Environmentally-Specific Empowered Leadership and Employee Green Creativity: The Role of Green Crafting and Environmental Culture

Abstract

This study investigates how environmentally-specific empowered leadership influences employee green creativity and the mechanisms underlying this relationship. Drawing on Self-determination theory, we examine green crafting as a mediating process and environmental culture as a boundary condition. Analysis of multi-wave data reveals three key findings: (1) environmentally-specific empowered leadership positively affects employees’ green crafting behaviors; (2) green crafting mediates the relationship between leadership and employee green creativity; and (3) environmental culture strengthens the positive effect of empowered leadership on green crafting, subsequently enhancing green creativity. These findings extend leadership theory by identifying how and when empowering approaches specifically facilitate environmental innovation. For practitioners, our results highlight the importance of combining empowering leadership practices with a supportive environmental culture to foster employee-driven sustainable solutions. Organizations can leverage these insights to enhance environmental performance through targeted leadership development and cultural initiatives.

1. Introduction

Today’s world is facing unprecedented environmental challenges, and corporations, as one of the major sources of global carbon emissions and resource consumption, have been given an important responsibility to promote sustainable development. According to a recent report by the United Nations Environment Program, global corporate activities contribute about 60% of greenhouse gas emissions, and the current status quo will lead to a 2.8 °C rise in global temperatures this century if no additional action is taken [1]. In the face of this challenge, organizations need their employees to demonstrate sustainable creativity and develop innovative environmental solutions to balance the dual demands of economic development and environmental protection [2]. Employee green creativity (EGC) i.e., the ability of employees to generate environmentally relevant ideas and sustainable solutions has become a key driver for organizations to achieve sustainable transformation and gain competitive advantage [3]. However, how to effectively stimulate EGC and sustainable innovation remains a major challenge for organizational management practices.

Within this context, scholarly attention has gravitated toward investigating the influence of leader behaviors on subordinates’ sustainable innovative performance [4]. In particular, environmentally-specific empowered leadership (EEL), a leadership style that emphasizes employee autonomy and participation in decision-making, provides new perspectives on stimulating EGC by granting them decision-making autonomy, providing knowledge support, and encouraging innovation [5]. Although some studies have preliminarily confirmed the positive relationship between EEL and employees’ innovative behaviors [6,7], the intrinsic mechanisms regarding their promotion of sustainable innovation and EGC have not been systematically explored, which limits our understanding of how to effectively stimulate employees’ environmental innovation.

A review of the literature reveals two major theoretical gaps in current research. First, although existing literature has explored the relationship between leadership and sustainable innovation [8], it has mostly focused on transformational or green inclusive leadership, environmentally-specific transformational leadership and exploitative leadership, and less directly explored the unique role of EEL in EGC [9,10,11,12], especially in-depth analysis of the intrinsic mechanisms by which the important concept of EEL promotes sustainable innovation. Second, previous investigations into leadership-driven sustainable innovation have concentrated on psychological mediators like self-efficacy [13], identification [14,15], and internal motivation [16], the role of employee proactivity remains underexplored. Contemporary perspectives suggest that employees actively construct their work environment rather than simply responding to leadership initiatives [17]. Green crafting (GC) represents a distinct extension of the general job crafting concept, specifically focused on environmental sustainability. While traditional job crafting refers to employees’ proactive changes to their job boundaries, relationships, and perceptions to enhance personal meaning and identity [17], green crafting uniquely emphasizes environmentally-oriented modifications to work. The process of GC, whereby individuals actively reconfigure their task boundaries, interpersonal connections, and cognitive frameworks, potentially serves as a critical intermediary mechanism in the EEL-EGC relationship.

To address these significant gaps in our understanding, we draw upon self-determination theory (SDT) to develop and test a comprehensive model of how EEL influences EGC through employee GC [18]. Recent research suggests that this theory provides a strong theoretical foundation for understanding sustainable behavior [16,19]. First, unlike leadership theories that focus primarily on leader behaviors, SDT centers on the psychological experiences of followers, specifically how environmental factors (including leadership) satisfy or thwart basic psychological needs. Second, SDT explicitly connects need satisfaction to autonomous motivation and proactive behavior, making it particularly suitable for understanding employee-initiated behaviors like GC. Third, recent extensions of SDT have specifically addressed environmental contexts, proposing that autonomy-supportive environments promote internalization of environmental values and subsequent pro-environmental behaviors [20]. SDT emphasizes the satisfaction of three basic psychological needs—autonomy, competence, and relatedness—as a core mechanism for promoting intrinsic motivation and proactive behavior [18,21]. Recent research suggests that this theory provides a strong theoretical foundation for understanding sustainable behavior [16,19]. Based on SDT, we argue that environmentally empowered leaders promote autonomous motivation for work shaping by meeting the basic psychological needs of employees, which in turn stimulates EGC.

Drawing upon Self-Determination Theory (SDT), we propose that green crafting (GC) serves as a critical mediating mechanism through which EEL influences EGC, while employee environmental consciousness (EC) moderates the relationship between EEL and GC. This study poses two core research questions: (1) How does EEL affect employees’ GC? (2) Does GC mediate the relationship between EEL and EGC? This paper extends the existing literature in two integrated framework addresses crucial gaps in sustainable leadership literature, which has traditionally overlooked the proactive role employees play in translating leadership influence into creative environmental outcomes. Our research is particularly valuable in the Chinese context, where organizations across diverse industries face intensifying environmental regulations and market pressure for green innovation, yet struggle to effectively mobilize employee-driven environmental initiatives. By examining both the “how” (mediation) and “when” (moderation) of leadership effectiveness in promoting environmental creativity, this study offers a comprehensive understanding that can inform both theoretical development and managerial practice in the pursuit of organizational sustainability across different sectors.

2. Theoretical Foundations and Research Hypotheses

2.1. Theoretical Foundations

Self-determination theory (SDT) asserts that there exists a continuum of autonomy from external regulation to internal integration that motivates an individual’s behavior, and that satisfying the three basic psychological needs of an individual, autonomy, competence, and belonging, is critical to promoting proactive individual behavior [18]. First, this theory provides an important perspective for understanding how environmentally-specific empowered leadership (EEL) influence employees’ green crafting (GC). EEL satisfy employees’ basic psychological needs in the environmental domain by granting them autonomy in environmental decision-making, providing environmental knowledge support and feedback, expressing trust in employees’ environmental competence, and creating a supportive environment [5,6], When these context-specific psychological needs are met, employees’ intrinsic motivation toward environmental issues increases, serving as a key precursor to creativity; Second, on SDT’s emphasis on autonomous motivation, we propose green crafting as a key mediating mechanism between EEL and employee green creativity(EGC). Green crafting theory suggests that employees proactively reshape their work boundaries, relationships, and cognitive frameworks to enhance meaning and identity [17]. Applied to environmental contexts, green crafting represents employees’ proactive modifications to integrate sustainability into their job roles. Third, SDT recognizes that situational factors influence the extent to which environmental support is transformed into internalized motivation and behavior [18]. Extending this principle, we propose that organizational environmental culture (EC) moderates the relationship between EEL and GC.

2.2. Environmentally-Specific Empowered Leadership and Green Crafting

EEL promotes employee GC in several ways. First, EEL satisfy employees’ need for autonomy by encouraging them to participate in environmental decision-making and providing autonomy to solve environmental problems [22]. Research suggests that employees are more inclined to proactively shape work boundaries when they perceive greater job autonomy [17]. For example, Thun and Bakker’s study found that empowering leaders were significantly and positively associated with employees’ GC behaviors, such as increasing structural job resources, increasing social job resources, and increasing challenging job demands [23]. Second, EEL enhances employees’ sense of environmental competence by providing training in environmental knowledge and skills, which satisfies employees’ need for a sense of competence [13]. Tang et al.’s study showed that employees are more likely to actively participate in job shaping when they perceive empowering behaviors of their leaders and when they have a sufficient sense of competence [24]. Finally, EEL emphasizes teamwork to solve environmental problems and create inclusive work environments that satisfy employees’ need for a sense of belonging [19].

GC as employees’ proactive behavior to integrate environmental elements into their work includes increasing environmental resources (e.g., seeking environmental knowledge, building environmental networks), increasing environmental challenges (e.g., setting higher environmental goals, taking on additional environmental tasks), and adjusting environmental perceptions (e.g., reevaluating the environmental significance of work) [25,26]. According to SDT, when employees’ basic psychological needs are satisfied, they develop higher autonomous motivation and consequently adopt proactive behaviors [21]. Empirical studies also support this view; for example, Lee et al.‘s meta-analysis found that empowered leaders significantly promote proactive behaviors, including GC, by satisfying employees’ basic psychological needs [8]. Therefore, we propose:

Hypothesis 1.

Environmentally-specific empowered leadership is positively related to employees’ and green crafting.

2.3. The Mediating Role of Green Crafting

In compliance with SDT, leadership behaviors typically affect work outcomes such as creativity by influencing employees’ psychological states and behaviors and thus creativity [18]. Based on the previous argument, environmentally specific empowering leaderships promote GC among employees by satisfying their basic psychological needs; in turn, GC promotes the emergence of EGC among employees by providing environmental resources, increasing environmental challenges, and adjusting environmental perceptions. Thus, GC may play a mediating role between environmentally empowered leadership and EGC.

While EEL may directly influence employee EGC, for example, by expressing expectations and providing direct support for environmental innovations [6], it is likely that this influence is partially realized through employees’ proactive behaviors. As Zhang and Bartol showed, empowering leaders influence creativity by promoting employees’ psychological empowerment and intrinsic motivation, which in turn influences creativity [6]. Similarly, in the environmental domain, Mittal and Dhar found that green transformational leadership influences EGC by stimulating employees’ environmental self-efficacy, which in turn influences EGC [27].

Specifically, EEL creates an environment conducive to employee self-directed action and enhances employees’ environmental motivation and sense of competence, but ultimately, the generation of environmental innovations relies on employees translating this motivation and competence into concrete work behaviors. GC, as a spontaneous work adjustment behavior of employees, represents the process by which employees transform leadership empowerment into actual action. Through GC, employees are able to optimize the allocation of resources according to their situations and work environments to create working conditions that are more conducive to green innovation [26]. Similar mediating mechanisms have been supported by empirical studies. For example, Lee et al. showed that environmentally specific empowering leadership influences innovation performance by promoting autonomous work behaviors among employees, which in turn affects innovation performance [7]. Besides, research in environmental sustainability contexts reveals that transformational green leadership catalyzes organizational eco-innovation through its effect on employee environmental conduct [16]. Complementary findings by Tang et al. demonstrate that employee proactivity serves as a crucial mediating mechanism linking leadership practices to innovative outcomes [24]. Therefor, we propose:

Hypothesis 2.

Employee green crafting mediates the relationship between environmentally-specific empowered leadership and employee green creativity.

2.4. The Moderating Role of Environmental Culture

Environmental culture, as an important contextual factor, has a significant impact on individual behavior and leadership effectiveness [28]. EC refers to the shared belief system among organizational members regarding environmental values, norms, and practices [29]. According to the situational intensity theory (SIT) [30], a strong organizational culture can clarify behavioral expectations, reduce behavioral uncertainty, and thereby enhance the effectiveness of specific leadership behaviors. In organizations with a strong EC, environmental behaviors are viewed as the norm and expected, making it easier for employees to understand and respond to environmentally empowered leadership behaviors [29]. Specifically, when an organization has a strong EC, EEL aligns with the organization’s overall values and behavioral expectations, thereby enhancing its legitimacy and credibility. At this point, the workforce has come to regard leadership’s environmental empowerment strategies as genuine and credible implementations, moving beyond mere symbolic or superficial demonstrations. The empirical evidence presented by Maitlo et al. suggests that corporate environments prioritizing innovation and ecological preservation amplify the effectiveness of green leadership in shaping employees’ environmental practices [21].

Additionally, a strong EC provides employees with additional environmental resources and support systems, such as environmental training and cross-departmental environmental cooperation mechanisms [29]. These resources and support systems synergize with the influence of EEL, further enhancing employees’ ability and motivation to engage in GC. As demonstrated by Zohar and Tenne-Gazit, when organizational culture aligns with leadership behavior, the influence of leadership on employee behavior is enhanced [28].

Conversely, in organizations with weak EC, environmental values are not emphasized, and environmental behaviors lack institutionalized support. In such cases, the influence of EEL may weaken, as employees may feel that environmental behaviors are inconsistent with the organization’s overall values or lack necessary organizational support [31]. For example, if an organization prioritizes short-term economic benefits over environmental values, employees may hesitate to actively respond to leadership authorization for environmental innovation out of concern that it does not align with the organization’s overall direction. Thus, we propose:

Hypothesis 3.

Environmental culture positively mediates the relationship between environmentally-specific empowered leadership and employee green crafting, meaning that when environmental culture is strong, the positive relationship between environmentally-specific empowered leadership and employee green crafting is stronger.

2.5. Integrative Model: Moderated Mediation

Based on the preceding analysis of the moderating effect of EC and the mediating effect of GC, we can further infer that EC moderates the indirect effect of EEL through GC on EGC. According to situational intensity theory [31], a strong organizational culture enhances the effectiveness of specific leadership behaviors by providing clear behavioral expectations and institutionalized support. In a strong EC context, EEL behaviors align closely with organizational values, not only enhancing their legitimacy and credibility but also securing organizational-level resource support and institutional safeguards. This consistent and supportive organizational environment makes employees more likely to translate leadership’s environmental empowerment into specific GC behaviors, which in turn promote the generation of EGC. For example, when an organization has a higher EC, employees engaging in GC not only receive support from their direct supervisors but also gain access to broader organizational resources and colleague support, all of which contribute to transforming work shaping into actual innovative outcomes [29]. Conversely, in organizations with lower ECs, even with the support of EEL, employees’ GC behaviors may struggle to effectively translate into EGC due to a lack of organizational-level recognition and support. This aligns with the findings of Zohar and Tenne-Gazit [28], who noted that consistency between organizational culture and leadership behavior enhances the effectiveness of leadership influence processes. Therefore, we expect that EC will enhance the indirect effect of EEL influencing EGC through GC. Based on this, we propose:

Hypothesis 4.

Environmental culture positively moderates the indirect effect of environmentally-specific empowered leadership influencing employee green creativity through green crafting, meaning that when environmental culture is strong, the indirect effect of environmentally-specific empowered leadership influencing employee green creativity through green crafting is stronger.

The theoretical model diagram is shown in Figure 1.

3. Methods

3.1. Sample and Procedure

Data collection was facilitated through Credamo, a comprehensive online crowdsourcing platform that enables participant screening based on demographic characteristics and response quality metrics to maintain data integrity [31]. Given the challenge of determining the exact population parameters [32], we employed statistical power analysis methodology to establish an appropriate sample size. Utilizing G*Power 3.0, we calculated the requisite sample dimensions to achieve the intended effect magnitude [33]. In accordance with established research protocols, while power and alpha levels were preset, the anticipated effect size required estimation [34]. The analysis parameters (effect size = 0.035, α = 0.05, power = 0.95, predictors = 5) yielded a necessary sample size of 445 participants.

To address concerns regarding common method bias, data collection was structured across multiple temporal points, with the entire survey process scheduled for completion within a month-long timeframe. Each valid questionnaire was compensated with 9 RMB. All data were exclusively used for academic research and not for any other purposes. Prior to formally completing the survey questionnaire, we emphasized to participants that we would ensure the anonymity of respondents and the confidentiality of the data. The questionnaire was administered online, and each participant was assigned a unique identifier. Only those who completed the first-wave questionnaire were eligible to participate in the second-wave survey, ensuring valid matching of the two datasets. For this purpose, we distributed 450 questionnaires to Credamo.

At Time Point 1, we primarily collected employees’ basic personal information and measurement items related to EEL and EC; At Time Point 2 (approximately two weeks later), we invited employees who participated in the first phase of the survey to participate again, primarily collecting measurement items related to GC; At Time Point 3, we resubmitted the questionnaire to employees who had completed the second phase, primarily collecting measurement items related to employee creativity. During the three rounds of questionnaire surveys, due to unforeseeable circumstances such as employee resignations, some employees were unable to fully participate in the second and third rounds of the questionnaire survey, resulting in a small number of missing questionnaires. Specifically, 410 data sets were collected in the first round, 330 in the second round, and 286 in the third round. After matching the three rounds of questionnaires on the Credamo platform, a total of 286 data points were recovered. After removing invalid questionnaires with missing answers or consistent responses [35], 229 valid questionnaires were obtained, resulting in a valid response rate of 80.07%. While our final sample size (229) is lower than the initially calculated size using G*Power (445), it is important to note that our sample size remains methodologically adequate based on established sample size guidelines in structural equation modeling and multivariate analysis. Specifically, according to the widely accepted heuristic proposed by Hair et al. and Kline, a sample size of 5–10 respondents per measured item is considered sufficient for reliable statistical analysis [34,35]. Our research instrument contained a total of 29 measurement items across all constructs, requiring a minimum sample size between 145 (5 times the number of items) and 290 (10 times the number of items). Our final sample of 229 falls well within this recommended range, suggesting adequate statistical power for our analytical approach.

Regarding industry distribution, 23.6% of employees were in the manufacturing sector, which represents the largest single industry category in our sample. The remaining participants came from various industries including: information technology (18.3%), service sector (15.7%), construction (10.5%), retail (9.2%), healthcare (8.7%), finance (7.4%), and others (6.6%).

3.2. Measures

The measurement instruments employed 5-point Likert-type response formats ranging from 1 (strongly disagree) to 5 (strongly agree). Following Brislin’s (1980) protocol, all measurement scales underwent systematic translation and back-translation processes to establish linguistic equivalence, with preliminary assessments conducted to confirm their cultural appropriateness within the Chinese context. All measurement items can be found in Appendix A.

EEL. The Scale developed by Badar et al. was adapted to an environmental context, resulting in a 13-item scale [36]. Sample items include “My supervisor encourages me to participate in important decisions related to the environment.” (Cronbach’s α = 0.85)

EC. The scale developed by Fraj et al. was used, comprising 6 items [37]. Examples include: “Our company strives to ensure that every employee understands the importance of environmental protection.” (Cronbach’s α = 0.76)

GC. The scale developed by Tims et al., modified to incorporate environmental contexts, the final scale includes 19 items [26]. Sample items include: “I actively seek out work resources related to environmental protection.” (Cronbach’s α = 0.82)

EGC. The Scale developed by Chen et al. was adopted, comprising 6 items [2]. Sample items include: “I strive to develop my environmental capabilities,” “I strive to develop my environmental knowledge and skills.” (Cronbach’s α = 0.70)

Control variables: Previous research suggests that several demographic characteristics may significantly influence both green crafting behaviors and environmental creativity, which could potentially confound our hypothesized relationships if not controlled for. First, gender has been found to relate to environmental attitudes and behaviors, with women often demonstrating stronger pro-environmental orientations than men [38,39]. Second, age can impact environmental innovation, as younger employees may have different environmental values and openness to new practices compared to older generations [40]. Third, educational level typically correlates with environmental awareness and creative problem-solving capabilities [41], potentially affecting employees’ ability to engage in both green crafting and green creativity. Fourth, working hours may influence employees’ capacity and energy available for discretionary environmental behaviors beyond core job tasks. Finally, industry type can determine the environmental context and opportunities for environmental initiatives available to employees [42]. By including these variables as controls, we can better isolate the specific effects of our theoretical variables of interest while accounting for these well-established demographic influences on environmental behaviors and creativity.

3.3. Data Analysis Strategies

In this study, SPSS 26.0 and AMOS 24.0 were used for data analysis. Firstly, exploratory factor analysis (EFA) was conducted through SPSS, and Cronbach’s α coefficient was calculated to test the reliability. Confirmatory factor analysis (CFA) was conducted using AMOS to calculate composite reliability (CR) and average variance extract (AVE) to test validity. Secondly, to assess the common method bias issue, Harman’s single-factor test and latent variable control method were simultaneously employed for detection. By calculating descriptive statistical indicators and conducting Pearson correlation coefficient analysis, the relationship patterns among variables were preliminarily examined. When verifying the research hypothesis, the hierarchical regression analysis method was used to test the direct effects between variables. A structural equation model was established with the aid of AMOS 24.0 to systematically test the mediation mechanism. The influence effect of moderating variables was investigated by using sample grouping comparison and simple slope analysis techniques. To enhance the robustness of the research conclusion, the influence of demographic variables was controlled during the analysis process, and the stability of the results was verified through comparative analysis of different sub-samples. All statistical tests were conducted using two-sided test criteria, and the significance threshold was set at p < 0.05.

4. Results

4.1. Common Method Bias

While our research design incorporated time-lagged data collection to minimize common method effects, we implemented statistical procedures to quantify potential measurement bias. The results of Harman’s single-factor assessment demonstrated that the leading factor explained 25.127% of variance, considerably below the 40% threshold, thus suggesting minimal impact of common method bias.

Besides, following Podsakoff et al.’s protocol, we conducted additional analyses to assess common method effects [43]. We established two comparative models using AMOS 24.0: an initial four-factor structure and a subsequent model integrating a common method factor. The comparative fit indices demonstrated marginal differences (ΔCFI = 0.012, ΔTLI = 0.019, ΔRMSEA = 0.005, ΔSRMR = 0.001), with all variations falling within the acceptable range of 0.03. This stability in model fit indicators substantiated the absence of significant common method bias [44].

4.2. Confirmatory Factor Analysis

We measured convergent validity based on a four-factor model, including the composite reliability between them, calculated based on standardized factor loadings and the AVE values. The results showed that the factor loadings of all items for each variable were above 0.7, and the factor loadings met the standards. The average extracted variance values and composite reliability for EEL, EC, GC, and EGC had AVE values and composite reliability coefficients of 0.45, 0.40, 0.45, 0.40, and 0.86, 0.80, 0.75, and 0.79, respectively.

While some AVE values fell below the conventional threshold of 0.5, several methodological considerations support the validity of our measurement model. First, as noted by Hair et al., AVE values slightly below 0.5 can be acceptable when composite reliability is above 0.7, which is the case for all our constructs (ranging from 0.75 to 0.86) [35]. Second, Fornell and Larcker argue that if AVE is less than 0.5 but composite reliability is higher than 0.6, the convergent validity of the construct is still adequate [45]. Third, recent methodological research by Voorhees et al. and Henseler et al. suggests that when factor loadings are significant and above 0.5 (in our case, all above 0.7), construct validity can be established even with lower AVE values [46,47].

Before proceeding with the next step of hypothesis testing, the research team also assessed the validity of the measurement model by comparing several nested models: (1) a four-factor model (environmental empowerment leadership, EC, green job shaping, and EGC as independent factors); (2) Three-factor model a (merging green job shaping and EGC into a single factor); (3) Three-factor model b (merging environmentally empowering leadership and EC into a single factor); (4) Two-factor model (merging predictor variables and outcome variables separately); (5) Single-factor model (all items loaded onto a single factor). As shown in

Table 1. Confirmatory factor analysis.

Model	χ2	df	χ2/df	CFI	TLI	RMSEA	SRMR
Four-factor model (EEL, EC, EGC, EEGC)	466.514	364	1.282	0.946	0.940	0.035	0.049
Three-factor model a (EEL, EC, EGC + EEGC)	552.406	374	1.477	0.906	0.898	0.046	0.054
Three-factor model b (EEL + EC, EGC, EEGC)	594.068	374	1.588	0.884	0.874	0.051	0.056
Two-factor model (EEL + EC + EGC, EEGC)	662.593	376	1.762	0.849	0.837	0.058	0.060
Single-factor model (EEL + EC + EGC + EEGC)	681.618	377	1.808	0.840	0.827	0.060	0.061

Notes: N = 229; + = Combination of factors; EEL = Environmentally-specific empowered leadership, EC = Environmental culture, GC = Green crafting, EGC = Employee green creativity.

, the four-factor model provided the best fit (χ²/df = 1.282, CFI = 0.946, TLI = 0.940, RMSEA = 0.035, SRMR = 0.049), supporting the discriminant validity of the measurement model.

4.3. Descriptive Statistics and Correlation Analysis

Descriptive statistics and correlation analysis are shown in

Table 2. Mean, standard deviation, and correlation of the main research variables.

Measure	Mean	SD	1	2	3	4	5	6	7	8
1. Gender	1.62	0.24
2.Age	2.04	0.81	−0.087
3.Education	2.91	0.45	−0.183 **	−0.183 **
4.Tenure	2.02	1.38	−0.101	0.858 *	−0.209 **
5. Enterprise Status	5.08	11.89	0.146 *	−0.182 **	−0.039	−0.163 *
6. EEL	4.08	0.18	0.062	0.117	0.165 *	0.071	−0.221 **
7.EGC	4.10	0.26	0.007	0.091	0.103	0.039	−0.278 **	0.654 **
8.GJC	4.05	0.15	0.033	0.086	0.069	0.052	−0.237 **	0.677 **	0.546 **
9.EEGC	4.14	0.17	0.044	0.029	0.049	−0.020	−0.196 **	0.587 **	0.491 **	0.697 **

Notes: N = 229; * p < 0.05, ** p < 0.01, EEL = Environmentally-specific empowered leadership, EC = Environmental culture, GC = Green crafting, EGC = Employee green creativity.

. The results indicate that EEL is significantly positively correlated with GC (r = 0.677, p < 0.01) and EGC (r = 0.587, p < 0.01), preliminarily supporting Hypothesis 1. GC is also significantly positively correlated with EGC (r = 0.697, p < 0.01), preliminarily supporting Hypothesis 2. Additionally, EEL was significantly positively correlated with EC (r = 0.654, p < 0.01), GC (r = 0.546, p < 0.01), and EGC (r = 0.587, p < 0.01), providing preliminary support for Hypothesis 4.

4.4. Hypothesis Testing

Table 3. Regression Analysis.

Variables	GJC				EEGC
	M1	M2	M3	M4	M5	M6
Gender	0.065	0.009	0.010	−0.001	0.067	0.022
Age	0.122	0.002	−0.008	−0.016	0.140	0.056
Education	0.062	−0.049	−0.047	−0.039	0.027	−0.016
Tenure	−0.071	−0.022	−0.009	−0.033	−0.161	−0.112
Enterprise Status	0.234	−0.097	−0.072	−0.059	−0.206	−0.045
EEL		0.644 ***	0.563 ***	0.606 ***		0.687 ***
EGC			0.163 **	0.205 **
EEL × EGC				0.182 **
GJC
R2	0.069	0.468	0.483	0.510	0.052	0.491
ΔR2	0.048	0.454	0.467	0.492	0.031	0.478

Notes: N = 229; ** p < 0.01, *** p < 0.001; EEL = Environmentally-specific empowered leadership, EC = Environmental culture, GC = Green crafting, EGC = Employee green creativity.

shows the results of hierarchical regression analysis. Hypothesis 1 proposes that EEL has a positive predictive effect on GC. In Model 2, EEL has a significant positive effect on GC (β = 0.644, p < 0.001), supporting Hypothesis 1.

Hypothesis 2 posits that GC mediates the relationship between EEL and EGC. According to the results of Model 7 in Table 3, when the variable of GC is included, the positive effect of EEL on EGC decreases from 0.687 (p < 0.001) to 0.222 (p < 0.01). At the same time, the effect of GC on EGC remains significant (β = 0.544, p < 0.001). The research team used Baron and Kenny’s method to conclude that GC partially mediates the relationship between EEL and EGC [48], thereby preliminarily validating Hypothesis 2. To further test the mediating effect of GC, we conducted a bootstrap analysis (repeated sampling 5000 times) using the PROCESS macro (Model 4). The results showed that the indirect effect of EEL on EGC through GC was significant (Effect = 0.381; SE = 0.077; 95% CI = [0.248, 0.553]), while the direct effect of EEL on EGC remained significant (Effect = 0.216, SE = 0.063, 95% CI = [0.091, 0.340]), supporting Hypothesis 2.

Hypothesis 3 examines the moderating influence of EC on the EEL-GC relationship. Prior to hypothesis testing, all variables underwent standardization to mitigate potential multicollinearity effects. Model 2 (Table 3) demonstrated a significant positive association between EEL and GC (β = 0.644, p < 0.001). Following EC’s introduction in Model 3, the positive relationship persisted (β = 0.563, p < 0.001). Subsequently, Model 4’s analysis incorporating the EEL-EC interaction term yielded a significant standardized coefficient (β = 0.182, p < 0.05), substantiating the hypothesized moderating effect.

Additionally, the research team used the PROCESS macro (Model 7) for analysis. Simple slope analysis (see Figure 2) showed that when EC was high (+1 SD), the positive relationship between EEL and GC was stronger (simple slope = 0.655, t = 9.215, p < 0.001); when EC was low (−1 SD), this relationship was weaker but still significant (simple slope = 0.446, t = 7.351, p < 0.001). The difference between these two slopes (Δslope = 0.209) was statistically significant, indicating that the influence of EEL on GC is 46.9% stronger for employees with high environmental consciousness compared to those with low environmental consciousness. This significant moderation effect demonstrates that employees’ internal environmental values substantially enhance their responsiveness to environmentally-specific leadership behaviors. These results strongly support Hypothesis 3.

Hypothesis 4 posits that EC functions as a positive mediator in the EEL-EGC relationship through GC. Analysis of the conditional indirect effects revealed distinct patterns at varying EC levels (

Table 4. Moderated mediation analysis.

Grouping Statistics	Effect	SE	LLCI	ULCI
High EGC (+1SD)	0.654	0.071	0.514	0.793
Low EGC (−1SD)	0.446	0.061	0.324	0.565
Intergroup differences	0.119	0.048	0.037	0.229

). Under conditions of high EC (M + 1SD), the indirect influence of EEL on employee EGC via GC demonstrated significant positive effects (indirect effect = 0.654, SE = 0.071, 95% CI = [0.514, 0.794]). Conversely, at low EC levels (M − 1SD), the mediated pathway remained significant but with reduced magnitude (indirect effect = 0.446, SE = 0.061, 95% CI = [0.324, 0.565]). The differential magnitude between high and low EC conditions (difference = 0.119) yielded a confidence interval excluding zero [0.037, 0.229], substantiating the statistical significance of this mediating effect. These empirical findings provide support for Hypothesis 4.

5. Discussion

Our findings revealed a strong positive relationship between EEL and GC (β = 0.644, p < 0.001), which represents a relatively large effect size. The comparatively stronger effect size observed in our study may be attributed to several contextual factors specific to the Chinese manufacturing industry. First, the hierarchical nature of Chinese organizations, characterized by relatively high power distance, may amplify the impact of leadership behaviors that explicitly grant autonomy and decision-making authority. When leaders in high power distance contexts deliberately empower employees—particularly for environmental initiatives that might otherwise be seen as management’s responsibility—this may produce a stronger effect than in contexts where employee participation is more normative. Second, the manufacturing sector in China has faced intense regulatory and market pressure for environmental compliance in recent years [49], creating a context where environmentally-specific leadership behaviors may carry heightened significance compared to general empowering behaviors studied in previous research.

Research findings indicate that green crafting partially mediates the relationship between EEL and EGC. This partial mediation effect (rather than full mediation) indicates that in the Chinese context, leadership influence retains a direct pathway. This aligns with China’s “relationship” and “face” culture, where even in an enabling environment, leaders’ direct influence and exemplary role remain crucial. This suggests that Chinese organizations promoting environmental innovation must balance empowerment with guidance—granting employees autonomy while maintaining clear leadership direction.

Research findings indicate that environmental culture positively mediates the relationship between EEL and GC. This moderating effect highlights the critical role of organizational environmental culture development in China. In China, organizational culture is often profoundly influenced by “collectivism” and “harmony” values. Research indicates that when organizations cultivate a strong environmental culture, the impact of environmentally empowering leadership on employees’ green crafting increases by 46.9%. This reflects the potent force of the “atmosphere isomorphism effect” in Chinese organizations—where individual behavior tends to align with perceived organizational norms. This resonates with traditional Chinese concepts of “leading by example” and “setting the tone from the top”.

6. Theoretical Contributions

First, this study expands the scope of sustainable leadership research by integrating EEL theory with environmental contexts. While previous studies have explored the relationship between leadership styles such as transformational leadership [2,8] and exploitative leadership [10] and environmental behavior, research on the role of empowerment leadership in promoting green innovation remains limited. Our findings indicate that EEL effectively promotes employees’ GC and EGC by granting employees autonomy in environmental decision-making, providing environmental knowledge support, and expressing trust in employees’ environmental capabilities. This finding enriches sustainable leadership theory and emphasizes the unique value of empowerment behaviors in green management [6,7].

Second, this study introduces GC as a key mediating mechanism, revealing the central role of employee proactivity in the green innovation process. Traditional research has primarily focused on psychological mechanisms such as intrinsic motivation [3] and environmental self-efficacy [13], while neglecting the importance of employee proactive behavior. Our findings indicate that employees are not merely passive recipients of leadership influence but active shapers of their work environment. Through GC. Employees integrate environmental elements into their work tasks, relationships, and cognition, thereby creating conditions more conducive to green innovation. This finding not only enriches the application of GC theory in the environmental field [17,26] but also provides a new perspective on understanding the formation of employees’ environmental behaviors.

Third, this study validated the moderating role of EC, emphasizing the importance of situational factors in promoting green behavior. The results indicate that a strong EC not only directly promotes employees’ GC but also enhances the effectiveness of EEL. This finding aligns with situational intensity theory [31] and previous research [29], indicating that consistency between organizational culture and leadership behavior has a synergistic effect on promoting employee behavior. By incorporating leadership behavior and organizational culture into the same model, this study provides a more comprehensive framework for understanding how multi-level factors collectively influence employee green behavior.

Fourth, this study extends the application of SDT to the environmental field. According to SDT, meeting employees’ needs for autonomy, competence, and relatedness is key to fostering intrinsic motivation and proactive behavior [18]. Our research indicates that EEL promotes employee GC and EGC by fulfilling employees’ basic psychological needs in the environmental field. This finding supports the core tenets of SDT while enriching its application in the context of sustainable development [19,21].

7. Practical Significance

First, organizations should prioritize the cultivation and development of EEL through structured approaches. Specifically, organizations can implement a three-module leadership training program: (1) an “Environmental Decision Empowerment” module that trains leaders to delegate environmental decision-making authority through techniques like environmental impact assessment mentoring and green solution workshops; (2) an “Environmental Knowledge Building” module focusing on industry-specific environmental regulations, green technologies, and carbon footprint analysis methods; and (3) a “Supportive Environmental Coaching” module developing skills for constructive feedback on environmental initiatives and psychological safety creation. Companies like Unilever have successfully implemented such programs by combining classroom sessions with three-month action learning projects where leaders apply these skills to actual environmental challenges in their departments. Additionally, organizations should incorporate environmentally empowered capabilities as a key evaluation criterion in leadership selection and promotion processes, using specific behavioral indicators such as “provides team members autonomy in implementing energy-saving solutions” and “effectively communicates environmental goals and strategies” in 360-degree leadership assessments.

Second, organizations should encourage and support employees’ GC through comprehensive systems. Specific measures may include: (1) establishing a tiered GC reward mechanism with three levels: individual recognition through monthly “Green Innovator” awards (50–100 USD or equivalent); team-based rewards where departments meeting quarterly environmental goals receive budget increases for sustainability projects (1–3% of department budget); and organization-wide profit-sharing linked to annual environmental performance metrics (0.5–2% of salary); (2) creating a digital knowledge-sharing platform with features such as a searchable database of employee-generated green innovations, discussion forums organized by department and function, monthly virtual roundtables with environmental experts, and a gamified point system where employees earn recognition for sharing and implementing green ideas.

Third, organizations should focus on building a strong EC to provide a supportive environment for EEL and employee green creativity. Specific strategies include: (1) embedding environmental values in organizational identity through formal environmental mission statements, department-level environmental charters, and visual environmental progress dashboards in common areas; (2) implementing a “Leadership Green Visibility” program where executives regularly participate in and document environmental initiatives (e.g., Patagonia’s requirement that executives spend two weeks annually working directly on environmental conservation projects); (3) establishing multi-level recognition systems including monthly environmental improvement stories in company communications, an annual “Environmental Impact Awards” ceremony with significant visibility, and considering environmental contributions in promotion decisions with specific weighting criteria (10–15% of evaluation scores); (4) allocating tangible resources such as a dedicated “Green Creativity Fund” (0.5–2% of annual budget) for employee-initiated environmental projects, technical environmental support teams available for consultation, and partnerships with external environmental organizations and experts to provide specialized knowledge.

8. Limitations and Future Research Directions

The use of a multi-time point data collection design, all variables were derived from employee self-reports, which may introduce common method bias. Future research could consider using multi-source data, such as combining leadership evaluations, peer evaluations, or objective performance metrics, to enhance the robustness of research conclusions. Specifically, for the measurement of EGC, leadership evaluations or team evaluations could be considered to obtain more objective assessments of creativity performance. Additionally, a notable limitation of our study is the absence of organizational-level control variables. Factors such as firm size, organizational structure, environmental management systems, and the intensity of environmental policies could potentially influence the relationships in our model. Specifically, we recommend that future studies employ multi-level modeling approaches that can simultaneously account for individual and organizational factors influencing employee green creativity.

Second, to the longitudinal nature of our study, participant attrition was inevitable. After removing invalid questionnaires with missing answers or inconsistent responses, we obtained 229 valid questionnaires, representing a response rate of 50.9% of the initial distribution. Primary reasons for this attrition included employee turnover and other unforeseen circumstances that prevented participants from completing all three survey rounds. While the 229 data points are reasonable, we recommend that future research replicate our findings with larger samples to enhance the robustness of the results.

Third, future research should explore how cultural differences influence the EEL-EGC relationship. In particular, the effectiveness of empowering leadership may vary significantly across cultural contexts characterized by different levels of individualism versus collectivism and power distance. For example, in collectivistic cultures like China, environmentally empowering leadership might function through different psychological mechanisms than in individualistic Western cultures, potentially emphasizing group-level environmental responsibility rather than individual autonomy. Similarly, in high power distance cultures, the delegation aspect of empowering leadership might face unique challenges or require specific adaptations to be effective. Cross-cultural comparative studies could identify culture-specific moderators that enhance or diminish EEL effectiveness, contributing to a more culturally nuanced theory of environmental leadership.

Fourth, an exciting direction for future research would be to conceptualize and empirically investigate team-level green crafting (TGC) and team environmental green creativity (TEGC) as emergent properties. While our study focused on individual-level processes, environmental challenges often require collective solutions through team coordination and collaboration. Future research could explore how individual GC behaviors aggregate and interact to form collective TGC, and how these team-level processes contribute to TEGC beyond the sum of individual contributions. Researchers could investigate the emergence processes (compilation versus composition), the role of team climate and team mental models in shaping collective environmental behaviors, and cross-level influences between individual and team environmental initiatives. This multi-level perspective would significantly advance our understanding of how environmental leadership influences outcomes across organizational levels.

Fifth, future research should investigate additional boundary conditions of EEL’s impact beyond environmental consciousness. Potential moderators worth exploring include: (1) organizational factors such as resource availability, competing priorities, and formalization degree; (2) job characteristics such as task interdependence and job autonomy; (3) leadership factors such as consistency between leaders’ environmental words and actions; and (4) external factors such as institutional pressures and stakeholder expectations. Understanding these boundary conditions would help specify when and under what circumstances EEL is most effective, allowing for more targeted implementation of environmental leadership practices.

9. Conclusions

This study reveals the underlying mechanisms and boundary conditions through which EEL promotes EGC. Based on multi-time point data from 229 employees, we find that EEL enhances EGC by stimulating employees’ GC, and that EC enhances the effectiveness of EEL. This study makes three theoretical contributions: first, it introduces empowerment theory into the environmental field, expanding our understanding of how leadership can promote employee environmental behavior; second, it reveals the mediating role of GC in the leadership creativity relationship, emphasizing the importance of bottom-up processes; and third, it clarifies how multi-level factors (leadership behavior and EC) synergistically influence employee green innovation. These findings offer practical insights for organizations seeking to balance environmental responsibility with innovation performance, suggesting that combining empowerment and cultural support can help build an organizational ecosystem that fosters green innovation. In today’s increasingly challenging environmental landscape, such integrated research holds significant implications for advancing sustainable practices within organizations.