Supply Logistics Research Articles

Advancement in global halal industry from farm to fork

In light of the increasing Muslim population worldwide, it is crucial to pay attention to their lifestyle and regulations. This is particularly important for facilitating trade with Muslim nations, especially since the majority of exporters to these nations are non-Muslim. The terms "Halal" and "Haram" hold significant value in the Muslim world, as they refer to what is permissible and forbidden, respectively, according to religious guidelines (Shari’ah). Global trade and the attachment of the Halal logo to products rely on these terms. Interestingly, non-Muslims have shown a positive attitude towards Halal products, believing that they are manufactured in a more hygienic, tasty, and safer manner. However, there are challenges that need to be addressed, such as the lack of an unified Halal certification and regulations for the entire Muslim world, particularly in the era of globalization. There is an urgent need for globally accepted Halal guidelines and regulations that cover the entire supply chain, including processing, logistics, technologies, retail and wholesale, marketing, and branding. This will ensure Halal integrity and enhance trade between non-Muslim and Muslim countries Keywords: Halal, Haram, Globalization, Halal Certification, Halal integration

AI-Driven Optimization of Last-Mile Delivery

The optimization of last-mile delivery represents a critical challenge in modern e-commerce logistics, consuming a substantial portion of total shipping costs. This comprehensive technical article examines how artificial intelligence and machine learning technologies are revolutionizing last-mile delivery operations through advanced route optimization, demand forecasting, and resource allocation. This article synthesizes findings from recent implementations across major logistics providers, demonstrating that AI-driven route optimization systems significantly reduce delivery times and decrease fuel consumption across diverse operational environments. Analysis of machine learning models deployed by leading e-commerce platforms shows marked improvements in delivery time prediction accuracy, achieving unprecedented precision in estimated delivery windows. This article examines key technical components, including dynamic routing algorithms, predictive demand modeling, and real-time fleet management systems, while also addressing implementation challenges such as data quality and system integration. Case studies from major logistics providers demonstrate substantial ROI improvements following AI implementation, with particular emphasis on neural network architectures optimized for urban delivery scenarios. This article provides a technical framework for understanding how AI technologies transform last-mile logistics while offering insights into future developments, including autonomous delivery systems and smart city integration.

Designing Smart Supply Chains Based on Digital AI Instruments and Mobile Technologies

Academic and industrial research on digital technology has been quite thorough. Nevertheless, scant information exists regarding the supply chain implementation of digital technology in industrial companies. To better understand supply chains, this article will look at why and how manufacturing companies are implementing digital technology. The goal of this paper’s literature analysis is to pinpoint current studies and perspectives on how these technologies could help digital supply chains (DSCs) operate better, faster, and more efficiently. The investigation looks at the technologies’ directions and challenges in improving the efficiency of digital help confinement, in addition to underlining their significance for supply chains and logistics. It investigates the managerial and practical issues in developing a new integrated paradigm for digital supply chains. Also, possible obstacles to DSCs and procurement will be examined, along with solutions. Consequently, this study pinpoints multiple opportunities for adding value when implementing Internet of Things (IoT) in the supply chain using mobile technology. Additionally, it suggests a method for creating business models for supply chain algorithms.

Linking Road to Logistic Progress in Kerala: An Analysis of the Influence of National Highway Development on Supply Chain and Logistics

Linking Road to Logistic Progress in Kerala: An Analysis of the Influence of National Highway Development on Supply Chain and Logistics

Optimizing food transportation processes for grocery stores across the US

In the rapidly evolving landscape of food logistics, optimizing transportation processes for grocery stores across the United States has become paramount to enhancing operational efficiency and ensuring the delivery of high-quality, perishable goods. This article examines the multifaceted challenges inherent in food transportation, including logistical complexities, environmental concerns, and rising operational costs. It highlights the importance of data-driven strategies, such as route optimization and machine learning algorithms, to improve delivery times and reduce waste. Additionally, the integration of advanced technologies, such as Internet of Things (IoT) sensors for temperature monitoring and automation in warehouse management, is explored to enhance the cold chain and ensure food safety. Moreover, the article emphasizes the critical role of strategic partnerships with third-party logistics providers and suppliers in streamlining operations and enhancing overall performance. Through in-depth case studies of successful grocery chains, it illustrates effective practices that have led to significant improvements in food transportation processes. The regulatory landscape surrounding food transportation is also analysed, underscoring compliance with safety standards and sustainability initiatives. Finally, the article looks ahead to future trends, including the potential impact of autonomous vehicles, blockchain technology, and sustainable practices on the food supply chain. By providing a comprehensive overview of best practices and innovative solutions, this article aims to equip grocery store operators and stakeholders with actionable insights to optimize their food transportation processes, ultimately leading to improved customer satisfaction and reduced environmental impact.

IoT-Enabled Cross-Platform Applications for Real-Time Logistics Monitoring

Internet of Things (IoT)The integration of Internet of Things (IoT) technology and cross-platform mobile applications has revolutionized real-time logistics monitoring, enabling unprecedented visibility, efficiency, and proactive management of supply chain operations. This article explores the key components of IoT-enabled logistics monitoring, including IoT sensors, data integration, real-time tracking, automated notifications, predictive maintenance, and proactive supply chain management. The benefits of implementing these solutions are highlighted, such as reduced risks, optimized routes, improved operational efficiency, and enhanced customer satisfaction. The article also discusses the challenges associated with IoT implementation, including data integration, connectivity, security, and privacy, and provides strategies for overcoming these obstacles. Through real-world case studies, the tangible impact of IoT-enabled cross-platform applications in logistics is demonstrated, showcasing the potential for significant improvements in cost savings, asset utilization, and overall supply chain performance. As the IoT landscape continues to evolve, the adoption of these technologies will become increasingly critical for logistics providers looking to maintain a competitive edge in the market.

Brexit consequences on supply chains: towards a risk management framework

ABSTRACT This article investigates Brexit-induced consequences on supply chains and logistics – as well as potential solutions and strategies by carrying out a content analysis through a literature review, the first to our knowledge. Our findings reveal that Brexit-induced consequences for supply chains include increased customs duty rate, labour supply issues, increased costs related to expected delays, tariff and nontariff barriers, added complexity to guarantee food safety, authenticity or security, increased food prices, as well as low-skilled households carrying the major load. Our findings regarding typical supply chain strategies or solutions for abovementioned Brexit-induced consequences include supply chain redesign, relocation of operations and markets, changing sourcing countries or regions, new information and communication technologies solutions such as traceability and blockchains, vertical and horizontal collaboration, resilience, better risk-recovery strategies, as well as the switch to ‘other’ metrics. Another result refers to the fact that we observe only a low level of theoretical grounding in (supply chain) risk management literature among the considered articles.

Why is demurrage important for logistics companies using container terminals? An analysis of the determinants of demurrage and its impact on firm performance

During the COVID-19 pandemic, severe demurrage in shipping and container terminals has led to a global logistics crisis and supply chain disruptions. Although the situation is gradually stabilizing, discussions persist on strategies to reduce volatility in container freight transportation. Demurrage imposes unnecessary costs, delays deliveries, and impedes the efficiency of container terminals. This study analyzes the factors influencing demurrage from the perspective of logistics companies, specifically, based on the characteristics of logistics companies and the attributes of the cargo owners they serve. Additionally, it explores the impact of demurrage levels on firm performance and investigates how this relationship may be moderated by container terminal characteristics. The empirical findings indicate that advancements in information systems within logistics companies, along with improved collaboration and contract compliance among cargo owners, can significantly reduce demurrage. This reduction in demurrage can enhance firm performance. Furthermore, credibility management and digitization of shipping documents also play a crucial role in minimizing demurrage. Building on previous research and empirical insights, this study emphasizes the importance of sustained long-term investment and policy support from the government for the digital transformation of logistics processes, complementing the efforts of both logistics companies and cargo owners.

Customers’ reuse intention to autonomous delivery vehicles in terminal delivery service: A valence theory perspective

Autonomous delivery vehicles (ADVs), as a new tool in terminal delivery, are currently used extensively. However, for the permanent success of the ADV industry, logistics providers need to understand the influencing mechanism of consumers' reuse intention of ADVs. Therefore, this research uses valence theory as basis in analyzing the elements and mechanisms affecting consumers’ reuse intention of ADVs. Survey data were assembled from 550 ADV consumers in China through online questionnaires, and partial least squares structural equation model was used as a tool for data analysis. Findings indicate that convenience and hedonic value can enhance the perceived value of ADVs. Perceived value can positively affect reuse intention through the attitude toward using ADVs, whereas perceived cost negatively affects the reuse intention through the attitude toward using ADVs. The discussion section of this paper summarizes the results and implications and provides valuable suggestions for logistics providers and developers.

Recirculation of construction and demolition Waste: A case study of Danish producers and demolishers

As resource scarcity increases, the construction industry recognizes the potential of Reverse Logistic Supply Chains (RLSC) for demolition waste. Implementing RLSC, however, lacks maturity and poses challenges due to the complexity of the construction industry. This paper is the first to investigate the critical interface between demolishers and producers. In particular, demolishers are crucial for the potential to valorize reclaimed construction wood as they are the gatekeepers of the materials. We apply an existing framework, conceptualized through a systematic literature review, to the case of a Danish shed producer and their collaboration with demolishers. Our data foundation includes qualitative data from semi-structured interviews with industry stakeholders and quantitative financial data on conventional as well as selective demolition. Through the analysis of material, information, and financial flows of reclaimed wood, this paper identifies inhibitors to these flows and reveals that producers can address the majority. Since responsibilities for reprocessing, transportation, and storage require clarification, making agreements for (1) reprocessing and (2) transportation, potentially facilitated by (3) a digital platform can support the producer in overcoming these inhibitors. Even though we show that selective demolition can be financially attractive for demolishers, our findings call for additional supportive regulation of tender practices. Further, we coin the concept of reversed value proposition as RLSC necessitate a reversed understanding of value creation. Overall, this paper contributes empirical evidence to the existing framework, extends it by adding inhibitors and flows, and suggests an extension with platform thinking to support the implementation of RLSC.

Methods of Balancing Technological Systems of Multiproduct Production

The functioning of the machine-building industry has its specifics, particularly periodic changes in the range (size, configuration, and others) of manufactured products. In addition, it is essential to consider the need to reduce the time spent on the production of each unit. Almost continuous changes in technology, failures in the supply of raw materials, uncoordinated logistics, and many other factors often cause significant and unproductive costs, leading to an increase in the technological stage. The most promising direction to reduce the technological time of manufacturing products by multiproduct enterprises is to reduce the waiting time owing to the uniform distribution of each technological transition according to the state of the available workshop equipment (plant, production area, enterprise). This study proposes a novel model of technological systems that enables the adaptation of technological processes for part manufacturing and comprises data structures that define their technical capabilities. The proposed algorithm facilitates a reduction in downtime and an increase in equipment utilization factor. It is possible to optimize the technological processes that change the structure of each production operation to adapt to the existing technology. Testing this methodology demonstrated a significant increase of 8% in the process utilization rate of machinery.

Evaluating Supply Chain Network Models for Third Party Logistics Operated Supply-Processing-Distribution in Thai Hospitals: An AHP-Fuzzy TOPSIS Approach

Background: This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, hospitals can enhance their operational efficiency, allowing healthcare professionals to focus on core tasks and ultimately improving service delivery. Methods: This research employed a dual methodology, combining an analytic hierarchy process (AHP) with a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). These approaches evaluated various SCM models based on multiple hospital logistics performance attributes. Results: The AHP results highlighted on-time delivery, patient safety, utilisation rate, and emergency procurement as critical criteria for selecting the optimal model. Fuzzy TOPSIS analysis identified the SCIII: W-G-H model as the most suitable for implementation in Thai hospitals. This model incorporates a centralised warehouse for negotiation leverage, a Group Purchasing Organisation (GPO) for cost efficiency, and regional SPD hubs for effective inventory management and rapid responses to demand fluctuations or emergencies. Conclusions: Adopting this SCM model is expected to significantly enhance supply chain performance, reduce operational costs, and improve the quality and safety of patient care in Thai hospitals.

FORMATION OF STRATEGICALLY-ORIENTED DIRECTIONS FOR THE DEVELOPMENT OF LOGISTICS ORGANIZATIONAL STRUCTURES

The article is devoted to the study of the influence of strategic management in increasing the efficiency and quality of logistics organizational structures. The article considers the classification of management decisions to ensure the effective operation of logistics providers, analyzes the essence of strategic management of organizations, features of corporate strategy, business strategy, and functional strategies. The reasons that make it difficult to transfer the logistics development strategy to lower levels of management have been identified. Theoretical approaches to the process of implementing logistics management strategies in organizational structures are proposed. It was determined that the key idea of the supply chain concept is the transition from functional management to management of cross-functional business processes. The advantages of strategically oriented organizations are highlighted, and it is also substantiated that a balanced system of indicators is effective for solving the problem of related business strategies and directions with the establishment of goals for the efficiency of logistics organizational structures. The four key processes that the Balanced Scorecard relies on to link short-term actions to long-term goals are described. Modern trends in changes in management styles from the management practices of advanced logistics providers are analyzed. The mechanism of application of the Deming cycle and reengineering of business processes is substantiated. It has been proven that effective implementation of the concept of strategic management of the logistics organizational structure is possible only when the organization is strategically oriented.

Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from the Ele.me platform. Quantitative methods, including the frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze satisfaction differences between men and women riders. The findings reveal an asymmetric pattern in satisfaction preferences: women riders place more emphasis on perceived value, while men riders prioritize service perceived quality. Although both groups rank platform image, product perceived quality, and rider expectations similarly, the importance of these factors varies significantly, indicating an underlying asymmetry in their expectations and values. Women riders express higher satisfaction with platform image, rider expectations, service perceived quality, and product perceived quality, with rider expectations showing the largest difference. Additionally, the multi-criteria decision-making methods used in this study offer insights for optimizing service performance in real-time crowdsourcing logistics platforms, particularly in handling uncertainty and enhancing system adaptability through fuzzy sets. These findings provide a basis for developing gender-specific strategies aimed at enhancing rider satisfaction, minimizing turnover, and improving platform adaptability—contributing to a more inclusive and sustainable logistics supply chain.

Optimizing last-mile delivery of essential medicines in Nigeria: Insights from Niger State’s health-care supply chain

Last-mile delivery of health commodities is a critical component of efficient supply chains, and third-party logistics (3PL) providers are pivotal in ensuring cost-effective and reliable product distribution. This study explores the implementation of last-mile delivery outsourcing by government-operated warehouses and drug management agencies (DMAs). This research focuses on the relationship between 3PL utilization and key performance metrics, such as cost reduction, timely delivery, and end-user satisfaction. This study combines a literature review, surveys, and interviews conducted with employees of the DMAs in Minna, Niger State, to establish significant correlations. The findings show that using 3PLs significantly reduced operational costs, improved the frequency of timely deliveries, and enhanced end-user satisfaction. These findings underscore the need for continued engagement with 3PL providers to optimize supply chain performance and improve service delivery outcomes. Managers are recommended to maintain and expand such collaborations to sustain these benefits.

Digital twin-based cross-enterprise production-delivery synchronization in a highly dynamic environment

Efficient collaboration between production and logistics is crucial for timely order fulfillment and stable operations of system, necessitating closer cooperation between manufacturers and third-party logistics providers. However, achieving cross-enterprise synchronization presents three main challenges. First, concerns regarding information privacy and security lead to disjointed and non-shared resources. Second, the decision-making is not coordinated and consistent in dealing with dynamic interference. Third, differentiated strategies emerge as manufacturers and 3PLs employ different batch processing methods for customer orders in pursuit of economies of scale. This multifaceted disconnect leads to significant asynchronization in cross-enterprise production-logistics, resulting in inefficiencies and increased costs throughout the system. To address these challenges, this paper focuses on three key aspects: a digital twin-based cross-enterprise information-sharing framework, a cross-enterprise synchronized mechanism, and a collaborative optimization based distributed decision method. These aspects provide an intelligent production-logistics synchronization solution in the unique environment of Industry 4.0. Finally, through a case study of a paint enterprise, this paper comprehensively evaluates the differences in performance of the Production-Logistics Synchronization System (PLSS) under various synchronization modes. The results indicate that the proposed solution enhances the collaborative efficiency of production-logistics while ensuring the information security of the collaborating parties, effectively reducing production and delivery costs.

Computational analysis of the Logistics Supply Chain from a global trade perspective

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

Evaluating the financial credibility of third-party logistic providers through a novel frank operators-driven group decision-making model with dual hesitant linguistic q-rung orthopair fuzzy information

In the relevant literature, there is no study dealing with the financial credibility of third-party logistic providers with the help of decision-making frames. Further, there are no criteria to evaluate the third-party logistics providers' creditworthiness in practice, and decision-makers in the banks consider their judgments and experiences to assess the demand of the logistics firms. This study proposes a multi-criteria group decision-making framework through a dual hesitant linguistic q-rung orthopair fuzzy (DHLq-ROF) set to manage uncertainties more effectively and make a theoretical contribution to the academic literature. For ranking, the score function and accuracy function are defined. Additionally, some novel operational laws based on Frank t-norms and t-conorms are defined for DHLq-ROF numbers. A wide range of generalized aggregation operators, such as DHLq-ROF Frank weighted averaging, DHLq-ROF Frank weighted geometric, DHLq-ROF Frank generalized weighted averaging, and DHLq-ROF Frank generalized weighted geometric operators, are also investigated. Beyond that, several prominent characteristics of the proposed operators are studied. It is applied to a financial credibility problem for a multinational organization to demonstrate the introduced model's applicability. Considering the results obtained regarding the importance of the criteria, the most crucial criterion is market indebtedness, followed by fleet vehicle structure and current rate criteria, respectively. The results indicate that UPS, Kuhne & Nagel and DHL Deutsche Post are the best third-party logistic providers. The sensitivity analysis shows that the framework possesses favourable flexibility and effectiveness. Thanks to the framework's ability to produce practical solutions to challenging decision-making problems, it can be reliably preferred in engineering and other fields.

Effect of Supplier Relationship Management Practices on Organizational Performance of Supermarkets in Kenya: A Case of Naivas Supermarkets in Nakuru County

Supplier relationship management is managing suppliers and vendors and enhancing strategic partnerships. The study’s goal was to establish the effect of supplier relationship management on organizational performance of Naivas supermarkets, Nakuru County. For companies to be established, they must focus on creating closer connections with other organizations to attain competitive advantage. This has made organizations develop the urgency to have lasting relationships with suppliers with intentions of increasing SC performance. This research sought to understand whether information sharing, buyer-supplier trust, supplier collaboration and supplier commitment positively contribute to organizational success and performance. SRM practices make organizational performance better however, there’s limited empirical evidence on their impact within supermarkets in Kenya, which presents a research deficiency that the research desired to fill. The investigation’s objectives included; to examine the effect of information sharing on the organizational performance of Naivas supermarket, to determine the effect of buyer-supplier trust on the performance of Naivas Supermarket, to determine the effect of supplier collaboration on the organizational performance of Naivas Supermarket. The theories were; social exchange theory, commitment trust theory of relationship marketing and resource-based theory. Descriptive research design was employed. The target population was 82 respondents working at the seven Naivas supermarket branches in Nakuru County. A census was employed in this study. The study used questionnaires and interviews. Questionnaires were issued to 82 respondents but only 70 were filled and returned. Interviews were conducted with top employees. Descriptive statistics and inferential statistics were employed for results interpretation. Data analysis was done through Microsoft excel Data analysis tool and SPSS. Results were displayed through tables. The first objective results showed that there’s a positive relationship between information sharing and organizational performance (r= .373, p value=0.001). The second objective results, imply a positive correlation between buyer-supplier trust and organizational performance (r=.369, p value= 0.001). Third objective indicated a significant positive relationship between supplier collaboration and organizational performance (r=.455, p value=0.000). The fourth objective’s results showed strong positive correlation between supplier commitment and organizational performance (r= .489, p value= 0.000). The study concluded that Naivas supermarkets in Nakuru consider practicing the objectives as this will lead to increased performance. The study recommends that it is important to have training programs for all involved and the service users have to be informed about the decisions that are related to supplier management. This study recommends that the supermarkets should work collaboratively with logistics providers.

IoT-driven load forecasting with machine learning for logistics planning

Forecasting electricity load in logistics is crucial for managing dynamic energy demands. This research introduces the Integrated Load Forecasting System (ILFS), integrating IoT-driven load forecasting with advanced machine learning. As pioneers in logistics-focused electricity load forecasting, we acknowledge challenges posed by operational metrics, external factors, and diverse features. Starting with thorough preparation, including managing missing data and normalization, ILFS incorporates novel approaches such as Hybrid Boruta with XGBoost (BXG) for feature selection and Uniform Manifold Projection and Approximation (UMAP) for lower dimensionality. In the classification phase, we introduce a pioneering approach: the Hybrid Huber Regression with ResNet (HRRN) model, fine-tuned using the Coyote Optimization Algorithm (COA). Demonstrating scalability and interpretability, ILFS adjusts to various electricity load data scenarios, capturing trends in logistics supply warehouses across different days. Validation metrics underscore ILFS’s efficacy, achieving 98% accuracy, 4 MAE, 12 MSE, 5 RMSE, and 0.99 R-squared (R2). With an average execution time of 7.2 s, ILFS outperforms current techniques, and rigorous statistical analyses support this superiority. ILFS emerges as a pivotal solution, meeting the necessities of precise electricity load forecasting in logistics driven by IoT technologies. This research strides towards harmonious integration of load forecasting, IoT, and logistics planning, ushering in advancements in the field.