Classifying Job Value Profiles and Employment Outcomes Among Culinary Arts Graduates

Abstract

The job values of college graduates are rapidly changing, but a mismatch between industry expectations and young chefs’ values has emerged. To capture the heterogeneity in job values that traditional variable-centered approaches may overlook, this study employed Latent Profile Analysis, a person-centered method, to classify the job value profiles of culinary arts graduates and examine their impact on major–job match and subjective well-being. A total of 386 culinary arts graduates, extracted from the Graduates Occupational Mobility Survey, were classified into six latent profiles. First, the most prevalent profile (Profile 4) emphasized environmental and developmental values, and was associated with a higher proportion of women and a greater likelihood of unemployment. Second, graduates who valued job attributes across all dimensions (Profile 1) were more likely to secure employment in or outside their field than those in Profiles 2, 3, and 5 were. Third, negative emotions increased the likelihood of belonging to Profiles 2, 3, and 5 compared to Profile 1. Finally, higher life satisfaction reduced the probability of belonging to Profiles 4, 5, or 6 compared to Profile 1. These findings emphasize the importance of aligning HR policies with graduates’ job values. Such alignment can enhance employment within graduates’ academic disciplines and improve their subjective well-being.

1. Introduction

In contemporary society, college graduates’ job values are rapidly evolving. Although job stability and economic compensation have traditionally been primary criteria, recent trends indicate that values such as work–life balance (WLB), self-actualization, and autonomy have gained greater significance [1,2]. According to the 2024 Youth Employment Trends Survey published by the Korea Employment Information Service, 63% of respondents indicated that they prioritized work–life balance over factors such as company size or wage benefits. Additionally, a growing demand exists for special leave, flexible working hours, and remote work arrangements [3]. This shift reflects the tendency to value personal growth and quality of life over economic stability, highlighting the changing preferences of younger generations who emphasize flexible work environments and self-directed career paths. These changes have been accelerated by the widespread adoption of remote and flexible work systems following the COVID-19 pandemic, which has intensified the transformation of young college graduates’ job values [4].

These changes in job values are particularly evident in specialized professions, such as chefs, who tend to exhibit lower job satisfaction and higher turnover rates than other occupations owing to factors such as long working hours, high job intensity, occupational stress, low job stability, and limited growth opportunities [5,6]. Furthermore, Cerasa et al. [7] found that among 710 Italian chefs, 47% experienced at least two or more health issues, including gastrointestinal problems, hypertension, and musculoskeletal disorders.

In the past, chefs primarily prioritized fulfilling their self-actualization needs through artistic achievement and technical skills, viewing these as core aspects of their profession. However, contemporary young chefs now place additional importance on factors such as job stability, economic compensation, working hours, work–life balance, and job autonomy [6,8]. Reflecting on these changes, a study by Na and Min [9] examined shifts in the job values of South Korean college graduates majoring in the culinary arts. They revealed that extrinsic values such as employee benefits, work environment, and commuting distance have become increasingly important. Despite these evolving job values, many companies in the hospitality and food service industries continue to manage their human resources based on traditional job value frameworks. This mismatch in job values acts as a significant factor discouraging culinary graduates from entering the industry [10]. Even when they secure employment, the failure to meet young chefs’ expectations leads to decreased job satisfaction, lower job engagement, and diminished performance [11,12]. Therefore, adopting new management strategies that reflect changing job values is imperative.

Research on job value has been conducted in various fields. Traditional studies on job values have primarily adopted a variable-centered approach, focusing on analyzing the relationships between specific variables [13,14]. While this approach identifies individual variables such as job satisfaction, career decision-making, and major satisfaction, it has limitations in capturing the multidimensional and interactive nature of individuals’ job values [15]. To address the limitations of the variable-centered approach, recent studies [16,17,18] have introduced a person-centered approach that allows for a more nuanced analysis of individual job values. The person-centered approach, which utilizes methods such as Latent Profile Analysis (LPA), identifies differences in job value types, and examines how antecedent and outcome variables interact across these types [19,20]. Given the high levels of stress and long working hours inherent in the culinary profession, chefs are likely to pursue various job values. It is therefore essential to identify their values and understand how these differences influence subjective well-being, major–job match employment, and other outcomes. However, in the hospitality and culinary fields, a lack of in-depth research exists utilizing this approach to analyze chefs’ diverse job values and the implications for work-related outcomes. Moreover, rapid technological advancements have shortened the generational divide [21], leading to the continuous emergence of new generations with distinct values and behavioral patterns. Consequently, it is imperative to conduct regular research to explore the characteristics and changes of these generations to better understand their evolving job values.

This study thus aimed to use LPA to classify the job values of culinary arts college graduates and analyze their impact on major–job match and subjective well-being, addressing the limitations of traditional variable-centered approaches. Our findings contribute to developing strategies tailored to the unique job values of culinary professionals, thereby enhancing their satisfaction and alignment with career goals.

2. Theoretical Background

2.1. Job Values and Profiles

This section examines the concept and classification of job values and explores LPA as a person-centered approach. Job values are defined as motivational beliefs that individuals consider important in their occupational environment [22]. These values serve as critical criteria in decision-making processes related to job selection and retention [23,24].

Job values studies have proposed various dimensions and approaches for analyzing individual job values. Hospitality sector research has commonly employed the traditional variable-centered approach, categorizing job values into a two-dimensional structure of intrinsic and extrinsic factors [25,26]. For example, Putra et al. [25] identified interest, meaningfulness, and accomplishment as components of intrinsic motivation, whereas financial rewards, promotion opportunities, and job security were categorized as extrinsic motivators. Similarly, Gwak and Yoon [14] classified culinary arts students’ job values into intrinsic factors, including relationships, creativity, and achievement, and extrinsic factors, such as economy, stability, and honor. Beyond this dichotomous classification, Papavasileiou et al. [27] extended the intrinsic-extrinsic framework by introducing prestige and social values as additional dimensions in a study of Japanese hospitality workers. They argue that these values interact complementarily within the hospitality industry. Although the variable-centered approach has been instrumental in identifying correlations between specific variables, it often fails to capture complex combinations of individual job values [28].

This limitation underscores the need for a person-centered approach; this has gained increasing attention in recent studies employing LPA. It allows a nuanced examination of the diverse configurations of job values across individuals, providing deeper insights into their impact on work-related outcomes. As shown in

Table 1. Subjects and value profiles in key prior studies.

Researcher	Subjects	Profile Types	Measurement Tool
Jung [17]	Generation Z College Students	Value-Diminished, Value-Exploring, Value-Elevated	Achievement, Diversity, Autonomy, etc. (13 items in total)
Park and Jo [29]	College graduates under 39 years old	Overall Low-Recognition, Stable Reward-Seeking, Value-Contemplation, Overall Emphasis, Stability-Oriented	Profiles reveal significant differences in job satisfaction and preferences.
Chen et al. [30]	Chinese Workers	Dominant, High-Midrange, Low-Midrange, Intrinsic Motivation-Minor, Intrinsic Motivation-Dominant	This study consists of 29 items and four dimensions: external motivation, intrinsic motivation, introjection motivation, and identification motivation.
Hara et al. [31]	Nurses	Self-Oriented type, Low Type, Medium-Low Type, Medium-High Type, High Type	Intrinsic work values were assessed with four items (e.g., work autonomy and growth), extrinsic work values with two items (e.g., job security and income), social work values with five items (e.g., contributing to society), and prestige work values with three items (e.g., authority and influence).
Lee et al. [32]	Korean Workers	Seeking Job Security and Income, Seeking Aptitude/Interest, Job Security, and Income, Seeking Balanced Values rather than Income, Income-oriented, Seeking Self-fulfillment, Job Security, and Income	Measured with six factors: job reputation, job security, income, aptitude/interest, self-fulfillment, and career prospects.
Ryu and Kim [33]	Graduates of 2-year or 3-year colleges	All-Values Cherishing type, Non-Cherishing type, Reputation/Environment/Growth Cherishing type, Environment/Growth Cherishing type	15 items from GOMS (e.g., labor income, working hours, etc.)
Hong and Lim [34]	Employees	Social Impact-Focused Type, Overall High Value-Seeking Type, Reward Preference Type, Low Social Impact-Seeking Type	12 items (e.g., wages, honor, social contribution, etc.)

, person-centered approaches employing LPA have been applied across various fields, with studies differing in their measurement tools, profile names, and number of profiles identified. For instance, Jung [17] classified the job values of Generation Z university students into three profiles, whereas Park and Jo [29] classified the job values of young college graduates into five profiles. Chen et al. [30] identified five worker profiles in diverse industries in China based on a combination of intrinsic and extrinsic motivations, whereas Hara et al. [31] categorized nurses’ job values into five types, according to the importance of intrinsic, extrinsic, social, and status-related values. Similarly, Lee et al. [32] classified Korean workers into three types based on their work–life balance, economic rewards, and job stability. Although these studies differ in their subjects, methodologies, and profile names, they consistently demonstrate LPA’s utility in identifying multidimensional configurations of job values and provide significant insights into work-related outcomes. However, research employing LPA to classify the job values of culinary arts graduates remains scarce. This study fills the gap by categorizing the job values of culinary arts graduates through LPA and examining the implications for their job–person fit and subjective well-being.

2.2. Job Value Profiles and Qualitative Employment Outcomes

This section examines how employment outcomes, particularly major–job match and subjective well-being, influence job value profiles among culinary arts graduates. College graduates’ employment outcomes are closely tied to their professional quality of life, career retention, and overall life satisfaction after entering the workforce [32], with ongoing research examining the factors influencing these outcomes [35,36]. Job values also play a significant role in employment outcomes, as the alignment between an individual’s job values and the work environment directly affects job satisfaction and performance [25,27]. Employment outcomes can be broadly divided into quantitative and qualitative outcomes [30]. Quantitative outcomes include objective and measurable indicators such as employment rates, job security, tenure, graduates’ employment status, and workforce continuity [30]. By contrast, qualitative outcomes reflect employees’ psychological and emotional satisfaction during job performance, encompassing job satisfaction, job–person fit, turnover intentions, and subjective well-being [37]. This study focuses on the relationship between job values and qualitative employment outcomes by specifically examining major–job match and subjective well-being.

Major–job match refers to the extent to which an individual’s job aligns with their academic major. Higher job congruence is associated with increased job satisfaction, whereas lower congruence tends to increase turnover intentions [38,39]. Kim and Lee [40] classified college graduates into four groups based on two key dimensions: major–job match and job satisfaction. Analyzing differences in job priorities among these groups, they found that graduates in the low match–low satisfaction, low match–high satisfaction, and high match–high satisfaction groups prioritized income as the most important factor when seeking employment. In contrast, those in the high match–low satisfaction group placed the greatest emphasis on personal aptitude and interests. Zeng et al. [41] found that many graduates pursue jobs unrelated to their major because of low compensation and limited opportunities in the social work field. Furthermore, the decision to choose a job aligned with one’s major was significantly influenced by a combination of professional values (e.g., social contribution and ethical responsibility) and material rewards (e.g., financial stability and high salaries). Choi and Seo [42] found that, among millennials, individuals with high intrinsic job values exhibited significant levels of job congruence, leading to higher job satisfaction. By contrast, extrinsic job values positively influenced job congruence only when adequate economic rewards were provided. Given this, job values are likely to play a pivotal role in helping culinary arts graduates adapt to their work environment and effectively perform their roles. Thus, this study aimed to examine the relationship between the job value profiles of culinary arts graduates and their job congruence, formulating the following hypothesis.

H1. 

The major–job match of culinary arts graduates differs based on their job value profiles.

Subjective well-being refers to an individual’s positive evaluation of their life, and is composed of a multidimensional structure that includes positive affect, negative affect, and life satisfaction [43,44]. In the hospitality industry, where frequent interactions with customers are essential, employees’ subjective well-being directly influences service quality and customer satisfaction [39,45,46]. Conversely, low subjective well-being increases burnout, reduces job engagement, and heightens turnover intention, thus adversely affecting organizational outcomes [47,48]. Therefore, organizational efforts to enhance employee well-being are crucial in the hospitality sector. Job values also influence subjective well-being. Vörös [49] analyzed OECD survey data of over 4000 workers, and highlighted that job values’ impact on well-being and job satisfaction varies by job type (e.g., organizational employees vs. self-employed individuals). Workers who prioritize intrinsic values, such as self-development, achievement, and autonomy, exhibit higher levels of job and life satisfaction, particularly self-employed individuals. Udayar et al. [50] found that Swiss workers with high resilience profiles experienced greater positive affect and job satisfaction, indicating that self-regulation and job fit play crucial roles in improving psychological well-being. Hirschi et al. [51] revealed that German adults who prioritized intrinsic values such as self-development and enjoyment of work experienced greater job satisfaction, which translated into overall life satisfaction. Similarly, Woo et al. [52] demonstrated that residents of five tourism destinations who valued self-actualization and job fit experienced enhanced work satisfaction, which positively affected their overall quality of life. These studies collectively emphasize the influence of job value profiles on life satisfaction, as well as positive and negative affect across various industries. Building on this foundation, this study aimed to examine the impact of culinary arts graduates’ job value profiles on their subjective well-being, focusing on positive and negative affect, and life satisfaction.

H2. 

The subjective well-being of culinary arts graduates will differ based on their job value profiles.

3. Methods

3.1. Research Model

This study employs LPA to identify the latent profiles of job value among culinary arts graduates. Subsequently, logistic regression analysis examines how major–job match status (unemployed, major–job match employment, major–job mismatch employment) and subjective well-being (life satisfaction, positive affect, negative affect) influence these latent profiles. The research model is presented in Figure 1.

3.2. Research Subjects

This study aimed to categorize the job values of individuals who graduated from culinary and baking-related departments, and analyze the relationships between these value types, major-related employment, and subjective well-being. For this purpose, data from the Graduate Occupational Mobility Survey (GOMS) was utilized. This study utilized data from the GOMS conducted by the Korea Employment Information Service (KEIS). The GOMS is designed to systematically assess university graduates’ employment status and labor market adaptation. It is particularly useful for analyzing the link between graduates’ majors and employment outcomes, and for evaluating labor market performance. The survey ensures reliability and validity through rigorous annual sampling and a systematic questionnaire design, serving as a critical foundational resource for academic research and policy formulation.

This study conducted an analysis focusing on three years of data (2018, 2019, and 2020), including the most recently released 2020 dataset. The research subjects were limited to university graduates from culinary and baking-related departments, excluding graduates aged 30 or older to maintain consistency and focus in the study. Ultimately, the final sample consisted of 386 individuals whose job values were categorized, and the relationships among these values, major-related employment, and subjective well-being were examined. Of the total sample of 386 respondents, 208 (54%) were male and 178 (46%) were female. Regarding college type, 75% (292 respondents) had graduated from 2–3 year colleges, while the remaining 25% (94 respondents) had graduated from 4-year colleges. Regarding employment status, the “unemployed” group consisted of 103 respondents, while among the employed, 78 were categorized as the “job mismatch” group, and 205 as the “job match” group.

3.3. Measurement Tools

This section describes the measurement tools used to assess job values, major–job match, and subjective well-being based on items from the GOMS.

Job value was measured using a scale designed to evaluate the factors considered important by university graduates when choosing a workplace. This study used 15 items provided by the GOMS, including income, working hours, and other factors related to workplace conditions and benefits. The survey included the following question: “How important do you think each of the following job attributes is?” Responses were rated on a 5-point Likert scale ranging from 1 (not important at all) to 5 (very important).

Major–job match was measured using a scale designed to assess the alignment between the graduates’ employment status and their field of study. In this study, a comprehensive evaluation of the major–job match of culinary graduates was conducted by considering both subjective and explicit criteria. First, the subjective criteria were assessed based on responses to the GOMS question: “To what extent do you think the tasks you perform in your current job align with your major (or primary major) when you enrolled in university?” (g191a144). Graduates who responded with 1 (not at all) or 2 (not much) were classified as having a major–job mismatch, and were coded as 2. Those who responded with 4 (well-aligned) or 5 (very well-aligned) were classified as having a major–job match and coded as 3. Graduates who selected three (neutral) were further evaluated using additional explicit criteria (industrial and occupational subclassification) to determine alignment. Specifically, graduates employed in the food service industry, accommodation facilities, or beverage establishments, and classified as Korean, Western, Chinese, Japanese, or other chefs, or beverage preparers were considered to have major–job match, and coded as 2.

Graduates who did not meet these criteria were classified as having a major job mismatch, and were coded as 1. Graduates who did not respond to these two items were considered unemployed, and were coded as 0. Among the 365 graduates analyzed here, 205 (53.1%) were classified as having major–job match, 78 (20.2%) as having major–job mismatch, and 103 (26.7%) as unemployed.

Subjective well-being was measured using a scale designed to assess life satisfaction and psychological happiness among culinary graduates. This study utilized the Subjective Well-Being Scale provided by GOMS, which consists of three items measuring positive affect, three items measuring negative affect, and three items measuring life satisfaction. Participants rated their agreement with the following statements regarding life satisfaction: (1) “I am satisfied with the personal aspects of my life (e.g., achievements, personality, health)”. (2) “I am satisfied with the relational aspects of my life (e.g., relationships with people around me)”. (3) “I am satisfied with the group to which I belong”. Life satisfaction was measured using a 7-point Likert scale ranging from 7 (very true) to 1 (not at all true).

Participants also rated how frequently they experienced the following emotions over the past month: “How often have you felt the following emotions in the past month?” Positive affect was assessed using the adjectives joyful, happy, and relaxed, while negative affect was assessed using the adjectives irritated, negative, and lethargic. Both positive and negative affect were measured using a 7-point Likert scale ranging from 7 (always felt) to 1 (never felt).

3.4. Analysis Method

To test the hypotheses, we used Jamovi 2.3, Excel, and SPSS 28.0. Frequency analysis was conducted to examine the respondents’ demographic characteristics and the distribution of their job values. LPA was performed using Jamovi 2.3, and Excel was used to identify latent groups with similar characteristics based on the respondents’ job values. Compared to traditional clustering methods such as k-means and hierarchical clustering, LPA offers probabilistic classification, evaluates model fit indices, and enables statistical comparisons between models. The optimal number of latent profiles was determined using model fit indices such as AIC, BIC, SABIC, Entropy, Bootstrap Likelihood Ratio Test (BLRT), and profile frequency. Finally, a multinomial logistic regression was applied to evaluate the relationships between major-related employment, subjective well-being, and job value profiles.

4. Results

4.1. Descriptive Statistical Analysis of Measurement Tools

The results of the descriptive statistical analysis are presented in

Table 2. Results of descriptive statistics of measurement tools.

Measurement Items	Mean ± S.D.	Minimum	Maximum	Skewness	Kurtosis
Income	4.31 ± 0.69	2	5	−0.603	−0.39
Working Hours	4.25 ± 0.69	1	5	−0.621	0.415
Personal Aptitude and Interest	4.29 ± 0.73	2	5	−0.634	−0.481
Relevance to the Field of Study	3.77 ± 1.07	1	5	−0.751	0.0891
Task Difficulty	3.68 ± 0.83	1	5	−0.185	0.0278
Workload	3.80 ± 0.79	1	5	−0.102	−0.415
Opportunities for Personal Development	4.18 ± 0.74	1	5	−0.539	−0.0671
Future Prospects of the Profession	4.20 ± 0.74	2	5	−0.54	−0.396
Job Stability	4.23 ± 0.75	2	5	−0.511	−0.687
Work Environment	4.22 ± 0.71	2	5	−0.474	−0.464
Welfare Benefits	4.14 ± 0.74	1	5	−0.616	0.482
Company Size	3.40 ± 0.97	1	5	−0.314	0.027
Commuting Distance	3.87 ± 0.87	1	5	−0.276	−0.612
Social Evaluation of the Job	3.53 ± 0.93	1	5	−0.516	0.517
Social Evaluation of the Work Performed	3.50 ± 0.92	1	5	−0.499	0.501
Life Satisfaction	5.10 ± 1.21	1.33	7	−0.266	−0.467
Positive Affect	4.88 ± 1.24	1	7	−0.224	−0.267
Negative Affect	3.71 ± 1.37	1	7	0.147	−0.493

. Among the job value measurement tools, income (4.31 ± 0.69) had the highest mean, while company size (3.40 ± 0.97) had the lowest. Additionally, an examination of skewness and kurtosis revealed that all variables had skewness values within ±2 and kurtosis values within ±7, indicating no violations of the normality assumption. Therefore, the variables used in this study are considered appropriate for statistical analyses that assume a normal distribution.

4.2. LPA on Job Values

4.2.1. Model Fit Results Based on the Number of Profiles

The results of the LPA conducted to categorize the job values of culinary graduates are shown in

Table 3. Comparison of model fit indices for LPA on job values of culinary arts graduates.

Classes	1	2	3	4	5	6	7	8
LogLik	−6951.0	−6383.5	−6091.8	−5930.5	−5821.3	−5533.5	−5449.1	−5401.9
AIC	13,962.0	12,858.9	12,307.5	12,017.1	11,830.5	11,287.0	11,150.1	11,087.8
BIC	14,081.0	13,040.9	12,552.8	12,325.6	12,202.4	11,722.1	11,648.6	11,649.5
SABIC	13,986.0	12,894.9	12,356.1	12,078.2	11,904.1	11,373.1	11,248.8	11,199.0
Entropy	1.000	0.905	0.910	0.906	0.901	0.971	0.955	0.953
BLRT		1135.3 *	583.4 *	322.4 *	218.6 *	575.5 *	168.9 *	94.3 *
1	386 (100.0)	282 (73.1)	79 (20.5)	83 (21.5)	67 (17.4)	52 (13.5)	48 (12.4)	48 (12.4)
2		104 (26.9)	237 (61.4)	59 (15.3)	60 (15.5)	34 (8.8)	34 (8.8)	34 (8.8)
3			70 (18.1)	180 46.6)	58 (15.0)	52 (13.5)	45 (11.7)	45 (11.7)
4				64 (16.6)	171 44.3)	151 (39.1)	50 (13.0)	48 (12.4)
5					30 (7.8)	71 (18.4)	105 (27.2)	105 (27.2)
6						26 (6.7)	75 (19.4)	56 (14.5)
7							29 (7.5)	24 (6.2)
8								26 (6.7)

* p < 0.001.

. To determine the optimal number of latent profiles, various statistical indicators such as the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), entropy, and Bootstrap Likelihood Ratio Test (BLRT) were comprehensively analyzed. AIC and BIC are critical indicators for evaluating model fit, with lower values indicating a better fit [53]. As shown in Figure 2, the AIC and BIC values gradually decreased in the models with three and four profiles, exhibited a sharp decrease in the 6-profile model, and then gradually decreased in the subsequent profiles. Entropy evaluates the clarity with which each data point belongs to a latent profile, with higher values indicating clearer distinctions between profiles [54]. As Figure 2 shows, the 6-profile model displayed a relatively high entropy of 0.97. The BLRT is a measure for comparing model fit, where a significant p-value indicates a statistically meaningful improvement in model fit [55]. In this study, the BLRT p-values were significant across all profile numbers, with the largest BLRT value observed in the 6-profile model. This suggests that the 6-profile model exhibited the most substantial improvement in fit compared to the previous model. Adding further profiles resulted in statistically significant but relatively smaller improvements. Additionally, according to Berlin et al. [56], each profile should represent more than 5% of the sample size to ensure interpretability. Examination of the frequencies and percentages of each profile here revealed no groups with proportions below 5%. Thus, all of the profiles maintained an interpretable group size. In summary, considering the AIC, BIC, Entropy, BLRT, and interpretability of the group sizes, the 6-profile model was identified as the most suitable for the data. Furthermore, all the profiles maintained an adequate size of over 5%, supporting their interpretability and leading to select the 6-profile model as the optimal solution.

4.2.2. Profile Characteristics Identified Through Z-Scores

In this study, six groups were derived using LPA, based on 15 job value items. To better understand the characteristics of each group’s evaluation of job value importance, each group’s mean values were standardized. The results of this analysis are presented in

Table 4. Mean values and Z-scores of job value across six profiles.

Job Value Items		Mean						z Score
		1	2	3	4	5	6	1	2	3	4	5	6
Environmental Value	Income	4.75	3.11	4.81	4.42	4.13	3.59	1.42	−1.01	1.50	0.93	0.50	−0.30
	Working Hours	4.79	3.11	4.67	4.35	3.98	3.47	1.47	−1.02	1.30	0.82	0.28	−0.48
	Work Environment	4.79	2.96	4.77	4.35	3.81	3.25	1.47	−1.24	1.45	0.82	0.02	−0.81
	Welfare Benefits	4.75	2.89	4.54	4.29	3.87	3.27	1.42	−1.34	1.10	0.73	0.11	−0.78
	Commuting Distance	4.67	3.09	3.87	3.90	3.67	3.29	1.30	−1.04	0.11	0.16	−0.18	−0.75
Task Value	Task Difficulty	4.48	2.97	3.60	3.73	3.31	3.08	1.02	−1.22	−0.29	−0.09	−0.72	−1.06
	Workload	4.56	2.94	3.79	3.88	3.38	3.08	1.13	−1.27	−0.01	0.13	−0.61	−1.06
	Relevance to the Field of Study	4.33	3.01	3.79	3.92	3.48	3.15	0.79	−1.17	−0.01	0.19	−0.46	−0.96
Developmental Value	Opportunities for Personal Development	4.67	2.92	4.40	4.42	3.85	3.23	1.30	−1.30	0.90	0.93	0.08	−0.84
	Future Prospects of the Profession	4.75	3.03	4.58	4.37	3.92	3.39	1.42	−1.13	1.16	0.85	0.19	−0.60
	Job Stability	4.81	3.06	4.77	4.42	3.81	3.35	1.50	−1.08	1.45	0.93	0.02	−0.66
	Personal Aptitude and Interest	4.73	3.07	4.56	4.54	4.10	3.46	1.39	−1.08	1.13	1.10	0.45	−0.50
Reputation Value	Company Size	4.35	2.93	3.33	3.33	3.10	2.90	0.82	−1.29	−0.69	−0.69	−1.03	−1.33
	Social Evaluation of the Job	5.00	2.98	2.98	4.00	3.00	2.94	1.79	−1.21	−1.21	0.30	−1.18	−1.27
	Social Evaluation of the Work Performed	4.90	2.98	3.00	3.92	3.02	2.97	1.64	−1.21	−1.18	0.19	−1.15	−1.23

The overall mean is 3.79, and the standard deviation is 0.68.

and Figure 3. The standardized results allowed for a clear identification of the relative emphasis or deemphasis that each group placed on specific job value factors. The characteristics of each group are summarized as follows. The first profile demonstrated high importance across all job value factors and was named the High Comprehensive Emphasis Profile. This group exhibits a broad interest in the diverse values and opportunities that a career can offer. The second profile showed a tendency to assign low importance to all job value factors, and was labeled with the Strong Comprehensive Deemphasis Profile. The third profile scored highly in income (1.50), work environment (1.45), and working hours (1.30) as environmental values, as well as job stability (1.45) and future prospects of the profession (1.16) as developmental values, indicating a strong emphasis on these aspects. However, this group showed markedly low importance for the social evaluation of the job (−1.21) and the social evaluation of the work performed (−1.18). This led its designation as the Reputation Deemphasis, Growth & Environment Emphasis Profile. The fourth profile included 151 individuals (39.1%), and represented the largest proportion of the sample. This group valued growth factors such as personal aptitude and interest (1.10), job stability (0.93), and opportunities for personal development (0.93) as well as environmental factors such as income (0.93), working hours (0.82), and work environment (0.82). Consequently, this was named the Environmental and Development Value Emphasis Profile. The fifth profile assigned low importance to reputation values such as the social evaluation of the job (−1.18), the social evaluation of the work performed (−1.15), and company size (−1.03). Additionally, they downplayed task-related values such as task difficulty (−0.72) and workload (−0.61). However, because the environmental and developmental value items were not particularly pronounced overall, this group was named the Reputation and Task Value Deemphasis Profile. The sixth profile assigned low importance to all job value factors.

4.3. Results of Multinomial Logistic Regression Analysis

This section presents the results of the multinomial logistic regression analysis, examining how life satisfaction, positive affect, and negative affect influence the probability of membership in each latent profile.

Table 5. Results of multinomial logistic regression analysis for six profiles with job match and subjective well-being.

Dependent	Predictor		Estimate	SE	Z	Odds Ratio
Profile 2	Gender	Female	−0.618	0.495	−1.248	0.539
	Type of college	4 year college	−0.532	0.600	−0.887	0.587
	Major–job match	mismatched	−0.984	0.637	−1.545	0.374
		matched	−1.260	0.587	−2.148 *	0.284
	Subjective well-being	Life satisfaction	−0.039	0.253	−0.152	0.962
		Positive affect	0.068	0.231	0.293	1.07
		Negative affect	0.414	0.189	2.193 *	1.513
Profile 3	Gender	Female	0.352	0.415	0.847	1.421
	Type of college	4 year college	0.311	0.461	0.675	1.365
	Major–job match	mismatched	−1.753	0.641	−2.736 **	0.173
		matched	−0.942	0.518	−1.817	0.39
	Subjective well-being	Life satisfaction	−0.309	0.239	−1.294	0.734
		Positive affect	0.316	0.221	1.425	1.371
		Negative affect	0.417	0.170	2.449 *	1.517
Profile 4	Gender	Female	0.644	0.342	1.881	1.903
	Type of college	4 year college	−0.016	0.394	−0.040	0.984
	Major–job match	mismatched	−0.964	0.514	−1.876	0.381
		matched	−0.439	0.458	−0.960	0.644
	Subjective well-being	Life satisfaction	−0.588	0.204	−2.875 **	0.556
		Positive affect	0.312	0.188	1.661	1.367
		Negative affect	0.078	0.144	0.537	1.081
Profile 5	Gender	Female	−0.102	0.394	−0.260	0.903
	Type of college	4 year college	0.338	0.433	0.780	1.402
	Major–job match	mismatched	−1.481	0.595	−2.490 *	0.227
		matched	−0.717	0.501	−1.431	0.488
	Subjective well-being	Life satisfaction	−0.492	0.225	−2.188 *	0.612
		Positive affect	0.306	0.208	1.472	1.358
		Negative affect	0.419	0.161	2.597 **	1.521
Profile 6	Gender	Female	0.423	0.512	0.827	1.527
	Type of college	4 year college	−0.913	0.714	−1.279	0.401
	Major–job match	mismatched	−0.746	0.802	−0.930	0.474
		matched	0.183	0.682	0.268	1.201
	Subjective well-being	Life satisfaction	−0.973	0.311	−3.132 **	0.378
		Positive affect	−0.018	0.285	−0.065	0.982
		Negative affect	−0.028	0.226	−0.125	0.972

R²McF = 0.063, R²CS = 0.033, R²N = 0.080, χ² = 77.9, df = 35, p < 0.001. * p < 0.05, ** p < 0.01. The analysis used the following reference categories: male for gender, 2–3 year colleges for type of college, unemployed for major–job match, and Profile 1 as the reference for the dependent variable. The second profile. This group was named the Moderate Comprehensive Deemphasis Profile.

presents the results of the study. Using Profile 1 (the High Comprehensive Emphasis Profile) as the reference category, the analysis evaluated whether each independent variable significantly predicted the likelihood of belonging to other profiles. The explanatory power of the logistic regression model was indicated by a McFadden’s R² of 0.063, Cox and Snell’s R² of 0.033, and Nagelkerke’s R² of 0.080. This suggests that the model did not fully explain the variance in the dependent variable. However, it is common for R² values to be lower in logistic regressions than in linear regressions, particularly in social science research with a limited number of explanatory variables [57]. The model fit was significant, with a chi-square (χ²) value of 77.9 (p < 0.001), indicating that the model adequately explains the data and that the independent variables contribute to the relationship with the dependent variable. Thus, the results were interpreted with a focus on the statistical significance of the individual predictors.

First, in Profile 2 (the Strong Comprehensive Deemphasis Profile), major-related employment and negative emotions had significant effects. Graduates employed in their field of study were 71.6% less likely to belong to Profile 2 than to Profile 1 (estimate = −1.260, p = 0.032). Conversely, a one-unit increase in negative emotions increased the likelihood of belonging to Profile 2 by approximately 151.3% compared with Profile 1 (estimate = 0.414, p = 0.028).

Second, in Profile 3 (Reputation Deemphasis, Growth, and Environment Emphasis Profile), major–job mismatch and negative emotions were significant predictors. Graduates not employed in their field of study were 82.7% less likely to belong to Profile 3 than Profile 1 (estimate = −1.753, p = 0.006). However, a one-unit increase in negative emotions increased the likelihood of belonging to Profile 3 by 151.7% compared with Profile 1 (estimate = 0.417, p = 0.014).

Third, life satisfaction was a significant predictor in Profile 4 (Environmental and Development Emphasis Profile). A one-unit increase in life satisfaction decreased the likelihood of belonging to Profile 4 by 44.4% compared with Profile 1 (estimate = −0.588, p = 0.004). This indicates that individuals with lower life satisfaction are more likely to belong to Profile 4.

Fourth, in Profile 5 (Reputation and Task Value Deemphasis Profile), major–job mismatch, life satisfaction, and negative emotions were significant predictors. Graduates not employed in their field of study were 77.3% less likely to belong to Profile 5 compared to Profile 1 (Estimate = −1.481, p = 0.013). Additionally, a one-unit increase in life satisfaction decreased the likelihood of belonging to Profile 5 by 38.8% compared to Profile 1 (Estimate = −0.492, p = 0.029). Conversely, a one-unit increase in negative emotions increased the likelihood of belonging to Profile 5 by 152.1% compared with Profile 1 (estimate = 0.419, p = 0.009).

Finally, in Profile 6 (Moderate Comprehensive Emphasis Profile), life satisfaction was a significant predictor. A one-unit increase in life satisfaction decreased the likelihood of belonging to Profile 6 by 62.2% compared with Profile 1 (estimate = −0.973, p = 0.002). This suggests that individuals with lower life satisfaction are more likely to belong to Profile 6.

5. Discussion

This study classified the job value profiles of culinary arts graduates using LPA and analyzed their effects on major–job match and subjective well-being. Using data from the GOMS provided by KEIS, this study examined 386 graduates majoring in culinary arts or confectionery, employing a person-centered analytical approach. The findings are summarized as follows.

First, it analyzes the job values of college graduates majoring in the culinary arts, and identifies six latent profiles. Among these, the fourth profile, characterized by a strong emphasis on environmental and developmental values, was the most prevalent. Additionally, culinary arts graduates in the fourth profile had a higher proportion of women than men and were more likely to be unemployed. This suggests that they may face challenges regarding employment and overall quality of life.

Second, graduates who valued their jobs across all dimensions were more likely to secure employment, whether aligned or misaligned with their field of study, compared to those belonging to Profiles 2, 3, and 5, who placed partial or minimal importance on job values. This finding indicates that job value plays a significant role in determining whether graduates will pursue careers in their fields of study.

Third, an increase in negative emotions among culinary arts graduates was associated with a 150% higher likelihood of belonging to Profiles 2, 3, and 5 than to Profile 1. This suggests that individuals who value all job aspects equally experience fewer negative emotions, whereas those who partially or entirely devalue job values are more likely to experience heightened negative emotions. These results align with prior research [58,59] showing that negative emotions can adversely affect individual job values and career choices.

Fourth, as life satisfaction increased among culinary arts graduates, the likelihood of belonging to Profiles 4, 5, or 6 decreased compared to Profile 1, with the sixth profile showing the lowest probability. This result suggests a strong connection between life satisfaction and job values, supporting previous studies [60,61] that found that higher life satisfaction fosters a more positive and balanced approach to job values.

The academic and practical implications of these findings are as follows: First, this study has significant theoretical implications as it diverges from the variable-centered approach commonly used in previous studies on job values. By employing a person-centered approach, this study captures the heterogeneity in job value perceptions among culinary arts graduates and classifies them into six latent profiles. Through an empirical examination of the relationships between these profiles, major–job match, and subjective well-being, this study provides a more nuanced understanding of how job values shape career trajectories. These findings contribute to the broader literature on career development and workforce segmentation, particularly in industries with diverse employment pathways like culinary arts. Second, attention should be paid to Profile 4, which includes the largest number of graduates and emphasizes environmental and developmental values. This profile had a higher proportion of female graduates than male graduates, and they were more likely to be unemployed than those in Profile 1, suggesting potential challenges in employment and overall quality of life. Graduates in this profile place high importance on the work environment’s qualitative aspects, such as how well the job aligns with their skills and interests. Based on these characteristics, targeted interventions should focus on bridging the gap between industry expectations and graduates’ career aspirations. Specifically, strategies should promote employment stability by developing structured mentorship programs, strengthening employer-university partnerships, and integrating personalized career development initiatives. Additionally, policymakers and industry leaders must recognize that work environment factors, such as work–life balance and professional growth opportunities, play a critical role in retaining talent within the culinary industry. One of the primary factors contributing to the higher unemployment risk among these graduates is the absence of clear career development roadmaps and tailored growth programs. To address this issue, companies must implement targeted initiatives that align with graduates’ career goals and establish a well-defined career trajectory.

Third, Profile 1 demonstrated a strong emphasis on task value, resulting in higher life satisfaction, whereas Profiles 2, 3, 4, 5, and 6 either moderately valued or de-emphasized task value, exhibiting relatively lower life satisfaction and higher levels of negative emotions. This finding underscores the critical role of prioritizing task values in enhancing subjective well-being. Therefore, both career guidance practices and organizational policies must be tailored to reflect and accommodate the importance of culinary arts graduates’ task values. Consequently, career guidance should focus on providing graduates with comprehensive information about industries and organizations that align with their task value priorities. Moreover, it is essential to support graduates in identifying and pursuing roles that correspond to their career aspirations and competencies. This approach will enable graduates to make more informed career decisions, particularly by considering the alignment between their academic backgrounds and professional responsibilities.

Fourth, organizations in the culinary and hospitality sectors must adapt their workplace structures to align better with the task values that young chefs prioritize. For instance, they should implement strategies to manage workloads more effectively, strengthen the alignment between job roles and graduates’ academic specializations, and calibrate task difficulties to suit their individual career stages. Such initiatives can help graduates derive greater meaning and value from their work and foster a heightened sense of accomplishment and sustained professional engagement. In conclusion, aligning career guidance and organizational policies with graduates’ task-value priorities can significantly enhance life satisfaction and reduce negative emotions. This alignment not only improves individual well-being, but also plays a pivotal role in promoting sustainable development and employment stability in the culinary and hospitality industries.

This study has several limitations that provide a basis for future research. First, while the GOMS data were utilized, the limited number of employed respondents made it difficult to fully reflect qualitative employment outcomes, such as wages and regular employment. This limitation may have reduced our findings’ generalizability. Future research should expand sample diversity and include a wider range of indicators related to qualitative employment outcomes. Second, the study did not analyze the impact of individual characteristics, such as age, parental education, or educational background (academic performance or internship experience) on the results. Future research should consider both individual and educational factors to classify job values more comprehensively and analyze employment outcomes in greater depth. Third, external environmental factors that may influence job values, career choices, and subjective well-being, such as regional economic conditions, industry trends, and the impact of COVID-19, were not considered. This limitation restricts the analysis of employment outcomes in a multidimensional context. Therefore, future studies should incorporate economic and social factors, along with external environmental conditions, to build a more comprehensive research model.

6. Conclusions

This study employed Latent Profile Analysis (LPA) to classify the job value profiles of culinary arts graduates and examine their effects on major–job match and subjective well-being. The findings underscore the heterogeneous nature of job values among graduates and their significant implications for employment outcomes and life satisfaction.

First, the analysis identified six distinct job value profiles, with Profile 4, characterized by an emphasis on environmental and developmental values, being the most prevalent. This profile exhibited a higher proportion of female graduates and a greater likelihood of unemployment, indicating potential employment challenges. Second, graduates who placed high importance on all job values demonstrated a higher likelihood of securing employment, suggesting that a comprehensive exploration of job values positively influences career outcomes. Conversely, those who assigned lesser importance to job values exhibited elevated negative affect and lower life satisfaction. While this study provides empirical insights into the relationship between job values and employment outcomes, it has certain limitations, including sample constraints and the exclusion of external variables. Future research should incorporate broader employment indicators, individual characteristics, and economic factors to develop a more comprehensive understanding of job values and career trajectories.