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This study aims to apply the theory of consumption value to analyze the utilization of Metaverse technologies within hospitality and tourism while examining the factors that impact consumer intentions to use the Metaverse.

This paper aims to consider an extensive study spanning the period October 2021 to March 2023 was conducted to understand the shifts in an individual's intention to use Metaverse technologies in hospitality.

The findings of this study confirm that individual attitudes to the Metaverse and trust in Metaverse technologies significantly impact their intention to use the Metaverse.

The study aims to provide fresh insights into how individuals perceive Metaverse technologies in the context of choosing hotels and resorts, which enriches the understanding of consumer behaviors around Metaverse technology in hospitality.

This study aims to consider not only tourist intentions to use the Metaverse but also how diverse consumption values impact user attitudes, an area currently underresearched.

This study investigates the application of collaborative inquiry within innovation management, employing platform thinking to address challenges of generalizability and relevance. The aim is to integrate Collaborative Inquiry methods, characterized by participatory, diffuse, and reflective practices, to transform research into a tool for impactful change in organizations in the field of innovation management.

A longitudinal participatory case study approach focuses on the IDeaLs case—a research platform that collaborated with multiple companies over several years. The data gathered and analyzed comes from the research project within the research platforms over the first two editions and from the research platform management and coordination activities.

The study introduces the Collaborative Research Platform Approach (CRPA), demonstrating its effectiveness in addressing typical constraints of traditional research methodologies through a real-world application within the IDeaLs case. The findings highlight the CRPA's potential in fostering a dynamic, co-creative research environment that bridges theoretical knowledge with practical applications, thus enhancing both scholarly and organizational outcomes while pursuing a future change within the organizations.

There are two main research implications. First, it proposes platform thinking as a theoretical lens to read a multi-stakeholder phenomenon in the research domain, confirming its nature of value-creation mechanisms, using it outside the business model and strategic space. Second, it offers a methodological contribution by presenting the CRPA framework.

The CRPA framework offers organizations a structured approach to managing collaborative research projects that align with both academic rigor and practical relevance. Companies engaged in the study reported enhanced ability to implement actionable insights from research, influencing real-time decision-making processes.

By fostering collaborative engagements across multiple stakeholders, the CRPA promotes a research culture that values inclusivity and practical impact, potentially leading to broader societal benefits through improved innovation management practices.

This paper contributes to the innovation management field by proposing the CRPA, which integrates principles of Platform Thinking with Collaborative Inquiry. This novel approach is designed to improve the applicability and scope of innovation research, offering a robust framework that enhances engagement and utility across academic and business domains. It uses platforms as a theoretical lens to read a multi-stakeholder environment in the research domain.

In the context of the journey toward digital transformation and the realization of a fully connected factory, concepts such as data science, artificial intelligence (AI), machine learning (ML) and even predictive models emerge as indispensable pillars. Given the relevance of these topics, the present study focused on the analysis of customer complaint data, employing ML techniques to anticipate complaint accountability. The primary objective was to enhance data accessibility, harnessing the potential of ML models to optimize the complaint handling process and thereby positively contribute to data-driven decision-making. This approach aimed not only to reduce the number of units to be analyzed and customer response time but also to underscore the pressing need for a paradigm shift in quality management. The application of AI techniques sought to enhance not only the efficiency of the complaint handling process and data accessibility but also to demonstrate how the integration of these innovative approaches could profoundly transform the way quality is conceived and managed within organizations.

To conduct this study, real customer complaint data from an automotive company was utilized. Our main objective was to highlight the importance of artificial intelligence (AI) techniques in the context of quality. To achieve this, we adopted a methodology consisting of 10 distinct phases: business analysis and understanding; project plan definition; sample definition; data exploration; data processing and pre-processing; feature selection; acquisition of predictive models; evaluation of the models; presentation of the results; and implementation. This methodology was adapted from data mining methodologies referenced in the literature, taking into account the specific reality of the company under study. This ensured that the obtained results were applicable and replicable across different fields, thereby strengthening the relevance and generalizability of our research findings.

The achieved results not only demonstrated the ability of ML models to predict complaint accountability with an accuracy of 64%, but also underscored the significance of the adopted approach within the context of Quality 4.0 (Q4.0). This study served as a proof of concept in complaint analysis, enabling process automation and the development of a guide applicable across various areas of the company. The successful integration of AI techniques and Q4.0 principles highlighted the pressing need to apply concepts of digitization and artificial intelligence in quality management. Furthermore, it emphasized the critical importance of data, its organization, analysis and availability in driving digital transformation and enhancing operational efficiency across all company domains. In summary, this work not only showcased the advancements achieved through ML application but also emphasized the pivotal role of data and digitization in the ongoing evolution of Quality 4.0.

This study presents a significant contribution by exploring complaint data within the organization, an area lacking investigation in real-world contexts, particularly focusing on practical applications. The development of standardized processes for data handling and the application of predictions for classification models not only demonstrated the viability of this approach but also provided a valuable proof of concept for the company. Most importantly, this work was designed to be replicable in other areas of the factory, serving as a fundamental basis for the company’s data scientists. Until then, limited data access and lack of automation in its treatment and analysis represented significant challenges. In the context of Quality 4.0, this study highlights not only the immediate advantages for decision-making and predicting complaint outcomes but also the long-term benefits, including clearer and standardized processes, data-driven decision-making and improved analysis time. Thus, this study not only underscores the importance of data and the application of AI techniques in the era of quality but also fills a knowledge gap by providing an innovative and replicable approach to complaint analysis within the organization. In terms of originality, this article stands out for addressing an underexplored area and providing a tangible and applicable solution for the company, highlighting the intrinsic value of aligning quality with AI and digitization.

In this study, students’ perceptions of the effective practices of their research mentors were examined. The research mentors implemented the practices informed by the Center for the Improvement of Mentored Experiences in Research (CIMER) mentorship competencies to mentor underrepresented students in engineering education research in a virtual environment.

This research experience for undergraduates (REU) program, situated in the United States of America, consisted of undergraduate students (i.e. mentees), graduate students and faculty mentors who all had at least one underrepresented identity in engineering (i.e. Black, Latiné/x, and/or women). Using qualitative methods, we used data from reflection surveys and follow-up interviews with REU mentees to understand the outcomes of the mentorship strategies employed by the mentors in the program. The data were analyzed thematically using CIMER model constructs and social capital theory as guiding frameworks.

The results indicated the identified strategies students perceived as the most impactful for mentorship throughout the program. Students in the REU gained knowledge on how to activate social capital in mentorship relationships and how to better mentor others.

The findings provide insight on how to operationalize the CIMER mentorship competencies to skillfully mentor underrepresented students in engineering. Given the size of the REU and the nature of qualitative research, the sample size was limited.

The results help inform mentorship practices for underrepresented individuals in engineering education and the workforce. Further, they add to the practical knowledge of implementing CIMER best practices virtually, at a time when the world has transitioned to more hybrid and virtual working and learning environments.

This study identifies impactful strategies for operationalizing mentorship strategies informed by theory- and evidence-based CIMER mentorship competencies. In addition, this study extends knowledge about how to implement mentoring best practices and engage mentorship in a virtual environment.

The purpose of this study is to determine the perception of graduates from teaching degree programs in Early Childhood and Primary Education carried out in Spain in accordance with the European Higher Education Area, who are currently working in classrooms, on their initial training in the educational treatment of diversity (ETD). In addition, potential differences were examined based on the teaching degree that was studied (Early Childhood or Primary).

This study used a mixed methodology including an ad hoc questionnaire and a semi-structured interview. Participants were 140 working teachers who had previously earned their degree in Early Childhood or Primary Education programs. Data analysis was carried out from an integrative perspective, using a basic descriptive focus and content analysis.

The results reveal that the new teachers considered that their initial training in the area of ETD was not as extensive as it should have been and as required by their daily teaching needs. They felt that they had acquired better education in the theoretical content as compared to the practical component. They mentioned a lack of training to attend to students entering the system at a later stage as well as for those with high intellectual abilities, noting that the initial training in ETD focused excessively on deficits and not enough on potentialities and other student diversities.

This study may be useful as it offers an improved adaptation to the reality of early education in ETD classrooms of future teachers, both for the competent education administrations and universities. It may also serve as a starting point to adjust the permanent training offer for teachers to their specific needs, making up for the deficiencies of their initial training.

This study examines the digital accessibility of information services for students with disabilities at the University of Jordan. Despite advancements in disability rights and technology, academic libraries often lag in providing fully accessible digital services.

The mixed-methods research involved quantitative surveys from 173 students with disabilities and a qualitative interview with the head of the information application department, in addition to a focus group interview with 10 students with disabilities. Quantitative analysis included means, standard deviations and four-way ANOVA to identify significant differences in perceptions. Qualitative insights highlighted specific issues and recurring themes, revealing significant gaps in digital accessibility.

The results revealed a weak level of digital accessibility of students with disabilities to information services in academic libraries in Jordan is very low. The findings indicate a need for improvements in library infrastructure, staff training and policy development. The study also offers insights into challenges in a developing country context and provides recommendations for enhancing library inclusivity and support structures, emphasizing the importance of aligning services with international accessibility standards.

The findings will primarily be beneficial for library managers to understand their library’s deficiencies and responsibility towards the local community and the enhancement of digital inclusion. This understanding will aid in planning training programs and workshops for employees on supporting students with disabilities. Additionally, it serves as a valuable resource for collaboration between libraries and educators to organize educational sessions for academic librarians in Jordan and other developing nations.

It serves as a valuable resource for collaboration between libraries and educators to organize educational sessions for academic librarians in Jordan and other developing nations. This research adds value to existing literature by highlighting the context in one developing country.

This study aims to investigate the synergies between the economic environment and the smart living dimension embedded in the current smart city initiatives, focusing on the localization of female entrepreneurship in contemporary cities. This interaction is under-investigated and controversial as it includes cities' practices enabling users and citizens to develop their potential and build their own lives, affecting entrepreneurial and economic outcomes. Building upon the perspective of the innovation ecosystems, this study focuses on the impact of smart living dimensions and R&D investments on the localization of female entrepreneurial activities.

The study uses a Generalized Method of Moments (GMM) and a panel dataset that considers 30 Italian smart city projects for 12 years to demonstrate the relationship between smart living practices in cities and the localization of female entrepreneurship. The complementary effect of public R&D investment is also included as a driver in the “smart” city transition.

The study found that the advancement of smart living practices in cities drives the localization of female entrepreneurship. The study highlights the empirical results, the interaction over the years and a current overview through choropleth maps. The public R&D investment also affects this relationship.

This study advances the theoretical discussion on (1) female entrepreneurial intentions, (2) smart city advancement (as a context) and (3) smart living dimension (as a driver) and offers valuable insight for governance and policymakers.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship. The findings provide valuable insights into the localization of female entrepreneurship in the context of smart cities.

The purpose of this study is to contribute to the existing literature on the importance of mentorship in academia, particularly in higher education. Specifically, this study aims to address the research gap related to academic mentorship from a gendered perspective. The Productive Mentoring Framework and relational–cultural theory theoretically support this study.

In this qualitative descriptive study, purposive sampling was used to recruit 19 participants for semi-structured interviews and a focus group. Two research questions guided this study: (1) How do individuals who identify as women describe the importance of mentorship in academia? (2) How do individuals who identify as women describe mentorship in academia from a gendered perspective? Using Braun and Clarke’s (2006) thematic analysis, a total of six themes emerged, with three themes identified for each of the two research questions from the data: (a) guidance and support, (b) personal and professional development, (c) inclusive and accountable relationships, (d) empathetic and supportive mentorship, (e) interpersonal connectivity and (f) gender empowerment and advocacy.

The research findings suggest that the participants held perceptions of gender disparity within academia. Additionally, empowering interpersonal relationships with other women and supportive environments were crucial in overcoming challenges and developing personally and professionally in higher education institutions. Future research is recommended to explore the perspectives of women supporting women and the perception of gender disparity in academia.

While successfully addressing the research questions, this study has limitations. One limitation was that this study had a relatively small sample size of participants who identified as women, which limited the focus of this research. Another limitation was that interview and focus group participants did not mention working with mentors who fall outside the traditional binary of male and female. Finally, limitations can occur in qualitative research as there is potential bias in the data analysis process. However, member-checking and codebook verification were utilized to minimize this constraint.

There are practical implications from the research for mentoring practices in academia. Since the results indicated benefits to women, institutions could prioritize mentoring programs, especially pairing same-gender mentors and mentees. This helps new employees navigate academia. Mentoring fosters interpersonal connectivity, improving academic culture. By supporting mentoring relationships and professional friendships, leaders positively impact dynamics within institutions. Gender disparities and systemic barriers call for advocacy within higher education. Mentor training programs should address these issues, providing a platform for solutions. Administrators' awareness may support efforts to improve equity.

The study is original in its focus on academic mentorship from a gendered perspective, as described by women in academia, notably higher education.

This study aims to comprehensively analyze the intersection of technology management and innovation management amidst the fourth industrial revolution, uncovering evolving trends and influential contributors.

Using the Bibliometrix R-package, this pioneering research conducts a bibliometric analysis to delve into innovation and technology management literature, quantifying scholarly output and identifying thematic breakthroughs.

The study reveals quantitative insights into the progression of innovation and technology management research, offering guidance on evolving trends, thematic breakthroughs and influential contributors.

The findings offer valuable insights for practitioners and managers, guiding them through emerging trends and recommending a dual focus on fundamental principles and emerging areas for strategic decision-making.

By fostering active engagement with evolving trends, this research contributes to the ongoing technology and innovation management discourse, potentially leading to societal benefits and advancements.

This study pioneers an in-depth bibliometric analysis at the intersection of innovation and technology management, offering unique insights and quantitative assessments of scholarly output and thematic trends, thus adding significant value to the existing literature.