Search Results (52)

Rapid technological changes and evolving labor market demands have increased the importance of identifying the competencies required for successful workforce participation. This study examines how digital competencies (DC) contribute to job market readiness (JMR) among university students and recent graduates in Saudi Arabia by investigating the mediating role of employability competencies (EC) and the moderating role of labor market dynamism (LMD). Drawing on Human Capital Theory and Career Construction Theory, the study develops an integrated framework explaining how individual competencies and labor market conditions jointly shape workforce preparedness. Data were collected using a stratified random sampling approach from 400 participants (248 final-year university students and 152 recent graduates) recruited from universities in Riyadh, Jeddah, Dammam, Medina, and Yanbu using a structured questionnaire. The hypotheses were tested using regression analysis and Hayes’ PROCESS macro, while confirmatory factor analysis was conducted using AMOS 27. The results indicate that DC positively influences both EC and JMR. EC also positively affected JMR and partially mediated the relationship between DC and JMR. Furthermore, LMD significantly strengthened the positive effect of DC on JMR, suggesting that digital competencies are becoming increasingly valuable in dynamic employment environments. This study contributes to the workforce preparedness literature by providing a more comprehensive explanation of how digital competencies are associated with job market readiness through employability competencies and identifying labor market dynamism as a contextual condition associated with the strength of this relationship. The findings offer implications for universities, policymakers, and students seeking to enhance employability outcomes and align workforce development initiatives with Saudi Arabia’s Vision 2030. Full article

Rural communities face persistent economic challenges, and universities increasingly serve as catalysts for regional entrepreneurial development. This study evaluates the RISE29 program, a consulting-based internship initiative placing interdisciplinary undergraduate teams as paid interns with small businesses in economically distressed counties of Eastern North Carolina, examining what students across disciplines learned. Drawing on Cope’s entrepreneurial learning framework as a sensitizing theoretical lens, the study asks: (1) What themes characterize the entrepreneurial learning experiences described by RISE29 interns across cohorts and disciplines? (2) How do reflective depth, student agency, and program satisfaction vary across cohort periods, disciplinary affiliations, and program structures? A multi-layered qualitative analysis of 158 written reflection papers submitted across ten cohorts (Spring 2019–Summer 2022) was integrated with deductive qualitative analysis guided by Cope’s entrepreneurial learning framework, constructivist grounded theory coding, reflexive thematic analysis, reflective depth coding, sentiment and tone analysis, and cross-group comparison. Seven themes emerged: communication as the central axis of learning; collaborative identity development; leadership identity formation; encounter with Eastern North Carolina’s rural communities; professional identity and career clarity; real-world learning and classroom transfer; and program satisfaction with constructive critique. All four dimensions of Cope’s framework were present across disciplines, and non-Business students, in several cases, demonstrated a high degree of analytical depth warranting further investigation. Reflective depth increased in cohorts using an expanded prompt, though overlapping structural changes across the study period preclude single-factor attribution. Place-based, consulting-driven experiential programs generate substantive entrepreneurial learning across disciplinary lines, though findings reflect students’ perceived learning rather than verified competency acquisition. These results support investment in client vetting, structured reflection, cross-disciplinary teaming, and in-person community engagement. Full article

Occupation-level psychological profiles, such as RIASEC interests and Big Five personality, underpin career counseling, person–job matching, and workforce research, but building them at scale has been expensive and limited to a few national taxonomies. The O*NET Interest Profiler, the largest operationalization of RIASEC, took more than two decades of worker surveys, expert ratings, and iterative empirical calibration to construct, and the 2022 Chinese Occupational Classification has no comparable psychological database. Large language models (LLMs) offer a scalable alternative, but using them as raters raises issues that single-model designs do not resolve: inter-rater reliability, calibration to external benchmarks, and systematic psychometric validation. We propose a multi-agent LLM framework in which three LLMs serve as separate expert raters, in-context anchors align the rating scale, and a separate arbitrator resolves rater disagreements. We applied the framework to all 1636 occupations in the 2022 Chinese Occupational Classification, producing six RIASEC and five Big Five scores per occupation. RIASEC dimensions showed uniformly excellent reliability (intraclass correlation coefficient, ICC [2,1] = 0.87 to 0.98) and high convergent correlations with O*NET (r = 0.84 to 0.96); structural validity received weak support (Tracey’s C = 0.653, ns), though the dimensions differentiated occupational categories as theory predicts, and the profile space recovered the administrative taxonomy (adjusted Rand index, ARI = 0.418). Big Five absolute agreement was uniformly high, although ICC(2,1) values for Conscientiousness and Neuroticism were attenuated by variance compression and model-level calibration offsets rather than rater disagreement. The Big Five scores are, therefore, suited to broad occupational differentiation, particularly on Openness and Extraversion, rather than to fine-grained rank ordering on Conscientiousness or Neuroticism. The framework also yields the first occupation-level RIASEC and Big Five database for the 2022 Chinese Occupational Classification, openly available for applied use. Full article

Career adaptability has been linked to academic achievement, yet the mechanisms underlying this association remain insufficiently understood, particularly among adolescents in highly competitive, exam-oriented educational systems. Based on Career Construction Theory (CCT) and the performance model of Social Cognitive Career Theory (SCCT), this study tested whether academic self-efficacy, academic outcome expectations, and metacognitive strategies mediated this association. A three-wave longitudinal study was conducted with 519 students from two general high schools in central China (40.85% boys; mean age = 16.28 years, SD = 0.82). Career adaptability was measured at Time 1, the three mediators were measured at Time 2, and academic achievement was measured at Time 1 and Time 3 using standardized examination scores in Chinese, mathematics, and English. After controlling for baseline achievement and demographic covariates, structural equation modeling with bias-corrected bootstrapping showed that T1 career adaptability had a significant total effect on T3 academic achievement, whereas the direct effect was nonsignificant after the mediators were included. Significant indirect effects were found through academic self-efficacy and metacognitive strategies. Academic outcome expectations did not significantly mediate the association, and the pathway from academic self-efficacy to academic outcome expectations was not supported. These findings indicate that career adaptability may contribute to later academic achievement mainly through students’ academic self-efficacy and metacognitive strategy use. Full article

AI technologies are changing the world of work in ways that are hard to predict, and this uncertainty is felt particularly strongly by young people who are just beginning to think about their futures. This study explores how high school students in Turkey perceive AI’s potential impact on their career choices, using Social Cognitive Career Theory (SCCT) and Uncertainty Management Theory (UMT) as interpretive lenses rather than formally tested models. SCCT helps frame AI as an environmental force that shapes how students think about their career options, while UMT helps explain how students emotionally and cognitively respond to uncertainty that cannot easily be resolved. Using a cross-sectional survey of 354 12th-grade students, we developed and validated the AI-Related Career Perception Questionnaire (AICP-Q), which yielded four factors: AI Anxiety and Career Precarity, AI Literacy and Technological Awareness, Proactive Career Adaptation, and Socio-Technical Uncertainty. Students showed moderate AI awareness but relatively high levels of socio-technical uncertainty. Academic track emerged as an exploratory statistical correlate of AI Anxiety, a descriptive association suggesting that students’ sense of threat from AI may relate more to the specific skill demands of their chosen field than to the prestige of their school, though no causal inference can be drawn from these cross-sectional data. A key finding is “the planning gap”: students recognized the potential career disruptions associated with AI but did not consistently respond with adaptive behaviors. Drawing on UMT, we advance the tentative hypothesis, to be tested in future research, that this pattern may relate to a lack of the appraisal resources needed to translate awareness into action; because these constructs were not directly measured, this remains an interpretive suggestion rather than an empirical finding. Full article

Psychological readiness for career choice represents a critical developmental task during adolescence, shaping subsequent educational paths and vocational self-determination. This study investigates the formation of such readiness among grade nine students in a public secondary school in Almaty, Kazakhstan, using an integrated psychological assessment approach. Grounded in Holland’s RIASEC theory and temperament-based perspectives, the study examines how vocational interests, temperament characteristics, and educational decision status interact in early career planning. Data were collected from 185 students during structured school-based diagnostic sessions employing a RIASEC vocational interest inventory, a temperament assessment, and a brief educational decision questionnaire. The findings reveal a differentiated structure of vocational interests, with social and investigative orientations most prevalent. While a majority of students reported preliminary career or educational choices, a substantial proportion remained undecided, indicating heterogeneous levels of psychological readiness. Temperament distributions suggest that emotional regulation plays an important role in translating vocational interests into concrete decisions. Overall, the results support conceptualizing psychological readiness as a multidimensional construct encompassing interest clarity, personality-related regulation, and decision commitment. The study highlights the importance of sustained, psychologically informed career guidance during key educational transitions and offers practical implications for school-based career counseling. Full article

Choosing a future career represents a complex developmental task, often accompanied by multiple concerns and anxieties. The Social Cognitive Career Theory and Life Design paradigm emphasize the importance of supporting individuals in managing career-related challenges. However, global stressors—such as the COVID-19 pandemic, the war in Ukraine, and increasing awareness of the climate emergency—have introduced new and multifaceted sources of uncertainty that are not adequately captured by existing instruments. This gap highlights the need for a psychometrically sound measure to assess emerging career-related concerns in the contemporary context. Accordingly, the study aimed to develop and validate the Career Concerns related to Perceived Environmental Challenges (CC-PEC Scale). Four studies were conducted. Study 1 employed exploratory factor analysis, supporting a three-factor structure (Career-related COVID-19 pandemic concern, Career-related war concern, and Career-related climate emergency concern). Study 2 confirmed this structure using confirmatory factor analysis and demonstrated measurement invariance across gender, supporting a hierarchical factorial model. Study 3 provided evidence of concurrent and discriminant validity through associations with related constructs. Study 4 offered preliminary evidence of stability and predictive validity using life satisfaction and flourishing as outcome variables. Overall, the findings support the CC-PEC Scale as a reliable and valid instrument for assessing career-related concerns linked to global environmental challenges. These results have important implications for research and career guidance interventions aimed at supporting young people’s career development in increasingly uncertain contexts. Full article

Based on social cognitive career theory, this study constructs and empirically tests a double-mediation model to elucidate the effect of proactive personality on professional identity among Chinese college students. Additionally, it delves into the mediating mechanisms underlying future self-continuity and career calling in this relationship. This study employs a three-stage data collection strategy, collecting data from 382 college students at a normal university in China. Statistical analysis results show that the proactive personality of college students has a significant positive impact on their future self-continuity, career calling, and professional identity. Meanwhile, future self-continuity and career calling of college students both play a mediating role in the influence of proactive personality on professional identity. In conclusion, the results of this study provide the academic community with a new perspective to explain the relationship between proactive personality and professional identity and can also provide specific guidance for improving college students’ professional identity in practice. Full article

The digital carbon footprint denotes the environmental impact generated by digital technologies throughout their lifecycle. Industry 4.0 manufacturing environments rely extensively on data processing, information storage, and artificial intelligence, thereby increasing energy demand and associated carbon emissions. These conditions have intensified interest in Green AI, particularly in applications such as predictive maintenance and collaborative human–machine systems. This research investigates determinants of behavioural intention to adopt Green AI through an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model tailored to Industry 4.0 and sustainability contexts. The framework incorporates performance expectancy, Industry 4.0 eligibility, technology influence, digital manufacturing competence, sustainability conditions, Green AI recognition, and green manufacturing concern. Data were obtained from an anonymous survey of 1003 Generation Z students enrolled in technical disciplines and preparing for manufacturing-oriented careers. Relationships among constructs were analysed using partial least squares structural equation modelling (PLS-SEM). The model demonstrates strong explanatory and predictive capability. Adoption intention is primarily associated with performance expectancy, Industry 4.0 eligibility, and digital manufacturing competence, while sustainability-oriented perceptions play a contextual rather than direct behavioural role. The study offers a domain-specific empirical extension of UTAUT within pre-workforce technical education rather than proposing a new acceptance theory. The findings reflect intention formation prior to labour-market entry and require validation in operational manufacturing settings before broader generalisation. Full article

Despite ongoing efforts to promote gender equity in the construction industry, women remain underrepresented at senior leadership levels. Prior studies have attempted to investigate women’s professional networks in construction through traditional survey- or interview-based approaches, which are often limited in scale and unable to capture the complexity of career mobility patterns. This study adopts a previously underexplored data source, LinkedIn, to examine and compare the career networks of female and male top managers in the Australian construction industry. Using 914 publicly available LinkedIn profiles, social network analysis was conducted in Python using the NetworkX library to construct affiliation-based career networks derived from shared organizational experience. Multiple network metrics were applied to compare network connectivity, cohesion, community structure, core and periphery positioning, and robustness. The results show that female top managers are more densely connected, more locally cohesive, and more globally integrated than their male counterparts. Female career networks also exhibit fewer but larger communities, deeper and more cohesive core structures, and greater robustness to the removal of structurally important individuals. These findings extend career capital theory by highlighting the gendered differences in professional networks and provide evidence-based guidance for women, organizations, and policymakers supporting equitable leadership pathways. Full article

Learning to teach represents a complex process of professional and personal transformation that involves constructing new professional identities, negotiating prior experiences, and engaging with the epistemologies of teaching. For both first- and second-career entrants, ITE is not only a pathway into employment but a significant phase of identity (re)formation and learning within the higher education context. Understanding the needs and challenges that pre-service teachers articulate during this phase therefore provides critical insight into how teacher education functions as a space of learning and belonging. Despite this, empirical research addressing this issue remains limited. Accordingly, the present study sought to address this gap by exploring the differences in the needs and challenges of first- and second-career pre-service teachers. Analysis of qualitative data collected from 123 Australian first- and second-career pre-service teachers revealed that both groups identified a strong need for more authentic, practice-based learning and sustained mentorship to bridge the persistent gap between theory and classroom practice. Despite shared concerns around behaviour management, assessment, and wellbeing, second-career entrants emphasised challenges related to transferring prior professional identities, navigating school cultures, and balancing study with family and financial responsibilities. These findings highlight the importance of differentiated, career-responsive approaches in initial teacher education that recognise diverse life experiences as central to professional learning and teacher identity formation. Full article

Leader–member relationships shape public sector performance, yet how leader–member exchange (LMX) operates through capability and motivation pathways remains underexplored. Drawing on social information processing and career construction theories, this study examines how LMX quality influences civil servant performance through career adaptability and perceived social impact. Moderated mediation analyses of survey data from 363 civil servants in Province A, China, reveal that higher-quality LMX enhances career adaptability and perceived social impact, which, in turn, predict higher task performance and organizational citizenship behavior. However, LMX differentiation weakens these positive effects when perceived as high. In practice, public agencies should prioritize high-quality, low-differentiation LMX systems that enhance civil servants’ performance. Full article

This study comprehensively evaluates the impact of remote work intensity on employee well-being, productivity, and sustainable practices within the IT sector, utilizing a cross-sectional online survey of 1003 employees. Findings reveal that remote work consistently boosts self-rated health, enhances perceived productivity, and promotes the adoption of sustainable workplace practices, with these benefits largely consistent across gender and most age groups. However, its effect on perceived stress is complex and significantly age-dependent, showing increased stress for younger employees (under 25) while mid-career professionals (26–35) experience stress reduction. Perceived stress did not emerge as a statistically significant mediator in the remote work-productivity relationship, suggesting that positive effects on productivity are primarily driven by direct mechanisms such as increased autonomy and flexibility. This research contributes to the Job Demands-Resources and Self-Determination Theory by illuminating how digital work demands and psychological needs are experienced heterogeneously across demographics in the remote context. Practical implications emphasize the need for differentiated stress management strategies tailored to younger employees, as well as a broader promotion of remote work, to enhance sustainable behavior within organizations. Methodologically, the study highlights the value of utilizing large, non-probability datasets, along with carefully constructed proxy scales, and proposes the future integration of AI-powered analytics for deeper insights. Full article

The highway and bridge industry is facing persistent challenges related to the high turnover of technical personnel, which poses risks to the continuity and sustainability of infrastructure development. Although Geographic Information System (GIS) training has increasingly been advocated as a strategy to stabilize the workforce, its practical application remains relatively limited across China. Drawing on the Conservation of Resources (COR) theory, this study examines whether GIS training is associated with lower turnover intention among technical staff, potentially through enhanced perceptions of career growth and reduced work-related anxiety. Based on 412 valid responses—primarily from technical personnel employed by major infrastructure enterprises such as regional subsidiaries of the China Communications Construction Group (CCCG) and China State Construction Engineering Corporation (CSCEC)—the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the proposed relationships. The findings indicate that GIS training is negatively associated with turnover intention, with career growth partially mediating this association. Additionally, work anxiety moderates the relationship, such that the link between GIS training and turnover intention appears weaker under higher levels of anxiety. This research contributes to bridging the gap between training practices and theoretical understanding, offering insights to inform workforce retention strategies in technology-intensive industries. Full article

Biomedical research training initiatives need rigorous evaluation to achieve national goals of supporting a robust workforce in the biomedical sciences. Higher science self-efficacy is associated with the likelihood of pursuing a science-related research career, but we know little about the psychometric properties of this construct. In this study, we report on a comprehensive validation study of the Science Self-Efficacy Scale using a robust sample of 10,029 undergraduates enrolled across 11 higher education institutions that were part of a biomedical training initiative funded by the National Institutes of Health in the United States. We found the scale to be unidimensional with an Omega hierarchical (ω_h) reliability coefficient of 0.86 and a marginal reliability of 0.91. Within the item response theory framework, we did not detect variation in item parameters across undergraduates’ race/ethnicity; however, one item had parameters that varied across gender identity. We determined that the Science Self-Efficacy Scale can be employed across undergraduates enrolled in science, and researchers can use the scale across a diverse group of students. Implications include ensuring that the scale functions consistently across diverse populations, enhancing the validity of conclusions that can be drawn from survey data analysis. Validating this construct with item response theory models strengthens its use for future research. Full article