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Article

Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field

by
Zhiliang Lyu
1,†,
Chengao Zhang
1,† and
Xiu Jin
2,*
1
Department of Business Administration, Semyung University, Jecheon-si 27136, Republic of Korea
2
Department of Business Administration, Gachon University, Seongnam-si 13120, Republic of Korea
*
Author to whom correspondence should be addressed.
†
Co-first authors.
Systems 2025, 13(4), 298; https://doi.org/10.3390/systems13040298
Submission received: 6 March 2025 / Revised: 9 April 2025 / Accepted: 15 April 2025 / Published: 18 April 2025
(This article belongs to the Special Issue Systems Analysis of Enterprise Sustainability)
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Abstract

:
Previous researchers have questioned and attempted to verify whether the association between organizational work system and individual and organizational performance indicates causality. A work system is a comprehensive concept; it may be of various types, and gaps exist between the type of organizational work system and performance. To fill these gaps, we investigated the causal relationship between how a high-performance work system improves creative performance via work involvement through social exchange theory, expectancy theory, and the ability–motivation and opportunity framework. Therefore, we established an amalgamated research framework that uses the moderated mediation model of learning method system of comprehensive systems to facilitate creative performance. To verify the above, this study conducted an empirical study targeting 315 organizational members working in Chinese small and medium-sized enterprises (SMEs). For empirical analysis, we utilized SPSS Macro Process, AMOS, and SmartPLS 4 Program. We found that high-performance work systems significantly improve work involvement and creative performance. Additionally, work involvement acts as a mediator between high-performance work systems and creative performance. However, the moderating effect of the learning method system of comprehensive systems was not significant. Overall, this research was conducted in consideration of the fact that there is a considerable lack of empirical research verifying the relationship between high-performance work systems and creative performance that promotes survival and competitiveness for SMEs. In addition, the learning method system of comprehensive system has not been studied actively and it was utilized with the expectation that it would be a variable that would receive new attention through this study. Finally, this research is expected to contribute to the research fields of SMEs and organizational work systems.

1. Introduction

The increasing level of uncertainty surrounding the current business environment makes creativity even more urgent if organizations aim to recover and survive [1,2,3], especially by navigating environments with limited resources [4] and creatively performing work around constraints [5]. As companies face increasingly complex challenges, they must be able to respond innovatively via a set of supported behaviors that drive creativity [6]. Organizational creativity is paramount to small and medium-sized enterprises (SMEs), enhancing competitiveness, promoting continuous innovation, corporate image, staff development, teamwork, and economic efficiency, and maintaining their competitive advantages. Many scholars have presented various research views on organizational creativity and its influence on SMEs’ development [7]. Therefore, creativity in SMEs presents a promising path for future research, contributing to establish a more substantial frame of knowledge [8]. Creativity and creative performance (CP) are regarded as contributory factors to SMEs, facilitating their sustainable development, and also contribute to academic research. In relation to CP, empirical research on the factors affecting CP has been actively conducted. For example, psychological empowerment [9], boundary-spanning behavior [10], spiritual leadership [11], and resonant leadership [12] are included. However, research on the impact of variables related to organizational work systems on CP is relatively lacking. Moreover, empirical research verifying the causal relationship between work systems and CP in SMEs is even more scarce. Considering the abovementioned research background, this study emphasizes the need to explore variables related to work systems, identify causal relationships affecting CP, and verify its influence, contributing to scholarship by expanding the research field on variables related to SMEs, creativity, and work systems.
The way SMEs adopt and implement high-performance work systems (HPWS) is different from that of major companies owing to a lack of bureaucracy, a fire-fighting spirit, funding, and informal and agile processes [13,14]. However, how an HPWS leads to innovation performance among SMEs remains under-researched and should be investigated further [13,14]. In addition, limited empirical research has been conducted to verify the real needs and requirements of SMEs in relation to work systems and CP. Especially in terms of CP, which leads to organizational sustainable performance and innovation, wide gaps exist among SMEs in China. Therefore, we attempt to address these gaps by measuring the effect of an HPWS on CP. This study does not simply demonstrate this causal relationship, but it focuses on exploring the path that induces CP and elucidating the process. Specifically, in relation to the process of producing CP, we attempt to address and verify it by measuring the mediating influence of a high-involvement work system on CP. Additionally, since CP is a main variable for SMEs, how to improve it is worth investigating. Therefore, this study verifies the moderating effect of the learning method system of comprehensive systems (LMSCS) to improve CP. In other words, it clarifies the moderating role and verifies the moderating effect through the interaction between the HPWS and LMSCS.
Based on the research background and research necessity presented above, this research provides a research model and the following main research goals.
First, by emphasizing the importance of CP to SMEs and exploring variables that enhance it, we establish an HPWS as an independent variable and clarify its role. Additionally, we explain how an HPWS enhances CP and clarify this causal relationship.
Second, as a way of enhancing CP, we verify the interaction effect of HPWS and LMSCS. This interaction effect is expected to increase the level of the mediating variable of work involvement (WI), and a higher level of WI will induce a higher level of CP. This is verified by presenting a moderated mediation model, contrary to a previous study that simply verified the causal relationship that increases CP.
Third, this research aims to suggest gaps in previous studies and to contribute to filling various gaps. Although previous studies have attempted to explore the influence of HPWS on employees’ creativity, both the underlying mechanism and boundary conditions are not yet fully understood [15]. In terms of the organization, while employee’s creativity is regarded as a core variable, it would also be valuable to measure CP furthermore. For more in-depth research, it is worth presenting a framework that can lead to CP by HPWS, as well as exploring the individual behavioral variables and verify the influence of the process through which HPWS induces CP through path analysis. This will allow us to expand the scope of research. Gaps exist between organizational work systems and CP. Previous research by Imran, Shabbir, and Mahmood (2020) verified the impact of HPWS on general job performance. We emphasize that it is worth verifying the effect of HPWS on CP that can be useful in specific and current competitive management environments, rather than simply overall job performance. This will contribute to expanding the research fields on HPWS and CP. In addition, the importance of corporate citizenship-oriented HPWS was emphasized and explained; organizations and managers should focus on fostering and enhancing CP through HPWS [16]. According to such gaps, we recognize that future research should focus on causal relationship between HPWS and CP. In addition, empirical research on HPWS and CP is still insufficient, and furthermore, empirical research targeting Chinese SMEs is insufficient. Therefore, this study aims to fill the gap by revealing how HPWS induces CP in Chinese SMEs.
Finally, the LMSCS is a variable that has not been studied extensively in current academics. The LMSCS is a sub-element of the learning organization–organizational system. This study aims to contribute to expanding the research area on the LMSCS by clarifying the interactive role of an HPWS and LMSCS and verifying the moderating effect. To this end, we design and verify a moderated mediation effect model, thereby contributing to expanding the research area of LMSCS.
By and large, research on the causal relationship between HPWS and CP is even more insufficient. Considering such gaps, rather than simply verifying the causal relationship between HPWS and CP, we seek to elucidate the process of how creativity is enhanced. Therefore, this research aims to identify the mediating role of WI, which has a key role in enhancing CP. This is explained through expectancy and social exchange theories. In relation to reveal specific paths to lead CP, this study is the first empirical study on how organizational systems enhance CP in Chinese SMEs, filling the gaps in previous research and contributing to strengthening and clarifying the scholarship. Table 1 below summarizes the research gaps identified through previous research.

2. Theoretical Background and Hypothesis

2.1. The Relationship Between HPWS and CP

HPWS refers to organizational members’ recognition of a human resource management system that aims to improve organizational members’ opportunities, participation, motivation, and capabilities to enhance organizational performance [17]. Additionally, employees’ CP is defined as the outcomes that organizational members consciously promote, create, and achieve as new ideas to benefit both them-selves and their teams, or their organizations [10,18]. The relationship between HPWS and CP should be logically explained drawing on social exchange theory. Social exchange theory suggests the exchange relationships entail nonprescribed obligations, and organizational members are generally feeling obliged to reciprocate [19,20]. For example, based on social exchange theory, when organizations support organizational members’ growth and work-related elements, provide fair treatment, and increase satisfaction, organizational members will be more committed to the organization and will respond to it by engaging in behaviors such as increasing organizational performance. Therefore, a quality exchange relationship via favorable treatment triggers various aspects of obligations to return the favor [21,22]. Having an HPWS leads organizational members to be more likely to accept available support and pressure [23], maximize the implementation and generation of creativity, and enhance the level of innovation performance [24]. An HPWS encourages strengthening organizational members’ skills via management practice in the form of job training. Then, the organizational members’ professional skills become a benchmark for recruitment and work position in organizations [25]. Moreover, an HPWS has a positive influence on knowledge management. Especially, it encourages organizational members to create new ideas, further sharing and developing understanding with one another, and promotes various changes in organizational operations [26]. An HPWS helps organizations build efficient and strong organizational climate and structure, which allows organizational members to transfer, create, and implement their knowledge, encouraging innovative work-related behaviors [27]. Such a management environment helps organizational members recognize the support they receive from their organizations through the HPWS and induces expectations for innovative performance. Based on social exchange theory, higher levels of perceived organizational support shape organizational members’ sense of obligation to repay organizations and increase higher level of organizational commitment and innovative behavior, which contributes to increased CP. In explaining the link between HPWS and CP, we use the ability–motivation and opportunity (AMO) framework. The AMO framework suggests that effective human resource management practices improve organizational members’ abilities, skills, and knowledge (A), motivation (M), and opportunities (O) to express their talents [28,29,30]. Similarly, this framework is used to present the relationship between HPWS and organizational innovation. An HPWS increases the level of organizational members’ abilities, skills, and knowledge to innovate—in other words, it establishes their talent and expertise [27,31,32,33,34,35]. In this process, an HPWS enhances employees’ willingness to generate new ideas [36,37,38]. We emphasize that, based on the theoretical and logical aspects presented above, an HPWS acts as a core predictor to enhance CP. This leads us to establish the first hypothesis of our study as follows:
Hypothesis 1. 
HPWS will significantly enhance organizational members’ CP.

2.2. The Mediating Effect of WI

WI is defined as organizational members being generally interested in, pre-occupied with, and identifying with their work [39,40]. An HPWS enhances organizational members’ involvement and participation, ensures quality management, and facilitates team building [41]. We suggest that an HPWS improves organizational members’ CP through the indirect effect of a high level of WI. We strengthen the logical aspect through psychological motivation theories such as expectancy theory, which mainly explains the process leading to CP. Expectancy theory suggests that an organizational member is driven to act in a certain way regarding motivation and effort, which are shaped through individual expectations of obtaining compensation [42,43]. Additionally, it explains the process underlying organizational members’ decisions on various behavioral alternatives [44]. With regard to performance and motivation in a mathematical form, Vroom (1964) proposed expectancy theory and suggested the performance is (P); a function of the product of motivational force is (M), and workers’ ability is (A)—in other words, P = f (M.A). The equation of expectancy theory can be expressed as Motivation = f∑(E → P) × (P → O) × V. E (effort) → P (performance) explains effort to performance expectancy (Expectancy); P (performance) → O (outcome) express performance to outcome expectancy (Instrumentality), and V is valence. Effort to performance expectancy (E → P) suggests individuals’ belief that efforts lead to the desired performance level, and performance is higher when the organizational member believes in and feels confident about their efforts. Additionally, performance to outcome expectancy (P → O) suggests that individuals’ belief that performance will lead to the desired outcomes. Valence (V) suggests the appreciation or preference of the outcome or end result [44].
The HPWS is a human resource practice designed to improve organizational members’ skills, productivity, and commitment, becoming a valuable source of competitive advantage [25]. Therefore, an HPWS plays a role in helping organizational members improve their work skills, arousing their passion for work, and making them more involved in their work. Additionally, im-proving the capabilities of an HPWS facilitates organizational members’ confidence and self-efficacy in their work and increases their engagement in achieving higher-level goals. This process explains that an HPWS increases performance through a higher level of organizational members’ WI. Moreover, it is regarded as a lubricant that creates and implements organizational work-related knowledge, encouraging innovative work-related behaviors [27]. This may encourage organizational members to foster innovative behavior, which is likely to foster the creativity needed to generate such behavior. In line with expectancy theory, it encourages organizational members to strive toward meeting specific goals or objectives. This is related to how valuable the goal that the organizational members are trying to achieve is; the more they perceive the goal as important and valuable to them, the more effort they will put into the goal and performance. In sum, expectancy theory explains that when organizational members put in effort to achieve a certain goal, this will lead to achievement. Ultimately, they will put in effort toward their goals or tasks owing to the expectation that they will receive satisfactory rewards. Specifically, performance is de-rived from the interaction between abilities and motivation. Additionally, as abilities improve, organizational members may have greater expectations about their own performance and will put in more effort to achieve performance through the expectation that they will be rewarded for their efforts. Therefore, a high-performance work system shapes organizational members’ creativity and confidence in relation to their works, motivating them to engage in higher levels of innovative behavior and CP via a high level of work effort and involvement. Based on expectancy theory and this logical basis, we formulate the following hypotheses:
Hypothesis 2. 
HPWS will significantly enhance WI.
Hypothesis 3. 
WI will significantly enhance organizational members’ CP.
Hypothesis 4. 
WI will significantly mediate the influence of HPWS on organizational members’ CP.

2.3. The Moderating Effect of Learning Method System of Comprehensive System

LMSCS is a concept that establishes organizational structures, processes, and institutional systems conducive to organizational members’ learning and innovation, as well as human, material, and financial resources invested in learning and innovation. LMSCS refers to those methods and systems that enable organizational members to truly learn new and valuable external knowledge, reflect on the relationship between events from past experience, and effectively communicate and share experiences related to methods and systems with each other [45]. Such roles suggest that the organization establishing a LMSCS will greatly enhance individual and organizational learning ability. Organizational members’ work ability is positively associated with skills, knowledge, attitudes, and organizational commitment [46,47,48]. We expect the HPWS and LMSCS to be predictors of organizational members’ ability, knowledge, and skills, with both variables having a positive relationship. An HPWS improves organizational members’ skill and knowledge level by ability-based initiatives [26], and it enhances work abilities that impacts organizational members’ satisfaction with high performance [25,49]. The LMSCS emphasizes organizational members’ learning and plays a positive role in developing valuable knowledge and abilities through work-related learning. Ultimately, an HPWS creates the LMSCS, and the two are considered to have a positive correlation.
We propose that the interaction between HPWS and LMSCS moderates the level of WI and CP. As suggested above, both the HPWS and LMSCS improve work-related abilities, knowledge, and skills, ultimately contributing to increasing organizational members’ self-efficacy. In particular, the LMSCS increases organizational members’ self-efficacy when their abilities, skills, and knowledge are higher through learning. Self-efficacy theory suggests that individuals’ capabilities in a specific domain related to an activity may have a substantial influence on their motivation to engage in specific actions within the domain [50,51,52,53]. Furthermore, performance capability in a certain domain acts as a precursor of creative capability in that domain [54]. Thus, belief in organizational members’ ability to adequately perform a job is necessary before one has the confidence in their abilities to be creative. In relation to that respect, a sense of general efficacy related to the job may be necessary for formulating more targeted, work-related, and creative self-efficacy [55]. In essence, organizational members with a higher level of self-efficacy tend to take up more challenging tasks involving creative practices [51]. Additionally, higher self-efficacy tends to approach problem solving in more innovative ways rather than in a patterned or routine way [56]. In short, organizational members with higher self-efficacy take up creative task as challenging activities and put maximum efforts into mastering them instead of regarding them as a threat to be avoided [57,58]. This research uses this notion from self-efficacy theory to suggest that self-efficacy beliefs for the specific ability and competence to achieve a higher level of challenging work and the increased motivation make organizational members more involved in their work. Drawing on self-efficacy theory, we suggest that when the LMSCS is higher, self-efficacy will be higher; this will strengthen organizational members’ motivation that induces a higher level of WI and allows them to accept more challenging tasks that increase CP. The positive interaction between the LMSCS and the HPWS will lead to higher levels of self-efficacy and thus higher levels of work engagement and CP. In sum, the mediation variable of WI is moderated through the positive interaction between the LMSCS and HPWS, that is, through the positive moderating role of the LMSCS. Therefore, the LMSCS is expected to moderate the relationship between HPWS and job engagement and CP. Furthermore, the mediating effect of WI on the relationship between HPWS and CP will be positively moderated by the LMSCS. Based on this theory and rationale, we propose the following hypothesis:
Hypothesis 5. 
The mediating effect of WI on relationship between HPWS and CP will be positively moderated by LMSCS.
Hypothesis 6. 
LMSCS will positively moderate the relationship between HPWS and CP.

3. Research Method

3.1. Sample Characteristics and Data-Collection Procedure

This study was a quantitative research study using data in the form of a survey. We conducted our empirical research to verify the impact of the HPWS on CP and derived a hypothesis verifying the mediating effect of WI in the process of the HPWS improving CP. Additionally, we derived a hypothesis verifying the interaction effect of the HPWS and LMSCS as a way of improving CP. To verify this hypothesis, this study collected data from organizational members working in SMEs in China from 1 April 2024, to 20 April 2024, in Shandong, Jiangsu, Zhejiang, Henan, and Shanxi provinces. Although we distributed 320 surveys and intended to use them for empirical analysis, 315 surveys were actually collected. Therefore, the collection rate was 98.4%. Participants were informed that their survey results would be used for empirical analysis in this study and that the results would be published.
To confirm the characteristics of the collected data, we conducted demographic characteristics analysis. From the results of demographic characteristics, 168 (53.3%) male and 147 (46.7%) female organizational members participated in this survey. In relation to age, those aged 21–30 years were 113 (35.9%), those aged 31–40 years 95 (30.2%), those aged 41–50 years 67 (21.3%), and those aged 51–60+ years 40 (12.6%). Regarding the participants’ educational background, 158 (50.2%) had a college degree; 109 (34.6%) had graduated university; 34 (10.8%) had a master’s degree, and 14 (4.4%) had a doctorate. Finally, with regard to the participants’ service years, 31 (9.8%) had been working in their enterprises for less than 1 year; 62 (19.7%) had been working there for 1–2 years, 43 (13.7%) for 3–4 years, 24 (7.6%) for 5–6 years, and 155 (49.2%) for 7 or more years.

3.2. Operational Definitions of Variables and Measurements

To measure HPWS, WI, LMSCS, and CP, all adopted scales were from the well-established literature and had already been proven as reliable measurements. In addition, the details on the use of measurement tools are as follows:
Regarding the setting of measurement tools, we did not need to translate the measurement items of moderation variable of LMSCS in to Chinese because the original version of the instrument is in Chinese. Additionally, the original measurement tools for the independent variable of HPWS, mediation variable of work involvement, and dependent variable of CP were in English; therefore, these three instruments were translated into Chinese. First, to ensure the accuracy of the measurement tool and the items’ content, the three authors independently translated all the English items into Chinese. Next, the three authors checked for errors in the content of the items translated by the others and revised them to ensure accuracy. The measurement tool was backtranslated from Chinese into English, and its similarity to the original English version was checked. Finally, we received confirmation from an English expert and conducted the survey using the measurement tool, the accuracy of which was finally confirmed. Specifically, all the measurement tools we selected were consistent with the topic of this study and have already achieved high reliability. The following section summarizes the operational definitions, measurement tools, and sources of all variables.
Regarding the operational definitions of variables and measurements, an HPWS is defined as organizational members’ recognition of a human resource management system that aims to improve organizational members’ participation, opportunities, motivation, and capabilities to increase organizational performance [17]. The HPWS scale was adapted from that developed by [59] and included 12 items such as “Employees are moved through a series of different job assignments to prepare them for future assignments” and “Employee’s job performance is appraised, to a significant extent, on how well he or she follows orders and company procedures and rules”. The reliability analysis result showed high reliability with a value of 0.971.
WI is defined as the degree to which organizational members are fully engaged in their work within the organization and have sufficient freedom in performing their work, as well as a strong sense of responsibility for their jobs. Based on the operational definitions developed in this study, the following measurement tools were utilized to consider not only organizational members’ tasks, but also the aspect of active participation in decision-making. To measure WI, we used the measurement tool developed by [60] and mainly used items on the involvement dimension. This measurement tool consisted of three items such as “I have enough authority to perform my job duties” and “I can complete my work according to my own opinions”. The reliability analysis result presented high reliability with a value of 0.917.
LMSCS is defined as encouraging and facilitating organizational members to continuously learn and improve creativity through organizational structure and management system. The LMSCS scale was adapted from the scale developed by [45] and included five items such as “Company adopts certain motivation systems to pro-mote employees’ continuous learning and innovation” and “Company’s management system is conducive to employees’ continuous learning and innovation”. The reliability analysis result showed high reliability with a value of 0.975.
CP refers to the outcomes of solving problems with various new ideas and approaches that maintain sustainable growth by improving the organization’s competitiveness [61]. To measure CP, we used the measurement tool developed by [62], which consisted of 13 items, including “Develops adequate plans and schedules for the implementation of new ideas” and “Comes up with new and practical ideas to improve performance”. The reliability analysis result showed high reliability with a value of 0.987.
A seven-point Likert-response scale was provided for each question dealing with participants’ attitudes about their work. Each item was scored through seven-point Likert scale with anchors of 1 = Strongly disagree, 2 = Disagree, 3 = Slightly disagree, 4 = Neither disagree or agree, 5 = Slightly agree, 6 = Agree, and 7 = Strongly agree. Appendix A lists the variables, measurement items, and references used in this study.
Drawing on the statement above, we present the research model in Figure 1.

4. Data Analysis and Results

4.1. Confirmatory Factor Analysis and Reliability Analysis

This research built on the results of exploratory factor analysis to specify the factor model via confirmatory factor analysis using the AMOS program, which was developed for structural equation modeling (SEM). Specifically, we performed SEM with confirmatory factor analysis using AMOS 23 to examine our research scales’ structure. The results show that HPWS consisted of 12 items, and the value of standardized regression weights was 0.728–0.880; HPWS consisted of 3 items, and the value of standardized regression weights was 0.773–0.859; LMSCS consisted of 5 items, and the value of standardized regression weights was 0.880–0.941; and CP consisted of 13 items, and the value of standardized regression weights was from was 0.855–0.913. All values of standardized regression weights were above 0.6, showing excellent levels and significant loadings values [63]. Additionally, the values of the average variance extracted (AVE) were HPWS = 0.636, WI = 0.688, LMSCS = 0.827, and CP = 0.791. All the AVE values were above 0.5, indicating excellent value and significance [64,65]. Furthermore, the values of composite reliability (CR) were HPWS = 0.971, WI = 0.795, LMSCS = 0.946, and CP = 0.973. All the CF values were above 0.7, indicating excellent value and significance [64,65]. In relation to the model fit index of the research model, the results showed that χ2(p) = 1834.848 (0.000), χ2/df = 3.855, RMSEA = 0.095, IFI = 0.919, TLI = 0.910, CFI = 0.919, PGFI = 0.634, and PNFI = 0.806. All results except RMSEA showed excellent values; RMSEA was 0.095, which is not regarded as an excellent value but an acceptable level. In particular, when the RMSEA value is greater than 0.10, it indicates a poor model fit [66]. Additionally, the values of χ2/df = 3.855, RMSEA = 0.095, IFI = 0.919, TLI = 0.910, CFI = 0.919, PGFI = 0.634, and PNFI = 0.806 in this study all showed excellent and acceptable levels. Overall, the model fit index showed that the model of this study was acceptable [67]. According to these results, convergent validity was verified and considered significant.
Moreover, we conducted reliability analysis to verify the reliability of the measurement tool. The reliability of HPWS was 0.971; WI was 0.917; LMSCS was 0.975; and CP was 0.987. If the reliability value is 0.7 or higher, the measurement tool is reliable and significant [68]. Therefore, all measurement tools in this study are reliable. Table 2 below shows the results of confirmatory factor and reliability analyses.

4.2. Descriptive Statistics and Correlation Analysis

Correlation analysis is a technique for analyzing whether the correlation between variables is significant before conducting regression analysis. Regression analysis can only be conducted if the correlation between variables is significant. The results of correlation analysis presented that all variables were significant. Specifically, HPWS was positively associated with WI (r = 0.849), LMSCS (r = 0.859), and CP (r = 0.864). In addition, WI is positively related to LMSCS (r = 0.751), and CP (r = 0.793). Finally, LMSCS is positively associated with CP (r = 0.792). In addition, the results of descriptive statistics showed that the mean value of HPWS = 5.532, WI = 5.352, LMSCS = 5.659, and CP = 5.578. Moreover, the standard deviation value of HPWS = 1.297, WI = 1.449, LMSCS = 1.372, and CP = 1.196. Table 3 illustrates the descriptive statistics and correlations between variables.
In this research, the heterotrait–monotrait ratio (HTMT) inference method was utilized to assess the discriminant validity among HPWS, WI, LMSCS, and CP variables. Following the guidelines by [69], discriminant validity is established if the HTMT inference values fall below the benchmark of 1. Table 4 presents the HTMT inference results, which were obtained through bootstrapping with 5000 resamples. The discriminant validity is further supported by the fact that all 5% and 95% confidence intervals are below 1. The results substantiate the existence of discriminant validity within this context. Table 4 presents the results of HTMT inference.
To verify the hypotheses in this research, we conducted analyses using AMOS 23.0 and SPSS 26 Macro Process. First, we conducted regression analysis using AMOS to verify hypotheses 1, 2, 3, and 4. Hypothesis 1 posited that HPWS has a positive effect on CP. The results showed that the positive effect of HPWS on WI was significant (estimate = 0.576, p < 0.001); thus, hypothesis 1 is supported. Hypothesis 2 established that HPWS has a positive effect on WI. Likewise, the results showed that the positive effect of HPWS on WI was significant (estimate = 0.886, p < 0.001); therefore, hypothesis 2 is supported. Hypothesis 3 established that WI has a positive effect on CP. The results showed that the positive effect of WI on CP was significant (estimate = 0.251, p < 0.001); thus, Hypothesis 3 is supported. Hypothesis 4 posited that WI mediates the relationship between HPWS and CP. The results showed that the indirect effect of HIPS was 0.247, and both Boot LLCI and Boot LUCI were 0.058 and 0.456, respectively. Regarding mediation effects, Boot LLCI and Boot LUCI should not include any 0. As our mediation effect test results showed that 0 was not included between Boot LLCI and Boot LUCI, the mediation effect was significant, and hypothesis 4 is supported. If we examine the results for the mediation effect more specifically, the independent variable of HPWS showed a significant direct effect on the dependent variable of CP; this indicates that HPWS has a partial mediation effect. Furthermore, the model fit indexes of the structural equation model for the mediating effect of HPWS showed that χ2(p) = 1287.561 (.000), χ2/df = 3.937, RMSEA = 0.097, IFI = 0.931, TLI = 0.920, CFI = 0.930, PGFI = 0.626, and PNFI = 0.787, which were at an acceptable level, and the model is significant. Table 5 below shows the results of hypothesis testing using AMOS.
Additionally, to verify the significance of the mediating effect, we verified the mediating effect of WI using SPSS Macro Process and Model 4 presented by [70]. First, the direct effect of HPWS on CP was verified. The direct effect was 0.681, se was 0.053, t-value was 12.952, and the significance level p-value was less than 0.001. In addition, the bootstrapping technique showed Boot LLCI was 0.578, Boot LUCI was 0.784, and 0 was not included between Boot LLCI and Boot LUCI. Therefore, the direct effect was verified to be significant. In relation to the mediating effect, an analysis was conducted on the indirect effect of HPWS on CP. According to the results, the indirect effect was 0.180, and Boot SE was 0.058. The bootstrapping technique presents that Boot LLCI was 0.071, Boot LUCI was 0.295, and 0 was not included between Boot LLCI and Boot LUCI. Therefore, these results indicate a significant partial mediating effect of HPWS. Therefore, the mediating effect of WI was secured and significant. Table 6 illustrates the results of the mediating effect of HIPS on the relationship between HPWS and CP via SPSS Macro Process. Table 6 shows the mediating effect of WI.
Hypothesis 5 established that the LMSCS positively moderate the mediating effect of WI on the relationship between HPWS and CP. The moderated mediating effect of LMSCS was verified using Model 7 presented in Hayes (2018) via SPSS Macro Process. However, the bootstrapping technique at three levels of LMSCS showed that 0 was not included between Boot LLCI and Boot ULCI, which was significant. However, the result of the index of moderated mediation was 0.001, Boot SE =0.002, Boot LLCI = −0.003, and Boot ULCI = 0.007. It can be confirmed that 0 is included in Boot LLCI and Boot ULCI. Therefore, the moderated mediation effect of LMSCS is considered insignificant, and therefore, Hypothesis 5 was not supported. Table 7 below shows the results of moderated mediation effect of LMSCS.
Finally, hypothesis 6 established that the LMSCS positively moderates the relationship between HPWS and CP. According to the results, HPWS and WI have a positive influence on CP. However, the interaction (HPWS × LMSCS) effect shows 0.008, the value of se = 0.013, t = 0.618, p = 0.537 (p > 0.05), Boot LLCI = −0.018, and Boot LUCI = 0.034. Based on these results, the p value was greater than 0.05, which was not significant, and 0 was included between Boot LLCI and Boot LUCI. Therefore, hypothesis 6 is not supported. Table 8 illustrates the result of the moderating effect of LMSCS on the relationship between HPWS and CP. In addition, Figure 2 below is a graph showing the moderating effect of LMSCS.
To further elucidate the effectiveness of the moderating effect of LMSCS, we conducted additional analyses. All variables were measured using a Likert 7-point scale. We divided the data into groups with LMSCS median greater than 4 and groups with LMSCS median less than 4. The group with LMSCS greater than 4 consisted of 269 data, and the group with LMSCS less than 4 consisted of 46 data. We tested the moderating effect of LMSCS on the relationship between HPWS and both WI and CP in the group with LMSCS less than 4. However, the moderating effect was not significant. However, in the group with LMSCS higher than 4, the moderating effect of LMSCS on the relationship between HPWS and both WI and CP was significant. Specifically, as shown in Table 9, the moderating effect of LMSCS on the relationship between HPWS and WI was significant (β = 0.126, t = 2.725, p < 0.01). Therefore, the moderating effect of LMSCS was verified to be significant in the group with high LMSCS, which showed that the higher the LMSCS, the stronger the positive effect of HPWS on WI. Figure 3 is a graph of the moderating effect of LMSCS on the relationship between HPWS and WI in the in the group with high LMSCS. The graph showed that the strongest positive moderating effect was observed at +2 standard deviation level, and that the larger the standard deviation, the stronger the moderating effect.
In addition, we verified whether LMSCS positively moderated the effect of HPWS on CP. Specifically, as shown in Table 10, the results verified that LMSCS positively moderated the effect of HPWS on CP and that the moderating effect was significant (β = 0.134, t = 3.057, p < 0.01). Therefore, the moderating effect of LMSCS was verified to be significant in the group with high LMSCS, which showed that the higher the LMSCS, the stronger the positive effect of HPWS on CP. Figure 4 is a graph of the moderating effect of LMSCS on the relationship between HPWS and CP in the in the group with high LMSCS. The graph showed that the strongest positive moderating effect was observed at +2 standard deviation level, and that the larger the standard deviation, the stronger the moderating effect.

5. Discussion

SMEs are the lifeblood of any country or nation, contributing to both its GDP and economy and facilitating its prosperity and future sustainability [71]. Therefore, this empirical study could expand the scope of the research field by suggesting and verifying ways to improve CP in Chinese SMEs, and it is expected to have academic significance and make a substantial contribution. Specifically, we verified the influence of HPWS on CP by the mediating effect of WI. Moreover, we attempted to explore and verify the moderating roles of LMSCS on the relationship between HPWS and both WI and CP. The results showed that the mediating effect of WI was significant. However, contrary to our expectations, the moderating effect of LMSCS was insignificant. Although the moderating effect was insignificant, this study was only the first attempt, and the results are expected to provide a direction for future research and contribute to the research areas of HPWS and CP.
This study was able to fill the gap that existed in previous studies. First, in understanding the mechanism of the influence of HPWS on the employee creativity, this study contributed to revealing the process by which HPWS affects creative performance beyond employee creativity. Through the research results, it was verified that HPWS ultimately increases creative performance by improving organizational members’ WI. Specifically, the process by which HPWS increases creative performance was explained through the mediating effect of organizational members’ WI. It reveals that HPWS essentially plays a positive role in promoting organizational members’ attitudes and behaviors. In other words, HPWS induces organizational members’ participation and involvement. Furthermore, as the level of WI increases, it is possible to predict behaviors such as brainstorming, information exchange, and knowledge sharing among organizational members. Eventually, such process was shown that it can activate organizational members’ creative performance to increase. Another gap is that previous studies have been conducted on the effects of HPWS on general job performance [72]. In addition, the previous study of [16] suggested that managers and organizations should focus on fostering and improving CP through HPWS. Therefore, this research focused on creative performance, which is considered a key outcome variable of organizational members. The results of the study verified that HPWS has a positive correlation with creative performance and is an antecedent variable that can directly and indirectly affect it. This has made a substantial contribution to filling the gap presented above. Finally, we presented a model of moderated mediation effects in increasing CP, but unfortunately, this effect was not significant. The specific reasons were discussed in the theoretical implications.
In accordance with the results, the empirical implications, managerial implications, research limitations, and future research directions are summarized as follows.

5.1. Theoretical Implications

This research makes four clear-cut theoretical contributions.
First, it makes an overall contribution by both building and verifying the research model by which high performance improves CP. The concept of an HPWS claims that systems of work practices for core organizational members in organizations lead to superior performance in some ways [29]. Furthermore, HPWS embodies core competence in the aspects of strategic human resource management [15]. In relation to how HPWS increases CP, the mainstream view indicates that HPWS improves organizational performance by increasing organizational members’ positive attitude, knowledge, and skills [73]. Acquiring more diverse, new knowledge will contribute to forming a mechanism for working in a new way, and since new technologies are highly related to innovation, this will have a positive effect on the creative thinking and behavior of organizational members. Moreover, organizational members who experience HPWS are encouraged to exchange information related to their job with colleagues. Furthermore, drawing on trait activation theory to predict extroversion personality strengthens the influence of HPWS experience on job-related information exchange. Eventually, the increased information exchange will increase organizational members’ CP [74]. This suggests that positive changes in technology and knowledge will ultimately be of great help in stimulating organizational members’ CP. Therefore, HPWS is a variable that facilitates CP.
Second, the process of HPWS leading to CP is improved mainly through WI; thus, HPWS promotes the level of organizational members’ CP by facilitating WI. A high-involvement work process is related to stronger satisfaction and better work–life balance, and it has no relationship with stress or fatigue [75]. Additionally, HPWS facilitate innovation by promoting organizational members’ involvement, continuous learning, and skill development, acting as drivers of innovative performance [76,77]. Particularly, the main role of HPWS is that it leads to a higher level of perceived organizational support experienced by organizational members [78]. Based upon the theoretical perspective of social exchange theory [19], the process of social exchange begins with managers treating their subordinates either positively or negatively; the subordinates then may choose to adopt positive or negative behaviors in exchange. Therefore, subordinates may have a positive attitude toward their organizations while witnessing desirable actions in their workplace, such as high level of organizational support and justice [79,80]. Social exchange theory is related to organizational support theory, which addresses the satisfaction of organizational members’ socioemotional needs. According to this theory, members present internal commitment to reciprocate the organizational support by displaying supportive work-related performance and further assisting organizations in reaching their objectives [81,82]. Thus, HPWS can strengthen organizational members’ sense of support from the organizations, which increases their satisfaction with their work and organizations they belong to and strengthens the sense of duty to repay them through social exchange. This suggests that HPWS can be enhanced by involving organizational members.
Third, we established the hypothesis that WI has a mediating effect on the relationship between HPWS on CP. The result showed that WI had a significant partial mediation effect, which indicates that HPWS has direct and indirect effects on CP. While organizational members have homogeneous, strong experiences, they cultivate a process of behaviors for knowledge exchange. Additionally, the process of collective behaviors in organizations manifests as organizational members’ overt communication and leads to explicit coordination in their work process [83]. In accordance with this communication process, organizational members can exchange task-relevant knowledge and information, which is an important source of innovation [84]. Moreover, through such explicit coordinating behaviors, the involved organizational member can aggregate discretionary actions toward the formation of a unified workforce and remove barriers to creation and the implementation of various creative ideas [85], which may lead to CP. In terms of specific paths leading to CP, a key element that enhances CP is WI. Thus, when organizational members perform their work, they freely utilize their abilities and skills by being immersed in the organization with sufficient freedom and responsibility, which increases creativity and leads to their CP.
Finally, one of the purposes of this study was to verify the interaction effect of HPWS and LMSCS. LMSCS was used as a moderating variable to enhance CP, and the interaction effect between HPWS and LMSCS was clarified. Furthermore, this study is the first to measure the interaction between HPWS and LMSCS to verify whether WI and CP can be increased. The LMSCS is a variable that is considerably under-researched, but we used it explore a new method for enhancing CP in this research. However, contrary to our expectations, the positive moderating effect of LMSCS was not valid. Therefore, the moderated mediating effect of LMSCS was found to be insignificant. However, when we verified the moderating effect by distinguishing between high and low LMSCS groups, we obtained another new result. In the group with high LMSCS, the moderating effects of LMSCS on the effects of HPWS on WI and CP were all significant, and a positive moderating effect was verified. This shows that the role and theories of the moderating effect of LMSCS that we utilized are significant in the group with high LMSCS. Unfortunately, the moderating effect of LMSCS was not significant in the group with low LMSCS. However, we argue that this problem is also a discovery of another new aspect of LMSCS. We argue that it is expected LMSCS in Chinese SMEs will have a significant interaction with variables in the individual aspect, such as expectations, motivation, and self-efficacy, rather than interacting with HPWS, which is a variable in the organizational aspect. A logical explanation for this is as follows:
Drawing on self-efficacy theory, organizational members’ capabilities in their specific work domain related to behaviors may lead to a substantial effect on their motivation to engage in specific actions within the domain [50,51,52,53]. LMSCS acts an important role in increasing self-efficacy as organizational members improve their abilities, knowledge, and skills, which are necessary for their task and work through learning. Additionally, the higher the self-efficacy, the stronger the confidence members have in their own abilities, which will facilitate organizational members to perform more difficult tasks and goals. Moreover, LMSCS promotes teaching, training and mutual communication, and sharing activities for organizational member to learn and innovate. It also includes the use of various methods and tools conducive to learning and innovation (such as systems thinking, improving mental models, team learning and dialogue, post-evaluation systems, and scenario planning) [45]. Therefore, LMSCS can enable them to involve themselves more in their works via the interaction effect of LMSCS and self-efficacy. Furthermore, intrinsic motivation acts as a lubricant that increases work involvement. In particular, the stronger the person–job fit, the stronger the intrinsic motivation of organizational members. LMSCS enhances organizational members’ the abilities, knowledge, and skills. In this situation, the interaction between intrinsic motivation and LMSCS ultimately leads to a higher level of work involvement. Based on the expectancy theory, if the value of goals and outcomes is considered important, organizational members’ expectations of goals and outcomes will be strong, which will eventually lead to the members’ efforts. LMSCS is a factor that increases the knowledge, ability, and skills required for goals and outcomes. Therefore, the interaction between organizational members’ expectations and LMSCS will further increase WI, which will ultimately increase the level of CP.

5.2. Managerial Implications

Our findings have at least three managerial implications.
First, as a set of human resource practices that are complementary internally and aligned with organizational strategies externally, HPWS is a core factor that aims to increase organizational members’ abilities and behavior, eventually improving their level of competitive advantage [86]. Compared to other elements, excellent institutional construction is more significant and effective in predicting employees’ creativity [15,87]. Therefore, introducing HPWS in SMEs and using HPWS to induce organizational members’ internal motivation, leading to positive attitudes and behaviors, is important. Positive motivation for one’s own work and performance ultimately increases members’ sense of participation, and fostering a more diverse way of thinking is critical. Furthermore, creating opportunities to acquire new skills through the HPWS will allow organizational members’ creativity to develop and CP to improve.
Second, we verified that the core reason for increasing organizational members’ CP is through WI. We argue that organizational members’ WI is associated with a high-involvement work system. This is a process of providing various information, knowledge, power, and rewards for working autonomously or independently of directions and management [88]. To utilize the high-involvement work system more efficiently, organizations need to regularly check what factors are positive for individual and organizational performance when performing work, and they should focus on pursuing and building an innovative system that allows organizational members to immerse themselves. Furthermore, since the high-involvement work system focuses on organizational members’ autonomy, creating a work environment where they exert their abilities to the fullest when performing work by granting them empowerment and autonomy is urgent. Additionally, to achieve creative results and thus greater CP, SMEs should reward organizational members for freely utilizing their own innovative methods rather than punishing them for their failures.
Third, to enhance CP, efforts from organizations, leaders, and subordinates are needed. Creativity is especially important in relation to individual abilities, and organizational members’ creativity stimulates autonomous motivation in both learning and life and eventually leads to a higher level of CP [89]. Moreover, creative self-efficacy in terms of individual ability is an important variable that enhances creative behavior and CP [90,91,92] Creative self-efficacy is created from successful experiences and learning. Therefore, the role of leadership is important in increasing organizational members’ creative self-efficacy, and leaders must create opportunities for subordinates to think in new ways. In particular, transformational leadership is regarded as critical in increasing creative self-efficacy. Additionally, in terms of organizational perspective, organizations should create an organizational culture that induces creative behavior and enhances creativity. When hiring employees, organizations should hire highly creative employees and influence the creativity of colleagues to enhance group creativity in SMEs.
Finally, the strategies of human resource management are important for SMEs to improve organizational members’ CP, and this is an essential element in enhancing CP. SMEs should consider strategies to develop organizational members’ creative abilities by improving their effectiveness and reliability in management activities [93,94]. Further, SMEs should pursue the direction of CP through the organizational members’ creativity because SMEs pursue organizational innovation in a rapidly changing and competitive business environment. To this end, SMEs should create an innovative atmosphere and provide organizational support that enhance CP. Perceived organizational support by organizational members is expected to lead to more positive attitudes toward and involvement with the organization and work, which will contribute to enhancing CP.

5.3. Limitations and Future Directions

While this research includes various aspects of contributions to the literature with regard to SMEs and research fields, it has limitations as well.
First, it used data collected through a questionnaire only once (Time 1) for empirical analysis. Our research is a cross-sectional study, and the results were derived based on the primary analysis. Such results are considered to have some limitations in clarity and specificity with regard to members’ cognitive level and behavioral changes and the organizational system over time. In future studies, longitudinal research should be conducted over a longer time period—for example, through a longitudinal empirical study to increase CP by conducting measurements at three time points [95]. In particular, at least three measurements over three months will be necessary. Longitudinal research solves how organizational members perceive the level of HPWS from the organization; moreover, it allows us to better measure the changes in the levels of high-involvement work system and of CP according to the changes over time in HPWS level. Longitudinal research will be able to produce more valuable research results.
Second, this research used a self-report research design and method. Measuring HPWS and LMSCS has no major limitations because these are related to the organizational members’ cognition. However, LMSCS are also related to behavior, and measuring CP by relying on superiors or managers is considered more appropriate than measuring by self-report. This aspect of the method is seen as a limitation. Therefore, the measurement subjects will need to be separated to reduce the problems of common method bias in future studies. For example, subordinates should measure the leaders’ characteristics or behaviors. In addition, superiors or managers should measure subordinates’ attitudes, behaviors, and performances.
Third, our study is the first to verify the mediating effect of WI on the impact of HPWS on CP and the moderating effect of LMSCS, which can be considered a valuable contribution. However, we conducted an empirical study targeting organizational members from Chinese SMEs only, which is considered a limitation. We are eager to understand whether the same research results would be obtained if we conducted an empirical study targeting other types of companies or SMEs in other countries in addition to Chinese SMEs. Therefore, conducting a comparative study targeting SMEs, large companies, and small companies in future studies would be more valuable, expanding the scope and identifying the differences between countries. Especially, the sample in our research (315 employees from Chinese SMEs) raises questions about generalizability. Depending on the type and characteristics of the organizations, there may be differences in various aspects such as organizational culture, management function, and leadership style. This study focused only on Chinese SMEs. Therefore, if in-depth research is conducted on small and large enterprises rather than SMEs, it is expected that there may be some differences results from this research. Future research will need to design a variety of measurement targets and conduct comparative studies. Specifically, it will be necessary to focus on large firms or cross-country samples, and furthermore, it will be necessary to verify any differences between countries by targeting companies from different countries. Furthermore, empirical research should be conducted on a variety of industries to verify the accuracy and differences in the analysis results in future studies. For example, the service industry [96], education industry [97], and bank industry [98].
Fourth, although utilizing various moderating variables as a way to enhance CP would have been more valuable, only the LMSCS was utilized as a moderating variable. This is because the LMSCS variable is not widely known in the literature or in empirical studies. This study is valuable in that it suggests the interaction with HPWS through a new approach utilizing the LMSCS. As it is the first attempt, and the moderating effect was insignificant, the result was contrary to our expectations, which is considered a limitation of this study. The moderating effect of the LMSCS is thought to be related to the amount of data collected in this study, organizational characteristics of SMEs, and context. In future studies, more data should be collected to confirm whether the significance of the moderating effect is verified in empirical research targeting large corporations. Additionally, empirical research should be conducted on moderating variables that promote CP, such as psychological safety [99], authentic leadership [100], manager coaching behavior [101], organizational identification [102], and job difficulty [103].
Fifth, we acknowledge that the RMSEA value (0.095) is not excellent. Therefore, the value of RMSEA is considered as a limitation of this research. Although the RMSEA value (0.095) is not excellent, previous research has emphasized that a RMSEA value of 0.095 is acceptable. For example, Zhang and Gao found an RMSEA of 0.095, which is well below 0.1 (Zhang & Gao, 2023). In addition, Zhu and Lin had an RMSEA of 0.095, which is less than 0.1, but the overall fitting of the model is acceptable (Zhu, & Lin, 2022). In relation to these results, we confirm that the value of RMSEA is not excellent, but it is not considered to be at an unacceptable level. In relation to such results, we emphasize that it is necessary to collect more data and measure whether the results of the fit index improve.
Finally, the last limitation of this study is that the research was conducted at the individual level, which has focused on organizational members in Chinese SMEs. For more in-depth insights, conducting empirical research divided into individual and group levels is important. Organizational performance is related to individual and group performance. Despite a substantial body of literature on organizational performance, gaps remain in understanding how individual and group aspects together in-fluence performance in specific organizational contexts, such as higher education and public sector [104]. We argue that future research is needed to explore the individual- and organizational-level elements leading to organizational performance.

Author Contributions

Conceptualization, Z.L. and C.Z.; methodology, X.J.; software, X.J.; validation, X.J.; formal analysis, X.J.; data curation, Z.L. and C.Z.; writing—original draft, Z.L. and C.Z.; writing—review and editing, X.J.; supervision, X.J. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no external funding.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this paper:
SMEsSmall and medium-sized enterprises
HPWSHigh-performance work system
LMSCSLearning method system of comprehensive systems
WIWork involvement
CPCreative performance
AMOAbility–motivation and opportunity
SEMStructural equation modeling
AVEAverage variance extracted

Appendix A

VariablesItemsReference
high-performance work system 1. This subsidiary offers training to improve the interpersonal skills of employees.[59]
2. New employees undergo extensive orientation training in order to learn the values and culture of this subsidiary and/or its American parent company.
3. Many of this subsidiary’s employees are moved through a series of different job assignments in order to prepare them for future assignments.
4. The employee selection process is very rigorous in this subsidiary (e.g., use of tests, aptitude test, interviews, etc.).
5. There is advance planning as to which of this subsidiary’s current employees will be transferred or promoted when there is a job vacancy.
6. An employee’s job performance is appraised, to a significant extent, on how well he or she follows orders and company procedures and rules.
7. We strive to keep a large salary difference between high and low performers in the same position.
8. An employee’s pay is closely tied to individual or group performance in this subsidiary.
9. Employees often work in self-directed teams.
10. This subsidiary extensively shares its financial and/or performance data with its employees.
11. This subsidiary devotes considerable resources to manager training and development.
12. We do a great deal of cross-training, so that managers are familiar with different jobs and can fill in for others when necessary.
Work involvement 1. I have sufficient authority to fulfill my job responsibilities.[60]
2. I have enough input in deciding how to accomplish my work.
3. I have enough freedom over how I do my job.
Learning method system of comprehensive system 1. My company adopts certain methods to promote employees’ continuous learning and innovation.[45]
2. Company adopts certain motivation systems to promote employees’ continuous learning and innovation.
3. My company will invest certain human, financial and material resources to promote employees’ continuous learning and innovation.
4. The organizational structure adopted by my company is conducive to employees’ continuous learning and innovation.
5. Company’s management system is conducive to employees’ continuous learning and innovation.
Creative performance 1. Suggests new ways to achieve goals or objectives.[62]
2. Comes up with new and practical ideas to improve performance.
3. Searches out new technologies, processes, techniques,
and/or product ideas.
4. Suggests new ways to increase quality.
5. Is a good source of creative ideas.
6. Is not afraid to take risks.
7. Promotes and champions ideas to others.
8. Exhibits creativity on the job when given the opportunity to.
9. Develops adequate plans and schedules for the implementation of new ideas.
10. Often has new and innovative ideas.
11. Comes up with creative solutions to problems.
12. Often has a fresh approach to problems.
13. Suggests new ways of performing work tasks.

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Systems 13 00298 g001
Figure 1. Research model.
Figure 1. Research model.
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Figure 2. The moderating effect of LMSCS.
Figure 2. The moderating effect of LMSCS.
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Figure 3. The moderating effect of LMSCS.
Figure 3. The moderating effect of LMSCS.
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Figure 4. The moderating effect of LMSCS.
Figure 4. The moderating effect of LMSCS.
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Table 1. Previous studies.
Table 1. Previous studies.
Previous Studies
Authors and DateStudy TitleStudy VariablesFindingsGaps
Miao & Cao (2019)High-performance work system, work well-being, and employee creativity: Cross-level moderating role of transformational leadership.High-performance work system, work well-being, employee creativity, transformational leadership.High-performance work system is positively related to employee creativity.
Work well-being mediated the relationship between
high-performance work system and employee creativity.		Although previous studies have attempted to explore the influence of HPWS on employees’ creativity, both the underlying mechanism and boundary conditions are not yet fully understood.
Imran, R., Shabbir, M. S., & Mahmood, A. (2020)High-Performance Work System: an important link between transformational leadership and job performance.High-performance work system, transformational leadership, Job performance.To measure job performance, items on task performance and in-role behavior were used and verified as a single job performance factor. The results of the study showed that HPWS has a positive significant
effect on job performance.		The gaps exist between organizational work system and creative performance. We emphasize that it is worth to verify the effect of HPWS on creative performance that can be useful in specific and current competitive management environments, rather than simply overall job performance.
Seong, Yang, & Zhang (2023)What Initiates Creativity in an Organization?: A Two-Horse Carriage of HRM and PO FitCorporate citizenship-oriented high-performance work system (CC-oriented HPWS); individual creativity; person-organization fit (PO fit)Corporate citizenship-oriented high-performance work system has a positive relationship with individual creativity. Corporate citizenship-oriented high-performance work system leads to high level of individual creativity.The importance of corporate citizenship-oriented high-performance work systems was emphasized and explained organizations and managers should focus on fostering and enhancing creative performance through HPWS.
According to suggested above, we recognize that the direction of future research, which reveals the causal relationship between high-performance work systems and creative performance should be conducted. In addition, an empirical research on high-performance work systems and creative performance is still insufficient, and furthermore, empirical research targeting Chinese SMEs is quite insufficient.
Table 2. The reliability and of confirmatory factor analysis.
Table 2. The reliability and of confirmatory factor analysis.
VariablesItemEstimateS.E.C.R.pStandardized
Regression
Weights		AVECRCronbach’s aLMSCSha
HPWSHPWS11 0.8040.6360.9310.971
HPWS20.910.04918.578***0.766
HPWS30.8940.05316.886***0.728
HPWS41.0130.0425.564***0.880
HPWS51.0250.04622.199***0.833
HPWS60.9810.04720.92***0.811
HPWS71.0520.05120.515***0.804
HPWS80.840.05216.047***0.718
HPWS90.9230.04520.588***0.805
HPWS101.0830.04922.283***0.833
HPWS111.0640.05718.612***0.766
HPWS121.0980.05320.899***0.811
WIWI11 0.8540.6880.7950.917
WI21.1190.0522.369***0.859
WI31.0750.0618.038***0.773
LMSCSLMSCS11 0.8800.8270.9460.975
LMSCS21.0580.03728.876***0.880
LMSCS31.060.03728.279***0.907
LMSCS41.0950.03531.675***0.937
LMSCS51.1190.03532.233***0.941
CPCP11 0.8960.7910.9730.987
CP21.040.03727.914***0.895
CP31.0260.02344.089***0.903
CP41.040.03629.126***0.906
CP51.080.03629.992***0.913
CP61.0670.03927.614***0.891
CP71.050.0426.284***0.876
CP81.0560.03927.368***0.888
CP91.010.03826.533***0.879
CP101.0220.0425.496***0.867
CP111.0090.04124.551***0.855
CP121.0330.03727.723***0.892
CP131.0570.03828.086***0.896
Model Fit Indexχ2(p) = 1834.848 (.000), χ2/df = 3.855, RMSEA = 0.095, IFI = 0.919, TLI = 0.910, CFI = 0.919, PGFI = 0.634, PNFI = 0.806
***: p < 0.001.
Table 3. The descriptive statistics and correlation analysis.
Table 3. The descriptive statistics and correlation analysis.
MeanStandard DeviationHPWSWILMSCSCP
HPWS5.5321.297-
WI5.3521.4490.849 ***-
LMSCS5.6591.3720.859 ***0.751 ***-
CP5.5781.2960.864 ***0.793 ***0.792 ***-
***: p < 0.001, **: p < 0.01. *: p < 0.05.
Table 4. The results of HTMT inference.
Table 4. The results of HTMT inference.
Original Data (O)Data Average (M)5.0%95.0%Data Average (M)Bias5.0%95.0%
HPWS → WI0.9580.9580.9360.9760.95800.9360.976
HPWS → LMSCS0.8840.8830.8340.9240.883−0.0010.8330.923
HPWS → CP0.8830.8830.8270.9280.883−0.0010.8240.927
LMSCS → WI0.8670.8650.8140.9080.865−0.0010.8130.907
LMSCS → CP0.8070.8060.7240.8730.806−0.0010.7190.870
WI → CP0.8610.8610.8050.9070.861−0.0010.8020.905
Table 5. The hypothesis test (AMOS).
Table 5. The hypothesis test (AMOS).
PathEstimateS.E.tp
HPWS → WI0.8860.04320.681***
HPWS → CP0.5760.0728.046***
WI → CP0.2510.0713.527***
Indirect effectEffectBoot LLCIBoot LUCI
HPWS → WI → CP
(X → M → Y)		0.2470.0580.456
Model Fit Indexχ2 (p) = 1287.561 (.000), χ2/df = 3.937, RMSEA = 0.097, IFI = 0.931, TLI = 0.920, CFI = 0.930, PGFI = 0.626, PNFI = 0.787
***: p < 0.001.
Table 6. The mediating effect of WI (SPSS Macro Process).
Table 6. The mediating effect of WI (SPSS Macro Process).
The Direct Effect of HPWS on CP
PathEffectsetpBoot LLCIBoot
LUCI
HPWS → CP0.6810.05312.952***0.5780.784
The Indirect Effect of HPWS on CP
PathEffectBoot SE.Boot LLCIBoot LUCI
HPWS → WI → CP
(X → M1 → Y)		0.1800.0580.0710.295
***: p < 0.001.
Table 7. Moderated mediation effect of LMSCS.
Table 7. Moderated mediation effect of LMSCS.
Dependent Variable: CP
ModeratorLevelConditional
Indirect Effect		Boot SEBoot LLCIBoot ULCI
LMSCS4.20000.1650.0520.0610.267
6.00000.1680.0540.0610.275
7.00000.1690.0560.0610.28
Index of moderated mediation
IndexBoot SEBoot LLCIBoot ULCI
0.0010.002−0.0030.007
Table 8. Moderating effect of LMSCS.
Table 8. Moderating effect of LMSCS.
Dependent Variable: CP
EffectsetpBoot LLCIBoot
LUCI
constant0.8540.322.6720.0080.2251.483
HPWS0.5020.0965.22300.3120.691
WI0.1790.0473.84600.0880.271
LMSCS0.1270.0771.6510.099−0.0240.278
Interaction (HPWS × LMSCS)0.0080.0130.6180.537−0.0180.034
Table 9. The moderating effect of LMSCS.
Table 9. The moderating effect of LMSCS.
Dependent Variable: WI
Model 1Model 2Model 3
βtβtβtVIF
Gender Dummy−0.061−1.387−0.062−1.409−0.068−1.5521.177
Age−0.030−0.558−0.030−0.563−0.022−0.4061.743
Education−0.011−0.238−0.009−0.182−0.016−0.3371.431
Service Year0.0821.5050.0811.4890.0681.2501.824
HPWS (A)0.746 ***17.5230.731 ***12.3670.686 ***11.3332.270
LMSCS (B) 0.0230.3860.0010.0172.220
Interaction (A × B) 0.126 **2.7251.328
R2 (Adjusted R2)0.566 (0.558)0.566 (0.556)0.578 (0.567)
F68.61157.01651.130
***: p < 0.001, **: p < 0.01. *: p < 0.05.
Table 10. The moderating effect of LMSCS.
Table 10. The moderating effect of LMSCS.
Dependent Variable: CP
Model 1Model 2Model 3
βtβtβtVIF
Gender Dummy0.0781.8660.0711.7010.0651.5821.177
Age0.0010.020−0.001−0.0220.0080.1611.743
Education−0.010−0.2250.0060.120−0.002−0.0501.431
Service Year0.0500.9530.0460.8800.0310.6091.824
HPWS (A)0.753 ***18.4580.656 ***11.7310.609 ***10.6642.270
LMSCS (B) 0.142 *2.5050.119 *2.1052.220
Interaction (A X B) 0.134 **3.0571.328
R2 (Adjusted R2)0.602 (0.595)0.612 (0.603)0.625 (0.615)
F79.658 ***68.759 ***62.148 ***
***: p < 0.001, **: p < 0.01. *: p < 0.05.
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Lyu, Z.; Zhang, C.; Jin, X. Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field. Systems 2025, 13, 298. https://doi.org/10.3390/systems13040298

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Lyu Z, Zhang C, Jin X. Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field. Systems. 2025; 13(4):298. https://doi.org/10.3390/systems13040298

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Lyu, Zhiliang, Chengao Zhang, and Xiu Jin. 2025. "Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field" Systems 13, no. 4: 298. https://doi.org/10.3390/systems13040298

APA Style

Lyu, Z., Zhang, C., & Jin, X. (2025). Organizational Work System as the Predictor of Creative Performance: A New Approach to the Learning Method System of Comprehensive Systems and Expansion of Research Field. Systems, 13(4), 298. https://doi.org/10.3390/systems13040298

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