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Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.

Many master’s students enrol in coursework-based programmes to improve their professional knowledge and skills for the job market. Most studies of employability in higher education focus on undergraduates rather than master’s students, although the number of master’s students worldwide has increased significantly in recent years. This study explores the factors involved in the perceived employability (PE) of master’s students in Hong Kong.

The authors first proposed a conceptual model of PE based on the social cognitive career theory. Using survey data from 786 master’s students in Hong Kong, the authors applied descriptive statistics and an ordinary least squares (OLS) regression to address the following research questions: How do master’s students gauge their PE? How do person, learning and environment variables influence the PE of master’s students?

The authors found that PE is influenced by students' approaches to learning and their institutional career support.

Few studies examined whether students' learning experiences during the master’s programmes influence their employability. This study highlights the importance of learning experiences and career support in coursework-based master’s programmes for enhancing graduate employability.

This study aims to adjust Thesis-type properties on Schema.org using metadata models and standards (MS) (Bibframe, electronic thesis and dissertations [ETD]-MS, Common European Research Information Format [CERIF] and Dublin Core [DC]) to enrich the Thesis-type properties for better description and processing on the Web.

This study is applied, descriptive analysis in nature and is based on content analysis in terms of method. The research population consisted of elements and attributes of the metadata model and standards (Bibframe, ETD-MS, CERIF and DC) and Thesis-type properties in the Schema.org. The data collection tool was a researcher-made checklist, and the data collection method was structured observation.

The results show that the 65 Thesis-type properties and the two levels of Thing and CreativeWork as its parents on Schema.org that corresponds to the elements and attributes of related models and standards. In addition, 12 properties are special to the Thesis type for better comprehensive description and processing, and 27 properties are added to the CreativeWork type.

Enrichment and expansion of Thesis-type properties on Schema.org is one of the practical applications of the present study, which have enabled more comprehensive description and processing and increased access points and visibility for ETDs in the environment Web and digital libraries.

This study has offered some new Thesis type properties and CreativeWork levels on Schema.org. To the best of the authors’ knowledge, this is the first time this issue is investigated.

Do digital technologies of early 21st century capitalism promote or reduce consumer sovereignty? This chapter addresses this question by examining John Kenneth Galbraith’s critique of consumer sovereignty during the post-war period of industrial society and looks at the insights he provides to understand the impact of platform capitalism on consumer sovereignty today. This chapter has the following sections: (1) I review the main postulates of Galbraith’s theory; (2) I highlight the main differences between traditional advertising and online behavioral advertising; (3) I explain how online behavioral advertisement strengthens Galbraith’s dependence effect and revised sequence theories; (4) I then discuss normative challenges raised by digital platform corporations to individual sovereignty; and (5) finally, I argue that platform capitalism is a mature form of Galbraith’s “new industrial state.”

As the current Coronavirus 2019 pandemic eases, international tourism, which was greatly affected by the outbreak, is gradually recovering. The attraction of countries to overseas tourists is related to their overall performance in the pandemic. This research integrates the data of vaccination of different countries, border control policy and holidays to explore their differential impacts on the overseas tourists’ intention during the pandemic. This is crucial for destinations to built their tourism resilience. It will also help countries and industry organizations to promote their own destinations to foreign tourism enterprises.

This study proposes an analysis based on panel data for ten countries over 1,388 days. The coefficient of variation is used to measure monthly differences of Chinese tourists’ intention to visit overseas country destinations.

Results show that, for tourist intention of going abroad: border control of the destination country has a significant negative impact; daily new cases in the destination country have a significant negative impact; domestic daily new cases have a significant positive impact; holidays have significant negative impact; daily vaccination of the destination countries has significant positive impact; and domestic daily vaccination have negative significant impact.

First, there is a large uncertainty in studying consumers’ willingness to travel abroad in this particular period because of unnecessary travel abroad caused by the control of the epidemic. Second, there are limitations in studying only Chinese tourists, and future research should be geared toward a broader range of research pairs.

First, from the government perspective, a humane response can earn the respect and trust of tourists. Second, for tourism industry, to encourage the public take vaccine would be beneficial for both the tourism destination and foreign tourism companies. The same effect can be achieved by helping tourists who are troubled by border control.

First, this research provides suggestions for the government and the tourism industry to deal with such a crisis in the future. Second, this study found that vaccination has a direct impact on tourism. This provides a basis for improving people’s willingness to vaccinate. Thirdly, this study proves suggestion for the destinations to build tourism resilience.

This study analyzes the unique control measures and vaccination in different countries during the pandemic, then provides suggestions for the tourism industry to prepare for the upcoming postpandemic tourism recovery. This study is valuable for improving the economic resilience of tourism destinations. Additionally, it helps to analyze the advantages and disadvantages of different restrain policies around the world.

In this chapter, the authors define the new business term, future-proofing, and apply it to knowledge preservation and curation. The fundamental principles of future-proofing and the challenges and mechanics are discussed. These challenges are discussed in developing future-proofed knowledge preservation, and a curation strategy is identified. The authors identify four challenges to future-proofing a knowledge preservation and curation strategy – availability, visibility, accessibility, and consumability of knowledge assets. Ultimately, the greatest challenge to future-proofing these strategies lies in the channels we use to create, transmit, share, and store knowledge assets. At a minimum, the chapter speaks to the critical importance of future-proofing the preservation of knowledge assets, so there is a possibility of curation at some point in a known or unknown future.

Reducing fatalities and increasing the number of students able to remain safe during an active shooter event is paramount to the health and well-being of schools and communities. Yet, methodological limitations and ethical concerns have restricted prior research on security measures during school shooter lockdown drills. This study aims to fill that gap by using virtual reality (VR) to statistically examine the effectiveness of active shooter response protocols in a simulated high school.

Using a full factorial, within-subjects experimental design, this exploratory investigation used VR technology to investigate whether automatic classroom door locks, centralized lockdown notifications and the presence of a school resource officer (SRO) significantly impacted student safety and casualty mitigation. Data were collected from a convenience sample of 37 individuals who volunteered to participate in 24 school shooter scenarios within a simulated virtual environment.

Multiple one-way analysis of variances indicated significant main effects for automatic classroom door locks and SRO presence. Automatic locks yielded faster lockdown response times, and both factors were significantly associated with higher numbers of secured classrooms.

Findings from the current study address the gap in existing literature regarding evidence-based school safety protocols and provide recommendations for using VR simulations to increase preparedness and reduce fatalities during an active school shooter event.

This study aims to reveal the factors that drive researchers to share data and to provide reference for promoting open scientific data.

Based on the theory of social capital and the theory of planned behaviour, hypotheses were proposed and the model was developed. The authors acquired 479 valid samples of Chinese researchers through questionnaires and conducted an empirical analysis via AMOS 23.0.

Attitudes towards data sharing are significantly and positively correlated with trust, reciprocity and social interaction, but not with a shared vision; willingness to share data is significantly and positively correlated with attitudes and perceived behavioural control, but not with subjective norms; furthermore, data quality, which performed the function of a moderating variable, was found to play a facilitating role in the above correlations. Based on the findings, suggestions for relevant entities were specified.

The study developed and validated an integrated theoretical framework, clarified the mechanism by which social capital and planned behaviour affect willingness to share data, hoping to provide reference and empirical support for subsequent studies as well as new ideas for data management and sharing.

For over a decade now, various stakeholders in accounting education have called for the integration of technology competencies in the accounting curriculum (Association to Advance Collegiate Schools of Business (AACSB), 2013, 2018; Accounting Education Change Commission (AECC), 1990; American Institute of Certified Public Accountant (AICPA), 1996; Behn et al., 2012; Lawson et al., 2014; PricewaterhouseCoopers (PWC), 2013). In addition to stakeholder expectations, the inclusion of data analytics as a key area in both the business and accounting accreditation standards of the AACSB signals the urgent need for accounting programs to incorporate data analytics into their accounting curricula. This paper examines the extent of the integration of data analytics in the curricula of accounting programs with separate accounting AACSB accreditation. The paper also identifies possible barriers to integrating data analytics into the accounting curriculum. The results of this study indicate that of the 177 AACSB-accredited accounting programs, 79 (44.6%) offer data analytics courses at either the undergraduate or graduate level or as a special track. The results also indicate that 41 (23.16%) offer data analytics courses in their undergraduate curriculum, 61 (35.88%) at the graduate level, and 12 (6.80%) offer specialized tracks for accounting data analytics. Taken together, the findings indicate an encouraging trend, albeit slow, toward the integration of data analytics into the accounting curriculum.

The research study intends to gain a better understanding of members' behaviors in the context of crowdsourcing contests. The authors examined the key factors that can motivate or discourage contributing to a team and within the community.

The authors conducted 21 semi-structured interviews with Kaggle.com members and analyzed the data to capture individual members' contributions and emerging determinants that play a role during this process. The authors adopted a qualitative approach and used standard thematic coding techniques to analyze the data.

The analysis revealed two processes underlying contribution to the team and community and the decision-making involved in each. Accordingly, a set of key factors affecting each process were identified. Using Holbrook's (2006) typology of value creation, these factors were classified into four types, namely extrinsic and self-oriented (economic value), extrinsic and other-oriented (social value), intrinsic and self-oriented (hedonic value), and intrinsic and other-oriented (altruistic value). Three propositions were developed, which can be tested in future research.

The study has a few limitations, which point to areas for future research on this topic. First, the authors only assessed the behaviors of individuals who use the Kaggle platform. Second, the findings of this study may not be generalizable to other crowdsourcing platforms such as Amazon Mechanical Turk, where there is no competition, and participants cannot meaningfully contribute to the community. Third, the authors collected data from a limited (yet knowledgeable) number of interviewees. It would be useful to use bigger sample sizes to assess other possible factors that did not emerge from our analysis. Finally, the authors presented a set of propositions for individuals' contributory behavior in crowdsourcing contest platforms but did not empirically test them. Future research is necessary to validate these hypotheses, for instance, by using quantitative methods (e.g. surveys or experiments).

The authors offer recommendations for implementing appropriate mechanisms for contribution to crowdsourcing contests and platforms. Practitioners should design architectures to minimize the effect of factors that reduce the likelihood of contributions and maximize the factors that increase contribution in order to manage the tension of simultaneously encouraging contribution and competition.

The research study makes key theoretical contributions to research. First, the results of this study help explain the individuals' contributory behavior in crowdsourcing contests from two aspects: joining and selecting a team and content contribution to the community. Second, the findings of this study suggest a revised and extended model of value co-creation, one that integrates this study’s findings with those of Nov et al. (2009), Lakhani and Wolf (2005), Wasko and Faraj (2000), Chen et al. (2018), Hahn et al. (2008), Dholakia et al. (2004) and Teichmann et al. (2015). Third, using direct accounts collected through first-hand interviews with crowdsourcing contest members, this study provides an in-depth understanding of individuals' contributory behavior. Methodologically, this authors’ approach was distinct from common approaches used in this research domain that used secondary datasets (e.g. the content of forum discussions, survey data) (e.g. see Lakhani and Wolf, 2005; Nov et al., 2009) and quantitative techniques for analyzing collaboration and contribution behavior.

The authors advance the broad field of crowdsourcing by extending the literature on value creation in the online community, particularly as it relates to the individual participants. The study advances the theoretical understanding of contribution in crowdsourcing contests by focusing on the members' point of view, which reveals both the determinants and the process for joining teams during crowdsourcing contests as well as the determinants of contribution to the content distributed in the community.