Understanding The Impact of Mentorship, Marketing Skills, And Personality Traits on Career Readiness Of Gen Z Apprentices

Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example

This study focuses on the career development of students at the senior secondary education level. The purpose of this research is to analyze the influence of self-potential and the school environment on students’ career development through the mediating role of the Double Track Program at SMAN Pilangkenceng. This study employs a quantitative approach using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. Data were collected through questionnaires from 92 students participating in the Double Track Program. The study hypothesizes that self-potential and the school environment have a significant influence on career development, both directly and through the mediating program. The findings indicate that the school environment has a positive and significant effect on students’ career development, both directly and through the Double Track Program, while self-potential shows no significant effect. This research contributes to the field of educational management by highlighting the effectiveness of the Double Track Program as a vocational innovation linking the educational environment with career readiness. The results emphasize the importance of strengthening school support and optimizing program implementation to enhance students’ employability and future career success.

ABSTRACTInformed by the Compensatory Internet Use theory, this study was aimed at revealing possible links between adults’ personality traits, Fear of Missing Out (FoMO), and Problematic Internet Use (PIU). Given the exploratory nature of this study, two statistical techniques were used: Smallest Space Analysis (SSA, a variant of multidimensional scaling), and Partial Least Squares Structural Equation Modeling (PLS-SEM). Data were gathered from 359 adults, by three questionnaires: Fear of Missing Out scale (FoMOs), Short Problematic Internet Use Test (SPIUT), and the Big Five personality trait questionnaire. The SSA results yielded a radex projection. The projection has confirmed the five-factorial theoretical structure of the Big Five personality traits. In the SSA projection, the PIU was found in the extraversion area, the FoMO in the neuroticism area, and both PIU and FoMO factors were in close proximity to each other. Based on the SSA map and the theoretical framework, PLS-SEM was deployed to discover possible links between the research factors. According to the results, the FoMO variable had a mediating role, linking neuroticism to PIU. Limitations, conclusions, and directions for further research are discussed.

Measurement errors wield the potential to introduce uncertainties and inaccuracies, casting shadows on data quality and jeopardizing the integrity of structural relationships. Notably robust against measurement errors, Partial Least Squares Structural Equation Modelling (PLS-SEM) has historically maintained a reputation for resilience. However, recent insights have unveiled its susceptibility to these errors, instigating a revaluation of its standing in the Structural Equation Modelling landscape. Overlooking measurement errors in PLS-SEM carry consequential repercussions, notably tainting the accuracy of structural relationships and introducing bias. This effect becomes particularly pronounced when dealing with an insufficient understanding of the intricate structural dynamics. Unfortunately, PLS-SEM currently lacks an all-encompassing remedy to address this concern. Consequently, the quantification of measurement errors impact in PLS-SEM gains paramount importance, fostering a demand for innovative strategies to propel its effectiveness forward. Notably, contemporary investigations have unmasked PLS-SEM's vulnerability to non-orthogonal errors. This revelation challenges the notion of its imperviousness to the detrimental influence of measurement errors, necessitating a comprehensive evaluation of its performance under such conditions. This study leveraged simulated data to extract empirical findings and employed parameters biasedness analysis. This analysis led to the determination that the stability of the PLS-SEM algorithm is compromised when exposed to diverse measurement error scenarios. Consequently, the outcomes generated exhibit both instability and bias. This bias becomes increasingly conspicuous as the magnitude of measurement errors intensifies. Thus, the study proposes avenues for elevating the robustness of PLS-SEM.

Background: Patient satisfaction is used as an important marker of the quality of medical services. This has an impact on patient loyalty and increases patient retention. Generally, perceptions of the quality of hospital services are based on patients' assessments of the services provided by the hospital, for example the relationship between patients and nurses, doctors and staff. Purpose: To determine factors related to general patient satisfaction. Method: Quantitative research with hypothesis testing without special treatment of subjects during the research period. Data was obtained through a survey of all patients who visited the emergency room at Budi Mulia Bitung Hospital in January 2024, totaling 170 respondents. The sample in this study was taken using a non-probability sampling method with the criteria, being more than 19 years old, cooperative, having a cell phone, and being able to be guided to fill out an online questionnaire. Results: All indicators in each dimension have an outer loading value of >0.7 and an AVE value for satisfaction with doctor services (0.703), emergency staff (0.860), emergency environment (0.656), general patient satisfaction (0.674). Cronbach's alpha and Composite Reliability values for all variables are above 0.7. The R-Square value for the general satisfaction variable is 0.948 and behavioral intention (0.944), so it can be said to be overfit. Based on the t-statistic value, p-value, and path coefficient, all variables in the research model tested are all significant. Conclusion: Satisfaction with physician services, emergency department staff, and emergency department environment are factors that are associated with general patient satisfaction and behavioral intentions. Keywords: Behavioral Intention; Patient Satisfaction; Partial Least Squares Structural Equation Modeling (PLS-SEM) Pendahuluan: Kepuasan pasien digunakan sebagai penanda penting untuk kualitas layanan medis. Hal ini berdampak pada loyalitas pasien dan meningkatkan retensi pasien. Umumnya persepsi kualitas pelayanan rumah sakit didasarkan pada penilaian pasien terhadap pelayanan yang diberikan rumah sakit, misalnya hubungan antara pasien dan perawat, dokter dan staf. Tujuan: Untuk mengetahui faktor-faktor yang berhubungan dengan general satisfaction patient. Metode: Penelitian kuantitatif dengan pengujian hipotesis tanpa perlakuan khusus terhadap subjek selama periode penelitian. Data yang diperoleh melalui survei kepada seluruh pasien yang berkunjung ke IGD RS. Budi Mulia Bitung pada bulan Januari 2024 sebanyak 170 responden. Sampel dalam penelitian ini diambil menggunakan metode non-probability sampling dengan kriteria, sudah berusia lebih dari 19 tahun, kooperatif, memiliki handphone, dan dapat dipandu untuk mengisi kuesioner online. Hasil: Semua indikator pada setiap dimensi memiliki nilai outer loading >0.7 dan nilai AVE physician care satisfaction (0.703), emergency department staff (0.860), emergency department environment (0.656), general satisfaction patient (0.674). Nilai cronbach’s alpha dan composite reliability pada semua variabel telah berada di atas 0.7. Nilai R-Square pada variabel kepuasan umum sebesar 0.948 dan niat berperilaku (0.944), sehingga dapat dikatakan overfit. Berdasarkan nilai t-statistik, nilai-p, dan koefisien jalur seluruh variabel dalam model penelitian yang diuji semuanya signifikan. Simpulan: Physician care satisfaction, emergency department staff, dan emergency department environment merupakan faktor-faktor yang berhubungan dengan general satisfaction patient dan behaviour intention. Kata Kunci: Behavioral Intention; Partial Least Squares Structural Equation Modeling (PLS-SEM); Patient Satisfaction.

Introduction: Educational leadership today faces mounting complexity, requiring school leaders to make rapid yet well-reasoned decisions that influence institutional success. Existing leadership development programmes, such as the National Professional Qualification for Educational Leadership (NPQEL), emphasise strategic thinking and performance; however, the specific psychological and behavioural traits that underpin decision-making remain underexplored. This study aims to investigate how self-efficacy (a psychological trait) and ambidextrous leadership (a behavioural trait) influence school leaders’ decision-making, with strategic thinking examined as a mediating cognitive process. Grounded in Social Cognitive Theory and Trait Theory, the research addresses a key gap in understanding how internal beliefs and adaptive leadership behaviours translate into decision-making competence through strategic cognition. Methods: A quantitative research design was employed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The sample comprised 275 school leaders across Malaysia who completed the NPQEL programme between 2018 and 2020. Data were analysed to test both direct effects and mediating pathways within a hypothesised structural model. Results: The findings indicate that both self-efficacy and ambidextrous leadership significantly predict decision-making capability. Importantly, strategic thinking was found to partially mediate these relationships, suggesting that school leaders with greater emotional and behavioural adaptability leverage strategic cognition to make more effective decisions. These results reinforce the necessity for leadership programmes to move beyond technical training by incorporating strategies that foster psychological resilience and strategic cognitive development. Conclusion: The study contributes to the theoretical advancement of educational leadership by integrating emotional, behavioural, and cognitive dimensions into a unified model of decision-making. Practically, it offers evidence-based insights for policymakers and educational institutions to enhance leadership preparation for complexity, ambiguity, and outcome-driven environments.

Food and dining are integral to the travel experience for tourists. Despite this, there is a lack of research on how tourists choose between dining in and dining out. Furthermore, these choices may be influenced by the tourists’ personality traits. To address this gap, this study explores how the Big Five personality traits impact tourists’ preferences for dining in or dining out hospitality services. We gathered data from 790 tourists through an online survey and employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the data. The results reveal that Openness to Experience is positively associated with the preference for dining in services but negatively associated with avoiding dining in or out. Conscientiousness is positively related to avoiding dining in or out. Extraversion is positively linked with the preference for dining in or out services, while Agreeableness has no association with either approaching or avoiding dining in/out. Neuroticism is positively associated with both approaching or avoiding dining in or out services. This study is not only one of the initial studies examining the influence of personality traits on tourists’ dining preferences but also help practitioners develop strategies via tourists’ personality traits to increase revenue for dining in/out services.

In management accounting research, the capabilities of Partial Least Squares Structural Equation Modelling (PLS-SEM) have only partially been utilized. These yet unexploited capabilities of PLS-SEM are a useful tool in the often explorative state of research in management accounting. After reviewing eleven top-ranked management accounting journals through the end of 2013, 37 articles in which PLS-SEM is used are identified. These articles are analysed based on multiple relevant criteria to determine the progress in this research area, including the reasons for using PLS-SEM, the characteristics of the data and the models, and model evaluation and reporting. A special focus is placed on the degree of importance of these analysed criteria for the future development of management accounting research. To ensure continued theoretical development in management accounting, this article also offers recommendations to avoid common pitfalls and provides guidance for the advanced use of PLS-SEM in management accounting research.

Researchers across a wide range of disciplines exploited the capabilities of partial least squares structural equation modeling (PLS-SEM). The rise in popularity of PLS-SEM is particularly noticeable 2013 onwards. The banking and finance discipline, however, hardly exploits the advantages of the PLS-SEM approach. PLS-SEM can be used for prediction and exploration in complex models with relaxed expectations on data. PLS-SEM is useful in identifying relationships between constructs. If the primary objective is theory development, PLS-SEM is appropriate.

This study investigates the influence of Big Five personality traits and motivation on student resilience among Malaysian university students. Personality traits: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism are established as core dimensions of individual differences, while motivation remains a central driver of academic performance and persistence. Drawing on Social Cognitive Theory and Self-Determination Theory, the study employed a quantitative survey design with data analyzed using Partial Least Squares-Structural Equation Modelling (PLS-SEM). The findings validated the proposed theoretical assumptions, demonstrating significant effects of both Big Five personality traits and motivation on student resilience, thereby supporting the study’s hypotheses (H1 and H2). The predictors explained a substantial proportion of the variance in resilience, with R² values ranging from 0.421 to 0.414. Importantly, the R² value of 0.414 exceeded Cohen’s (1988) recommended threshold of 0.26, affirming the robustness and stability of the research model. These results highlight that personality traits and motivation positively and meaningfully enhance resilience among students. The study contributes theoretically by bridging Social Cognitive Theory and Self-Determination Theory in understanding resilience, and practically by providing insights for universities and policymakers to develop targeted interventions that strengthen resilience and motivation. Such efforts are crucial to improving student well-being, adaptability, and academic success in Malaysia’s higher education context.

This study examines the impact of talent management on employee performance and employee ambidexterity at Universitas Terbuka. The research involved 164 respondents, consisting of lecturers and educational staff. The sample profile indicates that the majority of respondents are aged between 26 and 35, with 54% being female. Educational background data reveal that 69% hold a master’s degree, while 5% have a doctoral degree. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the validity, reliability, and structural relationships among variables. Convergent validity was evaluated using outer loading values and Average Variance Extracted (AVE), confirming that the indicators of talent management, employee ambidexterity, and employee performance meet the validity requirements. Discriminant validity was tested using the Fornell-Larcker criterion, ensuring that each construct is distinct from others. Reliability tests, measured through composite reliability and Cronbach’s Alpha, demonstrate that all constructs exhibit high internal consistency. The structural model analysis, including F-square, R-square, and adjusted R-square, shows that talent management significantly influences employee ambidexterity (R² = 0.622) and moderately affects employee performance (R² = 0.355). Path analysis using bootstrapping confirms the direct and indirect effects of talent management on employee ambidexterity and performance, highlighting the importance of talent management in enhancing workforce capabilities. This research provides valuable insights into human resource strategies within higher education institutions, emphasizing the role of effective talent management in improving employee adaptability and overall performance. Future studies should explore additional mediating factors to further understand the dynamics between talent management and organizational outcomes.

This study explores the mediating effect of personality traits in the relationship between entrepreneurial intentions and student academic performance. The sample comprised 175 students from a top-ranked Tamil Nadu, India university. Data was collected using a survey questionnaire as the research instrument. A descriptive research design was employed to understand the variables under investigation comprehensively. Partial Least Squares Structural Equation Modeling (PLS-SEM) and SPSS v25 was utilized as the statistical analysis tool. This study used the Theory of Planned Behaviour as a theoretical framework to explore the mediating effect of personality traits in the relationship between entrepreneurial intentions and academic performance among university students. The study’s findings revealed essential insights into the relationship between entrepreneurial intentions, personality traits, and academic performance. The results showed that personality traits significantly mediate the relationship between entrepreneurial intentions and academic performance. This finding suggests that a student’s personality traits influence the impact of entrepreneurial intentions on academic performance. Furthermore, the study found that while entrepreneurial intentions did not have a significant direct effect on academic performance, they did have a substantial indirect effect through personality traits. This indicates that personality traits act as a crucial mechanism through which entrepreneurial intentions can influence academic performance among students.

This study seeks to establish the influence of the Big Five personality traits, which include Openness, Neuroticism, Conscientiousness, Agreeableness, and Extraversion, on growers’ willingness to embrace crop insurance schemes. Furthermore, it explores the role of Attitude, Subjective Norms, and Perceived Behavioral Control, as proposed in the Theory of Planned Behavior (TPB), on this relationship. Using a structured questionnaire, data were collected from 412 growers of arecanut and pepper. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via Smart-PLS 3.3. The analysis revealed that Perceived Behavioral Control (β = 0.462**), Subjective Norms (β = 0.260**), and Attitude (β = 0.115**) positively influenced growers’ behavioral intentions. Interestingly, the Big Five personality traits themselves did not have a direct effect on these intentions. Further mediation analysis demonstrated that Attitude and Subjective Norms fully mediated the effects of Extraversion (α = 0.026**, β = 0.069), Neuroticism (α = 0.019**, β = –0.016), and Openness (α = 0.024**, β = 0.069) on Behavioral Intention. However, these variables did not mediate the relationship between Agreeableness (α = 0.011, β = 0.058), Conscientiousness (α = –0.017, β = –0.080), and Behavioral Intention. Additionally, perceived behavioral control mediated the link between personality traits and intention, though this was not the case for Conscientiousness. This study contributes to the application of the TPB by incorporating the Big Five personality traits and exploring their interaction with the TPB dimensions.

This study explores the mediating effect of personality traits in the relationship between entrepreneurial intentions and student academic performance. The sample comprised 175 students from a top-ranked Tamil Nadu, India university. Data was collected using a survey questionnaire as the research instrument. A descriptive research design was employed to understand the variables under investigation comprehensively. Partial Least Squares Structural Equation Modeling (PLS-SEM) and SPSS v25 was utilized as the statistical analysis tool. This study used the Theory of Planned Behaviour as a theoretical framework to explore the mediating effect of personality traits in the relationship between entrepreneurial intentions and academic performance among university students. The study's findings revealed essential insights into the relationship between entrepreneurial intentions, personality traits, and academic performance. The results showed that personality traits significantly mediate the relationship between entrepreneurial intentions and academic performance. This finding suggests that a student's personality traits influence the impact of entrepreneurial intentions on academic performance. Furthermore, the study found that while entrepreneurial intentions did not have a significant direct effect on academic performance, they did have a substantial indirect effect through personality traits. This indicates that personality traits act as a crucial mechanism through which entrepreneurial intentions can influence academic performance among students.

This research aims to investigate the factors that influence the effectiveness of Information Systems (IS) Governance in Higher Education Institutions (IPT) using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The background of this research reflects the importance of IS in supporting operations, management and decision making in a higher education environment that is increasingly complex and dependent on technology.The PLS-SEM method analyzes the relationship between key variables that influence the effectiveness of IS governance at IPT. It is a powerful multivariate statistical approach that allows factor analysis and regression in a single framework, allowing researchers to holistically understand how factors relate to each other. The results of this research will likely provide valuable insight for decision-makers at IPT in improving IS management and utilization. Practical implications include the development of more effective policies, better management strategies, and improved IS infrastructure. In addition, this research is also expected to provide an essential contribution to academic literature in understanding the factors that influence the effectiveness of IS governance in the higher education context. By better understanding the factors that influence the effectiveness of IS governance, IPT can increase its competitiveness, improve the quality of educational services, and support the achievement of its strategic goals. This research is expected to significantly contribute to understanding how IS governance can be implemented and managed more effectively in higher education environments through the PLS-SEM approach.