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This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

With the increasing importance of technology in hospitality and tourism, technology-driven service innovation has been a salient topic discussed from both customers’ and suppliers’ perspectives. However, there has been a lack of research that provides an overview of research on technology-driven service innovation. The purpose of this study is to review current discussions on technology-driven service innovation and provide directions for future studies in the hospitality and tourism literature.

A total of 82 articles on technology-driven service innovation were collected from top-tier hospitality and tourism journals. The papers were analyzed using content analysis to derive key topics discussed in the literature. Such discussions were made by different service innovation categories, antecedents, outcomes and theories. Future research agendas were suggested based on the research gap found in the literature.

The results indicate that prior discussions on technology-driven service innovation viewed technology as a service or service delivery method, with limited focus on management, marketing and institutional service innovation. In addition, the study reveals five key topics that need further discussion, such as cocreative technology, human resources management, strategy management, emerging technology and digital transformation.

While there have been increasing studies that reveal determining roles of technology in service innovation, scarce research introduced the new concept of technology-driven service innovation, suggesting a comprehensive approach. By adopting the unique approach of technology-driven service innovation, the research reveals the multifaceted roles of technology in service innovation and areas that need further discussion to implement highly sustainable strategies.

The research adds to the knowledge of technology-driven service innovation by providing a holistic view of current discussions, finding research gaps and proposing future research agendas for extended discussion.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.