologies.
Parinaz Esmaeili, Morteza Rasti-Barzoki,
Volume 35, Issue 4 (12-2024)
Abstract
This paper examines the simultaneous decisions regarding advertising, pricing, and service to supply chain coordination involving one manufacturer and one retailer. Demand is impacted by these decisions, with service playing a crucial role in enhancing customer loyalty and boosting sales. The study employs three well-known game theory approaches—Nash, Stackelberg-Retailer, and Cooperative games—to analyze their effects on the supply chain. Optimal strategies for both the manufacturer and the retailer are identified within each approach, and the strategies' results are compared. Results show that the retailer manufacturer, and the entire system achieves higher profits through the Stackelberg-Retailer game compared to the Nash game, while the Cooperative game results in the highest overall profits. Finally, the Nash bargaining model is outlined and analyzed to assess opportunities for sharing profits.
Martin D Arango-Serna, Cristian G Gomez-Marin, Conrado Augusto Serna-Uran, Silvana Ruiz-Moreno,
Volume 36, Issue 1 (3-2025)
Abstract
In recent years changes in freight transport demand, both locally and internationally, have significantly increased cargo flows to and from logistics centers. As a result, it is essential to develop effective methods for assessing freight accessibility to road corridors designated for land cargo transportation. This paper proposes a methodology that facilitates the freight accessibility analysis to a road corridor for land cargo transportation. The accessibility analysis considers several key variables such as the mobilized tons, the overall conditions of the roads, the route lengths connected to the corridor, and origin-destination nodes associated with the productive chains mobilized by this transportation mode. We validate the methodology through a comprehensive case study conducted in Colombia. The results reveal road corridors such as Llanos de Cuivá (Yarumal) - La Apartada (Córdoba), and Soledad - Barranquilla present the lowest accessibility measure and require infrastructure investments to enhance road corridor accessibility and promote the efficient transportation of goods. Furthermore, it offers valuable insights into characterizing areas with significant cargo generation and reception, enabling targeted improvements in transportation industry responsiveness.
Nia Budi Puspitasari, Anggit Kurnia Alfiati Devytasari, Aries Susanty ,
Volume 36, Issue 1 (3-2025)
Abstract
Sustainable Development Goals (SDGs) 12 promotes environmentally responsible consumption and production. One of its sub-objectives is to improve sustainable public procurement practices, in line with national policies and priorities. Sustainable Public Procurement (SPP) is a process of public organizations carrying out goods/services procurement activities that consider economic, social, and environmental aspects. This study identifies and evaluates the factors that drive the implementation of SPP in Yogyakarta Provinces, and seeks recommended solutions based on these driving factors. The respondents selected as the object of this study were 30 procurement actors in Yogyakarta Province. In this study, the driving factors for the application of SPP were divided into 6 factors with 22 subfactors. The analysis method used is the RII method. RII is a method for identifying the relative importance of causation of an event based on its likelihood and effect using the Likert Scale. The results showed that 6 of the 22 subfactors that encourage the implementation of SPP are the availability of sustainable products, sustainable goods/services procurement policies and procedures, the availability of sustainable human resources, the availability of sustainable product/service suppliers, organizational values, and the cost of sustainable products/services.
Imam Djati Widodo, Qurtubi Qurtubi, Elisa Kusrini, Feris Firdaus, Roaida Yanti,
Volume 36, Issue 1 (3-2025)
Abstract
Food supply chain management has become a crucial issue due to increasing food waste caused by globalization and population growth, which not only harms the environment but also social and economic aspects. The circular model has proven to be a powerful solution to overcome this, but its implementation is quite challenging due to the involvement of many stakeholders along the supply chain. So, it is important to understand the driving factors of a circular economy in the food supply chain (FSC) which can stimulate the development of a circular food supply chain, the barrier factors that can cause the failure of circular practices in the FSC, as well as strategies to overcome and mitigate the barriers that arise. Therefore, this study conducted a systematic literature review by analyzing 43 articles to answer specific research questions related to drivers, barriers, and circular food supply chain (CFSC) strategies. The results present nine main drivers, main barriers, and strategies, of which there are 47 sub-drivers, 50 barriers, and 47 strategies. Out of all the strategies identified, 24 greatest strategies using Pareto and SWOT analysis can be adopted for CFSC practice in Indonesia. This research contributes to the existing literature with the strategies, along with the responsible FSC stakeholders.
Muh Syarif, Ismie Roha Mohamed Jais, Iffan Maflahah, Ihsannudin Ihsannudin,
Volume 36, Issue 1 (3-2025)
Abstract
The research focuses on improving the performance of the corn supply chain in Madura Island, Indonesia. The purpose of the study is to identify, evaluate, and prioritize risks that have the potential to disrupt the smooth operation of the corn supply chain. The research method uses Failure Mode and Effects Analysis (FMEA) to identify risk levels and Root Cause Analysis (RCA) approach for mitigation strategies. Risk level assessment is based on severity, probability, and detectability at the level of farmers, middlemen, processing industries, and distributors. Based on the analysis, it shows that the risks are a priority in handling and prevention as well as proposals that can be made to improve the root cause of the occurrence of risks with the highest category based on the RPN value at the farmer level are the occurrence of pest and disease attacks (648), the middleman level is when the amount of corn is abundant (336), the processing industry level is the price of corn is unpredictable (252), and the level of distributors is a limitation in product promotion (324). To improve the efficiency and quality of the corn supply chain, namely increasing storage capacity, using more efficient processing technology, flexible production planning, and more innovative marketing strategies. The managerial implications of corn-supply chain risk assessment are the need to improve product quality, corn supply stability, price management, and strengthen partnerships and mutual benefits between all parties in the supply chain. Every element of the supply chain needs to encourage the adoption of modern technologies in maize cultivation, processing, and distribution to increase productivity and reduce risks associated with manual processes. It is necessary to establish mitigation strategies to address environmental risks, including the implementation of sustainable agricultural practices and early warning systems.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k. Nageswara, Bereket Haile Woldegiorgis,
Volume 36, Issue 2 (6-2025)
Abstract
So far, several models for measuring supply chain performance (SCP) have been developed. The supply chain operation reference (SCOR) model is regarded as the most crucial in the manufacturing business. However, none of the models, including the SCOR model, are comprehensive enough to measure the overall SCP of manufacturing firms. In practice, the existing models are only used in a few of the numerous steps necessary to calculate the overall SCP. Furthermore, the existing models lack fundamental elements that a model should include. The objective of this research is to develop a powerful SCP measurement using a systematic literature review (SLR). Accordingly, this research has proposed a complete supply chain operations measurement (C-SCOM) model. The proposed model consists of four major components: the application of the SCOR model, the application of the AHP method, a template that enables overall SCP calculation, and a direction for linking supply chain management practices (SCMPS) with gap analysis. By having these features, the model provides users with the ability to calculate the overall SCP, conduct gap analysis, carry out benchmarking, and link the gap analysis outputs to existing SCMPs, which the previous models lack. The validation using the fuzzy Delphi technique reveals that the proposed model is unique in its explicitness and will be user-friendly for real-world industrial applications. Finally, this study contributes to the body of knowledge by providing a comprehensive model that could help solve the real challenges that manufacturing firms face when measuring SCP.
Hendro Prassetiyo, Said Muhammad Baisa, Arif Imran, Sri Suci Yuniar, Rangga Try Anugrah,
Volume 36, Issue 2 (6-2025)
Abstract
This study focuses on optimizing vendor selection in laser cutting services through a comprehensive evaluation framework integrating the Vendor Performance Indicator (VPI) and the Fuzzy Analytical Network Process (F-ANP). The methodology quantifies vendor performance across five key criteria: quality, cost, delivery, flexibility, and responsiveness. The results indicate that product quality (39.7%) and cost efficiency (41.4%) are the most influential factors in vendor selection. Sensitivity analysis reveals that a 10% increase in quality consistency improves overall vendor ranking stability by 15%, while cost variations above 8% significantly affect final rankings. The study recommends implementing performance-based contracts, quality assurance protocols, and digital supply chain solutions to enhance vendor assessments. Collaborative partnerships with top-performing vendors can yield mutual benefits and foster sustainable practices, aligning with the company's resilience and operational excellence objectives.
Alemayehu Derege,
Volume 36, Issue 2 (6-2025)
Abstract
The booming of construction sector, including cement factories, has been great success, however, the price of cement has been quadrupled. Among others, critical shortage of cement is observed throughout the country regardless of the success, demanding a critical investigation into its supply chain, governance and regulatory system. Mixed, qualitative and quantitative approaches are applied to investigate the value chain, its administration and regulatory framework. SEM was used to index the level of cement supply distortions in the country. Samples are taken through referral technique from stratified target group across Ethiopian cement supply chain, starting from factory CEO to end-users, from purposively selected major factories. Multinomial logit model is used to analyze the determinant of cement supply distortion. The study found mis-management of regulation, high intervention with ineffective regulatory measure, opened up a room for bribery, favoritism, government interventionism and amplified the roles of intermediaries beyond the market requirement. Brokers are involved in about 85 percent of the country's total cement distribution. Besides, not only intermediaries but also the factories and their agents are contributing a lot in cement supply distortion. The supply chain distortion is observed in all market types, black, gray, and white respectively. The regulatory framework is ineffective and few regulatory bodies are fixed towards reactive measures. Majority of cement distribution is facilitated by brokers and factory agent. Hoarding and smuggling emerge as the most influential factors, with their increase being strongly and significantly linked to a rise in high and severe illegal cement distribution. Regulatory strength and administrative malpractice display complex patterns, indicating that having policies in place is not sufficient; effective enforcement is crucial. Strengthening regulatory, good governance and law enforcement system reduces the cement supply distortion while long run digitalization should be targeted along with supply side intervention.
Mojtaba Nowrouzifasih, Anwar Mahmoodi, Reza Maihami,
Volume 36, Issue 3 (9-2025)
Abstract
The demand for green products has increased in the past few years due to the heightened awareness of environmental issues and the increasing use of green products by consumers. Thus, choosing the best strategy for green product manufacturers is essential. At the same time, producers and retailers are likely to have their decisions influenced by government actions. In this study, we attempt to determine the product's price and greenness within two competitive supply chains. The study investigates the pricing of two substitutable and green products in which each supply chain produces a green product. Using Nash and Stackelberg Game models, we determine how supply chains and their members interact. A Nash model involves two competing supply chains with equal power, within each supply chain, however, there is a Stackelberg competition between the retailer and the manufacturer. The Stackelberg model assumes that one of the supply chains is the market leader. The results show that with increasing government intervention (government's adjustment factor and green level floor for subsidies), regardless of Nash or Stackelberg structures, the green level of the product will increase, and wholesale and retail prices will decrease. Additionally, the price changes in the retailer-Stackelberg structure are greater than those in the manufacturer-Stackelberg structure. Also, by bearing the greenness cost by the manufacturer or retailer, companies can positively impact their profits as well as the level of greenness in their products. When the manufacturer makes an investment in greenness, the retailer and consumer benefit from it, and ultimately become the main force behind the development of green products.
Ida Lumintu, Achmad Maududie,
Volume 36, Issue 3 (9-2025)
Abstract
Effective inventory management is critical for mitigating inefficiencies such as overproduction, excessive holding costs, and stockouts. This study leverages DBSCAN and GMM clustering methods, combined with Principal Component Analysis (PCA) for dimensionality reduction, to categorize inventory data into distinct risk-based clusters. The analysis highlights that DBSCAN outperformed GMM, achieving a silhouette score of 0.62 compared to 0.49, while identifying three meaningful inventory clusters. Each cluster reflects unique combinations of risk factors, providing actionable insights for optimizing inventory levels. The study demonstrates how these clusters enable targeted strategies to address inefficiencies and improve overall inventory management. Limitations include the reliance on historical data, which may not fully capture dynamic market conditions, and the assumption of fixed clustering parameters. The findings underscore the importance of choosing clustering algorithms suited to the data's characteristics and highlight the potential of PCA in enhancing computational efficiency. Future research should explore dynamic clustering techniques and integrate real-time data streams to refine inventory management strategies further.