Search results

One of the most critical changes to academic library services in the last decade has been the development and implementation of research data services (RDS). This paper seeks to provide a comprehensive understanding of conceptual models for the RDS space.

An extensive and comprehensive review of the literature on conceptual models for RDS is performed.

Various conceptual models for RDS provide a compelling tool for guiding and evaluating RDS development and implementation within academic libraries.

An insightful review and synthesis of context and issues in RDS models will help academic libraries to plan, develop and advance their RDS.

In today's global and competitive corporate environment characterised by rapidly changing information, knowledge and technology (IKT), researchers must be upskilled in all aspects of research data management (RDM). This study investigates a set of capabilities and competencies required by researchers at selected South African public universities, using the community capability model framework (CCMF) in conjunction with the digital curation centre (DCC) lifecycle model.

The post-positivist paradigm was used in the study, which used both qualitative and quantitative methodologies. Case studies, both qualitative and quantitative, were used as research methods. Because of the COVID-19 pandemic rules and regulations, semi-structured interviews with 23 study participants were conducted online via Microsoft Teams to collect qualitative data, and questionnaires were converted into Google Forms and emailed to 30 National Research Foundation (NRF)-rated researchers to collect quantitative data.

Participating institutions are still in the initial stages of providing RDM services. Most researchers are unaware of how long their institutions retain research data, and they store and backup their research data on personal computers, emails and external storage devices. Data management, research methodology, data curation, metadata skills and technical skills are critically important RDM competency requirements for both staff and researchers. Adequate infrastructure, as well as human resources and capital, are in short supply. There are no specific capacity-building programmes or strategies for developing RDM skills at the moment, and a lack of data curation skills is a major challenge in providing RDM.

The findings of the study can be applied widely in research, teaching and learning. Furthermore, the research could help shape RDM strategy and policy in South Africa and elsewhere.

The scope, subject matter and application of this study contribute to its originality and novelty.

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.

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

This study aims to examine the state of embedded librarianship in African academic libraries by exploring the extent of librarian embedment in research processes in selected academic libraries in Africa.

A survey was conducted to collect data using an online questionnaire. The study population was comprised of librarians who directly support researchers throughout the research process in the scholarly communication and information services sections. Purposive sampling was used to select librarians, and 63 responses were received from the target of 100. The collected data were analysed using the statistical package for the social sciences (SPSS) software, and content analysis was used to analyse open-ended questions.

The study results showed that the extent and nature of librarians' embeddedness in the research process vary across different university contexts in Africa. Challenges and areas of research skill gaps among librarians were identified, and propositions to address the research skill gaps were provided.

The study findings can be used as a framework for libraries to embed librarians in the research process. The study made recommendations with practical implications for library practitioners in academia, and institutions offering library and information science education, and the library management responsible for the research process.

A study brings a novel perspective by examining the state of embedded librarianship in the African context. Its contribution generates knowledge and insights that inform the development of effective embedded librarianship practices in African academic libraries to enhance research support services and advancement of scholarly research in the region.

This paper explores the different open science policy effects on the knowledge generation process of researchers in basic sciences: biology, chemistry and physics.

This paper uses a qualitative methodology with a content analysis approach. It uses seventeen semi-directed interviews.

The main perceived effect of open science is access to research inputs, with open access, open research data and code reuse as primary sources. Another issue is the increase of collaboration with other colleagues in terms of the ability to collaborate faster and encouraging the exchange of ideas. However, this benefit does not translate to the division of labor in large transnational teams. Time spent on tasks like cleaning up data and code, scooping and other ethical issues are unfavorable aspects noted.

Policymakers could use this study to enhance current open science policies in the countries.

This study analyzes the perspectives of basic sciences researchers from two countries about open science policies. The main conclusion is the fact that open science policies should focus on the research process itself – rather than research outputs – in order to effectively tackle inequalities in science.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-03-2023-0135

It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.

The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).

The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.

Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.

This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.

Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.

The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

This paper outlines how Design for Lean Six Sigma methods aided a medical device manufacturing company in developing a new strategic space management and approval process for its manufacturing site.

The project demonstrates the application of the Design for Lean Six Sigma and structured Define, Measure, Analyse, Design, and Verify methodology in designing and implementing a process that enables the case study manufacturing site to improve its space utilisation and free up space.

The project was validated in one manufacturing department, and the Design for Lean Six Sigma methodology resulted in creating 15% new space for that area, with opportunities identified to free up 44.7% of the total manufacturing floor space and realise over €2.2 million cost savings as well as start to manufacture new products launched.

The manuscript highlights for the first time how the Design for Lean Six Sigma methodology can be utilised for space utilisation and can be leveraged by other manufacturers. The current study's limitations are that it is a single-site case study application. Future longitudinal case studies on Design for Lean Six Sigma application in more manufacturing space utilisation projects would be useful. This study has implications for identifying best practices for Design for Lean Six Sigma methodology application in the device industry, thus improving the state of the art for introducing new manufacturing lines.

This is the first published work to utilise Design for Lean Six Sigma methodology for space utilisation in a medical device company. This review will provide medical devices and other manufacturing organisations with recommendations on utilising Design for Lean Six Sigma and design for improved space utilisation to reduce costs.