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The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective.

A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework.

This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected.

The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases.

This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

The data economy mainly relies on the surveillance capitalism business model, enabling companies to monetize their data. The surveillance allows for transforming private human experiences into behavioral data that can be harnessed in the marketing sphere. This study aims to focus on investigating the domain of data economy with the methodological lens of quantitative bibliometric analysis of published literature.

The bibliometric analysis seeks to unravel trends and timelines for the emergence of the data economy, its conceptualization, scientific progression and thematic synergy that could predict the future of the field. A total of 591 data between 2008 and June 2021 were used in the analysis with the Biblioshiny app on the web interfaced and VOSviewer version 1.6.16 to analyze data from Web of Science and Scopus.

This study combined findable, accessible, interoperable and reusable (FAIR) data and data economy and contributed to the literature on big data, information discovery and delivery by shedding light on the conceptual, intellectual and social structure of data economy and demonstrating data relevance as a key strategic asset for companies and academia now and in the future.

Findings from this study provide a steppingstone for researchers who may engage in further empirical and longitudinal studies by employing, for example, a quantitative and systematic review approach. In addition, future research could expand the scope of this study beyond FAIR data and data economy to examine aspects such as theories and show a plausible explanation of several phenomena in the emerging field.

The researchers can use the results of this study as a steppingstone for further empirical and longitudinal studies.

This study confirmed the relevance of data to society and revealed some gaps to be undertaken for the future.

This paper aims to investigate the relationship between green human resource management (GHRM) practices and employee innovative work behaviour in the hospital. Although previous studies have examined the association between GHRM and various organisational outcomes, its nexus with employee innovative work behaviour has been largely unexplored.

This study used a quantitative approach and tested hypotheses. The research design adopted both an explanatory and descriptive approach since there were limited past data or studies to reference. The study population was human resource and administrative managers at Korle Bu Teaching Hospital who have implemented GHRM practices. The sample size consisted of 264 respondents, selected using simple random sampling. Data were collected through structured questionnaires.

The collected data were analyzed using descriptive statistics, correlation and regression analysis. The results revealed that green training, green hiring and green compensation were significant predictors of innovative work behaviour among employees.

This study contributes to the understanding of the impact of GHRM practices on employee innovative work behaviour in the healthcare sector. The study recommends that organisations should view their training investments as financial investments and focus on hiring individuals with strong environmental sensibilities. Additionally, effective reward criteria should be developed to promote GHRM practices.

Pakistan, being a developing country, still has a long way to go to see progress in the field of research managers and administrators (RMAs). This chapter briefly explains the profession’s ecosystem in the country, its evolution, available data, and the future of the field. The type and quantum of extramural research happening in Pakistan are quite significant in terms of the number of grants as well as the total annual funding. Despite this progress, the growth of research management and administration as a profession is slow-paced because of the lack of recognition of RMAs as a profession, complemented by the dearth of schools that teach this formally in the country. The future, however, sounds promising as more and more people are gradually undertaking this dynamic field and working formally to acquire the knowledge and skills to become better research management and administration professionals.

The purpose of the article is to assess the effectiveness, compliance, adoption and lessons learnt from the pilot implementation of a data integration solution between an acute care hospital information system (HIS) and a long-term care (LTC) home electronic medical record through a case report.

Utilization statistics of the data integration solution were captured at one-month post implementation and again one year later for both the emergency department (ED) and LTC home. Clinician feedback from surveys and structured interviews was obtained from ED physicians and a multidisciplinary LTC group.

The authors successfully exchanged health information between a HIS and the electronic medical record (EMR) of an LTC facility in Canada. Perceived time savings were acknowledged by ED physicians, and actual time savings as high as 45 min were reported by LTC staff when completing medication reconciliation. Barriers to adoption included awareness, training efficacy and delivery models, workflow integration within existing practice and the limited number of facilities participating in the pilot. Future direction includes broader staff involvement, expanding the number of sites and re-evaluating impacts.

A data integration solution to exchange clinical information can make patient transfers more efficient, reduce data transcription errors, and improve the visibility of essential patient information across the continuum of care.

Although there has been a large effort to integrate health data across care levels in the United States and internationally, the groundwork for such integrations between interoperable systems has only just begun in Canada. The implementation of the integration between an enterprise LTC electronic medical record system and an HIS described herein is the first of its kind in Canada. Benefits and lessons learnt from this pilot will be useful for further hospital-to-LTC home interoperability work.

This study investigates perceptions of the use of online tracking, a passive data collection method relying on the automated recording of participant actions on desktop and mobile devices, for studying information behavior. It scrutinizes folk theories of tracking, the concerns tracking raises among the potential participants and design mechanisms that can be used to alleviate these concerns.

This study uses focus groups composed of university students (n = 13) to conduct an in-depth investigation of tracking perceptions in the context of information behavior research. Each focus group addresses three thematic blocks: (1) views on online tracking as a research technique, (2) concerns that influence participants' willingness to be tracked and (3) design mechanisms via which tracking-related concerns can be alleviated. To facilitate the discussion, each focus group combines open questions with card-sorting tasks. The results are analyzed using a combination of deductive content analysis and constant comparison analysis, with the main coding categories corresponding to the thematic blocks listed above.

The study finds that perceptions of tracking are influenced by recent data-related scandals (e.g. Cambridge Analytica), which have amplified negative attitudes toward tracking, which is viewed as a surveillance tool used by corporations and governments. This study also confirms the contextual nature of tracking-related concerns, which vary depending on the activities and content that are tracked. In terms of mechanisms used to address these concerns, this study highlights the importance of transparency-based mechanisms, particularly explanations dealing with the aims and methods of data collection, followed by privacy- and control-based mechanisms.

The study conducts a detailed examination of tracking perceptions and discusses how this research method can be used to increase engagement and empower participants involved in information behavior research.

This case study will illustrate how the Southern African Research and Innovation Management Association (SARIMA) set in motion a professionalisation journey through close collaboration with its members while leveraging strategic partnerships and funding opportunities. The case study will highlight the impetus that inspired the journey, and the outputs aimed at accelerating the professionalisation of research management and administration (RMA) beyond Southern Africa.

This chapter discusses the growing importance of research-related information in the face of increased complexities and competitiveness within higher education environments globally. It provides some reflections on the importance of institutional research cultures to effectively address these challenges, focussing on the African context, and the role of effective research support through institutional structures such as a dedicated research office. The increasingly strategic role of research management has led to the need for a more active and visionary role in the positioning of institutions by supporting decision-making and contributing to the development and visibility of institutional research portfolios. The authors provide their insights into the scope of research-related information, the need for research offices to perform this strategic function, how these information sets can be applied in reports, evidence-based decisions, institutional showcasing, and enhanced research support. The chapter includes aspects to consider when establishing a research-related information management function within institutions.

The purpose of this research is to develop a generic framework of a digital twin (DT)-based automated construction progress monitoring through reality capture to extended reality (RC-to-XR).

IDEF0 data modeling method has been designed to establish an integration of reality capturing technologies by using BIM, DTs and XR for automated construction progress monitoring. Structural equation modeling (SEM) method has been used to test the proposed hypotheses and develop the skill model to examine the reliability, validity and contribution of the framework to understand the DRX model's effectiveness if implemented in real practice.

The research findings validate the positive impact and importance of utilizing technology integration in a logical framework such as DRX, which provides trustable, real-time, transparent and digital construction progress monitoring.

DRX system captures accurate, real-time and comprehensive data at construction stage, analyses data and information precisely and quickly, visualizes information and reports in a real scale environment, facilitates information flows and communication, learns from itself, historical data and accessible online data to predict future actions, provides semantic and digitalize construction information with analytical capabilities and optimizes decision-making process.

The research presents a framework of an automated construction progress monitoring system that integrates BIM, various reality capturing technologies, DT and XR technologies (VR, AR and MR), arraying the steps on how these technologies work collaboratively to create, capture, generate, analyze, manage and visualize construction progress data, information and reports.