Integrating self-efficacy and career anchor: a multi-dimensional model to enhance vocational college students' employment competitiveness

doi:10.21203/rs.3.rs-4968554/v1

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Research Article

Integrating self-efficacy and career anchor: a multi-dimensional model to enhance vocational college students' employment competitiveness

https://doi.org/10.21203/rs.3.rs-4968554/v1

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With With the growth of the digital economy and the advancement of China's “Made in 2025” initiative, people pay more and more attention to the employment competitiveness of graduates from vocational colleges. Based on career anchor theory and self-efficacy theory, this study uses a partial least square structural equation model to analyze the sample data. It discusses the influence mechanism of cross-professional learning, career development and planning, and career network expansion on employment competitiveness. The results show that these factors significantly improve students' employment competitiveness, while self-efficacy and employment matching play an important mediating role. This study provides valuable insights for governments in formulating education policies, emphasizes the importance of supporting cross-disciplinary learning and providing systematic and personalized career development and planning guidance, and makes specific recommendations to strengthen career guidance and services. This study innovatively integrates self-efficacy theory and career anchor theory to build a brand new theoretical framework. Such cross-theoretical integration not only deepens the understanding of the psychological mechanism of individual career development, but also provides a new research path and perspective for subsequent research.

career anchor

career development and planning

career network expansion

self-efficacy

employment competitiveness

With the strategy of "Made in China 2025" and the development of the digital economy, the employment competitiveness of students in higher vocational colleges and universities has become the focus of social attention. According to the National Bureau of Statistics and the Ministry of Education, the employment rate of graduates from higher vocational colleges and universities nationwide reached about 85% in 2023, slightly higher than that of ordinary undergraduate graduates. This phenomenon is attributed to the state's emphasis on vocational education and the support of related policies. For example, the Measures on Creating New Consumption Scenarios to Cultivate New Growth Points of Consumption proposes to promote employment growth through diversified consumption scenarios. In addition, the Ministry of Education has issued Comprehensive Policy Provisions and Institutional Documents on Vocational and Continuing Education and Policies on Employment and Entrepreneurship for Graduates of Higher Education Institutions, which further enhance the attractiveness of vocational education and employment rates (Sudan, 2023) The The comprehensive employment guidance and services and entrepreneurship support policies also further help students plan their career paths and realize their entrepreneurial dreams (Kieu et al., 2023; Zheng, 2023).

Although higher vocational colleges and universities aim to enhance students' vocational literacy and employment competitiveness through professional skills training and career planning, students still face the problems of insufficient vocational literacy and asymmetric employment information (Lei, 2023; Rausch et al., 2024). Although the state has introduced several policies to improve students' employment rate and competitiveness, in practice, these policies have had mixed results. Some higher education institutions still have deficiencies in internship and career guidance, and students cannot fully utilize these policy resources (Mawonedzo & Banda, 2024; Schneider & Pilz, 2024).

Ideally, students should be able to enter the job market smoothly through a sound vocational education system and employment guidance services, obtain jobs that match their professional skills, and have a high level of vocational literacy and the ability to acquire information. However, in reality, students face the problems of a mismatch between skills and market demand, poor information channels ,and a lack of vocational literacy in the employment process (Wang, 2022). These problems seriously affect their employment competitiveness and career development path.

Research on the employment competitiveness of students in higher vocational colleges and universities has become an important area of education and career development research. Relevant studies have focused on the following aspects: first, the effects of career decision self-efficacy and emotional intelligence on employment competitiveness, and high self-efficacy and emotional intelligence significantly increase students' employment motivation and success rate (Zhou et al., 2023) Second, how IT skills training enhances employment competitiveness, IT skills training helps students to adapt to the market demand, and improve their professional and social adaptability (Widarto et al., 2023). and then, the impact of career development learning (CDL) on job competitiveness, CDL programs enhance students' ability to transition from school to work through career advice and support (Jiménez Ramírez et al., 2023); Additionally, the impact of social and academic capital on job competitiveness, rich social connections and high academic capital significantly increase students' job search competitiveness (Fernando & Wickramasinghe, 2024); and finally, the role of career guidance and services and school-enterprise partnerships and internships, which help students plan career paths, provide internship and employment opportunities, and enhance practical experience (Kim et al., 2022). While substantial progress has been achieved in boosting the employability of students in higher vocational institutions, the majority of previous research has primarily employed single-dimensional analyses, lacking comprehensive and multidimensional theoretical pathways.

This research addresses this gap by identifying and examining the critical factors influencing students' employment competitiveness in higher education through a multidimensional framework. By employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for an in-depth analysis of sample data, this study not only introduces fresh theoretical insights but also offers empirical evidence to aid educational institutions and policymakers in devising effective educational strategies and policies.

To reach this objective, this research will integrate career anchor theory and self-efficacy theory, examining how interprofessional learning, career development and planning, and career network expansion mediate their combined effects on students' employment competitiveness via self-efficacy and employment matching. Utilizing quantitative research methods, these various influences will be deeply analyzed, ultimately providing theoretical and empirical support for enhancing the employment competitiveness of students in higher education.

The research addresses three primary questions:

What mechanisms do interprofessional learning, career development and planning, and career network expansion use to influence students' employability?

To what extent do self-efficacy and employment matching mediate this influence?

How do self-efficacy and employment matching impact students' job competitiveness individually?

Findings indicate that interprofessional learning, career development and planning, and career network expansion notably improve the employment competitiveness of students in higher education. Specifically, interprofessional learning significantly boosts students' self-efficacy and employment matching through acquiring multidisciplinary knowledge and skills. Career development and planning enhance self-efficacy and employment matching via systematic career guidance and clear career strategies. Career network expansion significantly augments self-efficacy and employment match. Further analysis demonstrates that self-efficacy and employment match directly bolster students' employment competitiveness. Interprofessional learning, career development and planning, and career network expansion indirectly elevate students' employment competitiveness by enhancing self-efficacy and employment matching.

Compared to previous studies, this research stands out in two key areas. One, career anchor theory, traditionally focused on career choice and development, is applied innovatively to study the employment competitiveness of students in higher vocational colleges, expanding its theoretical application. Two, by merging career anchor theory and self-efficacy theory, the research elucidates how interprofessional learning, career development and planning, and career network expansion impact students' employment competitiveness through self-efficacy and employment matching. Self-efficacy theory highlights an individual’s confidence in their abilities and performance under challenges, while career anchor theory delves into core values and motivations in career choices. Integrating these theories offers a comprehensive and insightful framework, addressing gaps in existing research and advancing educational theories.

The following sections of this study encompass the literature review and research hypotheses, research design detailing data sources, questionnaire, and analytical methods, empirical analysis with statistics, reliability and validity, model fit, regression analysis, and mediation effect analysis, and the discussion and conclusion.

2.1 Literature Review

2.1.1 Career anchor theory

Developed by Edgar H. Schein in the 1970s, Career Anchor Theory explains core values, motivations, and aptitudes in career choices. Schein identified that individuals have a stable pattern in career decisions based on internal values and self-concepts, termed "career anchors". Through extensive research, he proposed eight anchors: technical/functional competence, managerial competence, autonomy/independence, security/stability, creativity, service/commitment, challenge, and lifestyle.

Despite its wide application in career choice and development research, the use of career anchor theory in studying students' employment competitiveness in higher education is limited. Applications and studies in various fields provide a theoretical background for this research. Ding (2021)discovered that matching career anchor type with career needs affects adaptation, particularly when entrepreneurial creativity aligns with managerial traits. Sugiyama et al. (2024) observed that stability and balance in career anchors enhance satisfaction and achievement, highlighting the importance of identifying career anchors that match core values. Yates( 2021)emphasized that integrating multiple theories of career choice and development, with career anchor theory as a key component, enhances career strategies and employment competitiveness. Martini and Arra (2023) found a strong alignment between career choices and personal values across cultures, suggesting that career anchor theory can help find careers that match cultural values. Widely used in career guidance in vocational colleges, Yates (2020)suggested that combining multiple development theories addresses career choice complexities, enhances competitiveness, and helps students understand and choose career anchors wisely.

Table 1

Research on the application of career anchor theory in different fields
author	Research	theoretical model	Variable Measurement	Key points
Julia Yates (2021)	Provide a comprehensive theoretical analysis of career choice and development, integrating multiple theoretical frameworks	Integrated Model of Career Choice and Development	Identity, environment, vocational learning, psycho-vocational resources	Career choice and development is a complex process that requires the integration of multiple theoretical frameworks to paint a complete picture
Keimei Sugiyama et al. (2022)	Emphasizing the balance between stability and dynamism of professional identity	A paradoxical theoretical model of professional identity maintenance and change	Anchoring and evolving power of professional identity	Proposes a single theoretical model of occupational identity maintenance and change that explains how occupational identities remain stable and change over time
Hong Chen et al. (2021)	Exploring the match between career anchors and job characteristics and examining biases in career choices and needs	Career Anchor and Job Characteristics Matching Model	Career needs (career anchors), career choices	Deviations between career choices and career needs were common, with the highest match between entrepreneurial creativity anchors and managerial traits, and the lowest match between lifestyle anchors
Martini, M. C., & Arra, A. (2023).	Compare similarities and differences in career choices and personal values to reveal the influence of cultural background on career choices	Schwartz Fundamental Values and Schein's Career Anchor Theory Model	Personal Values (PVQ scale), Career Anchors (COI scale)	There is a high degree of congruence between personal values and career choices, with openness favoring self-directed and entrepreneurial careers and conservatism favoring safe and stable careers
Julia Yates (2020)	Provide a theoretical foundation for career guidance for students in higher education, emphasizing the complexity and diversity of career choices	Integrated Model of Career Choice and Development	Identity, environment, vocational learning, psycho-vocational resources	Provide a variety of theoretical frameworks for career development that will help career guidance practice

2.1.2 Self-efficacy theory

Formulated by psychologist Albert Bandura in 1977, self-efficacy theory is integral to his broader social cognitive theory. It defines self-efficacy as an individual's confidence in their ability to complete specific tasks or achieve goals successfully.

In recent times, self-efficacy theory has seen extensive application and research in employment fields. Covering areas such as career decision-making, entrepreneurial intentions, and career maturity, its impact is evident. Ramadhani and Hardew (2024) discovered that higher career decision-making self-efficacy correlates with greater occupational tenacity. Lee et al. (2022) observed that career decision-making self-efficacy enhances career resilience through preparatory behaviors. Regarding entrepreneurial intentions, Thanh (2023) found self-efficacy influences intentions via entrepreneurial passion, with role models serving as a moderating factor. Radityo et al. (2024) highlighted that self-efficacy mediates between entrepreneurship education and entrepreneurial intentions, underscoring the necessity of boosting self-efficacy to enhance these intentions. In career maturity, Lee et al. (2024) showed that vocational education programs utilizing Edu-tech significantly raise career decision self-efficacy and career maturity. Rozamuri (2022) also indicated that self-efficacy and locus of control positively affect career maturity. These findings underscore self-efficacy's critical role in improving job competitiveness, providing both theoretical and practical insights for career development.

Table 2

Studies related to self-efficacy theory in employment
author	Research	theoretical model	Variable Measurement	Key points
M. Ihsan Ramadhani, Ayatullah Kutub Hardew (2024)	Exploring the Impact of Career Decision Making Self-Efficacy on Career Tenacity	Career Decision Making Self-Efficacy and Career Tenacity	Career Decision Making Self-Efficacy Scale (CDMSE)	The study found a significant positive correlation between career decision self-efficacy and career tenacity
Baiyan Du et al. (2024)	Analyzing the Impact of Career Decision Self-Efficacy on Career Adaptability	Career Decision Self-Efficacy and Career Adaptability	Career Decision Self-Efficacy Scale, Career Adaptability Scale	Career decision-making self-efficacy significantly and positively influences career preparation behavior, which in turn influences career adaptability
Thuy Doan Thi Thanh, Le Hoai Viet (2023)	The Effects of Self-Efficacy, Entrepreneurial Passion, and Role Models on Entrepreneurial Intentions	Self-efficacy and entrepreneurial intentions	Self-Efficacy Scale, Entrepreneurial Passion Scale	Self-efficacy mediates the influence of entrepreneurial intentions through entrepreneurial passion, and role models moderate the relationship between entrepreneurial passion and entrepreneurial intentions
Herdiyan Radityo et al. (2024)	Exploring the mediating role of self-efficacy between entrepreneurship education and entrepreneurial intentions	Self-efficacy as a mediator between entrepreneurship education and entrepreneurial intentions	Self-Efficacy Scale, Entrepreneurial Intention Scale	Self-efficacy significantly mediates the relationship between entrepreneurship education and entrepreneurial intentions
Paula McMahon (2023)	Tools and Strategies for Identifying and Developing Student Self-Efficacy	Self-efficacy theory	Self-Efficacy Scale	Enhancing Student Self-Efficacy by Building Supportive Online Learning Environments
Svetlana Asyanova et al. (2024)	Exploring the Impact of Self-Efficacy on Academic Performance	Self-efficacy and academic performance	Self-Efficacy Scale, Academic Performance Scale	There is a significant positive correlation between self-efficacy and academic performance
Yeo Jin Lee et al. (2024)	Effects of a vocational education program using Edu-tech on career decision-making self-efficacy and career maturity of secondary school students	Edu-tech Vocational Education Program	Career Decision Making Self-Efficacy Scale, Career Maturity Scale	Vocational education programs using Edu-tech have significantly increased the career maturity of students
Arif Murti Rozamuri (2023)	The effect of self-efficacy and control points on career maturity	Self-efficacy and career maturity	Self-Efficacy Scale, Control Point Scale	Self-efficacy and control points have a significant positive effect on career maturity

Drawing from the literature, the career anchor theory and self-efficacy theory's application in employment is well acknowledged. Career anchor theory elucidates individuals' core values and motivations in career choices and development, while self-efficacy theory highlights confidence in one's abilities and performance when facing challenges. The beneficial effects of these theories on career development and adaptability are well established. Interprofessional learning promotes technical/functional anchors and self-efficacy; career planning strengthens managerial and challenging anchors and self-efficacy; career network expansion enhances service/commitment anchors and self-efficacy. This combined perspective addresses the limitations of a single theory, thoroughly enhancing students' employment competitiveness. Therefore, integrating career anchor theory and self-efficacy theory to examine the influence of interprofessional learning, career development and planning, and career network expansion on college students' employment competitiveness is highly viable.

2.2 Research variables

Employment competitiveness is an individual's capacity to secure and sustain job opportunities in the labor market, encompassing vocational knowledge, skills, work experience, social connections, career attitudes, and personality traits. Utilizing career anchor theory and self-efficacy theory, this research identifies five key factors influencing college students' employment competitiveness: interdisciplinary learning, career development and planning, career network expansion, self-efficacy, and employment matching.Interprofessional learning enables students to acquire a broad range of knowledge and skills, fostering integrative and innovative capabilities (Plasman et al., 2022; Sio et al., 2022). Career development and planning cultivate effective strategies by evaluating interests, abilities, and career goals (Esther & Bancy, 2021).Career network expansion facilitates career growth by establishing and maintaining professional relationships that provide access to career information, support, and resources (Su et al., 2020). Self-efficacy impacts motivation, persistence, and behavioral performance, serving as a crucial psychological factor in academic and career achievements (Stroumbakis et al., 2021). Employment fit denotes the alignment between an individual's abilities and the demands of a job, with a high level of fit enhancing career satisfaction and performance (Plasman et al., 2022). The description of the measurement items for the above variables is shown in Table 2.

Table 3

Table of Observed Variables
variable name	Variable category	observed variable	Literature sources
interdisciplinary study (IPL)	independent variable	1. I have had the opportunity to participate in an interdisciplinary course of study.	Tynjälä (1999)
		2. Interdisciplinary learning has enhanced my ability to solve complex problems.
		3. I have learned new knowledge and skills in interprofessional studies.
		4. Interdisciplinary learning has enhanced my teamwork skills.
		5. Interdisciplinary studies have given me a broader understanding of my future career options.
Career Development and Planning (CDP)		1. I regularly develop a personal career development plan.	Lent, Brown, & Hackett (1994).
		2. My career development plan contains clear short- and long-term goals.
		3. I have regularly assessed and adjusted my career development plan.
		4. I consider the Career Development Program to be very important for my future career development.
		5. I take current job market conditions into account when developing my career development plan.
		6. My career development plan includes upgrading my professional skills and knowledge.
Career Network Expansion (CNE)		1. I regularly participate in professional social events related to my profession.	Seibert, Kraimer, & Liden (2001).
		2. I have many friends and colleagues in specialized fields.
		3. I am active in expanding my professional network in various ways.
self-efficacy (SE)	intermediary variable	1. I am confident that I am up to the professional challenges ahead.	Bandura (1997)
		2. I am confident in my professional skills and abilities.
		3. When faced with difficulties, I have the confidence to find solutions to problems.
employment matching (EM)		1. I believe that my professional skills are highly compatible with the requirements of my future career.	Kristof-Brown, Zimmerman, & Johnson (2005).
		2. I was able to find a position in my field of specialization when I was looking for a job.
		3. My career plans are in line with market needs.
		4. My educational background is compatible with the career I am pursuing.
		5. My expectations for my future career are consistent with the reality of the work environment.
		6. I work where I feel that my skills match the requirements of the job.
Employment Competitiveness (EC)	implicit variable	1. I believe I have what it takes to excel in a competitive job market.	Fugate, Kinicki, & Ashforth (2004).
		2. I am optimistic about my career prospects.
		3. I have shown great confidence and aplomb in my job search.
		4. I have the key skills required for a wide range of occupations.
		5. I am able to adapt quickly to new work environments and responsibilities.
		6. I am able to communicate effectively with colleagues and superiors.
		7. I can actively seek and take advantage of opportunities for professional development.

This study seeks to thoroughly investigate the factors influencing college students' employment competitiveness by analyzing the aforementioned variables and their measurement items, providing both empirical support and a theoretical foundation.

2.3 Research hypothesis

(4) Interprofessional Learning and Self-Efficacy and Employment matching

Existing research points to the fact that interprofessional learning integrates knowledge from different disciplines and enables students to learn in diverse contexts. Nugroho et al. (2023) showed that this type of learning enhances students' confidence and self-efficacy. Interprofessional learning emphasizes solving real-world problems in different disciplinary contexts and enhances students' problem-solving skills. Su (2022) The study found that CDP combined with STEM education significantly enhanced students' professional skills and self-efficacy. Interprofessional learning requires teamwork, where students from different disciplinary backgrounds collaborate with each other. Hiscox et al. (2022) noted that teamwork enhanced students' self-efficacy and received more support and feedback through collaboration. Huang et al. (2024) (2024) found that interprofessional learning helped students clarify their career direction and improve the clarity of their career decision-making, thus enhancing their self-efficacy. Based on this, the following hypotheses were proposed in this study:

H1: Interprofessional learning has a positive and significant effect on self-efficacy.

Interprofessional learning not only expands students' knowledge but also enhances their competitiveness in multiple fields. It has been shown that interprofessional learning significantly improves students' employment matching, i.e., the fit of students' skills and knowledge with industry needs. Selvi et al. (2019) noted that interdisciplinary learning can contribute to students' achievement of the SDGs while significantly improving students' employability and fit. Sihvola (2014) explored the impact of interdisciplinary education on careers, proposing the T-shaped competency model, which is the possession of in-depth knowledge and skills in a particular field (the vertical part of the T), along with a breadth of competencies across disciplines (the horizontal part of the T). Bagares (2024) and Santos and BAE (2022) showed that students with T-shaped competencies have higher competitiveness and job matches in the job market. Based on this, this study proposes the following hypothesis:

H2: Interdisciplinary learning positively and significantly influences employment matching.

(5) Career development and planning with self-efficacy and employment matching

Self-efficacy is a critical psychological factor in career development and decision-making. The study by Hamzah et al. (2021) examined how career decision self-efficacy impacts college students' career adaptability. It found that self-efficacy significantly influences career adaptability through career preparation behaviors. This indicates that career development planning can boost students' career choice and adaptation abilities by enhancing their self-efficacy. Additionally, Lee et al. (2022) discovered that career decision self-efficacy greatly affects career preparation behaviors and plays a crucial role in improving career adaptability. Thus, the following hypotheses are proposed in this research:

H3: Career development and planning have a positive and significant effect on self-efficacy.

Employment matching degree refers to the degree of fit between an individual's skills and knowledge and the needs of the job. It has been shown that systematic career development and planning can significantly improve an individual's employment fit, i.e., by helping individuals find the most suitable jobs through match optimization algorithms, experiential career planning, personality assessment, and fuzzy hierarchical analysis (Kurt &ı Özbakır, 2020; Snyder & Hartwell, 2023). Based on this, the following hypotheses are proposed in this study:

H4: Career development and planning have a positive and significant effect on employment matching.

(6) Career Network Expansion and Self-Efficacy and Employment matching

Career network expansion is the process by which individuals access career information, resources, and opportunities by establishing and maintaining career connections. This process includes not only networking with peers and professionals, but also involves active participation in professional social events, joining professional associations, attending industry conferences, and utilizing social media platforms. Alemdar et al. (2022) study found that broader and higher-quality professional networks increased Noyce teachers' self-efficacy, leading to higher retention rates in high-need schools. Zhou et al. (2023) The study noted that the number of connections in the film and television industry was significantly and positively related to career decision self-efficacy, and the more extensive the professional network, the stronger the individual's career decision self-efficacy was (Loureiro & Lovett, 2023). This suggests that rich professional network resources and support can significantly enhance individuals' self-confidence and competence in career decision-making. Based on the above review, the following hypotheses are proposed in this study:

H5: Professional network expansion positively and significantly influences self-efficacy.

Expanding one's career network not only provides valuable career information but also increases employment opportunities, aiding individuals in finding the most suitable jobs. Studies indicate that expanding occupational networks can significantly enhance individuals' employment matching. Through these networks, individuals gain access to more career information, comprehend industry trends and job requirements, and identify and seize suitable job opportunities, thereby improving employment matching (Serodio et al., 2024; Ustin et al., 2024). Based on this review, the following hypotheses are proposed in this study.

H6: Career network expansion positively and significantly influences employment matching.

(7) Self-efficacy and Employment Competitiveness

Self-efficacy is an individual's belief and confidence in their ability to perform successfully in a specific task or domain. Kang (2023) and Hayati and Idin (2024) showed that participation in extracurricular activities positively influenced college students' employment self-efficacy through the mediating role of information-seeking strategies, where purposeful and exploratory strategies enhanced this relationship, while unstructured search strategies were negatively associated with it. Furthermore. Kanar and Bouckenooghe (2021) and Pukkinen et al. (2023) studies also found that certain extracurricular activities were positively related to college students' self-efficacy, suggesting that this may influence key outcomes such as employability. These studies suggest that frequent participation in extracurricular activities may increase students' self-efficacy, which in turn may enhance their employability (Cai & Yu, 2024). Based on this, the following hypotheses were proposed in this study:

H7: Self-efficacy has a positive and significant effect on the employment competitiveness of university students.

(8) Employment matching and Job Competitiveness.

A high employment match implies a high degree of congruence between an individual's competencies and the job requirements, leading to increased productivity, job satisfaction, and career potential. Pan et al. (2020) found that higher employment fit significantly improves employee productivity and employment accessibility. Individuals can perform tasks more effectively when their skills and knowledge are highly matched to the demands of the job. Similarly. Birchenall (2008) finding suggest that a high employment match not only enhances an individual's job performance, but also promotes employees' performance in innovative tasks and enhances their adaptability and competitiveness. Based on this, the following hypotheses are proposed in this study:

H8: There is a positive and significant effect of employment matching on the job competitiveness of college students.

(9) The mediating role of self-efficacy

The above hypotheses mentioned that "Interdisciplinary learning has a positive and significant effect on self-efficacy", "Career development and planning has a positive and significant effect on self-efficacy", "Career network expansion has a positive and significant effect on self-efficacy" and "Self-efficacy has a positive and significant effect on college students' employment competitiveness". A significant impact on self-efficacy," "career development and planning positively and significantly impact self-efficacy," "career network expansion positively and significantly influences self-efficacy," and "self-efficacy positively and significantly affects the employment competitiveness of college students." Thus, it is posited that interprofessional learning, career development and planning, and career network expansion enhance college students' employment competitiveness through self-efficacy. Based on this, the following hypotheses are proposed:

H9: Interprofessional learning positively and significantly impacts college students' job competitiveness through self-efficacy.

H10: Career development and planning positively and significantly influence the job competitiveness of college students through self-efficacy.

H11: Career network expansion positively and significantly impacts college students' job competitiveness through self-efficacy.

(10) The mediating role of employment matching

The above hypotheses mentioned that "Interdisciplinary study has a positive and significant effect on the degree of employment matching", "Career development and planning has a positive and significant effect on the degree of employment matching", "Expansion of career network has a positive and significant effect on the degree of employment matching" and "The degree of employment matching has a positive and significant effect on the degree of employment competitiveness of college students". A significant impact on employment matching degree," "career development and planning positively and significantly impact employment matching degree," "career network expansion positively and significantly influences employment matching degree," and "employment matching degree positively and significantly affects the employment competitiveness of college students." Thus, it is posited that interprofessional learning, career development and planning, and career network expansion all enhance college students' employment competitiveness through employment matching degree. Based on this, the following hypotheses are proposed:

H12: Interprofessional learning positively and significantly impacts college students' job competitiveness through employment matching.

H13: Career development and planning positively and significantly influence college students' job competitiveness through employment matching.

H14: Career network expansion positively and significantly impacts college students' job competitiveness through employment matching.

2.4 Research model

Drawing from the literature review and proposed hypotheses, this study develops a multidimensional impact analysis model to investigate how three educational strategies—interprofessional learning, career development and planning, and career network expansion—influence college students' employment competitiveness. Anchored in self-efficacy theory and career anchor theory, the model identifies interprofessional learning, career development and planning, and career network expansion as independent variables, with self-efficacy and employment matching serving as mediating variables. Figure 1 illustrates the model's overall framework.

3.1 Data sources

To increase the diversity of the sample, this study utilized a purposive sampling method by selecting students enrolled in higher vocational and technical colleges in the provinces of Beijing, Guangdong, Fujian, Hubei, Hunan, Jiangxi, Zhejiang, and Shandong as survey respondents. Data collection was conducted through electronic questionnaires, and as of December 16, 2023, 2356 questionnaires had been collected. After screening, the total number of valid questionnaires was 589, with an effective recovery rate of 25%.

3.2 Questionnaire design

The questionnaire designed for this study consisted of three sections: instructions for completion, basic information, and factors influencing employment competitiveness. The instructions for completion section explains the purpose of the survey and assures that the data collected will only be used for research purposes. Information such as gender, grade level, major studied whether it belongs to a major within a cluster of majors, and the region where the school is located are intended to understand the background of the participants.

The Employment Competitiveness Influencing Factors section encompasses seven dimensions: interprofessional learning, career development and planning, career network expansion, self-efficacy, job match, skill match, and employment competitiveness. Each dimension includes 3–7 measurement items, with the questionnaire using a 7-point Likert scale. The scale ranges from "1" to "7," signifying strongly disagree, disagree, slightly disagree, neutral, slightly agree, agree, and strongly agree, respectively. "Strongly disagree" indicates that the scenario described in the questionnaire does not reflect reality at all, while "Strongly agree" signifies complete alignment with reality. "Neutral" represents a midpoint stance.

3.3 Methods of analysis

This research employs SPSS and Structural Equation Modeling (SEM) to empirically examine the factors influencing college students' employment competitiveness. Descriptive statistical analyses, which include the frequency of categorical variables and the mean and standard deviation of continuous variables, were conducted to gain an initial understanding of the sample characteristics. The convergent and discriminant validity of the questionnaire constructs were evaluated using factor analysis, and the validity of these constructs was tested through confirmatory factor analysis (CFA). Structural equation modeling was utilized to test the research hypotheses, perform model fit assessments, estimate SEM path coefficients, and conduct mediation analysis.

4.1 Basic information

A survey of 589 students from higher education institutions collected data on key variables to thoroughly analyze the impact of interprofessional learning, career development and planning, and career network expansion on college students' employment competitiveness. In terms of gender distribution, 53.6% (316) were male and 46.4% (273) were female. In terms of belonging to a major group, about 72.84% (429) of the students indicated that their majors belonged within a major group, while 27.16% (160) of the students believed that their majors did not belong to a major group. Regarding the type of institution, 71.14% (419) of the students were from dual high schools and 28.86% (170) were from non-dual high schools. The detailed data analysis is presented in Table 4.

Table 4

Frequency table for basic information
Variable	ValueLabel	(%)
distinguishing between the sexes	a male	316 (53.6)
	females	273 (46.4)
Whether the major studied is within a cluster of majors	be	429 (72.84)
	clogged	160 (17.16)
Whether the institution is a dual-enrollment institution	be	419 (71.14)
	clogged	170 (28.86)
	Total	589

4.2 Descriptive Statistics Reliability Analysis

As can be seen in Table 5, the mean values ranged from 4.54 to 5.03, and the standardized factor loadings, synthetic reliability, and mean variance extraction all met the criteria of Fornell and Larcker (1981), so the study had good reliability and validity.

Table 5

Descriptive Statistics and Reliability (or Mean, Standard Deviation)
Variable		Mean	Std.	Std.	CR	AVE
IPL	IPL1	4.75	1.63	0.741	0.902	0.649
	IPL2	4.77	1.59	0.805
	IPL3	4.76	1.58	0.826
	IPL4	4.71	1.54	0.842
	IPL5	4.78	1.54	0.81
CDP	CDP1	4.54	1.53	0.696	0.912	0.633
	CDP2	4.82	1.56	0.813
	CDP3	4.86	1.55	0.808
	CDP4	4.9	1.48	0.843
	CDP5	5.03	1.6	0.795
	CDP6	4.8	1.5	0.809
CNE	CNE1	4.86	1.5	0.842	0.876	0.703
	CNE2	4.94	1.47	0.858
	CNE3	4.93	1.47	0.814
SE	SE1	4.74	1.53	0.792	0.859	0.67
	SE2	4.66	1.5	0.843
	SE3	4.75	1.53	0.819
EM	EM1	4.74	1.57	0.839	0.936	0.709
	EM2	4.75	1.49	0.846
	EM3	4.72	1.55	0.836
	EM4	4.82	1.5	0.856
	EM5	4.75	1.51	0.851
	EM6	4.75	1.52	0.825
EC	EC1	4.66	1.47	0.8	0.935	0.674
	EC2	4.66	1.51	0.844
	EC3	4.6	1.51	0.856
	EC4	4.62	1.55	0.829
	EC5	4.64	1.51	0.835
	EC6	4.69	1.52	0.803
	EC7	4.59	1.52	0.779
Note: IPL: Interprofessional Learning; CDP: Career Development and Planning; CNE: Career Network Expansion; SE: Self-Efficacy; EM: Employment Match; EC: Employment Competitiveness.

4.3 Distinguishing Validity

According to Fornell & Larcker (1981) the AVE square root of a construct is said to have discriminant validity if it is greater than the correlation coefficient between the constructs. As shown in Table 6, this study meets the scholars' criteria and therefore has good discriminant validity.

Table 6

Discriminant validity of the measurement model
	AVE	IPL	CDP	CNE	SE	EM	EC
PL	0.649	0.806
CDP	0.633	0.587	0.796
CNE	0.703	0.574	0.688	0.838
SE	0.670	0.534	0.595	0.587	0.819
EM	0.709	0.602	0.643	0.625	0.479	0.842
EC	0.674	0.463	0.506	0.496	0.629	0.585	0.821
Note: IPL: Interprofessional Learning; CDP: Career Development and Planning; CNE: Career Network Expansion; SE: Self-Efficacy; EM: Employment Match; EC: Employment Competitiveness.

4.4 Model fit analysis

Both RMSEA and SRMR were below 0.08, and TLI, CFI, AGFI and GFI were above 0.9, and the model fits shown in Table 7 met the criteria. Thus it shows that the model has a good fit.

Table 7

Model fit
Model fit	Criteria	Model fit of research
MLχ2	The small the better	799.786
DF	The large the better	394.000
Normed Chi-sqr (χ2/DF)	1 < χ2/DF < 3	2.03
RMSEA	< 0.08	0.042
SRMR	< 0.08	0.045
TLI (NNFI)	> 0.9	0.966
CFI	> 0.9	0.969
GFI	> 0.9	0.941
AGFI	> 0.9	0.935

4.5 Regression analysis

As shown in Table 8, Interprofessional Learning (IPL) (b = 0.213), Career Development and Planning (CDP) (b = 0.328) & Career Network Expansion (CNE) (b = 0.258) significantly influenced (p < 0.001) Self-Efficacy (SE). Interprofessional Learning (IPL) (b = 0.301), Career Development and Planning (CDP) (b = 0.376) and Career Network Expansion (CNE) (b = 0.269) significantly influenced (p < 0.001) Employment Match (EM). Self-efficacy (SE) (b = 0.429) and Employment Match (EM) (b = 0.321) significantly affect (p < 0.001) Employment Competitiveness (EC). The explanatory power of Interprofessional Learning (IPL), Career Development and Planning (CDP), and Career Network Expansion (CNE) in explaining self-efficacy (SE) was 44.1%. The explanatory power of Interprofessional Learning (IPL), Career Development and Planning (CDP), and Career Network Expansion (CNE) to explain Employment Match (EM) is 52.2%. The explanatory power of Self-Efficacy (SE) and Employment Match (EM) to explain Employment Competitiveness (EC) is 50%.

Table 8

Regression coefficients
DV	IV	Unstd	S.E.	Unstd./S.E	Std.	R²
SE	IPL	0.213	0.052	4.086	0.212	0.441
	CDP	0.328	0.070	4.711	0.287
	CNE	0.258	0.059	4.353	0.268
EM	IPL	0.301	0.051	5.925	0.275	0.522
	CDP	0.376	0.067	5.598	0.304
	CNE	0.269	0.056	4.778	0.258
EC	SE	0.429	0.048	8.901	0.453	0.500
	EM	0.321	0.041	7.789	0.368

4.6 Analysis of intermediation effects

From Table 9 mediation model indirect effect analysis table can be obtained, in the IPL→SE→EC and IPL→EM→EC on two specific indirect effects, the p-value reached significant, and the confidence interval does not contain 0, indicating that the indirect effect is established, on behalf of the mediation effect is established. And on the two specific indirect effects of CDP→SE→EC and CDP→EM→EC, the p-values both reached significance and the confidence intervals did not contain 0, indicating that the indirect effect was established, representing the mediating effect was established. As well as on the two specific indirect effects of CNE→SE→EC versus CNE→EM→EC, the p-values both reached significance and the confidence intervals did not contain 0, indicating that the indirect effect was established, representing that the mediating effect was established.

Table 9

Analysis of indirect effects of mediation models
Effect	Point Estimate	product of coefficients			Bootstrap 1000 times
		product of coefficients			Bias-corrected 95%
		S.E.	Z-Value	p-value	Lower bound	Upper bound
overall effect
IPL→EC	0.188	0.040	4.691	0.000	0.113	0.271
Specific indirect effects
IPL→SE→EC	0.091	0.029	3.10	0.002	0.041	0.155
IPL→EM→EC	0.097	0.023	4.155	0.000	0.055	0.147
overall effect
CDP→EC	0.262	0.053	4.941	0.000	0.156	0.359
Specific indirect effects
CDP→SE→EC	0.141	0.041	3.428	0.001	0.060	0.219
CDP→EM→EC	0.121	0.032	3.724	0.000	0.062	0.193
overall effect
CNE→EC	0.197	0.046	4.312	0.000	0.116	0.298
Specific indirect effects
CNE→SE→EC	0.111	0.034	3.283	0.001	0.051	0.186
CNE→EM→EC	0.086	0.025	3.408	0.001	0.046	0.156

From the results of analyzing the data in Table 8, Table 9 and Fig. 2, it can be seen that interprofessional learning has a significant positive effect on self-efficacy (β = 0.212, P < 0.01), and the hypothesis H1 is established; interprofessional learning has a significant positive effect on employment matching (β = 0.275, P < 0.01), and the hypothesis H2 is established; career development and planning has a significant positive effect on self-efficacy (β = 0.287, P < 0.01), hypothesis H3 is established; career development and planning has a significant positive effect on employment match (β = 0.304, P < 0.01), hypothesis H4 is established; career network expansion has a significant positive effect on self-efficacy (β = 0.268, P < 0.01), hypothesis H5 is established; career network expansion has a significant positive influence is significant (β = 0.258, P < 0.01), hypothesis H6 is established; self-efficacy has a significant positive influence on employment competitiveness (β = 0.453, P < 0.01), i.e., H7 passes the test and the hypothesis is established; employment matching degree has a significant positive influence on employment competitiveness (β = 0.368, P < 0.001), i.e., H8 passes the test, the hypothesis is established. Its model path analysis is shown in Fig. 2.

Note

* indicates p < 0.05, ** indicates p < 0.01, *** indicates p < 0.001

5.1 Empirical results

This study used structural equation modeling to quantitatively analyze the multidimensional competitiveness of 589 students from higher vocational colleges and universities in several provinces, including Jiangxi, Hunan, and Hubei and compared them with related studies at home and abroad. The study constructed a multidimensional analytical model of employment competitiveness and explored the factors affecting the employment competitiveness of college students and their multidimensional mechanism of action. Through rigorous tests of reliability and validity, as well as the analysis of the measurement model and structural model, a total of 14 hypotheses, including 8 main effects and 6 mediating effects, were tested, and all hypotheses were verified. The empirical results of this study are shown in Table 10.

Table 10

Empirical results
effect (scientific phenomenon)	Hypothetical content	Verification results	Comparison with existing research literature
main effect	H1: Interprofessional learning has a positive and significant effect on self-efficacy	Accepted	with Nugroho et al. (2023), Su (2022), Hiscox et al. (2022), Huang et al. (2024) The findings are consistent.
	H2: Interdisciplinary study has a positive and significant effect on employment matching	Accepted	with Selvi et al. (2019), Sihvola (2014), Bagares (2024), Santos and BAE (2022) The findings are consistent with those of the
	H3: Career development and planning has a positive and significant effect on self-efficacy	Accepted	In agreement with Hamzah et al. (2021), Lee et al. (2022) the results of the study are consistent.
	H4: Career development and planning have a positive and significant effect on employment matching	Accepted	In agreement with Kurt and Özbakır (2020), Snyder and Hartwell (2023) findings.
	H5: Professional network expansion has a positive and significant effect on self-efficacy	Accepted	Consistent with the findings of Alemdar et al. (2022), Zhou et al. (2023), Loureiro and Lovett (2023).
	H6: Career network expansion has a positive and significant effect on employment matching	Accepted	In agreement with Serodio et al. (2024), Ustin et al. (2024), and Ustin et al. (2024), the findings are consistent with those of
	H7: Self-efficacy has a positive and significant effect on employment competitiveness of university students	Accepted	with Kang (2023), Hayati and Idin (2024), Kanar and Bouckenooghe (2021), The findings of Cai and Yu (2024) were consistent.
	H8: Employment match has a positive and significant effect on the employment competitiveness of university students	Accepted	In line with Pan et al. (2020), Birchenall (2008) The findings are consistent with those of
intermediary effect (scientific phenomenon)	H9: Interprofessional learning has a positive and significant effect on college students' employment competitiveness through self-efficacy	Accepted	with Nugroho et al. (2023), Su (2022), Huang et al. (2024), Kanar and The findings of Bouckenooghe (2021) are consistent.
	H10: Career development and planning has a positive and significant effect on college students' job competitiveness through self-efficacy	Accepted	with Hamzah et al. (2021), Lee et al. (2022), Cai and Yu (2024), Kanar and Bouckenooghe (2021) are consistent with the findings of the study.
	H11: Career network expansion has a positive and significant effect on college students' job competitiveness through self-efficacy	Accepted	With Alemdar et al. (2022), Zhou et al. (2023), Loureiro and Lovett (2023), Pukkinen et al. The findings are consistent with those of the
	H12: Interprofessional learning has a positive and significant effect on college students' employment competitiveness through employment matching	Accepted	with Selvi et al. (2019), Sihvola (2014), Bagares (2024), and Pan et al. (2020) are in agreement.
	H13: Career development and planning has a positive and significant effect on college students' job competitiveness through employment matching	Accepted	With Kurt and Özbakır (2020), Snyder and Hartwell (2023), Pan et al. (2020), The findings of Birchenall (2008) are consistent.
	H14: Career network expansion has a positive and significant effect on college students' job competitiveness through employment matching degree	Accepted	Consistent with the findings of Serodio et al. (2024), Ustin et al. (2024), Pan et al. (2020), and Birchenall (2008).

5.2 Conclusions of the study

This research integrated career anchor theory and self-efficacy theory to systematically examine the effects of interprofessional learning, career development and planning, and career network expansion on the employment competitiveness of students in higher vocational colleges and universities. It also explored the mediating roles of self-efficacy and employment matching. The findings revealed that these factors significantly boost students' employment competitiveness. Interdisciplinary learning enhances self-confidence and adaptability through the acquisition of multidisciplinary knowledge and skills. Career development and planning improve professionalism with clear career goals and strategies. Career network expansion increases social capital through extensive social connections and resource support. Self-efficacy strengthens students' confidence in tackling employment challenges, and employment matching ensures that students' skills align well with market needs. By enhancing self-efficacy and employment matching, these factors interact to provide comprehensive support and significantly elevate students' competitiveness in the job market.

5.3 Research contributions

This research expands the application of career anchor theory by integrating career theory and self-efficacy theory, creating a systematic framework to explain how various factors collectively influence students' employability. This approach offers new perspectives and methodologies for future studies. Unlike previous research, this study not only validates the established theoretical framework but also uncovers the complex interactions among different factors, leading to a more comprehensive understanding of vocational education and employment research.

The findings offer valuable insights for educational practice and policy formulation. Educational institutions can enhance students' overall employment competitiveness by strengthening interprofessional learning, implementing systematic career development and planning, and expanding vocational networks. Policymakers can develop more targeted and effective educational policies to support vocational education based on these findings.

5.4 Research recommendations

This research delves into various factors that enhance the employment competitiveness of students in higher vocational colleges and universities, offering strategic recommendations to help these institutions improve their students' workplace competitiveness effectively.

Enhancing interdisciplinary education opportunities: Interdisciplinary education significantly boosts students' self-efficacy and employment matching. Vocational colleges should actively develop interdisciplinary courses and programs to encourage students to engage in interdisciplinary learning and practice. This can be achieved by offering interdisciplinary elective courses, organizing interdisciplinary projects and activities, and establishing cooperative relationships with external higher education institutions to broaden students' learning horizons. These initiatives not only help students build a comprehensive knowledge system but also enhance their adaptability to diverse work environments, thereby increasing their job market competitiveness.

Implementing systematic career development and planning: To enhance students' self-efficacy and improve their job market matching, vocational education institutions need a comprehensive career development planning system. This system should start at enrollment, including career planning education. Implementation methods can include specialized career planning courses, personalized career counseling, field visits to enterprises, and career-oriented lectures, guiding students to establish clear career goals and development paths. Additionally, institutions should strengthen industry ties and create pathways for internships and practical training, allowing students to hone their professional skills and gain real-world experience.

Broadening career networks: A robust professional network is crucial for increasing students' employment opportunities and employment matching. Vocational colleges should assist students in building and expanding their professional networks by organizing alumni networking events, industry alliance activities, and career exchange salons. These events can bridge the gap between students and industry leaders. Colleges can also invite senior managers and industry leaders as guest lecturers and organize regular lectures and interactive sessions to help students stay updated with industry trends while accumulating valuable networking capital, thus enhancing their job market competitiveness.

Optimizing employment guidance and services: Vocational colleges and universities need to enhance their employment guidance and services by building a comprehensive employment assistance system. It is recommended that institutions establish a dedicated employment guidance department and employ qualified career consultants to provide a range of services, including job-search strategy training, resume-writing guidance, and interview simulations. Additionally, long-term cooperation with enterprises should be deepened, with regular campus recruitment activities and vocational skills competitions to broaden students' employment channels. Strengthening school-enterprise linkages and customizing talent cultivation based on market needs can enhance students' practical skills and professional ethics, thereby boosting their workplace competitiveness.

5.5 Research Limitations and Future Prospects

Despite the progress made in this study, there are still limitations. The sample was mainly from higher vocational colleges and universities in certain regions, which may affect the generalizability of the results, and the use of a cross-sectional design could not reveal the dynamic changes among variables. Future studies should expand the sample to cover different regions and types of higher vocational colleges and universities, and adopt a longitudinal design to track changes in students at different points in time. In addition, it is recommended that data collection methods be improved to utilize mixed methods and big data technologies, and that the mechanisms of the mediating variables be explored in depth to enhance the comprehensiveness and prospective nature of the study.

Conflict of Interest Statement:

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Funding:

This work is supported by Jiangxi Province education science "13th Five-Year Plan" 2023 key topics(Project number: 20ZD086.) and Jiangxi Province university humanities and social science research project༈Project number: JY22106

Author Contribution

Shuangshuang Liu is the sole author of this research paper and is responsible for writing every part of the manuscript

Acknowledgement

Thanks to my friend Chunling Huang for guiding me in writing this research paper

Data Availability

The data that support the findings of this research are available from the corresponding author upon reasonable request

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No competing interests reported.

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Integrating self-efficacy and career anchor: a multi-dimensional model to enhance vocational college students' employment competitiveness

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Abstract

Figures

1 Introduction

2 Literature Review and Research Hypothesis

2.1 Literature Review

2.1.1 Career anchor theory

2.1.2 Self-efficacy theory

2.2 Research variables

2.3 Research hypothesis

2.4 Research model

3 Research design

3.1 Data sources

3.2 Questionnaire design

3.3 Methods of analysis

4 Empirical analysis

4.1 Basic information

4.2 Descriptive Statistics Reliability Analysis

4.3 Distinguishing Validity

4.4 Model fit analysis

4.5 Regression analysis

4.6 Analysis of intermediation effects

5 Discussion and conclusions

5.1 Empirical results

5.2 Conclusions of the study

5.3 Research contributions

5.4 Research recommendations

5.5 Research Limitations and Future Prospects

Declarations

Conflict of Interest Statement:

Funding:

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

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