The Impact of Protean Career on Job Satisfaction and Performance of Lecturers at Private Universities

The Impact of Protean Career on Job Satisfaction and Performance of Lecturers at Private Universities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Protean Career on Job Satisfaction and Performance of Lecturers at Private Universities Asmini Asmini, Andi Adawiah, Sukriadi Sukriadi, Andi Muhammad Yusuf This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8043063/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose – This study investigates the effect of personality, competitiveness, and competence on protean career orientation, job satisfaction, and performance of lecturers at private universities. It aims to validate six hypotheses through a structural model that integrates psychological and institutional career determinants. Methodology – A quantitative explanatory design was applied using structured surveys distributed online and offline to 246 permanent lecturers across Region IX Sulawesi. Measurement instruments were derived from validated theoretical constructs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0. Findings – Results reveal that personality and competitiveness positively influence protean career orientation, while personality and competence significantly enhance job satisfaction. Protean career and job satisfaction also show strong predictive effects on lecturer performance, with all hypotheses statistically supported. Originality – This study offers a novel framework combining psychological traits and institutional factors to explain academic career trajectories, particularly in the underrepresented context of Indonesian private universities. It contributes actionable insights for talent development policy and strategic academic HR management. Figures Figure 1 1. Introduction In an era of rapid institutional change and increasingly complex professional demands, lecturers at private universities face pressure to adapt independently in managing their career development. Protean career orientation, which emphasizes autonomy and personal values in career decision-making, is a strategic approach that can significantly improve job satisfaction and academic performance (Bazine, Peña-Jimenez, & Déprez, 2023 ; Sultana & Malik, 2019 ). In the context of institutional management, a deep understanding of the impact of protean career orientation offers opportunities for the formulation of more adaptive, competitive, and sustainable human resource management policies (Sinniah et al., 2019 ; Tee, Cham, Low, & Lau, 2022 ; Thasimmim, Johannes, Yacob, & Junaidi, 2025 ). Protean career orientation has become an increasingly prominent self-directed approach in competitive and institutionally unstable higher education environments. A values-based and independent approach to career planning enables faculty members to achieve higher job satisfaction and demonstrate optimal academic performance (Herrmann, Hirschi, & Baruch, 2015 ; Redondo, Sparrow, & Hernández-Lechuga, 2021 ). Studies indicate that proactive behavior influenced by protean orientation can enhance productivity and organizational commitment while reducing intentions to leave the institution (Bazine et al., 2023 ; Hollywood, McCarthy, Spencely, & Winstone, 2020 ). This is particularly relevant for faculty members at private universities, who often face structural challenges and career development that is not systematically institutionalized. Previous studies have shown that protean career orientation has a positive effect on job satisfaction and performance of lecturers, both directly and through the mediation of career competence and employability perceptions (Herrmann et al., 2015 ; Sultana & Malik, 2019 ; Tee et al., 2022 ). Institutional factors such as compensation, career development, organizational culture, leadership style, and work relationships also play a role in strengthening these effects (Permana et al., 2021 ; Samsuri, Notosudjono, & Sunaryo, 2024 ; Sultana & Malik, 2019 ; Suparjo, 2017 ). However, few studies have empirically focused on the population of lecturers in private universities in Indonesia or comprehensively examined the interaction between demographic factors and protean orientation (Sern, Ho, Sambasivan, & Yee, 2014 ), making this study relevant and filling an important gap in the literature. Table 1 The Condition of Private Higher Education Institutions in Region IX Sulawesi. Condition of Private Higher Education Institutions South Sulawesi Southeast Sulawesi West Sulawesi Total Number of institutions: 1.210 University 541 104 32 677 Institute 72 20 9 101 College 216 46 26 288 Academy 68 17 4 89 Polytechnic 28 25 0 53 Community Academy 2 0 0 2 Academic Positions totalling 13.570 Junior Lecturer 3.883 1,027 618 5528 Lecturer 3.366 660 197 4223 Assistant Professor 2.546 428 50 3024 Associate Professor 653 27 4 684 Professor 110 1 0 111 Source: Report of the Higher Education Service Agency Region IX Sulawesi, 2021 Table 1 reveals the highly heterogeneous landscape of private higher education institutions in Region IX Sulawesi, with a total of 1,210 institutions spread across three provinces: South Sulawesi, Southeast Sulawesi, and West Sulawesi. The composition of institutions includes universities, institutes, colleges, academies, polytechnics, and community academies, reflecting the diversity of organizational structures and educational orientations. In terms of human resources, there are 13,570 faculty members, with the majority holding junior academic positions such as junior lecturers and lecturers, while the number of professors remains very limited (only 111). This disparity in the distribution of academic positions highlights challenges in faculty career development, particularly at private higher education institutions, which is the primary focus of this study. A solution is for institutions to develop career autonomy-based professional development programs, strengthen mentoring, and increase job autonomy to support lecturers' independent career adaptation (Riza et al., 2024 ; Zhu & Gao, 2024 ). Additionally, protean orientation contributes to higher employability and career success, particularly in dynamic and structurally constrained organizational environments (Nurmilah, Bafadal, Ery Tri, Imron, & Muslim, 2020 ; Tee et al., 2022 ). Thus, protean careers are not merely an individual approach but also a sustainable institutional strategy to enhance the competitiveness and retention of academic human resources. Therefore, it is important to comprehensively examine the relationship between personality and competitiveness toward protean careers. On the other hand, the literature indicates that job satisfaction is influenced by various competencies, including communicative, technical, and interpersonal competencies (Carter, Murray, & Gray, 2011 ; De Grip, Sieben, & Stevens, 2009 ), as well as personality traits such as agreeableness and emotional stability (Kang & Malvaso, 2023 ; Steel, Schmidt, Bosco, & Uggerslev, 2019 ). Protean career itself has been proven to positively contribute to work performance, particularly through increased adaptability, employability, and self-management (Sultana & Malik, 2019 ). Furthermore, the relationship between job satisfaction and performance has been identified as positive, although moderated by factors such as organizational climate and reward systems (Idris, Adi, Soetjipto, & Supriyanto, 2020 ; Ramasamy, Inore, Muduli, & Singh, 2023 ). Based on these findings, the following six hypotheses are proposed: Personality has a positive impact on protean career Personality has a positive impact on job satisfaction Competitiveness has a positive impact on protean career Competence has a positive impact on job satisfaction Protean career has a positive impact on performance Job satisfaction has a positive impact on performance The objectives and novelty of this study are to empirically identify the influence of personality, competitiveness, and competence on protean career, job satisfaction, and performance of lecturers in private universities, which have not been comprehensively explained in an integrated model. The most common claim supported by evidence is that proactive personality, interpersonal competence, and a competitive environment positively contribute to independent career orientation, job satisfaction, and academic performance outcomes. The future perspective of this work is the development of a talent management system based on career personalization and adaptive flexibility, which can serve as the basis for institutional policies to promote the sustainability of academic human resources in the dynamic and digital work era. 2. Research Method This study used a structured survey method conducted through online and offline channels to collect data from private university lecturers in Region IX Sulawesi. This dual approach ensured inclusion across geographical and technological boundaries while taking into account institutional differences in digital access and engagement. The online survey utilized platforms such as WhatsApp and institutional email lists to reach tech-savvy respondents (Lawelai, Sadat, & Harakan, 2024 ), and the offline survey was conducted in collaboration with academic units and administrative offices to capture a variety of academic profiles and positions. This strategy ensured balanced participation and better representation, as seen in the demographic breakdown in Table 2 . Table 2 Demographic information of respondents Respondents N = 246 Number Percent Gender Male 139 56,50 Female 107 43,50 Age 24–39 100 40,65 40–65 146 59,35 Education Master's degree 196 79,67 Doctoral degree 50 20,33 Academic Position Lecturer 43 17,48 Assistant Professor 102 41,46 Associate Professor 76 30,89 Professor 25 10,16 Rank Classification IIIa 28 11,38 IIIb 53 21,54 IIIc 45 18,29 IIId 18 7,32 IVa 38 15,45 IVb 35 14,23 IVc 12 4,88 IVd 6 2,44 IVe 11 4,47 Source: Primary Data Processing, 2025 This study uses a structured survey approach to collect primary data from permanent lecturers working at private universities in Region IX Sulawesi. Respondents were selected using purposive sampling based on academic position, educational level, and geographical distribution covering three provinces: South Sulawesi, Southeast Sulawesi, and West Sulawesi. The total number of respondents was 246, consisting of 56.50% males and 43.50% females, with ages ranging from 24 to 65 years. The instrument used was an electronic questionnaire based on theoretical indicators validated from relevant literature (see Table 3 ), using a five-point Likert scale. Content validation was conducted through expert review and a pilot test with 30 lecturers to ensure the accuracy and reliability of the instrument. The questionnaire was distributed online via an e-survey platform during January–February 2025 and was directly supervised by the research team to ensure proportional regional representation. The collected data were then exported in an encrypted format (.csv) and stored in the institutional repository for academic audit purposes. Analysis was conducted using the SmartPLS 4.0 application with a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, which is suitable for exploratory models with latent variables and multiple indicators. Table 3 Measurement items and sources Variable Code Measurement items Source Personality (PER) PER1 Do you use your personal values to guide your career decisions? (Fryczyńska & Pleśniak, 2024 ; Sern et al., 2014 ) PER2 Do you take initiative in managing your career development? Competency (CMP) CMP1 Do you have a clear understanding of your career goals and how to achieve them? (Sultana & Malik, 2019 ) CMP2 Do you actively build and maintain professional relationships? CMP3 Do you possess the necessary skills for your current job and future career aspirations? Protean Career (PC) PC1 Do you prioritize your personal values over organizational values in your career? (Fryczyńska & Pleśniak, 2024 ; Sern et al., 2014 ; Sultana & Malik, 2019 ) PC2 Do you independently manage your career path and decisions? PC3 Do you regularly reflect on your career goals and progress? PC4 Do you engage in networking activities to advance your career? Job Satisfaction (JS) JS1 Are you satisfied with the nature of your work and tasks? (My Dieu, Al Mamun, Nawi, & Muniady, 2020 ) JS2 Are you satisfied with your relationships with colleagues? JS3 Are you satisfied with your salary and benefits? Performance (PMC) PMC1 Do you consistently meet or exceed your job performance expectations? (Sultana & Malik, 2019 ; Suparjo, 2017 ) PMC2 Do you contribute to innovative practices in your work? PMC3 Do you demonstrate high levels of professional competence in your role? PMC4 Do you engage in continuous learning and development within your organization? Source: Fryczyńska & Pleśniak ( 2024 ) etc. Table 3 were developed based on theoretical constructs and adapted from previous studies relevant to the field of human resource management and academic careers. For example, indicators PER1 and PER2 represent the protean personality dimension, which focuses on the use of personal values and initiative in career decision-making, adapted from Fryczyńska & Pleśniak ( 2024 ) and Sern et al. ( 2014 ). Indicators CMP1–CMP3 reflect career competencies in the form of goal clarity, professional networking, and work skills based on constructs from Sultana & Malik ( 2019 ). The protean career orientation dimension is measured through four indicators, PC1–PC4, which include autonomy in career decisions, career reflection, and networking activities. Meanwhile, job satisfaction and performance are measured through indicators from My Dieu et al. ( 2020 ), Suparjo ( 2017 ), and Sultana & Malik ( 2019 ), focusing on satisfaction with tasks, coworkers, compensation, as well as contributions to innovation and professional competence. By adopting and adapting constructs from various scientific literatures, the development of indicators in this instrument aims to ensure conceptual validity and enable a comprehensive evaluation of the contribution of each variable to protean career, job satisfaction, and performance of lecturers in the context of private institutions. 3. Results and Discussions Analytical steps include construct validity testing (AVE, CR, and Cronbach's α), analysis of relationships between latent variables, hypothesis testing, and model fit assessment (SRMR, Chi-Square, and NFI). Multicollinearity and residual distribution checks were conducted to ensure inferential validity. Internal validity was obtained from adequate construct reliability testing, while external validity was maintained through sample distribution that represented the characteristics of institutions and academic staff in the study area. Table 4 Descriptive statistics Item Mean Standard Deviation Excess Kurtosis Skewness PER1 0,964 0,410 -0,571 -0,145 PER2 1,198 0,541 -0,571 0,145 CMP1 2,649 0,855 -0,094 0,184 CMP2 1,735 0,511 0,420 0,217 CMP3 1,407 0,583 -0,565 -0,209 PC1 1,814 0,668 -0,479 0,068 PC2 2,446 0,703 0,397 0,178 PC3 2,046 0,786 -0,282 0,019 PC4 2,274 0,790 -0,173 0,052 JS1 1,359 0,536 -0,012 -0,162 JS2 1,789 0,707 -0,380 0,074 JS3 2,268 0,741 -0,079 0,097 PMC1 1,892 0,830 0,093 -0,235 PMC2 1,743 0,620 -0,573 0,111 PMC3 1,808 0,600 -0,128 0,043 PMC4 1,576 0,660 -0,250 -0,163 Source: Data Analysis using Smart-PLS, 2025 Table 4 shows the distribution of mean values and standard deviations for each construct indicator. The competency indicators (CMP1–CMP3) have the highest mean values, with CMP1 at 2.649 and PC2 at 2.446 for protean career orientation, indicating that respondents are relatively active in planning their careers and understanding their professional goals. Meanwhile, indicators such as PER1 (0.964) and PER2 (1.198) show lower variation but still reflect a tendency toward personal values and initiative as forms of protean personality. Skewness and kurtosis ranging from − 0.573 to 0.420 indicate that the data distribution is relatively normal and not extreme, making it suitable for further valid analysis. Table 5 Average extracted variance, composite reliability, and Cronbach's α statistics. Constructs Items Loadings AVE CR CA Personality PER1 0,912 0,770 0,870 0,706 PER2 0,841 Competency CMP1 0,519 0,556 0,783 0,580 CMP2 0,859 CMP3 0,813 Protean Career PC1 0,744 0,455 0,768 0,622 PC2 0,712 PC3 0,619 PC4 0,613 0,554 0,787 0,614 Job Satisfaction JS1 0,844 JS2 0,707 JS3 0,671 Performance PMC1 0,558 0,533 0,818 0,705 PMC2 0,785 PMC3 0,800 PMC4 0,752 Notes: AVE: Average Variance Extracted, CR: Composite Reliability, CA: Cronbach's Alpha. Source: Data Analysis using Smart-PLS, 2025 Table 5 confirms the reliability and validity of the constructs through Composite Reliability (CR), Cronbach’s Alpha (CA), and Average Variance Extracted (AVE) values. All constructs show CR values above the minimum threshold of 0.7 and CA values ranging from 0.58 to 0.87, indicating adequate internal consistency of the instrument. Convergent validity was also achieved, with AVE values mostly above 0.5, except for protean career (0.455), which is still within the tolerance limit based on PLS-SEM literature for constructs with reflective indicators. These results reinforce that the instrument used can be trusted to measure the latent variables under study accurately and consistently. Table 6 Correlation matrix with the square root of AVE on the diagonal PER CMP PC JS PMC PER 0,877 CMP 0,247 0,746 PC 0,231 0,301 0,674 JS 0,190 0,236 0,194 0,745 PMC 0,283 0,367 0,449 0,400 0,730 Source: Data Analysis using Smart-PLS, 2025 Table 6 presents the correlation matrix between the main constructs—Personality (PER), Competency (CMP), Protean Career (PC), Job Satisfaction (JS), and Performance (PMC)—with the square root of the Average Variance Extracted (AVE) values displayed diagonally as indicators of discriminant validity. The AVE values for each construct are above the inter-construct correlations (Agarwal, 2011 ), such as PER (0.877) being greater than its correlation with other constructs, indicating that each construct is more correlated with its own indicators than with other constructs. The highest correlations were found between Protean Career and Performance (0.449) and between Competency and Performance (0.367), indicating a theoretically strong relationship. These results support the discriminant validity of the model and strengthen the conceptual structure that each construct has distinct differences and specific roles in explaining academic performance variables. Table 7 Average extracted variance, composite reliability, and Cronbach's α statistics. Constructs Items Loadings AVE CR CA Personality PER1 0,912 0,770 0,870 0,706 PER2 0,841 Competency CMP1 0,519 0,556 0,783 0,580 CMP2 0,859 CMP3 0,813 Protean Career PC1 0,744 0,455 0,768 0,622 PC2 0,712 PC3 0,619 PC4 0,613 0,554 0,787 0,614 Job Satisfaction JS1 0,844 JS2 0,707 JS3 0,671 Performance PMC1 0,558 0,533 0,818 0,705 PMC2 0,785 PMC3 0,800 PMC4 0,752 Notes: AVE: Average Variance Extracted, CR: Composite Reliability, CA: Cronbach's Alpha. Source: Data Analysis using Smart-PLS, 2025 Table 7 reaffirms the evaluation of construct reliability and validity through three main indicators: AVE, CR, and CA. The Personality construct shows strong reliability with a CA of 0.706 and a CR of 0.870, accompanied by a high AVE (0.770), indicating consistency and the construct's ability to explain the variance of its indicators (Lawelai et al., 2024 ). The Competency construct also demonstrates good convergent validity with an AVE of 0.556 and adequate internal reliability (CA = 0.580; CR = 0.783). Meanwhile, the Protean Career construct consists of two groups of indicators (PC1–PC4 and PC2–PC4), each with AVE close to the minimum threshold (0.455 and 0.554), but CR and CA remain within the acceptable reliability threshold. The Job Satisfaction and Performance constructs demonstrate solid measurement performance, with AVE values of 0.745 and 0.533, respectively, and composite reliability above 0.8. This reinforces that each construct exhibits consistency and accuracy in measurement and can be used for valid structural model analysis and replicated in future research. Table 8 Model fit Indicators Saturated Model Estimated Model SRMR 0,103 0,109 d_ULS 1,438 1,608 d_G 0,423 0,440 Chi-Square 621,645 631,313 NFI 0,413 0,404 Source : Data Analysis using Smart-PLS, 2025 Table 8 presents the model fit indicators to test the suitability of the research model structure to the collected empirical data. The SRMR (Standardized Root Mean Square Residual) value of 0.103 for the saturated model and 0.109 for the estimated model is still within the tolerance limit of < 0.110, indicating that there is sufficient fit between the theoretical model and the observed data. The NFI (Normed Fit Index) values of 0.413 and 0.404 indicate moderate fit, considering the complexity of the variables and sample size. Additionally, the d_ULS and d_G values of 1.438 and 0.423 for the saturated model indicate non-extreme model deviation from actual data. Although the Chi-Square values are quite high (621.645 and 631.313), this is common in models with many indicators and does not directly indicate model rejection in the PLS-SEM approach. This suggests that the model structure is acceptable and can be used for hypothesis testing, with statistical adequacy supporting internal validity in further interpretation. After ensuring adequate validity and reliability, the researchers tested the proposed research model using the Partial Least Squares (PLS) method. Figure 1 shows the structural relationship between six latent constructs: personality, competitiveness, competence, protean career, job satisfaction, and performance. The influence paths between constructs are clearly visualized through the coefficient values displayed above the connecting arrows, as well as the R Square values on the dependent constructs (Marzuki, Lawelai, Sadat, & Nastia, 2022 ; Wilkes & Karimi, 2025 ). An R² value of 0.325 for performance indicates that 32.5% of the variation in lecturer performance can be explained by job satisfaction and protean career together. Meanwhile, the R² value for job satisfaction is 0.242, indicating the simultaneous contribution of personality and competence. The highest path coefficients are recorded between protean career and performance (β = 0.394) and between job satisfaction and performance (β = 0.325), supporting the positive direction of the relationships proposed in the hypotheses. Table 9 Summary of results Hypothesis Coefficients STDEV P Values Results Personality has a positive impact on protean career 0,171 0,062 0,008 Accepted Personality has a positive impact on job satisfaction 0,149 0,070 0,045 Accepted Competitiveness has a positive impact on protean career 0,271 0,062 0,000 Accepted Competency has a positive impact on job satisfaction 0,203 0,072 0,005 Accepted Protean careers have a positive impact on performance 0,394 0,060 0,000 Accepted Job satisfaction has a positive impact on performance 0,325 0,064 0,000 Accepted Source: Data Analysis using Smart-PLS, 2025 Table 9 summarizes the results of testing six main hypotheses in the structural model, showing path coefficients, standard deviation values, significance values (p-values), and hypothesis acceptance status. All hypotheses were accepted , with p-values < 0.05 for each relationship, indicating strong statistical significance. The highest influence was observed between protean career and performance (β = 0.394; p = 0.000), followed by job satisfaction on performance (β = 0.325; p = 0.000), indicating that these two variables are dominant predictors of faculty performance. Meanwhile, competitiveness also showed a substantial influence on protean career (β = 0.271; p = 0.000). These findings reinforce the theoretical argument in the study that personality factors, competence, and job satisfaction play an important role in developing adaptive careers and enhancing professional output (Farla, Perizade, Zunaidah, & Andriana, 2024 ) among lecturers at private universities. The results of this study indicate that all hypotheses proposed can be accepted statistically, meaning that personality, competitiveness, and competence significantly influence protean career orientation, job satisfaction, and performance of lecturers in private universities. These findings support the principle that careers that are independent and flexible tend to thrive in dynamic academic environments, especially when supported by proactive personal characteristics and relevant competencies (Rincón-Moreno & Ramírez-Garzón, 2024 ; Rincón Moreno, 2024 ). The highest path coefficients between protean career and performance (β = 0.394) and between job satisfaction and performance (β = 0.325) reinforce that these two variables are important indicators in explaining academic productivity. Most results align with previous studies e.g. (Herrmann et al., 2015 ; Sultana & Malik, 2019 ; Tee et al., 2022 ) though there are minor exceptions in the protean career construct, which shows a low AVE value (0.455), indicating that its indicators are not fully convergent. This may be due to varying perceptions of the concept of “career autonomy” that have not yet been fully internalized among private university lecturers. Additionally, the correlation between personality and job satisfaction is relatively weak (r = 0.190), suggesting that personal characteristics may not be the primary determinant of satisfaction but are more influenced by environmental factors such as recognition and work relationships. Theoretically, this study enriches the approach to human resource management based on autonomous behavior and personal values. Protean careers are proven to be not merely individual preferences, but institutional strategies that can improve lecturer retention, productivity, and institutional competitiveness (Murugappan & Priya Durga, 2015 ; Rincón-Moreno & Ramírez-Garzón, 2024 ). The practical implication is the need for a more flexible career development system, with a focus on mentoring, competency strengthening, and recognition of faculty personality as part of talent management. This is particularly relevant in the private higher education ecosystem, which faces structural pressures and career system fluctuations (Teixeira, Rocha, Biscaia, & Cardoso, 2014 ; Wheaton, 2020 ). The limitations of this study include the concentration of data only in Region IX Sulawesi and the measurement of protean career constructs, which can be further refined with additional more contextual indicators. Alternative explanations, such as the role of organizational culture or differences in academic generations, may influence the strength of the relationships between variables and need to be explored in further studies. Nevertheless, the strong internal validity and stable model structure provide a foundation for generalizing these findings to other private institutions in Indonesia with similar characteristics. Further studies are recommended to test this model in cross-regional settings and with a longitudinal approach to understand the dynamics of faculty careers over time. 4. Conclusions Based on the results and discussions, this study proves that personality, competence, and competitiveness have a positive contribution to protean career development, job satisfaction, and performance of lecturers in private universities. Protean career is proven to be a strong mediator between individual characteristics and academic achievement, with significant support from job satisfaction as a determining factor. All hypotheses were statistically accepted, indicating that autonomous and personal value-based career approaches are increasingly relevant in dynamic and structurally constrained academic environments. The main implication of these findings is that academic human resource management needs to shift to a more flexible and adaptive career personalization system. The most common claim supported by evidence is that individuals with a proactive character and high interpersonal competencies are better prepared to cope with institutional pressures through protean career strategies. The future perspective of this work encourages the development of institutional policies based on sustainable talent management, as well as the strengthening of mentoring and professional development programs that support faculty competitiveness and retention in the digital work era. Declarations Clinical trial number: Not applicable. Corresponding author: Sukriadi ( [email protected] ) Consent to Publish Not applicable. Consent to Participate All participants were informed about the purpose of the study, the voluntary nature of their participation, and their right to withdraw at any time without penalty. Informed consent was obtained electronically prior to completing the questionnaire. Written informed consent was obtained from respondents who participated in the offline survey. All responses were collected anonymously, and no participant was under the age of 16. Ethics Approval This study was reviewed and approved by the Ethics Committee of Universitas Lamappapoleonro (Approval No.: UL-ETIK/2025/07–021). All procedures were conducted in accordance with institutional guidelines and the ethical standards of the 1964 Helsinki Declaration and its subsequent amendments. Competing Interests The authors declare no competing interests. 5 Funding This research received no external funding. Author Contribution Author Contributions StatementA.A. (Asmini) conceived the research idea, designed the study framework, and led the manuscript preparation.A.Adw. (Andi Adawiah) contributed to the development of the theoretical model and conducted the literature review.S. (Sukriadi) performed the data analysis using SmartPLS, interpreted the statistical results, and revised the methodology section.A.M.Y. (Andi Muhammad Yusuf) assisted with data collection, validation, and the preparation of tables and figures.All authors contributed to the discussion, reviewed the results, and approved the final version of the manuscript. Acknowledgement The authors would like to express their sincere gratitude to the Higher Education Service Institution Region IX Sulawesi (LLDIKTI IX) for providing access to institutional data and supporting coordination with private universities during the data collection process. We also thank the participating lecturers for their valuable time and contributions in completing the survey. Data Availability The datasets generated and analyzed during this study are not publicly available due to institutional data protection regulations but are available from the corresponding author on reasonable request. References Agarwal, N. K. 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Developing professional lecturers in higher education: Case study in private colleges. International Journal of Innovation, Creativity and Change , 10 (11), 275–283. Retrieved from https://www.ijicc.net/images/vol11iss1/11126_Rifa_2020_E_R.pdf Permana, A., Aima, M. H., Ariyanto, E., Nurmahdi, A., Sutawidjaya, A. H., & Endri, E. (2021). The effect of compensation and career development on lecturer job satisfaction. Accounting , 7 (6), 1287–1292. https://doi.org/10.5267/j.ac.2021.4.011 Ramasamy, A., Inore, I., Muduli, K., & Singh, S. (2023). Evaluation of Factors Affecting Job Satisfaction Pathways for Improved Sustainable Business Performance in Emerging Economies. International Journal of Social Ecology and Sustainable Development , 14 (1), 1–17. https://doi.org/10.4018/IJSESD.328217 Redondo, R., Sparrow, P., & Hernández-Lechuga, G. (2021). 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Jurnal Ilmiah Peuradeun , 12 (1), 249–272. https://doi.org/10.26811/peuradeun.v12i1.1078 Samsuri, Notosudjono, D., & Sunaryo, W. (2024). The Impact of Organizational Culture, Transformational Leadership and Job Satisfaction on the Performance of Private University Lecturers. Journal of Ecohumanism , 3 (7), 1434–1445. https://doi.org/10.62754/joe.v3i7.4305 Sern, M. L. C., Ho, J. A., Sambasivan, M., & Yee, W. F. (2014). The influence of demographic variables on lecturers’ protean careers orientation. International Journal of Economics and Management , 8 (Specialissue), 25–42. Retrieved from http://www.ijem.upm.edu.my/vol8noS/bab02.pdf Sinniah, S., Mohamed, R. K. M. H., Mior, W. R., Harith, A., Izni, W. N., & Rawshdeh, Z. A. (2019). Talent retention in private universities of Malaysia. International Journal of Engineering and Advanced Technology , 8 (6 Special Issue 3), 233–239. https://doi.org/10.35940/ijeat.F1038.0986S319 Steel, P., Schmidt, J., Bosco, F., & Uggerslev, K. (2019). The effects of personality on job satisfaction and life satisfaction: A meta-analytic investigation accounting for bandwidth–fidelity and commensurability. Human Relations , 72 (2), 217–247. https://doi.org/10.1177/0018726718771465 Sultana, R., & Malik, O. F. (2019). Is protean career attitude beneficial for both employees and organizations? Investigating the mediating effects of knowing career competencies. Frontiers in Psychology , 10 (JUN). https://doi.org/10.3389/fpsyg.2019.01284 Suparjo. (2017). Professional competence and service innovation in higher education institutions in Central Java, Indonesia. European Research Studies Journal , 20 (4), 622–636. https://doi.org/10.35808/ersj/916 Tee, P. K., Cham, T. H., Low, M. P., & Lau, T. C. (2022). The role of perceived employability in the relationship between protean career attitude and career success. Australian Journal of Career Development , 31 (1), 66–76. https://doi.org/10.1177/10384162211021940 Teixeira, P. N., Rocha, V., Biscaia, R., & Cardoso, M. F. (2014). Revenue diversification in public higher education: Comparing the university and polytechnic sectors. Public Administration Review , 74 (3), 398–412. https://doi.org/10.1111/puar.12215 Thasimmim, S. N., Johannes, J., Yacob, S., & Junaidi, J. (2025). Effect of Contingency Leadership, Competence, and Personality Traits on the Productivity of Permanent Lecturers of Private Universities Mediated by Compensation. Insight , (13), 195–239. https://doi.org/10.32999/2663-970X/2025-13-9 Wheaton, A. (2020). Shift happens; moving from the ivory tower to the mushroom factory. Higher Education Research and Development , 39 (1), 67–80. https://doi.org/10.1080/07294360.2019.1670145 Wilkes, R., & Karimi, A. (2025). Visualizing Social Theory with Embedded Relational Diagrams: Theoretical Illustration, Development, and Innovation. American Sociologist . https://doi.org/10.1007/s12108-025-09651-9 Zhu, L., & Gao, Y. (2024). Protean career orientation, supervisor perceptions and organizational career growth: a moderated mediation model. Current Psychology , 43 (10), 8913–8930. https://doi.org/10.1007/s12144-023-05021-1 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8043063","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":554096386,"identity":"9f0e79da-c7be-4583-b55c-85d4573fdf62","order_by":0,"name":"Asmini Asmini","email":"","orcid":"","institution":"Universitas Lamappapoleonro","correspondingAuthor":false,"prefix":"","firstName":"Asmini","middleName":"","lastName":"Asmini","suffix":""},{"id":554096387,"identity":"163f2221-6cf3-47f4-a4ac-b67663594483","order_by":1,"name":"Andi Adawiah","email":"","orcid":"","institution":"Universitas 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10:02:14","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140133,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8043063/v1/2eceba2ffc7d9dbd92a18152.html"},{"id":97429941,"identity":"480f3d28-7d71-4529-af3d-baf7a5ec8081","added_by":"auto","created_at":"2025-12-04 10:02:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38484,"visible":true,"origin":"","legend":"\u003cp\u003eStructural model (path coefficient)\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8043063/v1/f632056b22853b029bef8020.png"},{"id":105022048,"identity":"03c9bb7d-b434-4c1f-b6d0-24983d086eb5","added_by":"auto","created_at":"2026-03-20 03:10:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1027914,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8043063/v1/1105bd0f-7118-4f57-8925-329b057b8024.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Protean Career on Job Satisfaction and Performance of Lecturers at Private Universities","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn an era of rapid institutional change and increasingly complex professional demands, lecturers at private universities face pressure to adapt independently in managing their career development. Protean career orientation, which emphasizes autonomy and personal values in career decision-making, is a strategic approach that can significantly improve job satisfaction and academic performance (Bazine, Pe\u0026ntilde;a-Jimenez, \u0026amp; D\u0026eacute;prez, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the context of institutional management, a deep understanding of the impact of protean career orientation offers opportunities for the formulation of more adaptive, competitive, and sustainable human resource management policies (Sinniah et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tee, Cham, Low, \u0026amp; Lau, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thasimmim, Johannes, Yacob, \u0026amp; Junaidi, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eProtean career orientation has become an increasingly prominent self-directed approach in competitive and institutionally unstable higher education environments. A values-based and independent approach to career planning enables faculty members to achieve higher job satisfaction and demonstrate optimal academic performance (Herrmann, Hirschi, \u0026amp; Baruch, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Redondo, Sparrow, \u0026amp; Hern\u0026aacute;ndez-Lechuga, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Studies indicate that proactive behavior influenced by protean orientation can enhance productivity and organizational commitment while reducing intentions to leave the institution (Bazine et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hollywood, McCarthy, Spencely, \u0026amp; Winstone, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This is particularly relevant for faculty members at private universities, who often face structural challenges and career development that is not systematically institutionalized.\u003c/p\u003e\u003cp\u003ePrevious studies have shown that protean career orientation has a positive effect on job satisfaction and performance of lecturers, both directly and through the mediation of career competence and employability perceptions (Herrmann et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Institutional factors such as compensation, career development, organizational culture, leadership style, and work relationships also play a role in strengthening these effects (Permana et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Samsuri, Notosudjono, \u0026amp; Sunaryo, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Suparjo, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). However, few studies have empirically focused on the population of lecturers in private universities in Indonesia or comprehensively examined the interaction between demographic factors and protean orientation (Sern, Ho, Sambasivan, \u0026amp; Yee, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), making this study relevant and filling an important gap in the literature.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe Condition of Private Higher Education Institutions in Region IX Sulawesi.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCondition of Private Higher Education Institutions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSouth\u003c/p\u003e\u003cp\u003eSulawesi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSoutheast\u003c/p\u003e\u003cp\u003eSulawesi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWest\u003c/p\u003e\u003cp\u003eSulawesi\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eNumber of institutions: 1.210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e677\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInstitute\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCollege\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e288\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcademy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePolytechnic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCommunity Academy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eAcademic Positions totalling 13.570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior Lecturer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1,027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e618\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5528\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLecturer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.366\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssistant Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3024\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e684\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProfessor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Report of the Higher Education Service Agency Region IX Sulawesi, 2021\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e reveals the highly heterogeneous landscape of private higher education institutions in Region IX Sulawesi, with a total of 1,210 institutions spread across three provinces: South Sulawesi, Southeast Sulawesi, and West Sulawesi. The composition of institutions includes universities, institutes, colleges, academies, polytechnics, and community academies, reflecting the diversity of organizational structures and educational orientations. In terms of human resources, there are 13,570 faculty members, with the majority holding junior academic positions such as junior lecturers and lecturers, while the number of professors remains very limited (only 111). This disparity in the distribution of academic positions highlights challenges in faculty career development, particularly at private higher education institutions, which is the primary focus of this study.\u003c/p\u003e\u003cp\u003eA solution is for institutions to develop career autonomy-based professional development programs, strengthen mentoring, and increase job autonomy to support lecturers' independent career adaptation (Riza et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhu \u0026amp; Gao, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, protean orientation contributes to higher employability and career success, particularly in dynamic and structurally constrained organizational environments (Nurmilah, Bafadal, Ery Tri, Imron, \u0026amp; Muslim, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, protean careers are not merely an individual approach but also a sustainable institutional strategy to enhance the competitiveness and retention of academic human resources.\u003c/p\u003e\u003cp\u003eTherefore, it is important to comprehensively examine the relationship between personality and competitiveness toward protean careers. On the other hand, the literature indicates that job satisfaction is influenced by various competencies, including communicative, technical, and interpersonal competencies (Carter, Murray, \u0026amp; Gray, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; De Grip, Sieben, \u0026amp; Stevens, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), as well as personality traits such as agreeableness and emotional stability (Kang \u0026amp; Malvaso, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Steel, Schmidt, Bosco, \u0026amp; Uggerslev, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Protean career itself has been proven to positively contribute to work performance, particularly through increased adaptability, employability, and self-management (Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, the relationship between job satisfaction and performance has been identified as positive, although moderated by factors such as organizational climate and reward systems (Idris, Adi, Soetjipto, \u0026amp; Supriyanto, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ramasamy, Inore, Muduli, \u0026amp; Singh, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Based on these findings, the following six hypotheses are proposed:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePersonality has a positive impact on protean career\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePersonality has a positive impact on job satisfaction\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCompetitiveness has a positive impact on protean career\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCompetence has a positive impact on job satisfaction\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eProtean career has a positive impact on performance\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eJob satisfaction has a positive impact on performance\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThe objectives and novelty of this study are to empirically identify the influence of personality, competitiveness, and competence on protean career, job satisfaction, and performance of lecturers in private universities, which have not been comprehensively explained in an integrated model. The most common claim supported by evidence is that proactive personality, interpersonal competence, and a competitive environment positively contribute to independent career orientation, job satisfaction, and academic performance outcomes. The future perspective of this work is the development of a talent management system based on career personalization and adaptive flexibility, which can serve as the basis for institutional policies to promote the sustainability of academic human resources in the dynamic and digital work era.\u003c/p\u003e"},{"header":"2. Research Method","content":"\u003cp\u003eThis study used a structured survey method conducted through online and offline channels to collect data from private university lecturers in Region IX Sulawesi. This dual approach ensured inclusion across geographical and technological boundaries while taking into account institutional differences in digital access and engagement. The online survey utilized platforms such as WhatsApp and institutional email lists to reach tech-savvy respondents (Lawelai, Sadat, \u0026amp; Harakan, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and the offline survey was conducted in collaboration with academic units and administrative offices to capture a variety of academic profiles and positions. This strategy ensured balanced participation and better representation, as seen in the demographic breakdown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDemographic information of respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eRespondents\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;246\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e139\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56,50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e43,50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40,65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59,35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaster's degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e79,67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDoctoral degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20,33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eAcademic Position\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLecturer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e17,48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssistant Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41,46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate Professor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30,89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProfessor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10,16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eRank Classification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIIIa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e11,38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIIIb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21,54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIIIc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18,29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIIId\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7,32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIVa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15,45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIVb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14,23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIVc\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4,88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIVd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2,44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIVe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4,47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: Primary Data Processing, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis study uses a structured survey approach to collect primary data from permanent lecturers working at private universities in Region IX Sulawesi. Respondents were selected using purposive sampling based on academic position, educational level, and geographical distribution covering three provinces: South Sulawesi, Southeast Sulawesi, and West Sulawesi. The total number of respondents was 246, consisting of 56.50% males and 43.50% females, with ages ranging from 24 to 65 years. The instrument used was an electronic questionnaire based on theoretical indicators validated from relevant literature (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), using a five-point Likert scale. Content validation was conducted through expert review and a pilot test with 30 lecturers to ensure the accuracy and reliability of the instrument.\u003c/p\u003e\u003cp\u003eThe questionnaire was distributed online via an e-survey platform during January\u0026ndash;February 2025 and was directly supervised by the research team to ensure proportional regional representation. The collected data were then exported in an encrypted format (.csv) and stored in the institutional repository for academic audit purposes. Analysis was conducted using the SmartPLS 4.0 application with a Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, which is suitable for exploratory models with latent variables and multiple indicators.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMeasurement items and sources\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCode\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMeasurement items\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonality (PER)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you use your personal values to guide your career decisions?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e(Fryczyńska \u0026amp; Pleśniak, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sern et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you take initiative in managing your career development?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetency (CMP)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you have a clear understanding of your career goals and how to achieve them?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e(Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you actively build and maintain professional relationships?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you possess the necessary skills for your current job and future career aspirations?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtean Career (PC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you prioritize your personal values over organizational values in your career?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e(Fryczyńska \u0026amp; Pleśniak, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Sern et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you independently manage your career path and decisions?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you regularly reflect on your career goals and progress?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you engage in networking activities to advance your career?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob Satisfaction (JS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre you satisfied with the nature of your work and tasks?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e(My Dieu, Al Mamun, Nawi, \u0026amp; Muniady, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre you satisfied with your relationships with colleagues?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAre you satisfied with your salary and benefits?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerformance (PMC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you consistently meet or exceed your job performance expectations?\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e(Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Suparjo, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you contribute to innovative practices in your work?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you demonstrate high levels of professional competence in your role?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDo you engage in continuous learning and development within your organization?\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eSource: Fryczyńska \u0026amp; Pleśniak (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) etc.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e were developed based on theoretical constructs and adapted from previous studies relevant to the field of human resource management and academic careers. For example, indicators PER1 and PER2 represent the protean personality dimension, which focuses on the use of personal values and initiative in career decision-making, adapted from Fryczyńska \u0026amp; Pleśniak (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and Sern et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Indicators CMP1\u0026ndash;CMP3 reflect career competencies in the form of goal clarity, professional networking, and work skills based on constructs from Sultana \u0026amp; Malik (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The protean career orientation dimension is measured through four indicators, PC1\u0026ndash;PC4, which include autonomy in career decisions, career reflection, and networking activities. Meanwhile, job satisfaction and performance are measured through indicators from My Dieu et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Suparjo (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and Sultana \u0026amp; Malik (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), focusing on satisfaction with tasks, coworkers, compensation, as well as contributions to innovation and professional competence. By adopting and adapting constructs from various scientific literatures, the development of indicators in this instrument aims to ensure conceptual validity and enable a comprehensive evaluation of the contribution of each variable to protean career, job satisfaction, and performance of lecturers in the context of private institutions.\u003c/p\u003e"},{"header":"3. Results and Discussions","content":"\u003cp\u003eAnalytical steps include construct validity testing (AVE, CR, and Cronbach's α), analysis of relationships between latent variables, hypothesis testing, and model fit assessment (SRMR, Chi-Square, and NFI). Multicollinearity and residual distribution checks were conducted to ensure inferential validity. Internal validity was obtained from adequate construct reliability testing, while external validity was maintained through sample distribution that represented the characteristics of institutions and academic staff in the study area.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItem\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExcess Kurtosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSkewness\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,964\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,410\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0,145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,571\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCMP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,855\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,184\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCMP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,420\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,217\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCMP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,583\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,565\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0,209\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,668\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,703\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,397\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,786\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,790\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,052\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,359\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,536\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0,162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,380\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,074\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,097\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0,093\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0,235\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,743\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,808\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0,043\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,576\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0,250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0,163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSource: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the distribution of mean values and standard deviations for each construct indicator. The competency indicators (CMP1\u0026ndash;CMP3) have the highest mean values, with CMP1 at 2.649 and PC2 at 2.446 for protean career orientation, indicating that respondents are relatively active in planning their careers and understanding their professional goals. Meanwhile, indicators such as PER1 (0.964) and PER2 (1.198) show lower variation but still reflect a tendency toward personal values and initiative as forms of protean personality. Skewness and kurtosis ranging from \u0026minus;\u0026thinsp;0.573 to 0.420 indicate that the data distribution is relatively normal and not extreme, making it suitable for further valid analysis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAverage extracted variance, composite reliability, and Cronbach's α statistics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstructs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLoadings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAVE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,706\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,580\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtean Career\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,622\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,614\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob Satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerformance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: AVE: Average Variance Extracted, CR: Composite Reliability, CA: Cronbach's Alpha.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e confirms the reliability and validity of the constructs through Composite Reliability (CR), Cronbach\u0026rsquo;s Alpha (CA), and Average Variance Extracted (AVE) values. All constructs show CR values above the minimum threshold of 0.7 and CA values ranging from 0.58 to 0.87, indicating adequate internal consistency of the instrument. Convergent validity was also achieved, with AVE values mostly above 0.5, except for protean career (0.455), which is still within the tolerance limit based on PLS-SEM literature for constructs with reflective indicators. These results reinforce that the instrument used can be trusted to measure the latent variables under study accurately and consistently.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation matrix with the square root of AVE on the diagonal\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCMP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eJS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePMC\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePER\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,877\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCMP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,746\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eJS\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePMC\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,730\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the correlation matrix between the main constructs\u0026mdash;Personality (PER), Competency (CMP), Protean Career (PC), Job Satisfaction (JS), and Performance (PMC)\u0026mdash;with the square root of the Average Variance Extracted (AVE) values displayed diagonally as indicators of discriminant validity. The AVE values for each construct are above the inter-construct correlations (Agarwal, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), such as PER (0.877) being greater than its correlation with other constructs, indicating that each construct is more correlated with its own indicators than with other constructs. The highest correlations were found between Protean Career and Performance (0.449) and between Competency and Performance (0.367), indicating a theoretically strong relationship. These results support the discriminant validity of the model and strengthen the conceptual structure that each construct has distinct differences and specific roles in explaining academic performance variables.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAverage extracted variance, composite reliability, and Cronbach's α statistics.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstructs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLoadings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAVE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCA\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,912\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,706\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePER2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,841\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetency\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,519\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,783\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,580\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,859\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCMP3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,813\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtean Career\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,622\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,614\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob Satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,707\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,671\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerformance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,533\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0,818\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0,705\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,800\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePMC4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNotes: AVE: Average Variance Extracted, CR: Composite Reliability, CA: Cronbach's Alpha.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSource: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e reaffirms the evaluation of construct reliability and validity through three main indicators: AVE, CR, and CA. The Personality construct shows strong reliability with a CA of 0.706 and a CR of 0.870, accompanied by a high AVE (0.770), indicating consistency and the construct's ability to explain the variance of its indicators (Lawelai et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The Competency construct also demonstrates good convergent validity with an AVE of 0.556 and adequate internal reliability (CA\u0026thinsp;=\u0026thinsp;0.580; CR\u0026thinsp;=\u0026thinsp;0.783). Meanwhile, the Protean Career construct consists of two groups of indicators (PC1\u0026ndash;PC4 and PC2\u0026ndash;PC4), each with AVE close to the minimum threshold (0.455 and 0.554), but CR and CA remain within the acceptable reliability threshold. The Job Satisfaction and Performance constructs demonstrate solid measurement performance, with AVE values of 0.745 and 0.533, respectively, and composite reliability above 0.8. This reinforces that each construct exhibits consistency and accuracy in measurement and can be used for valid structural model analysis and replicated in future research.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModel fit\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndicators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSaturated Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimated Model\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSRMR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,109\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ed_ULS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,608\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ed_G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,440\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChi-Square\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e621,645\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e631,313\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNFI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,413\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,404\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource\u003c/b\u003e: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e presents the model fit indicators to test the suitability of the research model structure to the collected empirical data. The SRMR (Standardized Root Mean Square Residual) value of 0.103 for the saturated model and 0.109 for the estimated model is still within the tolerance limit of \u0026lt;\u0026thinsp;0.110, indicating that there is sufficient fit between the theoretical model and the observed data. The NFI (Normed Fit Index) values of 0.413 and 0.404 indicate moderate fit, considering the complexity of the variables and sample size. Additionally, the \u003cem\u003ed_ULS\u003c/em\u003e and \u003cem\u003ed_G\u003c/em\u003e values of 1.438 and 0.423 for the saturated model indicate non-extreme model deviation from actual data. Although the Chi-Square values are quite high (621.645 and 631.313), this is common in models with many indicators and does not directly indicate model rejection in the PLS-SEM approach. This suggests that the model structure is acceptable and can be used for hypothesis testing, with statistical adequacy supporting internal validity in further interpretation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAfter ensuring adequate validity and reliability, the researchers tested the proposed research model using the Partial Least Squares (PLS) method. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the structural relationship between six latent constructs: personality, competitiveness, competence, protean career, job satisfaction, and performance. The influence paths between constructs are clearly visualized through the coefficient values displayed above the connecting arrows, as well as the R Square values on the dependent constructs (Marzuki, Lawelai, Sadat, \u0026amp; Nastia, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wilkes \u0026amp; Karimi, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). An R\u0026sup2; value of 0.325 for performance indicates that 32.5% of the variation in lecturer performance can be explained by job satisfaction and protean career together. Meanwhile, the R\u0026sup2; value for job satisfaction is 0.242, indicating the simultaneous contribution of personality and competence. The highest path coefficients are recorded between protean career and performance (β\u0026thinsp;=\u0026thinsp;0.394) and between job satisfaction and performance (β\u0026thinsp;=\u0026thinsp;0.325), supporting the positive direction of the relationships proposed in the hypotheses.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCoefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSTDEV\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP Values\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eResults\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonality has a positive impact on protean career\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePersonality has a positive impact on job satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetitiveness has a positive impact on protean career\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCompetency has a positive impact on job satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtean careers have a positive impact on performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,394\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob satisfaction has a positive impact on performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0,325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0,064\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAccepted\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSource: Data Analysis using Smart-PLS, 2025\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e summarizes the results of testing six main hypotheses in the structural model, showing path coefficients, standard deviation values, significance values (p-values), and hypothesis acceptance status. All hypotheses were \u003cb\u003eaccepted\u003c/b\u003e, with p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for each relationship, indicating strong statistical significance. The highest influence was observed between protean career and performance (β\u0026thinsp;=\u0026thinsp;0.394; p\u0026thinsp;=\u0026thinsp;0.000), followed by job satisfaction on performance (β\u0026thinsp;=\u0026thinsp;0.325; p\u0026thinsp;=\u0026thinsp;0.000), indicating that these two variables are dominant predictors of faculty performance. Meanwhile, competitiveness also showed a substantial influence on protean career (β\u0026thinsp;=\u0026thinsp;0.271; p\u0026thinsp;=\u0026thinsp;0.000). These findings reinforce the theoretical argument in the study that personality factors, competence, and job satisfaction play an important role in developing adaptive careers and enhancing professional output (Farla, Perizade, Zunaidah, \u0026amp; Andriana, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) among lecturers at private universities.\u003c/p\u003e\u003cp\u003eThe results of this study indicate that all hypotheses proposed can be accepted statistically, meaning that personality, competitiveness, and competence significantly influence protean career orientation, job satisfaction, and performance of lecturers in private universities. These findings support the principle that careers that are independent and flexible tend to thrive in dynamic academic environments, especially when supported by proactive personal characteristics and relevant competencies (Rinc\u0026oacute;n-Moreno \u0026amp; Ram\u0026iacute;rez-Garz\u0026oacute;n, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Rinc\u0026oacute;n Moreno, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The highest path coefficients between protean career and performance (β\u0026thinsp;=\u0026thinsp;0.394) and between job satisfaction and performance (β\u0026thinsp;=\u0026thinsp;0.325) reinforce that these two variables are important indicators in explaining academic productivity.\u003c/p\u003e\u003cp\u003eMost results align with previous studies e.g. (Herrmann et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sultana \u0026amp; Malik, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) though there are minor exceptions in the protean career construct, which shows a low AVE value (0.455), indicating that its indicators are not fully convergent. This may be due to varying perceptions of the concept of \u0026ldquo;career autonomy\u0026rdquo; that have not yet been fully internalized among private university lecturers. Additionally, the correlation between personality and job satisfaction is relatively weak (r\u0026thinsp;=\u0026thinsp;0.190), suggesting that personal characteristics may not be the primary determinant of satisfaction but are more influenced by environmental factors such as recognition and work relationships.\u003c/p\u003e\u003cp\u003eTheoretically, this study enriches the approach to human resource management based on autonomous behavior and personal values. Protean careers are proven to be not merely individual preferences, but institutional strategies that can improve lecturer retention, productivity, and institutional competitiveness (Murugappan \u0026amp; Priya Durga, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rinc\u0026oacute;n-Moreno \u0026amp; Ram\u0026iacute;rez-Garz\u0026oacute;n, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The practical implication is the need for a more flexible career development system, with a focus on mentoring, competency strengthening, and recognition of faculty personality as part of talent management. This is particularly relevant in the private higher education ecosystem, which faces structural pressures and career system fluctuations (Teixeira, Rocha, Biscaia, \u0026amp; Cardoso, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wheaton, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe limitations of this study include the concentration of data only in Region IX Sulawesi and the measurement of protean career constructs, which can be further refined with additional more contextual indicators. Alternative explanations, such as the role of organizational culture or differences in academic generations, may influence the strength of the relationships between variables and need to be explored in further studies. Nevertheless, the strong internal validity and stable model structure provide a foundation for generalizing these findings to other private institutions in Indonesia with similar characteristics. Further studies are recommended to test this model in cross-regional settings and with a longitudinal approach to understand the dynamics of faculty careers over time.\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eBased on the results and discussions, this study proves that personality, competence, and competitiveness have a positive contribution to protean career development, job satisfaction, and performance of lecturers in private universities. Protean career is proven to be a strong mediator between individual characteristics and academic achievement, with significant support from job satisfaction as a determining factor. All hypotheses were statistically accepted, indicating that autonomous and personal value-based career approaches are increasingly relevant in dynamic and structurally constrained academic environments. The main implication of these findings is that academic human resource management needs to shift to a more flexible and adaptive career personalization system.\u003c/p\u003e\u003cp\u003eThe most common claim supported by evidence is that individuals with a proactive character and high interpersonal competencies are better prepared to cope with institutional pressures through protean career strategies. The future perspective of this work encourages the development of institutional policies based on sustainable talent management, as well as the strengthening of mentoring and professional development programs that support faculty competitiveness and retention in the digital work era.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCorresponding author:\u003c/strong\u003e\u003cp\u003eSukriadi ([email protected])\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConsent to Publish\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003cp\u003eAll participants were informed about the purpose of the study, the voluntary nature of their participation, and their right to withdraw at any time without penalty. Informed consent was obtained electronically prior to completing the questionnaire. Written informed consent was obtained from respondents who participated in the offline survey. All responses were collected anonymously, and no participant was under the age of 16.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of Universitas Lamappapoleonro (Approval No.: UL-ETIK/2025/07\u0026ndash;021). All procedures were conducted in accordance with institutional guidelines and the ethical standards of the 1964 Helsinki Declaration and its subsequent amendments.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003e5 Funding\u003c/h2\u003e\u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions StatementA.A. (Asmini) conceived the research idea, designed the study framework, and led the manuscript preparation.A.Adw. (Andi Adawiah) contributed to the development of the theoretical model and conducted the literature review.S. (Sukriadi) performed the data analysis using SmartPLS, interpreted the statistical results, and revised the methodology section.A.M.Y. (Andi Muhammad Yusuf) assisted with data collection, validation, and the preparation of tables and figures.All authors contributed to the discussion, reviewed the results, and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to express their sincere gratitude to the Higher Education Service Institution Region IX Sulawesi (LLDIKTI IX) for providing access to institutional data and supporting coordination with private universities during the data collection process. We also thank the participating lecturers for their valuable time and contributions in completing the survey.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed during this study are not publicly available due to institutional data protection regulations but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAgarwal, N. K. (2011). Verifying survey items for construct validity: A two-stage sorting procedure for questionnaire design in information behavior research. \u003cem\u003eProceedings of the ASIST Annual Meeting\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(1), 1–8. https://doi.org/10.1002/meet.2011.14504801166\u003c/p\u003e\n\u003cp\u003eBazine, N., Peña-Jimenez, M., \u0026amp; Déprez, G. R. M. (2023). 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Effect of Contingency Leadership, Competence, and Personality Traits on the Productivity of Permanent Lecturers of Private Universities Mediated by Compensation. \u003cem\u003eInsight\u003c/em\u003e, (13), 195–239. https://doi.org/10.32999/2663-970X/2025-13-9\u003c/p\u003e\n\u003cp\u003eWheaton, A. (2020). Shift happens; moving from the ivory tower to the mushroom factory. \u003cem\u003eHigher Education Research and Development\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(1), 67–80. https://doi.org/10.1080/07294360.2019.1670145\u003c/p\u003e\n\u003cp\u003eWilkes, R., \u0026amp; Karimi, A. (2025). Visualizing Social Theory with Embedded Relational Diagrams: Theoretical Illustration, Development, and Innovation. \u003cem\u003eAmerican Sociologist \u003c/em\u003e. https://doi.org/10.1007/s12108-025-09651-9\u003c/p\u003e\n\u003cp\u003eZhu, L., \u0026amp; Gao, Y. (2024). Protean career orientation, supervisor perceptions and organizational career growth: a moderated mediation model. \u003cem\u003eCurrent Psychology\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(10), 8913–8930. https://doi.org/10.1007/s12144-023-05021-1\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8043063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8043063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose – This study investigates the effect of personality, competitiveness, and competence on protean career orientation, job satisfaction, and performance of lecturers at private universities. It aims to validate six hypotheses through a structural model that integrates psychological and institutional career determinants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethodology – A quantitative explanatory design was applied using structured surveys distributed online and offline to 246 permanent lecturers across Region IX Sulawesi. Measurement instruments were derived from validated theoretical constructs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFindings – Results reveal that personality and competitiveness positively influence protean career orientation, while personality and competence significantly enhance job satisfaction. Protean career and job satisfaction also show strong predictive effects on lecturer performance, with all hypotheses statistically supported.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOriginality – This study offers a novel framework combining psychological traits and institutional factors to explain academic career trajectories, particularly in the underrepresented context of Indonesian private universities. It contributes actionable insights for talent development policy and strategic academic HR management.\u003c/p\u003e","manuscriptTitle":"The Impact of Protean Career on Job Satisfaction and Performance of Lecturers at Private Universities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 10:02:09","doi":"10.21203/rs.3.rs-8043063/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e3533fb2-d9ec-4d1d-80db-9b895624f6aa","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T03:09:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 10:02:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8043063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8043063","identity":"rs-8043063","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}