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This study aims to evaluates a public policy program that finances projects for the development of innovative technological solutions. This paper analyzed the influence of human and social capital on the development of the projects, under the perspective of the policy’s effectiveness and efficiency. This specific policy adopted the funding model of economic subsidy by means of grants, which shows the significant engagement of the public sector in applying nonrefundable resources more directly through loans, assuming the role of an entrepreneurial state, according to Mazzucato (2011, 2018) and Tavani and Zamparelli (2020).

This is a quantitative-descriptive study, according to Marconi and Lakatos (2017). This study is descriptive, for presenting information on innovation projects funded by FUNCAP (Ceará Foundation for Support to Scientific and Technological Development). In addition, this study is quantitative, by establishing multivariate relationships among the variables that relate to human capital and social capital, which are relevant to technological and innovative development, and by introducing variables on technological evolution, proposed as measures of the program’s effectiveness (DTRL, MkTRL) and efficiency (ETRL).

This paper sought to contribute on public policies for innovation, more specifically on analyzing variables that may affect the development of technological and innovative projects in knowledge-intensive companies. The authors studied capitals potentially important for these companies in the development of innovative projects. Specifically, the authors sought to understand the importance of human capital and how it reflects in technical and scientific knowledge of the project team and of social capital and how it reflects the connection and social relationship among different team members. The results presented that the degree of efficiency of the public funding program depends on how much the teams of the benefited projects have accumulated knowledge, skills and technical capacities – the so-called teams’ human capital.

It is important to address the research sample as a research limitation, which had 72 responses obtained, from a submission rate of 284. Another study limitation is on the qualitative analysis of the topics addressed from the companies and policymakers perspectives, considering that the quantitative nature of the study does not allow for a deeper understanding of the qualitative perspective of the actors involved in the phenomenon studied. As recommendations for future studies, it is suggested to conduct qualitative studies on the aspects studied here. In this sense, it is possible to conduct case studies for specific companies, or policymakers, to clarify and deepen the relationships between the themes addressed here.

As for the practical implications of the research, both for managers of public funding programs and for company managers, the benefits of human capital, related to innovative project development teams, are important in programs that deal with technological development projects. In practice, this means that the greater the human capital of academic background of the members of the supported project teams, the more efficient the projects are in the process of developing their technologies by using the resources provided (Ashford, 2000; Chen et al., 2008; Lerro et al., 2014).

Hence, the authors conclude that the evaluated innovation-funding program through grants achieved acceptable results in terms of promoting the technological evolution of the benefited projects and bringing the technologies closer to the market. Its efficiency was the least favorable result, showing that the program needs to focus on improving this specific aspect. Within the investigated program, the issue that needs enhancement (efficiency – ETRL) was the one that presented significant relationships with the human and social capital of the benefited projects’ teams. Thus, it is possible that, by selecting more projects that have teams with high capital, the efficiency of the public policy, in this case the development of projects with high technological and innovative potential, will be possibly reached.

The findings strengthen the need for innovation public policies designed and implemented in a systemic way in the science, technology and innovation ecosystem, to provide a technological infrastructure and human capital necessary for developing projects with high technological and innovative potential (Ergas, 1987; Audretsch and Link, 2012; Caloghirou et al., 2015; Edler and Fagerberg, 2017; Silvio et al., 2019).

This systematic review, following preferred reporting items for systematic reviews and meta-analysis guidelines, rigorously investigates the emergent role of virtual reality (VR) technology in human movement training. The purpose of this study is to explore the effectiveness and evolution of VR in enhancing movement training experiences.

Acknowledging its pivotal role in diverse applications, such as sports and rehabilitation, human movement training is currently experiencing accelerated evolution, facilitated by the proliferation of wearable devices and mobile applications. This review conducted an exhaustive search across five different electronic databases, such as Web of Science, PubMed and ProQuest, resulting in the selection of 69 eligible articles published within the past five years. It also integrates 40 studies into a narrative summary, categorized based on the level of immersion offered by respective VR systems.

Enhanced immersion in VR potentially augments the effectiveness of movement training by engendering more realistic and captivating experiences for users. The immersive and interactive environments provided by VR technology enable tailored training experiences accompanied by precise, objective feedback. This review highlights the benefits of VR in human movement training and its potential to revolutionize the way training is conducted.

This systematic review contributes significantly to the existing literature by providing a comprehensive examination of the efficacy and evolution of VR in human movement training. By organizing the findings based on the level of immersion offered by VR systems, it provides valuable insights into the importance of immersion in enhancing training outcomes. In addition, this study identifies the need for future research focusing on the impacts of VR on learning and performance, as well as strategies to optimize its effectiveness and improve accessibility.

The purpose of this article is to examine all the studies carried out within the scope of e-HRM and smart HRM, grouped according to the sub-functions of technical and HRM. The use of technology in HRM has started since the mid-1990s. However, this study focused on the articles published after 2014 in order to keep up to date. Any search strategy should allow for the completeness of the search to be evaluated. The terms “electronic-HRM”, “AI and HRM”, “Industry 4.0 and HRM”, “Society 5.0 and HRM”, “Human Resource Information Systems” and “Digital Technologies and HRM” “Human-robot interaction” has been questioned in IEEE Xplore, ALM digital library, Emerald Insight, SpringerLink, and Science Direct. The Web of Science and Scopus were also queried to double-check the findings and find other relevant articles in lesser-known libraries. Google Scholar was also used for forward and backward searches. These online databases have been chosen because they present the most important peer-reviewed full-text journals, conference proceedings, book chapters. Then, the references of each article were reviewed for additional articles on digital technologies and HRM. Each subsequent article is then reviewed for additional reference.

A total of 5,580 articles have been reviewed. Duplicate items have been removed. The titles and abstracts of 3,500 articles have been scanned to identify potential articles. The full-text evaluation of 2,554 was based on compliance with the inclusion criteria. In addition, 2,458 studies have been excluded. In total, 96 studies have been selected for data extraction. Additionally, questionnaires and reviews have been used to provide comprehensive research on e-HRM and smart HRM. The search terms used are expected to cover most, if not all, of the studies involving e-HRM and smart HRM.

The study carried out in this article is qualitative research. In the article, which methods are used and what has changed in e-HRM and smart HRM are examined. In particular, it has been thought about what can happen with the inclusion of human-machine interaction, AI, chatbots, industry 4.0 and information systems in HRM. Unlike previous studies, this review takes HRM from a broader perspective and groups it by topic, both by technical and HR functions. In addition, the reviewed articles provide brief information about the AI technologies used. In particular, criteria were taken into account according to the field, type and subject of the articles.

This study has the distinction of being the first in the literature in terms of examining all the studies carried out within the scope of e-HRM and smart HRM and grouped according to the sub-functions of technical and HRM in line with its purpose. The article focuses specifically on research published after 2014. It is expected to contribute to the literature in terms of collecting all studies in a single article. Other contributions of this article can be summarized in four main articles: 1) it presents a summary of previous research by grouping the studies on e-HRM and smart HRM according to the interests of researchers. 2) It saves time for the reader as it provides a brief explanation of the studies on the subject. 3) Instead of explaining in detail the general details analyzed in other articles, it offers a practical perspective by focusing on the type, subject and field of the article. 4) With the digitalization of HRM, new, up-to-date research and techniques are introduced.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

The purpose of this paper is to provide an extensive examination and analysis of the current literature on the use of blockchain technology in courts. The paper aims to explore the potential benefits of implementing blockchain technology in courts, such as increasing transparency and accountability, improving the efficiency of court procedures and enhancing the security of court records. Additionally, the paper intends to identify the challenges and limitations of using blockchain technology in courts and propose potential solutions to overcome these obstacles. The ultimate goal is to provide a comprehensive understanding of the potential applications and implications of blockchain technology in the context of the court system.

The research design of this study is qualitative, involving a thorough examination and analysis of existing literature on the use of blockchain technology in courts. The data collection procedure involves gathering information from various sources, such as academic publications, official reports and other relevant records. Data analysis is conducted using a thematic analysis approach, which identifies and categorizes recurring themes that emerge from the data. This approach ensures that the results are credible, dependable and accurate representations of the experiences of the participants. By using these methodologies, the study is able to draw meaningful conclusions and insights into the use of blockchain technology in courts.

The major findings of this paper suggest that the implementation of blockchain technology in courts has the potential to bring significant benefits such as increased transparency, efficiency and security. The use of blockchain technology in courts can enable the creation of tamper-proof records that are immutable, secure and transparent, which can help prevent fraud, reduce costs and enhance trust in the judicial system. However, adopting this technology also poses challenges and limitations, such as interoperability, governance and scalability. Overall, the paper concludes that while there are challenges to be addressed, the benefits of blockchain technology in courts are significant and should be explored further.

The study has several limitations that need to be taken into account. Firstly, the availability of data on blockchain implementation in the court system is limited, making it challenging to provide a comprehensive analysis of the topic. Thus, the study’s findings may not be generalizable to other contexts. Secondly, the study takes a technology-centric approach and does not consider blockchain technology’s social and legal implications in court operations. Thirdly, the case studies presented in this paper are limited to a few countries. Moreover, the implementation of blockchain technology in the court system is still in its early stages and lacks standardization, technical expertise and regulatory frameworks. Lastly, uncertainty around the legal framework may hinder its widespread adoption and use.

The practical implications of this study suggest that the use of blockchain technology in courts has the potential to improve efficiency, security, transparency and accountability in the court system. It can reduce the risk of data tampering, expedite case resolution and lower the cost of legal proceedings. Therefore, this study provides a framework for courts to consider blockchain technology’s potential benefits and explore its future adoption.

The social implications of this study are significant, as the adoption of blockchain technology in the court system can have a profound impact on society. Firstly, by increasing transparency and accountability, blockchain technology can promote public trust in the court system and improve access to justice, particularly for disadvantaged communities (Liu et al., 2020). Secondly, blockchain technology can reduce the reliance on intermediaries, such as lawyers, and streamline the case management process, making legal services more accessible and affordable for the general public (Khurana, 2020). Finally, the use of blockchain technology can create a more secure and efficient court system, enhancing the overall effectiveness of the judicial system and promoting public confidence.

This study provides an original contribution to the literature by exploring the use of blockchain technology in courts from a qualitative research design perspective. While there are a growing number of studies on the potential applications of blockchain technology in various fields, this study provides a comprehensive examination of the current literature on the use of blockchain in courts, identifying the benefits and limitations of its implementation. The study’s focus on the strengths and limitations of blockchain technology and its implications in court adds to the originality of this research.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in organizations. There was a knowledge hiatus regarding the contribution of the deployment of ML and AI technologies and their effects on organizations and society.

This study was grounded on the dynamic capabilities (DC) and ML and AI automation-augmentation paradox literature. This research study examined these theoretical perspectives using the response of 239 Indian organizational chief technology officers (CTOs). Partial least square-structural equation modeling (PLS-SEM) path modeling was applied for data analysis.

The results indicated that ML and AI technologies organizational usage positively influenced DC initiatives. The findings depicted that DC fully mediated ML and AI-based technologies' effects on firm performance and social performance.

This study contributed to theoretical discourse regarding the tension between organizational and social outcomes of ML and AI technologies. The study extended the role of DC as a vital strategy in achieving social benefits from ML and AI use. Furthermore, the theoretical tension of the automation-augmentation paradox was explored.

Organizations deploying ML and AI technologies could apply this study's insights to comprehend the organizational routines to pursue simultaneous competitive benefits and social gains. Furthermore, chief technology executives of organizations could devise how ML and AI technologies usage from a DC perspective could help settle the tension of the automation-augmentation paradox.

Increased ML and AI technologies usage in organizations enhanced DC. They could lead to positive social benefits such as new job creation, increased compensation to skilled employees and greater gender participation in employment. These insights could be derived based on this research study.

This study was among the first few empirical investigations to provide theoretical and practical insights regarding the organizational and societal benefits of ML and AI usage in organizations because of their DC. This study was also one of the first empirical investigations that addressed the automation-augmentation paradox at the enterprise level.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

This study aims to critically review the emerging technological developments and digitalization efforts in the hospitality and tourism (HT) industry and discuss the implications of digitalization on various stakeholders (e.g. consumers, employees, companies and operators) with reference to value creation.

This paper is a conceptual, critical reflection paper. Thus, the study reflects the authors’ assessment and reflection of the current digitalization efforts in the HT industry with a particular interest in value creation.

The study suggests that digitalization is still in its infancy state in terms of adoption and value creation in the HT industry. Yet, there are various opportunities for all stakeholders to benefit from existing and emerging digitalization applications.

This study can be used by industry professionals and scholarly researchers as a reflection of past and current digitalization efforts in the HT industry. Moreover, the study offers directions regarding the future digitalization movement in the HT industry and how such a movement might create important value propositions for various stakeholders.

The study is uniquely positioned as a critical reflection paper on the digitalization effort of the HT industry and offers new practical insights regarding how digitalization could create value for industry stakeholders as it finds more application areas. In this regard, it differs from prior review studies that focused solely on the use of new and emerging technologies in HT operations.

By extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.

By using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.

Findings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.

The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.

This is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.