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Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

The purpose of this study is to examine the state of research into adoption of machine learning systems within the health sector, to identify themes that have been studied and observe the important gaps in the literature that can inform a research agenda going forward.

A systematic literature strategy was utilized to identify and analyze scientific papers between 2012 and 2022. A total of 28 articles were identified and reviewed.

The outcomes reveal that while advances in machine learning have the potential to improve service access and delivery, there have been sporadic growth of literature in this area which is perhaps surprising given the immense potential of machine learning within the health sector. The findings further reveal that themes such as recordkeeping, drugs development and streamlining of treatment have primarily been focused on by the majority of authors in this area.

The search was limited to journal articles published in English, resulting in the exclusion of studies disseminated through alternative channels, such as conferences, and those published in languages other than English. Considering that scholars in developing nations may encounter less difficulty in disseminating their work through alternative channels and that numerous emerging nations employ languages other than English, it is plausible that certain research has been overlooked in the present investigation.

This review provides insights into future research avenues for theory, content and context on adoption of machine learning within the health sector.

The objective of this study is to improve the food supply chain performance taking into consideration the fundamental concepts of traceability by combining the current frameworks, its principles, its implications and the emerging technologies.

A narrative literature review of already existing empirical research on traceability systems was conducted resulting in 862 relevant papers. Following a step-by-step sampling process, the authors ended up with 46 final samples for the literature review.

The main findings of this study include the various descriptions of the architecture of traceability systems, the different sources enabling this practice, the common desirable attributes, and the enabling technologies for the deployment and implementation of traceability systems. Moreover, several technological solutions are presented, which are currently available for traceability systems, and finally, opportunities for future research are provided.

It provides an insight, which could affect the implementation process of traceability in the food supply chain and consequently the effective management of a food traceability system (FTS). Managers will be able to create a traceability system, which meets users' requirements, thus enhancing the value of products and food companies.

This study contributes to the food supply chain and the traceability systems literature by creating a holistic picture of where something has been and where it should go. It is a starting point for each food company to design and manage its traceability system more effectively.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.

This study aims to evaluate blockchain as an e-government governance model. It assesses its alignment with legal frameworks, emphasizing robustness against disruptions and adherence to existing laws.

The paper explores blockchain’s potential in e-government, focusing on legal, ethical and governance aspects. It conducts an in-depth analysis of blockchain’s integration into data governance, emphasizing legal compliance and resilient security protocols.

The study comprehensively evaluates blockchain’s implementation, covering privacy, interoperability, consensus mechanisms, scalability and regulatory alignment. It highlights governance’s critical role in ensuring legal compliance within blockchain paradigms.

Ethical and legal concerns arising from blockchain adoption remain unresolved. The study underscores how blockchain challenges its core principles of anonymity and decentralization in e-government settings.

The framework outlined offers potential for diverse technological environments, albeit raising ethical and legal queries. It emphasizes governance’s pivotal role in achieving legal compliance in blockchain adoption.

Blockchain’s impact on legal and ethical facets necessitates further exploration to align with its core principles while addressing governance in e-government settings.

This study presents a robust framework for assessing blockchain’s viability in e-government, emphasizing legal compliance, despite ethical and legal intricacies that challenge its fundamental principles.

This paper aims to examine the concept of standardization beyond its traditional use in generating and implementing standards and good practice guidelines (S&GPG) by looking at existing and emerging trends.

This paper utilizes two primary approaches to categorizing S&GPG for better comprehension: categorization based on provenance as well as based on subject matter.

A significant concern related to categorizing S&GPG based on provenance or subject is the constant proliferation of standards being developed and introduced every year. This rapid growth in standards requires frequent re-categorization to keep up with the dynamic nature of this field. To tackle this problem, this paper explores emerging concepts such as ontological representation and frameworks that offer archives and records management (ARM) professionals.

Standardization refers to establishing uniform rules through mutual agreement to ensure consistency. The study of standardization goes beyond the development of individual S&GPG, encompassing their practical application in work settings. Categorizing standards alone may not fully capture their actual use. However, abstraction mechanisms like ontological representations, models and frameworks can demonstrate how these standards have been leveraged. This paper provides illustrative examples rather than an exhaustive list to showcase how these mechanisms have been applied in research projects or as practical tools.

This paper explores the emerging topic of standardization from the perspective of ontological representations and models or frameworks. In addition, it also contributes to the discussion of the 2022 version of ARMA International’s Information Governance Implementation Model and the 2020 version of the World Bank Group's Records Management Roadmap, providing unique insights into these topics.

Robotics and automation are successful in construction, health and safety, but costs and expertise hinder their use in developing nations. This study examined mobile apps as a more accessible and affordable alternative.

This descriptive study explored the use of mobile apps in construction, health and safety management. It used a literature review to identify their availability, accessibility, and capabilities. The study consisted of four five stages: searching for relevant apps, selecting them based on versatility, examining their specific functions, removing untested apps and discussing their functions based on empirical studies.

A comprehensive literature review identified 35 mobile apps that are relevant to health and safety management during construction. After rigorous analysis, eight apps were selected for further study based on their relevance, user friendliness and compliance with safety standards. These apps collectively serve 28 distinct functions, including first-aid training and administration, safety compliance and danger awareness, safety education and training, hazard detection and warnings.

This study suggests that mobile apps can provide a cost-effective and readily accessible alternative to robotics and automation in health and safety management in construction. Further research is needed to accurately assess the efficacy of these apps in real-world conditions.

This study explored the use of apps in health and safety management, highlighting their diverse capabilities and providing a framework for project managers, contractors and safety officers to select suitable apps.