Mindsets at work: unpacking the effects of work–care conflict and rumination on employee creativity - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Psychol . 2026 Mar 7;14:533. doi: 10.1186/s40359-026-04270-6 Search in PMC Search in PubMed View in NLM Catalog Add to search Mindsets at work: unpacking the effects of work–care conflict and rumination on employee creativity Liping Li Liping Li 1 Hospitality Business School, Sichuan Tourism University, #459 Hongling Road, Longquanyi District, Chengdu, 610100 China Find articles by Liping Li 1 , Yao Han Yao Han 1 Hospitality Business School, Sichuan Tourism University, #459 Hongling Road, Longquanyi District, Chengdu, 610100 China Find articles by Yao Han 1, ✉ , Ying Yang Ying Yang 1 Hospitality Business School, Sichuan Tourism University, #459 Hongling Road, Longquanyi District, Chengdu, 610100 China Find articles by Ying Yang 1 , Jun Yang Jun Yang 2 School of Economics & Management, Tongji University, Shanghai, China Find articles by Jun Yang 2 Author information Article notes Copyright and License information 1 Hospitality Business School, Sichuan Tourism University, #459 Hongling Road, Longquanyi District, Chengdu, 610100 China 2 School of Economics & Management, Tongji University, Shanghai, China ✉ Corresponding author. Received 2025 Sep 22; Accepted 2026 Feb 26; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13081245 PMID: 41795114 Abstract Purpose This study examines the mechanisms through which employee mindset influences creativity, analyzing the antecedent role of work-care conflict, the mediating effect of creative self-efficacy, and the moderating role of work-related rumination. Design/methodology/approach Using a two-wave time-lagged survey design, data were collected from 324 employee-supervisor dyads across five high-tech enterprises. Structural equation modeling was employed for data analysis. Findings Work interfering with caregiving negatively affects growth mindset while positively affecting fixed mindset. Caregiving interfering with work only negatively affects growth mindset. Creative self-efficacy mediates the relationship between both mindsets and creativity. Problem-solving pondering enhances the effect of growth mindset and buffers the negative impact of fixed mindset, while affective rumination weakens the effect of growth mindset. Originality/value Integrating Conservation of Resources Theory and Trait Activation Theory, this research reveals the dual-path mechanism through which work-care conflict influences creativity via mindset, and clarifies the distinct moderating effects of different forms of rumination. This research also provide practical guidance for organizations to mitigate the negative impact of work-care conflict, guide employees to engage in positive work-related rumination, and cultivate a growth mindset, thereby enhancing employee creative self-efficacy and creativity. Keywords: Mindset, Employee creativity, Work, Related rumination, Work, Care conflict, Creative self, Efficacy Introduction Mindsets are individuals’ beliefs and assumptions about how themselves, others, organizations, and the broader world function [ 18 ]. In contemporary workplaces, employees increasingly face work–care conflict (a tension between work demands and personal caregiving responsibilities) driven by demographic shifts, aging populations, and dual-career households. This conflict has become a critical stressor impacting employee well-being and performance [ 28 , 82 ]. As employees navigate such competing roles, their mindsets—key cognitive orientations—may be shaped in ways that influence creativity, a capability essential for organizations in the VUCA environment [ 6 ]. Against the backdrop of digital transformation, creativity has become increasingly crucial for organizations. Research on the relationship between creativity and corporate value creation indicates that among companies with higher creativity scores, two-thirds achieve above-average revenue growth, and 70% deliver above-average total shareholder returns [ 86 ]. Although mental models and mindsets have recently attracted scholarly attention, much of the research has remained at the theoretical level, focusing on definitions, functions, and classifications [ 15 ]. Only recently have scholars linked mindsets to creativity, showing they shape intrinsic motivation, knowledge integration, and persistence in creative endeavors [ 20 , 41 , 87 ]. Prior studies confirm mindset as a core cognitive driver of creative-related behaviors. Growth mindset promotes proactivity, and employees with this mindset are more likely to join cross-departmental innovation projects [ 25 , 42 ] and show greater persistence in creative challenges [ 20 ]. Managers with a growth mindset more frequently exhibit effective leadership behaviors, paving the way for innovation [ 37 ]. Fixed mindset, is linked to avoidance behaviors, such as rejecting creative tasks for fear of failure [ 57 ] and low willingness to learn new creative skills [ 41 ]. Mindsets also serve self-regulatory functions [ 52 , 74 ]. Long-term situational stress (like persistent work-care conflict) can trigger adaptive adjustments via resource depletion and cognitive restructuring [ 53 ], aligning with the “situational embedding model” of mindset evolution [ 47 ]. Even fixed creative mindset can reduce knowledge hiding and facilitate innovation in a suitable motivational climate [ 91 ]. Nevertheless, theoretical debate persists over whether traits like creativity are fixed or malleable, and how beliefs about these traits influence performance [ 51 ]. Implicit personality theory distinguishes fixed mindset (traits as unchangeable) from growth mindset (traits as malleable) [ 17 ]. While growth mindset generally facilitates creativity and fixed mindset inhibits it [ 57 ], the internal mechanisms linking mindset to creativity remain underexplored. Most research focuses on direct effects, with limited attention to mediating and moderating processes [ 39 , 57 ]. To address this gap, this study integrates trait activation theory and conservation of resources theory to propose an integrated model. We examine work–care conflict as an antecedent of mindset, creative self-efficacy as a mediator between mindset and creativity, and work-related rumination as a moderator. Work-related rumination includes problem-solving pondering (enhancing constructive cognitive processing; [ 83 ],) and affective rumination (undermining creativity; [ 35 , 90 ]). Using a two-wave time-lagged design, we collected data from 324 employee-supervisor dyads across five high-tech enterprises in Shanghai and Chengdu. Structural equation modeling (SEM) and bootstrap analysis were used for data analysis. Key theoretical contributions include: (1) Based on Trait Activation Theory, reveal the antecedent mechanism of work-care conflict as a situational cue to activate mindset, expanding the research on situational antecedents of mindset; (2) Based on Conservation of Resources Theory, reconstruct creative self-efficacy as a stress-sensitive resource, clarifying its resource transmission mechanism in the conflict-mindset-creativity chain; (3) Based on Dual-Process Cognitive Theory, distinguish the differential moderating effects of problem-solving pondering and affective rumination, establishing a boundary condition framework for the impact of mindset on creativity. The remainder of this paper is structured as follows: Sect. “ Conceptual background and hypothesis development : elaborates on theoretical background and research hypotheses; Sect. “ Research design ” introduces the research design; Sect. “ Data analysis and results ” presents data analysis results; Sect. “ Discussion and conclusion ” discusses theoretical implications, managerial implications, limitations, and future research directions; and the final section concludes the study. Conceptual background and hypothesis development The impact of work-care conflict on mindset Trait Activation Theory (TAT) offers a useful lens for understanding how external situations interact with individual traits to shape workplace behavior [ 77 , 78 ]. Building on the classic “nature versus nurture” debate [ 4 , 44 ], TAT emphasizes the dynamic interplay between person and situation, suggesting that traits are expressed when relevant situational cues are present. As mindset represent both intrinsic cognitive orientations and products of environmental influences, TAT provides a suitable framework to explore how workplace conditions—particularly work–care conflict—shape employees’ psychological patterns and creativity [ 47 ]. Mindset formation has long been studied from cognitive and developmental perspectives. Norman [ 56 ] describes mindset as personalized internal models shaped by experience, while Piaget highlights the joint influence of genetic predispositions and environmental learning [ 48 ]. Communication, education, and organizational settings all play crucial roles in reinforcing or modifying existing mindsets [ 53 , 58 ]. Thus, employees’ mindset are not static but evolve in response to contextual pressures [ 18 ]. This study focuses on the “short-term adaptive changes of mindset under stressful situations” rather than the fundamental transformation of long-term stable traits. Work–family conflict, defined as the tension arising from incompatible demands between work and family domains [ 3 ], is a well-established stressor that drains psychological and emotional resources [ 85 ]. Work-care conflict is a specific subtype of work-family conflict, which means responsibilities for child care or elder care compete with work obligations [ 82 ]. The core differences reflected in three aspects. First, Work-care conflict Focus on caregiving responsibilities with strong responsibility attributes such as childcare and eldercare, rather than general family demands such as housework and family socialization [ 13 ], Second, caregiving responsibilities are accompanied by higher emotional investment and moral responsibility, and the psychological pressure caused by them is significantly higher than that of general family demands [ 88 ]; (3) Time rigidity: The time windows of caregiving tasks (such as picking up and dropping off children, accompanying medical treatment) are fixed, making role conflict more difficult to alleviate through time management. The rising prevalence of dual-career households and demographic aging has intensified this tension, making it a pressing issue for employees across different life stages [ 36 ]. Work–care conflict is a situational stressor and manifests in two forms: work interfering with caregiving (WIC), when excessive work demands undermine caregiving duties; and caregiving interfering with work (CIW), when caregiving responsibilities disrupt work performance and recovery experiences [ 82 ]. Both forms create role overload and lead to negative spillovers across domains. Work-care conflict is more likely to trigger moral guilt(e.g., “failing to fulfill caregiving responsibilities”), and this emotional experience will strengthen the resource scarcity perception of fixed mindset [ 50 ]; Moreover, the continuity of caregiving responsibilities requires continuous emotional regulation, which is more likely to consume cognitive resources required for creativity than general family demands [ 2 ]. Research shows that such persistent conflicts reshape employees’ perceptions of themselves and their environments, altering motivational resources like creative self-efficacy [ 2 , 89 ]. According to Trait Activation Theory (TAT), situational cues that match individual trait relevance can trigger the expression of corresponding traits [ 77 , 78 ]. Work-care conflict serves as a critical situational cue in the workplace. Specifically, WIC creates a situational constraint where work demands occupy cognitive and emotional resources originally allocated to caregiving. This constraint activates the ‘resource scarcity trait’ in individuals, thereby reducing their belief in the malleability of abilities (growth mindset) and strengthening the belief in fixed abilities (fixed mindset). In contrast, CIW disrupts work rhythm and task completion, activating the ‘environmental adaptability trait’—individuals facing such interference tend to doubt their ability to adjust to dual roles, thus weakening growth mindset and strengthening the belief in fixed abilities (fixed mindset). Besides, From an implicit theory perspective, mindset act as self-regulatory systems that guide cognition and behavior. Exposure to high levels of work–care conflict can therefore reinforce fixed mindset—emphasizing constraints and limitations—while undermining growth mindset, which thrives on adaptability and learning [ 50 , 62 ]. Implicit Theory emphasizes that individuals’ implicit beliefs (mindset) guide their interpretation of external situations [ 17 ], while TAT focuses on how situational cues (work-care conflict) activate trait expression [ 77 ]. The integration of the two theories reveals a situation-belief-behavior chain: Work-care conflict (situational cue, TAT) interacts with individuals’ implicit beliefs about ability malleability (Implicit Theory) to shape mindset. Specifically, when facing WIC, individuals with a strong implicit belief in ability malleability (growth-oriented inherent trait) may view the conflict as a temporary challenge and maintain growth mindset; in contrast, individuals with a weak implicit belief in ability malleability (fixed-oriented inherent trait) are more likely to perceive the conflict as a resource constraint, thus shifting to fixed mindset [ 24 ]. This integration clarifies that mindset is not only an inherent belief (Implicit Theory) but also a trait expression triggered by situational cues (TAT). In sum, work–care conflict, by consuming scarce cognitive and emotional resources, exerts significant influence on employees’ mindset. The two dimensions—WIC and CIW—are expected to differentially relate to growth and fixed orientations. Thus, we propose: H1: Work–care conflict significantly influences mindset. H1a: Work interfering with caregiving (WIC) negatively relates to growth mindset. H1b: WIC positively relates to fixed mindset. H1c: Caregiving interfering with work (CIW) negatively relates to growth mindset. H1d: CIW positively relates to fixed mindset. The effect of mindset on creative self-efficacy and employee creativity Employee creativity often involves high uncertainty and requires sustained intrinsic motivation [ 55 ]. A key factor enabling such motivation is creative self-efficacy, or the belief in one’s ability to produce creative outcomes [ 66 ]. Creative self-efficacy is a belief in one’s ability to produce creative outcomes, and a mediating resource linking mindset to creativity [ 79 ]. While, it’s a “stress-sensitive psychological resource” rather than a general mediating variable [ 5 , 46 ]. It fosters persistence in problem-solving, encourages risk-taking and novel idea generation, and enhances sensitivity to innovative environments [ 64 ]. While leadership and work conditions shape creative self-efficacy less attention has been paid to internal cognitive dispositions such as mindset. A growth mindset enables individuals to regulate their thoughts, emotions, and behaviors more effectively, thereby enhancing domain-specific self-efficacy [ 69 , 80 ]. In contrast, a fixed mindset often reduces intrinsic motivation, limiting creative engagement to existing frameworks. Empirical studies generally confirm the positive link between growth mindset and creative self-efficacy [ 26 , 65 ], though findings on fixed mindset remain mixed. Some evidence suggests a negative association, as resource-constrained individuals avoid risk and become trapped in a loss spiral that inhibits creativity [ 26 ]. Others find no significant relationship, implying that fixed mindset may weaken rather than fully block creative self-efficacy [ 43 , 73 ]. H2: Mindset significantly influences creative self-efficacy. H2a: Growth mindset positively predicts creative self-efficacy. H2b: Fixed mindset negatively predicts creative self-efficacy. Conservation of Resources (COR) theory provides further insight. Resources—such as personal characteristics, energies, and conditions—are crucial for managing stress and sustaining performance [ 23 , 27 ]. A growth mindset functions as a positive resource that promotes resilience, learning from failure, and resource accumulation [ 1 ]. Conversely, a fixed mindset represents a state of resource scarcity, leading individuals to conserve energy, avoid risk, and reduce creative engagement [ 32 , 72 ]. Thus, mindset not only directly influences creativity but also operates through creative self-efficacy as a resource mechanism. In summary, growth mindset enhances creative self-efficacy by fostering confidence, persistence, and adaptability, which in turn promote employee creativity. Fixed mindset, by contrast, is expected to weaken creative self-efficacy and thereby hinder creativity, though the strength of this effect may vary across contexts. Creative self-efficacy thus mediates the relationship between mindset and creativity. Based on this reasoning, we propose: H3: Creative self-efficacy mediates the relationship between mindset and employee creativity H3a: Creative self-efficacy mediates the negative relationship between growth mindset and employee creativity. H3b: Creative self-efficacy mediates the negative relationship between fixed mindset and employee creativity. The moderating effect of work-related rumination on the relationship between mindset and creativity Work-related rumination, first proposed by Cropley and Zijlstra [ 14 ] as repetitive work-related thoughts, is not exclusively negative—while high stress-related rumination impairs sleep and well-being [ 49 ], it can also involve problem-solving or goal-pursuit that boosts satisfaction and performance [ 38 ]. Adopting Syrek and Antoni’s [ 75 ] Goal Progress Theory-based definition (deliberate, off-work recurring thoughts with positive/negative content), this study conceptualizes it as a post-work cognitive process. Work-related rumination can be conceptualized along two dimensions [ 68 ]. Affective rumination involves intrusive, negative thoughts focused on emotional stressors, undermining creative self-efficacy and suppressing creativity. Empirical evidence shows it negatively predicts work engagement and creativity, and positively predicts burnout, with effects persisting for up to two years [ 34 , 35 , 90 ]. Conversely, problem-solving pondering entails reflective examination of work challenges, exploring alternative solutions, and generating creative ideas, yielding positive emotions and enhancing creativity [ 7 , 83 , 90 ]. Its benefits are also temporally stable, positively affecting creativity and engagement over extended periods [ 35 ]. Although its two dimensions have different functions, they uniformly serve the moderating mechanism of mindset influencing creative self-efficacy. Affective rumination is a passive, emotion-focused cognitive depletion mechanism, manifested as repeated thinking about negative emotions caused by work-care conflict; problem-solving pondering is an active, goal-focused cognitive gain mechanism, manifested as reflection and optimization of conflict coping strategies [ 30 , 61 ]. Given most individuals experience both types concurrently, their underlying mechanisms and boundary conditions warrant investigation. Mindset improvement has been extensively explored in management research [ 70 , 84 ], and the Persistent Cognition Model provides theoretical support for the differential effects of work-related rumination [ 9 ]. As intrusive negative thinking, affective rumination (AR) may, on the one hand, consume cognitive resources and lead to self-regulation failure, hindering the conversion of growth mindset into creative self-efficacy [ 30 ]. On the other hand, it may amplify the perception of role failure and activate ego threat, causing individuals with a growth mindset to doubt their ability to cope with dual roles [ 38 ]. Thus, AR is hypothesized to weaken the positive effect of growth mindset on creative self-efficacy. Meanwhile, AR may further exacerbate resource depletion and negative emotional experiences, thereby strengthening the inhibitory effect of fixed mindset on creative self-efficacy. In contrast, problem-solving pondering (PSP) is goal-directed and does not trigger excessive physiological activation [ 14 , 19 , 30 ]. It can not only help individuals with a growth mindset focus on creative strategies by enhancing attentional control [ 19 ] but also supplement psychological resources through generating positive emotions [ 83 ], thereby strengthening its positive effect on creative self-efficacy. For individuals with a fixed mindset, PSP encourages them to explore alternative solutions, leading them to view ability limitations as temporary states that can be improved through strategic adjustments [ 14 ]. Consequently, PSP may weaken the negative impact of fixed mindset on creative self-efficacy. Thus, affective rumination impairs recovery and creativity, whereas problem-solving pondering supports them [ 61 , 67 , 81 ]. Based on the above reasoning, we hypothesize: H4: Work-related rumination moderates the relationship between mindset and creative self-efficacy, and thus the effect of mindset on employee creativity. H4a: Problem-solving pondering strengthens the positive effect of growth mindset on creative self-efficacy, thereby enhancing employee creativity. H4b: Problem-solving pondering weakens the negative effect of fixed mindset on creative self-efficacy, thereby mitigating its impact on employee creativity. H4c: Affective rumination weakens the positive effect of growth mindset on creative self-efficacy, thereby reducing its impact on employee creativity. H4d: Affective rumination strengthens the negative effect of fixed mindset on creative self-efficacy, thereby intensifying its impact on employee creativity. In summary, the theoretical model of this study is shown in Fig. 1 . Fig. 1. Open in a new tab Theoretical model Research design Data collection and sample profile This study employed a supervisor-subordinate matched-pair design with a two-wave time-lagged approach (two-week interval) to mitigate common method bias. Data were collected from core departments (e.g., design and R&D) of five high-tech companies located in Shanghai and Chengdu, China. Through collaboration with company management, we ensured smooth implementation of the survey process. In the first phase, 350 questionnaires were distributed to employees in core departments, primarily measuring demographic variables, work-family conflict, time pressure, and perceived organizational support, with 331 valid responses returned. Two weeks later, in the second phase, the same employees were surveyed on variables including work-related rumination and creative self-efficacy, while their direct supervisors were invited to evaluate these employees’ creativity. All questionnaires were returned in this phase with no attrition. All employee questionnaires were completed anonymously in the absence of their immediate supervisors to ensure response authenticity. Supervisor evaluations were conducted using an independent coding system to ensure rating accuracy and precise matching with corresponding employee questionnaires.In the first round, 350 questionnaires were distributed, and 331 were collected, resulting in a loss rate of 5.4%. There were no questionnaire losses in the second round. After all the questionnaires were collected, we paired them according to the codes and eliminated any invalid questionnaires. Ultimately, we obtained 324 valid questionnaires, resulting in a response rate of 92.6%. The final sample of 324 employees was diverse: 58.3% were female; the majority (83.3%) were between 26 and 40 years old; nearly all (94.4%) held a bachelor’s degree or higher; and most (81.8%) had over 3 years of work tenure. Measurement tools All constructs were measured using established scales on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). We followed a rigorous translation-back-translation procedure [ 8 ] to adapt the scales into Chinese. Work-care conflict A 10-item scale from Netemeyer et al. [ 54 ] and Carlson and Frone [ 12 ] was used, which adapted and recombined with recent researches on work-care conflict [ 33 , 82 ]. With 5 items each for work interfering with caregiving (WIC; e.g., “My work hours make it difficult for me to meet my caregiving responsibilities”) and caregiving interfering with work (CIW; e.g., “Caregiving demands interfere with my work activities”). Cronbach’s α of WIC is 0.922, and 0.876 for CIW. Mindset Dweck’s [ 17 ] 8-item scale measured growth (4 items, e.g., “No matter who I am, I can significantly change my level of creativity”) and fixed (4 items, e.g., “My creativity is something I cannot change”) mindsets. Cronbach’s α of growth mindset is 0.920, and 0.927 for fixed mindset. Work-related rumination Cropley & Zijlstra [ 14 ] 10-item scale assessed affective rumination (5 items, e.g., “I feel tense thinking about work-related issues”) and problem-solving pondering (5 items, e.g., “I think about how to improve my job performance”). Cronbach’s α of Affective rumination is 0.899, and 0.813 for problem-solving pondering, Creative self-efficacy A 3-item scale by Tierney and Farmer [ 79 ] was used (e.g., “I believe I can solve problems creatively”). Cronbach’s α is 0.724. Creativity Supervisors rated employee creativity using Farmer et al.’s [ 21 ] 4-item scale (e.g., “This employee seeks new ideas and ways to solve problems”). It’s not a measure of “general creativity,” but focuses on context-specific creative behaviors in the workplace. Cronbach’s α is 0.720. Control variables We controlled for gender, age, education, work tenure, and annual income, which are commonly included in creativity research. Analytical strategy Data analysis will proceed in three stages. First, we will assess the measurement model’s reliability and validity using confirmatory factor analysis (CFA). Second, we will examine descriptive statistics and bivariate correlations. Finally, we will test our hypothesized model—including direct, mediating, and moderating effects—using structural equation modeling (SEM) or hierarchical regression analysis, with bootstrapping for indirect effects. Based on the theory-driven principle, this study selects control variables, focusing on demographic characteristics that may simultaneously affect the ‘caregiving demand-mindset-creativity’ chain, to exclude irrelevant interference and improve the accuracy of causal inference. Data analysis and results Confirmatory factor analysis and discriminant validity We conducted confirmatory factor analysis (CFA) to examine the discriminant validity of our eight key constructs: work interfering with caregiving (WIC), caregiving interfering with work (CIW), growth mindset (GM), fixed mindset (FM), problem-solving pondering (PSP), affective rumination (AR), creative self-efficacy (CSE), and creativity (EC). A series of nested models were tested and compared against our hypothesized eight-factor model, in which all constructs were distinct. As shown in Table 3 , the eight-factor model demonstrated a superior fit to the data (χ 2 /df = 1.785, CFI = 0.916, TLI = 0.906, RMSEA = 0.063, SRMR = 0.053), with all indices meeting acceptable thresholds [ 93 ]. This model fit significantly better than all alternative models, including a single-factor model (Δχ 2 highly significant), providing strong evidence for the discriminant validity of the constructs used in this study. Table 3. The mediating effect coefficients Mediating path Effect SE T value P value LLCI 95% ULCI 95% GM → CSE → EC 0.169 0.070 2.416 0.016 0.053 0.330 FM → CSE → EC 0.147 0.051 0.925 0.355 −0.173 −0.032 Open in a new tab Abbreviation meaning: same as Table 1 Common method bias Following Podsakoff et al. [ 63 ], we employed both procedural and statistical remedies to mitigate common method bias. Procedurally, we collected data from two sources (employees and their supervisors) at two different time points and ensured respondent anonymity. Statistically, we used the unmeasured latent method factor technique. A common method factor was added to the eight-factor model, creating a nine-factor model. The fit results were χ2 = 3099.127, df = 562, RMSEA = 0.059, CFI = 0.908, TLI = 0.903, SRMR = 0.051. The results showed no significant improvement in model fit (ΔCFI/TLI < 0.02, with slight decreases; RMSEA = 0.059, SRMR = 0.051). This indicates that common method bias is not a serious concern in this study. Descriptive statistics and correlation Table 1 presents the descriptive statistics and intercorrelations for all study variables. The results reveal several significant correlations that provide preliminary support for our hypotheses. Table 1. Descriptive statistics and correlation analysis Variables M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 Age 2.505 0.789 1 Gender 0.695 0.462 −0.044 1 Education 3.060 0.421 −0.107 0.120 1 Years of employee 2.710 0.830 0.784*** −0.153* −0.036 1 Annual Incomes 1.965 0.660 0.237*** −0.052 0.261*** 0.330*** 1 WIC 2.583 1.259 −0.204** 0.102 −0.091 −0.214** −0.192** 1 CIW 2.278 0.983 −0.182** 0.088 −0.116 −0.164* −0.288*** 0.816*** 1 GM 5.099 1.311 0.254*** −0.048 0.126 0.233*** 0.159* −0.311*** −0.185** 1 FM 2.759 1.440 −0.170* −0.011 −0.212** −0.152* −0.173* 0.269*** 0.159 −0.909*** 1 PSP 5.697 0.806 0.247*** 0.048 0.104 0.248*** 0.120 −0.432*** −0.301*** 0.312*** −0.287*** 1 AR 2.468 1.091 −0.177* 0.059 −0.075 −0.203** −0.172* 0.714*** 0.622*** −0.214** 0.178* −0.352*** 1 CSE 5.776 0.719 0.231*** −0.067 0.144* 0.242*** 0.222** −0.563*** −0.435*** 0.390*** −0.297*** 0.549*** −0.492*** 1 EC 5.437 0.844 0.097 −0.061 0.147* 0.098 0.214** −0.505*** −0.440*** 0.261*** −0.199** 0.425*** −0.411*** 0.650*** 1 Open in a new tab N = 324; Two-tailed test WIC Work interfering with caregiving, CIW Caregiving interfering with Work, GM Growth mindset, FM Fixed mindset, PSP Problem-solving pondering, AR Affective rumination, CSE Creative self-efficiency, EC Employee creativity *p <0.05 ；** p<0.01 ；***p <0.001 As shown, work interference with caregiving (WIC) was negatively correlated with a growth mindset (GM) ( r = −0.311, p < 0.01) and positively correlated with a fixed mindset (FM) ( r = 0.269, p < 0.01). Conversely, caregiving interference with work (CIW) was negatively correlated with a growth mindset ( r = −0.185, p < 0.01) but was not significantly correlated with a fixed mindset. Furthermore, creative self-efficacy (CSE) was positively correlated with a growth mindset ( r = 0.390, p < 0.01) and negatively correlated with a fixed mindset ( r = −0.297, p < 0.01). Finally, creative self-efficacy showed a strong positive correlation with employee creativity (EC) ( r = 0.650, p < 0.01). Hypothesis testing We examined the hypothesized relationships using regression analysis. The results, presented in Table 2 , support several of our proposed paths. Table 2. Path coefficients of structural equation model Dependent variable Independent variable Coefficient Standard Deviation T value P value GM WIC −0.497 0.102 −4.877 0.000 CIW −0.272 0.138 1.966 0.049 FM WIC 0.477 0.130 3.673 0.000 CIW 0.265 0.162 −1.634 0.102 CSE GM 0.222 0.085 2.602 0.009 FM −0.162 0.064 0.964 0.035 PSP 0.364 0.138 2.637 0.008 AR −0.127 0.050 −2.531 0.011 GM × PSP 0.328 0.129 −2.550 0.011 FM × PSP −0.249 0.138 −1.808 0.047 GM × AR −0.122 0.091 −1.330 0.009 FM × AR 0.231 0.085 −2.706 0.093 EC CSE 0.763 0.081 9.399 0.000 Open in a new tab Abbreviation meaning: same as Table 1 Regarding the direct effects, work interference with caregiving (WIC) negatively influenced a growth mindset (GM) (β = −0.497, p < 0.001) and positively influenced a fixed mindset (FM) (β = 0.477, p < 0.001). Caregiving interference with work (CIW) also negatively impacted a growth mindset (β = −0.272, p < 0.05), but its effect on a fixed mindset was not significant. As predicted, a growth mindset positively affected creative self-efficacy (CSE) (β = 0.222, p < 0.01), while a fixed mindset had a negative impact (β = −0.162, p < 0.05). For the moderating effects, problem-solving pondering (PSP) positively moderated the relationship between a growth mindset and CSE (β = 0.328, p < 0.05) and also moderated the link between a fixed mindset and CSE (β = −0.249, p < 0.05). Conversely, affective rumination (AR) negatively moderated the relationship between a growth mindset and CSE (β = −0.122, p < 0.01), but its moderating effect on the fixed mindset-CSE link was not significant. H1d was not supported. Finally, creative self-efficacy was a strong positive predictor of employee creativity (β = 0.763, p < 0.001). To test the mediating role of creative self-efficacy, we conducted a bootstrap analysis. The results in Table 3 show a significant indirect effect of a growth mindset on creativity via CSE (effect = 0.169, 95% CI [0.053, 0.330]). The indirect effect of a fixed mindset on creativity via CSE was also significant (effect = −0.147, 95% CI [−0.173, −0.032]). This confirms that creative self-efficacy is a significant mediator in both paths. The bootstrap analysis in Mplus 8 (see Table 4 ) confirmed the moderating effects. Problem-solving pondering (PSP) significantly moderated the relationship between growth mindset (GM) and creative self-efficacy (CSE) (95% CI [−1.036, −0.061]) and between fixed mindset (FM) and CSE (95% CI [−0.937, −0.152]). Affective rumination (AR) significantly moderated the GM-CSE relationship (95% CI [−0.592, −0.036]), but its moderating effect on the FM-CSE link was not significant (95% CI [−0.762, 0.074]). The moderating effects are further visualized in the simple slope plots below (see Fig. 2 ), which intuitively depict the differing strength and direction of the relationships between mindset and CSE under high and low levels of PSP and AR. Table 4. The moderating effect coefficients Moderating path Level Coefficients SD T value P value LLCI 95% ULCI 95% PSP moderating GM → CSE Low −0.106 0.162 −0.653 0.514 −0.417 0.229 High 0.549 0.146 3.773 0.000 0.255 0.784 Difference 0.655 0.257 −2.550 0.011 −1.036 −0.061 PSP moderating FM → CSE Low 0.311 0.143 2.180 0.029 −0.030 0.524 High −0.188 0.161 −1.165 0.244 −0.482 −0.167 Difference −0.499 0.276 −1.808 0.071 −0.937 −0.152 AR moderating GM → CSE Low 0.343 0.094 3.669 0.000 0.163 0.533 High 0.100 0.150 0.667 0.505 −0.181 0.401 Difference −0.243 0.183 −1.330 0.184 −0.592 −0.036 AR moderating FM → CSE Low −0.170 0.124 −1.362 0.173 −0.370 0.139 High 0.293 0.086 3.414 0.001 0.130 0.466 Difference 0.463 0.171 −2.706 0.007 −0.762 0.074 Open in a new tab Abbreviation meaning: same as Table 1 Fig. 2. Open in a new tab Simple slope plots of the moderating effects Results from the moderated mediation analysis (Table 5 ) indicated a significant moderating effect of problem-solving pondering on the mediation path through creative self-efficacy for both growth mindset (index =, 95% CI [−0.795, −0.062]) and fixed mindset (index =, 95% CI [−0.719, −0.127]). Affective rumination also significantly moderated the mediation for growth mindset (index =, 95% CI [−0.445, −0.114]), but its effect on the fixed mindset path was non-significant (index =, 95% CI [−0.578, 0.076]). H4d was not supported. As shown in the following simple slope graph (see Fig. 3 ), it can be further intuitively observed that under high and low levels of PSP and AR, the influence of mindset on employees’ creativity through creativity self-efficacy shows different intensifies and directions. Table 5. Moderated mediating effect coefficients Moderated mediating path Level Coefficients SD T value P value LLCI 95% ULCI 95% PSP moderating GM → CSE → EC Low −0.081 0.123 −0.655 0.512 −0.306 0.184 High 0.419 0.115 3.630 0.000 0.206 0.625 Difference 0.500 0.194 −2.581 0.010 −0.795 −0.062 PSP moderating FM → CSE → EC Low 0.238 0.111 2.133 0.033 −0.025 0.422 High −0.143 0.122 −1.176 0.240 −0.357 0.132 Difference −0.381 0.210 −1.814 0.070 −0.719 −0.127 AR moderating GM → CSE → EC Low 0.262 0.072 3.658 0.000 0.138 0.423 High 0.076 0.118 0.647 0.518 −0.134 0.329 Difference −0.186 0.136 −1.364 0.172 −0.445 −0.114 AR moderating FM → CSE → EC Low −0.129 0.093 −1.395 0.163 −0.273 0.113 High 0.224 0.066 3.415 0.001 0.107 0.355 Difference 0.353 0.124 −2.848 0.004 −0.578 0.076 Open in a new tab Abbreviation meaning: same as Table 1 Fig. 3. Open in a new tab Simple slope plots of the moderated mediation effects Results Based on 324 valid supervisor-subordinate dyads and drawing on Conservation of Resources and Trait Activation Theories, this study investigated the mechanism between employee mindset and creativity. The results show that work interference with caregiving negatively influences a growth mindset but positively influences a fixed mindset. Caregiving interference with work negatively affects a growth mindset, but its effect on a fixed mindset is not significant. A growth mindset promotes creative self-efficacy, whereas a fixed mindset undermines it. Furthermore, problem-solving pondering amplifies the positive effect of a growth mindset and buffers the negative effect of a fixed mindset on creative self-efficacy. Affective rumination weakens the positive effect of a growth mindset but does not significantly exacerbate the negative effect of a fixed mindset. Finally, creative self-efficacy mediates the relationship between both mindsets and employee creativity. All hypotheses were supported except H1d and H4d. Discussion and conclusion Main findings This study systematically explores the mechanism of work-care conflict influencing employee creativity through mindset, with creative self-efficacy as a mediator and work-related rumination as a moderator. The main findings are as follows: Work-care conflict has a differential impact on mindset: Work interfering with caregiving (WIC) significantly negatively affects growth mindset (β = −0.497, p < 0.001) and positively affects fixed mindset (β = 0.477, p < 0.001); caregiving interfering with work (CIW) only significantly negatively affects growth mindset (β = −0.272, p < 0.05), and its positive impact on fixed mindset is not significant (β = 0.265, p > 0.05). H1d is not supported, which may be attributed to the different nature of WIC and CIW. WIC (work interfering with caregiving) is often perceived as a long-term, uncontrollable stressor (e.g., permanent overtime due to project demands), which strengthens individuals’ belief that their ability to balance roles is fixed (fixed mindset) [ 92 ]. In contrast, CIW (caregiving interfering with work) is more likely to be viewed as a temporary, controllable constraint (e.g., short-term child illness or elderly parent care), which only weakens individuals’ confidence in adjusting to dual roles (growth mindset) but does not trigger the perception of fixed ability [ 50 ]. Additionally, correlation analysis shows that CIW has a lower correlation with fixed mindset ( r = 0.159, p > 0.05) compared to WIC ( r = 0.269, p < 0.01), further confirming that CIW does not significantly shape fixed mindset. Mindset affects employee creativity through creative self-efficacy. Growth mindset significantly positively predicts creative self-efficacy (β = 0.222, p < 0.01), and fixed mindset significantly negatively predicts creative self-efficacy (β = −0.162, p < 0.05); creative self-efficacy further significantly positively predicts employee creativity (β = 0.763, p < 0.001). Bootstrap analysis confirms that creative self-efficacy mediates the relationship between growth mindset and creativity (effect = 0.169, 95% CI [0.053, 0.330]) and between fixed mindset and creativity (effect = −0.147, 95% CI [−0.173, −0.032]). Work-related rumination plays a dual moderating role. Problem-solving pondering (PSP) strengthens the positive effect of growth mindset on creative self-efficacy (β = 0.328, p < 0.05) and weakens the negative effect of fixed mindset on creative self-efficacy (β = −0.249, p < 0.05); affective rumination (AR) weakens the positive effect of growth mindset on creative self-efficacy (β = −0.122, p < 0.01), but its role in strengthening the negative effect of fixed mindset on creative self-efficacy is not significant (β = 0.231, p > 0.05). H4d is not supported, possibly due to the resource ceiling effect. Fixed mindset itself leads to severe depletion of psychological resources (e.g., low confidence in creative ability), and affective rumination (which further consumes resources) does not produce an additional amplification effect on the negative impact of fixed mindset (COR Theory; [ 23 ]). Specifically, when individuals have a fixed mindset, their creative self-efficacy is already at a low level; even if affective rumination increases, the space for further reducing creative self-efficacy is limited. This is consistent with prior research that the moderating effect of rumination is more significant for positive cognitive states (e.g., growth mindset) than for negative cognitive states (e.g., fixed mindset) [ 90 ]. Additionally, the interaction coefficient of FM × AR is positive but non-significant (β = 0.231, p > 0.05), indicating that affective rumination may have a weak tendency to strengthen the negative effect, but this tendency is not statistically significant due to the resource ceiling. Theoretical implications This study offers a systematic examination of the relationship between mindset and employee creativity by integrating the COR Theory, TAT, and Implicit Personality Theory. The theoretical contributions are structured into three core dimensions (expansion of antecedent mechanisms, reconstruction of mediating mechanisms, and deepening of boundary conditions), clarifying the study’s advancements in the existing literature. First, expansion of antecedent mechanisms by revealing the situational activation path of mindset under work-care conflict. Prior research on mindset antecedents has primarily focused on individual inherent traits or long-term developmental experiences [ 18 , 53 ], with limited attention to how short-term situational stressors shape mindset dynamics. This study fills this gap by anchoring on Trait Activation Theory (TAT) and Implicit Personality Theory, identifying work-care conflict (a caregiving-specific subtype of work-family conflict with unique attributes of strong responsibility binding, high emotional investment, and time rigidity) as a critical situational cue for mindset adjustments. Work interfering with caregiving (WIC) activates the “resource scarcity trait,” reducing growth mindset and strengthening fixed mindset, while caregiving interfering with work (CIW) activates the “environmental adaptability trait,” primarily weakening growth mindset. The integration of TAT and Implicit Personality Theory constructs a “situation-belief-behavior” chain, where work-care conflict interacts with individuals’ implicit beliefs about ability malleability to shape mindset as a dynamic trait expression rather than a static inherent belief, expanding the situational antecedent research of mindset and enriching the “situational embedding model” of mindset evolution [ 47 ] by demonstrating that even relatively stable cognitive orientations can undergo short-term adaptive changes under targeted situational stress. Second, Reconstruction of mediating mechanisms by positioning creative self-efficacy as a stress-sensitive psychological resource. Existing studies generally treat creative self-efficacy as a general mediating variable between mindset and creativity [ 69 ], overlooking its contextual sensitivity in stressful scenarios. This study reconstructs its theoretical role based on Conservation of Resources (COR) Theory, redefining it as a stress-sensitive psychological resource that dynamically responds to the interaction of work-care conflict, mindset, and rumination. As a core resource transmission carrier in the “conflict-mindset-creativity” path, it is enhanced by growth mindset (which promotes resource accumulation) and undermined by fixed mindset (which leads to resource depletion), and further regulated by work-related rumination. Problem-solving pondering supplements psychological resources to strengthen its mediating role, while affective rumination consumes resources to weaken it. This reconstruction breaks through the static understanding of creative self-efficacy in prior research, clarifying its dual attributes of resource transmission and stress response in complex situational contexts. It also enrich the application of COR Theory in creativity research by revealing how psychological resources operate dynamically in the interplay of stressors and cognitive orientations. Third, Deepening of boundary conditions by establishing a dual-path moderation model of work-related rumination. Prior studies on the boundary conditions of the mindset-creativity relationship have mostly focused on organizational context or leadership styles [ 37 , 42 ], with insufficient attention to individual cognitive processing mechanisms. This study distinguishes the differential moderating effects of the two dimensions of work-related rumination to construct a refined boundary condition framework. Problem-solving pondering (PSP) acts as an active cognitive gain mechanism that enhances attentional control and generates positive emotions to supplement psychological resources for individuals with a growth mindset [ 19 ] and encourages those with a fixed mindset to view ability limitations as temporary [ 91 ], reducing negative impacts on creative self-efficacy; in contrast, affective rumination (AR) serves as a passive cognitive depletion mechanism that consumes cognitive resources and activates ego threat, weakening the positive effect of growth mindset on creative self-efficacy [ 30 , 38 ], while its amplification effect on fixed mindset is constrained by the resource ceiling effect. This dual-path moderation model clarifies the heterogeneous regulatory roles of different cognitive processing modes, responding to the call for in-depth exploration of “how mindset influences creativity under different cognitive states” [ 90 ] and enriching the understanding of boundary conditions in the mindset-creativity relationship, thereby providing a theoretical basis for guiding individuals to adopt adaptive cognitive strategies to enhance creative performance. Managerial implications This study offers practical guidance for managers seeking to support employees in managing work–care conflict and work-related rumination, thereby enhancing mindset, creative self-efficacy, and overall creativity. Firstly, employees can mitigate the negative effects of work–family conflict by fostering a growth mindset and engaging in problem-solving pondering rather than affective rumination. Cultivating positive emotions through proactive reflection, continuous learning, and resilience-building can enhance self-efficacy and facilitate creative problem-solving [ 40 ]. In addition, employees experiencing negative emotions should actively employ stress regulation strategies, seek organizational or professional support, and engage in self-transcendence practices, all of which promote psychological health and creative thinking. Secondly, managers play a critical role in shaping employees’ cognitive and emotional responses to stress. They should encourage employees to focus on problem-solving, foster positive rumination, and reduce the prevalence of affective rumination. Practical measures include guiding employees to recognize opportunities for growth amid challenges, creating a relaxed and supportive work environment, and monitoring rumination patterns, especially among quieter or more passive staff. Proactive interventions, such as offering psychological support or coaching for employees experiencing persistent negative rumination, can help maintain confidence and reduce the psychological burden [ 16 ]. Thirdly, For the non-significant effect of CIW on fixed mindset, organizations can provide temporary care support (e.g., emergency care leave, on-site childcare services) to help employees perceive CIW as controllable, thereby preventing the transition from temporary role stress to fixed mindset. For the non-significant moderating effect of affective rumination on fixed mindset, managers should focus on early intervention for employees with a fixed mindset—providing targeted creativity training and positive feedback to improve their creative self-efficacy before resource depletion reaches a ceiling. Furthermore, organizations should cultivate an open, inclusive, and psychologically safe culture that encourages employees to seek support and utilize available resources. Strategies include adjusting workloads and performance expectations, providing mindfulness or stress-reduction training, and promoting active collaboration and help-seeking behaviors. These interventions can reduce the negative impact of stress and affective rumination, enhance self-efficacy, and create a conducive environment for innovation. Furthermore, organizations should cultivate an open, inclusive, and psychologically safe culture that encourages employees to seek support and utilize available resources. Strategies include adjusting workloads and performance expectations, providing mindfulness or stress-reduction training, and promoting active collaboration and help-seeking behaviors. Organizations also should provide differentiated support based on employees’ caregiving types (e.g., flexible working hours for employees with childcare responsibilities, emergency care leave for employees with eldercare responsibilities), further highlighting the practical value of conceptual distinction. These interventions and supports can reduce the negative impact of stress and affective rumination, enhance self-efficacy, and create a conducive environment for innovation. Limitations and future research This study has several limitations that also point to directions for future research. First, regarding the research design, the cross-sectional assessment of work-related rumination fails to capture its dynamic nature, as rumination fluctuates with work pressures and personal events. While the two-wave time-lagged design initially mitigates common method bias, it struggles to fully separate temporal effects from short-term fluctuations. Future research could adopt a three-wave design (T1: mindset and demographic variables; T2: work-care conflict and work-related rumination; T3: creative self-efficacy and employee creativity) to clarify the temporal sequence of variables, or use longitudinal, daily diary, or experience-sampling methods [ 22 ] to more accurately track rumination patterns and strengthen causal inferences. A more rigorous approach entails differentiating care demand types (e.g., childcare vs. eldercare), intensity (daily duration, task complexity), and interruptions’ predictability (frequency of unexpected events)—factors that may impact cognitive depletion, rumination, and self-efficacy, as well as cognitive states and creative performance, through distinct resource depletion paths. Future research will therefore incorporate these dimensions into questionnaire design to precisely measure caregiving types (childcare/eldercare/others), intensity, and predictability, thereby uncovering heterogeneous mechanisms across caregiving scenarios and refining the work-care conflict-creativity relationship model. Second, in terms of variable coverage, this study focuses on cognitive-level mediators and moderators but overlooks unobserved factors such as individual stress coping styles or personality traits, which may also influence the relationships among mindset, creative self-efficacy, and employee creativity [ 29 ]. Controlling for these variables in future research could refine the understanding of core mechanisms. Third, regarding the scope of analysis, the research primarily examines individual-level growth and fixed mindsets, with insufficient exploration of team-level collective mindsets, shared cognitive frameworks, and interaction processes—collective mindsets may shape employee creativity through distinct pathways. Additionally, the characteristics and effects of mindset across different employee populations (e.g., varying job types, roles, and cultural contexts) remain underexplored. Cross-cultural studies could clarify whether and how the impact of mindset on creativity differs across organizational and national contexts [ 57 , 76 ], and future research could use domain-specific scales (e.g., creative mindset scales [ 31 ]) to further verify the model. Fourth, in terms of measurement tools, while the supervisor-rated creativity scale effectively captures practically validated workplace creative behaviors (integrating feasibility, value, and novelty—core dimensions hard to cover by single objective indicators; [ 21 ]), it lacks objective output indicators (e.g., number of patents, adopted innovation proposals). Future research could supplement such objective data to verify the model’s cross-measurement robustness. Fifth, methodologically, emerging neural and cognitive research offers new avenues. Techniques like EEG, MRI, and human–computer interaction paradigms can elucidate how growth and fixed mindsets differentially influence cognitive control, emotion regulation, and creative processes [ 71 ]. Indirect measures (e.g., projective or behavioral assessments; [ 60 ]) can complement self-report data to capture subtle or implicit cognitive patterns. Finally, regarding practical interventions, while growth mindset interventions have been shown to enhance creativity and related outcomes [ 10 , 11 ], their long-term effectiveness is uncertain due to potential mindset reversion [ 59 ]. Future studies should examine the duration, frequency, and mechanisms of interventions to foster enduring benefits. Additionally, exploring mediating and moderating mechanisms within the Inputs–Processes–Outputs (IPO) model of creativity (e.g., creative identity, intrinsic interest, self-perceived creative competence) could deepen understanding of mindset’s influence across individual and team levels [ 45 ]. Acknowledgements The authors would like to express their sincere gratitude to the management and employees of the five high-tech enterprises in Shanghai and Chengdu for their valuable participation and support in the data collection process. The authors also thank the anonymous reviewers and the editor for their constructive comments and suggestions that have significantly improved the quality of this manuscript. Abbreviations AR Affective rumination CFA Confirmatory factor analysis CIW Caregiving interfering with work COR Conservation of Resources CSE Creative self-efficacy EC Employee creativity FM Fixed mindset GM Growth mindset PSP Problem-solving pondering SEM Structural equation modeling TAT Trait Activation Theory WIC Work interfering with caregiving VUCA Volatility, Uncertainty, Complexity, Ambiguity Authors’ contributions Liping Li: Conceptualization, Methodology, Writing-review & editing, Writing-original draft, Data curation, Formal analysis, Funding acquisition. Yao Han: Writing-review & editing, Methodology, Resources. Ying Yang: Writing-review & editing. Jun Yang: Methodology, Investigation. All authors read and approved the final manuscript. Funding The authors gratefully acknowledge the financial support of the Youth Fund for Humanities and Social Sciences of the Ministry of Education (Grant No. 22YJC630057). Data availability The datasets generated and analysed during the current study are not publicly available due to the confidentiality agreements signed with the participating high-tech enterprises to protect their organizational and employee privacy, but are available from the corresponding author on reasonable request with the permission of the participating enterprises. The measurement scales used in this study are all established and publicly available scales, with citations provided in the “ Measurement tools ” section of the manuscript. Declarations Ethics approval and consent to participate This study was approved by the Academic Committee of the Hilton College of Hotel Management, Sichuan Tourism University (Approval Reference: E20250107; Approval Date: January 8, 2025). All procedures were conducted in accordance with the principles of the Declaration of Helsinki (2013 revision). Informed written consent was obtained from all individual participants and their direct supervisors prior to data collection. Participants were informed of the study’s purpose, the anonymous nature of data processing, their right to withdraw at any time without penalty, and the confidentiality of all responses. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Agarwal P. High-performance work systems and burnout: the moderating role of mindset and the need for achievement. Int J Organ Anal. 2022;30(6):1803–18. [ Google Scholar ] 2. Alok S, Banerjee S, Singh S. 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Data Availability Statement The datasets generated and analysed during the current study are not publicly available due to the confidentiality agreements signed with the participating high-tech enterprises to protect their organizational and employee privacy, but are available from the corresponding author on reasonable request with the permission of the participating enterprises. The measurement scales used in this study are all established and publicly available scales, with citations provided in the “ Measurement tools ” section of the manuscript. 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