Supply Chain Stakeholders Research Articles

Designing Efficient and Equitable Freight Services Markets for Sustainable Economic Performance

Despite the indispensability of freight trucking services and truckers’ role as critical stakeholders in supply chains, relatively little attention has been paid to analyzing small independent truckers’ roles. Shippers often prefer working with larger trucking companies to the detriment of smaller independent truckers, who must grapple with an inherently disadvantageous job market. Furthermore, in the presence of uncertainty or peak demand periods, trucker shortages can pose significant economic challenges for shippers and downstream customers. In this paper, we propose an analytical framework to address these challenges in efforts to enhance the sustainability of the freight service industry. We formulate and solve a weighted bi-objective optimization model that simultaneously maximizes the total profits of both shippers and truckers to design a sustainable freight services market. Further, we leverage Monte Carlo simulation trials to examine how all players in this market can achieve a better solution under uncertainty. Ultimately, after evaluating multiple scenarios, we find that shippers and truckers yield the highest economic benefits under a balanced design that leverages principles of supply chain coordination, while satisfying all demand from shippers. This framework can serve as a decision support tool for policymakers who aim to ensure all stakeholders in the market can become and remain profitable. Based on our findings, this study suggests practical implications on how to consider humanitarian policies aimed at promoting equity for truckers and ensuring the timely shipment of essential products for both shippers and truckers.

ECONOMIC THEORY AND PRACTICAL IMPACTS OF DIGITAL TRANSFORMATION IN SUPPLY CHAIN OPTIMIZATION

Digital transformation has emerged as a critical driver of innovation and efficiency in supply chain management, reshaping traditional economic paradigms and yielding profound practical implications. This paper delves into the economic theory underpinning digital transformation in supply chain optimization and explores its practical impacts on businesses and industries. In terms of economic theory, we examine the evolution from traditional supply chain models to digitally-enabled ecosystems. The integration of digital technologies such as big data analytics, artificial intelligence, and blockchain revolutionizes supply chain dynamics, enhancing efficiency, reducing costs, and mitigating risks. Drawing on game theory applications, we elucidate strategic interactions among supply chain stakeholders and the implications of digital transformation on their decision-making processes. Turning to practical impacts, we investigate how digital transformation enables enhanced visibility, real-time tracking, and predictive analytics, fostering agility and responsiveness in supply chain operations. Automation and AI-driven insights empower decision-makers to optimize resource allocation and mitigate disruptions effectively. Through case studies, we illustrate the tangible benefits and strategic advantages accrued by organizations embracing digital transformation. However, this transformation is not devoid of challenges. Cybersecurity threats, data privacy concerns, and the integration complexities of legacy systems pose significant hurdles. Addressing these challenges necessitates a holistic approach encompassing technological innovation, regulatory frameworks, and workforce development. Looking ahead, future trends such as blockchain integration, IoT applications, and sustainability initiatives promise further advancements in supply chain optimization. This paper underscores the imperative for ongoing research and adaptation to harness the full potential of digital transformation in reshaping the future of supply chain management. Keywords: Economic Theory, Practical Impacts, Digital Transformation, Supply Chain Optimization.

Stakeholder pressure and circular supply chain practices: Moderating roles of environmental information exchange capability and circular innovation orientation

AbstractThis study deploys institutional theory and Resource orchestration theory (ROT) to examine the roles supply chain stakeholder pressure, circular innovation orientation (CIO) and environmental information exchange capability (EIEC) play in adopting Circular supply chain (CSC) practices. This study uses a partial least square structural equation modelling (PLS‐SEM) to analyse survey data gathered from 290 managers of manufacturing Small and medium enterprises (SMEs) in Ghana. This study finds that pressure from supply chain stakeholders substantially drives manufacturing SMEs' CSC practices. This study confirms that EIEC negatively moderates the relationship between supply chain stakeholder pressure and CSC practices. Finally, this study confirms the complementarity between CIO and EIEC through moderating effects between supply chain stakeholder pressure and CSC practices. This study advances circular supply chain management (CSCM) literature by testing a research framework that examines important but rarely studied roles of CIO and EIEC in SMEs' CSC practices adoption under supply chain stakeholder pressure through institutional and resource orchestration perspectives.

Risk Factors of Perishable Product Supply Chain: Literature Review and A Proposed Framework for Future Research

United Nations statistics show that about one-third of globally transported perishable products are annually wasted due to damage. Where in the perishables supply chain is most likely to go wrong and how can this be corrected or prevented? This article aims to review the literature 50 articles related to the risk factors of perishable products supply chain and cluster the risk factors of perishable products supply chains. Identifying 140 risk factors from 235 risk factors through duplication filtering. And the researcher therefore clusters of risk factors with hierarchical clustering (divisive: distance matrix) into 19 clusters by KNIME machine learning. These findings offer valuable insights for future research on orchid’s supply chain risk management for sustainability in Thailand, top global orchid exporter. For the benefit of orchid supply chain stakeholders in Thailand can develop appropriate and sustainable supply chain risk management in the future. Thailand 3rd National Logistics Development Strategy (2017-2021) emphasizes cold chain logistics to elevate agricultural and industrial supply chains to meet standards. Implementing a cold chain system is vital to reduce losses, enhance traceability, and lower production costs.

The mediating role of information integration: information technology capabilities and supply chain resilience in Ugandan agro-food processing firms

PurposeThis paper aims to investigate the relationship between information technology (IT) capabilities, information integration and supply chain resilience within the context of a developing country.Design/methodology/approachEmploying a structured questionnaire survey, the study collected cross-sectional data from 205 agro-food processing firms in Uganda, drawn from a sample of 248. The data were subsequently analyzed using SPSS version 27 to validate the hypothesized relationships.FindingsThe study findings revealed that IT capabilities and information integration are positively and significantly associated with supply chain resilience. Moreover, it established a positive and significant link between IT capabilities and information integration. The results further revealed both IT capabilities and information integration account for 62.2% of the variance in supply chain resilience (SCRES) in agro-food processing firms in Uganda. Notably, the findings revealed the partial mediating role of information integration, addressing the need to understanding the mechanisms through which IT capabilities influence SCRES.Research limitations/implicationsFirst, the study used a cross-sectional design which makes it difficult to test causality. Some of the study variables need to be studied over time due to their inherent behavioral elements such as collaboration and information sharing. Hence, future research that could, where possible, collect longitudinal data on the study variables would add value to the findings. Second, the study was limited to agro-food processing firms in Uganda in selected districts of Kampala, Wakiso, Mukono and Jinja. Further research needs to be done in other sectors such as service industry and other geographical locations in Uganda and other developing economies to provide more generality of the findings. Third, the study was based on IT capabilities, information integration and supply chain resilience. There are other variables that affect supply chain resilience such as business continuity planning strategy, interactions between teams within an organization in building resilience, supply chain velocity, system orientation and flexibility among others which can be interesting for further research.Practical implicationsManagers are advised to motivate their IT-related personnel. Efficient use of IT systems by staff, especially who are skillful at self-study, enhances their ability to respond to disruptions accordingly. This enhances SCRES. Additionally, to get feedback from supply chain stakeholders, agro-food processing firms should assess the quality of their supply chain services through using IT capabilities as well as integrating their information.Originality/valueThis study contributes to existing literature by adopting information processing perspective to provide an empirical understanding of IT capabilities and information integration as key resources and capabilities essential for information processing in building SCRES. Furthermore, the study introduces the novel insight of the mediating role of information integration as a pathway in which IT capabilities enhance SCRES in agro-food processing firms in Uganda.

Forging Pathways to Circular Economy Excellence: Integrating Industry 4.0 with Quality Management

The convergence of industry 4.0 technologies with supply chain operations and sustainability initiatives has sparked interest in integrating supply chain quality management with these advancements, termed SCQM 4.0. A comprehensive literature review spanning 1998 to 2023, analyzing 232 papers, unveiled key trends, identified research gaps, and outlined a future research agenda for SCQM 4.0. The review culminated in the development of a comprehensive theoretical framework for SCQM 4.0 geared towards fostering sustainability within a circular economy framework, encompassing economic, social, and environmental dimensions. Notably, the study implies a rising enthusiasm for leveraging industry 4.0 tools such as the internet of things, blockchain, traceability systems, and smart packaging to enhance quality management within circular supply chain operations. Additionally, it proposes SCQM 4.0 strategies aimed at achieving holistic sustainability objectives in circular economies, underscoring implications for further scholarly inquiry in this dynamic field. To promote supply chain quality management digitalization, supply chain stakeholders should analyze research gaps and develop practical implementation plans using the SCQM 4.0 framework. Additionally, exploratory qualitative investigations among organizations and industries should be conducted to identify essential components in sustainable SCQM 4.0.

The Convergence of Corporate Sustainability and Social Responsibility in Modern Business Contexts: A Bibliometric Analysis

Abstract Global challenges such as climate change, the Covid-19 pandemic, and geopolitical instability have driven organizations to embed sustainability into their strategies and operations, moving away from the profit-driven mindset to a broader emphasis on societal value. Sustainability, today a widespread concept in academia and business, requires balancing social, environmental, and economic responsibilities to achieve long-term success. Embracing the Triple Bottom Line (TBL) model, organizations aim for profit while also positively impacting society and the environment. However, there is a prevailing tendency to emphasize rights over responsibilities, a pattern that needs to shift in order to promote sustainability. This paper contributes to the body of knowledge on corporate sustainability by exploring its relationship with social responsibility. A bibliometric analysis was conducted on a sample of 9,378 documents processed using VOSviewer. The study examines the interplay between sustainability, social responsibility, and corporate sustainability, mapping out key concepts and visualizing their networks. Furthermore, the links to other key themes such as performance, management, innovation, strategy, governance, supply chain management, leadership, stakeholders, and others were also explored. Social-responsibility disclosure was also found to be an emergent topic in terms of organizational accountability and transparency.

Machine learning to predict grains futures prices

AbstractAccurate commodity price forecasts are crucial for stakeholders in agricultural supply chains. They support informed marketing decisions, risk management, and investment strategies. Machine learning methods have significant potential to provide accurate forecasts by maximizing out‐of‐sample accuracy. However, their inherent complexity makes it challenging to understand the appropriate data pre‐processing steps to ensure proper functionality. This study compares the forecasting performance of Long Short‐Term Memory Recurrent Neural Networks (LSTM‐RNNs) with classical econometric time series models for corn futures prices. The study considers various combinations of data pre‐processing techniques, variable clusters, and forecast horizons. Our results indicate that LSTM‐RNNs consistently outperform classical methods, particularly for longer forecast horizons. In particular, our findings demonstrate that LSTM‐RNNs are capable of automatically handling structural breaks, resulting in more accurate forecasts when trained on datasets that include such shocks. However, in our setting, LSTM‐RNNs struggle to deal with seasonality and trend components, necessitating specific data pre‐processing procedures for their removal.

The South Korean Perspective on German Animal Welfare Certified Pork

Industry stakeholder requests for improved animal welfare practices in German meat production have steadily increased in recent years. A transformation of German animal husbandry systems would almost certainly result in higher production costs. Against this background, producers and the meat industry are concerned about losing their international competitiveness while implementing improved animal welfare practices. As South Korea is an established trading partner for Germany, the objective of this explorative study is to assess South Korean meat market trends with a special focus on meat quality and animal welfare in order to evaluate export chances for German pork produced under higher animal welfare standards. Using a triangulation, the results of semi-structured interviews (n=15) with South Korean pork supply chain stakeholders are combined with the results of an online survey of South Korean consumers (n=723). Results indicate that the market potential for German meat produced under higher animal standards is still low in South Korea. Stakeholders associate improved husbandry conditions with healthier animals, benefits to human health and rank animal welfare as a key element of sustainability. However, due to consumers’ lack of knowledge and their price sensitivity, animal welfare is neither a unique selling point, nor linked to meat quality.

Longitudinal analysis of interorganizational collaborative networks of cross-laminated timber (CLT) construction

Purpose Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction. Design/methodology/approach The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies. Findings The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors). Originality/value The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

Using inverse DEA and machine learning algorithms to evaluate and predict suppliers’ performance in the apple supply chain

In an era where sustainability is paramount, this study presents a novel analytical framework that uses inverse data envelopment analysis (IDEA) and machine learning to optimize supplier performance in Apple's supply chain. We introduce the application of IDEA to recalibrate operational benchmarks, focusing on substantial CO2 reduction, and couple this with advanced predictive algorithms to proactively steer supplier practices toward Apple's sustainability targets. The study systematically simulates scenarios to achieve 30%–50% CO2 cuts, setting a precedent for environmental strategy integration. Beyond environmental metrics, our approach rigorously evaluates economic indicators such as earnings persistence and market recognition, providing a holistic view of supplier viability. The research employs machine learning, notably random forest and k-Nearest neighbors, to distill unbiased insights from historical data, ensuring precise, objective supplier assessments. Our findings offer a strategic blueprint for corporations and supply chain stakeholders aiming to embed sustainability into their operational ethos, supported by data-centric decision-making. These methodologies and insights contribute valuable perspectives to sustainable supply chain management and predictive analytics discourse. Finally, the study offers guidance on implementing CO2 reduction strategies and evaluating suppliers' economic performance, aligning with Sustainable Development Goals (SDGs) objectives.

Barriers to Industry 4.0 technology adoption in agricultural supply chains: a Fuzzy Delphi-ISM approach

PurposeThe purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.Design/methodology/approachThe study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.FindingsThe results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.Research limitations/implicationsThe robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.Practical implicationsThe study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.Originality/valueIt is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.

Blockchain Traceability Adoption in Low-Carbon Supply Chains: An Evolutionary Game Analysis

Blockchain technology has brought innovation to supply chain management, particularly in managing carbon emissions in the manufacturing sector. However, there is a research gap regarding the policy tools and the role of local governments in implementing blockchain technology to achieve carbon emissions traceability. Additionally, the strategic relationships and policy implications resulting from the implementation of blockchain technology are not examined systematically. An effective method for examining the strategies used in interactions between supply chain stakeholders and governments is evolutionary game theory, or EGT. This paper employs mathematical modelling and MATLAB 2016 software simulation to examine the decision-making process of manufacturing companies when considering implementing blockchain technology traceability. Specifically, the subjects in the model include product manufacturers (PM), product suppliers (PS), and local governments (LGs). The aim is to examine the decision-making behavior of carbon traceability participants in blockchain technology. This paper analyses the most effective blockchain-based traceability strategies for low-carbon supply chain members under a variety of scenarios by modifying the parameters. The findings suggest the following: (1) Manufacturers and suppliers need to manage the cost of blockchain traceability, collaborate to create an environmentally friendly product certification system, and improve brand image. (2) Local governments should set up efficient reward and punishment systems to incentivize supply chain stakeholders to engage in the blockchain traceability system. The aforementioned discoveries furnish policymakers with guidance to encourage the implementation of blockchain-based carbon footprint traceability technology, thereby establishing a transparent carbon footprint traceability framework across the entire supply chain.

Analyzing the Role of Artificial Intelligence and Machine Learning in Optimizing Supply Chain Processes in Kenya

Purpose: The aim of the study was to analyze the role of artificial intelligence and machine learning in optimizing supply chain processes
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: Artificial intelligence (AI) and machine learning (ML) play a pivotal role in optimizing supply chain processes by enhancing demand forecasting accuracy through sophisticated algorithms. They streamline inventory management by predicting demand patterns and automating replenishment tasks, leading to reduced stockouts and excess inventory. AI-powered analytics enable real-time insights into supply chain performance, identifying bottlenecks and inefficiencies for proactive decision-making.
 Unique Contribution to Theory, Practice and Policy: Theory of technology acceptance model (TAM), resource-based view (RBV) theory & dynamic capabilities theory may be used to anchor future studies on analyzing the role of artificial intelligence and machine learning in optimizing supply chain processes. Encourage supply chain stakeholders to adopt blockchain solutions for enhanced transparency, traceability, and efficiency. Advocate for regulatory frameworks that promote the adoption of blockchain technology in supply chains while addressing concerns related to data privacy, interoperability, and standardization.

Impact of Blockchain Technology on Supply Chain Management Efficiency and Transparency in Pakistan


 Abstract
 Purpose: The aim of the study was to influence the impact of blockchain technology on supply chain management efficiency and transparency
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: A study on the impact of blockchain technology on supply chain management in Pakistan revealed significant improvements in efficiency and transparency. Through blockchain integration, supply chain processes experienced reduced delays and increased automation, leading to streamlined operations. Transparency was notably enhanced, with real-time tracking of goods and secure data sharing among stakeholders, mitigating risks of fraud and error. These findings suggest that adopting blockchain technology holds promise for enhancing supply chain management in Pakistan by fostering greater efficiency and transparency.
 Unique Contribution to Theory, Practice and Policy: Diffusion of innovations theory, information processing theory & resource dependency theory may be used to anchor future studies on the impact of block chain technology on supply chain management efficiency and transparency. Encourage supply chain stakeholders to adopt blockchain solutions for enhanced transparency, traceability, and efficiency. Advocate for regulatory frameworks that promote the adoption of blockchain technology in supply chains while addressing concerns related to data privacy, interoperability, and standardization.

A STUDY ON EFFICIENCIES AND HINDRANCES TO BIM IMPLEMENTATION IN INDONESIAN CONSTRUCTION PROJECTS

BIM is an integrated system where processes are conducted seamlessly, influencing information exchange not only among software but also among stakeholders. BIM is identified as a method that can be employed to enhance the efficacy and efficiency of construction projects, along with the quality of construction projects. The research aims to evaluate the effectiveness, challenges, and overall performance of BIM in the construction industry in Indonesia, providing insights into the extent to which BIM is utilized and its impact on construction projects in Indonesia. The research uses a literature review method to identify the BIM implementation process and its correlation with BIM maturity. The research results demonstrate the continued high demand for BIM resources among Indonesian construction projects. The use of BIM has been utilized in the construction, design, and planning phases of projects. The maturity of BIM utilization is predominantly associated with collaboration, team building, communication, and clash detection. BIM adoption is still quite low in Indonesia, particularly concerning legality, the availability of BIM requirements, supply chain participation, stakeholder involvement, and standard setting. Keywords: BIM; Performance; Project.

Analysis of factors and solutions to poor supply chain quality in a manufacturing organisation

Background: With about 55% of operating costs in manufacturing organisations coming from costs of supply chains, coupled with a 6% increase in supply chain costs incurred by a manufacturing organisation during the financial year 2021–2022, supply chain managers need to ascertain factors contributing to high supply operating cost and ascertain suitable strategies to lower supply chain management cost.Objectives: The purpose of this study is to unveil the factors and the solutions to poor supply chain quality in a steel product manufacturing organisation.Method: A qualitative approach conducted via an interview guide was used in this study. Perceptions of key supply chain stakeholders within a steel product manufacturing organisation formed the basis of the exploring factors contributing to poor supply chain quality and the solutions thereof. The Pareto chart was created to ascertain the critical factors that contribute to poor supply chain quality.Results: The study revealed that inventory stock-out, management decisions, process deviations, longer lead times, suppliers and unreliable enterprise resource planning (ERP) system issues contributed to poor supply chain quality.Conclusion: Supply chain managers should make use of strategies such as safety and consignment stock policy, just-in-time (JIT) system, supplier evaluation exercise for supplier selection, localisation of the sourcing of raw materials, customised ERP systems, job rotation and dashboards, with a view to improve visibility and efficiency of supply chain processes.Contribution: The study serves as a knowledge advisor to supply chain managers, on the critical factors contributing to poor supply chain quality, and the solutions thereof.

Non-fungible tokens: The missing ingredient for sustainable supply chains in the metaverse age?

Non-fungible tokens (NFTs), unique digital assets on a blockchain that can represent ownership of digital or physical items, are potentially ground-breaking in their capacity for transforming the sustainability of supply chains. This paper explores and discusses how NFTs, analysed through the lens of the Technology Organisation Environment (TOE) framework, can drive supply chain sustainability and overcome the barriers to Blockchain Technology (BCT) adoption. We elucidate the unique value proposition of NFTs and explore the potential of ‘phygital products’ for linking digital NFTs to physical goods. Based on the existing literature and a review of real-world case studies, we propose that NFTs can (1) incentivise supply chain stakeholders to engage in more sustainable practices; (2) enhance customer willingness to pay for sustainable products; (3) provide anti-counterfeit measures; (4) support circular business model growth. A sustainable 'Mint-to-Order' production strategy starting with the creation (minting) of an NFT is proposed based on a synthesis of the findings. The use of NFTs has significant implications for both digital and physical product offerings and sustainable supply chain management (SSCM) practice making a compelling case for adoption. This paper is one of the first to explore the potential of using NFTs to drive sustainability in supply chains forming an essential component of a metaverse nexus and delineating a future research agenda.

Blockchain based transparent and reliable framework for wheat crop supply chain.

The wheat crop that fulfills 35% of human food demand is facing several problems due to a lack of transparency, security, reliability, and traceability in the existing agriculture supply chain. Many systems have been developed for the agriculture supply chain to overcome such issues, however, monopolistic centralized control is the biggest hurdle to realizing the use of such systems. It has eventually gained consumers' trust in branded products and rejected other products due to the lack of traceable supply chain information. This study proposes a blockchain-based framework for supply chain traceability which provides trustable, transparent, secure, and reliable services for the wheat crop. A crypto token called wheat coin (WC) has been introduced to keep track of transactions among the stakeholders of the wheat supply chain. Moreover, an initial coin offering (ICO) of WC, crypto wallets, and an economic model are proposed. Furthermore, a smart contract-based transaction system has been devised for the transparency of wheat crop transactions and conversion of WC to fiat and vice versa. We have developed the interplanetary file system (IPFS) to improve data availability, security, and transparency which stores encrypted private data of farmers, businesses, and merchants. Lastly, the results of the experiments show that the proposed framework shows better performance as compared to previous crop supply chain solutions in terms of latency to add-blocks, per-minute transactions, average gas charge for the transaction, and transaction verification time. Performance analysis with Bitcoin and Ethereum shows the superior performance of the proposed system.

Streamlining supply chains: An efficiency-driven permissioned blockchain framework for data reduction

In the ever-evolving landscape of supply chain management, the quest for efficiency has become paramount. This abstract explores a groundbreaking solution that combines the power of permissioned blockchain technology with innovative data reduction strategies to redefine how supply chains operate. Traditional supply chain systems often grapple with data overload, causing delays, inaccuracies, and operational inefficiencies. However, this abstract presents a promising approach that unleashes efficiency by harnessing the capabilities of a permissioned blockchain. Through data reduction techniques tailored to the needs of supply chain management, this approach streamlines the flow of information while maintaining security and trust among participants. This paper seeks into the technical foundations of permissioned blockchains, highlighting their suitability for supply applications where confidentiality and controlled access are imperative. Furthermore, it examines various data reduction methodologies, emphasizing their role in minimizing redundant data, optimizing communication, and enabling real-time decision-making. The impact of this innovative approach on supply chain stakeholders is profound. It reduces data related bottlenecks, enhances transparencies, and fosters collaboration among participants. Additionally, it provides a scalable framework adaptable to diverse supply chain ecosystems. As supply chain efficiency becomes increasingly important in our interconnected world, this permissioned blockchain-driven data reduction strategy offers a compelling vision for the future. It promises to unlock a new era of streamlined operations, cost savings, and improved customer satisfaction, ultimately shaping the next generation of supply chain management.