Internal overcompetition: strategies to overcome stress and health threats

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Internal overcompetition: strategies to overcome stress and health threats

Chen Mingze, Josai International University (Japan)

Yasuyuki Yamaoka,

Open University of Japan (Japan)

Sitsada Sartamorn,

Bournemouth University (the United Kingdom)

Hiroko Oe,

Josai International University (Japan)



Abstract

In today's China, internal overcompetition is a serious problem for people's mental and physical health. It provokes stress and fatigue, physical and mental exhaustion; reduces educational qualifications; makes it difficult to find a job; leads to irregular patterns of overtime work (e.g., “996” and “007”). In China, the scale of this problem is so great that it is considered a separate concept (Nei Juan). Since 2021, it has been a subject to regulation by the government. When considering this problem, it is important to understand its dual nature and strike a balance. On the one hand, sustainable competition stimulates innovation and technological progress, nurtures talent, strengthens the nation 's qualification potential, contributing to China's emergence as a global economic centre. On the other hand, it leads to effort inflation, which can deprive employees of motivation and lead to their leaving abroad. With this in mind, the article formulates eight research hypotheses and builds two mathematical models. The first model considers this dual nature of internal overcompetition through a complex system of interdependent relationships that mediate its impact on human life as a stimulant (promoting self-discipline, resilience, increased self-esteem and self-confidence) and an inhibitor (relentless race for achievement, loss of joy in life). The second model also takes into account the role of family and encouragement from the immediate environment to reduce stress as a mediating variable. The study was based on a survey of 280 working adults in China aged 20 to 40 with less than six years of work experience. Answers to 14 questions were rated on the 5-point Likert scale. The data were analysed via IBM SPSS Version 26 and SPSS AMOS Version 26. The following statistical methods were used in the study: descriptive statistics, correlation analysis, factor analysis, and structural modelling. Data reliability was confirmed using the Cronbach 's alpha coefficient. The sample adequacy was confirmed using the Kaiser-Meyer-Olkin criterion. Convergent and discriminant validity was also confirmed. Four of eight research hypotheses were proven. Young professionals who previously faced competition in high school and university now face competition in society. To cope with this stress, they seek support from their families and effective organisational support; they find meaning in overcoming competition while making efforts. The study results form the basis for the development of support measures aimed at overcoming internal overcompetition. They provide valuable information on how to navigate the difficult conditions faced by the younger generation.

Keywords: overcompetition; involvement; Nei Juan; motivation; de-stress.



INTRODUCTION

Background of the study

In the latter half of 2020, a photo of a student in China riding a bicycle while writing or studying on a computer went viral on the internet, sparking various discussions among students in China. While it is applaudable for students to dedicate their limited time to study and to pursue progress, at the same time, it is challenging to comprehend the decision to study during such unconventional hours, especially while engaged in activities such as cycling (Johnson, 2023). This behaviour, occurring when concentration on both activities is difficult, not only affects traffic but also lacks consideration for personal and others' comfort, making it unsuitable for society (Jensen et al., 2023). This incident led people to term such irrational competitive behaviour as Nei Juan or “internal overcompetition” (Meng-ying, 2021).

Nei Juan, originally an academic term, is translated as “involution” in English. The concept of involution was developed by two anthropologists. One of them was Clifford Geertz, an American anthropologist who, based on research in rural Java, referred to a situation in which, due to population density, the only option for agricultural development in limited arable land is inward-focused development (White, 2007). The other anthropologist, Alexander Goldenweiser, described a phenomenon in which a certain cultural model, after reaching a certain final form, neither stabilises nor transforms into a new form but continuously becomes more complex internally (Geerts, 1984). In today's context, this refers to a phenomenon where individuals within the same group compete for limited resources, leading to a decrease in the individual's `effort-to-reward ratio', which can be seen as an “inflation” of effort (Wang & Subramaniam, 2023).

In contemporary China, internal overcompetition is severe, affecting both students and working professionals. For students, the impact reduces educational qualifications, making it challenging to secure employment, even for graduate students, resulting in physical and mental exhaustion. For working professionals, internal overcompetition has given rise to non-regular overtime work patterns, such as “996” or “007”, affecting physical well-being and causing stress and fatigue (Liu et al., 2020).

Measures are required to support the mental well-being of the generation leading the nation, ensuring that the alleviation of exhaustion and stress resulting from internal overcompetition does not contribute to the fatigue of China's market economy and social culture.



RESEARCH OBJECTIVES AND ORIGINALITY

In China's current context, in which the distinction between effort and internal overcompetition is not clear, internal overcompetition is a critical issue that needs consideration (Wang & Subramaniam, 2023) and, therefore, needs a clear definition. In China, extracurricular training institutions have emerged, since all students must pass the university entrance examination to enrol in college. Regardless of whether students enjoy studying, they choose to study at these extracurricular training institutions based on comparisons with their parents and other students (Liang, 2024). Consequently, these institutions have become excessively competitive, with unimaginably high prices for many families.

In China, a game called “Gaokao Warriors” has emerged, featuring the country's college entrance exam system, known as “Gaokao” (Howlett, 2023). The game satirically depicts high school students facing various challenges and monsters striving to improve their grades and enter their dream university (Young et al., 2023). The game has garnered attention for its humorous take on the rigorous Chinese education system (Howlett, 2023). Simultaneously, they deprive students of their time, not providing visible assistance or further exhausting them. This exhaustion exacerbates the phenomenon of internal overcompetition.

This study aims to identify crucial factors for alleviating stress and fatigue among young professionals in China with less than six years of work experience and to obtain guidelines for developing programmes to address internal overcompetition in China. The research involves extracting factors for stress reduction among workers through consulting and proposing frameworks for practical support. It seeks insights into the experiences of the young generation regarding overcompetition, explores considerations for desirable support measures and investigates how they perceive and cope with this issue internally. This study aims to provide insights and support for demanding conditions by examining how individuals navigate challenging environments.

The attempt to propose a framework for alleviating and supporting the stress associated with the internal overcompetition faced by the younger generation is this study's primary originality and contribution, aiming to provide practical insights. stress fatigue overcompetition

LITERATURE REVIEW

Current situation and challenges of overcompetition in China

Nei Juan is a Chinese concept that can be translated as “internal overcompetition” or “internal excessive competition”. It refers to a situation in which members of society excessively compete for a certain amount of resources or opportunities, leading to an inflation of effort. As a result, it becomes challenging for individuals to obtain the expected rewards. This concept mainly describes situations in Chinese society or educational systems in which intense competition and stress arise (Meng-ying, 2021).

To address this issue, on 24 July 2021, the Central Committee of the Communist Party of China and the State Council issued the “Opinions on Further Reducing the Burden of Homework and Extracurricular Training for Students in the Compulsory Education Stage” (Double Reduction Policy). This policy not only restricts extracurricular training institutions in China, which have been significantly impacted, but also aims to resolve internal overcompetition to some extent (Cheng & Chen, 2023). Additionally, the Chinese government has taken legal measures against phenomena such as workplace “996” and “007”, prohibiting companies from having such overtime events and implementing such practices. This policy indicates that the Chinese government is addressing the issue of internal overcompetition (Zhang, 2021).

However, due to resource shortages, the malicious formation of competition among individuals for comparison with others persists, multiplying the pressure on students and local communities and leading to a decline in motivation. It is challenging for the government's policies to immediately resolve the formation of vicious competition and the resulting decline in motivation, fatigue and stress, especially as people increasingly opt for a laid-back approach (Wang et al., 2024). If the aim is to address internal overcompetition, we believe that it is meaningful to consider not only the government's policy but also the causes of reduced motivation and the formation of fatigue and stress, neither of which can be resolved quickly.

The dual nature of competition: Light and shadow

China's intense competition presents a dual nature, embodying both positive and negative aspects. On the one hand, robust competition propels innovation, economic growth and technological advancements, shedding light on the nation's dynamism. This competitive drive fosters a climate where businesses strive for excellence, pushing boundaries and contributing to global progress. However, this fervent competition has a shadow side, marked by an overwork culture, as evidenced in the infamous “996” work schedule (Li, 2023). This dark aspect raises concerns about workers' well-being, leading the government to enact measures to address excessive overtime. Thus, while competition fuels China's ascent as a global economic powerhouse, the dual nature of its impact necessitates a delicate balance to harness its benefits while mitigating the adverse effects on individuals and society (Huang et al., 2023).

Especially for students caught in the whirlwind of competition, excessive competition can corrode their mental well-being, strip away motivation and lead to an exodus abroad. In contrast, it also stimulates and produces exceptional talents, contributing to the nation's foundation by producing a pool of skilled individuals.

Competition as bitterness of life

For the young generation poised at the centre of the whirlwind of competition, the relentless pursuit of success may cast competition as the bitter essence of life. The pressure to outperform peers, excel academically and secure coveted opportunities can create an environment in which competition becomes not only a mere facet of life but rather a pervasive force, defining the very essence of existence (Fei & Abdullah, 2023). In this narrative, the incessant demands of competition may seem to overshadow the joys of learning and personal growth, transforming life into a relentless race for achievement (Arnett, 2023).

For these young individuals, competition becomes an all-encompassing reality, potentially overshadowing life's diverse experiences and joys. The constant quest for success, often driven by societal expectations and the fear of falling behind, may transform the journey into a series of challenges and hurdles. However, it is crucial to recognise that competition also serves as a crucible for resilience, determination and skill development amid bitterness (Bolsinger, 2020). While acknowledging the challenges posed by overcompetition, it is essential to foster an environment that cultivates a balanced perspective, enabling young individuals to navigate the complexities of competition while preserving the richness and fulfilment of life's other dimensions (Williams, 2021).

Stress exhaustion and surrounding support

In the realm of stress exhaustion, the pivotal role of family and surrounding support becomes evident in alleviating the burdens of strain (Moberg et al., 2023). Stress, a pervasive aspect of modern life, can affect individuals both mentally and physically (Cianfarani & Pampanini, 2023). In this context, the unwavering support of family members and encouragement from one's immediate environment emerge as crucial antidotes. A robust family network serves as a sanctuary where individuals can freely express their concerns and find solace (Dufur et al., 2023). Moreover, understanding and empathy from friends and colleagues create a supportive atmosphere, fostering resilience and emotional well-being. The collective strength of familial and social bonds is a buffer against the deleterious effects of stress, providing individuals with the emotional scaffolding needed to navigate challenges and restore balance and calmness (Koehly and Manalel, 2023).

Rewards to oneself: Benefits of winning in competition

Winning in competition brings external recognition and yields valuable internal rewards. The journey of striving for success fosters self-discipline, resilience and a growth mindset (Noble et al., 2023). Achieving victory instils a sense of accomplishment, boosting self-esteem and confidence (Dewan & Dewan, 2023). Moreover, it cultivates a spirit of perseverance and the ability to overcome setbacks, essential attributes for personal development. The competitive arena becomes a training ground that hones individuals' skills and pushes them beyond their limits. The experience of winning teaches individuals to handle both success and failure gracefully, imparting valuable life lessons. Additionally, the joy and satisfaction derived from overcoming challenges contribute to a positive mental outlook (Arslan & Wong, 2023). Thus, the benefits of winning in competition extend beyond the accolades, enriching the individual with skills, character development and a resilient mindset that lasts far beyond the competitive moment.

METHODOLOGY

Modelling and hypotheses

Taking inspiration from these insights, this study has established the hypotheses and analytical model to be tested, as outlined in Figure 1.

Figure 1. Conceptual framework of the direct impact model

Source: Generated by the author (2024)

In this study, drawing from the insights of previous research, we incorporate the hypotheses on the significance of support from family and friends in reducing stress (Zhou et al., 2023). In addition to the model outlined in Figure 1, we establish a secondary model positioning the support factor as a mediating variable. This allows for a more detailed examination of the assumed relationships between the elements, aiming to scrutinise further the intricacies of these dynamics (Figure 2). The relevant hypotheses are summarised in Table 1.

Figure 2. The analytical model incorporating the mediating effect

Source: Generated by the author (2024)

Table 1 indicates the constructed hypotheses, which are described in Figure 2.

Table 1. Hypotheses of our study (authors' arrangement)

H number	Hypotheses
H1	“The dual nature of competition: Light and shadow” has a significant impact on “Rewards to oneself: Benefits of winning in competition”.
H2	“Competition as bitterness of life” has a significant impact on “Rewards to oneself: Benefits of winning in competition”.
H3	“The dual nature of competition: Light and shadow” and “Competition as bitterness of life” have a mutual relationship.
H4	“The dual nature of competition: Light and shadow” has a significant impact on “Stress exhaustion and surrounding support”.
H5	“Competition as bitterness of life” has a significant impact on “Stress exhaustion and surrounding support”.
H6	“Stress exhaustion and surrounding support” has a significant impact on “Rewards to oneself: Benefits of winning in competition”.
H7	“The dual nature of competition: Light and shadow” has an indirect effect on “Rewards to oneself: Benefits of winning in competition” through “Stress exhaustion and surrounding support”.
H8	“Competition as bitterness of life” has an indirect effect on “Rewards to oneself: Benefits of winning in competition” through “Stress exhaustion and surrounding support”.

Source: Generated by the author (2024)

Data collection and analysis

In this paper, we used the quantitative analysis. A questionnaire survey was conducted among 280 working adults in China between the ages of 20 and 40. The survey included 14 questions, which were answered on a 5- point Likert scale (South et al., 2022; Batterton and Hale, 2017). The raw data were analysed using IBM SPSS Version 26 and SPSS AMOS Version 26. Using descriptive statistics, correlation, factor analysis and structural equation modelling (SEM), we analysed and evaluated the constructed model with measurements.

Data analysis and the method justification

The raw data were analysed using IBM SPSS Version 26 and SPSS AMOS Version 26. The analysis encompassed various statistical techniques, including descriptive statistics, correlation analysis, factor analysis and SEM. In-depth scrutiny and assessment of the constructed model and associated measurements were conducted as a part of our analytical approach.

Several advantages in data analysis can be highlighted to justify the use of SEM. First, SEM allows for a comprehensive assessment of the complex relationships among multiple variables. This extends beyond simple correlations and accommodates causal relationships and modelling of latent concepts.

SEM also enables simultaneous estimation of observed variables and the latent structural model, extracting rich information from the data. This method is particularly effective when multiple indicators and latent variables are intricately interconnected.

Furthermore, by considering error terms and adjusting the goodness-of-fit of the model, SEM allows for more realistic modelling (Oe and Yamaoka, 2023). This capability enhances the accuracy of assessing how well-observed data align with the theoretical structure. SEM is particularly beneficial when delving into the theoretical modelling and alignment of empirical data in complex datasets. It facilitates researchers in conducting more comprehensive and refined data analysis, ultimately providing deeper theoretical insights.

RESULTS

Data profile

The data profile is succinctly described here. A meticulous consideration of balance across attributes facilitated the collection of a targeted sample of 280. This achievement aligns with the intended goal outlined in the paper.

Table 2. Demographic profile

Profile	Frequency	Percentage (%)	Cumulative percentage (%)
Gender
Female	100	35.7	35.7
Male	180	64.3	100.0
Total	280	100.0
Age
20-24	29	10.4	10.4
25-29	91	32.5	42.9
30-34	124	44.3	87.1
35-39	29	10.4	97.5
40s	7	2.5	100.0
Total	280	100.0
Education
Junior High	4	1.4	1.4
High school	13	4.6	6.1
Career college	36	12.9	18.9
University	206	73.6	92.5
Grad school	21	7.5	100.0
Total	280	100.0

Source: Generated by the author (2024)

Table 3 provides descriptive statistics of the subject evaluations in this research through the Likert scale among the collected data.

Table 3. Descriptive analysis

Questionnaire	N	Min.	Max.	Mean	Dev.
9. I am impatient and worried because of internal hypercompetition.	280	1	5	3.51	1.087
10. Internal hypercompetition has had a significant impact on your life.	280	1	5	3.46	1.097
11. Do you think internal hypercompetition is something you do not like because your efforts are wasted?	280	1	5	3.47	1.185
12. Do you dislike internal hypercompetition with those around you?	280	1	5	3.47	1.120
13. Do you think internal hypercompetition does not contribute to your ambition?	280	1	5	3.10	1.185
14. I think internal hypercompetition has both positive and negative aspects.	280	1	5	3.63	1.172
15. I think internal hypercompetition is a problem, and I will do something to solve it.	280	1	5	3.52	0.994

The physical and mental exhaustion caused by 280 1 5 3.15 1.299

internal hypercompetition is a stressful memory for me,

even after I have found a job. Ill I

Internal hypercompetition has made me think that 280 1 5 3.25 1.252

competing wastes time.

As a student, internal excessive competition 280 1 5 3.26 1.239

exhausted me both mentally and physically, but I had

friends, parents and siblings who supported me.



Table 3 (cont.). Descriptive analysis

Questionnaire	N	Min.	Max.	Mean	Dev.
19. When I was a student, I was exhausted both mentally and physically due to internal hypercompetition, and I wish there had been supportive services, such as consultation services and consultants.	280	1	5	3.07	1.235
20. I survived internal over-competitiveness and am where I am today because I boldly took on the competition.	280	1	5	3.28	1.164
21. I want to praise myself for winning excessive internal competition and getting a job.	280	1	5	3.31	1.152
22. I am satisfied with my life now that I got a job after winning internal competition.	280	1	5	3.26	1.241

Notes: N - number of respondents; Min. - minimum value; Max. - maximum value; Mean - average value; Dev. - deviation

Source: Generated by the author (2024)

Next, to confirm the absence of multicollinearity in the multivariate analysis, we examined the correlations among the candidate items assumed as latent variables in the SEM analysis. As shown in Table 4, all observed variables were reasonably related to each other without showing very high correlations. Thus, these variables may be candidates for further analysis.

Table 4. Correlation diagram

Q9	Q10	Q11	Q12	Q13	Q14	Q15	Q16	Q17	Q18	Q19	Q20	Q21	Q22
Q9 Pearson Correlation 1
Sig. (2-tailed)
Q10 Pearson Correlation	.508**	1
Sig. (2-tailed)	0.000
Q11 Pearson Correlation	.452**	.497**	1
Sig. (2-tailed)	0.000	0.000
Q12 Pearson Correlation	.467**	.467**	.602** 1
Sig. (2-tailed)	0.000	0.000	0.000
Q13 Pearson Correlation	.362**	.300**	.471**	.428**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000
Q14 Pearson Correlation	.440**	.478**	.324**	.357**	.193**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.001
Q15 Pearson Correlation	.470**	.560**	.431**	.424**	.240**	.499** 1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000
Q16 Pearson Correlation	.322**	.373**	.428**	.458**	.430**	.276**	.346**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q17 Pearson Correlation	.328**	.312**	.309**	.327**	.369**	.223**	.285**	.610**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q18 Pearson Correlation	.345**	.371**	.366**	.408**	.475**	.208**	.297**	.586**	.503**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q19 Pearson Correlation	.278**	.279**	.265**	.373**	.443**	.263**	.301**	.597**	.548**	.574** 1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q20 Pearson Correlation	.358**	.292**	.374**	.396**	.374**	.251**	.362**	.476**	.427**	.457**	.428**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q21 Pearson Correlation	.356**	.333**	.371**	.398**	.391**	.389**	.403**	.446**	.423**	.420**	.378**	.503**	1
Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Q22 Pearson Correlation	.299**	.286**	.329**	.376**	.425**	.313**	.334**	.454**	.479**	.420**	.442**	.523**	.510**	1

**. Correlation is significant at the 0.01 level (2-tailed).

Source: Generated by the author (2024)

FACTOR ANALYSIS

A factor analysis was performed on the data set from which multicollinearity was eliminated to prepare the SEM (Kyriazos & Poga, 2023). Cronbach's alpha was also evaluated for each generated factor (Table 5). The 14 questions presented in Table 5 resulted in the generation of four factors. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.920, and the rotation sums of squared loadings were 67.40%.

The first factor, comprising four questions, is named “Stress exhaustion and surrounding support”. The second factor, composed of four questions, is “The dual nature of competition: Light and shadow”. The third factor, consisting of three questions, is named “Competition as bitterness of life”. The fourth factor, made up of three questions, is named “Rewards to oneself: Benefits of winning in competition”. The reliability coefficients (alpha) for each factor are 0.841, 0.793, 0.749 and 0.758, respectively, all indicating reliability above 0.7, ensuring the reliability of the data (Bonett & Wright, 2015; Roberts and Priest, 2006; Cole, 1987).

Table 5. Factor analysis Observed variance 1 2 19. When I was a student, internal hypercompetition 0.797 0.138 exhausted me mentally and physically, but I wish there had been supportive services, such as consultation services and consultants.	3 0.110	4 0.213	Alpha Factor 0.841 Stress, exhaustion and surrounding support
16. The physical and mental exhaustion caused by internal hypercompetition is a stressful memory for me, even after I have found a job.	0.744	0.194	0.256	0.227
17. Internal hypercompetition has made me think that competing is a waste of time.	0.744	0.168	0.072	0.280
18. When I was a student, excessive internal competition exhausted me mentally and physically; however, I had friends, parents and siblings who supported me.	0.714	0.118	0.321	0.187
14. I think internal hypercompetition has both positive and negative aspects.	0.077	0.787	-0.006	0.257	0.793 The dual nature of competition: Light and shadow
15. I think internal hypercompetition is a problem, and I will do something to solve it.	0.149	0.752	0.163	0.222
10. Internal hypercompetition has had a significant impact on your life.	0.242	0.721	0.348	-0.021
9. I am impatient and worried because of internal hypercompetition.	0.159	0.587	0.417	0.135
11. Do you think internal hypercompetition is something you do not like because your efforts are wasted?	0.121	0.332	0.774	0.154	0.749 Competition as bitterness of life
12. Do you dislike internal hypercompetition with those around you?	0.216	0.351	0.672	0.189
13. Do you think internal hypercompetition does not contribute to your ambition?	0.347	-0.031	0.666	0.302
22. I am satisfied with my life now that I got a job after winning internal competition.	0.321	0.146	0.158	0.737	0.758 Rewards to oneself: Benefits of winning in competition
21. I want to praise myself for winning excessive competition and getting a job.	0.218	0.292	0.174	0.720
20. I survived internal over-competitiveness and am where I am today because I boldly took on the competition.	0.303	0.144	0.247	0.681

Notes: Extraction method: Principal component analysis Rotation method: Varimax with Kaiser normalisation

Rotation converged in seven iterations.

Source: Generated by the author (2024)

Convergent and discriminant validity test

We performed convergent and discriminant validity tests. The results are shown in Table 6.

In Table 6, N is the number of samples, Mean is the mean of each factor, SD is the standard deviation, Alpha is Cronbach's alpha, CR is composite reliability, AVE is the mean-variance standard and the bold values on the main diagonal are the square root of AVE (Cable et al., 2002; Cheung et al., 2017).

All CR values are greater than or equal to 0.5, indicating that there are no data reliability issues (Hayes, 2015).

Table 6. Convergent and discriminant validity test

	N	Mean	SD	Alpha	CR	AVE	F1	F2	F3	F4
Factor 1	280	3.182	1.034	0.841	0.837	0.563	0.750
Factor 2	280	3.530	0.856	0.793	0.798	0.568	0.462**	0.754
Factor 3	280	3.346	0.950	0.749	0.748	0.374	0.577**	0.582**	0.611
Factor 4	280	3.282	0.974	0.758	0.756	0.763	0.648**	0.510**	0.569**	0.837

Notes: **p < 0.01.

Notes: N - number ofsamples; Mean - mean of each factor; SD - standard deviation; Alpha - Cronbach's alpha; CR - composite reliability; AVE - mean-variance standard. The bold values on the main diagonal are the square root of AVE.

Source: Generated by the author (2024)

Test validations were performed to assess how newly developed scales or tests aligned with other relevant scales or tests (convergent validity) and simultaneously differentiate them from measures of different constructs (discriminant validity) (Cheung et al., 2023). Specifically, the aim was to confirm that different scales measuring the same construct aligned with each other and were simultaneously distinct from scales measuring different constructs (Campbell & Fiske, 1959).

These validations were carried out to evaluate the validity of the measurement tools or tests and to ensure reliability. As a result of these tests, the newly generated scale demonstrated high alignment with existing scales, indicating convergent validity. At the same time, it exhibited discrimination from measures of different constructs. Based on these results, the scale adopted in this study can be considered effective for further analysis.

STRUCTURAL EQUATION MODELLING

Direct model

Based on the preliminary results of the tests, the SEM approach was used (Pituch and Stevens, 2015). Figure 3 shows the results of the SEM calculations based on the conceptual framework of the direct model shown in Figure 1. The values representing the validity of the SEM are chi-square/degrees of freedom of 1.711 (chi-square = 54.767, df = 32), GFI is 0.963 (> 0.9), AGFI is 0.939 (> 0.9), CFI is 0.977 (> 0.9) and RMSEA is 0.050 (< 0.08) within each limit. This means that the model is valid (Oe and Yamaoka, 2023; Guo 2022; Cheung et al., 2017; Hayes, 2015; Babin and Svensson, 2012).

Now, the latent factor “The dual nature of competition: Light and shadow” as Factor 1 to “Rewards to oneself: Benefits of winning in competition” as Factor 3 has a path coefficient of 0.246 (*p < 0.05). Next, the path from “Competition as bitterness of life” as Factor 2 to “Rewards to oneself: Benefits of winning in competition” has a path coefficient of 0.528 (***p < 0.001). The path connecting the covariance between “The dual nature of competition: Light and shadow” and “Rewards to oneself: Benefits of winning in competition” has a path coefficient of 0.775 (***p < 0.001), indicating a mutual relationship. As described above, the analysis in Step 1 confirms that the hypothesis is supported (Table 7).

Figure 3. SEM results in Step 1

Source: Generated by the author (2024)

Table 7. Path coefficient for Step 1

To	From	Std. Regression weights	P
Rewards to oneself: Benefits of winning in competition	<---	The dual nature of competition: Light and shadow	0.246	*
Rewards to oneself: Benefits of winning in competition	<---	Competition as bitterness of life	0.528	***
DNC1	<---	The dual nature of competition: Light and shadow	0.637	1fix
DNC2	<---	The dual nature of competition: Light and shadow	0.692	***
DNC3	<---	The dual nature of competition: Light and shadow	0.750	***
DNC4	<---	The dual nature of competition: Light and shadow	0.729	***
CBL1	<---	Competition as bitterness of life	0.773	1fix
CBL2	<---	Competition as bitterness of life	0.770	***
CBL3	<---	Competition as bitterness of life	0.592	***
ROB1		Rewards to oneself: Benefits of	0.707	1fix
		winning in competition
ROB2		Rewards to oneself: Benefits of	0.714	***
		winning in competition
ROB3	<---	Rewards to oneself: Benefits of winning in competition	0.725	***
Competition as bitterness of life	<-->	The dual nature of competition: Light and shadow	0.775	***

Note 1: *p < 0.05, **p < 0.01, ***p < 0.001.

Note 2: DNCx is an observed variable of the dual nature of competition: light and shadow. CBLx is an observed variable of the competition as bitterness of life. ROBx is an observed variable of the reward to oneself: benefits of winning in competition.

Note 3:1fix means that the coefficient is fixed at 1.

Source: Generated by the author (2024)

In Step 1, we created a very simple delta-shaped model that shows “internal overcompetition”. It consists of three latent factors: “The dual nature of competition: Light and shadow (DNC)” and “Competition as bitterness of life (CBL)” towards “Rewards to oneself: Benefits of winning in competition (ROB)”. In the actual competition world, however, there is someone's support or advice. Therefore, in Step 2, we attempted to analyse a model that approximates the real world, including “stress exhaustion and surrounding support”.

Figure 4 shows the Step 2 model. We observed a necessary latent factor, which is “stress exhaustion and surrounding support (SES)” before “Rewards to oneself: Benefits of winning in competition” as a latent factor (ROB).

Mediating role model

The tools used are IBM SPSS v26 and AMOS v26. Boots strap was used 5,000 times. The respective values for the validity of the SEM are chi-square/degrees of freedom of 1.560 (chi-square = 111.383, df = 71), GFI is 0.948 (> 0.9), AGFI is 0.922 (> 0.9), CFI is 0.975 (> 0.9), and RMSEA is 0.045 (< 0.08), within each limit. This means that the model is valid (Oe and Yamaoka, 2023; Guo 2022; Cheung et al., 2017; Hayes, 2015; Babin and Svensson, 2012).

Overlooking the path from the same latent factor as Step 1, DNC to ROB has a path coefficient of 0.177 (p > 0.05, which means it is not significant), (Lower -0.008, 1.405). Next, CBL to ROB has a path coefficient of 0.186 (p > 0.05, which means it is not significant), (Lower -0.514, Upper 1.044). This phenomenon shows that the two latent factors of DNC and CBL have no significant relationship with ROB. The covariance path between DNC and CBL has a path coefficient of 0.775 (***p < 0.001), which means these two have a strong mutual relationship.

All these data are shown in Table 8.

Now, considering the path over SES, the most important issue in Step 2, the path coefficient for DNC to SES has a path coefficient of 0.082 (p > 0.05, which means it is not significant) (Lower -0.508, 1.020). Next, CBL to SES has a path coefficient of 0.632 (**p < 0.01), (Lower -0.224, Upper 1.305). This means that only CBL to SES is significant.

Next, SES to ROB has a path coefficient of 0.576 (***p < 0.001) (Lower 0.335, Upper 0.806). This means that the only path of CBL to SES to ROB is significant. Moreover, we observed indirect effect from DNC to ROB through SES and CBL to ROB through SES. DNC to ROB is 0.177 (p > 0.05) (Lower -0.169, Upper 0.210), which is not significant. The path coefficient for CBL to ROB is 0.364 (***p < 0.001) (Lower -0.179, Upper 0.650), which is significant. The results of this analysis present a relief factor for the real world of competition.

The R2 of the latent factor for SES is 0.494, and ROB is 0.733, which is high, indicating a strong correlation in this model. Therefore, the model concretely and theoretically shows that strengthening SES in the real competition world strengthens ROB.

Figure 4. SEM results in Step 2

Source: Generated by the author (2024)

Table 8. Path coefficient for Step 2

Direct path	95% PC
To	From	Std. regression weights	P	Lower	Upper
Stress exhaustion and surrounding support	<-- -	The dual nature of competition: Light and shadow	0.082	0.521	-0.292	0.342
Stress exhaustion and surrounding support	<-- -	Competition as bitterness of life	0.632	***	0.356	1.002
Rewards to oneself: Benefits	<--	Stress exhaustion and	0.576	***	0.335	0.806
of winning in competition	-	surrounding support
Rewards to oneself: Benefits of winning in competition	<-- -	The dual nature of competition: Light and shadow	0.177	0.117	-0.106	0.468
Rewards to oneself: Benefits of winning in competition	<-- -	Competition as bitterness of life	0.186	0.176	-0.178	0.546
	<--	The dual nature of
DNC1		competition: Light and	0.692	***
		shadow
	<--	The dual nature of
DNC2		competition: Light and	0.727	***
		shadow
	<--	The dual nature of
DNC3		competition: Light and	0.635	1fix
		shadow
	<--	The dual nature of
DNC4		competition: Light and	0.752	***
		shadow
CBL1	<-- -	Competition as bitterness of life	0.758	1fix
CBL2	<-- -	Competition as bitterness of life	0.768	***
CBL3	<-- -	Competition as bitterness of life	0.612	***
SES1	<--	Stress exhaustion and	0.741	1fix
	-	surrounding support
SES2	<--	Stress exhaustion and	0.814	***
	-	surrounding support
SES3	<--	Stress exhaustion and	0.737	***
	-	surrounding support
SES4	<--	Stress exhaustion and	0.728	***
	-	surrounding support
ROB1	<--	Rewards to oneself: Benefits	0.717	1fix
	-	of winning in competition
ROB2	<--	Rewards to oneself: Benefits	0.721	***
	-	of winning in competition
ROB3	<--	Rewards to oneself: Benefits

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