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In the context of accelerated digital transformation, organizations increasingly operate as complex systems in which strategic decision-making is challenged by uncertainty, data heterogeneity, and bounded rationality. The integration of artificial intelligence (AI) into organizational processes is therefore redefining how decisions are supported and enacted. This study develops and validates an integrated conceptual model that explains how trust in AI-based decision support systems (AI-DSSs), data transparency and quality, perceived usefulness, and ease of use influence decision-making efficiency and the intention to adopt AI-DSS in complex organizational contexts. The empirical analysis is based on a questionnaire survey administered to 324 respondents from Romanian organizations operating in IT, services, industry, and public administration. Data were analyzed using partial least squares structural equation modeling (PLS-SEM) implemented in SmartPLS 4. The results show that data transparency and quality strongly enhance trust in AI-DSS (β = 0.784, p < 0.001). Trust positively influences both perceived usefulness (β = 0.229, p < 0.01) and perceived ease of use (β = 0.482, p < 0.001), confirming its role as a key psychological enabler of favorable technology perceptions. Furthermore, perceived ease of use significantly affects perceived usefulness (β = 0.597, p < 0.001). Regarding adoption-related attitudes, perceived usefulness (β = 0.352, p < 0.001), trust (β = 0.311, p < 0.001), and perceived ease of use (β = 0.135, p < 0.05) exert significant positive effects on the intention to adopt AI-DSS, which in turn demonstrates a strong association with decision-making efficiency (β = 0.544, p < 0.001). By extending traditional technology acceptance models (TAM) with AI-specific dimensions—namely transparency, data quality, and trust—this study contributes to the literature on decision-making in complex systems and offers practical insights for organizations seeking to improve decision effectiveness through AI-based support.

\"The Future of Open Data flows from a multi-year Social Sciences and Humanities Research Council (SSHRC) Partnership Grant project that set out to explore open government geospatial data from an interdisciplinary perspective. Researchers on the grant adopted a critical social science perspective grounded in the imperative that the research should be relevant to government and civil society partners in the field. This book builds on the knowledge developed during the course of the grant and asks the question, \"What is the future of open data?\" The contributors' insights into the future of open data combine observations from five years of research about the Canadian open data community with a critical perspective on what could and should happen as open data efforts evolve. Each of the chapters in this book addresses different issues and each is grounded in distinct disciplinary or interdisciplinary perspectives. The opening chapter reflects on the origins of open data in Canada and how it has progressed to the present date, taking into account how the Indigenous data sovereignty movement intersects with open data. A series of chapters address some of the pitfalls and opportunities of open data and consider how the changing data context may impact sources of open data, limits on open data, and even liability for open data. Another group of chapters considers new landscapes for open data, including open data in the global South, the data priorities of local governments, and the emerging context for rural open data.\"-- Provided by publisher

Purpose This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger. Design/methodology/approach The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis. Findings The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency. Research limitations/implications This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management. Practical implications Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations. Social implications In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment. Originality/value This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

Today's healthcare data management systems are facing key challenges in terms of data transparency, traceability, immutability, audit, data provenance, flexible access, trust, privacy, and security. Also, a large portion of existing healthcare systems leveraged for managing data are centralized that pose potential risks of single point of failures in case of natural disasters. Blockchain is an emerging and disruptive decentralized technology that has the potential to significantly revolutionize, reshape, and transform the way data are being handled in healthcare industries. In this paper, we discuss how leveraging blockchain for healthcare data management systems can lead to stimulate innovations and bring major improvements. We present the key blockchain features and characteristics. We discuss the premier advantages of adopting blockchain technology along with opportunities for healthcare industries. We present recent on-going projects and case studies to show the practicality of blockchain technology for various healthcare applications. We identify and discuss important open research challenges hindering the successful adoption of blockchain in the healthcare sector. Finally, we outline several future research directions.

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative). A systematic review, combined with a stakeholder survey, presents an overview of current practices and recommendations for dataset curation in health, with specific focuses on data diversity and artificial intelligence-based applications.

PurposeBlockchain technology (BT) is setting world-shattering standard in all type of transactions in business. BT has the prospective to drastically transform supply chain (SC). The main challenge is to enhance trust among the SC stakeholders. This paper aims to identify and prioritize the factors and its challenges that influence the adoptability of BT in SC. The prioritization of these factors will be helpful to the practitioners to decide the strategy of implementing the BT in SC.Design/methodology/approachThe factors influencing adoption of BT are identified from the review of literature and expert opinion is used to rank the factors influencing the adoptability of BT in SC using grey relational analysis (GRA).FindingsWe identified and prioritized key factors: inter-organizational trust and relational governance as organizational challenge, data transparency and data immutability as technological challenge, interoperability and product type as operational challenge and social influence and behavioral intention as social challenge that influences adoptability of BT in SC.Originality/valueThe priority of these factors will guide future researchers and industry practitioners to plan rational and financial strategy for implementing BT in SC.

Internal auditing demands innovative and secure solutions in today’s business environment, with increasing competitive pressure and frequent occurrences of risky and illegal behaviours. Blockchain along with secure databases like encryption improves internal audit security through immutability and transparency. Hence integrating blockchain with homomorphic encryption and multi-factor authentication improves privacy and mitigates computational overhead. Recently, blockchain applications for internal audits in the enterprise sector are still emerging. Thus, blockchain technology in auditing provides the benefits of enhanced transparency and immutability in data processing, which can establish new solutions for internal auditing but still lacks encryption techniques. The research proposed a framework called “BlockCryptoAudit” to enhance internal audit processes through cryptographic encryption methods and blockchain technology, ensuring secure and transparent audit operations. The proposed approach integrates an additive homomorphic Paillier encryption scheme with blockchain to create a safe and tamper-resident audit trail. Utilizing homomorphic Paillier encryption, BlockCryptoAudit ensures that computations may be performed on encrypted audit data while safeguarding data privacy. The applied blockchain hyperledger component guarantees the immutability and transparency of encrypted audit records, resulting in a decentralized and tamper-resistant record. By limiting data accessibility to authorized individuals based on specified responsibilities, role-based access restrictions handled using smart contracts further strengthen security. The study protects audit data’s security and confidentiality by encrypting it and putting it on a blockchain. The study compares the proposed BlockCryptoAudit with models like B-OAP, BSE-DF, and EG-FLB regarding risk mitigation, audit quality, security overhead, and audit trail effectiveness. With little security overhead, BlockCryptoAudit beats out B-OAP, BSE-DF, and EG-FLB in terms of risk mitigation (98%) and audit quality (99%). It is an effective way to improve internal audit processes and guarantee data integrity due to its high performance.

Clinical study reports (CSRs) are highly detailed documents that play a pivotal role in medicine approval processes. Though not historically publicly available, in recent years, major entities including the European Medicines Agency (EMA), Health Canada, and the US Food and Drug Administration (FDA) have highlighted the importance of CSR accessibility. The primary objective herein was to determine the proportion of CSRs that support medicine approvals available for public download as well as the proportion eligible for independent researcher request via the study sponsor. This cross-sectional study examined the accessibility of CSRs from industry-sponsored clinical trials whose results were reported in the FDA-authorized drug labels of the top 30 highest-revenue medicines of 2021. We determined (1) whether the CSRs were available for download from a public repository, and (2) whether the CSRs were eligible for request by independent researchers based on trial sponsors’ data sharing policies. There were 316 industry-sponsored clinical trials with results presented in the FDA-authorized drug labels of the 30 sampled medicines. Of these trials, CSRs were available for public download from 70 (22%), with 37 available at EMA and 40 at Health Canada repositories. While pharmaceutical company platforms offered no direct downloads of CSRs, sponsors confirmed that CSRs from 183 (58%) of the 316 clinical trials were eligible for independent researcher request via the submission of a research proposal. Overall, 218 (69%) of the sampled clinical trials had CSRs available for public download and/or were eligible for request from the trial sponsor. CSRs were available from 69% of the clinical trials supporting regulatory approval of the 30 medicines sampled. However, only 22% of the CSRs were directly downloadable from regulatory agencies, the remaining required a formal application process to request access to the CSR from the study sponsor.

Purpose The global food industry is faced with the dilemma of finding a balance between food wastage and food shortage. Approximately one-third of food produced globally goes to waste, while about 800 million people suffer from undernourishment. Given this context, the purpose of this study is to investigate the unresolved challenges related to enhancing transparency associated with products of high perishability and low shelf life. Design/methodology/approach The authors conducted 25 interviews with global agri-food supply chains (AFSCs) experts to ask what impedes the progress of the current technologies, such as blockchain, to enable transparency and traceability (T&T) in AFSCs. Findings The findings indicate barriers at the individual, firm and supply chain levels. Based on these barriers, the authors propose an interconnected framework to explain technologically-driven T&T and guide on barrier removal from AFSCs. The authors conclude that by applying technology (i.e. blockchain) the authors can resolve the tension of supporting T&T in AFSCs. This can enable the efficient and transparent tracking of goods, reduction of food waste and loss, as well as promotion of the use of recyclable packaging and further sustainable practices and materials, all of which are aligned with a range of UN Sustainable Development Goals (2, 8, 10 and 12). Moreover, the authors see that some factors are interrelated. Based on these factors, the authors build an interconnected framework to guide on barrier removal from AFSCs. Managers in AFSC would find the findings especially relevant. Originality/value Drawing on industrial network theory and signalling theory, the authors propose an interconnected framework for explaining barriers (challenges) and potential solutions (opportunities) to T&T in AFSCs. This framework is developed by examining the interconnections of barriers at micro, meso and macro levels and applying signalling theory to explain how solutions address these barriers. The specific contributions of this study are: the list of barriers that impede the implementation of technological solutions for T&T in AFSCs; and a three-stage framework that explains how to remove the barriers for T&T. The study is limited by the focus on blockchain, which calls for future research once the next decentralised technology becomes available.