Entrepreneurial Leadership and Green Innovation–Model

1. Abstract

The Entrepreneurial Leadership and Green Innovation—Model, formulated and psychometrically validated by Ali, Jiang, Ali, and Qadeer (2023), is an advanced structural and psychometric assessment instrument grounded in upper echelons theory. Designed to capture the strategic mechanisms driving corporate ecological sustainability, the instrument evaluates a comprehensive moderated mediation framework wherein entrepreneurial leadership influences organizational green innovation (GI) through the developmental conduit of organizational learning culture, while simultaneously accounting for the moderating contingency of environmental dynamism. The complete measurement inventory comprises 30 operationalized items administered via structured professional interviews and evaluated on a seven-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”).

Empirical validation of the measurement model was conducted among executive leadership and senior managers of manufacturing and commercial enterprises in China. Psychometric evaluations confirm exceptional construct validity and internal consistency reliability. Confirmatory factor analysis (CFA) affirmed the integrity of a four-factor structure comprising entrepreneurial leadership, organizational learning culture, environmental dynamism, and green innovation. Model fit indices demonstrated robust structural alignment: χ²/df = 2.63 (p < .001), Comparative Fit Index (CFI) = 0.95, Goodness-of-Fit Index (GFI) = 0.92, Normed Fit Index (NFI) = 0.94, Root Mean Square Residual (RMR) = 0.03, and Root Mean Square Error of Approximation (RMSEA) = 0.04. Convergent validity was established across all latent constructs with Average Variance Extracted (AVE) values comfortably exceeding the standard 0.50 benchmark, alongside composite reliabilities (CR) surpassing 0.70. Cronbach’s alpha coefficients ranged from .729 to .871, confirming strong internal consistency. Common method variance was statistically evaluated using Harman’s single-factor test, where the primary factor accounted for only 31.612% of the variance (total explained variance: 74.486%), confirming the absence of substantial common method bias. The instrument stands as a psychometrically sound, cross-culturally validated diagnostic tool for research in strategic management, corporate environmental performance, and organizational behavior.

2. Keywords

Entrepreneurial Leadership, Green Innovation, Organizational Learning Culture, Environmental Dynamism, Upper Echelons Theory, Psychometrics, Convergent Validity, Sustainable Strategic Management, Ecological Innovation, Structural Equation Modeling

3. Authors

• Adnan Ali — School of Management, Xi’an Jiaotong University, Xi’an, Shaanxi, China. ORCID: 0000-0001-8836-8851.
• Xu Jiang (Corresponding Author) — School of Management, Xi’an Jiaotong University, No. 28, Xianning West Road, Xi’an, Shaanxi, 710049, China. Email: [email protected]. ORCID: 0000-0002-1388-3469.
• Afzaal Ali — School of Management, International Islamic University Islamabad, Islamabad, Pakistan. ORCID: 0000-0002-7323-6781.
• Abdul Qadeer — School of Management, Xi’an Jiaotong University, Xi’an, Shaanxi, China. ORCID: 0000-0002-0786-2223.

4. Purpose

The fundamental purpose of the Entrepreneurial Leadership and Green Innovation—Model measurement instrument is to systematically measure, diagnose, and model the psychological, cultural, and environmental pathways through which top-tier executive leadership mobilizes enterprise-wide ecological sustainability. Rapid global environmental degradation, intensifying climate change mandates, stringent carbon neutrality targets, and increasing stakeholder pressure have elevated corporate sustainability from a peripheral corporate social responsibility (CSR) obligation into an existential strategic imperative. However, transitioning legacy business operations toward sustainable green practices requires radical departures from entrenched administrative routines. The operationalization of this measurement model addresses a critical theoretical and empirical gap: elucidating precisely how executive entrepreneurial attributes translate into technological and operational environmental innovations.

From an applied organizational perspective, this measurement tool provides corporate boards, senior executives, industrial psychologists, and management consultants with a standardized metric to evaluate leadership efficacy in navigating green transitions. Standard leadership frameworks (e.g., transactional, transformational, or authentic leadership) often fail to capture the concurrent demands of opportunity exploitation, risk tolerance, and rapid organizational capability re-orchestration necessary for environmental transformation. By isolating entrepreneurial leadership within an ecological framework, the model assesses an executive’s capacity to envision green market niches, mobilize collective commitment toward ecological problem-solving, and foster a risk-tolerant climate conducive to novel green technologies.

In academic and behavioral research, the model enables rigorous testing of moderated mediation frameworks. The instrument specifically measures not only direct leadership inputs and innovation outcomes, but also the cognitive and systemic organizational infrastructure through which leadership influences operational staff—namely, the organizational learning culture. Furthermore, it measures the external boundary conditions defined by environmental dynamism (i.e., technological volatility, market unpredictability, and regulatory fluctuations). By providing a statistically validated 30-item architecture, the tool allows researchers to dissect whether leadership behaviors directly ignite green innovation or whether their primary function is to cultivate an absorptive, generative learning environment that autonomously generates green outcomes, especially when buffeted by rapid market flux.

5. Psychological Construct

The instrument operationalizes a multidimensional structural system composed of four interconnected psychological, cultural, and strategic constructs. Each latent dimension represents a distinct conceptual domain within contemporary organizational psychology and strategic management:

1. Entrepreneurial Leadership (EL)

Entrepreneurial Leadership represents an executive behavioral style that blends the visionary, opportunity-seeking orientations of entrepreneurship with the inspiring, capability-building capacities of strategic leadership. Grounded in the conceptualization established by Gupta, MacMillan, and Surie (2004), entrepreneurial leadership within this model encompasses two core psychological scenarios: scenario enactment (the cognitive framing and articulation of ambiguous environmental challenges into actionable, high-potential green opportunities) and cast enactment (the mobilization, psychological empowerment, and resourcing of organizational followers to execute innovative initiatives). Rather than relying on rigid command-and-control hierarchies, entrepreneurial leaders exhibit high risk tolerance, proactiveness, psychological safety cultivation, and cognitive flexibility, actively encouraging personnel to challenge legacy industrial paradigms in pursuit of sustainable technological breakthroughs.

2. Green Innovation (GI)

Green Innovation is operationalized as the hardware, software, process, and administrative innovations that firms implement to mitigate ecological harm, minimize resource depletion, reduce carbon emissions, and satisfy institutional environmental benchmarks while enhancing commercial competitiveness. Consistent with the foundational work of Chen, Lai, and Wen (2006), the construct encompasses two foundational facets:

• Green Product Innovation: The conceptualization, design, manufacture, and commercialization of end-products characterized by non-toxic materials, energy efficiency, recyclability, biodegradability, and minimal environmental impact across their entire life cycle.
• Green Process Innovation: The fundamental redesign and optimization of existing internal manufacturing, operational, and supply chain processes to eliminate toxic emissions, reduce water and energy consumption, recycle industrial byproducts, and achieve operational eco-efficiency.

3. Organizational Learning Culture (OLC)

Organizational Learning Culture captures an enterprise-wide shared values system, normative framework, and behavioral pattern that promotes continuous inquiry, knowledge creation, information acquisition, reflective dialogue, and generative adaptation. Drawing from Peter Senge’s learning organization paradigms and the psychometric operationalizations of Marsick and Watkins (2003), this construct reflects the firm’s internal capacity to unlearn obsolete, environmentally destructive operational habits and absorb cutting-edge environmental sciences. In this model, OLC serves as the psychological and systemic bridge (mediator) through which an entrepreneurial leader’s ecological vision permeates departmental silos, converting individual employee insights into institutionalized collective competencies.

4. Environmental Dynamism (ED)

Environmental Dynamism represents an external contingency construct reflecting the rate of change, instability, technological disruption, and unpredictability characterizing the firm’s external industry environment (Dess & Beard, 1984; Jansen et al., 2006). In contexts defined by high environmental dynamism, customer green preferences fluctuate rapidly, governmental ecological policies undergo sudden overhauls, and technological standards evolve unpredictably. The construct serves as a contextual moderator, measuring the degree to which external industry turbulence amplifies or attenuates the strategic potency of organizational learning culture in producing green innovations.

6. Theoretical Framework

The theoretical framework underpinning the instrument is anchored primarily in Upper Echelons Theory, originally formulated by Donald C. Hambrick and Phyllis A. Mason (1984) and subsequently refined by Hambrick (2007). Upper echelons theory posits that organizational outcomes, strategic choices, and competitive postures are direct reflections of the cognitive bases, psychological values, personality dispositions, and strategic orientations of the firm’s top executives. Complex strategic environments cannot be perceived with objective completeness; instead, top managers construct personalized, boundedly rational interpretations of their operational realities based on their psychological attributes and experiential filters.

Within this measurement model, the central premise asserts that the strategic pursuit of green innovation cannot be viewed merely as an automatic response to external regulatory mandates. Instead, ecological transformation is a high-level strategic decision dictated by the presence of entrepreneurial leaders at the corporate helm. Leaders possessing an entrepreneurial mindset filter environmental regulatory pressures not as punitive operational burdens, but as ripe commercial frontiers for innovative value creation. Consequently, their idiosyncratic strategic choices guide the allocation of capital, technical assets, and human talent toward sustainable R&D activities.

To provide a comprehensive explanation of how leadership psychology manifests as concrete operational innovations, the model integrates Organizational Learning Theory (Argyris & Schön, 1978; Senge, 1990) and the Natural-Resource-Based View (NRBV) of the firm (Hart, 1995). The NRBV asserts that competitive advantage in modern industry is inextricably tied to capabilities that facilitate environmentally sustainable operations, specifically pollution prevention, product stewardship, and sustainable development. However, such strategic capabilities cannot emerge in a cultural vacuum. Entrepreneurial leaders stimulate this transformation by instilling an organizational learning culture. Under the behavioral influence of the upper echelons, a pervasive learning climate fosters psychological safety, empowers generative dialogue, and dismantles cognitive rigidities, allowing cross-functional teams to experiment with green engineering methodologies without fear of conventional innovation failures.

Finally, the framework incorporates Contingency Theory (Lawrence & Lorsch, 1967) to establish the moderating role of environmental dynamism. Contingency theory postulates that the effectiveness of internal organizational processes (such as a learning culture) depends on their fit with external environmental turbulence. When environmental dynamism is pronounced, customer demands for clean products shift abruptly, competitor maneuvers accelerate, and environmental compliance thresholds tighten. Under these intense conditions, the capability to learn rapidly, reconfigure operational assets, and deploy green innovations becomes paramount, amplifying the positive indirect relationship between executive entrepreneurial leadership and enterprise green innovation.

7. Validity

The empirical validation of the instrument followed rigorous psychometric standards, establishing content, cross-cultural, convergent, and discriminant validity across multiple stages of empirical investigation.

Content and Cross-Cultural Translation Validity

To guarantee that the measurement tool retained absolute semantic, conceptual, and linguistic equivalence across cultural contexts, the authors implemented a systematic back-translation technique conforming to the cross-cultural methodological protocol established by Berry (1980). Items adapted from validated baseline literature in English were translated into Simplified Chinese by bilingual management scholars, followed by an independent blind back-translation into English executed by language specialists unfamiliar with the research objectives. Any conceptual discrepancies were systematically resolved.

Following linguistic adaptation, content validity was rigorously audited via a pre-test pilot study involving Chief Executive Officers (CEOs) and senior plant directors from Chinese manufacturing firms. These industry leaders critically reviewed the instrument for item lucidity, syntactic naturalness, domain coverage, and contextual appropriateness within the Chinese commercial ecosystem. Qualitative feedback resulted in subtle semantic refinements, confirming high face and content validity before full field administration.

Convergent Validity

Convergent validity evaluates the extent to which independent measurement items of a specific construct share a high proportion of common variance. In accordance with the statistical thresholds established by Hair et al. (2010), convergent validity requires standardized item factor loadings to be statistically significant and ideally ≥ 0.70, Average Variance Extracted (AVE) values to surpass 0.50, and Composite Reliability (CR) metrics to exceed 0.70. Across all four latent constructs within the model:

• Standardized factor loadings for each item loaded cleanly and significantly onto their designated constructs (all p < .001).
• The calculated Average Variance Extracted (AVE) for all dimensions comfortably surpassed the 0.50 threshold, demonstrating that each latent construct accounted for more than half of the variance observed across its operational indicators.
• Composite Reliabilities for all constructs exceeded 0.70, providing statistical confirmation of convergent validity.

Discriminant Validity

Discriminant validity confirms that each latent construct represents a theoretically and empirically distinct operational domain that does not inadvertently capture the conceptual variance of other constructs. Discriminant validity was evaluated using the classical criteria outlined by Anderson and Gerbing (1988) and Fornell and Larcker (1981). Specifically, the square root of the AVE for every construct was compared against the bivariate correlation coefficients shared between that construct and all other latent dimensions in the model. In all instances, the square root of the AVE was substantially higher than the inter-construct correlations, statistically confirming robust discriminant validity throughout the instrument.

Common Method Bias Evaluation

Because cross-sectional, self-report survey instruments deployed in corporate environments face potential vulnerability to common method variance (CMV), the authors implemented both procedural and statistical remedies as prescribed by Podsakoff et al. (2003). Procedural protections included ensuring absolute anonymity, assuring respondents that there were no objectively “correct” or “incorrect” answers, and counterbalancing the presentation of questionnaire sections. Statistically, Harman’s single-factor test was executed via exploratory Principal Component Analysis (PCA). The unrotated factor solution extracted multiple distinct factors that collectively explained 74.486% of the total cumulative variance. The primary, largest single factor accounted for only 31.612% of the variance—falling comfortably below the conservative 40% and 50% critical thresholds. These empirical results verified that common method bias did not present a threat to the study’s measurement integrity.

8. Reliability

The internal consistency reliability of the instrument was comprehensively assessed through both traditional parameter estimates (Cronbach’s alpha) and structural equation modeling parameters (Composite Reliability). High internal consistency guarantees that the items assigned to each subscale are mutually coherent, measuring the exact same underlying psychological or strategic facet with negligible measurement error.

As documented in the psychometric report by Ali et al. (2023), the Cronbach’s alpha coefficients for the full battery of scales ranged from .729 to .871 across all dimensions. These figures substantially surpass the classic benchmark of .70 recommended by Hair et al. (1998) and Nunnally and Bernstein (1994) for established behavioral and organizational instruments. Furthermore, composite reliability scores across all constructs exceeded the rigorous 0.70 cutoff proposed by Hair et al. (2010), demonstrating that random measurement variance within the indicator sets was minimal and confirming high overall scale dependability.

9. Factor Analysis

To validate the underlying dimensional architecture of the instrument, a comprehensive Confirmatory Factor Analysis (CFA) was conducted using maximum likelihood estimation. The hypothesized structural model was specified as a four-factor baseline configuration consisting of four distinct, correlated latent variables: (1) Entrepreneurial Leadership, (2) Organizational Learning Culture, (3) Environmental Dynamism, and (4) Green Innovation.

The statistical fit of the hypothesized four-factor measurement model was evaluated against empirical sample data using an array of primary fit indices:

• Chi-Square to Degrees of Freedom Ratio (χ²/df): 2.63 (p < .001). This value falls comfortably below the conservative upper threshold of 3.0 (and the wider tolerance limit of 5.0), signifying an acceptable discrepancy between the sample covariance matrix and the implied model covariance matrix.
• Comparative Fit Index (CFI): 0.95. This exceeds the widely recognized .90 benchmark (and meets the stricter .95 standard proposed by Hu and Bentler, 1999), demonstrating outstanding comparative fit relative to a baseline null model.
• Goodness-of-Fit Index (GFI): 0.92. This surpasses the recommended .90 threshold, indicating that a high proportion of the observed variance-covariance matrix is reproduced by the model.
• Normed Fit Index (NFI): 0.94. This comfortably exceeds the standard .90 threshold, confirming that the hypothesized model achieves strong specification improvement over the independence model.
• Root Mean Square Residual (RMR): 0.03. This falls well below the standard .05 cutoff, indicating minimal residual variance among the individual covariance pairs.
• Root Mean Square Error of Approximation (RMSEA): 0.04. This achieves the strict benchmark of ≤ .05 (with a confidence interval bounded below .08), demonstrating high model precision and low residual error in population covariance estimation.

To further demonstrate that the hypothesized four-factor structure represented the most parsimonious and empirically defensible model, rival alternative nested models (including a single-factor common model where all 30 indicators loaded onto one general factor, as well as various two-factor and three-factor collapsed configurations) were comparatively evaluated. The hypothesized four-factor specification exhibited statistically superior fit across all benchmark criteria, confirming the distinct structural integrity of the four latent constructs.

10. Instrument / Measurement Tool

• Instrument Name: Entrepreneurial Leadership and Green Innovation—Model (EL-GI Measurement Battery)
• Test Type: Standardized Organizational Inventory / Executive Survey Questionnaire
• Total Item Count: 30 items
• Primary Dimensions / Subscales:
  • Entrepreneurial Leadership (assessing scenario enactment, cast enactment, green visionary orientation, risk-taking, and proactiveness)
  • Organizational Learning Culture (assessing continuous learning dialogue, collaboration, environmental knowledge acquisition, and shared vision)
  • Environmental Dynamism (assessing technological change rate, customer preference shifts, competitive volatility, and market unpredictability)
  • Green Innovation (assessing Green Product Innovation and Green Process Innovation)
• Authentic Response Scale: Responses are captured using a seven-point Likert scale, where 1 represents “strongly disagree” and 7 represents “strongly agree”.
• Administration Format: Structured on-site or remote professional interview administration with enterprise decision-makers (CEOs, senior corporate executives, plant managers, R&D directors), ensuring high data completion and minimizing cognitive misinterpretation.
• Available Languages: English (original baseline adaptation) and Simplified Chinese (formally back-translated and cross-culturally validated via Berry’s 1980 protocol).
• Target Population: Human adults (aged 18 years and older), specifically corporate executives, enterprise founders, operations directors, and managerial personnel operating in industrial, manufacturing, and commercial enterprises.
• Scoring and Aggregation Protocol: Each subscale is scored by computing the mean composite score of its constituent indicator items (ranging from 1.00 to 7.00). High aggregated scores denote elevated levels of executive entrepreneurial leadership, mature organizational learning cultures, intense external market dynamism, or advanced deployment of green product and process innovations.

11. Permissions & Fee and Test Year

• Test Year: 2023
• Original Publication Venue: Creativity and Innovation Management (John Wiley & Sons, Inc.)
• Commercial Availability: Non-commercial. The measurement model was developed exclusively for academic, empirical, and institutional research purposes.
• Fee: No fee is required for non-commercial scholarly research and educational applications.
• Permissions & Correspondence: Researchers seeking to utilize, reproduce, adapt, or deploy the complete Chinese or English measurement battery must obtain formal permission from the corresponding author:
  Prof. Xu Jiang
  School of Management, Xi’an Jiaotong University
  No. 28, Xianning West Road, Xi’an, Shaanxi, 710049, China
  Email: [email protected]

12. References

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• Marsick, V. J., & Watkins, K. E. (2003). Demonstrating the value of an organization’s learning culture: The dimensions of the learning organization questionnaire. Advances in Developing Human Resources, 5(2), 132–151. https://doi.org/10.1177/1523422303005002002
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
• Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. Doubleday/Currency.

13. Items of the Scale