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The rapid integration of the Internet of Things (IoT) into logistics and supply chain management (SCM) marks a significant transformation towards enhanced efficiencies, security, and sustainability. Through a comprehensive bibliometric analysis of 2680 publications from the Scopus database, this study charts the evolution of IoT within logistics and SCM and reveals a shift from foundational explorations to mature implementations. The research unfolds a complex thematic structure, highlighting the revolutionary impacts of IoT and related technologies such as RFID, the synergy of Industry 4.0 with SCM through Artificial Intelligence (AI) and the Industrial Internet of Things (IIoT), the strategic role of blockchain for enhanced traceability and security, and the advent of novel communication and encryption technologies for secure data exchanges. Further, the analysis categorizes the scholarly discourse into critical areas including big data and IoT optimization in SCM, IoT-driven innovation in the food supply chain, applications of blockchain and smart contracts, digital transformation through Industry 4.0, security advancements with intelligent systems, and the exploration of advanced technologies for Industry 4.0 and 5.0. This review not only delineates the intellectual landscape of IoT applications in logistics and SCM but also identifies emerging research areas such as blockchain integration, 5G potential, and AI-driven optimizations, suggesting pathways for future research to broaden the understanding in this dynamically evolving field. It serves as an essential resource for academics and practitioners, providing insights into the transformative role of IoT in logistics and SCM and proposing directions for future technological and academic endeavors.

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Since the emergence of smart logistics as a vital paradigm, it has garnered significant interest from independent firms and governments worldwide, including China. This study aims to examine the relationship between Smart Logistics Policy (SLP) and firm performance both theoretically and empirically. Utilizing data from A-share companies listed on the Shanghai and Shenzhen stock exchanges between 2012 and 2017, this study analyzes the relationship between SLP and firm performance using Propensity Score Matching (PSM) and Difference-in-Differences (DID). The results indicate that SLP significantly enhances a firm's financial performance. Additionally, a heterogeneity test on financial performance reveals that the impact of SLP varies based on ownership and industrial sector. Unexpectedly, SLP has a negative impact on corporate social responsibility (CSR) performance. The heterogeneity test on CSR performance shows that the SLP effect on CSR exhibits no significant difference based on ownership. Furthermore, the impact of SLP on CSR is significantly greater for manufacturing firms compared to non-manufacturing firms. Consequently, this study offers theoretical support and empirical evidence regarding the effects of SLP on firm performance.

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Due to regional differences in industrial structure levels, the development of the logistics industry in rural areas faces various challenges and opportunities. The objective is to explore how the high-quality development of the logistics industry influences rural revitalization at various tiers of industrial structure. It employs a benchmark regression model to dissect the influence that the logistics industry's high-quality development exerts on fostering rural revitalization. Moreover, a panel threshold model is employed to examines this impact across different levels of industrial structure. It demonstrates that enhancing the logistics industry significantly supports rural revitalization, with its impact varying across different levels of industrial structure. Hence, it is imperative to develop customized strategies for the logistics industry that account for the varying industrial structure in rural areas. It emphasizes the logistics industry's role in facilitating rural growth and recommends adopting tailored development strategies corresponding to the industrial structure's evolution to boost rural revitalization. Despite valuable insights, this study has limitations in reflecting regional trends and exploring other factors beyond the direct impact of logistics on rural revitalization, pointing to potential avenues for future research.

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Meat quality (MQ) is unstable during cold chain logistics (CCL). Different technologies have been developed to enhance MQ during the CCL process, while most of them cannot cover all the links of the cold chain because of complex environment (especially transportation and distribution), compatibility issues, and their single effect. Electric fields (EFs) have been explored as a novel treatment for different food processing. The effects and potential advantages of EFs for biological cryopreservation have been reported in many publications and some commercial applications in CCL have been realized. However, there is still a lack of a systematic review on the effects of EFs on their quality attributes in meat and its applications in CCL. In this review, the potential mechanisms of EFs on meat physicochemical properties (heat and mass transfer and ice formation and melting) and MQ attributes during different CCL links (freezing, thawing, and refrigeration processes) were summarized. The current applications and limitations of EFs for cryopreserving meat were also discussed. Although high intensity EFs have some detrimental effects on the quality attributes in meat due to electroporation and electro-breakdown effect, EFs present good applicability opportunities in most CCL scenes that have been realized in some commercial applications. Future studies should focus on the biochemical reactions of meat to the different EFs parameters, and break the limitations on equipment, so as to make EFs techniques closer to usability in the production environment and realize cost-effective large-scale application of EFs on CCL.

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Advancements in cell therapy have the potential to improve healthcare accessibility for eligible patients. However, there are still challenges in scaling production and reducing costs. These challenges involve various stakeholders such as the manufacturing facility, third-party logistics (3PL) company, and medical center. Proposed solutions tend to focus on individual companies rather than addressing the interconnectedness of the supply chain's challenges. The challenges can be categorized as barriers from product characteristics, regulatory requirements, or lagging infrastructure. Each barrier affects multiple stakeholders, especially during a boundary event like product handover. Therefore, solutions that only consider the objectives of one stakeholder fail to address underlying problems. This review examines the interconnecting cell therapy supply chain challenges and how they affect the multiple stakeholders involved. The authors consider whether proposed solutions impact individual stakeholders or the entire supply chain and discuss the benefits of stakeholder coordination-focused solutions such as integrated technologies and information tracking. The review highlights how coordination efforts allow for the implementation of widely-supported cell therapy supply solutions such as decentralized manufacturing through stakeholder collaboration.

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Modular integrated construction (MiC) is now widely adopted by industry and governments. However, its fragile and delicate logistics are still a concern for impeding project performance. MiC logistic operations involve rigorous multimode transportation, loading-unloading, and stacking during storage. Such processes may induce latent and intrinsic damage to the module. This damage causes safety hazards during assembly and deteriorates the module's structural health during the building use phase. Also, additional inspection and repairs before assembly cause uncertainties and can delay the whole supply chain. Therefore, continuous monitoring of the module's structural response during MiC logistics and the building use phase is vital. An IoT-based multi-sensing system is developed, integrating an accelerometer, gyroscope, and strain sensors to measure the module's structural response. The compact, portable, wireless sensing devices are designed to be easily installed on modules during the logistics and building use phases. The system is tested and calibrated to ensure its accuracy and efficiency. Then, a detailed field experiment is demonstrated to assess the damage, safety, and structural health during MiC logistic operations. The demonstrated damage assessment methods highlight the application for decision-makers to identify the module's structural condition before it arrives on site and proactively avoid any supply chain disruption. The developed sensing system is directly helpful for the industry in monitoring MiC logistics and module structural health during the use phase. The system enables the researchers to investigate and improve logistic strategies and module design by accessing detailed insights into the dynamics of MiC logistic operations.

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Promoting the green development of the logistics industry has become a focal point of attention in China. This study combines an improved gravity model and social network analysis method, focusing on the nineteen provinces of the Yangtze Economic Belt and Yellow River Basin. It constructs a spatial correlation network of carbon emissions in the logistics industry from 2010 to 2021, exploring its formation mechanism and spatial evolution characteristics. The study utilizes a quadratic assignment procedure model to investigate internal driving factors. Building upon this, the study employs an improved STIRPAT model to predict the emission reduction path of the future logistics industry. Results are as follows: (1) Carbon consumption is most pronounced in Shandong, Jiangsu, and Shanghai. The carbon emission shows the characteristics of larger downstream; (2) The bridges of carbon emission-related networks gradually shift from Shandong to Shanxi, Anhui, and Sichuan. Carbon emissions in each sector and spatial spillover effects exhibit dynamic correlations and interactive influences; (3) Energy intensity, freight volume, and the spatial correlation network of the logistics industry are highly correlated; (4) The overall carbon emissions from the logistics industry show a decreasing trend in the future. Anhui and Shaanxi provinces will have high carbon emissions in 2035. The conclusions aim to provide policy suggestions for the region's low-carbon transformation.

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How to accurately assess logistics industry efficiency to identify production issues and provide support for optimizing logistics efficiency has become a current research challenge. Range adjust measure (RAM) is a method for efficiency assessment in data envelopment analysis. Currently, the RAM model only applies under the variable returns to scale condition and not to other conditions. This paper aims to establish a modified RAM (MRAM) model by revising the ranges for inputs and outputs of the RAM model. Under the constant returns to scale (CRS) condition, we first develop the RAM-CRS model. Then, by introducing radial models to define the lower bounds of inputs and the upper bounds of outputs, the MRAM is proposed. The logistics data from 18 provinces are collected to validate the practicality of the MRAM model. We compare the results of the MRAM with those of the RAM-CRS and conclude that the range bounds under RAM-CRS are too tight, which results in efficiency values at a relatively low level. The MRAM with modified bounds appropriately alleviates this restriction. We also compare the MRAM and the additive model. The results show that the efficiency of the MRAM is more accurate.

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In this study, we inserted a dynamic chemical reaction system that can generate CO2 into Janus hydrogel (JH) to develop a multidimensional preservation platform that integrates hygroscopicity, antibacterial activity, and modified atmospheric capacity. The double gel system developed using sodium alginate/trehalose at a 1:1 ratio effectively encapsulated 90% of citric acid. Furthermore, CO2 loss was avoided by separately embedding NaHCO3/cinnamon essential oil and citric acid microcapsules into a gelatin pad to develop JH. Freeze-dried JH exhibited a porous and asymmetric structure, very strongly absorbing moisture, conducting water, and rapidly releasing CO2 and essential oils. Furthermore, when preserving various fruits and vegetables in practical settings, JH provided several preservation effects, including color protection, microbial inhibition, and antioxidant properties. Our study findings broaden the application of JH technology for developing chemical reaction systems, with the resulting JH holding substantial promise for cold chain logistics.

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Introduction: Due to global industrialization and urbanization, natural disasters, accidents, and public health emergencies happen frequently. These events cause significant loss of life and property damage to countries worldwide. In the context of frequent public emergencies, enhancing emergency logistics response capabilities is crucial, ensuring rapid supply of rescue materials and support for rescue personnel, thereby saving lives and reducing economic losses. Methods: In order to identify the changes and enhancement paths of the emergency logistics response capability of Chinese regions under the shocks of public emergencies, this paper innovatively constructs emergency logistics response capability measurement indicators. This paper uses the entropy weight TOPSIS method and panel quantile regression model to quantify the change and enhancement paths of China's regional emergency logistics response capability under different events. Results: It is found that: (1) The gap in emergency logistics response capability among Chinese regions is widening, with the internal difference in the eastern region higher than that in the west, while the difference in the central region is relatively low. (2) China's emergency management department can effectively transform social logistics into emergency logistics, thereby promoting the improvement of emergency logistics response capabilities. (3) Sudden geological disasters break through the limits of social logistics resources when they cross lower scales, resulting in the failure of emergency logistics response capabilities. Discussion: This paper expands research on assessing emergency logistics capabilities, addressing issues in existing assessments such as reliance on single indicators and subjective measurement methods. Additionally, it quantifies the dynamic changes in China's regional emergency logistics response capabilities under public emergencies by extending the study of event content, types, and impacts. This enhances discussions on the effects of public emergencies. Finally, from an empirical perspective, the paper explores pathways to enhance regional emergency logistics response capabilities in China. In practice, this paper assists countries worldwide in assessing whether different regions of China can effectively provide emergency support for various resources in direct investments, thus providing a scientific basis for investment decisions.

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Logistics is critical in every company's supply chain (SC), and outsourcing helps businesses concentrate on their core competencies. Third-party logistics (3 PL) or logistics service providers (LSPs) assist businesses in cutting costs while improving performance, sustainability, and revenue. Logistics evaluation and LSPs choice are complicated and critical components of value delivery. This study aims to review logistics outsourcing literature to understand the trends, prospects, factors, and strategies used in logistics companies' outsourcing choices. This work examines the literature on LSPs selection published between 2010 and 2023. This paper uses VOSviewer (version 1.6.19) to visualize the relationships. Pricing, timely shipment, service quality, reliability, agility, technology, and consumer feedback are the most commonly utilized, whereas societal and environmental factors are seldom used. The study comprises journal publications, the year, selection criteria, and assessment methodologies. Numerous scholars have discovered and employed many critical selection criteria. Many investigators have also embraced multi-criteria decision-making (MCDM) methodologies, and their fuzzy form is widely used. In conclusion, recommendations for theorists and managers, limits, and future directions for research are offered.

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Human performance in the rail freight yard has been identified as a source of risk for rail freight operations. This is both within the yard itself, and also with train preparation issues leading to incidents on the network. The rail freight yard is an area that has received limited research attention. Over 30 hours of observations were conducted at five major freight yards in Great Britain, along with 30 interviews of rail freight ground staff. Task models, human performance factors and potential solutions that were further explored in a workshop with freight personnel. This analysis led to an understanding of freight yard activities, the impact of freight yard design and environment, and the role external pressures on freight yard performance including upstream planning. The implications are discussed for both current freight operations, and for future technology and process change within the rail freight sector.

Human performance in the rail freight yard is critical to safety and performance, but receives little research attention. A structured study included observations in the yard, interviews with ground staff, and a validation workshop. Results include task models, influencing factors, potential solutions and implications for future technology and process change.

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PURPOSE: This study aims to focus on studies that qualitatively explore prison food experience. The goal is to elaborate a framework to better understand how prison food shapes the worldwide carceral experience. DESIGN/METHODOLOGY/APPROACH: This systematic literature review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. It consists of four phases: identifying the studies, screening the studies, evaluating the eligibility of screened studies and inclusion of studies. After the four phases, ten studies (nine qualitative studies and one with mixed methods) were included in the review. FINDINGS: There is a consensus among the researchers in the reviewed literature that prison food shapes the carceral experience. More specifically, four themes that encompass the experience of people with prison food emerged from the reviewed literature: food appreciation (taste of the prison food and perceived nutritional value), food logistics (preparation, distribution and consumption), food variety (institutional menu and commissary store) and food relationships (symbol of caring or power or punishment). ORIGINALITY/VALUE: The literature reviewed demonstrated that when incarcerated individuals have a negative view of prison food, the carceral experience is negatively impacted. This systematic review identified four dimensions that encompass the food experience within the prison environment, providing a framework for navigating this subject.

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To effectively solve the reverse logistics distribution problem caused by the increasing number of scrapped parts in the automotive market, this study constructs a multi-trip green vehicle routing problem model with time windows by comprehensively considering the coordination between carbon dioxide emissions and cost efficiency. A hybrid adaptive genetic algorithm is proposed to solve this problem, featuring innovative improvements in the nearest neighbor rule based on minimum cost, adaptive strategies, bin packing algorithm based on the transfer-of-state equation, and large-scale neighborhood search. Additionally, to efficiently obtain location data for supplier factory sites in the distribution network, a coordinate extraction method based on image recognition technology is proposed. Finally, the scientific validity of this study is verified based on the actual case data, and the robust optimization ability of the algorithm is verified by numerical calculations of different examples. This research not only enriches the study of green vehicle routing problems but also provides valuable insights for the industry to achieve cost reduction, efficiency enhancement, and sustainable development in reverse logistics.

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This study investigates the enhancement of the home delivery distribution network for COVID-19 Home Isolation (HI) kits during the Delta variant outbreak of the SARS-CoV-2 virus in Bangkok Metropolitan Area, Thailand. It addresses challenges related to limited resources and delays in delivering HI kits, which can exacerbate symptoms and increase mortality rates. A k-means clustering approach is utilized to optimize the assignment of service areas within the COVID-19 HI program, while discrete event simulation (DES) evaluates potential changes in the home delivery logistics network. Real-world data from the peak outbreak is used to determine the optimal allocation of resources and propose a new logistics network based on proximity to patients' residences. Experimental results demonstrate a significant 44.29 % improvement in overall performance and a substantial 40.80 % decrease in maximum service time. The findings offer theoretical and managerial implications for effective HI management, supporting practitioners and policymakers in mitigating the impact of future outbreaks.

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The rapid development of the logistics industry has driven innovations in parcel sorting technology, among which the swift and precise positioning and classification of parcels have become key to enhancing the performance of logistics systems. This study aims to address the limitations of traditional light curtain positioning methods in logistics sorting workshops amidst high-speed upgrades. This paper proposes a high-speed classification and location algorithm for logistics parcels utilizing a monocular camera. The algorithm combines traditional visual processing methods with an enhanced version of the lightweight YOLOv5 object detection algorithm, achieving high-speed, high-precision parcel positioning. Through the adjustment of the network structure and the incorporation of new feature extraction modules and ECIOU loss functions, the model's robustness and detection accuracy have been significantly improved. Experimental results demonstrate that this model exhibits outstanding performance on a customized logistics parcel dataset, notably enhancing the model's parameter efficiency and computational speed, thereby offering an effective solution for industrial applications in high-speed logistics supply.

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The effective management of the medicine supply chain is crucial for ensuring the availability of essential medicines and supplies in public health facilities. This study aimed to determine the utilization of the electronic logistic management information system (e-LMIS) in public health facilities and its implications for the medicine supply chain. A mixed methods approach, combining both quantitative and qualitative data collection methods, was used. The study included 106 healthcare providers from 35 public health facilities in Singida District. Six key informants were interviewed using a qualitative method. Of the 106 participants, 62.3% said they were somehow competent in e-LMIS utilization. In in-depth interviews, respondents underscored the system's utility for tracking stock levels, procurements, and managing orders. Staff shortages and a lack of customized training were mentioned as major challenges hindering efficiency in managing drug supplies. This study highlighted the positive impact of e-LMIS on various aspects of the medicine supply chain, including the timely submission of orders and enhanced inventory management. Sustained management support and the regular utilization of the e-LMIS system are crucial for building and maintaining competence among healthcare providers, thereby optimizing the medicine supply chain and ultimately improving healthcare delivery.

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This paper reports a case study in which an improvement in nursing work was achieved through the introduction of a traceability system compatible with radio-frequency identification (RFID) and bar codes for the management of medical materials. In verifying the RFID-based system in an operating room, the work time was reduced to approximately one-tenth of that of barcode reading. In the catheterization laboratory, a system consisting of a cartel management system utilizing bar codes and an RFID-compatible inventory management cabinet was introduced. The system eliminates the need to cut and paste packages onto vouchers after the cases are completed and digitizes the data sent to the medical affairs department for secure billing. We are implementing this system at many facilities, and, in addition to improving the work of nurses, we are taking new steps to improve hospital management through data linkage.

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This paper evaluates GHG emissions and energy usage in "short" and "long" cold chains for oranges, table grapes, and apples transported from South Africa to a retail store in Scotland. Novel formulae assess energy usage and emissions based on cold chain duration. "Short" chains show carbon footprints between 0.87 and 1.28 kg CO2e/kg of saleable fruit, contrasting starkly with extended cold chains. Extending storage durations increases emissions; a one-month extension results in 24-27 % emissions for oranges and grapes and 16 % for apples. Six months of CA storage of apples increases emissions by 96 % compared to "short" cold chains. Energy consumption follows a similar trend as emissions. This research informs policymakers and consumers, emphasising the need for sustainable and "short" cold chains. This is also the first paper that comprehensively assesses both the energy requirements and emissions outputs in a fruit supply chain based on the combined transport and storage duration of the cold chain from tree to retail markets.

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In humanitarian aid scenarios, the model of cumulative capacitated vehicle routing problem can be used in vehicle scheduling, aiming at delivering materials to recipients as quickly as possible, thus minimizing their wait time. Traditional approaches focus on this metric, but practical implementations must also consider factors such as driver labor intensity and the capacity for on-site decision-making. To evaluate driver workload, the operation times of relief vehicles are typically used, and multi-objective modeling is employed to facilitate on-site decision-making. This paper introduces a multi-objective cumulative capacitated vehicle routing problem considering operation time (MO-CCVRP-OT). Our model is bi-objective, aiming to minimize both the cumulative wait time of disaster-affected areas and the extra expenditures incurred by the excess operation time of rescue vehicles. Based on the traditional grey wolf optimizer algorithm, this paper proposes a dynamic grey wolf optimizer algorithm with floating 2-opt (DGWO-F2OPT), which combines real number encoding with an equal-division random key and ROV rules for decoding; in addition, a dynamic non-dominated solution set update strategy is introduced. To solve MO-CCVRP-OT efficiently and increase the algorithm's convergence speed, a multi-objective improved floating 2-opt (F2OPT) local search strategy is proposed. The utopia optimum solution of DGWO-F2OPT has an average value of two fitness values that is 6.22% lower than that of DGWO-2OPT. DGWO-F2OPT's average fitness value in the algorithm comparison trials is 16.49% less than that of NS-2OPT. In the model comparison studies, MO-CCVRP-OT is 18.72% closer to the utopian point in Euclidean distance than CVRP-OT.