Supply Chain Research Articles

Blockchain Interoperability Frameworks: A Comparative Analysis of Cross-Chain Solutions for DLT Innovation

This article comprehensively analyzes blockchain interoperability as a crucial frontier in distributed ledger technology (DLT) innovation. Through systematic examination of current interoperability solutions, technical challenges, and implementation frameworks, the study provides insights into the evolving landscape of cross-chain communication and its implications for industry adoption. The article evaluates prominent interoperability frameworks, including the Interledger Protocol, Cosmos Network, Polkadot, and Canton Network, analyzing their architectural approaches, security mechanisms, and practical applications. Key findings reveal significant progress in addressing fundamental challenges such as protocol standardization, consensus mechanism compatibility, and scalability constraints while highlighting remaining cross-chain security and governance obstacles. The article demonstrates substantial benefits of blockchain interoperability across various sectors, with notable implementations in supply chain management reducing documentation errors by 65%, cross-border financial services decreasing settlement times from days to minutes, and healthcare data exchange improving information accessibility by 75%. Through examination of technical requirements, governance models, and risk mitigation strategies, this research establishes a comprehensive framework for implementing interoperable blockchain solutions while maintaining security and regulatory compliance. The article contributes to the growing knowledge in DLT innovation and provides practical insights for stakeholders working towards achieving seamless blockchain interoperability.

The Role Of Cost Accounting In Enhancing Supply Chain Efficiency In International Business Operations

To improve supply chain efficiency in global corporate operations, this study investigates the function of cost accounting. The growing interconnectedness of global marketplaces has made efficient cost management a crucial component for businesses looking to stay ahead of the competition. The main goal of this study is to investigate how supply chain performance can be maximized through the use of cost accounting techniques to pinpoint major cost drivers and enhance decision-making. A thorough analysis of different cost accounting approaches and how they are used in supply chains, with an emphasis on Activity-Based Costing and technological integration, is part of the objective of the study. The primary issue discussed is the dearth of empirical knowledge about how cost accounting is implemented in various business contexts, especially in multinational settings and service-oriented industries. A qualitative research methodology is used, and the analysis is supported by secondary data from company reports, academic publications, and related literature. Supply chain efficiency is greatly increased by precise cost identification, strong cost management systems, and cooperative supplier relationships, according to key results. Limitations, however, include issues with cultural and legal disparities in global settings as well as a dearth of empirical data in some businesses. The consequences of the study are both theoretical and practical, providing firms looking to enhance their cost management plans and operational effectiveness with insightful information. By filling in current research gaps, this study advances our knowledge of the relationships between supply chain performance and cost accounting.

Coordinating the Reverse Factoring System: Buying Back and Bargaining

Reverse factoring is a retailer-led supply chain financing system that can enhance liquidity of suppliers and reduce factoring fraud. This paper proposes a bargaining game theory model to analyze the profit distribution in reverse factoring for a two-echelon supply chain system that comprises a core retailer and a capital-constrained supplier. By taking into account the retailer’s credit loss risk, the impact of buying back and bargaining is investigated. Our study shows that in reverse factoring without buying back, the supplier would rather not bargain but the retailer would like to negotiate the wholesale price if the supplier’s bargaining power is low. If buying back exists and the supplier’s bargaining power is low, the retailer is also willing to negotiate the wholesale price. If there is no bargaining but the supplier takes a large portion of the supply chain’s profit, buying back is preferred. Furthermore, when there is bargaining on the wholesale price, both supplier and retailer can benefit from buying back. In addition, bargaining on the buy-back price in reverse factoring is bargaining-proof. Our study first contributes to the growing body of literature on reverse factoring and bargaining game theory. Two managerial implications for reverse factoring also emerge from the study. We find that bargaining should be considered if the supplier tends to coordinate the supply chain financing system by buying back the retailer’s unsold products. In addition, both supplier and retailer should negotiate the wholesale price as they cannot benefit from bargaining on the buy-back price.

Opportunities and challenges of drones and internet of drones in healthcare supply chains under disruption

This study investigates the use of drones and the Internet of Drones (IoDs) in healthcare supply chains (HSCs), highlighting the opportunities and challenges of integrating them to respond to HSCs disruptions, an area that is currently under-examined in supply chain literature. A mixed methods approach is employed in this research. The article establishes important contributions. Firstly, it evaluates and integrates current research to provide new insights for dealing with pandemics and other similar emergencies. Secondly, the article framework reveals relevant political, economic, social, technological, environmental, and legal influencing factors to respond to disruptions. Thirdly, the analysis through the SCOR provided a hierarchical process model for HSCs enabled by drones and IoDs. Fourthly, the paper provides a framework for a shift from people-dependent HSCs to technology-dependent HSCs. Promising future research directions are indicated to advance the supply chain research on this topic.

The Influence of Entrepreneurial Orientation on Supply Chain Resilience: Evidence from the Small and Medium Sized Enterprises

The increasing supply chains disruptions globally often leave many businesses and SMEs vulnerable. The question is whether entrepreneurial orientation of SMEs will make them more resilient to supply chain disruptions. With limited research on the relationship between entrepreneurial orientation and SMEs’ supply chain resilience (SCR) this study seeks to extend our knowledge in that respect. Grounded on the resource-based view and dynamic capabilities theory, this study examined the influence of entrepreneurial orientation on the supply chain resilience of SMEs. Five constructs of entrepreneurial orientation were adapted from literature. A cross-sectional study was employed wherein an online questionnaire was used to collect data from a sample of 173 SMEs owners/or managers. Structural equation modelling (SEM) with partial least square (PLS) technique was used to test the hypothesised model. The overall findings point towards the significant influence of EO on the SCR of SMEs as evidenced by the significant positive effect of innovativeness, risk-taking, pro-activeness and competitive aggressiveness, and autonomy dimensions of entrepreneurial orientation. These results imply that it is critical that SMEs adopt an intentional entrepreneurial oriented management philosophy which can be fostered in several ways including the promotion of a flexible organizational culture that promotes and rewards innovativeness among SME employees, and collaborative efforts between SME owners/managers and policy makers on risk management awareness and competitive aggressiveness literacy and training campaigns.

Systematic Risks of the Global Lithium Supply Chain Network: From Static Topological Structures to Cascading Failure Dynamics.

Recent years have seen increasing concerns on supply chain risks of lithium, a critical material for achieving e-mobility transition and climate ambitions. These risks propagate both along the life cycle and across national boundaries in a multilayer network. However, most previous studies are either only based on static network measures or focused on individual layers, ignoring dynamic cascading risks and interconnected and interdependent relationships along life cycle stages and across economies. Here, we integrated trade-linked material flow and complex network analyses to investigate intricate interconnections, interdependencies, and systematic risks of the global lithium supply chain. Both static and dynamic measures of the global lithium supply chain network exhibit a "robust-yet-fragile" property: robust for random shocks yet fragile for targeted shocks and robust for small or local disruptions yet fragile for large or cascading failures. Portugal, Brazil, Singapore, Canada, Finland, Norway, South Africa, Israel, Hungary, and the United Arab Emirates are most likely to be affected by supply disruptions. A hypothetical USA-China trade decoupling will increase the severity and susceptibility of network-wide failures by around 5%. Our results call for global collaborations and collective efforts to balance efficiency and security and avoid a "zero-sum game" in securing the lithium supply chain.

Adapting to uncertainty: A quantitative investment decision model with investor sentiment and attention analysis

In the face of global uncertainties, including pandemics, economic fluctuations, disruptions in supply chains, major disasters, wars, and impending economic crises, the financial landscape and the impact of investor sentiment on the return of stock index futures can be significantly altered. Understanding the relationship between investor sentiment, attention, and stock index futures returns in the face of these diverse challenges has become particularly critical. However, existing research does not adequately consider the effect of these unexpected events on the market and the shifts in investor attention. Using the COVID-19 pandemic as a case study, this research proposes a dynamic quantitative investment decision-making model that considers the influence of investors’ attention and emotional characteristics, aiming to adapt to the financial market under these global changes and improve the accuracy of quantitative investment forecasting. Initially, the Bidirectional Encoder Representations from Transformers model is employed to analyze investor comment data, extract information on investor attention and emotional characteristics, and construct investor sentiment indicators. Subsequently, a stock index futures forecasting method based on Variational Mode Decomposition algorithm and Support Vector Regression (SVR) model is constructed, and the grey wolf optimization algorithm is introduced to optimize the parameters of the SVR model. Guided by investor sentiment indicators, different market states are further distinguished, and appropriate investment strategies are implemented to effectively enhance the returns of quantitative investment. When compared with models that neglect investor attention and emotional characteristics, the results show that considering investor sentiment indicators not only improves the predictive ability of the model, but also reduces cognitive bias and market risk.

Mathematics of Machine Learning: An Introduction

Over the course of just a few decades, machine learning has grown into a force which shapes modern life perhaps as much as the combustion engine or wireless communication. As we drive to work, machine learning algorithms extract license plate numbers from images captured by automatic cameras at busy intersections. At work, they measure our productivity and govern our supply chains. In our personal lives, they power product recommendations on online shopping sites and suggestions on social media. In our homes and on our devices, they recognize our voices and our faces. They process our loan applications and evaluate our medical images. More globally, they stabilize power grids and assist in planning flight routes. There is not a space in our public and personal lives which machine learning has not at least begun to affect. For a field as ubiquitous, it is fairly poorly represented in our common knowledge. This article aims at giving a high level introduction to some core tasks, ideas and methods of machine learning for readers who are familiar with at least some undergraduate mathematics. Advanced readers may get more from certain sections, but our goal is to present a self-contained picture which requires little knowledge beyond calculus in multiple variables and elementary linear algebra. For readers who have not taken many of the advanced classes, this may also motivate why certain fields of study are of interest in applications. One big omission in this article are deep neural networks, i.e. the models which underly 'deep learning.' Due to their special importance, they will be discussed in a separate companion article.

Data-Driven Analysis of Supply Chain Integration’s Impact on Procurement Performance in International EPC Projects

Integrated supply chain management is essential for enhancing procurement efficiency and project outcomes in international engineering, procurement, and construction (EPC) projects. Despite its acknowledged importance, there is a paucity of understanding regarding the precise effects of supply chain integration on procurement processes in this context. This research analyzes 45 projects overseen by prominent Chinese international contractors to bridge this gap. The research employs Pearson correlation analysis to identify robust correlations among critical components of supply chain integration, procurement management, and procurement performance. Essential elements, including operational performance, procurement contract management, and stakeholder engagement, are identified as critical determinants of project success. The study seeks to examine how international EPC contractors incorporate the complete procurement management process via supply chain integration. Contractors can improve operational efficiency and procurement management by forming partnerships with stakeholders to acquire and integrate resources, hence enhancing project outcomes. This ongoing enhancement process improves procurement efficiency and bolsters the competitiveness of Chinese contractors in the global EPC market. The study underscores the efficiency and sustainability of procurement processes, demonstrating how optimized supply chain integration advances broader sustainability objectives by minimizing waste, enhancing resource utilization, and promoting environmentally and socially responsible procurement practices in international projects. The research offers significant empirical data and insights for academic inquiries and actual company implementations.

Buyer–supplier TMT background misalignment and green innovation performance: the moderating roles of TMT tenure and incentives

PurposeWhile top management teams (TMTs) play an important role in shaping firms’ strategic choices and performance outcomes, studies on green innovation have rarely considered the influence of the TMT demographics of firms and their suppliers. Drawing upon upper echelon theory, this study investigates the impact of buyer–supplier TMT misalignment on green innovation performance, along with potential moderators of this effect.Design/methodology/approachThe empirical setting is Chinese-listed manufacturing firms that are present in both the Chinese Research Data Services Platform (CNRDS) database and the China Stock Market and Accounting Research (CSMAR) database. The study employs panel data regression methods on a dyadic dataset of 530 paired buyer–supplier firm-year observations over the period 2008–2019.FindingsBuyer–supplier TMT misalignment in terms of functional background and educational level is negatively associated with buyer green innovation performance. This negative effect can, however, be mitigated by TMT tenure and long-term incentives in buyer firms.Originality/valueBy introducing the notion of TMT background misalignment to the supply chain, this study advances the understanding of relational TMT demographics in predicting organizational performance and extends upper echelon theory.

Recent advances in dark fermentative hydrogen production from vegetable waste: role of inoculum, consolidated bioprocessing, and machine learning.

Waste-centred-bioenergy generation have been garnering interest over the years due to environmental impact presented by fossil fuels. Waste generation is an unavoidable consequence of urbanization and population growth. Sustainable waste management techniques that are long term and environmentally benign are required to achieve sustainable development. Energy recovery from waste biomass via dark fermentative hydrogen production is a sustainable approach to waste management. Vegetable waste is generated in plenty over the food supply chain and being a rich source of carbon and other nutrients it has been studied for production of biohydrogen. This review aims to offer a comprehensive overview on the potential of vegetable waste as a feedstock for dark fermentative biohydrogen production. The hydrogen output from dark fermentative process is lower and additional strategies are required to improve the production. This review addresses the challenges generally encountered during dark fermentative hydrogen production using vegetable waste and the importance of methods such as bioaugmentation and application of extremophiles for process enhancement. The role of machine learning in the field of biohydrogen production is briefly discussed. The application of dark fermentative effluents for secondary valuable product generation and its contribution to the biohydrogen biorefinery is discussed as well.

The Logistics Cost of Cikarang Dry Port: A General Review

High logistics costs in Indonesia are thus one of the principal economic inefficiencies that restrain the country's growth and competitiveness in the global marketplace. In this context, the paper focuses on the contribution of the Cikarang Dry Port (CDP) to the national economy. This qualitative research draws on an extended narrative review of the Cikarang Dry Port. These results reflect how the CDP is pivotal in reducing logistics costs, benefiting clients and manufacturing firms around the dry port area through bettered transportation and logistics service provision. The study also puts much emphasis on the fact that logistics efficiency is not only crucial at the level of individual enterprise performance but also, more broadly, for Indonesia's economic landscape. The CDP consolidates supply chains and reduces transportation costs, ultimately building overall cost competitiveness for Indonesian enterprises in more state and international markets. The study calls for the Indonesian government to invest in developing and upgrading the infrastructure of the Cikarang and Bekasi areas. These strategic investments would also help reduce the overall cost of logistics, thereby creating an enabling environment for business operations and playing a role in the economic development and growth of the nation.

Improving the forecasting approach for crude oil sourcing at an oil refining firm: a decision theory perspective

Accurate price forecasting is pivotal for making informed sourcing decisions. This study addresses this need by empowering logistics and supply planning managers at a leading European oil refining company through the innovative use of unstructured big data analytics. By applying the CIMO (Context, Intervention, Mechanism, and Outcome) framework, the research refined the oil price forecasting process, which is crucial for optimising sourcing strategies. A novel approach was employed, combining sentiment analysis via deep learning models with traditional autoregressive integrated moving average (ARIMA) models, introducing sentiment as a vital exogenous variable. Through comprehensive stakeholder interviews, the study identified critical gaps and opportunities, leading to the development of a forecasting solution that significantly enhanced predictive accuracy. This advancement eliminated the need for manual interventions by senior decision-makers, streamlining the decision-making process. This research utilises decision theory and also demonstrates the transformative power of unstructured big data analytics in supply chain management. By integrating time series modelling with advanced sentiment analysis, this study provides a blueprint for leveraging technological advancements in rapidly evolving markets. The originality of this work lies in its practical application, showcasing essential capabilities that are increasingly vital in supporting sourcing practices within a volatile global landscape.

Decision-Making for Quality Visibility in Green Supply Chain Based on Blockchain Technology

Decision-Making for Quality Visibility in Green Supply Chain Based on Blockchain Technology

Factors Influencing Selection of Dairy Products by Retailers with Special Reference to Amul - A Study in Raipur

This report summarizes the comprehensive analysis of the behavior of retailers, product range, and promotion strategies by the fast-moving consumer goods (FMCG) companies in the dairy products industry. The study was done during a two-month internship at Amul, with an objective to get practical knowledge about the distribution, marketing, and sales activities of FMCG companies through General Trade, Modern Trade, and Horeca channels. These considerations include profit margins, available products, reliable supply chain, and brand equity to arrive at a conclusion. Thereby, findings suggest the preference of retailers for trusted brands by the consumers having quality assurance and consistent supplies because of the perishability aspect related with dairy products such as milk, curd, and paneer. In addition, kiosk events, wall paintings, and shutter advertisements have proven to have a positive effect on the visibility of the brand and engagement of the consumers with the brand, thus affecting the decision of retailers to stock. Shelf space allocation was also observed to depend on consumer demand, brand promotions, and product differentiation in competitive retail environments. Through market visits and retailer feedback, the study provided actionable recommendations to strengthen Amul's brand presence and optimize product turnover. This internship emphasized the importance of close relationships and support mechanisms from strong retailers in fostering brand loyalty and market growth in the FMCG industry. Keywords: Distribution Efficiency, Brand Loyalty in Dairy, Retailer Relationship Management.

A Study on the Research Clusters in the Humanitarian Supply Chain Literature: A Systematic Review

Background: The humanitarian supply chain (HSC) literature has observed significant growth in past years. The wide range of research areas and the interdisciplinary nature of humanitarian work have generated the need to examine and classify the literature. Previous reviews have examined particular research domains such as quality, data analytics, performance measurement, and dynamics capabilities. This article examines the HSC literature, tracing its evolution and proposing a systematic review and roadmap for future researchers. Method: We adopted bibliometric, network, and citation analyses to extract insights into the HSC literature. Results: The integrated approach helped map the previous literature and identified research keywords, clusters, authors’ collaborative network, and seven research fields. The literature classification and clustering were performed for the articles published before the literature surge during the COVID-19 pandemic to avoid potential biases that could arise from the significant increase in HSC research published during this period. Conclusions: Some of the original contributions to this article include the classification of research clusters and the identification of emerging research topics in the HSC domain. Our findings indicate research opportunities in the sustainability, performance measurement, and innovation aspects of the HSC. This study provides potential research roadmaps for future research in this field.

Nutrition-sensitive climate risk across food production systems

Abstract Global nutrition targets remain unmet, as over half of preschool-aged children and two-thirds of non-pregnant women of reproductive age worldwide suffer from micronutrient deficiencies. Climate change poses a growing threat to global food and nutrition security, but existing climate risk assessments often overlook the critical roles of both terrestrial and aquatic nutrient-rich foods that are vital for dietary diversity and micronutrient supply. In this study, we introduce an innovative framework that integrates data on future climate extremes, nutrient supply dependencies, and diet-related climate vulnerability. Our comprehensive analysis assesses nutrition-sensitive climate risk to five essential micronutrients across production systems. By mid-century (2041-2060), we estimate that 75% of calcium, 30% of folate, 39% of iron, 68% of vitamin A, and 79% of vitamin B12 produced in primary food products will face frequent climate extremes (at least every other year) globally. Nearly fifty countries are projected to face high domestic climate risk for two or more micronutrients during this period, with ten countries facing high risk across all five. We outline distinct climate risk profiles to offer data-driven entry points into strategies for bolstering the resilience of micronutrient supply chains and advancing progress toward global nutrient targets in the face of a changing climate.

Dampak Perdagangan Bebas Bagi Ekspor Produk Tuna dan Cakalang Indonesia

The open trading system without restrictions, known as free trade, allows for increased product competitiveness in international markets. Tuna and skipjack commodities are Indonesia's flagship products and play a significant role in fisheries exports. This study investigates the impact of free trade on tuna and skipjack exports, identifies challenges, and explores appropriate management strategies. The findings reveal that Indonesia faces challenges such as global competition, threats to the sustainability of marine resources due to overfishing, and demands to meet international standards. However, free trade offers opportunities to expand markets and reduce tariff barriers. The use of technology, supply chain digitalization, and innovation are crucial to enhancing efficiency and product competitiveness. To sustain marine resource conservation and maintain Indonesia's position as a leading tuna producer globally, the government must implement regulations and collaborate with industry stakeholders. Through a comprehensive strategic approach, Indonesia can preserve marine ecosystem sustainability while continuing to increase the contribution of tuna and skipjack exports to the national economy.

Impact of Red Wine Vinegar-Based Solution on Bacterial Communities of Squid and Shrimp Skewers: A Classic and Genomic Approach

AbstractSeafood is an essential component of a balanced and healthy diet, which increases its demand. However, its biological composition and high moisture content make these products extremely perishable. To prevent spoilage, and the consequent food waste and financial expenses throughout the seafood supply chain, new technologies have been successfully developed to inhibit bacterial growth, the main cause of seafood spoilage. This work aimed to test a shelf life extension technique for seafood skewers whilst maintaining an all-natural label using a financially feasible red wine vinegar treatment applied by immersion or pulverisation. Bacterial growth was monitored by classical methods and by 16S rRNA gene amplicon sequencing during the 5 days of storage. Immersion of samples in a vinegar-based solution effectively reduced Pseudomonas and Enterobacterales counts (by 2 log cfu/g), immediately after application and throughout storage. The overall structure and diversity of the bacterial community were analysed, and a strong reduction in bacterial diversity and impact on bacterial composition was observed immediately after immersion in the red wine vinegar solution. In untreated samples, Pseudomonadota (especially the Gammaproteobacteria class) was the principal phylum, whereas the microbiota of the treated samples was dominated by Bacillota (mainly the Bacilli class). Sensory analysis revealed a mild vinegar or vinaigrette flavour in treated samples; however, these characteristics were not unpleasant. Although applying a vinegar-based solution by immersion promoted a significant reduction in the growth of spoilage bacteria during the first days of storage, further tests are required to confirm the shelf life extension.

From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins

The impacts of climate change on agricultural production are becoming more severe, leading to increased food insecurity. Adopting more progressive methodologies, like smart farming instead of conventional methods, is essential for enhancing production. Consequently, livestock production is swiftly evolving towards smart farming systems, propelled by rapid advancements in technology such as cloud computing, the Internet of Things, big data, machine learning, augmented reality, and robotics. A Digital Twin (DT), an aspect of cutting-edge digital agriculture technology, represents a virtual replica or model of any physical entity (physical twin) linked through real-time data exchange. A DT conceptually mirrors the state of its physical counterpart in real time and vice versa. DT adoption in the livestock sector remains in its early stages, revealing a knowledge gap in fully implementing DTs within livestock systems. DTs in livestock hold considerable promise for improving animal health, welfare, and productivity. This research provides an overview of the current landscape of digital transformation in the livestock sector, emphasizing applications in animal monitoring, environmental management, precision agriculture, and supply chain optimization. Our findings highlight the need for high-quality data, comprehensive data privacy measures, and integration across varied data sources to ensure accurate and effective DT implementation. Similarly, the study outlines their possible applications and effects on livestock and the challenges and limitations, including concerns about data privacy, the necessity for high-quality data to ensure accurate simulations and predictions, and the intricacies involved in integrating various data sources. Finally, the paper delves into the possibilities of digital twins in livestock, emphasizing potential paths for future research and progress.