The Green Dilemma: The Impact of Inconsistent Green Human Resource Management and Innovation on Employees’ Creative Performance

Abstract

With increasing global attention on environmental sustainability, fostering employees’ green creativity has become crucial for organizations. However, the high costs and complexity of green initiatives frequently result in superficial measures rather than genuine innovation, creating a contradiction between corporate green rhetoric and actual practices. Drawing on cue consistency theory and social information processing theory, this study examines how the inconsistent implementation of green human resource management (GHRM) and organizational green innovation (OGI) impacts employees’ green creativity, with uncertainty perception as a critical psychological mediator. Data were collected from 410 employees across diverse industries using structured surveys and we validated the model through polynomial regression and response surface analysis. We found that both green human resource management and organizational green innovation were positively correlated with employees’ green creativity. Perceived uncertainty mediated the relationship between their synergistic effects and green creativity. Notably, alignment between green human resource management and organizational green innovation amplified their positive impact on green creativity. When the two were misaligned, their combined effect on employees’ green creativity exhibited a U−shaped relationship. This study demonstrates that organizations should implement coherent environmental strategies that align GHRM with OGI to foster sustainable innovation in practice.

1. Introduction

As global environmental challenges intensify, sustainability has emerged as a central pillar of modern business strategy [1]. This shift reflects a fundamental change in how employees cognitively process and emotionally respond to corporate environmental stewardship, which now significantly influences workplace attitudes and behaviors [2]. Organizations face mounting psychological pressure to authentically address climate change, as employees increasingly evaluate their employers through both ecological impact and internal policy-behavior consistency lenses. This dynamic creates complex cognitive dissonance when perceived environmental commitments diverge from actual practices, directly impacting employee motivation and organizational trust.

The United Nations Sustainable Development Goals (SDG 8) framework emphasizes this psychological dimension by advocating “sustained, inclusive and sustainable economic growth” that addresses both environmental and human behavioral factors [3]. Within this context, Green Human Resource Management (GHRM) has emerged as a critical psychological contract between organizations and employees, integrating environmental sustainability into fundamental HR processes [4]. GHRM practices, ranging from eco-conscious recruitment to sustainability-focused performance metrics [5], represent more than operational changes; they constitute powerful psychological signals that shape employee perceptions, attitudes, and ultimately, their green creative behaviors.

Under the influence of national policies and societal expectations, many companies often seek to project an environmentally responsible image by implementing formal green policies [6]. Enterprises are experiencing intensified multistakeholder scrutiny from civil society and governmental regulators, creating an institutional pressure mechanism that accelerates strategic pivots from traditional resource-intensive development paradigms to circular economy-aligned transition pathways [7]. However, the high costs and complexity of green initiatives frequently result in superficial measures, such as policies or promotional campaigns, rather than genuine green innovation. For instance, companies like Nike have been accused of “green washing”, promoting sustainability efforts in marketing while failing to implement significant changes in their production processes. This disconnect between the company’s green rhetoric and its actual practices creates a contradiction for employees. While green HR practices, such as performance evaluations based on environmental responsibility, encourage employees to contribute to sustainability, they may feel demotivated when they observe limited tangible outcomes in green innovation. If staff members view the company’s dedication to sustainability as insincere, it may dampen their enthusiasm for coming up with creative ideas related to sustainable products and so on. On the flip side, when there is a genuine match between the organization’s policies and actions, it tends to encourage more active participation in green innovation endeavors.

This raises an important research question: How does the alignment or misalignment between the employees’ perception of organization’s green HR practices and real innovation affects employees’ green creativity? Given the growing importance of green creativity for organizations aiming to meet sustainability goals, understanding this relationship is crucial for fostering a more sustainable and innovative workplace of enterprises.

The implementation of GHRM has many benefits for enterprises and organizations, such as green technology innovation, organizational culture, corporate environmental performance, etc. [8]. GHRM has also been linked to employees’ enhanced green creativity [9], mediated by mechanisms such as ethical leadership [10], green work engagement [11], and enabling green culture factors such as employee empowerment [12]. Other mediating pathways include environmentally felt responsibility and active engagement in eco-initiatives [13].

Researching moderating mechanisms, scholars have emphasized the role of leadership styles. For instance, Farooq, R. proposed that green transformational leadership could mediate the relationship between the two constructs [14]. Ahmad et al. validated the moderating role of ethical leadership style in this relationship; Abualigha et al. explored the moderating effect of spiritual leadership between the two [11]. Muisyo et al. confirmed the moderating influence of environmentally specific servant leadership [12]. Additionally, there is research that focuses on the impact of employee characteristics, using individual traits of employees as moderating variables. Moreover, Ahmed et al., drawing on Self−Determination Theory (SDT), proposed that organizational factors, specifically the quality of green communication, could moderate the relationship between the two constructs [13].

However, despite these advances, existing studies have largely overlooked the internal psychological tension caused by the perceived inconsistency between green HRM and actual green innovation within organizations. The mechanisms through which these inconsistent perceptions influence employees’ green creative behavior remain underexplored. Addressing this gap is crucial for understanding how employees cognitively and emotionally respond to misaligned sustainability practices and how such responses ultimately shape workplace innovation.

Therefore, this study introduces employee uncertainty perception as a key mediating variable to investigate how GHRM and organizational green innovation jointly influence employees’ green creativity. Drawing on cue consistency theory, this study uses a polynomial regression analysis to investigate under the conditions of consistency and inconsistency, that is, under the conditions of alignment and misalignment, employees’ green creative behavior.

2. Theoretical Foundation

2.1. Cue Consistency Theory

The cue consistency theory (CCT) suggests that individuals form attitudes and behaviors based on the consistency of the information they receive from various sources about an entity [15,16]. When the cues provided by an organization, such as policies, behaviors, and practices, are consistent, they reinforce each other, leading individuals to integrate these signals into their attitudes and behaviors in a coherent way [17]. In particular, when multiple sources of information about an entity align, people are more likely to develop stronger, more consistent attitudes and engage in behaviors that reflect these integrated values [16,18]. Conversely, when there is inconsistency between the cues, such as a gap between a company’s green initiatives and its actual green practices, individuals may place more emphasis on the negative aspects of the cues, which can lead to disengagement or a decrease in motivation [19,20].

Given the core premise of cue consistency theory that consistent cues from an organization create a coherent message for employees, this theory is particularly relevant to understanding how organizational green behavior affects employee attitudes and behaviors, such as green creativity. For example, when an organization presents consistent signals about its commitment to sustainability—through both green HR practices (such as performance evaluation systems rewarding green behavior) and actual green innovations—employees are more likely to internalize these cues, which could enhance their motivation and creativity in green initiatives. However, if an organization demonstrates inconsistencies—promoting green values in its HR practices while not following through with substantial green innovation—employees may perceive these actions as contradictory, potentially undermining their motivation to engage in green creative behavior.

Accordingly, we adopted cue consistency theory [16] as the theoretical foundation for our research, as it effectively explained how the consistency or inconsistency of organizational signals influenced employee behavior, particularly in relation to green creativity.

2.2. Social Information Processing Theory

Social information processing theory (SIPT) [21], posits that individuals develop attitudes and behaviors based on the social cues they receive from their environment. This theory emphasizes the role of information provided by organizational practices, leadership, and colleagues in shaping employees’ behavior. In the context of GHRM, employees’ green creativity is influenced by signals such as sustainability-oriented HR policies and organizational green innovation initiatives. When these cues are aligned, employees may present more positively to support green innovation, contributing to sustainable practices.

However, if employees receive inconsistent or contradictory signals—for example, when organizations promote green development but fail to implement genuine green innovations—this can create confusion or skepticism. As a result, employees may feel demotivated, reducing their willingness to contribute innovative ideas for green products, services, or processes.

Thus, SIPT is particularly useful in examining how organizational cues about sustainability, communicated through HRM and leadership, influence employees’ attitudes and creativity. It highlights the importance of consistent, clear signals for promoting green innovation and creativity within organizations.

3. Literature Review and Hypothesis Development

3.1. GHRM, OGI, and EGC

The core of GHRM is to integrate environmental management into the entire process of human resource management, including recruiting environmentally conscious employees, enhancing employees’ environmental knowledge and skills, formulating training courses to improve employees’ environmental participation, and providing guidance on environmentally friendly behaviors [22]. Employees are rewarded for considering environmental performance in the performance appraisal system. GHRM directly enhances employees’ environmental awareness and skills by implementing environmentally oriented recruitment, training, performance management, and reward and punishment measures, thereby stimulating their green behavior and creativity [23]. In addition, GHRM enhances employees’ green perceived organizational support [24]; employees believe that the organization will value their contribution to environmental sustainability and reward them accordingly, which is crucial for the development of green creativity, as employees who are supported by the organization are more likely to innovate and implement green solutions [25]. At the same time, through the training of environmental protection knowledge and skills, the implementation of green performance appraisal management, and reward and punishment measures, GHRM creates an organizational atmosphere conducive to environmental protection management [26], through which employees’ green innovative thinking is inspired and transformed into green creativity.

Organizational green innovation (OGI) promotes the green creativity of employees by introducing new systems, products, and processes that reduce the environmental burden of enterprises. Organizational green innovation refers to reducing the environmental burden of enterprises through the introduction of new systems, products, and processes. It is the outstanding performance and achievement of enterprises putting their determination for green development into practice. Firstly, the organization’s green innovation strategy can stimulate employees’ green creativity [27]. Secondly, an organizational green innovation strategy gives rise to green transformational leadership, which has a positive impact on employees’ green creativity [27,28]. In addition, GHRM plays an intermediary role between green transformational leadership and employees’ green creativity by implementing environmentally oriented recruitment, training, performance management, and reward and punishment measures, which directly enhance employees’ environmental awareness and skills, thus stimulating their green behavior and creativity [26]. At the same time, employees’ green role identification and the organization’s transactive memory system strengthen the connection between green entrepreneurial orientation and employees’ green creativity. To sum up, organizational green innovation comprehensively affects employees’ green creativity through a variety of direct and indirect ways and promotes employees’ innovative thinking and behavioral performance in environmental protection and sustainable development [26].

Therefore, GHRM and OGI both convey to employees the signal of the organization’s pursuit of green development, so that the working environment of employees is permeated with the concept of green development, which can influence employees through psychological processes to a certain extent, such as cognition and behavior, affecting employees’ green innovative thinking and thus positively affecting employees’ green creativity [29].

Enterprises’ GHRM practices and organizations’ green innovation behaviors may provide employees with relevant information about green development [5], affecting their individual motivations such as environmental values, environmental protection capabilities, or green motivations. According to the consistency theory, the determination for green development can be conveyed to employees by implementing green development practices such as organizational green innovation to shape the organizational environment for green development from both conceptual and practical dimensions and psychologically influence employees. With green innovative thinking, employees also show green innovative behaviors in order to maintain the consistency of their individual behaviors, which positively impacts on EGC. Therefore, this study proposes hypothesis 1 and hypothesis 2:

H1: 

GHRM positively affects EGC.

H2: 

OGI positively affects EGC.

3.2. GHRM and OGI

Based on the CCT, after individuals obtain information from different channels, their judgments are more inclined to maintain consistent information, and at the same time, their actions show the same consistency as their judgments [30]. Combined with hypotheses 1 and 2, GHRM and OGI positively affect EGC. GHRM and OGI are both signals that organizations release to employees to pursue the green development that the organization advocates and puts into practice [9,29]. According to the cue consistency theory, employees rely on the environment during their actions. A variety of information is used as clues, and its consistency is evaluated. When the clues are consistent, the perception of the information is enhanced. Therefore, when employees receive signals that the organization pursues green development through GHRM and the information released by the OGI, employees judge that the organization wants to pursue green development, and because the information they receive about green development is consistent, it enhances employees’ awareness of green development. As a result, employees align their behaviors with organizational behaviors, that is, employees actively show behaviors that are in line with the concept of green development and therefore may show a higher level of EGC. Therefore, this study proposes hypothesis 3:

H3: 

When GHRM and OGI are consistent, compared with the case where both levels are low, when both levels are high, the level of EGC is higher.

Consistency theory suggests that when the cues an individual obtains from the environment present inconsistent information, negative biased cognition dominates the individual’s information processing process, and they are more inclined to focus on negative information [20]. When GHRM is inconsistent with organizational green innovation, that is, the signals released by the organization to employees to advocate the pursuit of green development are inconsistent, the level of GHRM (the level of organizational green innovation) is very high. According to social information processing theory, when employees receive environmental protection information and green concepts, their recognition of green concepts is enhanced [31,32,33,34]. When the level of GHRM (OGI level) decreases and reaches the same level as the OGI level (GHRM level), during this process, employees receive non-environmental protection information provided by both parties at the same time, so the level of green creativity decreases. As the organization’s green innovation level (GHRM level) further increases, employees once again feel environmental protection information and green concepts, which enhances their recognition of green concepts. Thus, employees’ green creativity levels rise again. Therefore, this study proposes hypothesis 4:

H4: 

When GHRM and OGI are inconsistent, the combined effects of both parties on EGC have a U-shaped relationship.

3.3. The Mediating Role of Uncertainty Perception

Individual uncertainty can be defined as a feeling of doubt or instability about oneself, values, and the environment. There is also uncertainty about the cause and effect of certain things in society [35]. This uncertainty affects the individual’s self−reflection on information, the cognitive processing mechanism, thereby also affecting individual behavioral activities [36]. A higher sense of uncertainty may lead to negative effects, such as increasing an individual’s disgust and uneasiness, and even doubting the meaning of social behavior. In GHRM, employees’ sense of uncertainty about information may originate from the uncertain work organizational environment, such as vague environmental protection measures or conflict situations, which may cause employees to doubt the meaning of green concepts and experience negative emotions about the concept of green development, thus leading to employees’ reluctance to demonstrate green creativity.

Existing research has shown that uncertainty is not only an important factor in the development of creativity, but in some cases, it can act as a catalyst to promote innovative thinking and action [37]. According to the cue consistency theory [30], faced with various information in the work environment, employees conduct consistency evaluations on it. When employees feel GHRM and organizational green innovation, they participate in green initiatives. Being exposed to environmental protection information and green concepts enhances their recognition of green concepts, thereby reducing their uncertainty perception of environmental protection or green innovation work and ultimately increasing their green creativity.

On the contrary, if employees feel that the level of GHRM and the organization’s green innovation are inconsistent, the information they receive about the green development concept will be inconsistent, which will lead to an increase in employees’ uncertainty perceptions of this behavior. According to the uncertainty perception theory, it may lead to employees’ negative emotions towards the green development concept and even doubt the existence of the green development concept, resulting in employees being unwilling to show green creativity. Based on this, this study proposes hypothesis 5:

H5: 

UP plays a mediating role between the combined effect of GHRM and OGI and EGC.

Based on the above hypothesis, our research model (see Figure 1) aims to explore how GHRM and organizational green innovation can promote EGC by affecting employees’ UP. GHRM and OGI act as independent variables as they are perceived by employees, so the variables in the model are all at the individual level.

4. Methodology

4.1. Participants

This article used employees from 28 provinces including Jiangsu, Guangdong, Shandong, and Fujian as the survey subjects. This study did not limit the age, gender, region, and other factors of the research subjects, thereby increasing the generalizability of the research conclusions. This study focused on the individual employee level and considered maximizing sample availability. Therefore, subjects were recruited online through the Credamo platform, and 450 questionnaires were distributed online. After data collection, firstly, based on the reversed items in the questionnaire scale, questionnaires with obviously contradictory answers were screened out. Secondly, questionnaires with answers too uniform to each scale question and questionnaires with too short an answering time were screened out. After the above steps, a total of 410 valid questionnaires were finally obtained from the 450 questionnaires initially distributed.

A demographic analysis of the collected subject data showed that in terms of gender, males and females accounted for 38.8% and 61.2%, respectively; in terms of job levels, they were mainly ordinary managers, grassroots managers, and middle managers, accounting for 38.5%, 25.1%, and 26.3%, respectively; in terms of education level, undergraduate students accounted for the largest proportion at 76.6%.

4.2. Measurement Instruments

The variable measurement scales involved in this study were all relatively mature homegrown or foreign-language scales, and a multi-person two-way translation method was used for foreign scales to avoid false information or omissions caused by the translation process. In addition to the control variables, the core scales in this article all used the Likert 5-point scoring method, with 1 to 5 ranging from “strongly disagree” to “strongly agree”. The specific description of the variables involved in this article is as follows.

4.2.1. GHRM

The GHRM scale developed by Dumont [38] includes 6 items. Example questions include “My company has set green assessment goals for employees” and so on. Cronbach’s Alpha coefficient of this scale was 0.860.

4.2.2. OGI

The OGI developed by Chang et al. [39] includes 6 items. Example items include “My company will find new ways to achieve environmental goals” and so on. Cronbach’s Alpha coefficient of the scale was 0.868.

4.2.3. EGC

The EGC scale developed by Chen et al. [40] includes 6 items. Specific measurement items include “My company will find creative solutions to solve environmental problems” and so on. Cronbach’s Alpha coefficient of this scale was 0.854.

4.2.4. UP

After revision, five items were selected from the UP Scale (1994) developed by Gifford Weary [36] and others. Typical items include “When people have multiple possible reasons for their green behavior, it is difficult for me to do so.”, “Determine which one is the actual cause”, etc. Cronbach’s Alpha coefficient of this scale was 0.810.

4.3. Variable Data Processing Technology

The hypothetical reasoning and theoretical framework suggested complex nonlinear relationships among the variables. A response surface analysis draws the results of a polynomial regression analysis into a surface diagram in three-dimensional space, which can show the complex relationship between the combination of two predictor variables and one outcome variable through three-dimensional images and obtain the influence of consistency and difference between predictor variables on the outcome variable. Based on the outstanding advantages of polynomial regression and response surface analysis in exploring such nonlinear (such as U-shaped) dynamic relationships and interactions, which may not be fully captured by simple models, this study used polynomial regression analysis combined with a response surface to analyze the complex relationships among variables. This allowed us to more accurately model and understand the complex mechanisms through which GHRM and OGI affect employee creativity. The above-mentioned measured variables in this study all used the mean as individual-level data for analysis. Secondly, before conducting polynomial regression, the descriptive information of the two predictor variables (GHRM and OGI) was first examined and centered to reduce the possibility of multicollinearity. Based on the two centered predictor variables GHRM and OGI, three new variables were calculated: the square of GHRM (GHRM²), the product of GHRM and OGI (GHRM × OGI), and the square of OGI (OGI²), and the result variable (EGC) was derived from the following polynomial regression equation:

$$EGC=b_0+b_{1}GHRM+b_{2}OGI+b_3{GHRM}^2+b_{4}GHRM\times OGI+b_5{OGI}^2+\epsilon$$

(1)

5. Results

5.1. Common Method Deviation Test

Harman’s single factor test results showed that the proportion of the first principal component was lower than the recommended threshold, indicating that the study homology variance was within the acceptable range. At the same time, this study used a confirmatory factor analysis to test the results. From Table 1, it can be seen that the Standardized Root-Mean-Square Residual (SRMR) of the single factor model was 0.054, which is greater than 0.05, indicating that the model was not well fitted, confirming that there was no bias. For serious common method bias problems, the next step of statistical testing can be carried out.

5.2. Confirmatory Factor Analysis

We used MPLUS 8.3 to conduct the confirmatory factor analysis. The relevant results (Table 1) suggested the fitting index of the four-factor model was significantly better than others, and they were all within the empirical values, indicating that our variables had strong discriminant validity.

Table 1. Nested model fitting analysis results.

Model	χ2	df	RMSEA	CFI	SRMR
Four-factor model: (GHRM, OGI, UP, EGC)	861.986	224.00	0.083	0.883	0.047
Three-factor model: (GHRM, OGI + UP, EGC)	1057.765	227.000	0.094	0.847	0.053
Two-factor model: (GHRM + OGI + UP, EGC)	1065.648	229.000	0.094	0.846	0.054
Single-factor model: (GHRM + OGI + UP + EGC)	1091.633	230.000	0.054	0.841	0.054

Note: + represents the merging factor.

Table 1. Nested model fitting analysis results.

Model	χ2	df	RMSEA	CFI	SRMR
Four-factor model: (GHRM, OGI, UP, EGC)	861.986	224.00	0.083	0.883	0.047
Three-factor model: (GHRM, OGI + UP, EGC)	1057.765	227.000	0.094	0.847	0.053
Two-factor model: (GHRM + OGI + UP, EGC)	1065.648	229.000	0.094	0.846	0.054
Single-factor model: (GHRM + OGI + UP + EGC)	1091.633	230.000	0.054	0.841	0.054

Note: + represents the merging factor.

5.3. Descriptive Statistical Results and Correlation Analysis

Table 2. Descriptive statistical analysis results (N = 410).

Variables	M	SD	1	2	3	4
GHRM	4.20	0.66	1
OGI	4.26	0.63	0.86 **	1
UP	1.85	0.73	−0.71 **	0.68 **	1
EGC	4.27	0.56	0.80 **	0.77 **	−0.68 **	1

Note: 1 = GHRM; 2 = OGI; 3 = UP; 4 = EGC. ** represents p < 0.01.

shows that GHRM was significantly positively correlated with EGC (r = 0.801, p < 0.01), and OGI was significantly positively correlated with EGC (r = 0.773, p < 0.01). There was a significant negative correlation between GHRM and EGC (r = −0.708, p < 0.01). There was a significant negative correlation between UP and EGC (r = −0.678, p < 0.01). These results provided preliminary support for hypotheses.

5.4. Path Analysis and Hypothesis Testing

This article used a hierarchical regression analysis to verify our hypotheses. Results (

Table 3. Main effect test result (N = 410).

	EGC
	Model (1)		Model (2)		Model (3)
	B	SE	B	SE	B	SE
(constant)	0.464	0.228	0.220	0.179	0.251	0.192
Gender	0.049	0.04	0.044	0.031	0.056	0.033
Age	−0.037	0.036	−0.002	0.028	−0.012	0.030
Education	−0.001	0.038	0.015	0.03	−0.011	0.032
Years of working with leaders	0.113	0.029	0.028	0.023	0.053	0.025
Job level	0.016	0.022	−0.002	0.017	−0.001	0.019
Enterprise nature	−0.021	0.029	−0.016	0.023	0.002	0.025
Enterprise establishment year	0.023	0.033	0.002	0.026	−0.002	0.028
Enterprise scale	0.036	0.027	0.008	0.021	0.020	0.022
Engaged in industry	−0.032	0.009	−0.011	0.007	−0.012	0.008
Environmental awareness	0.803	0.043	0.434	0.041	0.439	0.046
GHRM			0.485 ***	0.03
OGI					0.458 ***	0.035
R2	0.546		0.725		0.682
F	47.951 ***		95.204 ***		77.255 ***
∆R2			0.179		0.135
∆F			258.048 ***		168.496 ***

Note: *** represents p < 0.001.

) showed that after controlling for the variables of personal characteristics and corporate characteristics, GHRM significantly positively impacted on EGC (B = 0.665, p < 0.001), and hypothesis 1 was supported. After controlling for the variables of personal characteristics and corporate characteristics, OGI significantly positively impacted on EGC (B = 0.664, p < 0.001), and hypothesis 2 was supported.

This paper used a polynomial regression analysis method combined with a response surface. As shown in

Table 4. Polynomial regression analysis results (N = 410).

Variables	EGC
	Mode (1)	Model (2)	Model (3)
(constant)	0.464	1.790	1.584
Gender	0.049	0.048	0.036
Age	−0.037	−0.001	−0.014
Education	−0.001	0.008	0.017
Years of working with leaders	0.113	0.027	0.032
Job level	0.016	−0.003	0.011
Enterprise nature	−0.021	−0.01	−0.005
Enterprise establishment year	0.023	−0.002	−0.006
Enterprise scale	0.036	0.009	0.000
Engaged in industry	−0.032	−0.009	−0.008
Environmental awareness	0.803	0.396	0.400
GHRM, b1		0.386 ***	0.348 ***
GHRM b2		0.142 **	0.429 **
GHRM2, b3			0.111 **
GHRM × OGI, b4			−0.17 **
OGI2, b5			0.180 ***
R2	0.546	0.731	0.748
∆R2		0.184 ***	0.202 ***
Consistency line
slope (b1 + b2)	0.777 ***
curvature (b3 + b4 + b5)	0.121 **
Inconsistencies Line
slope (b1 − b2)	−0.081
curvature (b3 − b4 + b5)	0.461 ***

*** represents p < 0.001, ** represents p < 0.01.

, after adding three quadratic terms, the ΔR2 of the model was significant, and subsequent polynomial regression and response surface analysis could be performed. The response surface analysis method used in this study mainly relied on the slope, curvature, and significance of the surface along the line of consistency (GHRM = OGI) and the line of inconsistency (GHRM = −OGI) to determine the degree of consistency and difference between the two predictor variables and the relationship between degree and outcome variable.

Based on the polynomial regression results, we used Origin to draw the response surface diagrams and curve diagrams of the surface under consistent and inconsistent situations. As shown in the regression results and response surface diagram (Figure 2), which present the response surface plot of the interactive influence relationship between the independent variables GHRM and OGI and EGC in the case of consistency and inconsistency. Figure 3 shows the trend of EGC with GHRM and OGI in the case of consistency (GHRM = OGI). The horizontal axis shows the values of GHRM and OGI, while the vertical axis shows the values of EGC. As can be seen from the figure, EGC showed an upward trend as the values of GHRM and OGI increased. This indicated that GHRM and OGI had a positive role in promoting EGC, that is, when the level of green human resource management and organizational green innovation increased, employees’ green creativity also increased. The slope (b₁ + b₂) was significant and more than zero, and the curvature (b₃ + b₄ + b₅) was significant. However, it can be seen from the figure that the curvature had little impact on the curve, and the curve showed a sloping downward trend. Therefore, the two predictor variables (GHRM, OGI) were lower than when both sides were consistent, and when both sides were unanimously high, the level of the outcome variable (EGC) was higher, that is, hypothesis 3 was confirmed.

Figure 4 shows the variation in the trend of EGC with GHRM and OGI in the case of inconsistency (GHRM = −OGI). The horizontal axis shows the values of GHRM and OGI, while the vertical axis shows the values of EGC. It can be seen from the figure that as the values of GHRM and OGI increased, EGC showed a trend of first decreasing and then increasing. The slope (b₁ − b₂) was not significant, the curvature (b₃ − b₄ + b₅) was significant and greater than zero, and the curve was “U”-shaped, that is, when green human resource management and organizational green innovation are inconsistent, if the level of GHRM is high and employees feel environmental information and green concepts, their recognition of green concepts is enhanced. Then, EGC levels are higher. When the level of GHRM decreases and reaches the same level as the OGI, during that process, employees receive non-environmental information provided by both parties at the same time, so the level of EGC decreases. As the level of OGI further increases, employees once again feel environmental protection information and green concepts, which enhances their recognition of green concepts. Thus, EGC levels increase, and hypothesis 4 is verified.

5.5. Mediation Effect Test

We built block variables to verify the mediating role of UP. Each item in the polynomial regression equation was multiplied by the coefficient in the polynomial regression result and then linearly combined to form a new block variable to represent the comprehensive effect of GHRM and OGI. The regression results are shown in

Table 5. Mediation effect test results (N = 410).

	EGC
	Model (1)		Model (2)
	B	SE	B	SE
(constant)	1.863	0.171	2.113	0.195
Gender	0.042	0.027	0.043	0.027
Age	0.003	0.025	0.003	0.025
Education	0.005	0.026	0.009	0.026
Years of working with leaders	0.011	0.020	0.006	0.020
Job level	−0.008	0.015	−0.007	0.015
Enterprise nature	−0.001	0.020	−0.002	0.020
Enterprise establishment year	−0.004	0.023	−0.005	0.023
Enterprise scale	0.006	0.018	0.008	0.018
Engaged in industry	−0.005	0.007	−0.002	0.007
Environmental awareness	0.253	0.040	0.245	0.039
Block variable	0.763 ***	0.036	0.705 ***	0.042
CU			−0.068	0.026
R2	0.786		0.789
F	132.259 ***		123.533 ***
∆R2			0.003
∆F			8.726 **

*** represents p < 0.001, ** represents p < 0.01.

. After adding uncertainty perception, compared with Model 6, Model 7’s explanation of EGC was significantly improved (ΔR² = 0.003, p < 0.001), and the impact of the block variables was still significant (p < 0.001). At the same time, the effect was also significant (p < 0.05), thus hypothesis 5 was confirmed.

6. Discussion and Conclusion

This study integrated theory with empirical research to explore the impact mechanism of the alignment between organizational green innovation and GHRM on employee green creativity and arrived at the following conclusions.

Firstly, both GHRM and organizational green innovation (OGI) positively influence employee green creativity. This finding is consistent with the existing literature, particularly regarding the impact of green management practices, as demonstrated by studies such as that of Luu [41], which showed that companies could motivate employees’ innovative behaviors through effective green management strategies. This suggests that enterprises should value the integration of green HRM and OGI and formulate more forward-looking green management policies.

Secondly, when GHRM and OGI are aligned, the level of employees’ green creativity is significantly higher than when both are low. This resonates with the “synergy effect” theory proposed by previous research such as that of Tu et al. [42], emphasizing the importance of coordination between green HRM and organizational innovation strategies. Enterprises can enhance the interaction between the two to improve employee innovation capabilities, thereby promoting the achievement of sustainable development goals. When GHRM and OGI are misaligned, the combined effect on employee green creativity exhibits a U-shaped relationship. Cue consistency theory focuses on how matching cues affect decision making. Our U-shaped findings demonstrate a more complex link between GHRM/OGI and creativity, highlighting that cue consistency can have nonlinear effects. This enriches the theory and shows its many manifestations in practical situations. This finding also provides a new perspective for understanding the complexity in green management practices and supports the “dynamic capabilities” theory proposed by Jurksiene and Pundziene [43], indicating that enterprises need to dynamically adjust their management strategies in the face of green innovation to adapt to the changing external environment.

Additionally, this study highlights the mediating role of uncertainty perceptions between the combined effect of GHRM and OGI and employees’ green creativity. This is consistent with the existing literature [44] indicating that employees’ sense of identification with green concepts and perceptions of uncertainty significantly affect their innovative behaviors. Therefore, when promoting green practices, enterprises should focus on enhancing employees’ sense of identification to reduce uncertainty and stimulate their creativity.

Furthermore, social information processing theory focuses on how individuals use social information. By introducing uncertainty perception, we showed how employees processed cues and uncertainty related to green initiatives, thus affecting their creativity. Enterprises should pay attention to employees’ psychological feelings, strengthen the dissemination of green concepts through training and communication, reduce uncertainty perceptions, and promote active participation and innovation among employees. The findings of this study also prompt managers to ensure consistency between GHRM and OGI when implementing GHRM and driving OGI to maximize EGC.

7. Implications

7.1. Theoretical Implications

Within the current academic research domain, the impact of GHRM and OGI on EGC has emerged as a focal point of study. Prior research has established the beneficial impact of GHRM on EGC [10,13], and similarly, OGI has been shown to positively affect EGC, yet the knowledge gap persists regarding the interplay of GHRM and OGI for EGC enhancement. By investigating how GHRM and OGI jointly impact EGC, this paper sought to bridge the existing academic void.

Firstly, the current research advances comprehension of the interconnected mechanisms bridging GHRM and OGI. GHRM encompasses not only the recruitment of employees with environmental awareness but also the cultivation of employees’ green skills and knowledge and motivation for staff to adopt green practices during routine tasks. These management practices provide an environment conducive to fostering employees’ green creativity, thereby laying a solid foundation for their innovation and environmentally friendly behaviors.

Secondly, this research examined the effects resulting from the alignment of GHRM frameworks with OGI systems on EGC. This research found that when there was an inconsistency between GHRM and OGI levels, it may have a negative impact on EGC. Therefore, organizations should strive to ensure that these two aspects of management practices complement each other to promote EGC.

Furthermore, this research emphasized the pivotal role of employees’ perception of organizational green development information in the transformation of GHRM and OGI into EGC. Employees adapt to work by receiving and interpreting the green development signals sent by the organization, which include GHRM practices and organizational green innovation activities. The accurate reception and interpretation of these signals by employees can enhance their green creativity; conversely, if employees receive unclear or inaccurate information, it may weaken their green creativity. Empirical data revealed that UP functioned as an intermediary pathway through which the collaborative influence of GHRM and OGI operates to affect EGC outcomes.

7.2. Practical Implications

First, enterprises should prioritize the implementation of GHRM and OGI to establish foundational support for EGC. Second, enterprises need to maintain alignment between the developmental levels of GHRM and organizational green innovation, as inconsistency between these two aspects may potentially generate adverse effects on sustainable development outcomes. Furthermore, enterprises should systematically monitor employees’ perceptions of corporate green development initiatives while consistently conveying green development signals through multiple channels. For instance, enterprises could administer standardized questionnaires to assess employee attitudes toward sustainability, implement structured green development training programs, and reinforce beliefs in environmental stewardship through institutionalized recognition systems. Finally, before implementing the sustainable development strategy, enterprises should consider the challenges that could emerge when harmonizing environmental initiatives with real-world implementation, such as inconsistency and employees’ uncertainty perception. Make strategic deployment and planning for these possible problems, and continuously monitor the whole process of sustainable transformation, so as to solve new problems immediately.

Decision-makers hold significant influence in fostering synergy between GHRM and OGI across sectors or nationwide. Effective methods to reach this target encompass formulating regulations, deploying verification procedures, and delivering encouragements. For example, policymakers could develop industry-specific GHRM and OGI standards that organizations can strive to meet. Certification programs can be introduced to recognize and reward organizations that effectively align their GHRM with OGI, thereby encouraging others to follow suit. Incentive measures such as tax breaks or grants can also be provided to organizations that demonstrate a strong commitment to GHRM and OGI alignment, further driving sustainable development in the industry or country.

8. Limitations and Future Research

This research has the following limitations: Firstly, the survey results relied on information gathered at one specific moment from participants. Consequently, the data were cross-sectional, leading to a deficiency in reflecting the social-interaction elements of employees’ green creativity. Future research could consider employing longitudinal case studies to further validate the research conclusions. Secondly, the study depended solely on employees’ self-assessments, which could be influenced by subjective bias. Subsequent investigations might incorporate diverse data sources (e.g., manager ratings of creative performance) or adopt a time-based research approach. Thirdly, due to the personnel constraints of the research team, the study did not comprehensively consider issues such as the duration of the organization’s GHRM and green innovation and whether the environmental attitudes of managers affected employees’ green perceptions. Subsequent studies might implement a follow-up survey method to persistently observe the previously assessed participants. Additionally, subsequent studies may investigate the intermediary processes and contextual factors linking OGI, GHRM, and EGC through diverse perspectives, enabling the development of a more comprehensive conceptual framework.