Supply Information Research Articles

Research on Collaborative Strategy of Supply Chain Management under the Background of NIKE Mass Customization

Abstract: With the continuous advancement of technology and the popularization of the Internet, consumers' demand for personalized products is increasingly high. Traditional production modes have been unable to meet consumers' demands for product uniqueness and personalized experiences, which requires manufacturing enterprises to shift towards mass customization modes with unique advantages in production efficiency and cost control. Taking Nike as an example, this paper analyzes its supply chain problems based on its financial report. It then explores Nike's mass customization process using C2M and 3D printing, as well as information collaboration methods in the supply chain. Additionally, the paper analyzes AR-based virtual fitting technology and evaluates Nike's internal matrix organizational structure for customization and collaboration. From the perspectives of Nike's technology level and internal organizational structure, this paper analyzes the supply chain management and information collaboration process in its mass customization process, aiming to provide references for related manufacturing industries in enterprise operation and technology application during the mass customization process.

Bond supply expectations and the term structure of interest rates

This paper investigates the influence of forward-looking government bond supply information on changes in the term structure of interest rates. While traditional arbitrage-free models suggest that bond supply should not impact bond yields, models accounting for preferred-habitat investors and imperfect asset substitutability raise this possibility. By analysing debt supply expectations derived from Germany's Treasury press releases, we find that news about expected bond supply affects bond yields, supporting the notion that supply expectations influence current interest rates. Our study also extends macro-finance models, highlighting the significant role of supply expectations in term structure dynamics. Additionally, we provide insights into the puzzle of German government bond yields falling below the ECB deposit rate.

Information sharing's impact on supply chain management, logistics, and organizational performance

This study investigates the relationships between supply chain management (SCM), logistics capability, information sharing, and organisational performance. Data was collected from 120 respondents in [industry/sector] using a quantitative research approach. The results of the analysis indicate that SCM, logistics capability, and information sharing are all positively and significantly related to organisational performance. Effective SCM practices, including integration, collaboration, and strategic planning, are essential for driving organisational success. Logistics capability, including delivery speed, dependability, and flexibility, is crucial in improving customer satisfaction and overall efficiency. Information sharing is a critical enabler of effective SCM and organisational performance, fostering collaboration, decision-making, and innovation. The study also found that demographic factors (gender, age, education) had limited impact on the relationships between the constructs. This suggests that the findings are generally applicable across different demographic segments. Overall, this study's findings highlight the importance of effective SCM, logistics capability, and information sharing as key drivers of organisational performance. Organisations prioritising these factors are more likely to achieve sustainable success in today's competitive business environment.

Fight, retreat, repeat: The male-male agonistic behavior in the wood-feeding cockroach, Panesthia angustipennis spadica (Dictyoptera: Blattodea: Blaberidae).

Competition is one of the most critical factors affecting animal behaviors. Aggressive interactions are central to acquiring resources or mating partners. Agonistic behavior is more common among males than females. Although laboratory observations of these behaviors give detailed descriptions under controlled conditions, field observations without human intervention are required because those supply information that provides insights into their function. In this paper, we report on the field observation and auxiliary laboratory experiments of male-male agonistic behavior of a wood-feeding cockroach, Panesthia angustipennis, and discuss its strategy. In the field, a male pushed the opponent with the horn on the pronotum out of a gap between two logs, under which a female was. After pushing, the male repeatedly returned to a place close to the female, even if it did not subdue the opponent entirely. It suggests that the male-male agonistic behavior in P. angustipennis has both attack and avoidance. The bout was repeated as the ejected male reapproached the male. In contrast, the inferior male often escaped in the laboratory recording after field observation. Keeping the fighting experience for several days may contribute to the males avoiding a "losing battle." This study significantly enhances our understanding of the mating strategy of P. angustipennis through male-male agonistic behavior and provides possibilities for its cognitive aspects from the fighting experience.

Achieving supply chain sustainability: enhancing supply chain resilience, organizational performance, innovation and information sharing: empirical evidence from Chinese SMEs

PurposeThis study aimed to explore the relationship between supply chain resilience (SCR) and organizational performance (OP), with innovation (INN) serving as a mediator and information sharing (IS) acting as a moderator.Design/methodology/approachThe study comprehensively examined the connections between SCR, OP, INN and IS. An exploratory approach and quantitative methods were employed. The data were collected from small and medium-sized manufacturing enterprises of three cities Xian, Hainan and Guangzhou of China via online questionnaire surveys conducted through Emails and WeChat. SmartPLS-4 was used for data analysis.FindingsThe findings indicated that SCR has a positive effect on sustainability efforts. Additionally, INN and effective IS both mediated and moderated this relationship, playing crucial roles in improving sustainability within the supply chain.Practical implicationsThe study offered practical insights for businesses to enhance their sustainability efforts. Managers can use these findings to develop strategies that improve SCR, foster INN and encourage effective IS, ultimately resulting in a more sustainable supply chain.Originality/valueThis study enriched the existing knowledge base by investigating the intricate relationships among SCR, OP, INN and IS, all within the context of achieving sustainability. By exploring these elements holistically, the research introduced originality and highlighted effective strategies for sustainable supply chain management.

Qualitative study on health self-management of patients with metabolic syndrome among bereaved population after earthquake

The study explore the influencing factors and healthy self-management of MS patients with bereaved relatives after Wenchuan and Yushu Earthquake of their real life; explore difficulties and challenges in the process of self-management; and supply information that could not be sought in quantitative studies. Purposive sampling was used to recruit 36 MS patients who are bereavement population in two earthquakes, and those patients met the inclusion criteria for semi-structured focus group interview. The Nvivo11 software was used to collate and analyze the transcribed data. The main influencing factors of health self-management behavior for MS patients are as follows: the degree of understanding of disease prevention knowledge, emotion management induced by earthquake trauma, the source of disease-related information, access and identification are very limited; ethnic traditional culture, religious beliefs, and production activities and routines before and after the earthquake is an important factor in their healthy self-management behavior. The lack of health beliefs and self-efficacy of MS patients among bereaved families after Wenchuan and Yushu earthquake are key obstacle in their self-management. The overall level of the knowledge of patients’ MS prevention, self-efficacy and self-management behaviors are still low. Some positive factors that can be changed including MS prevention knowledge, self-efficacy, social support, and family function. Some negative factors which can be improved afterwards, including negative coping style, traumatic life experiences from earthquake and smoking.

An ML-Based Solution in the Transformation towards a Sustainable Smart City

The rapid development of modern information technology (IT), power supply, communication and traffic information systems and so on is resulting in progress in the area of distributed and energy-efficient (if possible, powered by renewable energy sources) smart grid components securely connected to entire smart city management systems. This enables a wide range of applications such as distributed energy management, system health forecasting and cybersecurity based on huge volumes of data that automate and improve the performance of the smart grid, but also require analysis, inference and prediction using artificial intelligence. Data management strategies, but also the sharing of data by consumers, institutions, organisations and industries, can be supported by edge clouds, thus protecting privacy and improving performance. This article presents and develops the authors’ own concept in this area, which is planned for research in the coming years. The paper aims to develop and initially test a conceptual framework that takes into account the aspects discussed above, emphasising the practical aspects and use cases of the Social Internet of Things (SIoT) and artificial intelligence (AI) in the everyday lives of smart sustainable city (SSC) residents. We present an approach consisting of seven algorithms for the integration of large data sets for machine learning processing to be applied in optimisation in the context of smart cities.

Category Mapping of Emergency Supplies Classification Standard Based on BERT-TextCNN

In recent years, the escalation in emergency occurrences has underscored the pressing need for expedient responses in delivering essential supplies. Efficient integration and precise allocation of emergency resources under joint government–enterprise stockpiling models are pivotal for enhancing emergency response effectiveness and minimizing economic repercussions. However, current research predominantly focuses on contract coordination and cost-sharing within these joint reserve modes, overlooking significant discrepancies in emergency supply classification standards between government and enterprise sectors, as well as the asymmetry in cross-sectoral and cross-regional supply information. This oversight critically impedes the timeliness and accuracy of emergency supply responses. In practice, manual judgment has been used to match the same materials under differing classification standards between government and enterprise reserves. Still, this approach is inefficient and prone to high error rates. To mitigate these challenges, this study proposes a methodology leveraging the BERT pre-trained language model and TextCNN neural network to establish a robust mapping relationship between these classification criteria. The approach involves abstracting textual representations of both taxonomical classes, generating comparable sentence vectors via average pooling, and calculating cosine similarity scores to facilitate precise classification mapping. Illustrated with China’s Classification and Coding of Emergency Supplies standards and Global Product Classification standards, empirical validation on annotated data demonstrates the BERT-TextCNN model’s exceptional accuracy of 98.22%, surpassing other neural network methodologies such as BERT-CNN, BERT-RNN, BERT-BiLSTM, etc. This underscores the potential of advanced neural network techniques in enhancing emergency supply management across diverse sectors and regions.

Humanitarian supply chain resilience: does organizational flexibility matter?

PurposeThe COVID-19 epidemic caused significant disruptions to numerous supply chains. In order to enhance the resilience of supply chains, Collaboration (CO), Information Alignment (IA), and Big Data Analytics Capability (BDAC) have emerged as contemporary strategies within the humanitarian context. This study was conducted to explore the mechanism via which the effect of BDAC, IA and CO on Humanitarian Supply Chain Resilience (HSCR) in the humanitarian space could be optimized through Organizational Flexibility (OF).Design/methodology/approachA model of six hypotheses was developed based on the Organizational Information Processing Theory (OIPT). Data from 127 supply chain managers in humanitarian organizations were used to test the hypotheses. The analysis employed both descriptive and inferential statistics using SPSS version 26 and Smart-PLS version 3.FindingsThe study revealed that BDAC, IA, and CO individually influence supply chain resilience in the humanitarian setting while OF did not moderate the relationship between BDAC, IA, CO, and HSCR.Practical implicationsIt is essential that humanitarian stakeholders prioritize factors that could increase supply chain resilience by employing contemporary BDA technologies, effective information flow, and collaborative strategies to set up a robust humanitarian SC system that could help lessen the impact of disasters.Originality/valueThis presents interesting insights that advance theoretical debates on how CO, IA, and BDAC under varying levels of OF could influence SCR in the humanitarian context. The paper further offers some useful guidance to managers in relief organizations who desire to build resilient supply chains by leveraging BDAC, collaboration and information alignment. Finally, the paper may also provoke future humanitarian scholars to replicate the study using different approaches.

Navigating uncertainties: impact of supply chain resilience on organizational performance, mediated and moderated model: Pakistan manufacturing sector case

PurposeThis study aimed to investigate the relationship between supply chain resilience and organizational performance with innovation as a mediator and information sharing as a moderator.Design/methodology/approachThe study thoroughly explored how supply chain resilience, organizational performance, innovation and information sharing are connected. It used an exploratory approach and quantitative methods. Data were collected from large manufacturing firms through online questionnaire surveys using Google Forms, emails and WhatsApp.FindingsThe findings demonstrated that supply chain resilience positively impacts sustainability efforts. Furthermore, leveraging innovation and effective information sharing mediated and moderated the relationship, playing pivotal roles in enhancing sustainability within the supply chain.Research limitations/implicationsThe study provided actionable insights for businesses to strengthen their sustainability efforts. Managers could utilize these findings to implement strategies that enhance supply chain resilience, drive innovation and promote effective information sharing, ultimately leading to a more sustainable supply chain.Originality/valueThis study contributed to the existing body of knowledge by examining the complex relationships between supply chain resilience, organizational performance, innovation and information sharing in the context of achieving sustainability. The exploration of these components in a holistic manner added originality to the research and shed light on effective strategies for sustainable supply chain management.

TorchClim v1.0: a deep-learning plugin for climate model physics

Abstract. Climate models are hindered by the need to conceptualize and then parameterize complex physical processes that are not explicitly numerically resolved and for which no rigorous theory exists. Machine learning and artificial intelligence methods (ML and AI) offer a promising paradigm that can augment or replace the traditional parameterized approach with models trained on empirical process data. We offer a flexible and efficient plugin, TorchClim, that facilitates the insertion of ML and AI physics surrogates into the climate model to create hybrid models. A reference implementation is presented for the Community Earth System Model (CESM), where moist physics and radiation parameterizations of the Community Atmospheric Model (CAM) are replaced with such a surrogate. We present a set of best-practice principles for doing this with minimal changes to the general circulation model (GCM), exposing the surrogate model as any other parameterization module, and discuss how to accommodate the requirements of physics surrogates such as the need to avoid unphysical values and supply information needed by other GCM components. We show that a deep-neural-network surrogate trained on data from CAM itself can produce a model that reproduces the climate and variability in the original model, although with some biases. The efficiency and flexibility of this approach open up new possibilities for using physics surrogates trained on offline data to improve climate model performance, better understand model physical processes, and flexibly incorporate new processes into climate models.

Land use change and Ecological Network in rapid urban growth region in Selangor region, Malaysia

Rapid urbanization will cause various land use changes and the vast occupation of green spaces, a critical factor in the deterioration of biodiversity in urbanized areas. Some species of wildlife are endangered due to habitat shrunk and fragmentation. However, Malaysia's current biodiversity protection range is still limited. The Ecological Network (EN) refers to a framework of ecological components, which can be obtained by geographical and technical approaches to support more ecological diversity ranges. Furthermore, little research has been found on EN in Malaysia and the impact of land use change on EN. Therefore, the Selangor region is selected as the study area. This paper quantifies land use change and measures the extent of land use change to obtain the EN’s change. The result has shown that forestland has decreased, explored by people for housing and agriculture from 2000 to 2020. The EN has a trend of fragmentation. Overall, this study's results imply that the land use change led to EN's worsened performance from 2000 to 2020 in the study area. This paper hopes that this research could help supply information on conserving biodiversity in future development and urban sustainable planning in Malaysia.

Cybersecurity in supply chains: Addressing emerging threats with strategic measures

This review paper explores the evolving landscape of cybersecurity threats within supply chains, highlighting strategic measures necessary to mitigate these risks. As supply chains integrate more deeply with digital technologies and global networks, they become more vulnerable to sophisticated cyber attacks that can severely disrupt operational integrity and security. This paper synthesizes existing literature to outline the major cybersecurity challenges faced by supply chains, examining case studies and best practices from various industries. Our findings underscore the prevalent threats such as ransomware, phishing, and insider attacks, which exploit the complex interdependencies and digital interfaces in supply chains. The review identifies effective strategic responses, including the integration of comprehensive cybersecurity frameworks, enhanced inter-organizational cooperation, and the implementation of real-time threat detection systems. Conclusively, the paper advocates for a holistic and proactive approach to cybersecurity, emphasizing continuous improvement and adaptive strategies to protect against the dynamic nature of cyber threats in supply chain contexts. Keywords: Cybersecurity, Supply Chain Management, Risk Assessment, Continuous Monitoring, Incident Response, Blockchain Technology, Artificial Intelligence (AI), Collaboration and Information Sharing, Cyber Threats, Emerging Technologies.

Influence of Supply Chain Integration, Information Sharing, and Supplier Relationships on Operational Efficiency of Manufacturing Companies

This research investigates the influence of supply chain integration, information sharing, and supplier relationships on operational efficiency in manufacturing companies across diverse industries. A quantitative research approach is employed, utilizing surveys to collect data from 300 organizations. Correlation analysis, regression analysis, mediation analysis, moderation analysis, and structural equation modeling are utilized to analyze the data and test hypotheses. The results demonstrate significant positive correlations between supply chain integration, information sharing, supplier relationships, and operational efficiency. Regression analysis confirms the significant impact of these dimensions on operational efficiency, with supply chain integration exhibiting the strongest effect. Mediation analysis reveals that information sharing and supplier relationships partially mediate the relationship between supply chain integration and operational efficiency. Moreover, the moderation analysis highlights industry sector as a significant moderating factor. The findings underscore the strategic importance of supply chain integration, information sharing, and supplier relationships in driving operational excellence and offer actionable insights for supply chain management practitioners.

Spillover effects in transit networks: A parameterized weight matrix spatial lagged approach

Public Transit (PT) systems aim to provide social, economic, and environmental benefits to modern cities offering reliable transportation service to users and ultimately reducing the problems related to traffic externalities due to car dependency. With the growing trend of urbanization and the associated phenomenon of cities’ sprawl being increasingly evident, significant attention should be given to understanding PT systems’ performance and then improving their efficiency. Considering the spatial characteristics of the PT system's performance promotes the environmentally friendly transport “character” that every city endeavors. This paper aims to incorporate the spatial spillover effects of a realistic PT system by augmenting information about the service network along with socio-economic variables, in a spatial demand-supply econometric framework. In detail, geographically separated demand and supply information on bus stops and lines was analyzed by a spatial econometric model, namely, the Spatial Lagged X (SLX) model which may be formatted so that can soundly handle, spatial and –in particular- network data like those coming from the General Transit Feed Specification (GTFS) protocol widely used in PT systems. The novelty and the importance of the proposed model rely on the ability to introduce transit network structure within the framework of spatial econometric regression, fostering the explanatory statistical analysis over networked information. The developed modeling approach was applied to the urban and rural PT system of Nicosia (Cyprus), incorporating the spatial spillover effects of the system over more than 1,500 bus stops, 40 lines, and 252 different but spatially connected postcode areas. The results of the SLX model were compared with other demand models of this form typically used, namely the Ordinary Least Square model and standard Spatial Autoregressive models, providing solid evidence of the benefits of incorporating the network structure in spatial demand modeling, giving valuable input for further planning purposes.

Reviewing Optimization Techniques in Supply Chains: AI and Blockchain Perspectives

The integration of Artificial Intelligence (AI) and Big Data Analytics (BDA) into Supply Chain Management (SCM) has transformed the industry by enhancing efficiency, accuracy, and responsiveness. This review paper provides a comprehensive analysis of current AI applications in SCM, focusing on demand forecasting, inventory management, logistics, and transportation. Various AI techniques, including time-series forecasting, clustering, neural networks, SARIMA, and LSTM models, are discussed in detail. The impact of cutting-edge technologies on supply chain traceability and efficiency, such as blockchain and the Internet of Things (IoT), is also examined in this article. Despite the significant advancements, challenges such as gaps in closed-loop supply chains, terminology inconsistencies, and the need for better technical-managerial alignment persist. This review recognizes future research directions to address and solve these challenges and highlights the potential for AI to drive further innovations in SCM. Through case studies and bibliometric analyses, this paper underscores the significance of a comprehensive strategy for supply chain redesign, integrating physical, facilities, and information management to enhance sustainability and market responsiveness. Keywords— Supply chain management , Artificial Intelligence (AI), Big Data Analytics (BDA), Demand forecasting, Inventory management, Logistics optimization, Blockchain , Internet of Things (IoT), Smart Transportation, Tactical planning, Strategic planning, Advanced available-to-promise (AATP), Sustainability in supply chain.

Solution approaches to reduce problems with unbalanced supply and demand in transportation and harvest planning

ABSTRACT This study addresses forestry planning challenges arising from supply-demand imbalances. In forest planning, supply often exceeds demand because supplies are known in advance, while demands are known more short term when ordered. This leads to so-called “creaming,” where forest planners select nearby areas first. With static supply and incremental demand information, average transportation distance increases over the planning horizon. To mitigate this, we propose an approach to artificially balance supply and demand. This can be achieved by including additional time periods with additional demand making up the factual difference. We evaluate three planning approaches to model the extended demand, varying the number of time periods and extension duration. Through simulations, we compare these approaches to traditional methods and theoretical solutions. Our proposed approach aims to better keep the average distance balanced throughout the overall planning periods. It ensures that average transportation distances are not excessively favorable in the initial periods, nor unreasonably high in the later periods, resulting in a favorable equilibrium in the average transportation distance over time. It makes sure that we do not need the additional truck capacity at certain times. We assess our proposed approaches using a case study from a Swedish forestry company, demonstrating their superiority over current practices.

A blockchain technology for improving financial flows in humanitarian supply chains: benefits and challenges

Purpose This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting. Design/methodology/approach The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology. Findings The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively. Research limitations/implications The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach. Originality/value This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

Bidimensional Spectroelectrochemistry with Tunable Thin-Layer Thickness.

Bidimensional spectroelectrochemistry (Bidim-SEC) is an instrumental technique that provides operando UV/vis absorption information on electrochemical processes from two different points of view, using concomitantly a parallel and a normal optical configuration. The parallel configuration provides information about chemical species present in the diffusion layer, meanwhile the normal arrangement supplies information about changes occurring both in the diffusion layer and, mainly, on the electrode surface. The choice of a suitable cell to perform Bidim-SEC experiments is critical, especially while working under a thin-layer regime. So far, most of the proposed Bidim-SEC cells rely on the use of spacers to define the thin-layer thickness, which leads to working with constant thickness values. Herein, we propose a novel Bidim-SEC cell that enables easy-to-use micrometric control of the thin-layer thickness using a piezoelectric positioner. This device can be used for the study of complex interfacial systems and also to easily measure the key parameters of an electrochemical process. As a proof of concept, the study of the roughening of a gold electrode in KCl medium is performed, identifying key steps in the passivation and nanoparticle generation on the gold surface.

Challenges in adopting blockchain technology in supply chain management: a too far fetched idea?

PurposeRecent technological advancements, often linked to Industry 4.0, require organizations to be more agile and innovative. Blockchain technology (BT) holds immense potential in driving organizations to achieve efficiency and transparency in supply chains. However, there exist some insurmountable challenges associated with the adoption of BT in organizational supply chains (SC). This paper attempts to categorically identify and systematize the most influential challenges in the implementation of BT in SC.Design/methodology/approachThis study resorts to an extensive literature review and consultations with experts in the field of supply chain management (SCM), information technology and academia to identify, categorize and prioritize the major challenges using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Combined Compromise Solution method (CoCoSo).FindingsThe top three classes of challenges revealed in this study are privacy challenges (PC), infrastructure challenges (IC) and transparency challenges (TC). Maintaining a balance between data openness and secrecy and rectification of incorrect/erroneous input are the top two challenges in the PC category, integration of BT with sustainable practices and ensuring legitimacy are the top two challenges in the IC category, and proper and correct information sharing in organizations was the top most challenge in the TC category.Originality/valueFuture scholars and industry professionals will be guided by the importance of the challenges identified in this study to develop an economical and logical approach for integrating BT to increase the efficiency and outcome of supply chains across several industrial sectors.