Digital and intelligent fresh-product supply chains increasingly rely on third-party logistics providers (TPLs) to record and disclose transport-process information. However, the TPL bears data-collection and digital-governance costs while capturing only part of the market value created by credible disclosure. This study develops a supplier-led Stackelberg game for a supplier–TPL–retailer supply chain. Contractual terms are negotiated before operation. Conditional on the negotiated contract, the supplier sets the wholesale price, the TPL selects the disclosure level, and the retailer determines the retail price. We derive decentralized equilibria under blockchain and non-blockchain regimes and compare cost-sharing and joint cost-sharing/revenue-sharing contracts. The results show that cost-sharing increases the TPL’s optimal disclosure level, but disclosure upgrades occur through discrete threshold jumps. Blockchain adoption depends jointly on fixed implementation costs and reliability improvements, and cost-sharing alone may not ensure both adoption and high-level disclosure. Introducing revenue-sharing allows the TPL to internalize part of the demand-side value generated by credible disclosure, leading to a Pareto-improving coordination interval for all supply-chain members. The findings provide a mathematical basis for designing incentive-compatible contracts for blockchain-enabled disclosure in digital fresh product supply chains.
Legacy enterprise resource planning (ERP) systems serve as the operational backbone of global commerce but often create bottlenecks due to their rigid, monolithic design. As organizations incorporate artificial intelligence (AI), these outdated systems struggle to support high-speed, parallel workflows, creating a significant integration challenge. This paper introduces a non intrusive modernization approach that overlays a decentralized multi-agent system (MAS) onto existing infrastructure without requiring invasive code changes. By developing a digital twin of the order-to-cash (O2C) process, we train autonomous agents through multi-agent reinforcement learning (MARL) to manage credit validation, inventory allocation, and fulfillment. We adapt the centralized training, decentralized execution (CTDE) framework to meet O2C constraints, enabling agents to learn globally optimal strategies while operating independently. Simulation results show that this architecture surpasses rule-based robotic process automation (RPA) baselines, increasing total throughput by 6.9% over a monolithic setup, though at a 6.3% error rate due to aggressive allocation policies. These results indicate that decentralized agent-based orchestration provides a scalable approach for modernizing legacy ERPs, offering increased agility without the risks associated with platform replacement.
Healthcare supply chains face increasing challenges related to counterfeit products, fragmented information flows, limited traceability, and insufficient coordination among distributed stakeholders.Existing centralized and partially decentralized approaches still encounter difficulties in maintaining immutable records, real-time verification, and trusted operational transparency across the pharmaceutical distribution process.This study investigates a distributed medical supply chain framework that improves traceability, compliance control, and operational reliability in healthcare logistics.A blockchain-enabled architecture was developed by integrating dynamic quick response (QR)-based identification, customizable smart contracts, and a hybrid consensus mechanism combining Proof-of-Work (PoW) and Proof-of-Stake (PoS).The framework assigned a unique cryptographic identity to each medicine unit and supported end-to-end verification through blockchain-linked QR validation.Smart contracts were designed to automate ownership transfer, compliance checking, and counterfeit detection throughout the supply chain workflow.The framework was implemented and evaluated in a simulated distributed environment using pharmaceutical transaction scenarios.The experimental results showed that the proposed approach achieved average validation accuracy of approximately 98.1%, maintained transaction throughput between 150 and 320 transactions per second (TPS), and reduced consensus delay through adaptive PoW-PoS coordination.The system also demonstrated strong resistance to forgery attempts and stable operational performance across repeated validation experiments.The results indicate that integrating blockchain governance mechanisms with QR-enabled authentication can improve transparency, trust, and traceability in distributed healthcare supply chains.The proposed framework provides a scalable systems engineering solution for pharmaceutical logistics management and offers a practical foundation for compliance-oriented digital transformation in healthcare supply networks.
Ethereum's EIP-1559 fee mechanism was designed under the assumption of homogeneous, myopic agents responding to a single congestion signal. We examine how this assumption interacts with the heterogeneous demand structure of real-world Ethereum users. Analyzing 62,142 confirmed transactions from seven operational firms across seven industries (January--March 2026), we document significant intraday gas-fee variation: fees peak at hour~12 UTC (7\,AM ET, $\hatβ_{12}=\$0.054$ above the U.S.\ evening baseline, $p<0.001$) and are associated with periods of elevated speculative-arbitrage activity. Operational firms exhibit heterogeneous scheduling responses moderated by transaction deferrability and gas intensity. Residual cost floors, i.e. the gap between observed expenditure and the counterfactual under perfect off-peak scheduling, range from 40.7\% to 92.5\% of actual expenditure, and persist even during the lowest-cost hours ($h\in\{20,21,22,23\}$ UTC, 3--6\,PM ET). We introduce an On-Chain Scheduling Matrix that maps firms to four scheduling regimes as a practical framework for managing gas-fee exposure under the current mechanism.
The retail and consumer packaged goods industries are at an inflection point; the autonomous, goal-oriented software agents are substituting the inflexible, analyst-reliant business decision cycles with closed-loop intelligence systems, which can perceive, reason, and act in real-time. The autonomy, proactivity, and constant learning of agentic AI redesign the pricing, trade promotion optimization, and supply chain coordination processes within complicated, multi-account business settings. Based on proven sources of empirical evidence in the literature on machine learning, multi-agent reinforcement learning, and supply chain optimization, the technical architecture of an agentic commercial system is discussed along five related dimensions: autonomous trade performance monitoring through perception-reasoning-action pipelines; cooperative multi-agent system design under the models of centralized training and decentralized execution; scenario simulation engine based on digital twin models; multi-objective trade promotion optimization with Pareto-front metaheuristic algorithms; and practical barriers of data infrastructure, model drift, organizational change management, and algorithmic governance. Bringing these capabilities together into a single agentic decision stack is a paradigm shift in the concept of commercial intelligence in retail and CPG, moving the operational center of gravity off retrospective dashboards and onto adaptive, constantly learning systems that coordinate the decisions on pricing, promotion, and supply.
Essais sur le crédit, la découverte des taux et les facteurs déterminants du prix des jetons en finance décentralisée Cette thèse explore les fondements économiques et comportementaux de la finance décentralisée (DeFi), un champ en pleine expansion où les fonctions de prêt, d'emprunt et de fixation des taux d'intérêt sont assurées par des contrats intelligents plutôt que par des institutions financières. À travers trois essais complémentaires, ce travail analyse la conception des protocoles de crédit décentralisés, la formation des taux d'intérêt dans des marchés automatisés et les déterminants fondamentaux et comportementaux de la valorisation des tokens DeFi.Le premier essai examine l'architecture du protocole Atlendis, qui permet des prêts non ou partiellement collatéralisés grâce à l'articulation entre souscription off-chain et exécution on-chain. Le deuxième propose un modèle théorique de découverte de taux basé sur une approche de jeu multi-unités, identifiant les conditions d'efficience et les frictions propres aux marchés décentralisés. Le troisième évalue empiriquement les facteurs économiques et comportementaux influençant les rendements des tokens, révélant le rôle central du sentiment des investisseurs et de la liquidité on-chain dans la dynamique des prix. En combinant ingénierie financière, modélisation théorique et analyse empirique, cette recherche met en lumière les mécanismes par lesquels la DeFi redéfinit l'intermédiation, la formation des prix et la gouvernance financière dans un environnement transparent et programmable.
The integration of blockchain technology into supply chain management represents a fundamental shift in how goods are tracked, verified, and transferred across global networks. This comprehensive research examines the implementation, impact, and challenges of distributed ledger technology across diverse supply chain ecosystems, with particular focus on transparency enhancement, counterfeit prevention, process efficiency, and stakeholder collaboration. Through a mixed-methods approach analyzing deployment data from 127 organizations across 18 industries over a four-year period, this study demonstrates that blockchain-enabled supply chains achieve an average improvement of 41.3% in traceability accuracy, reduce documentation processing times by 67.8%, and decrease disputes among supply chain partners by 52.4%. The research further reveals that smart contract implementations automate approximately 38.6% of routine supply chain transactions, reducing administrative costs by an average of 31.7% while minimizing human error in compliance verification. Counterfeit detection capabilities improve by 89.2% in pharmaceutical and luxury goods sectors through immutable product provenance tracking. However, the study identifies significant implementation barriers including interoperability challenges with legacy systems, scalability limitations during peak transaction periods, regulatory uncertainty across jurisdictions, and substantial upfront investment requirements averaging $2.3 million per enterprise implementation. The carbon footprint of certain consensus mechanisms, particularly proof-of-work, presents environmental concerns that necessitate alternative approaches for sustainable adoption. This paper proposes a phased implementation framework emphasizing pilot testing, stakeholder education, hybrid architecture models, and regulatory engagement to balance innovation with operational stability. The findings indicate that while blockchain technology offers transformative potential for supply chain transparency and efficiency, successful adoption requires strategic alignment with business objectives, collaborative ecosystem development, and measured progression from discrete applications to integrated systems. The research contributes to both academic understanding and practical implementation guidelines for distributed ledger technology in complex supply chain environments.
Abstract Around three-quarters of Bitcoin transactions occur off-chain. While most empirical studies focus exclusively on on-chain transactions, only few papers analyse off-chain transactions. The empirical evidence of Bitcoin market considering both types of trading strategies remains limited. This paper is one of the first to present an empirical analysis of both on- and off-chain demand and supply-side factors and their short- and long-run relationship with the Bitcoin price. Employing the ARDL approach with daily data from 2019 to 2024, we demonstrate a differentiated contribution of on-chain and off-chain drivers to the Bitcoin price. In the long-run, off-chain demand pressures have a significant relationship with the Bitcoin price. In the short-run, both off-chain demand and supply factors are statistically significantly related to the Bitcoin price. The relationship between blockchain transactions and the Bitcoin price is also present, albeit likely operating through a different channel than off-chain trades. These findings confirm the dual nature of the Bitcoin market, in which price movements are related to both market fundamentals and speculative considerations captured by on- and off-chain trades, respectively.
Christian Finke, Tamino Marahrens, Matthias Schümann
As supply chains (SCs) face increasing pressure from ecological demands, ethical expectations, and global disruptions, Distributed Ledger Technology (DLT) is gaining attention as a potential enabler of transparent, secure, and automated processes, helping to meet the expectations of customers and regulatory authorities. Nevertheless, the lack of generally valid design recommendations hinders its implementation. Therefore, we adopted grounded theory principles within a design science research approach to address this gap. Subsequently, we derived 11 overarching expert insights for developing a DLT operating model in SCs and 15 for its implementation by conducting 16 expert interviews. These insights were finally used to extract 19 generally valid design recommendations for applying DLT in SC processes that contribute to practical implementations and the framing of realistic adoption expectations by guiding researchers and practitioners.
The complexity of modern supply chain networks requires sophisticated approaches to inventory management that can effectively handle demand uncertainty and coordinate decisions across multiple organizational levels. This paper proposes a novel hierarchical multi-agent reinforcement learning framework for dynamic inventory allocation in multi-echelon supply chains facing stochastic demand patterns. The hierarchical architecture decomposes the inventory control problem into strategic and operational decision layers, where high-level agents coordinate allocation policies across distribution networks while low-level agents optimize local replenishment decisions. The framework integrates Centralized Training with Decentralized Execution paradigm, enabling autonomous agents to learn coordinated policies through shared experience while maintaining operational independence during deployment. Experimental results demonstrate that the proposed approach achieves significant reductions in total system costs compared to traditional base-stock policies and single-agent reinforcement learning methods, while effectively mitigating the bullwhip effect in supply chains with high demand variability.
The demand for goods transported by Cargo has existed at all predominant times. A large number of shipments are moved daily based on the demand that exists both in the local and the global market. In the current scenario of cargo shipment, the state of freight is usually monitored throughout the shipment process. This is entirely based on the simple temperature-based regulated storage system called cold-chain. Unfortunately, this temperature-based system does not entirely ensure the preservation of cargo shipments. This paper presents the design of a blockchain-powered Decentralized Application (DApp) to monitor Cargo in heavy goods vehicles. It includes implementing the Ropsten test network, which is integrated with a centralized cloud platform. Moreover, details of a complete evaluation of the architecture in terms of its working functionality were added, and its effectiveness in terms of its performance efficiency and real-time operation. To overcome these limitations, alternative solutions, including adopting Layer-2 scaling solutions such as Polygon or transitioning to Proof of Stake (PoS)-based blockchains for faster and more cost-effective transactions, are recommended. Selective use of Blockchain, where only critical violations are recorded, mitigates the issue of high transaction costs. Routine sensor data is efficiently managed using Google Firestore, ensuring optimal cost efficiency. The system currently relies on Infura for blockchain node access, which introduces external dependencies and potential points of failure. To reduce these risks, the adoption of self-hosted Ethereum nodes is recommended for enhanced control and reliability.
Jinho Cha, Young‐Chul Kim, Junyeol Ryu, Sangjun Park · 6 authors
This study develops a strategic procurement framework integrating blockchain-based smart contracts with bounded demand variability modeled through a truncated normal distribution. While existing research emphasizes the technical feasibility of smart contracts, the operational and economic implications of adoption under moderate uncertainty remain underexplored. We propose a multi-supplier model in which a centralized retailer jointly determines the optimal smart contract adoption intensity and supplier allocation decisions. The formulation endogenizes adoption costs, supplier digital readiness, and inventory penalties to capture realistic trade-offs among efficiency, sustainability, and profitability. Analytical results establish concavity and provide closed-form comparative statics for adoption thresholds and procurement quantities. Extensive numerical experiments demonstrate that moderate demand variability supports partial adoption strategies, whereas excessive investment in digital infrastructure can reduce overall profitability. Dynamic simulations further reveal how adaptive learning and declining implementation costs progressively enhance adoption intensity and supply chain performance. The findings provide theoretical and managerial insights for balancing digital transformation, resilience, and sustainability objectives in smart contract-enabled procurement.
This study examines values and adoption conditions of Blockchain Technology (BCT) in horizontal demand forecast sharing among retailer, focusing on the influence mechanism of transparency-restriction approaches and BCT's endogenous effects on firms' sharing incentives. We model a supply chain with one manufacturer and multiple retailers, comparing four BCT-enabled data-sharing regimes: open access (permissionless) versus no-open access (permissioned), with or without encryption. Results show that restricted transparency, combined with selective accessibility, aligns individual and collective incentives by curbing wholesale price inflation and improving forecast accuracy. Contrary to intuition, higher transparency does not universally benefit retailers; supplementary encryption can balance data utility and privacy, enabling Pareto-superior outcomes. We further demonstrate BCT can reduces moral hazards in horizontal sharing (e.g. sharing biased forecast), allowing retailers to leverage aggregated demand signals without inefficiently verification. However, excessive transparency in BCT can accelerates retailers' profit erosion, akin to perfect competition. These findings offer micro-foundations for adopting visibility-restriction technologies (e.g. Zero-Knowledge Proofs) and guide the design of context-specific BCT systems. By reconciling transparency-privacy tensions and demonstrating BCT's endogenous role in forecasting, this study advances strategies for enhancing supply chain resilience through BCT innovation.
Distributed ledger technology has already been integrated into areas like supply chain management. However, other areas such as e -commerce have been largely neglected in research. For this reason, three application areas-customer experience, transactions and security mechanisms-of distributed ledger technology in e -commerce are identified and described through a systematic literature review. The results are then discussed by highlighting recurring themes and observed potentials. Three possible research areas can ultimately be der ived from this: decoupling from traditional platforms and marketplaces; integrating DLT into e -Commerce systems; new e -commerce business models with DLT that can be considered in the face of new and traditional e -commerce organisations
Rules of origin are a core element of any free trade agreement, but their complexity can present significant challenges for efficient and compliant use. This paper discusses the challenges and opportunities in automating origin calculations for businesses involved in cross-border trade. It focuses on the role of Enterprise Resource Planning (ERP) systems, customs software and Long-Term Supplier Declarations (LTSDs) in simplifying compliance with preferential origin rules. Focusing on the United Kingdom’s trade, the paper outlines key factors businesses must consider to effectively automate origin management, such as rules interpretation, data quality, legal documentation and supplier cooperation. The potential roles of distributed ledger technology (DLT) and automation within customs declarations software are also explored.
The cold-chain supply of perishable fruits continues to face challenges such as fuel wastage, fragmented stakeholder coordination, and limited real-time adaptability. Traditional solutions, based on static routing and centralized control, fall short in addressing the dynamic, distributed, and secure demands of modern food supply chains. This study presents a novel end-to-end architecture that integrates multi-agent reinforcement learning (MARL), blockchain technology, and generative artificial intelligence. The system features large language model (LLM)-mediated negotiation for inter-enterprise coordination, Pareto-based reward optimization balancing spoilage, energy consumption, delivery time, and climate and emission impact. Smart contracts and Non-Fungible Token (NFT)-based traceability are deployed over a private Ethereum blockchain to ensure compliance, trust, and decentralized governance. Modular agents-trained using centralized training with decentralized execution (CTDE)-handle routing, temperature regulation, spoilage prediction, inventory, and delivery scheduling. Generative AI simulates demand variability and disruption scenarios to strengthen resilient infrastructure. Experiments demonstrate up to 50% reduction in spoilage, 35% energy savings, and 25% lower emissions. The system also cuts travel time by 30% and improves delivery reliability and fruit quality. This work offers a scalable, intelligent, and sustainable supply chain framework, especially suitable for resource-constrained or intermittently connected environments, laying the foundation for future-ready food logistics systems.
This research aims to investigate financing decisions of capital-constrained small and medium-sized enterprise (SME) manufacturers and distributors under a Green Supply Chain (GSC) framework. By evaluating the impact of Supply Chain Finance (SCF) instruments, this study utilizes Stackelberg game model to explore a decentralized decision-making system. To our knowledge, this investigation represents the first exploration of game models that uniquely compares financing through trade credit, where the manufacturer offers zero-interest credit without discounts with reverse factoring, while also considering distributor’s efforts on sustainable marketing under the impact of supportive government policies. Our study suggests that manufacturers should adopt reverse factoring for optimal profits and actively participate in distributors’ financing decisions to address inefficiencies in decentralized systems. Furthermore, the distributor’s demand quantity, profits and sustainable marketing efforts show significant increase under reverse factoring, aided by favorable policies. Finally, the results are validated through Python 3.8.8 simulations in the Anaconda distribution, offering meaningful insights for policymakers and supply chain managers.
Blockchain technology, underpinned by distributed ledger systems, has evolved from a novel innovation into a transformative and integral component of enterprise digitization across industries. Since its inception with Bitcoin in 2008, blockchain has expanded beyond cryptocurrencies, with applications in operations management (OM) growing rapidly across industries. Despite its promise, however, the integration of blockchain into OM is not without challenges. Scholars have identified significant barriers to successful implementation, ranging from technological and organizational hurdles to regulatory complexities (Chod et al. 2020; Hanisch et al. 2025; Lin et al. 2022; Lumineau et al. 2021; Sodhi et al. 2022; Zhan et al. 2025). This Special Issue on Operational Perspectives on Blockchain Applications presents cutting-edge research that explores blockchain's opportunities, challenges, and implications for OM. The articles in this issue provide a diverse and empirically grounded examination of blockchain applications across industries and operational contexts. We will discuss each contribution in turn. However, prior to that, it is useful to dig into the operational nuances, opportunities, and challenges presented by the focal context. Our editorial discussion opens accordingly, outlining the technological, organizational, and regulatory challenges while identifying the conditions under which blockchain can deliver value. We also touch on the broader societal implications of blockchain, addressing its political, economic, social, environmental, and legal dimensions before describing how each of the papers in the special issue contributes to understanding, critical to operations management. Finally, our editorial discussion concludes by charting a research agenda, highlighting key questions and interdisciplinary approaches needed to advance both theoretical and practical understanding of blockchain in OM. Working processes need to be discovered, described, and understood before they can be improved, controlled, and prescribed. Quite a bit of work is needed merely to describe some of the important activities, practices, processes, and operating systems utilized in diverse organizations. Only then can we begin to sink our teeth into developing better theories about how best to manage them. For this purpose, Ilk et al. (2021) conceptualize the Bitcoin blockchain (and other mainstream permissionless blockchains) as a two-side dataspace market, where users demand a certain amount of dataspace in a future block to store their transactions, and miners compete to produce such dataspace by creating new blocks. To facilitate this market in a decentralized manner—that is, with no centralized party absorbing demand and controlling supply—users attach a transaction fee (which is higher for users with a higher waiting cost) that becomes one of the miners' sources of revenue. With the increasing popularity1 of Bitcoin and Ethereum, demand frequently exceeds supply, creating contemporaneous system congestions. The congested service pricing literature, which dates back to the management of highway tolls (Naor 1969) and electric power supply (Viswanathan and Edison 1989) and extends in modern days to subscription pricing of cloud services (Cachon and Feldman 2011) and surge pricing of gig economy platforms (Cachon et al. 2017), yields a generalized conclusion. Specifically, “offering multiple service grades that each render a different delay distribution at a different price” improves both perceived customer satisfaction and service provider profit (Van Mieghem 2000, 1249). Permissionless blockchains, as congested service systems, are no exception to this rule. Although no centralized party (i.e., firm or platform) sets the priority price menu, users bid transaction fees to differentiate the service grades (i.e., transaction confirmation speeds) they desire. More details on the process view of permissionless blockchain transactions can be found in Shang et al. (2023, 106–108). Although early Ethereum-based smart contract applications were rarely associated with OM or any other real-world assets, their ingenuity inspired a whole class of permissioned blockchains (also referred to as private or consortium chains), in which only an authorized group of users can participate, setting the stage for enterprise applications (Fan et al. 2024; Pun et al. 2021). While blockchain offers considerable potential, its successful implementation is hindered by technological, organizational, and regulatory barriers. Below, we highlight seven of the most critical challenges to blockchain implementation discussed in the press and in the literature. Low throughput and high transaction fees. The primary reason that mainstream cryptocurrency systems cannot be used for day-to-day payment is their throughput limits: 3 per second for Bitcoin and 13 per second for Ethereum.2 This limitation is in sharp contrast with the processing capacity of established financial systems like Visa, which is capable of handling approximately 5000 transactions per second (Malik et al. 2022). Such scalability limits are largely inevitable for permissionless blockchains that aim to ensure decentralization and security, widely known as the “blockchain trilemma” in the industry.3 The throughput limit results in a frequently congested service system with transaction fee spikes (Ilk et al. 2021; Shang et al. 2023), which has been 2.87 USD per transaction for Bitcoin in 2020. This hinders the economic viability of small value transactions even in situations where network latency is less of a concern (e.g., users with high waiting tolerance). Meanwhile, permissioned blockchains typically do not face throughput limits, as dataspace suppliers are usually the blockchain owners and hence do not have to be incentivized via instruments such as transaction fees. However, due to the lack of public visibility and the corporate ownership of these blockchains, this solution is unlikely to be suitable for all applications. Algorithm fairness. Advocates of permissionless blockchains often highlight their morally significant goal of improving access to money transfer services for unbanked and underbanked populations (Andreasson 2022). Importantly, much of the wealth on permissionless blockchains is created through mining/staking revenue—that is, through participation on the supply side—and small users typically cannot meet the entrance threshold for this revenue stream. Further, while large senders can develop sophisticated algorithms to estimate the desired transaction fee more accurately, small senders typically rely on the free-to-use fee recommendation tools crypto wallets provide. Encouragingly, this disparity is somewhat alleviated by new transaction fee mechanism designs (Zhao, Wu, et al. 2025). Decentralization–efficiency tradeoff. The management of a cryptocurrency system is typically maintained by a decentralized autonomous organization (DAO). A DAO's daily operational tasks include the development of, voting on, and execution of crowdsourced proposals (Zhao et al. 2022). Yet, not all project decisions are strategic enough to warrant crowdsourcing of ideas from stakeholders, and the inefficiency of doing so affects operational agility and the quality of service provided by the DAO. Further, while decentralization can improve service levels for users and providers, it reduces profits for founders, reflecting a broader tension between decentralization and efficiency (Gan et al. 2023). Governance frictions are compounded by token-weighted voting, where those holding more tokens have greater influence, creating a mismatch between token ownership and subject expertise (Benhaim et al. 2023, 2025; Tsoukalas and Falk 2020). Cross-chain interoperability. A successful blockchain application often requires coordination of activities across multiple chains. This is especially true for enterprise applications, where material flow needs to be traced on a permissioned blockchain (for obvious business confidentiality reasons) and payment of goods should preferably happen on a permissionless blockchain. In general, the lack of universal standards creates a fragmented landscape in which disparate blockchain platforms are developed in isolation. This technical challenge of interoperability is further complicated by the need to integrate blockchain with legacy systems, which typically lack the flexibility to accommodate cryptographic protocols and distributed data synchronization (Babich and Hilary 2019). Standardization of input data. Many of the cargo tracking and supply chain traceability blockchain applications assume the existence of a data on-ramp that is accessible to and standardized across participants. This is far from reality. As Fan et al. (2024, 3) put it, “a small supplier, say, in India or China, is unlikely to have the resources or expertise to set up an arrangement to access blockchain.” Even if such access is set up by a large participant of the permissioned blockchain, such as a superstore retailer, the input data from thousands of small suppliers across the world might not be properly digitized and standardized. Both the invasive and non-invasive approaches to bridging the physical–digital interface in blockchain applications have merits and drawbacks (Klöckner et al. 2023). Buy-in from partner organizations. Lin et al. (2022) highlight buy-in from partners along with information complexity as two important drivers that determine the success of blockchain pilots in real life. They stress the importance of reducing information complexity as well as increasing buy-in among supply chain partners. Critically, the cost and hassle of implementation are borne by all organizations that the cargo passes through, including port authorities, customs agencies, shipment forwarders, trucking companies, and so on. Some of these organizations lack the basic incentive to even digitize their paperwork, let alone upload information onto a blockchain owned by another company. Regulatory uncertainty. Regulatory challenges present another significant barrier to blockchain adoption in OM. The regulatory framework for blockchain is still in a nascent stage, with many jurisdictions lacking clear guidelines regarding its use, especially in non-financial contexts such as OM (Wagner et al. 2025). The cross-border nature of many supply chains makes it even more challenging to reconcile diverse regulatory environments; thereby complicating large-scale implementations (Wamba and Queiroz 2020). In summary, blockchain presents a range of unique characteristics, implementation challenges, and potential transformative impacts. Figure 1 captures many of these, as well as presenting new opportunities to apply common theoretical lenses used by researchers to understand this new technology, including Transaction Cost Economics (TCE), Principal Agent Theory (PAT), and Resource-Based View (RBV). These features are pushing the OM community to consider additional theoretical arguments regarding blockchain-related operational dynamics so as to more comprehensively understand, anticipate, and ultimately contribute to practice and scholarship in this domain. More specifically, traditional theoretical frameworks commonly applied in OM, such as transaction cost economics, principal–agent theory, and the resource-based view, have proven effective for analyzing centralized systems where information is controlled and trust is built through well-established interorganizational relationships. However, blockchain disrupts these conventional relationships by enabling peer-to-peer interactions governed not by a central authority but by cryptographic mechanisms and consensus protocols. For instance, the immutability of recorded transactions and the inherent decentralization of blockchain networks modify the traditional calculus of trust and coordination costs. These features create “trustless” environments where the need for intermediaries is significantly reduced. This shift calls into question the applicability of many preexisting theoretical models that assume reliance on centralized control and interpersonal trust (Lumineau et al. 2023). Given these fundamental differences, one promising direction for future research is to expand network theory and social capital theory in OM by integrating the notion of distributed trust. Whereas social capital theory has been used to explain performance improvements arising from strengthened interorganizational relationships (Saberi et al. 2019), blockchain technology challenges these premises by redistributing trust across the network without necessarily relying on strong personal or organizational ties (Lumineau et al. 2023). Similarly, although transaction cost theory provides insight into how blockchain can lower the costs of verification and contracting by obviating the need for costly intermediaries, the theory does not fully account for the dynamic interplays that arise when trust is engineered digitally and contractual obligations are embedded in smart contracts (Halaburda et al. 2024). As Babich and Hilary (2019) note, new theoretical models need to capture not only the cost-saving benefits of disintermediation but also the potential trade-offs in terms of data insecurity and operational inflexibility. There is also a growing recognition that hybrid frameworks, which merge elements of institutional theory and network governance with emerging blockchain paradigms, may be necessary to understand new organizational forms like DAOs (Zhao et al. 2022). The need for novel theoretical frameworks is particularly critical when considering the impact of blockchain on various stakeholders within the OM ecosystem. Traditional models generally emphasize dyadic relationships between buyers and suppliers, but blockchain enables multi-stakeholder environments in which data transparency, provenance, and auditability permeate complex, global supply networks. For example, Chod et al. (2020) show how blockchain can improve financing in agricultural supply chains by enabling farmers to use harvest inventory as loan collateral. Using multi-signature setups tied to an immutable blockchain, transactions require confirmation from both humans (e.g., lenders or warehouse operators) and automated systems (e.g., IoT sensors). This approach allows for real-time verification of collateral, reduces information asymmetry, and unlocks capital, particularly in settings prone to fraud. Together, the articles in this Special Issue make a multifaceted contribution to OM, demonstrating the impact of blockchain technology in various operational forms on strategic decision-making, worker participation, competitive and network dynamics, and intellectual property protection across different sectors. These studies use robust empirical methods and diverse theoretical frameworks to offer novel insights into the role of blockchain in OM. Some of the studies use qualitative methods for developing theory concerning conditions for successful and failed blockchain adoption. Zhan et al. (2025) develop theory through an inductive, multi-case research design revealing the influence of founder power on blockchain adoption. Meanwhile, Hanisch et al. (2025) use an in-depth, longitudinal case study to explore the centralization–decentralization paradox of a group of studies or designs at the of or a and et al. (2025) on adoption of smart contracts and their operational studies use data from network or blockchain platforms Ethereum, and For example, (2025) and approaches to the operational impact of different consensus protocols on and worker et al. (2025) a by integrating ownership theory, and approaches to explore how decentralized ownership in DAOs et al. (2025) further develop the discussion by analyzing the transformative of blockchain on the protection of in In a et al. (2025) the impact of a on the operational the and et al. (2025) use an to the of on a decentralized and a centralized social These articles theoretical and empirical approaches to blockchain in OM, a on its strategic and operational most of the articles on or methods data from blockchain while a articles case studies and This may be due to the lack of large-scale data on OM Below, we will into the of each Zhan et al. (2025) explore how in dimensions of and ownership the and of blockchain adoption in technology provider that a centralized process and in by integrating insights from traditional to use decentralized approaches and rely on This work contributes to bridging and blockchain in OM, strategic implications for how the successful of supply chain Hanisch et al. (2025) study governance challenges in blockchain the centralization–decentralization paradox in a blockchain on paradox theory, they show that between might arise when and conditions are not These and the that limit the for the blockchain explain platforms and on a study of smart contract adoption and transaction cost economics, et al. (2025) that smart contract adoption improves operational efficiency with to and costs. They also that with high supply chain complexity more from smart contract adoption those with a distributed supply (2025) the critical role of mechanisms in blockchain two consensus and study on the by The that the design of worker participation and the of decentralization necessary for operational empirical that which blockchain as transaction costs and reduces to This study the understanding of blockchain as a organizational and provides OM with a novel on how automated governance mechanisms from consensus protocols can et al. (2025) contribute to this emerging by addressing blockchain's implications in intellectual property protection and particularly in the of work offers a framework through which mechanisms can facilitate and value in industries. The study how as a of both ownership and an between management and operational within OM. et al. (2025) the potential of blockchain to intellectual on the protection of in transaction cost to the the present a of how smart contracts and can while reducing market offer insights into the operational necessary to decentralized protection systems, further the potential of blockchain in traditional OM et al. (2025) the discussion to the competitive of platforms by analyzing the which an while to and participants. The this impact on the operational integrating insights on DAOs with theory, the how a unique of that disrupts traditional centralized The empirical to the mechanisms by which blockchain can market dynamics, demonstrating the broader strategic cost implications for OM. Finally, et al. (2025) how to on decentralized social which lack central authority and rely on community Using an with data from and the and show these methods in decentralized to centralized on decentralized networks and more but in a The research contributes to operations management by decentralized platforms as systems and practical insights for governance and Given the from the most research on the it clear that research questions and that might our understanding of blockchain's application opportunities and potential for OM. research question of in this framework is as do different blockchain governance impact operational efficiency and trust in on this should consider the between permissioned and permissionless blockchain how of decentralization and the role of smart contracts influence both and A study methods might performance data from blockchain with qualitative to how governance models trust among supply chain critical for effective potential of study into how blockchain can be embedded within enterprise and supply chain information systems to the and for more blockchain technology new models for inventory management of that account for customer of et al. 2024). might traditional inventory models with systems, case studies or controlled that improvements in and in with the of operations management such studies should on process details and merely the of technology and such as inventory A further further to is, can blockchain be to in supply chains This of research tracking and smart contracts the for and as well as how this technology can a role by in supply networks. studies that supply chain performance across as well as studies to blockchain's impact under various be particularly question might can blockchain be to in supply or should supply chain be with blockchain technology to or data However, these questions might also more in the of information systems particularly if their is not to operational process In future research in this will from into the multifaceted implications of blockchain technology for OM. research the impact of blockchain governance on operational efficiency and the transformative potential of blockchain for inventory management and supply chain and the capacity to in the face of central to both theoretical and practical an interdisciplinary approach that from public information technology, and organizational theory, future research can develop frameworks that the real-world challenges of blockchain in supply networks. The implications of blockchain in OM are multifaceted and transformative (Klöckner et al. 2022). blockchain challenges centralized power decentralization and it reduces costs and barriers to market financial it also disrupts traditional systems and new blockchain and its benefits on addressing the blockchain offers tools to but challenges to it regulatory frameworks while questions about data and cross-border Blockchain not a technological innovation but a for societal To fully its potential, interdisciplinary among and is addressing its challenges and its blockchain can contribute to practices, and social The future of blockchain in OM will on our to its transformative potential while the complexities of its
Efficient smart contract implementation affects gas fees required for deployment and invocation, contributing to the usability and sustainability of blockchain applications that rely on smart contracts. Optimizing smart contract codes is crucial to curb the continued rise of costs related to deploying and invocating smart contracts. This work proposes an extended version of static smart contract optimizer to reduce unnecessary gas fees caused by inefficient smart contract code implementation. Thirty open-licensed Ethereum smart contract codes in the Solidity programming language are included for optimization using the proposed static optimizer. The results show a decrease of 11,447 gas for deployment and 25 for invocation. Additional optimization using the Solidity compiler optimizer reveals a further gas reduction of 9,331 for deployment. Although there was a slight gas increase of 23 during invocation. These findings demonstrate the contribution of the proposed static optimizer in optimizing code implementation for Solidity smart contracts in terms of deployment and invocation. In addition to the gas reductions, the functionalities of the optimized smart contracts remain the same.