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Through the development of an empirical model and using community sport organizations (CSOs) as the basis for intervening variables, this study aims to ascertain the impact of Muslim household consumption, sport development officers (SDOs) and CSOs on Islamic sport development (ISD) during the COVID-19 pandemic.

All of the sports branch managers in Banten Province make up the study’s sample. Non-probability sampling with a purposive sampling strategy was the sampling method used. Making use of a questionnaire to gather data, 275 different sets of data are available for analysis.

Partial least squares is a tool for technical data analysis. With a t-statistic value of 71.358, the Moslem household consumption construct had a favorable and significant impact on the SDO construct. With a t-statistic value of 1.111, the Moslem household consumption construct had a positive but not statistically significant impact on ISD.

With a t-statistic value of 3.926, the Moslem household consumption construct had a positive and statistically significant impact on CSOs. With a t-statistic value of 1.111, the SDO construct had a positive and statistically significant impact on ISD. This study makes a new contribution by providing practical recommendations for the relationship between ISD authorities, community sports organizations and the positive and substantial impact on the development of the community and ISD.

The primary aim of this paper is to concurrently use the data types to enhance econometric analysis in the housing market in developing countries, particularly Namibia.

Scholarly discussions on econometric analysis in the housing market in sub-Saharan Africa suggest that the inadequacy of time series data has impeded studies of such nature in the region. Hence, this paper aims to comparatively analyse the impact of economic fundamentals on house prices in Namibia using real and interpolated data from 1990 to 2021 supported by the ARDL model.

It was discovered that in all the three types of data house prices were affected by fundamentals except real GDP in the long term. It was also noted that there were not much significant variations between the real data and the interpolated data frequencies. However, the results of the annual data and the semi-annual interpolated data were more analogously comparable to the quarterly interpolated data

It is suggested that the adoption of interpolated data frequency type should be based on the statistical significance of the result. In addition, the need to monitor the nexus of the housing market and fundamentals is necessary for stable and sustainable housing market for enhanced policy direction and prudent property investment decision.

The study pioneer to concurrently use the data types to enhance econometric analysis in the housing market in developing countries.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

The paper discusses a partnership between Huston–Tillotson University (HT), a Historically Black College and University (HBCU) and the Austin Independent School District (AISD), a minority-serving school district, both in Austin, Texas, with a grant provided by Apple Inc. (Apple). The purpose of the partnerships is that valuable relationships can increase the number of African American male teachers in primary and secondary education in minority-serving public schools. The African American Male Teacher Initiative (AAMTI) at HT was created as an innovative approach to recruit and select 20 African American males each year of a four-year grant provided by Apple.

This paper reviewed the literature on the lack and need for African American male public school teachers. Once the data is established during a three-to-four-year period, a mixed-method approach will be utilized to examine data retrieved from interviews, surveys, demographics of student participants, numerical data and retention and graduation rates. This will establish whether strategic partnerships can successfully increase the number of qualified African American males in public education.

This paper proposes and provides research evidence that African American male teachers can positively impact all students in the classroom setting.

There is limited data to test a hypothesis on the effectiveness of a partnership between the university and public school to increase the number of African American male teachers through recruitment – selection and retention efforts. Therefore, follow-up research is needed for the first graduating class of 2024.

The broader impact of this paper is to show that partnerships between universities and public schools with corporate sponsorship can positively increase the number of African American male teachers prepared to teach in public schools through strategic recruitment and selection efforts.

This paper can serve as a model for universities and school districts to implement. High placement of prepared Black male teachers in public schools can reduce the school-to-prison pipeline and juvenile homicides and defeat generational poverty.

Much research highlights the problems associated with a lack of African American male teachers. This paper includes the challenges but offers a sound basis for practical solutions.

The motivation to participate in crowdsourcing (CS) platforms is an emerging challenge. Although researchers and practitioners have focused on crowd motivation in the past, the results obtained through such practices have not been satisfactory. Researchers have left unexplored research areas related to CS pillars, such as the evolution of the crowd’s primary motivations, seekers applying effective policies and incentives, platform design challenges and addressing task complexity using the synchronicity of the crowd. Researchers are now more inclined to address these issues by focusing on sustaining the crowd’s motivation; however, sustaining the crowd’s motivation has many challenges.

To fill this gap, this study conducted a systematic literature review (SLR) to investigate and map the challenges and factors affecting sustained motivation during CS with the overcoming implications. Studies that satisfied the inclusion criteria were published between 2010 and 2021.

Important sustainable factors are extracted using the grounded theory that has sustained participation and the factors' cohesion leads to the identification of challenges that the pillars of CS face. Crowds being the most vital part of CS contests face the challenge of engagement. The results reported the factors that affect the crowd’s primary and post-intentions, perceived value of incentives and social and communal interaction. Seekers face the challenge of knowledge and understanding; the results identify the reason behind the crowd’s demotivation and the impact of theories and factors on the crowd's psychological needs which helped in sustaining participation. Similarly, the platforms face the challenge of being successful and demanding, the results identify the latest technologies, designs and features that seekers proclaim and need the platforms designer's attention. The identified task challenges are completion and achievement; the authors have identified the impact of trait of task and solving mechanisms that have sustained participation.

The study identifies, explores and summarizes the challenges on CS pillars researchers are facing now to sustain contributions by keeping participants motivated during online campaigns. Similarly, the study highlights the implication to overcome the challenges by identifying and prioritizing the areas concerning sustainability through the adoption of innovative methods or policies that can guarantee sustained participation.

In recent years patents have become a very popular data source for forecasting technological changes. However, since a vast amount of patents are “worthless” (Moore, 2005), there is a need to identify the promising ones. For this purpose, previous approaches have mainly used bibliographic data, thus neglecting the benefits of textual data, such as instant accessibility at patent disclosure. To leverage these benefits, this study aims to develop an approach that uses textual patent data for predicting promising patents.

For the identification of promising patents, the authors propose a novel approach which combines link prediction with textual patent data. Thereby the authors are able to predict the emergence of hitherto unmentioned bigrams. By mapping these future bigrams to recent patents, the authors are able to distinguish between promising and nonpromising patents. To validate this approach, the authors apply the methodology to the case example of camera technology.

The authors identify stochastic gradient descent as a suitable algorithm with both a receiver operating characteristic area under curve score and a positive predictive value of 78%, which outperforms chance by a factor of two. In addition, the authors present promising camera patents for diverse application fields, such as cameras for surgical systems, cameras for rearview vision systems in vehicles or light amplification by stimulated emission of radiation detection and ranging cameras for three-dimensional imaging.

This study contributes in at least three directions to scholarship. First, the authors introduce a novel approach by combining link prediction with textual patent analysis and, in this way, leverage the benefits of both worlds. Second, the authors add to all theories that regard novel technologies as a recombination of existing technologies in presenting word combinations from textual data as a suitable instrument for revealing recombination in patents. And third, the approach can be used by scholars as a complementary or even integrative tool with conventional forecasting methods like the Delphi technique or Scenario planning.

At least three practical implications arise from the study. First, incumbent firms of a technology branch can use this approach as an early-warning system to identify technological change and to identify opportunities related to their company’s technological competence and provide inspiration for new ideas. Second, companies seeking to tap into new markets may also be interested in the approach as managers could anticipate whether their company’s technological competences are in line with upcoming trends. Third, the approach may be used as a supportive tool for various purposes, such as investment decisions or technology life cycle analysis.

The approach introduces textual patent data as suitable means for forecasting activities. As the statistical validation reveals, the promising patents identified by the approach are cited significantly more often than patents with less promising prospects.

The study aims to evaluate PubMed publications on ChatGPT or artificial intelligence (AI) involvement in scientific or medical writing and investigate whether ChatGPT or AI was used to create these articles or listed as authors.

This scoping review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. A PubMed database search was performed for articles published between January 1 and November 29, 2023, using appropriate search terms; both authors performed screening and selection independently.

From the initial search results of 127 articles, 41 were eligible for final analysis. Articles were published in 34 journals. Editorials were the most common article type, with 15 (36.6%) articles. Authors originated from 27 countries, and authors from the USA contributed the most, with 14 (34.1%) articles. The most discussed topic was AI tools and writing capabilities in 19 (46.3%) articles. AI or ChatGPT was involved in manuscript preparation in 31 (75.6%) articles. None of the articles listed AI or ChatGPT as an author, and in 19 (46.3%) articles, the authors acknowledged utilizing AI or ChatGPT.

Researchers worldwide are concerned with AI or ChatGPT involvement in scientific research, specifically the writing process. The authors believe that precise and mature regulations will be developed soon by journals, publishers and editors, which will pave the way for the best usage of these tools.

This scoping review expressed data published on using AI or ChatGPT in various scientific research and writing aspects, besides alluding to the advantages, disadvantages and implications of their usage.

Within the scope of broadening participation and developing diverse talents in STEM leadership, this paper aims to deliver a research study that explores faculty leaders’ caring intelligence as STEM leadership intelligence. STEM leadership intelligence is the knowledge, skills, traits and aptitude essential to effective leadership in STEM education.

A previously developed STEM caring-oriented academic managerial leadership framework (SCAMLF) and a typology of STEM faculty leadership styles were used to thematically analyze the caring intelligence and leadership qualities of STEM faculty leaders. Interview transcripts of 18 STEM faculty leaders at Historically Black Colleges and Universities (HBCUs), provided by the Center for the Advancement of STEM Leadership (CASL), were used as data in this study.

The empirical evidence gained from this study highlighted important themes, descriptors and narratives for exploring caring intelligence and leadership intelligence of STEM faculty leadership in HBCUs.

Although the generalizability of the study is limited because of the sample size, STEM caring was found to be the most common dimension present in the reflections of participating STEM faculty leaders with diverse leadership styles. Implications for future research on STEM leadership intelligence were discussed.

Studying caring intelligence as a form of leadership intelligence provides a new and innovative means of assessing STEM leadership intelligence. Caring intelligence can be employed to predict the mindset, performance and behaviors of STEM faculty leaders.

A nation's economic development is adversely affected by the rising population and the lack of employment opportunities, necessitating the promotion of entrepreneurial activities. This study aims to unfurl the critical factors shaping university students' entrepreneurial intentions (EI) in an emerging economy.

The study assessed the EI of 640 university students across India's top 5 central universities through structural equation modeling by extending the entrepreneurial event model (EEM) and dark triad theory. Mediation and moderation techniques were used to examine the model's direct and indirect linkages.

The results show that propensity to act (PTA), perceived resilience (PRS) and narcissism (NAR) magnify desirability, significantly increasing students' EI. The association between the underlying constructs is partially mediated by the PTA and perceived desirability (PD). In addition, the linkage between PD and students' EI is strengthened by the pursuit of excellence (PoE) and weakened by perceived risk (PR).

The study's findings could assist educators, universities, aspiring entrepreneurs, financial institutions, policymakers, investors, venture capitalists, incubators and accelerators in reinforcing entrepreneurial culture in India by establishing a link between crucial personality traits and intentions to start entrepreneurial ventures.

Personality traits such as NAR, resilience and the PoE have not received much attention in the entrepreneurship literature and call for a rigorous inquiry. The study tries to embrace these dominant personality traits by broadening the perspectives of EEM and dark triad theory via a comprehensive conceptual model. It also explores the role of the PoE and PR as moderators to examine the possible association between the identified constructs.

Shifting to OLSL classes during the pandemic can bring learners ambivalent experiences: negative, positive or both appraisals toward the technologies. However, few studies have examined how ambivalent experiences can influence students' learning behaviors, specifically cyberslacking and active participation. Using the challenge-hindrance stressor framework, this study investigates the impact of challenge and hindrance appraisals on these learning behaviors.

This study uses a mixed methods approach to answer research questions. An interview was conducted to identify the key components of ambivalent appraisals, and a survey was conducted to empirically examine the impact of challenge and hindrance appraisals on learners' behaviors in online live streaming learning (OLSL) contexts. The data of 675 university students were analyzed using structural equation modeling.

This study found that hindrance appraisal leads to cyberslacking while challenge appraisal leads to active participation, but it can also cause cyberslacking. Social presence has a double-edged effect, acting as both a facilitator and inhibitor, strengthening the effect of hindrance appraisal on cyberslacking and the impact of challenge appraisal on active participation.

Prior studies have primarily focused on the negative side (techno-distress) of technology appraisals. This study simultaneously examines the positive side, techno-eustress, on learners' behaviors in OLSL contexts, and explores the moderating effects of social presence. This study contributes to the technostress and technology adaptation literature by revealing how technology-induced ambivalent appraisals impact behavioral responses. It offers important theoretical and practical implications for education tool designers.