Logistics Operations Research Articles

Big Data Analytics and Innovation in the Sustainable Performance of Electronic Waste Reverse Logistics: An Empirical Study in India

Abstract Electronic waste (e-waste), encompassing discarded electrical and electronic devices, demands effective reverse logistics management to ensure optimal resource use and environmental preservation. Despite growing interest in Big Data Analytics within the scientific community, its slow practical implementation in e-waste management and the absence of validated measurement models hinder both industry adoption and empirical studies. To address these challenges and drawing upon the Resource-Capability-Advantage (RCA) theory, this study aims to investigate the interplay between Big Data Analytics (BDA) management capabilities, BDA talent capabilities, Reverse Logistics (RL) innovation, and sustainable RL performance. A conceptual model was tested using primary data from practitioners and managers in India’s e-waste reverse logistics network, with Structural Equation Modeling (SEM) as the primary analytical method. The results highlight the multifaceted contributions of Big Data Analytics Management and Talent Capabilities to Reverse Logistics Innovation and Sustainable Reverse Logistics Performance.

The effect of employee competence and competence – job – fit on business performance through moderating role of social exchange: A study in logistics firms

Improving business performance is an important task for all businesses, including the logistics industry. However, at present, there are few studies on the influence of employee competence and competence-job-fit on business performance, in which employee performance and job satisfaction are mediating variables and social exchange is moderating the relationships between employee competence and employee performance and job satisfaction. This research gap will be solved by the authors in this research to achieve the goal of improving the performance of enterprises. Quantitative research method is applied in the research. Data were collected through survey from 181 logistics enterprises in Ho Chi Minh City. The author believes that the research results will contribute significantly to the success of promoting the performance of logistics enterprises as well as to the theoretical basis of employee competence, competence-job fit, job satisfaction, employee performance, and business performance.

Innovative Benchmarking of Offshore Wind O&M Strategies via AIS Data Analysis

Abstract By analyzing AIS data, this study provides independent insights into the diverse logistic concepts deployed by wind farm operators. The benchmarking framework developed herein facilitates the evaluation of logistic efficiency, resilience, and sustainability, thereby contributing to the identification of best practices in offshore wind operations and maintenance (O&M) logistics. The methodology encompasses data collection, preprocessing, and analysis phases. By providing a transparent and data-driven mechanism for benchmarking offshore wind O&M logistics, this study aids in the identification of inefficiencies and the formulation of strategies to enhance logistic operations. The results indicate significant variations in logistic efficiency across different offshore wind farms (OWF), suggesting that the adoption of best practices could lead to substantial improvements.

The performance model of logistic distribution centers: Quality function deployment based on the Best-Worst Method.

This paper aims to evaluate the performance of logistic distribution centers (LDCs) by Quality Function Deployment (QFD) based on the Best-Worst Method (BWM). The originalities of this paper include: (1) exploring five constructs with 20 customer requirement attributes (CRAs) for LDCs' operations based on the SERQUAL model, (2) using the QFD model to identify five primary divisions and 18 corresponding service technical requirements (STRs) for LDCs' operations, (3) recognizing the top five STRs should be prioritized for the allocation of limited resources from House of Quality (HoQ), including cargo order (7.15%), value-added activities (6.68%), document preparation (6.31%), consolidating and assembling (6.10%), and document management (6.00%), (4) applying the Best-Worst Method (BWM) to estimate CRAs' relative weight. The proposed research model can provide a methodological reference to the relevant literature in association with logistics operations and multiple-criteria decision analysis (MCDA).

The Mediating Role of Supply Chain Integration in the Relationship Between Supply Chain Strategy and Logistics Performance

The Mediating Role of Supply Chain Integration in the Relationship Between Supply Chain Strategy and Logistics Performance

DOMINANTS FOR THE NATIONAL ECONOMIES’ COMPETITIVENESS

This article is devoted to innovation as a prerequisite for the national economies' sustainable development and a domain for their global competitiveness. The paper aims to highlight the internal essence of mutual relations between innovation, competition, and economic growth. It was assumed that innovation positively affected the competitive behaviour of economic agents and eventually contributed to an increase in public welfare. Regarding the period from 2007 to 2022, we considered the sample of Central European countries and the Baltic states. Theoretical generalization has been applied to systematize the factors determining competition and innovation. We used statistical methods and comparative analysis to investigate the indicators' dynamics. The interdependencies between macroeconomic dynamics and a set of competition and innovation indicators have been assessed. It was proved that the proportion of medium and high-tech industry value added in the total value added of manufacturing was quite important, yet not the ultimate criterion for ensuring high growth rates and sustainable development. The dynamics of commercial spending on research and development had been ambiguous and unsustainable. To ensure strategic competitiveness, national governments should encourage innovation in their respective business communities. The sampled economies have been examined considering a set of innovation and competition indicators (e.g., gross capital formation, research and development expenditures, logistics performance, export technological structure, carbon dioxide emission, and renewable energy consumption). Considering the implications of globalization, tax burden as an integral characteristic of the national economy's competitiveness has been evaluated as well. It was pointed out that: a) a stable, understandable and transparent tax policy should be implemented to protect the investors' property rights; b) a system of total anti-corruption measures aimed at preventing the practices of receiving undue benefits should be set; and c) the business sector should improve own environmental and social responsibility complexly, introduce resource-saving, green and circular economy.

Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce

PurposeArtificial intelligence (AI) usage improves e-commerce logistics efficiency. However, many actors can play significant roles, such as supply chain consistency (SCC), last-mile logistics (LML) performance and collaboration and coordination among logistics firms. This study aims to assess how SCC and LML performance mediate and collaboration and coordination moderate the relationship between AI usage and logistics efficiency.Design/methodology/approachA structured questionnaire was used to collect the data. A total of 245 valid responses were received from Indian e-commerce businesses. The data were then analysed using AMOS v25 and structural equational modelling using SPSS for regression, PROCESS macro for mediation and moderated mediation analysis.FindingsThe findings show that AI usage independently impacts logistics efficiency, with SCC and last-mile delivery performance as mediating variables. Collaboration and coordination among logistic firms are also critical moderators in enhancing AI’s efficacy in logistic operations. The study findings suggest the integration of AI into logistic operations and provide implications to managers on the urgency of fostering a collaborative and synchronised environment to utilise the full potential of AI in e-commerce businesses.Originality/valueThis study not only contributes to the field of logistics theory by presenting empirical data on the various ramifications of AI but also offers practical guidance for logistics firms, particularly those operating in developing economies, on how to strategically employ AI to enhance operational efficiency and attain a competitive advantage in the era of e-commerce logistics in the digital age.

Optimizing and evaluating the performance of integrated supply production centers: A hybrid heuristic-simulation applied to olive oil waste circular supply chains

This study examines the potential of an integrated bio-commodity supply-production center. Previous research has demonstrated the financial viability of circular bio-economies through Mixed Integer Linear Programming (MILP) or simulation. However, these models 1) do not incorporate the necessary logistics operations for biomass collection and storage, 2) do not integrate and optimize those with the requirements of multi-products line lot sizes. A Geographic Information System (GIS) based model is proposed, integrating insertion and genetic algorithms with a hybrid (ABM-DES) simulation model. A case study in Greece's Fthiotida region, a hub for olive cultivation, investigates the production of pellets, olive cakes, and pomace oil from prunings and Two-Phase Olive Mill Waste (TPOMW). The findings suggest that the model allows for a more accurate estimation of impacts when considering the supply and production operations. In particular, it shows how the frequency and lot sizes of replenishment cycles, influenced by the varying numbers of mechanized harvesters employed, significantly impacts the fluctuation observed in the return on investments. Running the model, it is found that the optimized system with two harvesters can reach a breakeven point, within just 36 months, and corresponding emissions of about 622,041 kgCo2eq. This provides a benchmark for other olive industries to harness unexploited resources.

Improving the Efficiency of Logistics Activities: Current Situation and Prospects

By looking at recent changes, strategic initiatives, and logistics performance indicators, the study examines Uzbekistan's logistics industry. There is a knowledge vacuum about these measures' efficacy in a worldwide setting. The study employs analytical and functional-structural techniques to pinpoint the main elements influencing Uzbekistan's logistics operations' effectiveness, such as infrastructure development, digitization, and multimodal transport system integration. The results show that digital innovation and infrastructural improvements have enhanced logistics performance and international ranking; yet, there are still issues with maximizing operational effectiveness and service quality. This study offers policymakers guidance for creating effective logistics frameworks by indicating that specific enhancements to Uzbekistan's logistics procedures and international collaborations can promote sustained economic growth in the country.

Research on the Development of Logistics Performance of E-Commerce Enterprises and its Influencing Mechanism on Customer Satisfaction

With the booming development of e-commerce industry, logistics performance has become one of the key factors of competitiveness for e-commerce enterprises, directly related to the customer satisfaction and market position of the enterprises. Under the background of digitalization and intelligentization, online shopping has become one of the main ways of daily shopping for consumers. As an important link in the transaction chain of e-commerce, logistics efficiency and quality directly affect the shopping experience and loyalty of consumers. This paper conducts an in-depth analysis of the current situation of logistics performance of e-commerce enterprises, the mechanism analysis of how it affects customer satisfaction, and explores solutions to the problem. Through the mechanism analysis, it is found that e-commerce enterprises can improve logistics performance by enhancing logistics speed, improving logistics service quality, reducing costs and increasing efficiency, strengthening green logistics, and enhancing cross-border e-commerce logistics capabilities. This can improve customer satisfaction, and the paper proposes suggestions such as optimizing logistics networks, enhancing logistics service training, fine-tuning management, promoting environmentally friendly packaging, optimizing transportation methods, and improving cross-border e-commerce logistics networks.

Institutional Strengthening and Improvement of National Logistics Performance Through The Establishment of A National Supply Chain Agency

The logistics sector has a very important role in driving Indonesia's economic growth. However, the national logistics system currently faces various obstacles that prevent it from reaching its full potential. Many challenges slow down the development of this sector. To overcome these obstacles, it is necessary to strengthen institutions that are able to integrate and optimize logistics performance throughout Indonesia. This research suggests the establishment of a National Supply Chain Agency as a solution to improve the coordination, efficiency, and effectiveness of the logistics system. The purpose of this study is to identify and evaluate the role and impact of the establishment of the National Supply Chain Agency on improving national logistics performance. This research uses a qualitative method with data collection from literature studies. The collected data were then analyzed through the stages of filtering, presenting, and drawing conclusions. The results showed that the establishment of the National Supply Chain Agency is an important step to improve logistics performance in Indonesia. The agency is expected to address current challenges, such as inefficiency, high logistics costs, and distribution delays. Thus, the National Supply Chain Agency is proposed as a solution to improve the competitiveness of national logistics, both in the domestic and international markets, and contribute to sustainable economic growth.

Automatic Scheduling Method for Customs Inspection Vehicle Relocation Based on Automotive Electronic Identification and Biometric Recognition

This study presents an innovative automatic scheduling method for the relocation of customs inspection vehicles, leveraging Vehicle Electronic Identification (EVI) and biometric recognition technologies. With the expansion of global trade, customs authorities face increasing pressure to enhance logistics efficiency. Traditional vehicle scheduling often relies on manual processes and simplistic algorithms, resulting in prolonged waiting times and inefficient resource allocation. This research addresses these challenges by integrating EVI and biometric systems into a comprehensive framework aimed at improving vehicle scheduling. The proposed method utilizes genetic algorithms and intelligent optimization techniques to dynamically allocate resources and prioritize vehicle movements based on real-time data. EVI technology facilitates rapid identification of vehicles entering customs facilities, while biometric recognition ensures that only authorized personnel can operate specific vehicles. This dual-layered approach enhances security and streamlines the inspection process, significantly reducing delays. A thorough analysis of the existing literature on customs vehicle scheduling identifies key limitations in current methodologies. The automatic scheduling algorithm is detailed, encompassing vehicle prioritization criteria, dynamic path planning, and real-time driver assignment. The genetic algorithm framework allows for adaptive responses to varying operational conditions. Extensive simulations using real-world data from customs operations validate the effectiveness of the proposed method. Results indicate a significant reduction in vehicle waiting times—up to 30%—and an increase in resource utilization rates by approximately 25%. These findings demonstrate the potential of integrating EVI and biometric technologies to transform customs logistics management. Additionally, a comparison against state-of-the-art scheduling algorithms, such as NSGA-II and MOEA/D, reveals superior efficiency and adaptability. This research not only addresses pressing challenges faced by customs authorities but also contributes to optimizing logistics operations more broadly. In conclusion, the automatic scheduling method presented represents a significant advancement in customs logistics, providing a robust solution for managing complex vehicle scheduling scenarios. Future research directions will focus on refining the algorithm to handle peak traffic periods and exploring predictive analytics for enhanced scheduling optimization. Advancements in the intersection of technology and logistics aim to support more efficient and secure customs operations globally.

Supply Chain Management in Smart City Manufacturing Clusters: An Alternative Approach to Urban Freight Mobility with Electric Vehicles

The development of green production types such as personalized production and shared manufacturing, which use additive technologies in city multifloor manufacturing clusters (CMFMCs), has led to an increase in last-mile parcel delivery (LMPD) activity. This study investigates the integration of electric vehicles and crowdshipping systems into smart CMMCs to improve urban logistics operations related to the distribution of products to consumers. The aim of this study is to improve the LMPD performance of these integrated systems and to provide alternative solutions for sustainable city logistics using the potential of crowdshipping and vehicle sharing fleets (VSFs) in the city logistics nodes (CLNs) of CMFMCs. The issues presented by the loading–unloading operations and sustainable crowdshipping scenarios for LMPD in CMFMCs are considered. This paper presents a new performance evaluation model for crowdshipping LMPD in CMFMCs using VSFs. The case study shows that the proposed model enables the analysis of LMPD performance in CMFMCs, taking into account their finite production capacity, and that it facilitates the planning of cargo turnover and the structure of VSFs consisting of e-bicycles, e-cars, and e-light commercial vehicles (e-LCVs). The model is verified based on a case study for sustainable LMPD scenarios using VSFs. The proposed model enables the planning of both short- and long-term logistics operations with the specified performance indicator of VSF usage in CMFMCs. The validity of using the integrated potential of crowdshipping and vehicle sharing services for LMPD under demand uncertainty in CMFMCs is discussed. This study should prove useful for decision-making and planning processes related to LMPD in CMFMCs and large cities.

Optimization of Truck–Cargo Matching for the LTL Logistics Hub Based on Three-Dimensional Pallet Loading

This study investigates the truck–cargo matching problem in less-than-truckload (LTL) logistics hubs, focusing on optimizing the three-dimensional loading of goods onto standardized pallets and assigning these loaded pallets to a fleet of heterogeneous vehicles. A two-stage hybrid heuristic algorithm is proposed to solve this complex logistics challenge. In the first stage, a tree search algorithm based on residual space is developed to determine the optimal layout for the 3D loading of cargo onto pallets. In the second stage, a heuristic online truck–cargo matching algorithm is introduced to allocate loaded pallets to trucks while optimizing the number of trucks used and minimizing transportation costs. The algorithm operates within a rolling time horizon, allowing it to dynamically handle real-time order arrivals and time window constraints. Numerical experiments demonstrate that the proposed method achieves high pallet loading efficiency (close to 90%), near-optimal truck utilization (nearly 95%), and significant cost reductions, making it a practical solution for real-world LTL logistics operations.

Analysis of Factors Affecting Logistic Performance Among Registered Freight and Forwarding Firms in Nairobi County, Kenya

Purpose: The general objective of the study was to establish the environmental factors affecting logistics performance among registered freight forwarding firms in Nairobi County, Kenya. The specific objectives comprised of examining the effect of the internal environment, external environment and firm size on the logistic performance of registered freight forwarding firms in Nairobi County, Kenya. Methodology: This study used a descriptive research design. The study targeted 1676 managing director and senior departmental level managers drawn from the registered freight and forwarding firms. Data was collected using questionnaires. The collected data was entered into SPSS 28 analytical tool where it was coded and analysed. Both descriptive and inferential analysis was applied. Findings: The findings showed that firm size had a positive and significant moderating effect on the relationship between environmental factors and performance of registered freight and forwarding firms in Nairobi County, Kenya. The study concludes that there is a positive and statistically significant relationship between internal environment factors and logistic performance. The study shows that while the structural aspects are important, the cultural and leadership elements play a more pivotal role in enhancing logistic performance. The study further concludes that external environment factors have a positive and significant effect on logistic performance. The study notes that infrastructure, policy and technology are crucial, but the potential benefits of technology may not be fully realized or uniformly adopted across the firms. The study also concludes that firms of all sizes can potentially achieve high logistic performance by focusing on effective resource utilization, strategic market analysis, and continuous development efforts. Unique Contribution to Theory, Policy and Practice: The study recommends that the policymakers should focus on simplifying documentation and customs procedures to reduce delays and improve the overall efficiency of logistic operations. The government should invest and increase support in research and development. The study also recommends that firms should establish clear communication policies that foster teamwork and engagement since encouraging participatory engagement and keeping employees informed of shared goals can spur productivity. Logistical firms should also invest in resources including human resource and financial resources. The firm should recruit and retain adequate and competent personnel to meet organizational goals as well as mobilize financial resources effectively to support investments in technology and infrastructure.

Development and construction of a cataract risk prediction model based on biochemical indices: the National Health and Nutrition Examination Survey, 2005-2008.

The aim of this study is to develop and validate a novel multivariable prediction model capable of accurately estimating the probability of cataract development, utilizing parameters such as blood biochemical markers and age. This population-based cross-sectional study comprised 9,566 participants drawn from the National Health and Nutrition Examination Survey (NHANES) across the 2005-2008 cycles. Demographic information and laboratory test results from the patients were collected and analyzed using LASSO regression and multivariate logistic regression to accurately capture the influence of biochemical indicators on the outcomes. The SHAP (Shapley Additive Explanations) scale was employed to assess the importance of each clinical feature, excluding age. A multivariate logistic regression model was then developed and visualized as a nomogram. To assess the model's performance, its discrimination, calibration, and clinical utility were evaluated using receiver operating characteristic (ROC) curves, 10-fold cross-validation, Hosmer-Lemeshow calibration curves, and decision curve analysis (DCA), respectively. Logistic regression analysis identified age, erythrocyte folate (nmol/L), blood glucose (mmol/L), and blood urea nitrogen (mmol/L) as independent risk factors for cataract, and these variables were incorporated into a multivariate logistic regression-based nomogram for cataract risk prediction. The area under the receiver operating characteristic (ROC) curve (AUC) for cataract risk prediction was 0.917 (95% CI: 0.9067-0.9273) in the training cohort, and 0.9148 (95% CI: 0.8979-0.9316) in the validation cohort. The Hosmer-Lemeshow calibration curve demonstrated a good fit, indicating strong model calibration. Ten-fold cross-validation confirmed the logistic regression model's robust predictive performance and stability during internal validation. Decision curve analysis (DCA) demonstrated that the nomogram prediction model provided greater clinical benefit for predicting cataract risk when the patient's threshold probability ranged from 0.10 to 0.90. This study identified blood urea nitrogen (mmol/L), serum glucose (mmol/L), and erythrocyte folate (mmol/L) as significant risk factors for cataract. A risk prediction model was developed, demonstrating strong predictive accuracy and clinical utility, offering clinicians a reliable tool for early and effective diagnosis. Cataract development may be delayed by reducing levels of blood urea nitrogen, serum glucose, and erythrocyte folate through lifestyle improvements and dietary modifications.

The macroeconomic determinants of trade openness in Latin American countries: A panel data analysis

Background Trade openness shows a positive impact on economic growth, supported by economic theory, and export diversification and economic complexity show a positive dynamic in trade openness in the world; however, a specificity is generated in South American countries. Therefore, the objective of the research is to analyse the macroeconomic determinants of trade openness in Latin American countries. Methods The research approach was quantitative and explanatory using panel data methodology from the databases of the World Bank, Harvard University and the Economic Commission for Latin America and the Caribbean for the period 2000-2020. Results The fixed effects panel data model showed that the variables that had a negative impact on trade openness were GDP, the economic complexity index and the logistic performance index, while the variables that had a positive impact were exports of high-tech products (a proxy for innovation), exports, imports, research and development expenditure and interregional trade in goods. Conclusions Therefore, during the analysis period of 2000-2020 in South America, based on the panel data analysis under fixed effects, a total of 8 countries had a negative impact on trade openness, and only the economies of Chile, French Guiana, and Brazil had a positive impact on trade openness; these economies are characterized by their better performance in the economic complexity index, their higher percentage of budget for research and development expenses, and their trade policies oriented towards the industrialization of their value-added products.

Avoidance of Medicine Wastage in Private Clinics In Hong Kong: Practitioners’ Perspectives

Hong Kong with its well-established healthcare and medicine system and professional health services is one of the renowned healthiest places in the world. In fact, Hong Kong's healthcare system is running on a dual-track basis comprising public and private sectors. This study intends to explore medicine waste management and sustainability. First, we examine the existing phenomenon of Hong Kong medicine waste. Also, we discuss the causes of medical waste from a private clinic doctors' perspective. In addition, we identifies possible policies and recommendations to minimize the medicine wastage in private clinic in Hong Kong as well as improve the healthcare supply chain practices. Qualitative research with in-depth interviews of doctors and medical practitioners have been carried out to gather their views and opinion of medication wastage, including the current medicine waste situation and the means of handling the expired medicines. Also, the study analyzes the centralized procurement platform effectiveness and suggests some possible policies for government to adopt. Interviewees mentioned that medication waste has occurred over decades. Medicine wastages are not only financial burdens, but also social burdens. If the medication waste problem cannot be alleviated, it will affect the population health and environment in the long run. An all-rounded healthcare supply chain with efficient logistics operations would help the government to collect excess medicines from private clinics and redistribute to some NGOs. In fact, all parties including manufacturers, distributors, prescribers, and patients have the responsibilities to maintain and implement suitable policies to prevent bulk medicine waste. This research study provides the foundation of medicine wastage in private clinics in Hong Kong. Future research can investigate the medicine wastage in other aspects as well as consolidate the literatures in both industrial and public perspectives.

Process Mining in der Intralogistik

Abstract The application of process mining opens up a wide range of possibilities for logistics, such as the identification of bottlenecks, the optimization of throughput times and the more efficient use of resources. However, in an area as dynamic and vulnerable as logistics, there are specific challenges that make the application of process mining difficult and therefore require special attention. A structured approach is therefore required to successfully implement process mining in practice. This publication presents a methodology that supports companies in effectively integrating process mining into their internal logistics operations. It includes project initialization, the extraction and preparation of the data to be analyzed, the execution of analyses, the interpretation of the results and the derivation of measures.

FORMATION OF A SYSTEM FOR ASSESSING THE EFFECTIVENESS OF INNOVATIVE DEVELOPMENT OF LOGISTICS ACTIVITIES OF MOTOR TRANSPORT ENTERPRISES ENGAGED IN FREIGHT TRANSPORTATION IN TERMS OF SUSTAINABLE DEVELOPMENT

The article discusses the importance of implementing innovations at road transport enterprises in the context of achieving the region's sustainable development goals. The author emphasizes that road transport enterprises are significant sources of harmful emissions and environmental pollution, so using innovative technologies, such as electric vehicles, hybrid cars, and alternative fuels, is an important tool for reducing the negative environmental impact. In particular, these technologies help to reduce greenhouse gas emissions and other harmful substances, which is in line with Sustainable Development Goals 7 (access to modern energy), 13 (combating climate change), and 15 (protecting terrestrial ecosystems). In addition, innovations in transport technologies, such as automated driving systems, help to improve road safety and reduce the number of road accidents, which is in line with Goal 3 (good health and well-being). The creation of new jobs and infrastructure development through the construction of electric charging stations and the introduction of intelligent transport systems (smart cities) are also linked to Sustainable Development Goals 9 (sustainable infrastructure) and 11 (sustainable urban development). The author analyses the performance indicators of innovations at motor transport enterprises, taking into account economic, social, and environmental aspects. Particular emphasis is placed on the adaptation of these indicators to the current realities of Ukraine. Using game theory, the article develops a model for the selection of optimal strategies for motor transport enterprises and the region. This model allows us to find the Nash equilibrium - a situation where both parties achieve the optimal result. Enterprises that implement innovations not only improve their own performance indicators, but also contribute to the achievement of sustainable development goals of the region. The article also presents two sets of strategies: for the development of logistics activities of a motor transport enterprise and the sustainable development of the region. Both approaches aim to comprehensively improve the region's environmental, economic, and social situation. The conclusions emphasize the importance of implementing innovation development assessment systems as a tool for making strategic decisions and improving the efficiency of logistics operations.