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With the rise and rapid development of the e-commerce industry, the pressure borne by the supply chain of e-commerce enterprises is increasing, which greatly increases the complexity and uncertainty of inventory management in the e-commerce supply chain. The study integrates system dynamics and collaborative supply chain inventory management to construct a new model. The study first uses the concept of system dynamics to optimize the supply chain inventory management system; then the collaborative supply chain is used to construct a system model by combining the optimized management system. The results show that the collaborative supply chain inventory management model constructed by the study can better accelerate the product turnover rate, improve the overall operational efficiency and market competitiveness of the supply chain, and can provide new support for the development of e-commerce enterprises. [ABSTRACT FROM AUTHOR]

This study aims to perform a comprehensive bibliometric investigation to navigate the colliding domains of blockchain technology and supply chain management from 2017 to 2023. A total of 724 scholarly documents were extracted, showing increased annual scientific productivity and revealing a detailed map of the academic landscape. Notably, publications in sources such as IEEE Access and Sustainability (Switzerland) have emerged as seminal sources, with scientists such as Jayaraman R. leaving a strong scholarly impact among changing publication volumes. Affiliations such as Khalifa University, Nirma University, and The University of Hong Kong appear as critical research hotspots, but China maintains a strong position in publication count. The analysis shows trending trajectories and collaborative networks among authors, institutions, and countries, and it generates a thematic map with five unique clusters. The study also delineates thematic progression and co-citation patterns, providing a prospective perspective into future research avenues. Overall, this study extends the scholarly discussion by providing a broad, yet intricately detailed picture of the contemporary academic landscape. [ABSTRACT FROM AUTHOR]

In this research, the properties and cementitious performance of thermally activated cement pastes (referred to as DCPs) are investigated. Hydrated pastes prepared from Portland cement and slag blended cement were subjected to different thermal treatments: 350 °C for 2 h, 550 °C for 2 h, 550 °C for 24 h and 750 °C for 2 h. The properties and the reactivity as SCM of the DCPs were characterised as well as their effect on the mechanical performance and hydration of new blended cements incorporating the DCPs as supplementary cementitious materials (SCMs). It was observed that the temperature and duration of the thermal treatment increased the grindability and BET specific surface area of the DCP, as well as the formation of C2S phases and the reactivity as SCM. In contrast, the mechanical strength results for the blended cements indicated that thermal treatment at 350 °C for 2 h provided better performance. The hydration study results showed that highly reactive DCP interfered with the early hydration of the main clinker phases in Portland cement, leading to early setting and slow strength gain. The effect on blended cement hydration was most marked for binary Portland cement–DCP blends. In contrast, in the case of ternary slag cement–DCP blends the use of reactive DCP as SCM enabled to significantly increase early age strength. [ABSTRACT FROM AUTHOR]

Prefabricated construction has proven sustainability and affordability through innovative solutions. Prefabricated housebuilding companies, as supply entities, play a vital role toward successful projects using prefabricated products. Many companies go into liquidation due to poor performance. Supply chain management performance is linked with organizational performance in the manufacturing domain. However, there is no performance framework to date for prefabricated housebuilding companies using supply chain management theory. The purpose of this study is to identify the supply chain management interventions in prefabricated housebuilding research and report relevant key performance indicators based on empirical evidence. These indicators were classified under performance dimensions and supply chain processes. These indicators were then checked for relevancy with subject matter by academic and industry experts engaged in prefabricated construction research and practice, respectively. Later an industry-wide Likert scale-based survey was conducted with experienced experts in practice, involved in the prefabricated construction business, for validation of the proposed framework. This study reports 40 key performance indicators, ranked under six principal component bodies of supply chain management, with low to high ranges from marketing to strategic management. The purposive selection is used for industry consultation with experts having practical experience. Survey results show all the indicators are highly significant except "Supplier driven strategy" which is still under a medium range of relative importance index. The top six key performance indicators are "Collaborative networking," "Quality assurance," "Entrepreneurial cognition," "Geographical proximity," "Intellectual property," and "Relationship marketing." The performance framework is suitable for vertically integrated companies involved in design, manufacturing, and construction. The qualitative nature of this framework is highly useful, with implementation ease, for companies to benchmark and gauge performance in a competitive market. This study explored the general supply chain management theoretical intervention for the development of an integrated performance framework as only specific elements were considered previously. [ABSTRACT FROM AUTHOR]

How do firms benefit from integrated enterprise systems (IES), and how does the IES implementation strategy influence the returns from IES? We investigated the implementation strategy that firms should follow to integrate multiple enterprise systems regarding the timing of adoption and the richness of modules. Borrowing theories from software development literature and enterprise system implementation literature, we developed two IES implementation strategies, i.e., the agile strategy (simple, quick, and flexible) and the phased strategy (rich, phased, and pre-determined). We collected a sample of 675 public firms from 1997 to 2004 at the module level, enabling us to distinguish enterprise resource planning (ERP) systems from customer relationship management (CRM) and supply chain management (SCM) systems. Our data contained the timing of purchase and "go-live" events of these system modules, helping us understand firms' detailed implementation decisions. We found that IES returns depend on the choices of ERP and CRM/SCM module foundation, ERP-CRM/SCM sequential connection, and the continued adoption of ERP and CRM/SCM modules. Fewer ERP or CRM/SCM modules at CRM/SCM go-live events, a quicker connection between ERP and CRM/SCM go-live events, and the continued adoption of ERP or CRM/SCM modules all were found to enhance IES returns. Our findings show that the agile strategy leads to more returns from IES than the phased strategy and suggest that firms should integrate multiple enterprise systems by going live with advanced system modules quickly after going live with basic enterprise system modules and by continually adding new modules. [ABSTRACT FROM AUTHOR]

This study investigates the factors influencing the implementation of blockchain in logistics in the United Arab Emirates (UAE), including security, privacy, end-user benefits, quality control, technology infrastructure, and lack of general awareness. A mixed-methods approach was used, with data collected through survey questionnaires and semi-structured interviews. The research targeted logisticians in the UAE's supply chain department, using random probability sampling and a sample size of 151 for surveys and using purposive sampling for recruiting 10 experts. Using SPSS 24.0, the Pearson Correlation analysis revealed a strong association between blockchain in logistics and IT infrastructure and awareness of blockchain in the UAE logistics sector. Exploratory factor analysis showed a significant difference towards the security of data in the implementation of blockchain in the logistics sector in the UAE. This research suggests that implementing blockchain technology in UAE logistics companies can enhance data security and quality control, influencing managers' decisions positively and recommends prioritizing data security and quality control. The study's geographical context emphasizes its contribution in the research area showing the importance of considering cost, benefits, security, IT infrastructure ownership, and awareness aspects in the adoption of blockchain technology in supply chain management. [ABSTRACT FROM AUTHOR]

In the United States, truck rates for perishable food, the per‐mile rate charged for trucking services to move perishable food from farms to stores, rose substantially in the post‐COVID‐19 pandemic era. We argue that rising truck rates is a signal of a broader shortage of truckers, but the connection between labor shortages, rising truck rates, and a lack of trucking services has yet to be established empirically. In this paper, we develop an empirical examination based on an equilibrium job search, matching, and bargaining framework in which we estimate the role of labor shortages in accelerating driver‐wage growth, and truck rates for agricultural products. We estimate the model by combining US Bureau of Census Current Population Survey data on truck driver wages with USDA‐Agricultural Marketing Service Service data on truck rates to establish the linkage between trucker supply and the demand for trucking services. We find that the COVID‐19 pandemic was responsible for a rise in for‐hire trucker wages of some 38%$38\%$, a rise in average truck rates of nearly 50%$50\%$ and that the gap between trucker‐job openings and successful matches explains a significant, but small, rise in truck rates. [ABSTRACT FROM AUTHOR]

We measure the performance of a real-world triadic supply chain (SC) network consisting of suppliers, 3PL, and retailers. Three-stage network slacks-based measure (NSBM) and multi-parametric bias correction generalised directional distance function (MPBC-NGDDF) approach are developed to deal with conventional and non-discretionary inputs, desirable and undesirable linking activities and outputs. The sample consists of 786 combinations of triad members. Using both NSBM and MPBC-NGGDF facilitates a sound SC performance evaluation and identification of optimal inputs and outputs. We also compare the NSBM and MPBC-NGDDF estimates against the network epsilon-based measure (NEBM) efficiencies. This comparative analysis reveals the weaknesses and strengths of each method in the context of a complex SC network. Identifying weaknesses and strengths draws on the appropriateness of optimal solutions and practical implications. The MPBC-NGDDF approach meets both appropriateness criteria. According to this approach, considerable reductions are needed in the number of employees used by suppliers, the production agility, the origin port distance from the suppliers, the destination port distance from the retailers, the time from placing an order to delivery to the retailers' premises, and distribution costs. [ABSTRACT FROM AUTHOR]

With the rapid development of modern medical technology and the dramatic increase in the amount of medical data, traditional centralized medical information management is facing many challenges. In recent years blockchain, which is a peer-to-peer distributed database, has been increasingly accepted and adopted by different industries and use cases. Key areas of healthcare blockchain applications include electronic medical record (EMR) management, medical device supply chain management, remote condition monitoring, insurance claims and personal health data (PHD) management, among others. Even so, there are a number of challenges in applying blockchain concepts to healthcare and its data, including interoperability, data security privacy, scalability, TPS and so on. While these challenges may hinder the development of blockchain in healthcare scenarios, they can be improved with existing technologies In this paper, we propose a blockchain-based healthcare operations management framework that is combined with the Interplanetary File System (IPFS) for managing EMRs, protects data privacy through a distributed approach while ensuring that this medical ledger is tamper-proof. Doctors act as full nodes, patients can participate in network maintenance either as light nodes or as full nodes, and the hospital acts as the endpoint database of data, i.e., the IPFS node, which saves the arithmetic power of nodes and allows the data stored in the hospitals and departments to be shared with the other organizations that have uploaded the data. Therefore, the integration of blockchain and zero-knowledge proof proposed in this paper helps to protect data privacy and is efficient, better scalable, and more throughput. [ABSTRACT FROM AUTHOR]

Globalization and multinational commerce have increased the dynamism and complexity of supply networks, thereby increasing their susceptibility to disruptions along interconnected supply chains. This study aims to tackle the significant concern of supplier selection disruptions in the Thai agri-food industry as a response to the aforementioned challenges. A novel supplier evaluation system, PROMETHEE II, is suggested; it combines the Fuzzy Analytical Hierarchy Process (FAHP) with inferential statistical techniques. This investigation commences with the identification of critical indicators of risk in the sustainable supply chain via three phases of analysis and 315 surveys of management teams. Exploratory factor analysis (EFA) is utilized to ascertain six supply risk criteria and twenty-three sub-criteria. Following this, the parameters are prioritized by FAHP, whereas four prospective suppliers for an agricultural firm are assessed by PROMETHEE II. By integrating optimization techniques into sensitivity analysis, this hybrid approach improves supplier selection criteria by identifying dependable solutions that are customized to risk scenarios and business objectives. The iterative strategy enhances the resilience of the agri-food supply chain by enabling well-informed decision-making amidst evolving market dynamics and chain risks. In addition, this research helps agricultural and other sectors by providing a systematic approach to selecting low-risk suppliers and delineating critical supply chain risk factors. By bridging complexity and facilitating informed decision-making in supplier selection processes, the results of this study fill a significant void in the academic literature concerning sustainable supply chain risk management. [ABSTRACT FROM AUTHOR]

This research investigates the optimal integration of Blockchain Technology (BT) in Supply Chain Management (SCM) within Chile's maritime ports. Utilizing fuzzy Logarithmic Methodology of Additive Weights (LMAW) and Double Normalization-based Multiple Aggregation Methods (DNMA), the study systematically identifies, prioritizes, and ranks key factors influencing BT adoption in SCM. The study's findings highlight crucial factors like enhanced transaction security, good supply chain practices, and risk management. Furthermore, it ranks the application of ports as prime candidates for BT integration. The research contributes theoretically by developing a hybrid model combining MCDA methods, and practically by guiding the strategic application of BT in the maritime logistics sector, aligning with the principles of Industry 5.0. This paper presents a novel approach that explores the utilization of BT in maritime supply chain management, incorporating MCDA in a vague environment. The research gap of this study lies in defining new contexts in both theoretical and practical literature reviews for extending the use of BT in SCM in the ports of Chile, according to Industry 5.0, to increase the efficiency and effectiveness of all aspects of operations in these places. The contribution of this research is applying hybrid MCDA methods in an uncertain environment to assist decision-makers (DMs) in better implementing BT in SCM in Chilean ports, according to Industry 5.0. [ABSTRACT FROM AUTHOR]

Due to social and psychological factors, the COVID-19 pandemic has impacted international trade, dampened consumption globally, and resulted in conservative investment and spending. To stimulate economic recovery while promoting the establishment of a positive consumption awareness among people, enterprises endeavor to enhance competitiveness and expand market share through various means, such as advertising and discounting. With more attention paid to environmentally friendly products, there are greater challenges encountered by green supply chain management. In this study, a green supply chain network problem is analyzed, involving a manufacturer and a retailer. In addition to the construction of centralized and decentralized decision models, two cost-sharing contracts are adopted to reduce promotion costs for the retailer and improve the level of greenery in products. With the help of game theory, equilibrium decisions can be made by solving the models. According to the results of numerical experiment, cost-sharing contracts can effectively improve the level of greenery in products and the profitability of the supply chain, despite the inability to achieve a win–win situation. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to identify the M protein trans-acting positive regulator (Mga) orthologue and its adjacent M-like protein (SCM) alleles in Streptococcus canis. Results: Using the 39 SCM allele isolates and polymerase chain reaction-based amplification and sequencing, we obtained the deduced Mga amino acid (AA) sequences. The 22 Mga sequences in whole-genome sequences were obtained by searching the National Collection of Type Cultures 12,191(T) Mga sequence into the database. The percentage identity to the type-strain Mga sequence was examined along with its size. The presence of the Mga-specific motifs was confirmed. Of the 62 strains, we identified 59 Mga sequences with an AA size of 509 (except for four different sizes). Percentage identity ranged from 96.66 to 100% with the confirmed Mga-specific motifs and diverse SCM allele populations. Our findings support the presence of an Mga orthologue and diverse SCM allele populations. [ABSTRACT FROM AUTHOR]

Continuous changes in today's market have exposed supply chain (SC) management to severe challenges. Such changes in the market are divided into two general categories: (1) Time-dependent changes such as political, economic, and cultural changes occurring over time and require decision-makers to consider the dynamics of decisions; and (2) Sudden changes and events such as diseases and natural disasters disrupting SCs. This paper investigates the impact of both changes on the decisions of a green supply chain. Moreover, these challenges may affect the organizations' activities in the market and arouse a conflict in the members' goals, leading to competition among members. This paper studies a game model for a dynamic–stochastic supply channel SC with one manufacturer and one retailer, where two types of products (green and non-green) are sold. In this study, two models are dynamically considered: The first model without demand disruptions and the second model with demand disruptions. Finally, the results are compared. On the other hand, due to environmental goals and to survive manufacturers under disruption, the government supports manufacturers in producing green products. Implementing this cooperation, the manufacturer also invests more in improving the greening level of green products, thereby enhancing its demand. Regarding numerous disruptions common in the automotive industry, this case study is conducted on the automotive supply chain to evaluate the models, and the results are presented in the form of numerical examples. Finally, to extract managerial insights, sensitivity analysis is performed on the main parameters of the problem. [ABSTRACT FROM AUTHOR]

The present study examines a supply chain consisting of a manufacturer and a retailer. The manufacturer produces a product with a national brand (NB) and the retailer selling both the NB product and his own premium store brand (PSB) product. The manufacturer competes with the retailer through improving the quality by using innovation over time. It is assumed that both advertising and enhanced quality play positive roles in customers' loyalty over time for the NB product. We propose four scenarios, including: (1) Decentralized (D), (2) Centralized (C), (3) Coordination with a revenue-sharing contract (RSH), and (4) Coordination with a two-part tariff contract (TPT). A Stackelberg differential game model is developed, and parametric analyses and managerial insights are provided based on a numerical example. Our results show that: (1) Introducing a PSB product alongside selling the NB product is profitable for the retailer, (2) In Scenario D and RSH, the manufacturer tries to increase the quality gap with the PSB product through innovation, (3) Customers' loyalty leads to higher prices, levels of innovation, quality, and advertising for the NB product, (4) The TPT contract can lead to perfect coordination and yield higher profits for the manufacturer and the retailer. [ABSTRACT FROM AUTHOR]

This paper examines demand information value and acquisition strategy for a supply chain composed of a supplier and a retailer under supplier encroachment, and considers the situation that both the enterprises can obtain information directly from the market. The problem is formulated with a Bayesian game model. A signaling mechanism is considered, i.e., the supplier's demand information will be signaled to the retailer through wholesale pricing. Under the signaling mechanism, this paper analyzes whether it is still worthy to the supplier and the retailer of acquiring information at a non-ignorable cost under dual information asymmetry. Moreover, this paper examines the interaction between channel substitution rate and information acquisition. Furthermore, subsidies for inducing information sharing and the signaling effects on the payoffs are also explored. The results propose strategy selections of encroachment and information acquisition based on cost thresholds. A double information inaccuracy effect is discovered, which comes from the fact that an enterprise receives the signal from another supply chain member as well as acquires information from the market. It is interesting to find that the information inaccuracy does not necessarily have a negative effect due to double information inaccuracy. The inaccuracy rate has a positive effect first and then a negative effect on the payoffs of the supply chain under certain conditions. The value of signaling of demand information is analyzed, revealing that lower substitution rate will make the signaling mechanism have a positive impact on the enterprises payoffs. Some managerial insights are presented in the end. [ABSTRACT FROM AUTHOR]

In addition to Internet-of-Things security, such as zero trust and supply chain issues, the environment surrounding secure components is rapidly changing due to advances in digital trust technologies such as confidential computing and digital identity. This article introduces the standardization trends in Global-Platform in response to these latest changes in the security environment. [ABSTRACT FROM AUTHOR]

The assembly of modular containers using building information modelling (BIM) technologies was studied. The purpose of this study was to analyse the literature on prefabricated (prefab) houses and explore the concept of creating a digital prototype of a building based on Huoshenshan hospital using Autodesk Revit software. This hospital was constructed to treat Covid-19 patients in early 2020. The article describes the methodology of installing modular containers and assembly structures using BIM technologies for rapid construction. The results of this study showed that building object implementation depends directly on a proper model with a step-by-step mechanism for installation. Due to the supply of prefab structures at the construction site, both initial project cost and project time can be reduced. Prefab house technology demonstrated the high efficiency of using BIM technology in the assembly of Huoshenshan hospital, which was constructed in 10 days. The need for information modelling data exchange with modern technology and systems, which allows the team to become acquainted with the project before installation work starts at the construction site, is investigated. [ABSTRACT FROM AUTHOR]

Summary: The meat industry plays a vital role in India's economy, contributing significantly to employment and GDP. In recent years, there has been a growing interest in digitalising the meat supply chain in India to address these challenges and enhance efficiency, transparency, and traceability. Digitalisation enables real‐time monitoring of environmental conditions, such as humidity and temperature, during storage and transportation, ensuring optimal preservation of meat products. Government initiatives, such as the Digital India programme and the Atma‐Nirbhar Bharat Abhiyan, provide support and incentives to foster digitalisation in the meat industry and other sectors. This study analysed the implementation of digital technologies and supply chain performance as the involvement of top management commitment is crucial while carrying out this task. It supports that the implementation of digital technologies would lead to an increase in supply chain collaboration and it further would lead to an increase in supply chain performance. This study will help robust and more unified supply chain by connecting the stakeholders digitally as well as by applying digital technologies for smooth industry operations. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the relationship between institutional pressures, supply chain integration and supply chain performance in the wooden furniture industry. Cross-sectional survey data collected from 86 registered wooden furniture firms in Uganda were analyzed using Partial Least Square Structural Equation Modeling. The study revealed that institutional pressures are positively and significantly related with supply chain performance and that supply chain integration plays a partial mediating role in the institutional pressures-supply chain performance relationship. Further, our component level analysis of institutional pressures reveals that whereas coercive pressure has a discernible positive influence on both supply chain integration and supply chain performance, mimetic pressure does not, while normative pressure positively influences only supply chain integration. These results underline the need to understand the role of individual components of institutional pressures and integration requirements in strategic supply chain management practice in order to boost supply chain performance of the wooden furniture firms. [ABSTRACT FROM AUTHOR]

In today's global business competition environment, the significant changes in the market environment make it very difficult for supply chain enterprises to gain a place in the fierce market only by their strength. This article will do the following research work to effectively play the role of supply chain management. First, the concepts, and characteristics, related applications of supply chain information sharing (IS) and genetic algorithm back propagation (GABP) neural networks, are expounded. Then, the feasibility of applying BP neural network (BPNN) to evaluate supply chain IS is analysed. Next, the assessment indicator system for IS is constructed from four aspects: IS infrastructure, IS member characteristics, IS content, and the quality of supply chain enterprises. Finally, the principle and algorithm of BPNN are analysed, the network model is constructed, the BPNN process based on GA is designed, and every step in the process is explained in detail. The sample input is provided for the network model by obtaining and sorting data. The supply chain IS assessment model based on the GABP neural network is constructed. The results show that the assessment model of supply chain IS based on the GABP neural network has high accuracy, and the highest network accuracy reaches 95.01%, which proves that the assessment model based on BPNN has certain advantages for the supply chain IS of the financial industry. [ABSTRACT FROM AUTHOR]

Image recognition is the key to smart logistics systems. Traditional handwriting feature extraction is difficult to meet the requirements of image recognition. Deep learning is used for image recognition. Firstly, convolutional neural network (CNN) and deep Boltzmann machines under deep learning are introduced. Second, cellular neural networks are used to perform feature recognition and extraction on images. Finally, a Parzen classifier is used to classify the obtained image features. The novelty is that through the structural design and research of the intelligent logistics system, the CNN is combined to construct a management system of supply chain logistics of image recognition and information processing. The experimental results show that the recognition accuracy time of the proposed improved fusion algorithm on the Mixed National Institute of Standards and Technology data set is 198.85 s. When the improved algorithm achieves the same recognition accuracy, it takes 159.65 s. The recognition efficiency of the improved algorithm is 19.71% higher than that of the unimproved algorithm. In addition, when the unimproved algorithm reaches the maximum number of iterations, the error rate is 2.47%. The error rate of the improved algorithm is only 0.74%. This study provides a basis for improving the image recognition accuracy and has certain practical value. [ABSTRACT FROM AUTHOR]

Supply chain risk management is crucial for the management of sports goods companies, which can help enterprises better complete the transparent and efficient management of the whole process from production to sales. However, there are inevitably some potential risks. Thereby, to study the supply chain risk management of badminton supplies companies in the general environment, the supply chain risk evaluation index system of badminton supplies companies is established in this study by studying the connotation of supply chain risk management and combining the steps of fuzzy comprehensive evaluation (FCE) method. Then, according to these evaluation indexes, the modelling process of the classification and regression tree (CART) algorithm in the corporate overall supply chain risk decision tree is proposed. Moreover, the corporate overall supply chain risk decision tree is established. Moreover, the financial data of 10 A‐share listed companies of badminton and other sports goods listed on the Shanghai Stock Exchange in 2020 are selected as the sample dataset for model training and testing. The potential risks of badminton enterprises are predicted. The results show that the scale of badminton enterprises has been increasing gradually since 2018, but the return on total assets has steadily decreased with the increase of years. It shows that the badminton supplies enterprise's input and output assets are unbalanced, and the overall asset operation effect is relatively poor. However, the growth rate of total assets shows a significant upward trend from 2018 to 2020, rising from 4% to 12.69%. It indicates that the corporate investment and domestic and foreign investment expansion in recent years are high‐speed. The FCE method is employed to obtain the maximum eigenvalue λmax of the enterprise, which is 5.4698. Then, the C.I value is 0.1205, the R.I value is 1.12, and the consistency ratio value is 0.0958 < 0.1, indicating that the judgement matrix is acceptable. It suggests that under the influence of the macro environment and economic situation, the sales situation of the badminton supplies company is subtly affected by the macro environment, and there is a great business risk. [ABSTRACT FROM AUTHOR]

The classification of musical emotion is a challenging problem due to the subjectivity of human perception. In order to analyse the emotion contained in music from the perspective of product supply chain management, the psychological model and characteristics of music emotion are introduced. Additionally, the current product supply chain and the composition of the two contracts are analysed based on the characteristics of online music products. Finally, a speech emotion recognition model based on a Fuzzy Cognitive Map (FCM) is proposed. Two corpora containing five emotions (sadness, anger, happiness, surprise, and boredom) are selected to test the performance and characteristics of the network. In order to evaluate the system performance, different acoustic features are extracted, including prosodic features, formant features, marginal spectral features, and Mel‐Frequency Cepstral Coefficients (MFCC). The results show that the average recognition rate of MFCC features on the Berlin emotional speech database is 70.36%, which is 0.75% higher than the second‐highest edge spectrum features and achieves better results. Meanwhile, on this database, the Musical Emotion Recognition System based on FCM (MERS‐FCM) is improved by 20.36%, 7.34%, and 4.12% compared with Back Propagation, K‐nearest neighbour, and support vector machine, respectively, which shows that MERS‐FCM has better performance. The research of the music emotion recognition system based on FCM can provide more reference paths for the use and development of music emotion information. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) technology has brought new reconstruction opportunities for the intelligence of the advertisement industry through the help of AI technologies such as machine learning and deep learning. First, the relationship between AI and the attractiveness of green advertisements is investigated, and the influence of different AI technologies in green advertisements on consumers' perception of the attractiveness of green advertisements is summarized. Second, based on the green advertisement dissemination rate data set, the data visualization exploration is carried out, and the data deletion and coding processing are carried out aiming at different characteristic variables. Finally, according to the problems existing in the current green advertisement communication and the high‐dimensional and sparse characteristics of the communication rate data set. In this paper, based on Deep FM (Factorization Machine), Gradient Boost Decision Tree (GBDT) is added to assist the experiment, and the prediction performance of green advertising communication is tested. The results are as follows. (1) Different AI expressions in green advertisements will affect consumers' perception of the attractiveness of green advertisements. (2) The prediction ability of Deep FM model after feature engineering is better than that of data cleaning only. The prediction effect of the model is obviously improved. The purpose of this paper is to integrate green advertising media communication into the ecological concept of harmonious coexistence between man and nature, strengthen the political belief of ecological civilization construction, and conform to the communication trend of today's severe ecological situation. [ABSTRACT FROM AUTHOR]

This exploration aims to promote the development of ice and snow sports (ISS), strengthen people's physiques and improve people's health level. First, the fuzzy comprehensive evaluation method is adopted to determine the importance weight of the intelligent cognitive factors of ISS. Then, based on the evaluation grade, the membership matrix of intelligent cognitive factors of ISS is constructed, and an individual cognitive ability evaluation model combining qualitative analysis with quantitative analysis is established. Statistical Product and Service Solutions (SPSS) 25.0 and Smartpls software are further used to determine the questionnaire items about the participation intention in ISS training. A structural equation model among individual participation intention, theoretical factors of planned behaviour and participation behaviour is constructed. After analysing the data obtained from the survey, the final results are as follows. (1) Harbin's largest number of ISS participants is 18–29 years old, accounting for 44.8%. Undergraduate education accounts for 47.5%. The number of participants whose monthly income is 6001–12,000 is the largest, accounting for 25%. (2) The number of people participating in skating is the highest, reaching 59.7%. The proportion of people who have participated in ISS for one year or less is the highest, reaching 45.8%. From the consumption amount perspective, the people spending 1000 yuan and below account for the highest proportion, so the consumption degree of ISS is mainly experiential consumption. (3) The correlation coefficient between subjective norms and individual participation intention is 0.598, indicating that the relationship between the two is significantly positive, that is, subjective norms will have a certain impact on individual participation intention. The correlation coefficient between behaviour attitude and participation intention is 0.697, indicating that the relationship between them is significantly positive. The correlation coefficient between perceived behaviour control and participation intention is 0.745, indicating a significant positive correlation between them. The research content provides a theoretical basis for the follow‐up ISS training intelligent cognition. It can also provide a reference for the further development of ISS in China. [ABSTRACT FROM AUTHOR]

In order to create higher benefits for enterprises in the university supply chain and make them meet the requirements of sustainable development, this study uses information ecology theory to study the cognitive management and transformation path of the green supply chain. Firstly, the related concepts of university supply chain management and green supply chain management are expounded, and the differences are mainly discussed. Then, the evaluation of supply chain greenness is studied. The fuzzy hierarchical comprehensive evaluation method combining quantitative and qualitative is used to establish the evaluation model. Finally, the proposed evaluation model is tested. The test results show that Suzhou University's greenness fuzzy evaluation score is 58.2 points, which is a medium level. The resource factor scored 61 points, the energy factor scored 52.9 points, the environmental factors scored 59.8 points, the economic factor scored 62.7 points, and the social factor scored 55.5 points. The company has obvious advantages in terms of resources and economy, but the level is not very high. The higher the cost synergy between enterprises and customers, the greater the environmental cost synergy. Therefore, manufacturing enterprises should strengthen communication and cooperation with customers. The higher the cost synergy control of manufacturing and waste recycling enterprises, the greater the synergy effect of environmental cost control. Therefore, increasing cooperation with waste recycling enterprises is conducive to developing environmental cost control and coordinated benefits. The proposed scheme provides some ideas for applying information ecology theory in the university supply chain. [ABSTRACT FROM AUTHOR]

This work aims to avoid the complex control process caused by complex coupling and serious interference of control variables in traditional greenhouse environmental control and achieve the adaptive control of agricultural greenhouse. This work studies smart agricultural greenhouses' adaptive control and supply chain management based on the intelligent fuzzy auxiliary cognitive system (IFACS). This work firstly expresses the intelligent fuzzy control theory and analyses data according to the fuzzy control set. Secondly, the adaptive control and supply chain management of the intelligent agricultural greenhouse are studied by using an intelligent fuzzy aided cognitive system. Finally, the light intensity and carbon dioxide content of the intelligent agricultural greenhouse are analysed; the temperature and humidity content of the intelligent agricultural greenhouse of the traditional control method and adaptive control are compared; the impact of carbon dioxide emissions on the environment under supply chain management is analysed. The research results indicate that the adaptive control of the intelligent agricultural greenhouse based on the IFACS can keep the greenhouse temperature within a specific range and reduce the impact of temperature on the development of agricultural greenhouses. The IFACS is effectively managed in the adaptive control of the intelligent agricultural greenhouse. From 2015 to 2020, the smart agricultural greenhouse supply chain management gradually reduced the content of greenhouse gas (GHG) emitted by the production and suppliers through the IFACS. The content of greenhouse gases emitted by product transporters did not change significantly, and the greenhouse gases emitted by non‐manufacturing suppliers gradually decreased. In 2020, supply chain GHG emission intensity decreased by 20% compared with 2015, and GHG emissions from product transportation also decreased by 6% compared with the previous year. This research has reference significance for the adaptive control of intelligent agricultural greenhouse by IFACS and the environmental control of agricultural greenhouse by supply chain management. [ABSTRACT FROM AUTHOR]

The traditional enterprise decision evaluation model based on neural network has the problems of mismatch with the optimal solution and slow convergence speed. In order to enable companies to make decisions that are in line with changes in the market, the particle swarm optimization (PSO) algorithm is used to optimize deep learning neural networks. Firstly, the model parameter setting is improved, and the inertia weight strategy of normal distribution attenuation is combined. On this basis, a normal distribution decay inertial weight particle swarm optimization (NDPSO) is proposed. The inertia weight of the optimized algorithm maintains a large value in the initial stage, which makes the PSO algorithm maintain a large step size in the optimization process and a small value in the later stage. Through experimental analysis, the trend parameter of the best normal distribution of the algorithm is obtained as 0.4433 and then using the detection function, the NDPSO algorithm is tested by two types of test functions. The NDPSO algorithm is compared with the optimization results of other algorithms which are optimized on the Sphere function. The minimum value of 554.29, the average value of 2032.11, and the standard deviation of 918.47, all of them are at the leading level. Taking into account other experimental results, it is proved that the normal distribution decay inertia weight can balance the global search and local development capabilities from the perspective of parameter improvement. It can speed up the convergence with ensuring the convergence accuracy. The improved PSO algorithm has certain optimization capabilities for neural network models. The use of optimized neural network models can enable companies to make decisions in line with changes in the market and optimize the dynamic relationship network of the company's supply chain, which is of great significance to the implementation of the company's international management. [ABSTRACT FROM AUTHOR]

The components of the logistics and supply chain are analysed to meet the needs of supply chain management and decision support, aiming at the complexity and uncertainty of the supply chain system. First, the characteristics of logistics demand and logistics service types of some enterprises are analysed. The factors affecting supplier selection are obtained through the questionnaire survey of some enterprises. Second, the mutual feedback relationship between the influencing factors of logistics service demand is analysed, and a fuzzy cognitive graph model of the selection process of enterprise logistics service providers is established. Finally, the fuzzy cognitive map (FCM) model is used to conduct an empirical study on the choice of logistics service providers. The results show that the ranking results of the three candidate logistics service companies based on FCM are WL1 (0.7233) > WL3 (0.6823) > WL2 (0.6764). When each node of the concept does not affect each other, the ranking result of the three candidate logistics service companies based on analytic hierarchy process (AHP) is WL1 (0.7265) > WL2 (0.6949) > WL3 (0.6920). The final evaluation result will be affected by the mutual influence relationship between the concept nodes. Overall, the lowest evaluation score is WL2, and the highest is WL1. The most suitable logistics service provider for the enterprise is WL1. The FCM model selected by the manufacturing enterprise logistics service provider is reasonable and feasible. The mutual feedback between evaluation factors affects the selection of logistics service providers in a company. The FCM can get a more accurate evaluation weight value and can realize the optimal choice of logistics suppliers. It provides reference and decision support for other enterprises. [ABSTRACT FROM AUTHOR]

In order to explore the international competitiveness of China's agricultural product supply chain, this paper combines machine learning algorithms to optimize the data processing process of agricultural product supply chain, and proposes a data processing method for agricultural product supply chain based on the intra‐column rules and inter‐column rules. According to the problems of my country's agricultural product supply chain, this paper establishes a new agricultural product supply chain management model based on the various modules of the supply chain link, and constructs a corresponding intelligent analysis model. Moreover, this paper combines machine learning algorithms to study the improvement path of the international competitiveness of China's agricultural product supply chain, and builds an intelligent model to improve the international competitiveness of China's agricultural products. Finally, after constructing the model, this paper obtains the path to improve the international competitiveness of China's agricultural products through the simulation operation model, which also verifies the effectiveness of the intelligent algorithm of this paper from the side. [ABSTRACT FROM AUTHOR]

Despite unprecedented quality improvement and defect prevention measures, producing a complete lot of perfect items is still highly unlikely due to the degradation of machines and processes over time. The previous studies on supply chains with defective/imperfect items have explored options such as process quality improvement investments, reworking, selling at a salvage value, or disposing of these items at an additional cost. This paper, contrary to existing literature, categorizes defective items into three types based on the level of imperfection: slightly, moderately, and highly defective items, and determines the optimal lot size for perfect and defective items. The focus is to develop a supply chain model for a single manufacturer and multiple retailers in the presence of defective items and manage defective products based on quality to generate profit from low-defective products rather than traditional defect rate reduction methods. Numerical examples and sensitivity analyses are presented to demonstrate the effectiveness of the proposed model in improving the total profit of the supply chain by optimizing production quantities. [ABSTRACT FROM AUTHOR]

Background: The Global Fund partnered with the Zimbabwean government to provide end-to-end support to strengthen the procurement and supply chain within the health system. This was accomplished through a series of strategic investments that included infrastructure and fleet improvement, training of personnel, modern equipment acquisition and warehouse optimisation. This assessment sought to determine the effects of the project on the health system. Methods: This study employed a mixed methods design combining quantitative and qualitative research methods. The quantitative part entailed a descriptive analysis of procurement and supply chain data from the Zimbabwe healthcare system covering 2018 – 2021. The qualitative part comprised key informant interviews using a structured interview guide. Informants included health system stakeholders privy to the Global Fund-supported initiatives in Zimbabwe. The data collected through the interviews were transcribed in full and subjected to thematic content analysis. Results: Approximately 90% of public health facilities were covered by the procurement and distribution system. Timeliness of order fulfillment (within 90 days) at the facility level improved from an average of 42% to over 90% within the 4-year implementation period. Stockout rates for HIV drugs and test kits declined by 14% and 49% respectively. Population coverage for HIV treatment for both adults and children remained consistently high despite the increasing prevalence of people living with HIV. The value of expired commodities was reduced by 93% over the 4-year period. Majority of the system stakeholders interviewed agreed that support from Global Fund was instrumental in improving the country's procurement and supply chain capacity. Key areas include improved infrastructure and equipment, data and information systems, health workforce and financing. Many of the participants also cited the Global Fund-supported warehouse optimization as critical to improving inventory management practices. Conclusion: It is imperative for governments and donors keen to strengthen health systems to pay close attention to the procurement and distribution of medicines and health commodities. There is need to collaborate through joint planning and implementation to optimize the available resources. Organizational autonomy and sharing of best practices in management while strengthening accountability systems are fundamentally important in the efforts to build institutional capacity. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been an unprecedented challenge for humanity, causing widespread disruptions to daily life and economies worldwide. However, amidst the challenges, it has also presented an opportunity to reflect on our competencies, capabilities, and objectives. One area that has gained significant attention during this time is the humanitarian supply chain management theories, which offered significant directions to the scholars engaged in operations and supply chain management, practitioners and policymakers. To further advance the theoretical boundaries of the humanitarian supply chain and expand the scope and boundaries of the discipline, a special issue has been organised. This issue includes 24 carefully selected articles that have gone through multiple rounds of review. The articles are all centred on the humanitarian crisis resulting from COVID-19 and offer a comprehensive understanding of the challenges faced by various stakeholders. Additionally, one relevant article from a previous issue has been included, which explores the potential use of drones in disaster relief operations. The articles included in this special issue have significant implications for theory, practice, and policy, providing valuable insights and direction for further research to expand the scope of the discipline. This particular issue is a crucial contribution to humanitarian supply chain management. It provides a deeper understanding of the complex challenges faced during a crisis and the best practices to overcome them. [ABSTRACT FROM AUTHOR]

The COVID-19 global health crisis forced border closings, strained resources and tightened funding, forcing humanitarian organisations to innovate. This paper aims to identify gaps in the literature on innovation in humanitarian supply chains, and to develop an appropriate framework for future research through a systematic literature review. We use a systematic literature review approach and synthesis the discussion of innovation in humanitarian supply chains after reviewing 43 papers. The synthesis identifies the different contexts for and outcomes of innovation in humanitarian supply chains. Our findings indicate that research on innovation in humanitarian supply chains is an underdeveloped topic. Gaps we identified in regards to the humanitarian context are: (1) a limited discussion of the contribution by the beneficiary to the supply chain; (2) a limited discussion of reconstruction innovations; (3) a lack of study on field application for complex innovations; (4) the lack of discussion of the role of individual knowledge in humanitarian supply chain innovation and finally (5) a lack of study of position innovations where humanitarian organisations use supply chains as a way to market effectively towards donors. [ABSTRACT FROM AUTHOR]

Disruption from the COVID-19 pandemic has caused major upheavals for manufacturing, and has severe implications for production networks, and the demand and supply chains underpinning manufacturing operations. This paper is the first of its kind to pull together research on both—the pandemic-related challenges and the management interventions in a manufacturing context. This systematic literature review reveals the frailty of supply chains and production networks in withstanding the pressures of lockdowns and other safety protocols, including product and workforce shortages. These, altogether, have led to closed facilities, reduced capacities, increased costs, and severe economic uncertainty for manufacturing businesses. In managing these challenges and stabilising their operations, manufacturers are urgently intervening by—investing in digital technologies, undertaking resource redistribution and repurposing, regionalizing and localizing, servitizing, and targeting policies that can help them survive in this altered economy. Based on holistic analysis of these challenges and interventions, this review proposes an extensive research agenda for future studies to pursue. [ABSTRACT FROM AUTHOR]

The procurement of food grains from farmers is one of the biggest challenges under the COVID-19 outbreak due to country-wise lockdowns. The present study aims to reconfigure the existing food grain supply chain network. The study advances the extant literature by proposing a novel mathematical model that considers the government guidelines issued to procure food grains from farmers under the COVID-19 situation. The model includes personal distancing, a key parameter relevant in the COVID-19 crisis, and has remained unaddressed in the existing literature. The proposed model is tested in India. The effect of different parameters like personal distancing cost, carbon emission cost, fixed cost, and transportation cost is also investigated under a given set of procurement centers. Finally, the procurement schedule for each procurement center is generated, which is especially useful for managing its activities and is also helpful to farmers to streamline the process. Results indicate that the proposed model is highly effective under pandemic emergencies like the current COVID-19 crisis. Policymakers and the government will find this model helpful in drafting relevant policies regarding food grain procurement under emergencies such as the COVID-19 outbreak. The distribution segment of the supply chain network is not part of the present research work. In future studies, this part could be then added to the whole of the procurement process, and both procurement and distribution can be assessed together again. [ABSTRACT FROM AUTHOR]

Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the "new normal" have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as "disruption tails." While the research community has undertaken considerable efforts to predict the pandemic's impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control. [ABSTRACT FROM AUTHOR]

To meet the projected increase in global demand for energy while tackling sustainability concerns, the widespread adoption of renewable energy is inevitable. Once harnessed, exports of this renewable energy from regions with excess resources are anticipated to those that will require imports of energy. The shipping sector will thus play a pivotal role in enabling such trade through energy carriers such as hydrogen, ammonia, methanol, and liquid organic hydrogen carriers. Furthermore, in addition to these energy carriers, carbon dioxide is also expected to become an important maritime trade commodity to achieve climate targets. Through the deployment of carbon capture utilization and storage, and more recently, negative emission technologies, carbon dioxide will need to be transported to regions with the appropriate infrastructure and resources necessary for their anticipated implementation. Presently, in light of these circumstances, the lack of experience in shipping a number of these energy carriers and carbon dioxide must be addressed. As such, an understanding of the techno-economic and environmental feasibility of the large-scale shipping of these commodities must be established at all scales of operation. Accordingly, this work proposes the use of process systems engineering based approaches to enable the marine transportation of these future energy carriers and carbon dioxide from a multi-scale perspective. To lay the foundation in support of this initiative, a framework that considers the multiple scales involved is then presented for the design and operation of progressive ships and their supply chains as part of a decarbonized energy system. [Display omitted] • Discussed the potential of shipping energy carriers and carbon in achieving climate targets. • Identified feasibility challenges surrounding the large-scale shipping of hydrogen carriers. • Proposed a multi-scale framework for the design of ships and supply chains. [ABSTRACT FROM AUTHOR]

In recent years, blockchain technology has attracted substantial interest for its capability to transform supply chain management and finance. This paper employs evolutionary game theory to investigate the application of blockchain in mitigating financial risks within supply chains, taking into account the technology's maturity and the risk preferences of financial institutions. By modeling interactions among financial institutions, small and medium enterprises (SMEs), and core enterprises within the accounts receivable financing framework, this study evaluates blockchain's impact on their decision-making and its efficacy in risk reduction. Our findings suggest the transformative potential of blockchain in mitigating financial risks, solving information asymmetry, and enhancing collaboration between financial entities and SMEs. Additionally, we integrate smart contracts into supply chain finance, proposing pragmatic procedures for their deployment in real-world contexts. Via a detailed examination of blockchain's maturity and financial institutions' risk preferences, this research demonstrates the primary determinants of strategic decisions in supply chain finance and underscores how blockchain technology fosters system stability using risk mitigation. Our innovative contribution lies in the design of smart contracts for the ARF process, rooted in blockchain's core attributes of security, transparency, and immutability, thereby ensuring efficient operation and cost reduction in supply chain finance. [ABSTRACT FROM AUTHOR]

This article thoroughly examines the influence of digital transformation on the efficiency of corporate supply chains. As global economic integration accelerates and technological innovations deepen, digital transformation has become key to enhancing core corporate competitiveness. This research, utilizing data from A-share listed companies in China between 2007 and 2022, analyzes how companies improve supply chain efficiency through digital transformation. Furthermore, the study establishes a theoretical framework that demonstrates how digital transformation facilitates supply chain efficiency from the perspectives of internal governance and external competition. The research indicates that digital transformation plays a key role in significantly enhancing supply chain efficiency. Furthermore, the results of the mechanism analysis confirmed that digital transformation contributes to enhancing corporate supply chain efficiency by improving the level of corporate governance and the degree of market competition. The study also finds that the effect of digital transformation on supply chain efficiency varies with different corporate backgrounds, indicating its heterogeneous impact. Lastly, an analysis of economic consequences shows that the increased supply chain efficiency resulting from digital transformation can reduce future external transaction costs, strengthening the company's market position and financial performance. This research provides strategic guidance for firms to develop robust strategies amid the digital wave and offers strong policy recommendations for promoting digital supply chain management and enhancing market adaptability. [ABSTRACT FROM AUTHOR]

During the past three decades the world has been witness to an alarming increase in the shortage of drugs and biomedical products in the field of anesthesia and surgical care. This situation can be particularly challenging when there are no therapeutic alternatives available, as is the case with some supplies and drugs for perioperative use. Anesthesiologists, who play a crucial role in the preparation of the drugs they administer, are particularly aware of these shortages. The reasons for these shortages are diverse and involve problems in supply, demand and government regulation. Among the causes identified are the increase in demand, bidding systems and the sustainability challenges faced by pharmaceutical companies. It is essential to understand these causes in order to seek strategies to reduce the risk of shortages of medicines and supplies. Addressing this challenge requires improving supply chain management, fostering transparency in information on stock-outs, promoting local production of medicines, and strengthening procurement and distribution regulations and policies. The solution to this problem requires a comprehensive and collaborative approach, with multiple stakeholders working together to ensure adequate access to needed medications in the anesthesia and surgical care setting. [ABSTRACT FROM AUTHOR]