As digital technology and innovation-driven strategies become central to corporate strategy, fostering employee creativity has emerged as a critical objective of digital transformation. However, extant research predominantly relies on linear methods and net-effect analyses, failing to adopt a configurational perspective that can elucidate the synergistic mechanisms among the factors shaping creativity during digital transformation. Based on the ability-motivation-opportunity (AMO) framework, this study integrates individual and contextual factors and employs fuzzy-set qualitative comparative analysis (fsQCA) to analyze three-wave survey data from 305 employees, thereby identifying the configurational paths that lead to high radical and incremental creativity. This approach addresses a key limitation in current research by capturing the complex, nonlinear causal mechanisms often overlooked by conventional analytical frameworks. The findings reveal that seven factors—digital transformation, digital transformational leadership, harmonious passion, obsessive passion, external search, intuitive cognitive style, and analytical cognitive style—combine to form three distinct configurations for radical creativity and three for incremental creativity. Specifically, harmonious passion is a common core condition for radical creativity, whereas digital transformation and digital transformational leadership act as substitutive antecedents. This study contributes a novel configurational understanding of employee creativity during digital transformation, highlighting the complementary and substitutive roles of AMO elements, and offers practical guidance for firms to stimulate contextually appropriate creativity.
As the digital economy intensifies, integrating digital technologies and innovation strategies has become a strategic imperative for firms. While crucial for achieving innovation and competitive advantage (Fang & Liu, 2024), digital transformation often falls victim to a high input, low return paradigm, where significant investments fail to materialize their innovative potential (Forth et al., 2020). This digital innovation dilemma often stems from a shortfall in employees’ creative motivation and capabilities, constraining the organizational absorption capacity necessary to leverage digital opportunities (Cai et al., 2020).
Talent constitutes a fundamental resource for enterprises, wherein employee creativity, augmented by digital technologies, serves as a pivotal mechanism for realizing innovative value through digital transformation (Bhatti et al., 2024). However, merely providing employees with digital tools is insufficient to motivate their adoption. The uncertainty inherent in such transformation can provoke negative psychological responses among employees (Liu et al., 2024), depleting the intrinsic energy necessary for creative endeavors and impeding the integration of technology into daily work practices. Consequently, examining the micro-level mechanisms through which digital transformation influences employee creativity is critical to resolving the “digital innovation dilemma.”
Creativity is often subdivided into radical and incremental forms (Gilson & Madjar, 2011). Radical creativity entails the generation of novel ideas that represent a departure from current paradigms, enabling transformative breakthroughs through new frameworks and processes. In contrast, incremental creativity focuses on making refinements and progressive enhancements to existing products, methodologies, and organizational structures. As distinct drivers of innovation, these two types prove critical at different developmental stages and under varying contextual demands (Bulut et al., 2022). Specifically, radical creativity is paramount in highly uncertain environments and dominates initial problem-solving phases, whereas incremental creativity becomes indispensable in relatively stable contexts and governs subsequent implementation. Consequently, for managers navigating digital transformation, discerning and stimulating the contextually appropriate form of creativity is essential, warranting targeted exploration (Yang et al., 2025).
The formation of creativity during digital transformation is a complex process arising from the interplay between individual and contextual factors (Hoffmann et al., 2016). Previous research has identified various antecedents of employee creativity through theoretical lenses such as the componential theory of creativity (Amabile, 2011) and self-determination theory (Puente-Díaz & Cavazos-Arroyo, 2017), which can be broadly categorized into ability, motivation, and opportunity dimensions (Li et al., 2024). However, the prevailing literature often treats creativity as a unidimensional construct, failing to distinguish between its different types. This oversight limits the generalizability of existing findings. Moreover, studies have predominantly focused on examining the independent net effects of antecedent variables, neglecting the synergistic mechanisms and the systemic impact of their configurations (Jia et al., 2024). Consequently, current theoretical paradigms are inadequate for capturing the complex, generative mechanisms of radical and incremental creativity in digital transformation.
Grounded in the AMO framework, the interactive and synergistic effects of ability, motivation, and opportunity constitute the core mechanism driving employee performance (Blumberg & Pringle, 1982). Therefore, to uncover the dynamic configuration patterns among influencing factors and identify the differences and commonalities in the driving paths of the two types of creativity, this study innovatively integrates configurational perspective and fsQCA to systematically deconstruct the generative paths of radical and incremental creativity in digital transformation. Specifically, this study focuses on exploring the configurational effects of opportunity (i.e., digital transformation, digital transformational leadership), motivation (i.e., work passion), and ability (i.e., cognitive style, external search) in driving employees’ radical and incremental creativity. Building on existing theoretical literature (Gruen et al., 2005; Zhou & Hoever, 2014), this study anticipates that during digital transformation, distinct configurations of employee ability, motivation, and opportunity will yield differentiated outcomes for radical versus incremental creativity.
This study advances our understanding of how organizational contexts and individual characteristics collectively shape employee creativity during digital transformation by adopting a configurational perspective. Theoretically, it contributes by clarifying the differential antecedents of radical versus incremental creativity and revealing the complementary and substitutive roles of AMO elements in fostering specific creativity types. Practically, the findings offer managers actionable insights for strategically cultivating the form of creativity most appropriate to their specific context.
Literature review and theoretical backgroundLiterature reviewDigital transformation refers to the process through which enterprises comprehensively reshape their business models, operational processes, products, and services by leveraging digital technologies to improve efficiency, optimize customer experience, innovate business models, and enhance competitive advantage (Schwarzmüller et al., 2018). While aimed at elevating operational efficiency, this transformation also precipitates a fundamental restructuring of human capital requirements. Consequently, employees, as the cornerstone of enterprise development, play a pivotal role in these initiatives (Bouckenooghe et al., 2023).
Recent research has begun to explore the micro-level psychological and behavioral effects of digital transformation on employees, examining phenomena such as resilience (Liu et al., 2024) and workplace incivility (Jin et al., 2025) through theoretical lenses like the job demands-resources (JD-R) framework and cognitive appraisal theory. However, these studies predominantly focus on employees’ passive adaptation responses, paying scant attention to their self-driven adaptation mechanisms as active agents of change. This oversight impedes the critical transition from passive coping to proactive mastery, ultimately constraining the deep implementation of digital transformation. It is crucial to recognize that employees are not merely passive recipients; their capacity to proactively adapt through creative practices is, in fact, the pivotal pathway to realizing the value of digital transformation (Bhatti et al., 2024).
Creativity, defined as the capacity to generate ideas that are both novel and useful, is commonly categorized based on novelty into radical and incremental types (Gilson & Madjar, 2011). Given their distinct underlying formation mechanisms (Madjar et al., 2011), this study integrates both types into a unified framework to specifically investigate their differential formation paths within the context of digital transformation.
Previous research has established that employee creativity is influenced by factors at both organizational and individual levels. At the organizational level, practices such as AI applications (Jia et al., 2024) and leadership styles including digital and transformational leadership (Öngel et al., 2023; Tse et al., 2018) are significant antecedents. At the individual level, key determinants encompass motivation, domain skills, and creativity-relevant skills (Amabile, 2011). Fundamentally, creativity arises from the interplay between environmental and individual factors. For instance, Ren and Song (2024) show that supportive versus constraining environments differentially shape how intrinsic and extrinsic motivation affect radical and incremental creativity. Similarly, Pollack et al. (2020) identify work passion as a core driver, with its effects contingent on individual traits and organizational contexts. Collectively, the evidences underscore that employee creativity emerges from the synergistic influence of organizational conditions and individual characteristics.
Furthermore, although antecedents like digital transformational leadership are often linked to enhanced employee creativity (Nabi et al., 2023; Öngel et al., 2023), the empirical evidence remains inconsistent. For instance, excessive transformational leadership may foster overdependence, thereby inhibiting creativity (Ma et al., 2020). Particularly in digital contexts, while such leadership can facilitate radical innovation, it may simultaneously detract from the focus on stability and incremental optimization, complicating its overall impact (Chen et al., 2018; Tarsuslu et al., 2024). We argue that these inconsistencies may stem from a failure to distinguish between creativity types, whose manifestation depends on individual and contextual contingencies. The configurational perspective advanced in this study offers an integrative framework to reconcile these contradictions by systematically examining how specific combinations of antecedents promote or inhibit distinct forms of creativity.
Despite expanding our knowledge of the antecedents of employee creativity, the literature is constrained by two principal limitations. Methodologically, an overreliance on linear regression and causal symmetry assumptions has hindered the development of a comprehensive framework capable of capturing the synergistic effects among diverse factors (Hoffmann et al., 2016), thereby limiting robust explanations of creativity’s complex mechanisms during digital transformation. Contextually, researchers have overlooked the unique nature of digital transformation, in which employee creativity simultaneously serves strategic imperatives and individual adaptation needs. Current investigations fail to systematically examine how digital transformation, leadership, and individual elements interact synergistically (Jin et al., 2025).
These theoretical limitations hinder practical guidance for organizations seeking to configure organizational conditions that effectively enhance creativity while aligning with individual characteristics. Therefore, grounded in the AMO framework, an important framework for examining the antecedents of creativity (Shin et al., 2018), this study aims to analyze how the configurational effects of employees’ ability, motivation, and opportunity during digital transformation differentially drive radical and incremental creativity.
Theoretical backgroundThe AMO theory posits that individual performance is a function of the interplay between an employee’s ability, motivation, and the opportunities provided by the organization (Blumberg & Pringle, 1982). Specifically, ability encompasses the skills, knowledge, and competencies required for employees to perform their work; motivation refers to intrinsic or extrinsic incentives that drive employees to exert effort; and opportunity denotes the organizational conditions enabling employees to leverage their abilities and motivation. A deficiency in any of these three elements can lead to sub optimal performance (Luo et al., 2024). Given that creativity is a critical indicator of employee performance (Harvey & Berry, 2023), the AMO framework offers a systematic paradigm for explaining its formation mechanisms. It not only elucidates how these core elements generate creativity individually but also provides a lens for deconstructing their synergistic interactions.
Although extant research has partially established the relationships between employee ability, motivation, opportunity, and creativity, attempts to model their interactions using multiplicative terms within linear regression frameworks have proven inadequate for capturing their complex dynamics (Furnari et al., 2021). This methodological limitation likely contributes to the inconsistent findings in the literature. In contrast, adopting a configurational perspective (distinct from traditional correlation-based methods) offers a promising approach to understanding how ability, motivation, and opportunity systematically influence creativity (Luo et al., 2024). Therefore, grounded in the AMO framework, this study investigates how distinct configurations of employee ability, motivation, and opportunity jointly drive the development of radical versus incremental creativity.
Antecedents of employee creativity in digital transformationEmployee ability and creativityExternal searchExternal search refers to the proactive process through which organizations or individuals identify, acquire, assimilate, and utilize new knowledge, information, technologies, ideas, or resources from external environments (Laursen & Salter, 2006). As a domain skill, it substantially enriches the complexity and flexibility of knowledge structures. An effective search strategy emphasizes a balance between breadth and depth (Yang et al., 2025), which serves to expand and refine employees’ domain knowledge and cognitive frameworks. This process enhances the architectural complexity of knowledge and provides a broader conceptual repertoire within one’s expertise. By simultaneously capturing diversified knowledge and specialized insights, effective external search constitutes a core capability that drives both radical and incremental creativity (Dahlander et al., 2016).
Cognitive styleAs a creativity-relevant skill, cognitive style reflects an individual’s characteristic reliance on either intuitive or analytical information processing systems (Epstein et al., 1996). An intuitive cognitive style is characterized by rapid, automatic, and unconscious processing that draws heavily on experiential knowledge, contextual cues, and affective responses. In contrast, an analytical cognitive style entails a deliberate, logic-based method requiring conscious, systematic information analysis and evaluation. These distinct cognitive styles have been shown to exert differential influences on radical versus incremental creativity (De Visser et al., 2014).
Individuals with an intuitive cognitive style often depart from conventional norms, demonstrating a preference for novel and unconventional problem-solving. Their broad, associative thinking fosters exploration and a heightened propensity for radical creativity (De Visser et al., 2014). This is because they excel at developing adaptive responses through the holistic integration of ambiguous information (Olson, 1985), making this style predominant in endeavors requiring groundbreaking ideas, such as developing novel products or seeking unconventional solutions (Kickul et al., 2009).
In contrast, individuals with an analytical style employ logical, systematic, and incremental methodologies (Armstrong & Priola, 2001). Their convergent thinking leads them to refine solutions within existing frameworks, focusing on identifying and resolving specific limitations (Ye et al., 2026). Consequently, they excel in incremental creativity, where practicality and feasibility are paramount. This style’s emphasis on procedural adherence further enhances its effectiveness in such contexts (Madjar et al., 2011).
Employee motivation and creativityWork passion represents a significant form of motivation, categorized into harmonious passion and obsessive passion based on whether the internalization of the activity into one’s identity is autonomous or controlled (Vallerand et al., 2003). These two types of passion reflect distinct motivational foundations, which subsequently exert differential influences on individual creativity (Pollack et al., 2020).
Individuals with harmonious passion identify authentically with their work and derive intrinsic enjoyment from it, which drives substantial investment of time, cognition, and affect into radical creative activities (Luh & Lu, 2012). By prioritizing personal growth, they view failures as opportunities for learning, demonstrating greater psychological flexibility and open-mindedness (Birkeland & Buch, 2015). This future-oriented achievement motivation fosters a persistent willingness to explore novel domains and pursue radical innovations, even in the face of potential setbacks (Wu & Lin, 2024).
Conversely, obsessive passion facilitates incremental creativity through a combination of task-focused intensity and risk-averse control mechanisms. Its extrinsic motivational orientation (e.g., driven by rewards or recognition) heightens focus on task completion and execution efficiency (Stoeber et al., 2011). This risk-averse disposition also encourages strict adherence to organizational protocols and a preference for making refinements within established frameworks (Wei et al., 2024). Consequently, this predictability-driven approach prioritizes incremental creative practices that offer predictable marginal returns, shorter implementation cycles, and immediate pragmatic value (Ren & Song, 2024).
Employee opportunity and creativityDigital transformationAccording to the JD-R model, digital transformation influences employee creativity through dual pathways of job resources and job demands (Ruiner et al., 2023). On the resource side, it furnishes opportunities for creative practices by enhancing information accessibility through digital tools, which helps overcome knowledge constraints and reduces repetitive tasks, thereby boosting organizational identification and willingness to innovate (Meske & Junglas, 2021). Furthermore, emerging work scenarios like human-machine collaboration and remote work introduce more intelligent and flexible methods, increasing employees’ autonomy (Putra et al., 2020) and freeing up time and energy for both radical and incremental creative activities.
On the demands side, digital transformation imposes heightened pressures that compel adaptive innovation. Employees must upgrade capabilities to master new digital literacies and restructure creativity-relevant skill sets. Digital work environments generate pressures to innovate or risk obsolescence (Clinton et al., 2017), forcing employees to engage in radical or incremental creative practice, to maintain competence (Scholze & Hecker, 2024).
Digital transformational leadershipDigital transformational leadership integrates digital thinking with traditional transformational leadership. It is characterized by leveraging digital technologies to inspire employee potential through a digital vision, thereby driving organizational adaptation to digital strategic objectives (AlNuaimi et al., 2022). By establishing digital transformation initiatives and challenging objectives, such leaders motivate employees toward proactive innovation while providing timely and constructive feedback (Schiuma et al., 2024). Under this leadership, employees develop a stronger instrumental understanding of digital transformation, which fulfills their psychological needs and channels their energy into intrinsic motivation for radical creative tasks.
However, this leadership style prioritizes transformative change and often diminishes the traditional emphasis on stability, risk control, and short-term objectives. Moreover, by providing extensive support, it may engender a psychological comfort zone that diminishes employees’ sensitivity to external pressures (Landay et al., 2022). Conversely, moderate pressure is a key mechanism for driving incremental creativity, as it incentivizes optimized solutions under resource constraint (Albort-Morant et al., 2020). When digital transformational leadership reduces perceived pressure, employees adapt to digital uncertainty without urgency to resolve it (Tarsuslu et al., 2024). Consequently, they may exhibit slower response and reduced efficiency in time-sensitive, low-error-tolerance incremental tasks, ultimately undermining incremental creativity.
Conceptual frameworkGrounded in the AMO theoretical framework, this study posits that employee creativity during digital transformation stems from the synergistic interactions among these three elements. Within the ability dimension, both domain skills and creativity-relevant skills constitute essential components for creativity development (Amabile, 2011). Domain skills, comprising an individual’s expertise, technical competence, and practical experience within a specific field, provide the foundational material for creative output and shape the scope of problem identification and resolution. External search, which involves the proactive acquisition of knowledge across organizational boundaries, is a critical domain skill that facilitates both radical and incremental creativity (Dahlander et al., 2016).
Creativity-relevant skills emphasize the capacity to transform knowledge into novel and useful outcomes. They encompass cognitive processes such as associative thinking, divergent thinking, and problem-solving (Amabile, 2011). Cognitive style serves as a key creativity-relevant skill, reflecting an individual’s stable patterns in processing information, perceiving environments, and structuring thought, which play a central role in mental model construction and decision-making (Epstein et al., 1996). Specifically, an intuitive cognitive style is more conducive to stimulating cross-boundary associations and divergent thinking, thereby promoting radical creativity, whereas an analytical cognitive style supports systematic optimization and process improvement, forming the ability foundation for incremental creativity (De Visser et al., 2014).
Within motivation dimension, this study employs the dualistic model of work passion, which comprises harmonious passion and obsessive passion (Vallerand et al., 2003), to explain employees’ inclinations toward different types of creative practices during digital transformation. Harmonious passion, arising from intrinsic enjoyment of the task itself, is often accompanied by positive affect and autonomous exploration, making it more likely to facilitate radical creativity. In contrast, obsessive passion, typically driven by external pressures or self-esteem needs, tends to emphasize risk control and compliance with norms, thereby facilitating incremental creativity (Yang et al., 2025).
Within the opportunity dimension, digital transformation and digital transformational leadership serve as critical contextual factors influencing employee creativity. Digital transformation enables creativity by providing technological empowerment and essential digital resources (AlNuaimi et al., 2022), while digital transformational leadership cultivates a climate conducive to radical creativity by articulating a digital vision and tolerating change and failure. It should be noted, however, that an excessive emphasis on transformation may divert attention from systemic risks and short-term performance, potentially suppressing incremental creativity (Chen et al., 2018; Tarsuslu et al., 2024).
Building on this reasoning, the study further proposes that the realization of employee creativity depends not on the isolated effect of any single factor, but on the configuration of ability, motivation, and opportunity. For instance, high radical creativity may emerge under conditions such as strong intuitive cognitive style, high harmonious passion, high digital transformational leadership, high external search and advanced digital transformation, reflecting synergistic activation of multiple elements. In contrast, high incremental creativity is more likely to be achieved in configurations featuring a strong analytical cognitive style, high obsessive passion, high digital transformation, high external search and low digital transformational leadership, indicative of a control-oriented optimization logic.
In summary, grounded in AMO theory, this study constructs a conceptual model (see Fig. 1) to systematically examine how different configurations of seven factors across the ability, motivation, and opportunity dimensions collectively shape the development of radical versus incremental creativity among employees during digital transformation.
MethodologySample and procedure
Data were collected from manufacturing enterprises undergoing digital transformation, contacted through channels including industry associations and research partnerships. The manufacturing sector represents a strategic focus of China’s digital transformation, offering strong contextual relevance, as these firms depend heavily on employee adaptability and creativity for efficient production and change implementation.
A three-wave survey design was employed to mitigate common method bias. Questionnaires were distributed on-site and via the Credamo platform to HR supervisors, who then forwarded them to employees. Participants were assured of confidentiality and anonymity to encourage candid responses.
At Time 1, we measured demographic variables and opportunity factors (digital transformation and digital transformational leadership), receiving 412 responses. At Time 2, measures of motivation (harmonious/obsessive passion) and ability (cognitive styles, external search) were administered, yielding 367 completed surveys (response rate: 89.1 %). At Time 3, employees self-reported their radical and incremental creativity, with 355 responses (96.7 % response rate).
After matching responses across waves using unique IDs, we excluded cases with straight-line responses or extreme outliers, resulting in a final valid sample of 305 employees and an overall response rate of 74.0 %. Table 1 presents the sample’s descriptive statistics.
Sample descriptive statistics.
All constructs were measured using established scales, which were rigorously translated following the translation-back-translation procedure. Unless otherwise noted, items were rated on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).
Digital transformation was measured using Nasiri et al.’s (2020) 5-item scale (α = 0.85). Sample item: “Our organization aims to achieve digital information exchange.”
Digital transformational leadership was assessed via AlNuaimi et al.’s (2022) 6-item adaptation (α = 0.93). Sample item: “Our leader inspires collective efforts toward shared digital transformation goals.”
Work passion was measured using Vallerand et al.’s (2003) dual-dimensional scale. Specifically, harmonious passion includes 7 items (α = 0.91). Sample: “My work harmoniously integrates with other life activities.” Obsessive passion includes 7 items (α = 0.96). Sample item: “I feel controlled by work demands.”
Based on the research by Laursen and Salter (2006), we selected a formative structural scale to measure external search, assessing employees’ average utilization of completely different types of external knowledge sources (a total of 8 sources, including customers, universities, research institutions, etc.). Following the approach outlined by Yang et al. (2025), to more comprehensively account for the breadth and depth of external search and accurately measure the overall extent of external search, we adopted a downward-compatible calculation method.
Specifically, the overall extent of external search was represented by the number of external search sources with scores ≥5. The scoring was based on a 7-point scale (1 = not used; 7 = frequently used). This indicator emphasizes both moderate intensity of use across multiple sources (depth) and a sufficient coverage of diverse sources (breadth), thereby comprehensively reflecting employees’ effective engagement in external knowledge acquisition. Conceptually, external search is a formative construct, meaning each type of source contributes uniquely and irreplaceably to the overall measure. Accordingly, we aggregated the sources into a composite index.
Cognitive style was measured using Epstein et al.’s (1996) scale adapted via De Visser et al.’s (2014) factor-loading criterion. Specifically, intuitive cognitive style includes 5 items (α = 0.92). Sample item: “I trust my gut feelings.” Analytic style includes 5 items (α = 0.90). Sample: “I enjoy solving problems requiring logical analysis.”
Creativity was measured using Madjar et al.’s (2011) dual-scale. Specifically, radical creativity includes 3 items (α = 0.92). Sample item: “I generate fundamentally novel ideas.” Incremental creativity includes 3 items (α = 0.89). Sample item: “I systematically refine existing workflows/technologies.”
Reliability and validity testingConfirmatory factor analysis (CFA) was conducted to assess the alignment between the measurement items and the theoretical model and to evaluate the discriminant validity among the constructs. The analyzed constructs included digital transformation (DT), obsessive passion (OP), harmonious passion (HP), incremental creativity (IC), radical creativity (RC), intuitive cognitive style (ICS), analytical cognitive style (ACS), and digital transformational leadership (DTL). External search was treated as a formative, quantitatively scored indicator and was therefore excluded from the CFA, which is suited for reflective latent constructs.
A series of nested CFA models were tested using AMOS. Model fit was evaluated with indices including χ2, df, CFI, TLI, SRMR and RMSEA. As shown in Table 2, the eight-factor model demonstrated acceptable to good fit and was superior to all alternative models. The fit indices (χ2=972.244, χ2/df=1.295, SRMR=0.031, RMSEA=0.031, CFI=0.985, TLI=0.983) indicate that the model fits the data well, supporting the discriminant validity of the eight core constructs.
Results of confirmatory factor analysis.
Although Harman’s single-factor test is frequently employed as an initial check for common method bias, it is known to have limitations in sensitivity and may be insufficient for detecting subtle biases. To address this concern more rigorously, we incorporated an unmeasured latent method factor into the confirmatory factor analysis (CFA) model. This approach provides a more robust assessment of potential common method variance (CMV). The results showed nearly identical model fit after incorporating the latent method factor (Δχ2/df=0.013, ΔSRMR<0.001, ΔRMSEA<0.002, ΔCFI<0.001, ΔTLI<0.001), indicating that common method bias did not significantly affect the results.
Furthermore, additional reliability and validity assessments were conducted. We computed the composite reliability (CR), average variance extracted (AVE), and heterotrait-monotrait ratio (HTMT) for each reflective construct. As presented in Table 3, all constructs demonstrated CR values above 0.70, AVE values exceeding 0.50, and all HTMT values between constructs were below 0.85. These results indicate satisfactory convergent validity and discriminant validity across all constructs.
Reliability and validity of the constructs.
Note: The HTMT range indicates the span of pairwise HTMT values between the construct and all other constructs, all of which are below 0.85.
This study employs an internal calibration approach, which anchors set membership based on the relative distribution of values within the sample (Pappas et al., 2017). Specifically, the mean of each condition was set as the crossover point (0.5). Values one standard deviation above the mean were assigned full membership (1.0), while values one standard deviation below the mean were assigned full non-membership (0.0). To prevent the exclusion of cases with ambiguous membership scores, particularly those exactly at the crossover point, we followed the procedure recommended by Campbell et al. (2016) and replaced any membership score of 0.500 with 0.501. A complete summary of the calibration anchors is provided in Table 4.
Anchors of calibration.
The results of the necessary condition analysis are presented in Table 5. The analysis reveals that no single antecedent condition meets the 0.9 consistency threshold for being a necessary condition. This indicates that no individual factor is sufficient by itself to explain employee creativity during digital transformation. Consequently, a configurational analysis is required to uncover the distinct pathways and underlying mechanisms for radical versus incremental creativity.
Analysis of necessary conditions.
Note: RC = radical creativity; IC = incremental creativity; DTL = digital transformational leadership.
To ensure analytical clarity and statistical reliability, we constructed and refined the truth table. In line with established practices (Douglas et al., 2020), a minimum case frequency threshold of 3 was adopted to screen out infrequent configurations and enhance the robustness of the causal relationships identified. After evaluating all 128 logically possible configurations, the analysis of radical creativity retained 237 cases (43 configurations, covering 77.7 % of the sample), while the analysis of incremental creativity retained 274 cases (49 configurations, covering 89.8 %). Although the retention rate for radical creativity is slightly below the conventional 80 % benchmark, this conservative approach minimizes potential distortion from rare configurations and strengthens the validity of the solutions.
The fsQCA was conducted using R software (version 4.2.0) with the QCA (version 3.23) and SetMethods (version 2.5) packages. Consistent with methodological benchmarks and the study’s context, we applied a raw consistency threshold of 0.80, a PRI consistency threshold of 0.75, and a minimum case frequency of 3 to ensure the robustness of the derived solutions.
This study conducted configurational analyses separately for high radical creativity and high incremental creativity as outcome variables, with the seven factors from the ability, motivation, and opportunity dimensions serving as antecedent conditions. The resulting configuration patterns were labeled according to the configurational theorizing process. As presented in Table 6, the analysis yielded three configurations for high radical creativity, labeled as “strategic traction-passion driven”, “leadership incentive-passion focused”, and “dual ability engine-autonomous breakthrough”. Similarly, three configurations for high incremental creativity were identified and termed “strategic pressure-constrained autonomy”, “strategic driven-analytical iteration”, and “analytical anchoring-benchmark optimization”.
Configurations for achieving high radical/incremental creativity.
Note: RC=radical creativity; IC=incremental creativity; ● core presence;○ peripheral presence; ⊗core absence;° peripheral absence.
The interpretation of the configurational results relies on two core metrics: consistency and coverage. Consistency measures the degree to which a specific configuration of conditions reliably leads to the outcome, with higher values indicating a more robust causal relationship. Coverage gauges the proportion of outcome instances explained by a configuration, where higher values denote greater explanatory scope. The two metrics jointly assess the reliability and empirical relevance of the solutions.
Both the consistency scores for individual configurations and the overall solution consistency exceeded the accepted thresholds (raw consistency > 0.80; PRI consistency > 0.75). The overall solution consistency was 0.911 for radical creativity and 0.922 for incremental creativity, while the overall solution coverage was 0.281 and 0.355, respectively. These results indicate that the identified configurations represent highly reliable causal pathways. The moderate coverage values are common in fsQCA and suggest that while the solutions explain a substantive portion of the cases, alternative pathways to high creativity may also exist.
To examine the potential influence of job type, we used job category as a case marker to trace its association with the identified configurational pathways. The results showed no clear differentiation; the distribution of cases across various job roles within each pathway appeared random. This suggests that, within our manufacturing sample, the pathways to high radical or incremental creativity are not significantly shaped by formal job categories.
A plausible explanation is that in manufacturing firms undergoing digital transformation, the boundaries between traditional job roles become blurred. Furthermore, employees across different roles are likely exposed to similar organizational resources, technological tools, and innovation climates. This shared contextual environment may attenuate the distinctive influence of job category, leading to the observed pattern where creativity pathways transcend formal job designations.
Configurations for high radical creativityType of strategic traction-passion drivenConfiguration R1 reveals a “strategic traction-passion driven” pattern, wherein high digital transformation and high harmonious passion synergistically foster radical creativity. According to JD-R theory, digital transformation enriches technological resources and provides a clear strategic direction, which establishes well-defined objectives and action frameworks for employees (Liu et al., 2024). This enhances their perceived resource availability and confidence in enacting change (Nasiri et al., 2020). The resulting strategic clarity, supported by reconfigured digital platforms, significantly reduces the uncertainties associated with exploratory innovation (Scholze & Hecker, 2023). This supportive context fulfills employees’ basic psychological needs, further strengthening their confidence and harmonious passion for cross-boundary exploration (Jin et al., 2025), thereby laying a solid resource and motivational foundation for radical creative endeavors.
Furthermore, individuals with a strong harmonious passion engage in work out of genuine interest and value alignment, experiencing a sense of volition and psychological freedom (Vallerand et al., 2003). This intrinsic motivation fosters a persistent drive for personal growth and a propensity to proactively seek out challenges, such as acquiring new skills and solving complex problems. This motivational disposition enables individuals to more readily pursue exploratory innovation, embrace uncertainty, and consequently exhibit higher levels of radical creativity during periods of digital transformation (Appu & Sia, 2017).
Type of leadership incentive-passion focusedConfiguration R2 reveals a “leadership incentive-passion focused” pattern, wherein high digital transformational leadership and high harmonious passion jointly facilitate high radical creativity. According to self-determination theory (Deci & Ryan, 2000), individual motivation is shaped not only by internal factors but also critically by external environmental elements, such as leadership. Digital transformational leadership motivates employees by articulating a compelling digital vision and implementation plan, which promotes deep internalization of transformation goals and strengthens both belief in the mission and harmonious passion (Majumdarr et al., 2024). This leadership style provides emotional and resourceful support, exhibits high tolerance for trial and error, and encourages diverse perspectives that challenge the status quo. Unlike directive management, it grants greater autonomy and enhances perceived competence, further consolidating harmonious passion and improving cognitive flexibility (AlNuaimi et al., 2022). Consequently, employees are more willing to engage in long-term, high-risk exploration, viewing radical creativity as a path to self-actualization.
Compared to R1, this configuration is particularly suited to the early stages of digital transformation, when strategic clarity is low and technological resources are not fully deployed. Here, digital transformational leadership compensates for low organizational maturity by effectively communicating the vision and clarifying goals, while employees’ harmonious passion ensures high engagement. Their synergy alleviates technological anxiety and cognitive barriers, making this configuration a key driver for radical creativity under such conditions.
Type of dual ability engine-autonomous breakthroughConfiguration R3 demonstrates that high radical creativity can be achieved through the confluence of three core individual-level conditions: a strong intuitive cognitive style, high harmonious passion, and active external search. According to Amabile’s (2011) componential theory, these elements represent the core ingredients of creativity: a strong intuitive style serves as a creativity-relevant skill that enables cross-boundary associations and original idea generation (Chen, 2020); high harmonious passion provides the intrinsic motivation for persistent, voluntary engagement in high-risk exploration (Appu & Sia, 2017); and active external search acts as a critical domain skill that supplies the necessary cross-domain knowledge for both ideation and implementation (Zhang et al., 2023). The core mechanism of this configuration is the synergistic interaction between individual ability and motivation, forming a “dual ability engine-autonomous breakthrough” pattern.
Unlike R1 and R2, which depend on favorable external opportunities (e.g., advanced digital transformation or strong leadership), R3 highlights a primarily self-driven pathway. This pattern is particularly salient in contexts requiring deep expertise and autonomous exploration, such as breakthrough R&D. It indicates that employees endowed with strong intrinsic motivation and key competencies can transcend organizational constraints and initiate radical creative practices autonomously, even when external support is limited.
Configurations for high incremental creativityType of strategic pressure-constrained autonomyConfiguration J1 reveals a “strategic pressure-constrained autonomy” pathway to high incremental creativity, driven by the combination of high digital transformation, high obsessive passion, and low digital transformational leadership. Grounded in the JD-R model, digital transformation increases job demands and technological complexity, creating performance pressure that compels greater effort (Scholze & Hecker, 2024). This external pressure reduces autonomy and disrupts psychological equilibrium, fostering a controlled form of internalization seen as obsessive passion (Vallerand et al., 2003), which directs employees toward adaptive, low-risk innovation. Concurrently, digital tools generate quantifiable performance goals that focus attention on predictable, incremental optimization (Liu et al., 2023). The low level of digital transformational leadership reinforces this pathway by creating an execution-oriented environment. Its limited support for change, low error tolerance, and restrained empowerment synergize with the external pressures, strengthening a control-oriented climate that further consolidates obsessive passion (Majumdarr et al., 2024; Zhang et al., 2025). Consequently, driven by this passion, employees channel pressure into continuous refinement within constraints, achieving incremental improvements to meet performance goals.
The role of low digital transformational leadership here should not be interpreted as a deficiency but as a differentiated style suited to specific contexts. This aligns with Kesting et al. (2015), who argue that different innovation types require distinct leadership. In this light, digital transformational leadership is not universally effective for all forms of innovation; the suitability of leadership styles varies depending on innovation goals and operational environments (Yang et al., 2025).
Specifically, in task environments that emphasize execution and operational efficiency, directive management (focused on process monitoring, resource coordination, and efficiency optimization) may be more effective than change-oriented digital transformational leadership in maintaining perceived pressure and execution focus within teams, thereby more effectively facilitating employee incremental creativity (Chen et al., 2018; Tarsuslu et al., 2024).
Considering its positive role in radical creativity (R2) and its potential inhibition here (J1), digital transformational leadership indeed exhibits a double-edged sword effect (Öngel et al., 2023). Managers should therefore dynamically adapt its intensity based on whether the strategic goal is radical breakthrough or incremental optimization.
Type of strategic driven-analytical iterationConfiguration J2 reveals a “strategic driven-analytical iteration” path to high incremental creativity, where high digital transformation and a strong analytical cognitive style act as core conditions. Within this mechanism, digital transformation provides technological platforms that decompose macro-level strategic goals into executable incremental tasks, generating continuous improvement demands (Liu et al., 2023). Simultaneously, a strong analytical cognitive style enables employees to leverage logical thinking for identifying key optimization points, translating strategic objectives into actionable, low-risk improvement plans, and utilizing digital tools for sustained refinement (Chen, 2020).
The core of this configuration lies in the synergy between the decomposition and risk-control capabilities offered by digital tools and employees’ systematic analytical style. This synergy enhances resource allocation efficiency and risk management, constructing a controlled and low-risk pathway for incremental creativity. In organizational environments with high digital maturity that require predictable improvements within a stable framework (e.g., standardized production lines), employees often face strict incremental pressures. Here, digital transformation serves as foundational support, enabling efficient task execution and process streamlining (Duan et al., 2023), while employees’ analytical style helps identify improvement opportunities and maintain focus under pressure, thereby significantly boosting incremental creativity.
Type of analytical anchoring-benchmark optimizationConfiguration J3 demonstrates that high incremental creativity can be achieved through the synergistic combination of a strong analytical cognitive style, high obsessive passion, and high external search. Grounded in Amabile’s (2011) componential theory of creativity, these three conditions align with the core components of creativity: obsessive passion provides the motivational drive, external search acts as a key domain-relevant skill for acquiring validated knowledge, and an analytical cognitive style serves as a crucial creativity-relevant skill that ensures logical rigor (Yang et al., 2025). Their interaction forms an externally-anchored, and risk-averse pathway to incremental creativity.
Specifically, obsessive passion drives the pursuit of practical improvements to gain recognition (Vallerand et al., 2003). High external search focuses on mature benchmarks, providing clear, low-risk optimization targets (Dahlander et al., 2016). The analytical cognitive style then enables systematic gap analysis and the design of executable refinement plans (De Visser et al., 2014).
Crucially, unlike J1 and J2, which rely more heavily on external opportunities to foster incremental creativity, the core mechanism of J3 reflects an endogenous synergy between motivation and ability at the individual level. As a result, even when external opportunities are less favorable, employees with these traits can still proactively align with industry information to advance cost-effective and risk-controlled incremental goals, such as reducing production costs or shortening delivery cycles. This enables them to effectively drive incremental creativity in contexts that emphasize steady improvement, such as manufacturing.
Robustness checksTo assess the robustness of the configurations, we employed three sensitivity tests. First, we adjusted the minimum case frequency threshold to 2 and then to 4. The analysis with a threshold of 2 incorporated more low-frequency configurations but retained the core causal paths. At the stricter threshold of 4, the solution remained consistent with the original findings, with the exception that configuration R3 was excluded. Second, increasing the raw consistency threshold from 0.80 to 0.85 yielded identical configurations. Third, raising the PRI consistency threshold from 0.75 to 0.80 resulted in a subset of the original configurations, with no significant change in overall consistency or coverage. Collectively, these robustness checks confirm the stability of the identified configurations (Luo et al., 2024).
Further robustness checks were conducted to verify the reliability of the results. A 70/30 holdout sample validation was performed to assess predictive validity. In the test set, the solutions for radical creativity (RC) demonstrated a consistency of 0.951 and a coverage of 0.481, while those for incremental creativity (IC) achieved a consistency of 0.970 and a coverage of 0.590, indicating satisfactory predictive validity. Moreover, the overall solution exhibited high out-of-sample consistency (0.968) and coverage (0.696). These results suggest that the identified configurations are robust and generalizable beyond the original sample.
Second, counterfactual analysis was conducted based on directional expectations derived from AMO theory. The results showed complete convergence between the intermediate and parsimonious solutions, both yielding the same four pathways with identical consistency and coverage metrics. This indicates that the findings are robust and not sensitive to alternative counterfactual assumptions. Although the resulting pathways are identical, the theoretical interpretation primarily relies on the intermediate solution, as it is derived under theoretically plausible counterfactuals and offers a more complete causal explanation.
To ensure full transparency, complete tables and figures associated with these analyses are provided in the online appendix.1
ConclusionsGrounded in the AMO framework, this study employs fsQCA to delineate the multiple conjunctural paths that drive employee creativity during digital transformation in Chinese manufacturing enterprises. The findings advance the theoretical understanding of employee creativity through a configurational lens and yield significant practical implications for manufacturing firms seeking to cultivate contextually appropriate forms of creativity.
First, the findings demonstrate that no single AMO element independently drives high creativity, underscoring the necessity of multidimensional alignment. Employee creativity emerges as a complex outcome arising from the nonlinear synergistic interactions among these elements. The identified configurational pathways reveal a dynamic coupling between external opportunities and individual ability-motivation characteristics. Furthermore, both radical and incremental creativity exhibit the principle of equifinality, meaning that multiple distinct configurations can lead to similarly high creative outcomes.
Second, the analysis identifies three core pathways to high radical creativity. Across all three, motivation elements are indispensable, with harmonious passion serving as a common core condition. Furthermore, a substitution effect exists among opportunity factors: digital transformation and digital transformational leadership can functionally substitute for one another across different pathways. In contrast, motivation and ability elements exhibit complementarity, as evidenced by the consistent presence of harmonious passion, intuitive cognitive style, and external search as core or peripheral conditions in all high-radical-creativity configurations.
Third, the study identifies three core pathways to high incremental creativity, with obsessive passion serving as an important condition across all configurations. Furthermore, specific constraints can enhance incremental creativity in certain contexts. For instance, in configuration J1, a low degree of digital transformational leadership acts as a core condition by maintaining task pressure and reinforcing an execution-oriented focus, thereby improving efficiency. Notably, whereas pathways J1 and J2 rely on external opportunities, configuration J3 demonstrates that a synergistic combination of individual-level motivation and abilities can drive incremental creativity even in the absence of strong external opportunities.
Fourth, the formation mechanisms of the two creativity types exhibit a fundamental pattern of ability divergence and opportunity complementarity. In terms of ability factors, a clear divergence exists: radical creativity relies on an intuitive cognitive style, whereas incremental creativity depends on an analytical cognitive style, corroborating the dual-processing theory of cognition. Regarding opportunity factors, a complementary logic applies: radical creativity is activated by open-type opportunities (e.g., leadership inspiration, abundant resources) that unlock harmonious passion, while incremental creativity is driven by constraint-type opportunities (e.g., performance pressure, controlled demands) that reinforce a control orientation. This pattern extends to motivation, confirming a matching principle whereby harmonious passion is a core motivator of radical creativity, and obsessive passion is a key motivator of incremental creativity.
Furthermore, the overall solution coverage values are moderate, which is a common characteristic in fsQCA studies and reflects the nature of the coverage metric itself. It is important to note that coverage indicates the proportion of outcome cases explained by the solution, not the reliability of the causal paths—which is assessed by consistency. The moderate coverage observed here indicates substantive heterogeneity in how creativity emerges, suggesting that other sufficient pathways may exist beyond those identified in our model. This, however, does not invalidate the configurations we have uncovered. On the contrary, their high consistency confirms that for the cases they explain, these pathways represent robust and reliable causal mechanisms for creativity formation.
Theoretical contributionsBy integrating seven key antecedents from the ability, motivation, and opportunity dimensions, this study employs fsQCA to uncover the multiple conjunctural causation underlying radical and incremental employee creativity during digital transformation in manufacturing, thereby addressing a significant limitation in the literature. Prior research predominantly adopts variable-centric approaches, which focus on linear effects of individual ability, motivation, or external opportunities (Li et al., 2024), yet fails to comprehensively explain the complex synergistic mechanisms driving creativity in digital contexts. Grounded in the AMO framework, this study identifies three distinct pathways each for radical and incremental creativity, demonstrating that no universally optimal single path exists. Instead, diverse AMO configurations can equally enable high creativity levels. This study extends AMO theory to digital transformation scenarios, pioneers configuration-based research pathways, and offers novel theoretical insights with an integrative analytical framework for understanding creativity’s nonlinear complexity.
Second, this study delineates the distinct configuration pathways and synergistic mechanisms underlying radical versus incremental creativity. The findings indicate that radical creativity relies on harmonious passion and an intuitive cognitive style as its core engines, whereas incremental creativity is driven predominantly by obsessive passion and an analytical cognitive style. This clear distinction confirms that each creativity type draws upon divergent motivational foundations and cognitive processing systems (Epstein et al., 1996). Importantly, these antecedent conditions are not mutually exclusive but can coexist and play complementary roles in different contexts. This insight provides organizations with a more nuanced understanding of creativity, highlighting that a single factor, such as digital transformation, can potentially foster both types of creativity, depending on its configuration with other individual and contextual factors.
Third, the study elucidates the synergistic enhancement patterns among AMO elements. The configurational analysis reveals a complementary relationship between motivation and ability factors, while a substitutive effect exists among opportunity factors. This indicates that organizations can activate creativity through differentiated allocations of opportunity resources.
Moreover, the findings demonstrate that specific constraints can facilitate incremental creativity. For instance, a lower degree of digital transformational leadership, by reinforcing a control-oriented and pressure-driven environment, was found to enhance execution efficiency in incremental tasks. This finding contrasts with much of the prior literature that predominantly highlights the positive influence of transformational leadership (Ardi et al., 2020; De Clercq & Mustafa, 2024). By distinguishing between creativity types and adopting a configurational lens, this study reconciles these inconsistencies: configuration R2 confirms that such leadership promotes radical creativity, whereas configuration J1 shows it can inhibit incremental creativity, thereby confirming its “dual-edged” effect.
This finding aligns with the contingency argument that different innovation types demand distinct leadership styles (Kesting et al., 2015). It underscores that leadership effectiveness must be evaluated against specific task requirements and innovation goals. Digital transformational leadership is not universally beneficial; its efficacy is contingent on the nature of the innovation and the context, providing a more nuanced, context-sensitive understanding of the leadership-creativity relationship.
Management implicationsFirst, enterprises should provide differentiated support for employees’ radical or incremental creativity based on the configurational effects of multiple factors. The study shows that no single factor is a necessary condition for either type of creativity; their formation relies on the synergistic interaction of multidimensional elements such as ability, motivation, and opportunity. Consequently, organizations must abandon uniform policies and establish dynamic multidimensional support systems that strategically deploy resources according to transformation phases, task characteristics, and employee profiles to activate targeted creativity types.
On one hand, the findings indicate that harmonious passion serves as a core condition for radical creativity. Organizations should therefore provide employees with autonomous exploration space and platforms, encouraging initiation of or participation in high-uncertainty radical projects. Establishing mechanisms for setback tolerance is equally critical to alleviate innovation risks and stimulate passion for challenging the status quo. Furthermore, configurations such as “strategic traction-passion driven” and “leadership incentive-passion focused” reveal that digital transformation and digital transformational leadership are crucial drivers of high radical creativity and exhibit a substitutive relationship. Consequently, in initial transformation phases or key breakthrough domains, organizations should ensure at least one of these elements is strongly activated: either by strengthening digital transformation (e.g., forming dedicated committees to communicate the vision, enhancing digital infrastructure) or, in contexts of strategic ambiguity or limited resources, by prioritizing the development of digital transformational leadership (e.g., through workshops to enhance vision articulation and empowerment skills). Such leaders must excel in envisioning a digital future, enabling cross-boundary exploration and high-risk experimentation, while cultivating a culture that encourages risk-taking and learns from failure.
On the other hand, obsessive passion serves as a critical motivational foundation for incremental creativity, necessitating the maintenance of appropriately controlled pressure. The “strategic pressure-constrained autonomy” configuration indicates that strong digital transformational leadership may dilute the urgency and focus required for incremental tasks. Therefore, during execution phases, leaders should minimize non-essential interventions and instead concentrate on process monitoring, resource coordination, and problem-solving to maintain teams’ awareness of objectives, timelines, and performance standards, thereby ensuring execution efficiency. Simultaneously, the “analytical anchoring-benchmark optimization” configuration suggests that organizations should implement focused external search strategies, such as creating knowledge repositories of competitor technologies, setting search scope thresholds, and deploying algorithmic tools to precision-screen and integrate external information.
It is critical for managers to adopt a context-sensitive and dynamic leadership strategy. When teams are engaged in core tasks involving disruptive innovation, technological breakthroughs, or new market development, digital transformational leadership should be emphasized. Leaders need to articulate a clear digital vision, encourage challenging the status quo, and tolerate exploratory failures to fully leverage its positive impact on radical creativity.
Conversely, when teams focus on process optimization, efficiency improvement, or quality refinement, the application of such leadership should be moderated or complemented with other styles. In these contexts, greater emphasis should be placed on setting clear execution goals, exercising strict process control, and implementing meticulous management. This helps prevent an excessive focus on “change” from diverting attention from implementation details, thereby fostering an environment conducive to incremental creativity.
Given that most organizations must balance exploration and exploitation (i.e., achieve organizational ambidexterity), managers should be capable of deploying leadership styles differentially across units. For example, digital transformational leadership can be strengthened in R&D departments to stimulate radical innovation, while a more transactional leadership style emphasizing stability and efficiency may be adopted in production and operations to ensure reliable execution and incremental improvement.
Finally, organizations should implement differentiated support strategies aligned with employees’ distinct cognitive styles, as intuitive and analytical styles are critical enablers of radical and incremental creativity, respectively. Managers should first establish an assessment system to regularly evaluate cognitive styles and maintain updated talent profiles incorporating these key traits, thereby enabling data-driven talent allocation. Based on the profiles, employees should be deliberately matched to tasks that fit their cognitive strengths: assign radical innovation tasks to highly intuitive employees, and allocate incremental optimization tasks to those with strong analytical styles. Furthermore, in highly creative functions such as R&D and design, forming teams that blend diverse cognitive styles can harness complementary advantages, ultimately maximizing the organization’s overall creative potential.
Limitations and further researchThis study has several limitations that offer directions for future research. First, despite employing a multi-wave survey design to mitigate common method bias (Podsakoff et al., 2012), the use of self-reported data still carries a risk of common method variance. Future research could strengthen the design by integrating multi-source data, such as constructing an objective digital transformation index from annual reports and patent data (Fang & Liu, 2024).
Second, the overall solution coverage of this study is relatively low. While this is a common phenomenon in fsQCA research, reflecting that configurational results can reveal multiple sufficient paths rather than covering all cases, it also suggests that there may be additional configurations influencing the formation of creativity. Future research could build on these findings by integrating complementary approaches, such as multi-level modeling or longitudinal case studies, to further validate and triangulate the identified configuration paths, thereby enhancing their robustness (Ho et al., 2016).
Finally, the generalizability of findings may be constrained by the focus on manufacturing firms at specific digital transformation stages. Future studies should validate and extend these results through cross-industry comparisons and by examining contextual factors such as digital maturity, organization size, and national culture.
CRediT authorship contribution statementYe Yang: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Conceptualization. Ling Yuan: Writing – review & editing, Supervision, Project administration, Funding acquisition. Songlin Yang: Writing – review & editing, Writing – original draft, Formal analysis, Conceptualization, Methodology. Ziyi Liu: Writing – review & editing, Writing – original draft, Formal analysis.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Beijing Natural Science Foundation (Grant Number. 9252013)
The National Social Science Fund of China (Grant Number. 23BGL051)
Ye Yang is a PhD candidate in the Business School of Hunan University, China. Her research interests focus on creativity, organizational behavior and knowledge management.
Ling Yuan (PhD) is a Professor in human resource management and labor relations in the Business School of Hunan University, China. His research interests focus on organizational behaviors of employee in China and labor relations in business sectors. Currently serves as the Director of the Institute of Corporate Performance Evaluation at Hunan University, a member of the Academic Committee of Hunan University, and a member of the Academic Committee of the Business School at Hunan University.
