Promoting Sustainable Development of Organizations: Performance Pressure, Workplace Fun, and Employee Ambidextrous Innovation

Abstract

In the context of an economic downturn, organizations need to continuously improve their performance requirements for employees, and in the macro environment of intensified competition, organizations need to continuously motivate employees to innovate in order to seize development opportunities. Flexibly adjusting to the internal pressure of an organization while ensuring organizational vitality can promote employee adaptive growth and achieve sustainable development in the organization. However, the impact of performance pressure on employee ambidextrous innovation is currently unknown. Based on this, this article explores the positive effects of performance pressure in influencing employee ambidextrous innovation through job involvement from the perspective of Affective Events Theory and uses workplace fun as a moderating variable in order to analyze the internal logic of long-term motivation for employee ambidextrous innovation in organizations. This article conducted a survey and analysis of 362 in-service employees in enterprises and institutions and found the following: (1) performance pressure has a significant positive impact on employee ambidextrous innovation; (2) job involvement plays a partial mediating role between performance pressure and exploratory innovation; (3) workplace fun has a moderating effect on the relationship between job involvement and exploitative innovation, and the higher the level of workplace fun, the stronger the positive impact of job involvement on exploitative innovation.

1. Introduction

In the macro environment of an economic downturn, external pressure forces organizations to improve their performance requirements internally [1]. In the increasingly fierce competition, organizations rely on employees to make broader and deeper innovation to seize the opportunities of the times. Employee innovation behavior has become a source of organizational innovation [2]. In order to achieve the dual development of performance and innovation, many organizations have begun to set high-performance goals for employees to promote their development. After feeling the external forces exerted by these organizations, employees will realize the need to improve their performance in order to avoid adverse consequences in the workplace; this subjective perception caused by external forces is called performance pressure [3,4]. Is performance pressure, which combines high risks and high requirements, promoting or inhibiting employee innovation? Different scholars have different views, and it is of practical significance to scientifically use performance pressure management to ensure organizational vitality and promote employee adaptive growth, promote the sustainable development of organizations and enterprises, and clarify the impact of performance pressure on employee innovation [5]. Previous studies have shown that performance pressure is an effective means of influencing employee innovation; this results-oriented work environment enables employees to better utilize and create knowledge [6]. Therefore, when organizations apply appropriate performance pressure, the creativity, innovation behavior, and innovative performance of employees will all be improved [7,8]. However, some studies have also pointed out that under high performance pressure, employees’ attention will shrink, and individuals will shift from a broad team perspective to a narrow self-attention perspective [9]. The weakening of cognitive function will lead to poorer performance in employees [10]. Employees with high levels of stress are more likely to feel fatigued and perform worse [11], which is not conducive to the emergence of innovation behavior.

From this, it can be seen that there are conflicting views on how performance pressure affects innovation, and some scholars have proposed that classifying innovation behavior for analysis may be the key to explaining this phenomenon [12]. Ambidextrous innovation behavior is essentially a collection of two types of innovation behaviors [13], which is a classification method of innovation behavior at the individual level, and has many similarities with ambidextrous innovation at the enterprise level, as it includes exploratory innovation and exploitative innovation [14]. Individuals need to continuously expand their current knowledge range when engaging in exploratory innovation, while in exploitative innovation, they basically only need to utilize their existing knowledge base; the novelty levels of the two types of innovation are different [15]. Inspired by this, we began to ponder how performance pressure can affect employee ambidextrous innovation behavior. On the one hand, we hope to explore the differences in the impact of performance pressure on different types of innovation. On the other hand, a recent study calls for exploring the triggering factors of high ambidextrous innovation among employees [14]. Existing research has not revealed the mechanism of the relationship between performance pressure and employee ambidextrous innovation. To address these issues, this study will discuss the impact mechanism and boundary conditions of individual-level performance pressure on employee ambidextrous innovation based on Affective Events Theory.

The Affective Events Theory suggests that affective events in the workplace can have an impact on employees’ attitudes and behaviors by triggering affective reactions [16]. Based on this, this article proposes that performance pressure, as an affective event in the workplace, can influence employees’ innovative behavior by forming an affective reaction. Existing research has shown that job involvement is one of the output outcomes of pressure [17] and an important mediating variable in the mechanism of innovation behavior [18]. Job involvement represents an individual’s psychological feeling of identifying with work, being willing to actively participate in work, and being very focused [19,20]. High levels of job involvement can positively predict employees’ creativity, so job involvement may be an affective reaction mediating the relationship between performance pressure and employee ambidextrous innovation.

In addition, a management approach that balances relaxation and leniency is more conducive to ensuring the long-term effectiveness of incentive mechanisms and promoting the establishment of sustainable organizations [21]. Ensuring the well-being of employees is one of the important measures in response to the United Nations Sustainable Development Goals [22]. Therefore, in addition to promoting employee innovation through appropriate pressure, it is also necessary for organizations to inject motivation into employees and provide them with support and encouragement. Recent research on Affective Events Theory has also found that the external situational factors of organizations can affect the relationship between employee affective reactions and work attitudes or behaviors [23]; workplace fun is a workplace characteristic that can make employees feel happy [24]. Existing research has shown that workplace fun, as an external motivating factor, can help employees engage in more innovative behaviors in a state of job involvement by enhancing their level of focus at work, promoting informal learning behaviors in the workplace, and creating a relaxed work atmosphere that is error-tolerant [25]. In an environment with a high level of workplace fun, employees will develop higher levels of innovation performance [26], creativity [27], and innovative behavior [28]. The moderating effect of workplace fun on employee innovation has not been studied yet; therefore, this study attempts to propose that workplace fun may be an external situational factor that can moderate the relationship between job involvement and employee ambidextrous innovation.

In summary, this study constructs an impact model on performance pressure and employee ambidextrous innovation behavior based on Affective Events Theory in the context of intensified external competition and the pursuit of sustainable development by enterprises [2]. Based on the Affective Events Theory of “work events—affective reactions—attitudes & behaviors” as the main influencing pathway [16], this study introduces the individual psychological factor of job involvement as a mediating variable and the organizational situational factor of workplace fun as a moderating variable in the mechanism model of employee performance pressure on ambidextrous innovation. The aim is to explain why some employees can perform well in innovation behavior under performance pressure, deepen the analysis of the relationship between performance pressure and employee ambidextrous innovation, and discuss specific measures to promote sustainable development of the organizations.

Finally, the organization of this study is as follows: Section 2 presents the theoretical framework and research hypotheses; Section 3 introduces the methodology of this study; Section 4 presents the results of empirical analysis; and Section 5 discusses the research results, theoretical significance, and practical implications and points out the limitations and future prospects of the study.

2. Theoretical Framework and Hypotheses

2.1. Affective Events Theory

Weiss and Cropanzano proposed the Affective Events Theory (AET) in 1996, which originated from research on job satisfaction and was used to explore the causal relationship between emotional experiences related to work [16]. The Affective Events Theory emphasizes that the characteristics of the work environment will affect attitudes and behaviors through individual affective reactions, forming a complete chain of “work events—affective reactions—attitudes & behaviors”. Affective reactions will play a mediating role in the relationship between work events and employee work attitudes and behaviors [29]. The behaviors influenced by affective events can be divided into judgment-driven behaviors and affective-driven behaviors, with different paths of influence. Affective-driven behaviors are directly influenced by affective reactions and do not exert effects through the path of work attitudes, while judgment-driven behaviors are the decision results generated after affective influence on work attitudes, and this influence mechanism is relatively complex.

Both the Attribution Theory of Emotion and the Cognitive Evaluation Theory of Emotion believe that cognitive evaluation determines the generation of emotions. Inspired by this content [30], the Affective Events Theory also believes that individuals will make initial and secondary evaluations of work events. In the initial evaluation stage, comprehensive evaluations are made based on factors such as individual goals and event values. Therefore, work events with less impact are only excluded by individuals in the initial evaluation stage and do not induce affective reactions. Only events that have a significant impact on individual goals and bring significant value or conflict will enter the main pathway of Affective Events Theory. Whether work events are positive or negative depends on an individual’s judgment [31]; therefore, the level of individual traits also determines the relationship between work events and affective reactions. In this theory, there is a difference between emotion and mood. The former has a short diffusion time and clear triggering factors, while the latter has a long diffusion time and unclear triggering factors. The differences in emotion and mood also determine the different impacts of work events [16].

In addition, the Affective Events Theory also distinguishes the impact of work environment characteristics. Work environment characteristics can induce affective events to trigger employee affective reactions and affect their work attitudes, which are influenced through affective pathways. In addition, individuals can also compare the characteristics of their work environment with their personal traits, directly forming their work attitudes without affecting them through affective reactions—that is, directly influencing employee behaviors and attitudes through nonemotional pathways [32]. Although individual traits have been proven to be a significant moderating factor in the relationship between work events and affective reactions, with the deepening and evolution of theory, studies have found that organizational contextual factors such as organizational culture can also moderate the relationship between affective reactions and employee attitudes and behaviors [23].

2.2. Performance Pressure and Employee Ambidextrous Innovation

Performance pressure is a specific type of work pressure that can be foreseen in the early stages of work compared to occasional pressures such as time and risk. It focuses more on factual outcomes and is linked to significant career outcomes for employees [33]. Under high-performance goals, individuals need to achieve their ideal goals while avoiding negative outcomes [34]. On the one hand, individuals believe that high performance can be used for expected returns, and external incentives create a firm belief in the necessity of pursuing outstanding performance. However, at the same time, the heavy pressure experienced behind such high demands, or the desire to achieve performance goals, will gradually internalize into a sense of urgency [4,33].

The impact of performance pressure on employees is complex. When employees are under significant pressure, it can cause long-term negative effects, such as deteriorating personal health and psychological conditions [35], weakening happiness [36], and employees themselves developing anxiety about the workplace [37]. This leads to a series of negative behaviors such as dishonesty, impoliteness, and deception [37,38]. Although performance pressure can bring certain negative impacts, once an organization lacks pressure, it will stagnate [39]. Many studies have shown that performance pressure can stimulate work enthusiasm and promote production behavior [40]. Some research results show that the positive impact of performance pressure is greater than the negative impact [41]. In particular, the implementation of performance pressure by organizations has a significant promoting effect on employee innovation [7,12].

Existing research has confirmed that work pressure can cause changes in individual attention [42], and work focus is a major prerequisite for innovative behavior. Innovation requires acquiring new knowledge and perspectives, and deep thinking based on the current situation will help individuals find ways to improve their existing work. Therefore, performance pressure will positively promote the generation of creativity [7]. Under performance pressure, employees will focus on tasks and use higher-order skills to perform more innovative behaviors [43]. Performance pressure seems to be a positive influencing factor, as individuals are more likely to gain a sense of value in overcoming difficulties when facing pressure that is conducive to work performance and career development [44]. Focusing on the field of ambidextrous innovation, although there is not much discussion on the relationship between performance pressure and ambidextrous innovation, existing research consistently explains the impact of performance pressure on employee ambidextrous innovation from the perspective of stress cognitive evaluation [45]: the evaluation of performance pressure by individuals determines the impact of performance pressure. When individuals perceive performance pressure as a job threat, they choose exploitative innovation with lower risk and better implementation. When individuals perceive performance pressure as a job challenge, they choose exploratory innovation with higher risk, and performance pressure will have a positive impact on ambidextrous innovation through different evaluation paths [12]. Overall, pressure can stimulate employees to showcase their own abilities, focus on work issues themselves, and engage in more exploration and learning, thereby positively affecting their exploratory and exploitative innovation. Based on the above considerations, this study proposes the following hypotheses:

H1a. 

Performance pressure has a significant positive impact on employee exploratory innovation behavior.

H1b. 

Performance pressure has a significant positive impact on employee exploitative innovation behavior.

2.3. Performance Pressure and Job Involvement

Performance management is an important tool in the practice of enterprise human resource management, which combines evaluation traits and development traits. Evaluation traits are used to assess the past performance of employees, while development traits are used to provide assistance for future performance improvement. Overall, the fundamental purpose of organizations adopting performance management is to help improve employee abilities and achieve organizational expectations [46]. A workplace that values employee performance is conducive to creating a collaborative atmosphere where colleagues work together with a relatively higher level of interpersonal trust [47]. Therefore, work pressure under performance management contains many positive meanings.

When facing high job requirements, employees will go through two stages: internalization and externalization. During the internalization stage, the employee will improve their adaptability, while during the externalization stage, the employee will strengthen information collection and thinking related to work [48]. The greater the performance pressure, the more employees need to focus on completing their work [49], which will enhance their learning motivation and encourage them to invest. This kind of work pressure can bring urgent emotional feelings to employees and motivate them to perform better. Referring to the Affective Events Theory, when affective events such as performance pressure act on individuals, they will then generate their own judgments about work and form their own affective reactions towards work. This study suggests that the psychological response of actively valuing performance evaluation goals, having sufficient learning motivation, and focusing on completing work under such performance pressure is very similar to the content of job involvement.

Job involvement is a positive affective response, and existing research has shown that individual characteristics, situational characteristics, and organizational supervisory behaviors can all affect job involvement [50]. In today’s increasingly competitive environment, the demand for self-development and continuity among employees is becoming stronger [51]. This study discusses the relationship between performance pressure and job involvement from the perspective of meeting employee needs, which is a positive influencing factor of performance pressure.

Firstly, performance pressure usually corresponds to clear performance goals. After achieving these goals, individuals can receive given compensation and benefits, such as performance-based pay and bonuses. Tangible rewards will directly improve employee job satisfaction and increase job recognition. This informational performance perception will enhance an individual’s willingness to put in extra effort [52]. In addition, behind performance goals, there is also an individual’s concern for career development, reflecting the importance that employees attach to performance, which belongs to intrinsic motivation. Behind this, a series of psychological perceptions, such as pride and expectations, will affect an individual’s level of involvement [46]. Therefore, from the perspective of value identification, high performance pressure can enhance employees’ internal motivation, increase their level of emphasis on work, and thus affect their level of involvement in work [53].

Secondly, the emergence of performance pressure means that employees are still far from achieving their goals. Individual achievement orientation will stimulate the motivating effect of performance pressure on employees, making them want to improve themselves and focus on their work. Under clear direction, it will generate stronger organizational contribution motivation [37]. Performance pressure can make employees aware that they have not yet met organizational requirements, so they will continue to learn and grow, focus on their work, and improve performance through their own actions [54]. Therefore, it is necessary to enhance job involvement. Based on the above considerations, this study proposes the following hypothesis:

H2. 

Performance pressure has a significant positive impact on job involvement.

2.4. The Mediating Role of Job Involvement

Existing research has found a complex mediating mechanism between pressure and innovation [55,56]. Job involvement is the output of pressure [17], and job involvement is an important mediator in the process mechanism of innovation behavior [18]. High levels of job involvement can positively predict the level of creativity of employees. The Affective Events Theory suggests that an affective reaction is a mediating variable between work events and work behaviors. Performance pressure, as an external force that causes internal emotional perception, belongs to affective events and will affect employee behaviors by forming work-affective reactions.

Job involvement is a state in which an individual psychologically identifies with work, expressing the relationship between the individual and the job and reflecting the level of employee focus and engagement in the job. The potential benefits of performance pressure lie in the ability for employees to gradually enhance their self-worth while overcoming difficulties related to performance pressure [57], thereby making individuals psychologically more accepting of their work, willing to focus and devote themselves to it, and thus increasing their level of job involvement. The increase in job involvement can give employees a stronger sense of meaning, thus motivating them to give more effort [58]. When individuals are solving work problems, the more they invest and focus, the more they are able to avoid the influence of external factors. This thinking state will be conducive to the burst of creativity, thereby enhancing employee creativity [59,60]. Assessing the threat of performance pressure can also help employees focus more on limited and clearly defined performance goals, even if their emotions are negative, it can still enhance their focus [61]. Employees who are highly involved in work have also been shown to exhibit a higher level of work identity and are willing to actively engage in existing work and generate a willingness to improve. These employees are more likely to demonstrate relatively high endurance, and a focus on work will enable them to perform better in innovation [62].

Both exploratory innovation and exploitative innovation represent innovative changes based on existing foundations, with only differences in knowledge learning and novelty. Therefore, overall, performance pressure will have a beneficial impact on ambidextrous innovation. However, the novelty level and risk level of exploratory innovation and exploitative innovation are different, so there are also differences in their intrinsic driving motivations [63]. Performance pressure helps employees with learning, stimulates exploration and trial and error, and triggers creative thinking. Therefore, we believe that job involvement plays a mediating role in the relationship between performance pressure and employee ambidextrous innovation, and this mediating role will be more evident in the impact path of exploratory innovation with stronger trial-and-error learning requirements. Based on the above considerations, this study proposes the following hypotheses:

H3a. 

Job involvement plays a mediating role between performance pressure and employee exploratory innovation.

H3b. 

Job involvement plays a mediating role between performance pressure and employee exploitative innovation.

2.5. The Moderating Effect of Workplace Fun

With the gradual development of the Affective Events Theory, scholars have gradually discovered that organizational or macro-environmental factors can moderate the effects of affective events [64]. The organizational environment has the potential to have a long-term positive impact [65]. In addition, previous studies have shown that in environments with a high level of workplace fun, employees will have higher levels of innovative performance [26], creativity [27], and innovative behavior [28]. Therefore, in the process of performance pressure affecting innovation, the positive moderating effect of fun activities is more likely to affect the positive correlation between job involvement and employee ambidextrous innovation, mainly due to the following three reasons.

Firstly, workplace fun can promote employee identification and involvement. In an environment where the organization provides support, it is more conducive to innovation [66]. Fun, as an activity that occurs in the workplace and can make employees feel happy, reflects the support of the organization toward employees [25,67]. Existing studies have found that employees can gain resources by interacting with others through activities that are enjoyable in the workplace, which can contribute to job engagement [68]. Under the joyful emotional experience, employees’ thoughts and behaviors will change [4]. This positive emotion is a supplement to the passive promotion of job involvement under performance pressure, and the innovation level will be significantly improved in a focused work state [69]. As employees become more engaged, they tend to think of new ways to improve their existing job performance and get involved in exploratory and exploitative innovation.

Secondly, workplace fun can promote informal learning among employees. Workplace fun is a social activity that involves complex group relationships [70]. From the perspective of interpersonal fun, engaging with colleagues in fun activities is beneficial for employees to get involved in the informal exchange of experiences and enhance relationships [71]. From the perspective of auxiliary fun, when organizations initiate interesting activities such as fun learning and roundtable discussions, communication between employees and colleagues can directly improve their work skills [72].

Thirdly, workplace fun can create an environment that is tolerant of errors. Fun activities in the workplace create an informal environment for employees to communicate and share. Communication can promote the generation and validation of creative ideas, support employees in listening to the opinions of colleagues or leaders to help employees eliminate high-risk ideas, and transform creative ideas into practical innovativation behaviors [73]. In this environment, employees are more likely to get involved in work and challenge and accept the risk of failure brought about by innovation [74].

Referring to the basic element relationships provided by Affective Events Theory, external situational factors can have an impact on the role of affective reactions. Through reviewing existing research, it has been found that workplace fun helps to enhance employee recognition and focus, promote informal learning, and build a relaxed atmosphere that is tolerant of errors, all of which contribute to encouraging employees to engage in more innovative behaviors when they are involved in work. Therefore, fun in the workplace can play a moderating role in the model of performance pressure. Based on the above considerations, this study proposes the following hypotheses:

H4a. 

Workplace fun positively moderates the relationship between job involvement and employee exploratory innovation.

H4b. 

Workplace fun positively moderates the relationship between job involvement and employee exploitative innovation.

In summary, the conceptual model of this study is shown in Figure 1.

3. Methodology

3.1. Sample and Procedures

As a quantitative study, this study was based on a questionnaire survey method, using a combination of convenience sampling and snowball sampling to obtain first-hand data and conducted empirical analysis based on this. The target of this survey is in-service workers in Chinese enterprises and institutions, and we conducted surveys through online and offline methods. In order to ensure the quality of questionnaire collection, we set the following restrictions on questionnaire filling: (1) Each participant in the survey can only receive compensation once, which can avoid the situation where the same user fills out the questionnaire repeatedly for the purpose of research compensation; (2) Participants cannot submit the questionnaire until it is fully filled out, ensuring that there are no missing values in the questionnaire; (3) Reverse questions were set to identify the content filled out by the participants based on the reverse questions and determine whether they answered seriously.

This study distributed questionnaires through various channels, and the formal questionnaire survey started in January 2024 and ended in February 2024. The cumulative number of participants reached 443. Based on the filling out of reverse items, invalid sample data such as failure to pass the reverse item test, strong regularity, and short answer time (less than 60 s) were excluded. Finally, 362 valid samples were retained, with a recovery rate of 81.72%.

3.2. Descriptive Statistical Analysis

The sample structure is shown in

Table 1. Descriptive statistical analysis of valid samples.

Sample Characteristics	Classification Criteria	Frequency	Percentage (%)
Gender	Male	149	41.16%
	Female	213	58.84%
Age	25 and below	152	41.99%
	26 to 35	114	31.49%
	36 to 45	48	13.26%
	46 to 55	42	11.60%
	56 and above	6	1.66%
Educational Background	College degree or below	46	12.71%
	Bachelor’s degree	179	49.45%
	Master’s degree	123	33.98%
	Doctoral degree or above	14	3.87%
Organization Type	State-owned enterprises	86	23.76%
	Private enterprises	103	28.45%
	Joint ventures or foreign-funded enterprises	22	6.08%
	Government agencies or public institutions	87	24.03%
	Other organization types	64	17.68%
Marital Status	Unmarried	229	63.26%
	Married	133	36.74%

. In terms of gender, male participants accounted for 41.16%, and female participants accounted for 58.84% of the sample structure, with a relatively average proportion of male and female samples. In terms of age, participants aged 25 and below accounted for the highest proportion, reaching 41.99%, followed by participants aged 26 to 35 at 31.49%, participants aged 36 to 45 at 13.26%, participants aged 46 to 55 at 11.60%, and participants aged 56 and above at 1.66%. In terms of educational background, the proportion of the sample with the highest education level being a bachelor’s degree was the highest, accounting for 49.75%, nearly half of the total sample size. The proportion of the sample with the highest education level being a master’s degree was the second highest, accounting for 33.98%. In addition, 12.71% of the sample had a college degree or below, and 3.87% of the sample had a doctoral degree or above. In terms of organization type, the distribution was relatively uniform, with state-owned enterprises accounting for 23.76%, private enterprises accounting for 28.45%, joint ventures or foreign-funded enterprises accounting for 6.08%, government agencies or public institutions accounting for 24.03%, and other samples accounting for 17.68%. In terms of marital status, there were relatively more unmarried samples, accounting for 63.26%, and married samples, accounting for 36.74%. Overall, the samples obtained from the study can represent the true situation of the participants, and further data analysis and research will be conducted.

3.3. Variable Measurement

The performance pressure scale is based on the scale developed by Mitchell [4], which is used to measure the degree of performance pressure experienced by employees in the workplace. The scale only contains one dimension, with a total of four items, such as “The pressures for performance in my workplace are high”. This scale has been widely used in the Chinese context, and its reliability and validity were fully validated. The Cronbach’s Alpha of this scale is 0.802.

The job involvement scale is mainly based on the scale developed by Kanungo [19], which is used to measure the degree of job involvement felt by employees in the workplace. The scale only contains one dimension. This study revised the original items to ensure reliability and validity when measured locally. The final revised scale consists of five items, such as “I live, eat and breathe my job”. The Cronbach’s Alpha of this scale is 0.836.

The workplace fun scale is mainly based on the Chinese workplace fun measurement scale developed by Wang [75], used to measure a series of work-related fun experienced by employees in the workplace. This study revised the original items to ensure reliability and validity when measured locally. The final revised scale consists of 4 dimensions, including 16 items, such as “Easy thematic discussions and training (art appreciation, themed visits, etc.)”. The Cronbach’s Alpha of this scale is 0.857.

The employee ambidextrous innovation scale for mainly draws on the ambidextrous innovation scale developed by Mom [14]. This study revised the original items to ensure reliability and validity when measured locally. The final revised 2-dimensional scale consists of 9 items, such as “Searching for new possibilities with respect to products/services, processes or markets”. The Cronbach’s Alpha of this scale is 0.878.

The setting of control variables is mainly based on the following considerations: demographic variables should be able to reflect the basic characteristics of the subjects and may also cause differences between performance pressure, job involvement, workplace fun, and employee ambidextrous innovation. By reviewing existing research, it was found that there are differences in the perception of performance pressure between males and females [76]. In the context of intergenerational labor force replacement, the younger generation may engage in more innovative behaviors due to their higher acceptance and learning abilities [77]. Married individuals need to share more time in family management compared to unmarried individuals, and balancing work–family conflicts may reduce job involvement [78]. At the same time, this may be to avoid the influence of different types of work units or educational levels on individual fun preferences and innovative activities. Referring to existing research practices, the educational background and the organization type were used as control variables [79]. In summary, this study sets five variables as control variables: gender, age, educational background, organization type, and marital status.

The questionnaire items are detailed in Appendix A.

4. Results

4.1. Confirmatory Factor Analysis

This study used Amos 24.0 to conduct confirmatory factor analysis on the model, and the discriminant validity results of the scale are shown in

Table 2. Comparison and analysis of model fitting.

Model	Factor	χ2/df	RMSEA	IFI	TLI	CFI
Five-factors model	PP, JI, WF, ERI, EII	2.063	0.054	0.899	0.888	0.898
Four-factors model	PP + JI, WF, ERI, EII	3.147	0.077	0.794	0.773	0.792
Three-factors model	PP + JI + WF, ERI, EII	3.752	0.087	0.734	0.709	0.732
Two-factors model	PP + JI + WF + ERI, EII	4.732	0.102	0.638	0.606	0.635
One-factor model	PP + JI + WF + ERI + EII	4.847	0.103	0.626	0.594	0.623

Note: N = 362, PP represents performance pressure; JI represents job involvement; WF represents workplace fun; ERI represents exploratory innovation; EII represents exploitative innovation.

. Performance pressure, job involvement, workplace fun, exploratory innovation, and exploitative innovation were used as independent factors for fitting tests. At this time, the five factors model had better adaptability than other models (χ²/df = 2.063, RMSEA = 0.054, IFI = 0.899, TFI = 0.888, CFI = 0.898), indicating that this study has good structural validity.

4.2. Common Method Variation

Most of the variables studied in this article are perceptions of events or emotions, with subjective tendencies. Although this study achieved the goal of diversifying the types of participants in terms of gender, location, and type of affiliation during the questionnaire-collection stage and ensured that all participants anonymously filled out information in order to ensure their authenticity, this study used self-evaluation data from employees, and the variable data were taken from the same time point, so this study used SPSS 26.0 and Harman single factor test to test the common method bias of the samples. Exploratory factor analysis was conducted on 32 items of 5 variables. The results of the principal component analysis showed that the eigenvalue of the maximum factor was 6.540, and the percentage of variance in the sum of squares was 12.307%, which was lower than the 30% standard. The cumulative total variance explained by the eight factors was 65.885%, which was higher than the 60% standard. Table 1 also showed that the fitting of a single factor was much worse than that of the five-factor model. All the above results proved that there was no serious problem of common method bias in this study. In addition, this study also used confirmatory factor analysis with the addition of a common method factor to further test. The fitting performance of the six factors model with common method factor (χ²/df = 2.051, RMSEA = 0.054, IFI = 0.908, TLI = 0.889, CFI = 0.906) was better than the five-factors model, but the added values of IFI, TLI, and CFI were all less than the threshold of 0.1 change. Therefore, the above three test results indicate that there is no obvious common method bias problem in this study.

4.3. Collinearity Test

To ensure that there is no multicollinearity issue between variables, this study conducted collinearity tests on eight variables, except for the outcome variable, using SPSS 26.0 software. The results of the collinearity test obtained from the study are shown in

Table 3. Collinearity test.

Variables	Tolerance	VIF
Gender	0.951	1.052
Age	0.377	2.651
Educational Background	0.773	1.293
Organizational Type	0.979	1.021
Marital Status	0.417	2.396
Performance Pressure	0.912	1.097
Job Involvement	0.789	1.268
Workplace Fun	0.822	1.216

. The tolerance of each variable is greater than 0.2, and the VIF (variance inflation factor) is in the range of 1.021~2.651, which is much less than 10. Therefore, it was determined that there is no obvious multicollinearity problem between the variables.

4.4. Correlation Analysis

According to the results in

Table 4. Correlation analysis.

Variables	1	2	3	4	5	6	7	8	9	10
1. Gender	1
2. Age	−0.150 **	1
3. Educational Background	0.193 **	−0.438 **	1
4. Organizational Type	0.005	0.019	−0.061	1
5. Marital Status	−0.154 **	0.758 **	−0.372 **	0.039	1
6. Performance Pressure	0.037	0.028	0.061	−0.060	−0.053	1
7. Job Involvement	−0.006	0.204 **	0.005	0.072	0.137 **	0.183 **	1
8. Workplace Fun	−0.018	−0.137 **	0.117 *	0.095	−0.114 *	−0.118 *	0.308 **	1
9. Exploratory Innovation	0.055	−0.034	0.140 **	0.026	−0.122 *	0.380 **	0.273 **	0.175 **	1
10. Exploitative Innovation	0.106 *	−0.014	0.056	−0.041	−0.095	0.355 **	0.163 **	0.109 *	0.636 **	1
Mean	1.588	1.994	2.290	2.834	1.367	3.522	3.110	2.734	3.459	3.533
Standard Deviation	0.493	1.081	0.734	1.470	0.483	0.722	0.725	0.603	0.725	0.661

Note: ** represents p < 0.01, * represents p < 0.05.

, there is a medium correlation between performance pressure and exploratory innovation (correlation coefficient r = 0.380, p < 0.01). There is a middle-level correlation between performance pressure and exploitative innovation (correlation coefficient r = 0.355, p < 0.01). There is a low correlation between performance pressure and job involvement (correlation coefficient r = 0.183, p < 0.01). There is a low correlation between job involvement and exploratory innovation (correlation coefficient r = 0.273, p < 0.01). There is a low correlation between job involvement and exploitative innovation (correlation coefficient r = 0.163, p < 0.01). There is a middle-level correlation between workplace fun and job involvement (correlation coefficient r = 0.308, p < 0.01). There is a low correlation between workplace fun and exploratory innovation (correlation coefficient r = 0.175, p < 0.01). There is a low correlation between workplace fun and exploitative innovation (correlation coefficient r = 0.109, p < 0.05). The results of correlation analysis preliminarily validate some hypotheses, and the direct, mediating, and moderating effects need to be further tested.

4.5. Hypothesis Testing

4.5.1. Direct Effects Analysis

This study used Amos 24.0 software to construct a structural equation model and examine the direct and mediating effects of performance pressure, job involvement, exploratory innovation, and exploitative innovation. The test results of the structural equation model are shown in

Table 5. Four-factors hypothesis model path coefficients (standardized).

Path	Estimate	S.E.	C.R.	p
Performance Pressure → Job Involvement	0.234	0.058	3.67	**
Job Involvement → Exploitative Innovation	0.088	0.066	1.349	0.321
Job Involvement → Exploratory Innovation	0.214	0.061	3.595	**
Performance Pressure → Exploitative Innovation	0.475	0.069	6.335	***
Performance Pressure → Exploratory Innovation	0.433	0.061	6.631	***

Note: N = 362, *** represents p < 0.001, ** represents p < 0.01.

and Figure 2. The four-factors structural equation model composed of performance pressure, job involvement, exploratory innovation, and exploitative innovation fits well (χ²/df = 3.196, RMSEA = 0.078, IFI = 0.892, TFI = 0.872, CFI = 0.891). Therefore, this study has good structural validity.

Based on the path coefficient table and path coefficient figure, it can be seen that performance pressure has a significant impact on the direct path of employee exploratory innovation (β = 0.433, p < 0.001), and the direct path of employee exploitative innovation is also significant (β = 0.475, p <0.001), as well as the effect pathway of performance pressure on job involvement (β = 0.234, p < 0.01). Thus, hypothesis 1a, 1b and hypothesis 2 are supported.

4.5.2. Mediation Effects Analysis

We set the sampling frequency to 5000 times and further tested the mediating effect of job involvement using the Bootstrap method in Amos 24.0. The test results are shown in

Table 6. Mediation effect test results (standardized coefficient).

Path	Estimate	S.E.	Bias-Corrected 95% CI			Percentile 95% CI
			Lower	Upper	p	Lower	Upper	p
PP → JI → ERI	0.050	0.230	0.015	0.106	0.003	0.011	0.099	0.008
PP → JI → EII	0.021	0.230	−0.017	0.078	0.228	−0.022	0.069	0.343

Note: N = 362, PP represents performance pressure; JI represents job involvement; ERI represents exploratory innovation; EII represents exploitative innovation.

In the path of “Performance Pressure → Job Involvement → Exploratory Innovation”, the bias-corrected method test results show a CI confidence interval of [0.106, 0.003], while the percentile method test results show a CI confidence interval of [0.011, 0.099]. The confidence interval does not include 0, indicating that job involvement has a significant mediating effect between performance pressure and exploratory innovation. Hypothesis 3a is supported. In the path of “Performance Pressure → Job Involvement → Exploitative Innovation”, the bias-corrected method test results show a CI confidence interval of [−0.017, 0.078], while the percentile method test results show a CI confidence interval of [−0.022, 0.069], both of which contain 0, indicating that the mediating effect of job involvement between performance pressure and exploitative innovation is not significant. Hypothesis 3b is not supported.

4.5.3. Moderation Effects Analysis

Hypothesis 4a predicts that workplace fun positively moderates the relationship between job involvement and exploratory innovation. Therefore, job involvement, workplace fun, and their interaction term are used as independent variables; exploratory innovation is used as the dependent variable; and control variables such as gender, age, educational background, organizational type, and marital status are added to Model 1. Next, job involvement and workplace fun are added to Model 1, set as Model 2. Finally, an interaction term between job involvement and workplace fun in Model 2 is added, set as Model 3. The test results are shown in

Table 7. Hierarchical regression results: moderating effect of workplace fun (a).

Variable Types	Variable	Dependent Variable: Exploratory Innovation
		Model 1	Model 2	Model 3
Control Variable	Gender	0.024	0.026	0.019
	Age	0.191 *	0.129	0.139
	Educational Background	0.143 *	0.106	0.130
	Organizational Type	0.039	0.012	0.006
	Marital Status	−0.212 **	−0.201 **	−0.193 **
Independent Variable	Job Involvement		0.248 **	0.247 **
	Workplace Fun		0.080	0.069
	Job Involvement × Workplace Fun			0.100
F		3.080 *	6.789 **	6.458 **
ΔF		3.080	15.427	3.790
R2		0.041	0.118	0.128
ΔR2		0.041	0.077	0.009

Note: N = 362, ** represents p < 0.01, * represents p < 0.05, and the median in the table is the standardized coefficient Beta.

After introducing the interaction term, the explanatory power of the model’s variance did not improve significantly, and the impact effect was not significant. Hypothesis 4a is not supported.

Hypothesis 4b predicts that workplace fun positively moderates the relationship between job involvement and exploitative innovation. Therefore, job involvement, workplace fun, and their interaction term are used as independent variables; exploitative innovation is used as the dependent variable; and control variables such as gender, age, educational background, organizational type, and marital status are added to Model 4. Next, job involvement and workplace fun are added to Model 4, set as Model 5. Finally, an interaction item between job involvement and workplace fun is added in Model 5, set as Model 6. The test results are shown in

Table 8. Hierarchical regression results: moderating effect of workplace fun (b).

Variable Types	Variable	Dependent Variable: Exploitative Innovation
		Model 4	Model 5	Model 6
Control Variable	Gender	0.094	0.096	0.089
	Age	0.154	0.119	0.130
	Educational Background	0.035	0.012	0.039
	Organizational Type	−0.035	−0.052	−0.059
	Marital Status	−0.182 *	−0.176 *	−0.166 *
Independent Variable	Job Involvement		0.147 *	0.146 *
	Workplace Fun		0.066	0.053
	Job Involvement × Workplace Fun			0.114 *
F		3.080 *	2.079	3.170 **
ΔF		3.080	2.079	5.757
R2		0.041	0.028	0.059
ΔR2		0.041	0.028	0.031

Note: N = 362, ** represents p < 0.01, * represents p < 0.05, and the median in the table is the standardized coefficient Beta.

. After introducing the interaction term, the explanatory power of the model’s variance increased by 1.2%, indicating a significant impact. Therefore, workplace fun can positively moderate the relationship between job involvement and exploitative innovation (Model 6, β = 0.114, p < 0.05), and hypothesis 4b is supported.

Based on the test results of hierarchical regression, we plotted the slope of the moderating effect of workplace fun, as shown in Figure 3, to visually demonstrate the moderating effect of workplace fun on job involvement and exploitative innovation. As shown in the figure, there is a negative correlation between job involvement and exploitative innovation in low-level workplace fun, while in high-level workplace fun, there is a positive correlation between job involvement and exploitative innovation. This partially supports hypothesis 4b, indicating that workplace fun moderates the correlation between job involvement and exploitative innovation.

5. Discussion

This article is based on the Affective Events Theory and tests the relationship between performance pressure, job involvement, workplace fun, and employee ambidextrous innovation. The results of the empirical analysis confirmed some of the hypotheses in this study and found that performance pressure does promote ambidextrous innovation among employees. Job involvement can play a mediating role between performance pressure and exploratory innovation, but this mediating role is not significant in exploitative innovation. In addition, workplace fun can also moderate the relationship between job involvement and exploitative innovation. These research findings have important theoretical value for the research fields of employee pressure management, fun activity management, and innovation management. This study explores the impact mechanism of performance pressure and employee ambidextrous innovation and draws the following conclusions:

(1) Performance pressure can positively predict employee ambidextrous innovation, indicating that the higher the performance pressure, the more employees will engage in ambidextrous innovation behavior. The discovery that performance pressure is beneficial for employee innovation is consistent with previous literature research [7]; previous research has demonstrated that under the guidance of high-performance goals, in order to gain recognition from the organization, employees will actively improve their performance [80]. As one of the main viewpoints of Affective Events Theory is that affective events can have an impact on individual behaviors [16], performance pressure, as an affective event in the workplace, directly affects work behaviors. Whether employees perceive anxiety when they see a gap between themselves and performance goals, or receive incentives from future benefits after achieving expected performance goals, performance pressure will have a driving effect [4,33]. This kind of emotion that drives employees to catch up with performance goals will lead them to make improvements in existing work and seek external breakthroughs. In the field of employee ambidextrous innovation research, scholars call for thinking and exploring the motivating factors of high employee ambidextrous innovation behavior [14]; the findings of this study respond to this call, showing that performance pressure is a stimulating factor for exploratory innovation and exploitative innovation. Flexibly regulating employee performance pressure may simultaneously stimulate employee performance in high ambidextrous innovation. Organizations can guide employees to engage in high ambidextrous innovation behavior through appropriate performance pressure management. Although most scholars previously believed that performance pressure has a significant negative impact that cannot be ignored [35,40], the results of this study confirm the driving force behind pressure.

(2) Job involvement plays a mediating role between performance pressure and exploratory innovation, indicating that performance pressure can encourage employees to form an attitude of paying attention to and valuing work. This is consistent with previous research findings [46,81], where the formation of a mindset of involvement can subsequently enhance individual innovation [59,60]. As previously found in research, employees in the psychological state of being involved in work tend to increasingly believe that achieving work goals is important, think deeply, and become more focused [62]. This also confirms the main mechanism in the Affective Events Theory that affects employee behavior after events trigger emotions [16]. However, the results of this study indicate that job involvement reflects an incomplete mediating effect, indicating that the mechanism by which performance pressure affects ambidextrous innovation still needs to be explored.

In addition, the mediating role of job involvement in the relationship between performance pressure and exploratory and exploitative innovation is not the same. Performance pressure can affect exploratory innovation through job involvement but cannot promote employee exploitative innovation through job involvement. By reviewing the content of Affective Events Theory, this study identified two possible reasons to explain the differences in this impact. One is that performance pressure directly affects exploitative innovation through nonemotional pathways and exploratory innovation through emotional pathways [32]. Perhaps the obstacles to initiating exploitative innovation are relatively small, and employees only need to compare their performance requirements with their own skill level to take action. However, exploratory innovation requires significant breakthroughs, and this is difficult to achieve solely by utilizing existing knowledge and skills. Therefore, it is necessary to first form a focused affective reaction of job involvement to promote exploratory innovation [15].

The second explanation is that exploitative innovation has other affective triggering factors, as Weiss and Cropanzano pointed out when proposing the Affective Events Theory that there are differences in the influence of mood and emotion [16]. Based on the research in this article, it can be found that exploratory innovation requires breakthrough innovation from scratch, and employees need multiple factors such as determination, courage, perseverance, and endurance. Only when employees accumulate a certain level of mood can they engage in exploratory innovation behavior. However, exploitative innovation is mostly based on improvements to existing work and can start based on existing knowledge and skills. Therefore, when employees perceive a gap between themselves and their performance goals, they will immediately engage in exploitative innovation behavior, which can be achieved without forming job involvement. Or there may be other mediating factors, such as brief and immediate emotional responses that can affect employee exploitative innovation. Further exploration and discussion can be conducted on the intermediary mechanism of exploitative innovation in future research.

(3) Existing studies mainly analyze the aftereffects of workplace fun but lack attention to its moderation effects [26,27,28]. This study found that workplace fun significantly moderates the relationship between job involvement and employee exploitative innovation. As recently discovered by research on Affective Events Theory, organizational factors can affect individual affective reactions and thus affect individual behaviors [23]. Workplace fun is stimulated by creating an environment of harmonious relationships, exchange of perspectives, informal learning, and tolerance for errors, which coincides with the views of scholars such as Yang [79]. This study found that workplace fun can moderate the relationship between job involvement and exploitative innovation, indicating that creating a relaxed and inclusive atmosphere for organizations is beneficial for employees to learn and unleash creative ideas. Providing interesting support activities such as fun training and psychological counseling for employees can help them directly improve their learning. However, we also found that workplace fun does not have a significant moderating effect on job involvement and exploratory innovation. This may be because fun activities correspond to communication and learning within the organization, and exploratory innovation relies more on employees continuously learning new knowledge and skills outside the organization on an existing basis [15]. Therefore, the moderating effect of workplace fun on exploratory innovation is not significant. This is why selecting the appropriate type of workplace fun activities is essential to guide employees toward innovation.

5.1. Theoretical Significance

Firstly, this study explores the positive impact of performance pressure on employee ambidextrous innovation. Most existing research has only revealed the negative effects of performance pressure as a specific type of work pressure [10,11] or explored the double-edged sword effect of performance pressure from both positive and negative perspectives [82]. The positive effects that performance pressure can bring to organizations have not received sufficient attention, and there are not many studies on how to promote ambidextrous innovation at the individual level of employees through effective performance pressure management. Unlike previous studies, this study delves into whether performance pressure can help stimulate ambidextrous innovation behavior at the employee level and compares and analyzes the differences in the impact of performance pressure on exploratory and exploitative innovation among employees, which helps to refine the relevant theoretical content in the field of performance pressure.

Secondly, this study expands the mechanism by which performance pressure affects employee ambidextrous innovation. Due to the fact that the research on ambidextrous innovation has not shifted from the enterprise level to the individual level for a long time, there is not much discussion on employee ambidextrous innovation, and existing research has not clarified how performance pressure affects individual ambidextrous innovation behavior. This study verifies the mediating role of job involvement between performance pressure and employee exploratory innovation, revealing the specific impact path of performance pressure on employee exploratory innovation. Currently, there is relatively abundant research on performance pressure and job involvement, while there is relatively little research on workplace fun and employee ambidextrous innovation. Therefore, based on the previous research, this study combines the above variables and uses job involvement as a mediator and workplace fun as a moderator to explore the impact mechanism of performance pressure on employee ambidextrous innovation. This study can strengthen the understanding of the intrinsic relationship between performance pressure, job involvement, workplace fun, and employee ambidextrous innovation and further expand the research on the antecedents of employee ambidextrous innovation.

Thirdly, it enriches the theoretical achievements of the emerging management practice of workplace fun. This study is based on the Affective Events Theory and regards workplace fun as a characteristic of the work environment in which organizations support employees. It verifies that workplace fun can play a moderating role in the positive correlation between job involvement and employee exploitative innovation. In addition, most existing studies consider workplace fun as an independent variable to examine its positive aftereffects [70,71], while few analyze workplace fun as a moderating variable. Therefore, this study helps to deepen the study of the mechanism of workplace fun and also enriches the application of Affective Events Theory in the study of workplace fun.

5.2. Practical Implications

Firstly, this study can provide direction for managers in promoting the sustainable development of organizations, helping them to more reasonably and effectively set performance goals and manage employee pressure. Performance management combines evaluation and development characteristics and is an important management tool [46]. Exploring the positive effects of performance pressure is beneficial for enterprise managers to motivate and encourage employees. This study found that there are differences in the impact of performance pressure on different types of innovative behavior among employees. This can help employees recognize the positive effects of performance pressure, guide them to correctly view and make good use of the performance pressure they bear in daily work, maintain long-term work motivation, and also help enterprises focus more on setting performance goals in management practice. In organizational management practice, proactive employee innovation plays a crucial role in the overall innovation performance of the enterprise and the shaping of its core competitiveness [2]. This study aims to deepen the organization’s understanding of the incentive path for employee proactive innovation; explore ways for enterprises to satisfy employee intrinsic motivation; and provide theoretical, technical, and methodological support for management consulting, which will contribute to the optimization of enterprise management practices. Therefore, studying the impact of performance pressure on employee ambidextrous innovation has practical significance.

Secondly, this study helps organizations build a flexible and effective employee innovation incentive mechanism. Creating a healthy and efficient work environment is conducive to promoting the common growth of organizations and individuals [83], so this study not only discusses the promoting effect of pressure but also focuses on the key role of fun activities as motivation. Providing employees with an organizational environment that is both stressful and motivating may be one of the ways to make organizations sustainable. These research results can serve as a reference for enterprises in designing fun activities in the workplace and help them create a more relaxed and enjoyable cultural environment. Through this study, enterprises can choose targeted fun activities based on the actual situation of organizational development and the internal needs of employees when designing activities, pay attention to employee fun preferences, and eliminate workplace fun activities that cannot benefit employees, helping employees achieve performance goals better and faster and improving innovative behavior in a targeted manner. The conclusion of this study can serve as a reference for human resource management practices in enterprises, providing measures and optimization suggestions for effectively motivating employees to actively innovate, helping enterprises create a positive and proactive innovation atmosphere, providing new ideas for the relationship between enterprises and employees, making employees work happily, and making organizations more resilient.

5.3. Research Limitations and Future Prospects

Firstly, the data-collection method of this study mainly adopts employee self-evaluation, and the collected cross-sectional data are from the same time period. Although the problem of sample homology error is not serious from the perspective of data representation, it cannot be completely eliminated. In addition, this study did not differentiate the industries or the occupations of the samples during the questionnaire survey. Therefore, it is recommended that future research be conducted using multiple time periods, multiple sources, or data-pairing methods. Future research can focus on the specificity of performance pressure in stimulating innovation in a certain industry or profession and also pay attention to the differences in the impact of different industries and occupations, expand the types and scope of samples, and further verify the relationship between performance pressure and employee ambidextrous innovation in different cultural contexts.

Secondly, this study mainly focuses on the individual perception of performance pressure among employees and its impact on ambidextrous innovation. Future research can categorize and compare the impact mechanism of performance pressure on individual innovation based on different levels of performance pressure, such as team level, company level, market level, etc. It is also possible to compare and study the differences in the impact of performance pressure on management and employee groups at the individual level in order to achieve differentiated incentives between groups.

Thirdly, this study only focuses on the positive impact of performance pressure on employee job involvement and ambidextrous innovation. Further discussion can be conducted on the negative pathways of performance pressure on ambidextrous innovation. The double-edged sword effect brought about by performance pressure and the U-shaped impact of performance pressure on employee psychology and behavior need to be explored. In addition, the impact on employee innovation when performance goals are unrealistic is also worth further discussion. In this study, the impact of workplace fun as a moderating variable on employee ambidextrous innovation was discussed. Subsequent studies can also use workplace fun as an antecedent variable to analyze its direct effect on ambidextrous innovation behavior.