Marc Hübschke, Marius Gros, Benedikt Latos, Elmar Holschbach · 5 authors
Purpose Blockchain technology is widely discussed as an enabler of transparency, efficiency and trust in supply chain management (SCM). However, empirical evidence on which blockchain-related success dimensions translate into value perceptions remains limited. This study aims to examine how the perceived relevance of blockchain success dimensions relates to realized benefits and whether these benefits contribute to overall perceived blockchain value. Design/methodology/approach A quantitative survey of 41 companies with blockchain experience in SCM is conducted. Success dimensions are prioritized using best–worst scaling (MaxDiff). Relationships between perceived relevance, dimension-specific benefits and overall perceived value are analyzed using partial least squares structural equation modeling (PLS-SEM). Exploratory analyses assess company characteristics. Findings Contrary to dominant expectations in academic and practitioner narratives, even highly prioritized blockchain success dimensions fail to translate into measurable firm-level value perceptions. While transparency and traceability are associated with significant dimension-specific benefits, these improvements do not produce statistically significant direct or indirect effects on overall perceived blockchain value. This suggests that localized operational gains alone may be insufficient to generate overall perceived value and indicates that blockchain benefits may depend on broader organizational and technological complements. Originality/value The study moves beyond identifying potential blockchain benefits by empirically differentiating which success dimensions matter and which do not. By combining MaxDiff with PLS-SEM, it offers a structured, mechanism-oriented framework for evaluating blockchain success and highlights boundary conditions for value realization in SCM.
With the standardization of the logistics market and advancements in innovation, trust issues arising from information asymmetry among supply chain participants have become increasingly prominent. This paper examines a blockchain-enabled collaborative regulatory system for logistics service supply chains involving the government, logistics enterprises, and the logistics market. Using evolutionary game theory, a three-party evolutionary game model is constructed and validated through system dynamics simulations to explore the impacts of various factors on the collaborative regulatory system. The results indicate that, during the system’s evolution, logistics enterprises stabilize first, followed by the government, with the logistics market converging the slowest. The added value of logistics services is identified as the core factor driving logistics enterprises to adopt blockchain, exhibiting a significantly stronger impact compared to regulatory benefits or improvements in quality and safety. While robust incentive policies can rapidly increase enterprises’ willingness to adopt blockchain technology, they concurrently weaken the government’s enthusiasm for regulation.
Background Scientific output on digital transformation in healthcare and pharmaceutical supply chains increased substantially after 2020, indicating growing research attention to resilient and digitally integrated logistics systems. However, the literature remains fragmented across technologies such as blockchain, artificial intelligence, Internet of Things, predictive analytics, cold chain monitoring and healthcare logistics optimization. Methods This study conducted a bibliometric analysis of scientific publications related to digital transformation and emerging technologies in healthcare and pharmaceutical supply chains. Data were retrieved from Scopus, PubMed and Web of Science databases following PRISMA 2020 screening principles. After duplicate removal and eligibility assessment, 83 peer-reviewed English-language journal articles published between 2015 and 2026 were included in the final analysis. Bibliometric mapping and thematic analysis were performed using VOSviewer and Bibliometrix/Biblioshiny. Results Within the analyzed corpus, the results showed a substantial increase in scientific publications after 2020, consistent with growing research attention to resilient and digitally integrated healthcare supply chains. Blockchain showed the highest visibility in keyword and citation-based analyses, particularly in relation to traceability, transparency and anti-counterfeit systems. Additional major research areas included artificial intelligence, predictive analytics, IoT-based cold chain monitoring and healthcare logistics optimization. Thematic analysis identified strong literature-based associations between digital technologies, supply chain resilience and pharmaceutical traceability systems. Conclusions Digital technologies are increasingly represented in research on healthcare and pharmaceutical supply chain transformation. The findings suggest that blockchain, AI and IoT technologies may support transparency, traceability and operational resilience. However, implementation barriers related to interoperability, infrastructure costs, data privacy and regulatory complexity remain significant challenges. These findings should be interpreted as bibliometric and thematic patterns within the analyzed English-language journal literature rather than direct evidence of technology implementation effectiveness.
To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation.
Supply chain finance (SCF) plays a pivotal role in maintaining liquidity and operational continuity across global value networks. However, systemic supply chain disruptions, macroeconomic volatility, and information asymmetry frequently expose SCF programs to severe friction and default risks. While digital transformation is widely touted as a catalyst for supply chain resilience, empirical evidence regarding the explicit mechanisms through which distinct digital transformation capabilities enhance Supply Chain Finance Resilience (SCFR) remains fragmented. Grounded in the Resource-Based View (RBV), Dynamic Capabilities Theory (DCT), and Information Processing Theory (IPT), this study develops and tests an integrated framework evaluating the direct and indirect impacts of Artificial Intelligence Capability (AIC), Blockchain Capability (BC), and Data Analytics Capability (DAC) on SCFR, mediated by Digital Trust in SCF Platforms (DT).Using a computational research simulation methodology, a respondent-level dataset (N=500) representing supply chain, finance, operations, and IT decision-makers across international enterprises was algorithmically generated under a defensible latent-variable covariance structure. Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000 bootstrap resamples was executed to evaluate the measurement and structural models. The structural analysis reveals that AIC (β=0.241,p<.001), BC (β=0.312,p<.001), and DAC (β=0.284,p<.001) significantly and positively drive Digital Trust in SCF Platforms, explaining 54.2% of its variance (R^2=0.542). Digital Trust, in turn, exerts a substantial direct effect on SCFR (β=0.385,p<.001). Furthermore, direct effects on SCFR were confirmed for DAC (β=0.218,p<.001) and AIC (β=0.152,p=.002), whereas the direct link from BC to SCFR was non-significant (β=0.071,p=.158). Formal mediation testing using percentile bootstrapping confirmed that Digital Trust fully mediates the relationship between Blockchain Capability and SCFR, while partially mediating the relationships for AIC and DAC. The overall structural model accounts for 58.6% of the variance in Supply Chain Finance Resilience (R^2=0.586,Q_"predict" ^2=0.412).This methodological prototype advances theoretical understanding by unpacking the granular capability configurations necessary to foster digital trust and financial resilience in supply networks. For practitioners and policymakers, the findings highlight that investing in blockchain technology yields minimal resilience benefits unless coupled with platform-wide digital trust mechanisms, whereas AI and analytics offer dual-pathway benefits across operational and relational domains.
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.