Increasing demand for transparency in agri-food through customer expectation and regulatory imposition has fostered a swift adoption of blockchain technology. Demand for transparency is rising in the agri-food industry driven by consumer expectations and regulatory requirements, which has fast-tracked the adoption of blockchain technology. It creates innovative solutions to augment traceability and combat food deception, while also informing consumers about their origin. Blockchain is by nature trusted and immutable; thus, it is well suited for agri-food stock chains. Considering that the transactions on such supply chains have to be safe and transparent, the existing Smart contract technology based on Ethereum is being improved. Even if updating is difficult and disruptive, the topic of data migration and its users is growing more difficult. This has led most of the agri-food sector migration to Binance Smart Chain (BSC). BSC offers the benefits of confirmation times for transactions, a more efficient consensus mechanism, and thus better scalability. On the latter aspect, use of BSC will eventually ease the updation of smart contracts, thereby upgrading the entire speed and reliability of blockchain solutions for ensuring transparency and traceability in a supply chain.
Purpose Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges, particularly concerning the inadequacy of supply chain information. To address this issue, our study employs the organizational information processing theory to explore how adopting blockchain technology enables firms to learn from and collaborate with their supply chain partners, ultimately facilitating their sustainable performance even in the presence of organizational inertia. Design/methodology/approach Underpinned by the organizational information processing theory and drawing data from 220 manufacturing firms in China, we use structural equation modeling to test our conceptual model. Findings Our results demonstrate that blockchain technology adoption can significantly enhance sustainable performance. Furthermore, supply chain learning acts as a mediator between blockchain technology adoption and sustainable performance, while organizational inertia plays a negative moderating role between blockchain technology adoption and supply chain learning. Originality/value These findings extend the existing literature on blockchain technology adoption and supply chain management, offering novel insights into the pivotal role of blockchain in fostering supply chain learning and achieving sustainable performance. Our study provides valuable practical implications for managers seeking to leverage blockchain technology to enhance sustainability and facilitate organizational learning.
Purpose The purpose of this study is to investigate the primary determinants influencing the acceptance of generative artificial intelligence (GAI) adoption within Blockchain-enabled environments. Further research will examine the impact of GAI adoption on supply chain efficiency (SCE) through the enhancement of Blockchain. Design/methodology/approach Drawing on innovation diffusion theory (IDT), this study used partial least square structural equation modelling (PLS-SEM) to look into the hypotheses. The data were gathered via online questionnaires from employers of Chinese supply chain enterprises that have already integrated Blockchain. Findings The findings of this study demonstrate that relative advantages (RAs), compatibility, trialability and observability have a significant positive effect on GAI adoption, while complexity harms GAI adoption. Above all, the GAI adoption has significantly enhanced Blockchain, thus effectively improving SCE. Practical implications The outcomes from this study furnish enterprises and organizations with valuable insights to proficiently integrate GAI and Blockchain capability, optimize supply chain management and bolster market competitiveness. Also, this study will help accelerate the successful integration of business processes and attain Sustainability Development Goals 9, industrial growth and industrial diversification. Originality/value To the extent of the author’s knowledge, the current status of the GAI study remains largely exploratory, and there is limited empirical evidence on integrating Blockchain capability and GAI. This research bridges the knowledge gap by fully revealing the optimal integration of these two transformative technologies to leverage their potential advantages in supply chain management.
Ma Del Valle Fernández Moreno, Juan Miguel Alcántara-Pilar, Marta Tolentino
Abstract This paper presents the results of a bibliometric analysis concerning the application of blockchain technology to logistics. It aims to discern the relational structure among past and current topics, predict emerging trends, and provide a longitudinal perspective on this research domain. Using co-word analysis techniques, we employ SciMAT software to analyze over 800 papers from 2016 to March 2023. The investigation enhances the understanding of blockchain technology, revealing that scientific production in this area revolves around eight primary thematic clusters. Visual representations of the results are provided through longitudinal maps and strategic diagrams, illustrating pivotal themes across the three study periods: blockchain and sustainability. Smart contracts emerge as a focal topic in the final period under consideration.
Supplier selection is a complex Multi-Criteria Decision-Making (MCDM) problem where decision-maker (DM) preferences heavily influence decision criteria and outcomes. Suitable suppliers capable of meeting performance criteria are central to successful Blockchain Technology (BT) implementation. Numerous qualitative factors influence blockchain adoption within organizations, particularly in the communication between retailers and suppliers via Blockchain, where qualitative uncertainties abound. This study aims to develop a robust system within a probabilistic and fuzzy framework to integrate DMs’ judgments amidst uncertainty effectively. Leveraging the Bayesian best-worst method (BWM), optimal weights for evaluating supplier criteria are determined. This method employs Markov-chain Monte Carlo (MCMC) to calculate the probability of preferring one criterion over another, facilitating confidence level elucidation between criterion pairs and enhancing criteria rankings. Supplier ranking is performed using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The efficacy of the proposed approach is demonstrated through a case study utilizing real data from the railway supply chain. Results indicate the model’s effectiveness in optimizing supplier selection and enhancing supply chain performance.
Lin Wang, Zeng Yu, Yongshun Xu, Ming Chi · 5 authors
In the era of globalization, enhancing construction supply chain resilience (CSCR) has become essential. Traditional supply chains face issues like information asymmetry, trust deficits, and inefficiencies, weakening their resilience. Blockchain offers a solution by improving transparency, trust, and coordination, but its impact on CSCR remains unclear. This study addresses the gap by developing a moderated mediation model to explore how blockchain influences CSCR through supply chain integration and the moderating role of environmental uncertainty. Data from 310 senior managers in Chinese construction firms were analyzed using structural equation modeling. The results showed that blockchain significantly improves CSCR, mediated by operational, informational, and relational integration, particularly under high uncertainty environments. The findings highlight blockchain’s potential to strengthen CSCR and provide theoretical insights into its mechanisms, offering practical guidance for construction companies to enhance supply chain processes through blockchain implementation.
Syed Abdul Rehman Khan, Adnan Ahmed Sheikh, Ibrahim Rashid Al Shamsi, Yu Zhang
In today’s fast-paced business settings, the metaverse as a shared marketplace has gained popularity and is helping businesses to develop crucial business strategies in their pursuit of sustainable performance. However, a lack of understanding and knowledge about the effectiveness of the metaverse and its related technologies creates a barrier. Therefore, the current study fills this gap and uses organizational information-processing theory to develop the theoretical framework to examine metaverse-related technologies (artificial intelligence and blockchain technology—BCT) and their direct and indirect effects on sustainable business performance, which no other study has examined. Using purposive sampling, the sample data from 326 SMEs were gathered and analyzed using a partial least square structural equation modeling (PLS-SEM). This study’s findings revealed that AI capabilities are vital for information gathering, analyzing, and decision-making in the metaverse context. BCT facilitates ensuring a transparent, visible, traceable, and immutable supply chain, which helps make it more resilient and improves the closed-loop supply chain (CLSC) system with positive technological advancements and significant effects on increasing sustainable business performance (SBP). This study’s findings help organizations understand the potential benefits of AI-enabled SMEs’ presence in the metaverse. The current investigation provides a strategy for managers to gain a competitive advantage, make the supply chain more robust, and enhance overall business performance.
Weizhong Wang, Yu Chen, Yi Wang, Muhammet Deveci · 6 authors
Abstract Many attempts have been made to identify barriers to blockchain adoption in supply chain; however, barriers to blockchain adoption in supply chain finance (SCF) are underexplored. This study prioritizes barriers to blockchain adoption in SCF and evaluates the barrier level of each alternative participant. We propose an integrated decision model to prioritize the barriers and evaluate their levels of alternative participants. To determine the barriers, we conducted a literature review. We then introduce an integrated weight calculation method by combining interval-valued Fermatean fuzzy (IVFF)-optimistic-pessimistic-utility values-based and IVFF-RS (ranking sum) methods to determine the barrier weights. To evaluate the barrier level of each alternative participant in SCF, the integrated IVFF-RAFSI (Ranking of Alternatives through Functional Mapping of Criterion Subintervals into a Single Interval) model is presented to rank the barrier, which uses a power-weighted aggregation operator to fuse experts’ opinions. A case study demonstrates the practicality of the integrated IVFF-RAFSI model. The results show that uncertain and competitive markets (weighted at 0.0676) are the most significant barriers. This finding also suggests that small and medium-sized processing enterprises have the highest barriers to blockchain adoption. Sensitivity and comparative analyses validate the steadiness and competency of the proposed model. These results indicate that the proposed methodology provides a systematic technique for analyzing barriers to blockchain applications in SCF.
• First comprehensive review of ML models for end-of-life product return predictions. • Integration of PRISMA systematic review with network and meta -analysis methods. • Key factors influencing ML prediction accuracy in reverse supply chains. • Six future research directions for AI-enhanced circular-economy logistics. The evolution of the circular economy has led to the adoption of circular supply chains, where efficient management of the reverse supply chain enhances resource utilization, minimizes waste, and fosters a circular supply chain. However, managing reverse supply chains presents numerous challenges including a lack of information transparency and traceability, inconsistent cooperation among stakeholders, and uncertainty in recycling process, such as variations in quantity, quality, and timing. To address these challenges, an information sharing framework that integrates blockchain technology with digital product passports (DPPs) is designed to manage reverse supply chain information. Subsequently, a system dynamics model is applied to evaluate the potential impacts and feasibility of this framework within the reverse supply chain and its implications for the forward supply chain. The results indicate that the application of the proposed framework enhance the legal recycling market, reduces the negative environmental impact of illegal recycling activities, mitigates the bullwhip effect within the forward supply chain, and improves market fulfillment rate. The proposed information sharing framework can be employed to enhance the information efficiency of the reverse supply chain, aid in the recovery of end-of-life products and critical resources utilization, thereby supporting the transition to a circular economy.
To cope with the advancements in blockchain technologies, novel platforms are rapidly evolving. This creates new business and financial opportunities for supply chain networks. Despite the extensive literature on blockchain technologies, few studies have focused on selecting the most suitable platforms for supply chain networks. Furthermore, such decisions may be influenced by the occurrence of future events causing system dynamics. The literature also fails to integrate uncertainty related to such system dynamics into this decision-making process. To address this gap, this study develops a novel and hybrid decision support system using the concept of stratification and multi-preference group decision making. To analyse blockchain technology platforms for a supply chain network, further enhancements are made to the developed model by utilising the principles of complex system behaviour, target-based normalisation, Markov chains and best-worst method. This research is the first to examine how such methods can work together to integrate dynamics of a complex system into the decision-making process. Moreover, the paper analyses a supply chain network blockchain platform technology with complex systems transitions. To validate the reliability of the method, a real-world problem is addressed, which is a blockchain platform technology selection problem in one of largest multinational and professional services networks in New Zealand. The study exposes the efficiency of the proposed approach to address such complex problems.
The pharmaceutical supply chain is a complex network involving multiple stakeholders and processes, making it susceptible to various inefficiencies and challenges such as counterfeiting, drug expiry, and inefficient inventory management. These challenges may lead to compromised patient safety and financial losses. Blockchain technology is a promising solution to these problems. This study develops a blockchain-enabled mathematical model for pharmaceutical supply chains. A distributed ledger is used to acquire the real-time drug transaction status throughout the supply chain. The study uses real-time data gathered from the distributed ledgers across the supply chain, ensuring optimum inventory with the minimization of expired drugs and transportation costs. By leveraging the proposed model, stakeholders can eliminate counterfeiting, reduce drug expiry, and ultimately ensure the integrity and safety of pharmaceutical products throughout their lifecycle. This model also helps manufacturers in decision making for drug manufacturing based on real-time data. Novelty of the study lies in real-time tracing and managing the drugs across the supply chain.
The global transition towards a circular economy demands the creation of advanced digital tools that enable transparency, trust, and sustainability across product lifecycles. Decentralized Digital Product Passports (DPP) are emerging as a transformative solution to address these challenges. This paper investigates digital product passports based on distributed ledger and Internet of Things (IoT) technologies. The framework aims to securely record, store, and share product-related data, such as material composition, environmental impact, and usage history, in a tamper-proof and decentralized manner. Using the immutable nature of distributed ledgers and integrating real-time IoT data collection, the DPP framework aligns stakeholder actions with circular economy objectives, including improved resource efficiency, increased product reuse, and optimized recycling processes.
The increasing pressure on global supply chains to reduce carbon emissions has driven the need for sustainable supply chain network design (SSCND). This paper proposes an innovative framework for SSCND that optimizes facility location and scale decisions under uncertainty using blockchain technology. By incorporating cap-and-trade regulations and carbon trading into a mixed-integer linear programming model, the study addresses both the economic and environmental objectives of supply chains. A two-stage stochastic programming approach is employed to optimize the SSCND. The first stage focuses on facility location decisions and the second stage on production adjustment, transportation, and carbon trading under demand uncertainty. The carbon trading decisions are integrated into the model by assigning a monetary value to carbon dioxide emissions and allowing for dynamic adjustments to real-time environmental impacts. A primal decomposition algorithm is introduced to address the computational challenges involved in solving the two-stage stochastic programming model. Numerical experiments based on data derived from SAIC Motor Corporation's supply chain demonstrate the effectiveness of the model and algorithm. This study provides an efficient approach for integrating environmental sustainability into supply chain management, offering valuable insights for industries aiming to achieve carbon neutrality.
The shift from a linear economy to a Circular Economy (CE) is crucial for achieving sustainability and reducing environmental impact However, large-scale CE implementation faces challenges such as a lack of transparency
With the development of consensus mechanism, researchers emphasize the need to strengthen the Proof of Stake consensus process. Problem like how to keep the transaction platform protocol fair; how to decentralize the digital transaction system etc. have still remained to be solved. The Proof of Stake also has potential to be applied in various fields. So, it is worth reviewing on the research in recent years to summarize the research methods and conclusions. Study is based on the classical research on Proof of Stake consensus mechanism, improvement of protocol and algorithm of Proof of Stake and application of Proof of Stake. Related developer documentation website, conference papers and authoritative papers were considered. The selected paper was systematically reviewed to make comments on their research methods and analysis the advantages and disadvantages of the research method. After that, the research conclusions are summarized, and potential valuable project or future challenge are described. Through researching on current researches in Proof of Stake, it ultimately leads to the conclusion that Proof of Stake consensus mechanism has better energy efficiency and scalability comparing to the Proof of Work. However, the problems of security and centralization have remained to be solve. In the future, these problems can be solved by improving the algorithm of it or develop new protocol like mixed one of Proof of Stake and Proof of Work.
Blockchain integration is revolutionizing traditional systems in various sectors.This study investigates its implementation in creating Decentralized Autonomous Organizations (DAOs) for more sustainable supply chains.By harnessing the transparency and security features inherent in blockchain technology, DAOs possess the transformative potential to significantly augment trust, efficiency, and sustainability within supply chain networks.This research not only explores the current landscape but also delves into the challenges encountered and proposes avenues for future inquiry to further advance the adoption and optimization of this innovative solution.
The occurrence of the fourth industrial revolution (Industry 4.0) has led many industries to the path of adopting new technologies. Such technologies include blockchain, artificial intelligence (AI), and the Internet of Things (IoT). Blockchain creates the opportunity to access data and information in a decentralized manner, resulting in increased customer satisfaction. This study develops a smart newsvendor model of the food industry with consignment contracts and blockchain technology. Under a consignment policy, the central division (manufacturer) can utilize the retailer’s warehouse for storage. The producer may also have the opportunity to share the holding cost with retailers without losing the ownership of products. The main contribution of this study is to analyze the profitability of the retailing and supply chain when the blockchain technology is implemented by the food industry. Moreover, a thorough investigation of profit and loss is conducted under a consignment contract when uncertain demand is encountered. This study mainly concerns perishable food items, and increasing volatility in market demand. Two cases of probabilistic uncertainty are considered, including uniform and normal distribution. The key investigations of this study are presented in terms of (a) the effect of adopting blockchain on market demand for the food industry, (b) analysis of company profitability for perishable food items and demand uncertainty, and (c) the effect of the consignment contract under blockchain technology in the food industry. Finally, this research develops an optimization tool to numerically analyze the effect of several factors of the blockchain technology on demand. Moreover, the optimal values of the design variables and the resulting maximum profitability provide valuable insights that support industry in formulating effective policies and making informed strategic decisions.
Purpose Under the current untrusted business environment, digital technologies, such as blockchain technology (BT), show the potential to digitally transform SC processes particularly the sourcing process (SP). Indeed, this process suffers from a lack of digitalization, a lack of trust and a high workload in the automotive supply chain (ASC). Therefore, BT coupled with smart contracts can deal with such issues by fostering trust, transparency, reliability and traceability as a digital solution. Design/methodology/approach This paper conducts multiple case studies in the automotive sector and interviews 11 managers from two firms. It follows the managers’ perspective to identify and analyze the main issues that occurred while conducting this process using the existing technology. Findings It proposes a new architecture for the smart sourcing process (SSP) that uses BT & smart contracts to mitigate the identified issues, enable traceability, improve resilience, eliminate intermediaries, automate tasks, and enhance trust and data management. Also, the paper provides a decision tree to help determine which blockchain platform is needed for adopting the SSP solution. Practical implications This study is useful for both academics and practitioners as it demonstrates the digitalization of one of the SC processes using BT and smart contracts, as well as develops a roadmap for digitalizing the SP of the ASC, and solves its vulnerabilities. Originality/value BT has been used by researchers to digitalize the sourcing process only in the public procurement area. Considering all the faced challenges by the private procurement area, this paper aims to present a new architecture for the digitalization of the SP using BT and smart contracts in the ASC as a private SC.
Cross-border logistics, as a key index connecting the economic activities of different countries and regions, has become increasingly important. However, cross-border logistics industry has faced challenges such as information asymmetry, data silos, and high fraud risks, which seriously constrain the productiveness and credibility of the supply chain, increase logistics costs, and affect customer experience. As a new direction of information technology development, blockchain technology (BT) provides an innovative path to solve these problems with its unique advantages of decentralization, tamper-proof data, high transparency, and traceability. This article proposes a BT-based cross-border logistics data sharing and exchange model. This model achieves real-time sharing and full traceability of logistics information through the distributed ledger technology of blockchain, breaking down data silos and enhancing the authenticity and credibility of data. The experimental results show that the proposed cross-border logistics data sharing and exchange model enhances supply chain transparency, fosters trust among stakeholders, reduces logistics costs, and boosts customer satisfaction.