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Abstract

This study draws upon the well-established Job Demands-Resources (JD-R) model in management science to construct a model examining how curiosity traits influence work creativity. The study focuses on frontline sales personnel in multinational corporations, utilizing 619 valid questionnaires to test the hypotheses. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze the data. The study demonstrates that curiosity traits can enhance creativity, with work engagement and intrinsic motivation as mediating factors, while job complexity moderates the impact of curiosity traits on work engagement and intrinsic motivation. This research makes a significant contribution to the existing body of knowledge by elucidating the link between curiosity traits and work creativity.

Keywords

curiosity traits intrinsic motivation job complexity work creativity work engagement

Introduction

It has long been recognized that the creativity of frontline employees who face customers is a key factor in corporate innovation (Schutte & Malouff, 2020). Long-term competitiveness in today’s dynamic business environment, which is marked by risk, volatility, and uncertainty, depends critically on an organization’s capacity for innovation. It is true that innovation is essential to provide businesses with a competitive edge (Azeem et al., 2021). The recent emergence of the COVID-19 pandemic in 2020, coupled with escalating international tensions in 2022, and the impending automation of jobs by artificial intelligence in 2023, have further exacerbated the challenges confronting global organizations (Abujarour et al., 2024). In light of these developments, organizational managers must actively explore effective management strategies, adjust the mindset of frontline employees, and implement measures aimed at mitigating the potential losses brought about by such challenges. Prior research has emphasized the fundamental contribution of employee creativity to an organization’s ability to maintain a competitive edge in the face of these challenges (Rumanti et al., 2023).

Over the past few decades, a growing body of research has indicated that employee creativity stems from within the employee, such that even in the absence of external incentives, creative employees possess an intrinsic drive to explore (Guo et al., 2021). Particularly in today’s highly uncertain business environment, the resources available to organizations to assist frontline sales personnel are extremely limited, while the challenges faced by frontline sales personnel are increasing and they are still required to exercise their creativity to accomplish their tasks (Chang & Shih, 2019). Consequently, the manifestation of creativity among frontline sales personnel is more contingent upon individual traits, and to gain a competitive edge and respond to the volatile external environment, human resource managers demand that frontline sales personnel unleash their inherent creative potential (Trachenko et al., 2021). Scholars in psychology and education have found a positive correlation between curiosity traits and creativity (Mahama et al., 2023), a discovery that highlights the pivotal role of curiosity as a fundamental personal resource, endowing frontline sales personnel with the ability to secure a competitive advantage. It is noteworthy that in the field of management, scholars have deconstructed the curiosity construct into five distinct dimensions: deprivation sensitivity, the joy of exploration, social curiosity, stress tolerance, and thrill-seeking (Kashdan et al., 2020). This comprehensive five-dimensional structure forms the basis for theoretical research on the manifestation of curiosity traits among employees in organizational contexts.

However, despite the evident significance of both curiosity traits and creativity in the realm of human resource management, limited research has delved into the intricate relationship between these two elements. Schutte and Malouff (2020) contend that curiosity is the most vital trait required by companies in times of rapid change and uncertainty, emphasizing that curiosity traits are the source of creativity. To date, existing literature has primarily explored the empirical connection between unidimensional curiosity/incomplete curiosity construct and creativity (e.g., Tsai & Zheng, 2021). The question of whether and through what pathways five-dimensional curiosity nurtures individual creativity remains unresolved, with mediating variables linking five-dimensional curiosity to creativity yet to be thoroughly investigated. Previous studies have explored how employee curiosity affects behavior through trait activation theory (Huang, 2021), individual creative action theory (Yi et al., 2019), or the use of flow to explain the connections between curiosity and creativity (Schutte & Malouff, 2020). However, a comprehensive theoretical framework fully elucidating the pathways linking employee curiosity traits to creativity is yet to be established. Therefore, to thoroughly study the link between employee curiosity traits and employee creativity, a full model framework is required in the field of management.

To address this research gap, this study introduces a conditional process model that elucidates the connection between the five-dimensional curiosity traits and work creativity, offering the following significant contributions. Firstly, our study provides empirical evidence confirming the positive correlation between a comprehensive five-dimensional structure of curiosity within the field of HRM and job creativity (Silva & Silva, 2022). This empirical research underscores the importance of examining the complete trait of curiosity as a subject of study. The findings advance our theoretical knowledge of how curiosity, as a complex concept, affects the creativity of front-line salespeople in the workplace. Second, based on the ideas of the JD-R Model, we offer a comprehensive explanation of the connection between employee curiosity qualities and work creativity. The study provides a theoretical framework that sheds light on how employees’ curious traits encourage personal work creativity. The association between curiosity characteristics and work creativity is mediated by work engagement and intrinsic motivation, according to research, while the relationship between curiosity traits and intrinsic motivation and employee curiosity and work engagement is moderated by job complexity. The research has expanded upon the JD-R model by highlighting the role of personal traits, in enhancing job resources and consequently promoting creative outcomes. Lastly, this investigation extends the application of the model to the field of management practices, particularly by examining the role of employee curiosity traits in the workplace. This extension fills a notable gap in the existing literature, enhancing our understanding of how senior leaders in organizations can effectively manage and leverage employee curiosity to drive organizational success (Wojtczuk-Turek, 2022). By establishing the associations between curiosity traits and various aspects of creativity, our study underscores the potential benefits of cultivating and leveraging curiosity in human resource management practices to foster a more innovative frontline sales team. This insight is particularly valuable for organizations aiming to enhance innovation and adaptability in a competitive business environment.

This study employs the JD-R model as the theoretical framework to investigate how the trait of curiosity influences job creativity through work engagement and intrinsic motivation. The remainder of this paper is organized as follows: Section 2 reviews the relevant literature and proposes the research hypotheses; Section 3 describes the research methodology, including sample selection, measurement instruments, and data analysis strategies; Section 4 presents the research findings and discusses them in conjunction with existing theories; and finally, the study concludes with a summary of the contributions, practical implications, and limitations.

Theoretical Background and Hypothesis Development

Employees’ Work Creativity and JD-R Model

The concept of psychological resources has emerged as a crucial construct in various psychological theories proposed by scholars in sociology. Hobfoll’s (2002) theoretical framework posits that psychological resources are both integrated and differentiated, encompassing anything that an individual perceives as aiding them in achieving their objectives (Halbesleben et al., 2014). Therefore, curiosity, a vital psychological resource for employees, plays a significant role in facilitating creativity.

According to T. Amabile (2012), creativity can be defined as the generation of novel and useful ideas. As such, the development of employees’ creativity is closely linked to their individual ideas, while innovation focuses on the tangible implementation of these ideas. The present study seeks to investigate the relationship between individual employee traits, specifically curiosity and creativity in the context of organizations. Specifically, we aim to explore how this relationship can be leveraged by an organization’s human resource management practices to foster creativity and innovation within the firm.

The theoretical foundation of this study is developed by drawing on the viewpoints of job demand resource (JDR; Figure 1). According to Demerouti et al. (2001), the JD-R is a valuable framework that aids in comprehending the mediation processes between employee traits and job creativity. Employee work characteristics are divided into two categories by the JDR: job resources and job demands. According to Hakanen and Roodt (2010), job demands are those components of the job that require a substantial amount of mental and physical effort and, if they are too large, may impede performance. On the other hand, job resources are characteristics associated with a job that positively affect workers’ learning and development, physical and mental health, and job accomplishment. According to Upadyaya and Salmela-Aro (2020), these tools can support individuals in reaching their professional objectives, foster personal development, and lessen the negative effects of working pressures on their physical and mental health.

Figure 1.

The model linking curiosity traits and work creativity.

In order to comprehend the dynamic function of personal resources, researchers have included the Conservation of Resource (COR) theory (Xanthopoulou et al., 2007) to expand on the viewpoints of JDR. “personal resources” describe a person’s conviction that they can effectively influence and manage their environment. Curiosity is seen as a personal resource that belongs to the individual. Researchers may better understand how employees’ curiosity traits affect workplace creativity and work results by including personal resources in the JD-R model.

Curiosity Traits

Curiosity has long been recognized as a significant motivational force that drives individuals to explore, learn, and engage in creative activities, as per the extant literature in education and psychology. In the management literature, Kashdan et al. (2020) formulated a five-dimensional model of curiosity that presents a comprehensive definition of the construct. The first dimension, deprivation sensitivity, pertains to an individual’s recognition of gaps in their knowledge and the consequent desire to fill those gaps. The second component, joyful exploration, is a state of surprise and enjoyment in learning about the world’s intriguing but little-known characteristics. The interest in comprehending the ideas and emotions of others makes up the third element of social curiosity. The fourth dimension, stress tolerance, relates to an individual’s ability to either accept or even benefit from the tension that accompanies novelty. The willingness to take chances with one’s appearance, financial situation, or social status to enjoy experiences that would improve one’s life is the fifth dimension, known as thrill-seeking.

As a personal resource, curiosity motivates individuals to address unresolved questions and reduce uncertainty (Toth, 2021). It is widely accepted that the exploratory spirit of a curious mind enhances imagination and cognitive abilities, fostering creative ideation and facilitating idea generation during the creative process (Zada et al., 2023). While recent studies in the management literature establish a positive association between individual curiosity and increased creativity, these studies tend to oversimplify the dimensions of the curiosity construct (Schutte & Malouff, 2020).

Interestingly, employee curiosity traits seem to be a double-edged sword, with some studies suggesting that curiosity can serve as both a hurdle and an instrument in employees’ socialization (Zada et al., 2023). Curious employees are inclined to adopt unconventional work methods, which entails a potential risk of loss or failure. Most companies and HR managers prioritize employee performance, and curiosity may pose a challenge to employees’ efforts to achieve desired outcomes. While employees with high levels of curiosity may gain more, uncertainty also increases the likelihood of failure on the job (Evans & Jirout, 2023).

Despite these challenges, employees with high curiosity levels demonstrate a strong commitment to achieving inherently rewarding goals, irrespective of additional benefits. They aim to minimize the loss of job resources by reducing risks and offsetting resource loss through curiosity and creativity. In doing so, they accumulate new work resources to cope with difficulties, reducing risk and offsetting resource loss. Additionally, individuals with high curiosity exhibit greater adaptability to change, perceiving novelty as an opportunity rather than a threat, enabling them to adjust rapidly to evolving circumstances (A. Singh & Murayama, 2024). High curiosity levels also foster open-mindedness, facilitating problem identification and alternative solution development (Evans & Jirout, 2023). Consistent with prior research, it has been demonstrated that each of the five dimensions of curiosity exerts a positive influence on creativity (Schutte & Malouff, 2020). Based on this, we put out the following theory:

H1: Curiosity traits are positively related to employees’ work creativity.

Work Engagement

Work engagement is a comprehensive construct encompassing cognitive, emotional, and behavioral dimensions. According to Rich et al. (2010), engaged workers are mentally focused, emotionally invested, physically active, and dedicated to helping the company succeed. As such, work engagement—described as an active, positive psychological state related to one’s job—is operationalized by the direction and intensity of cognitive, emotional, and behavioral energy.

Despite the growing interest in work engagement, the role of curiosity in this construct within the field of HRM has received limited attention. Nevertheless, research in pedagogy suggests that curiosity significantly facilitates learning and growth by encouraging individuals to explore the unknown (Salhab & Daher, 2023). Indeed, individuals with higher curiosity levels are more likely to engage in activities deepening their understanding of their interests and actively participate in challenging tasks requiring high energy levels (Zada et al., 2023).

Resources can operate as a buffer, reducing the negative effects of high demands on employee well-being. The JD-R model offers a framework for understanding the interaction between work demands, resources, and well-being outcomes, including burnout and engagement (Koroglu & Ozmen, 2022). According to a study, employees who face high demands report reduced levels of burnout when they have access to high levels of resources, which is consistent with this hypothesis (Kwon & Kim, 2020). Studies also show that interactions between resources and demands have an impact on employee engagement. High levels of demands and resources are correlated with high levels of job engagement, indicating that resources can both mitigate possible negative consequences of demands and magnify their good benefits. Building on the above discussion, we propose the following hypothesis:

H2: Curiosity traits are positively related to work engagement.

Intrinsic Motivation

Intrinsic motivation, as defined by Oldham and Cummings (1996), refers to the degree to which an employee is naturally driven and enthusiastic about engaging in work activities for the inherent satisfaction they provide, rather than being motivated by external rewards or pressures. Such motivation has been observed primarily in infants, who exhibit a remarkable ability to generate new structured behaviors in unstructured environments without clear external reward signals (Martinez et al., 2023). According to Ryan and Deci (2000), this kind of behavior can be conceptualized within the framework of intrinsic motivation and attributed to the inherent curiosity of infants. Psychologists have further proposed that curiosity traits can give rise to endogenous motivation, a type of intrinsic motivation driven by exploration (Huang, 2021). This suggests that while the significance of intrinsic motivation may diminish with age, adults can still cultivate some of the abilities they possessed as infants through intrinsic motivation that is driven by curiosity.

According to a recent JDR study, work resources positively affect intrinsic motivation (Park, 2023). This emphasizes the value of work resources and their part in helping employees develop and maintain intrinsic motivation. Furthermore, because curiosity traits have been shown to promote intrinsic motivation as a feature, they are regarded as a major antecedent of intrinsic motivation (Ryan & Deci, 2000). Furthermore, there is a positive association between the two variables and intrinsic motivation, which is necessary for employees to be creative at work (Shalley et al., 2000). In light of the foregoing debate, it is reasonable to assume that inquisitive qualities have a beneficial impact on intrinsic motivation, which in turn encourages employees to be creative in their jobs:

H3: Curiosity traits are positively related to intrinsic motivation.

The Mediating Role of Work Engagement

Increasing personal resources can help employees sustain engagement over time, as Bakker and Demerouti (2017) have shown in the JDR. Job demands and job/personal resources function as antecedents to employee engagement. Numerous studies and practical applications have examined the connection between work engagement and job performance; individuals who are highly engaged tend to have more emotional and social connections to their work as well as a stronger concentration on job-related goals (Tran et al., 2021). Furthermore, according to Zhang et al. (2021), these workers have a higher propensity to participate in corporate citizenship activities, which might improve their job performance even more. Additionally, engaged employees tend to identify more strongly with their jobs, making it difficult for them to disengage from their roles and leave the organization (Mattar et al., 2025). As a result, dedicated employees are more likely to remain with their companies and continue to invest personal resources in their work.

The JDR predicts that resources can reduce burnout while also contributing to engagement (Toth, 2021). Building on this notion, employees who possess the curiosity trait can invest this personal resource in their work and gain creativity while being engaged in their tasks. Therefore, it is reasonable to expect that employee curiosity and employees’ work creativity may be mediated by work engagement. Building on this, we hypothesize that:

H4: Work engagement mediates the relationship between employee curiosity traits and work creativity, such that higher levels of work engagement lead to stronger positive associations between employee curiosity and work creativity.

The Mediating Role of Intrinsic Motivation

Drawing on component theory, Amabile and Pratt (2016) posits that employee creativity is contingent upon the interplay of expertise, creative thinking, and task motivation. A crucial facet of this process is task motivation, which enables employees to distinguish between what they can do and what they will do in their work (Yuan & Woodman, 2021). Morris et al. (2022) differentiate between intrinsic motivation, driven by curiosity and enjoyment or personal challenge, and extrinsic motivation, driven by external goals. Extant research suggests that intrinsic motivation is more conducive to creativity than extrinsic motivation, making it a key driver of creative outcomes (T. Amabile, 2012).

From the view of the COR theory, employees who lack interest in the problems at hand may invest fewer resources to address these issues, thereby leading to less innovative solutions (Xanthopoulou et al., 2007). In contrast, employees with intrinsic motivation are more likely to thoroughly understand problems from multiple perspectives, gather relevant information, and select the most appropriate solution from a range of alternatives (Yesuf et al., 2023). This finding is consistent with JD-R model-based research, which suggests that individual resources start processes linked to intrinsic motivation and creative activity (Moon et al., 2020). Positive emotions are thought to be evoked by intrinsic motivation, and these feelings can then impact work creativity (Shalley et al., 2000). Amabile believes that intrinsic motivation is the fundamental component of creativity and that workers are more creative when faced with interesting, captivating, and difficult tasks (Amabile & Pillemer, 2012). Thus, the association between employee creativity and curious traits may be mediated by intrinsic motivation:

H5: Intrinsic motivation mediates the relationship between curiosity traits and creativity, such that higher levels of Intrinsic motivation lead to stronger positive associations between employee curiosity and work creativity.

The Moderating Role of Job Complexity

Job complexity refers to the degree to which autonomy, non-routine tasks and freedom in decision-making are required at work and has been formally associated with employees’ intellectual flexibility and openness to new experiences (Kohn & Schooler, 1982). The core of job complexity is that it requires employees to use a variety of complex skills, and complex jobs are psychologically challenging for employees (Afsar & Umrani, 2020). Therefore, highly complex jobs require employees to adopt novel approaches to solve problems.

Existing research on the JD-R has found that job complexity is related to creativity (Li et al., 2023). People who work in difficult positions may need to be creative in order to overcome certain obstacles, which may call for them to use both internal and external resources. Higher job complexity corresponds to higher skill levels required by employees, not only because employees with higher skill levels tend to be selected for more complex jobs but also because performing more complex jobs inherently promotes the development of employees’ professional skills, thereby improving their future performance (Audenaert et al., 2017). When employees feel that an assigned task is difficult, they seek resources to complete the task successfully. Afsar and Umrani (2023) stated that task complexity can be regarded as environmental support that enhances the value of an employee’s initiative that is used to perform a job effectively and independently. These environmental supports positively influence employees’ initiative through personality traits such as achievement motivation.

As mentioned above, employees with curiosity traits in complex jobs will fully embrace their roles while mobilizing their physical, emotional, and cognitive abilities to maintain a high level of engagement when facing challenges (O’Brien et al., 2020). Therefore, employees exhibiting high levels of curiosity in complex jobs have the opportunity to better utilize their energy in their work. In contrast, simple jobs involve relatively straightforward tasks and fixed processes, making it difficult for employees to generate new and unique ideas (Audenaert et al., 2017). Consequently, when work is relatively complex, employees with high curiosity are expected to demonstrate greater engagement. The following hypothesis follows from this reasoning:

H6a: Job complexity moderates the relationship between curiosity traits and work engagement, such that the higher the level of job complexity, the stronger the relationship between curiosity traits and work engagement.

Similarly, some scholars argue that the structure of work contributes to employees’ intrinsic motivation within their jobs (T. Amabile, 2012). Jobs that are designed to be complex and demanding (high in job complexity) are expected to foster higher levels of intrinsic motivation compared to relatively simple and routine jobs (Hackman & Oldham, 1980). Employees with a propensity for curiosity may engage in tasks for the enjoyment and interest derived from the tasks themselves, leading to intrinsic motivation regarding the tasks, which helps to stimulate creative behavior rather than relying on habitual responses (Amabile et al., 1994). Therefore, when job complexity is high, employees with strong curiosity should exhibit higher levels of intrinsic motivation. We propose the hypothesis:

H6b: Job complexity moderates the relationship between curiosity traits and intrinsic motivation such that the higher the level of job complexity, the stronger the relationship between curiosity traits and intrinsic motivation.

Research Methods

Measurement of Constructs

To gather our data, we designed a questionnaire. To ensure the caliber and precision of the measures, we used a translation–back translation procedure and engaged two translators who spoke Chinese and English well. The elements relevant to the research constructs and their sources are listed in Table 1. Each characteristic was measured using a five-point Likert scale, where 1 represents strongly disagree and 5 represents strongly agree. The following are the variables:

Table 1.

Construct Measures and Results of the Measurement Analysis.

Constructs	No. of items	Cronbach’s α	AVE	CR
Employee curiosity		.95
Deprivation sensitivity	5	.90	0.73	0.91
Joyous exploration	5	.90	0.72	0.90
Social curiosity	5	.93	0.78	0.93
Stress tolerance	5	.93	0.78	0.93
Thrill-seeking	5	.94	0.79	0.94
Work Creativity	6	.89	0.65	0.89
Work engagement		.87
Cognitive engagement	4	.91	0.78	0.91
Emotional engagement	4	.87	0.72	0.87
Behavioral engagement	4	.87	0.72	0.88
Intrinsic motivation		.90
Challenge	5	.89	0.71	0.90
Enjoyment	5	.93	0.79	0.94
Job complexity		.90
Skill variety	3	.88	0.81	0.88
Task significance	3	.81	0.72	0.81
Task identity	3	.91	0.85	0.91
Autonomy	3	.88	0.81	0.90

Note. N = 619. AVE = average variance extracted; CR = composite reliability (rho_a).

All factor loadings are significant at p < .0001.

Curiosity Traits (CT): This questionnaire variable, from Kashdan et al. (2020), was to be provided by employees to assess the salesperson’s curiosity. This measure has 25 Likert-type items, which were split into the five widely acknowledged characteristics of curiosity (stress tolerance, cheerful exploration, social curiosity, deprivation sensitivity, and thrill-seeking), each with five items. Work Creativity (WC): Using six questions from the 13-item creativity scale from earlier research, we assessed employee creativity (George & Zhou, 2001). To lessen the cognitive load on employees, we kept the items that were easily evaluable and pertinent to the service context. Work Engagement (WE): This variable questionnaire was taken from Shuck et al. (2017). Their work engagement scale consists of three dimensions: cognitive, emotional and behavioral (four items for each dimension). Intrinsic Motivation (IM): Intrinsic motivation refers to the interest in doing an activity for its own sake, and the pleasure and satisfaction derived from that participation. The scale includes 12 items adapted from T. M. Amabile et al. (1994). These items were divided into two well-accepted aspects of curiosity: challenge and enjoyment (five items each). Job complexity (JC): The respondents filled out a modified version of the Job Diagnostic Survey (Morgeson & Humphrey, 2006) in order to gauge the complexity of their jobs. Three items per dimension—Skill Variety, Task Significance, Task Identity, and Autonomy—were scored.

Sample and Data Collection

This study employed a two-part questionnaire survey method with a cross-lagged longitudinal design. Conducted with strict adherence to principles of voluntariness and confidentiality, the survey was carried out from October 25, 2023, to April 25, 2024. Employees completed the first part of the questionnaire, which inquired about their curiosity traits, work engagement, intrinsic motivation, and job complexity. The second part examined the assessment of workers’ work creativity, targeting the employees’ supervisors. Since managers’ responsibilities are closely aligned with the daily activities of employees, they are often well-equipped to identify and evaluate the creative elements of employees’ work. Participants included managers and employees who responded to specially crafted questionnaires on two occasions, with a 6-month interval.

In terms of survey management, we contacted executives enrolled in the Advanced Master of Business Administration program at Tsinghua University in China, inviting them to represent their companies in the survey. The companies they are affiliated with have a substantial number of front-line sales personnel and are located across various regions in China, spanning diverse industries. These executives were informed that the study aims to enhance organizational performance and were requested to have both their employees and managers complete the questionnaires. The participating companies place a high emphasis on innovation. After obtaining their confirmation, we distributed questionnaires to a total of 47 chief executive officers, who expressed their willingness to facilitate the survey within their respective organizations. A total of 619 employees completed the questionnaires, yielding a response rate of approximately 69.4%. The responses were meticulously organized to minimize potential coding errors and other systemic issues. We assured all participants of the anonymity of their responses.

The frontline sales personnel hailed from various industries, such as the internet (92), retail (45), apparel (48), catering (43), energy transportation (68), education (67), finance (47), equipment (52), healthcare (21), media (24), real estate (23), and others. On average, they had been in their current positions for slightly over 8 years. According to the valid analysis, the sample comprised slightly more than half women (53.4%), with 64.3% of the sample aged between 25 and 35. In terms of educational attainment, the subjects were highly educated, with 74.1% holding bachelor’s degrees and 11.7% holding master’s or higher degrees (masters, doctoral degrees).

Ethical Considerations

Ethical approval for this study was obtained from the institutional Ethics Review Committee. To minimize potential risks, all survey responses were collected anonymously, and no identifiable information was recorded. Participation was voluntary, and respondents could discontinue at any time without penalty. Informed consent was obtained in the form of implied consent: at the beginning of the questionnaire, participants were informed that the survey was for academic research purposes, that participation was voluntary, and that responses would remain confidential and anonymous. Proceeding with the survey indicated their consent. Organizational leaders were informed of the general purpose of the study and agreed to facilitate the survey within their organizations. The potential risks to participants were minimal, and the potential benefits, contributing to knowledge on workplace behavior, employee motivation, and creativity, clearly outweighed these risks. This procedure is consistent with Section 8.05 of the APA Ethical Principles, which permits dispensing with written informed consent in minimal-risk, anonymous survey research conducted in organizational settings.

Common Method Variance

The structural equation modeling of partial least squares (PLS-SEM) is used to ascertain whether there are any correlations between our constructs. This method finds the strongest linear correlations between latent variables by mathematically exacting computations. The PLS methodology was determined to be the most suitable strategy for this study based on the characteristics of the sample data and the metrics that need to be analyzed. Other path analytical approaches can only handle reflective indicators, but the PLS method can handle both formative and reflective indicators of the constructs (Falk & Miller, 1992).

Consistent with prior research (Lindell & Whitney, 2001), we were cognizant of the potential risk of common method variance. To address this concern, we implemented several procedural techniques during the questionnaire design and survey administration phases. Specifically, (a) we anonymized respondents to alleviate their concerns about potential repercussions from their answers, thereby fostering a more candid and truthful response environment. Additionally, (b) we randomized the order of questions to prevent respondents from inferring the study’s objectives through the sequence of inquiries, which in turn reduced the likelihood of biased or patterned responses. (c) We also clarified scale elements to ensure that respondents could easily understand and accurately interpret the response options. Furthermore, (d) we provided clear and concise instructions to guide respondents through the survey process, minimizing confusion and enhancing their ability to provide accurate answers. (e) Finally, we applied the marker variable approach to detect and control for potential common method variance by including items unrelated to the study’s constructs, allowing us to assess the extent of any spurious correlations. These procedural adjustments collectively increased the likelihood that respondents would attempt to provide accurate answers. Moreover, they reduced the possibility that respondents could infer the study’s purpose and feel compelled to give consistent responses. Consequently, the integrity and reliability of the data were significantly enhanced.

Analyses and Results

To assess the normality of the variables, we conducted both the Kolmogorov-Smirnov and Shapiro-Wilk tests. Additionally, Mahalanobis distance was applied to identify and remove extreme outliers, ensuring the robustness of the dataset. Following data preprocessing, this study first examined the direct effects of the five dimensions of curiosity on work creativity, aiming to elucidate the unique contributions of each curiosity trait to employees’ creative performance in the workplace (Table 4). The results indicate that certain curiosity dimensions exert a significant positive influence on work creativity, highlighting the critical role of specific facets of curiosity in fostering creative problem-solving and innovative thinking.

To empirically test the proposed hypotheses, the analysis was conducted using a three-model approach. Model 1 served as the baseline, incorporating only the control variables—education and occupation. Model 2 was employed to assess the direct effects of curiosity traits on work creativity (H1), work engagement (H2), and intrinsic motivation (H3), as well as the mediating effects of work engagement and intrinsic motivation on work creativity. In this model, curiosity traits were introduced as independent variables. Finally, to examine the moderating effects proposed in H6a and H6b, Model 3 was constructed by extending Model 2 to include interaction terms, enabling a more comprehensive evaluation of these relationships.

Measurement Model Assessment

In accordance with Hair et al. (2020), we evaluated the validity and reliability of the measures employed for the research components using a confirmatory composite analysis (CCA) using reflecting measurement model within the PLS-SEM (SmartPLS 4.1). Tables 2 and 3 display the CCA results. At a very significant level (p < .01), all standardized loadings (λ) exceed the 0.70 criterion (Hair et al., 2011). The indicator loadings’ squares (λ2) surpass the 0.50 barrier when it comes to indicator dependability (Hair et al., 2019). High construct reliability is demonstrated by values for composite reliability and Cronbach’s alpha (α) that are all higher than the .70 criterion (Bagozzi & Yi, 1988). Each concept appears to have sufficient convergent validity if the average variance recovered for the constructs is more than the 0.50 criterion (Fornell & Larcker, 1981). Table 2 displays the findings of the heterotrait–monotrait ratio of correlations (HTMT). In order to prove discriminant validity, we decided to use the HTMT ratio rather than the Fornell and Larcker criteria, after the advice of Henseler et al. (2015). Good discriminant validity is suggested by the HTMT values not exceeding the threshold scores of 0.85 and 0.90 and the absence of the value 1 in the HTMT confidence intervals (Henseler et al., 2015).

Table 2.

HTMT Ratios Associated With Correlations Between Constructs.

Variables	EC	WE	IM	JC	WC
1 EC	-
2 WE	0.61	-
3 IM	0.55	0.50	-
4 JC	0.12	0.17	0.15	-
5 WC	0.61	0.60	0.61	0.09	-

Note. N = 619. Bootstrap = 5,000. EC = employee curiosity; WE = work engagement; IM = intrinsic motivation; JC = job complexity; WC = work creativity.

Table 3.

Assessing Structural Model Results by Endogenous Constructs.

	Model 1			Model 2			Model 3
Variables	R ²	Adjusted R²	Q ²	R ²	Adjusted R²	Q ²	R ²	Adjusted R²	Q ²
WE	.01	.00	.00	.30	.30	.12	.32	.31	.13
IM	.01	.00	.00	.27	.26	.14	.29	.29	.16
WC	.04	.04	.03	.46	.45	.29	.46	.45	.29

Note. R²: prediction of all endogenous constructs; Q²: predictive relevance of the model. WE = work engagement; IM = intrinsic motivation; WC = work creativity.

Structural Model Assessment

Using the variance inflation factors (VIFs) connected to the predictors, we first assess if multicollinearity is an issue, as per Hair et al. (2020). As can be shown in Table 2, no major multicollinearity issue was encountered during the model estimates because all of the predictors’ VIF values are below the 4 threshold values recommended by Hair et al. (2019). The R², modified R², and Q² scores are then used to assess the structural model predictions. The R² values indicate that for the final target endogenous construct FP, the amount of variation explained rose from .04 in model 1 to .46 in model 3. These findings demonstrate that when the substantively hypothesized linkages are added to model 1, which merely connects the control variables to the endogenous components, the predictive power of the model can increase significantly. Additionally, the final endogenous construct WC’s Q² values rose in model 3 from .03 to .29. Again, changes in these values indicate that adding the substantive hypothesized relationships substantially improves Model 1’s predictive relevance. All things considered, these results demonstrated the importance of the hypothesized paths in this research.

Tests of Structural Paths

The estimations of the t values and standardized path coefficients are shown in Table 3. Cohen’s (1988)f² is used to compute the effect sizes associated with these estimations. This function assesses the predictive power of each independent component in the model. The testing of the structural routes is shown together with these effect sizes. As seen in Table 4, model 2, EC capacity has a positive and substantial impact on WC (β = .27, p < .01, f² = 0.08), supporting hypothesis H1. Additionally, WE (β = .54, p < .01, f² = 0.41) and IM (β = .51, p < .01, f² = 0.36) are positively impacted by EC, indicating that H2 and H3 are supported.

Table 4.

Results From Structural Model Estimation.

				Model 1			Model 2			Model 3
Path	Β	t-Value	VIF	β	t-Value	VIF	β	t-Value	VIF	β	t-Value	VIF
JE → WC	.12	3.59**	1.65
DS→ WC	.18	5.09**	1.65
ST→ WC	.14	3.70**	1.72
SC→ WC	.15	4.65**	1.54
TS→ WC	.14	4.38**	1.60
Educational→WE				−.02	0.32	1.04	−.05	0.64	1.04	−.03	0.36	1.05
Educational→IM				.00	0.11	1.04	−.00	0.09	1.04	.01	0.28	1.05
Educational→WC				−.01	0.39	1.04	−.01	0.52	1.04	−.02	0.54	1.04
Occupation→WE				.07	1.57	1.09	.04	1.04	1.09	.07	1.68	1.17
Occupation→IM				.03	0.62	1.09	.00	0.05	1.09	.02	0.51	1.17
Occupation→WC				.06	1.65	1.09	.05	1.58	1.09	.56	1.58	1.09
EC→WC (H1)							.56	11.9**	1.64	.56	11.9**	1.64
EC→WE (H2)							.54	17.95**	1.01	.53	17.27**	1.03
EC→IM (H3)							.51	11.01**	1.01	.51	10.95**	1.03
WE→WC							.25	5.92**	1.50	.25	5.93**	1.50
IM→WC							.30	5.27**	1.45	.30	5.62**	1.45
JC→WE										.12	2.68**	1.30
JC→IM										.10	2.44**	1.30
EC × JC→WE (H6a)										.14	3.76**	1.02
EC × JC→IM (H6b)										.12	2.63**	1.02

Note. EC = employee curiosity; WE = work engagement; IM = intrinsic motivation; JC = job complexity; WC = work creativity; JE = joyous exploration; DS = deprivation sensitivity; ST = stress tolerance; SC = social curiosity; TS = thrill-seeking.

p < .01.

Table 5 reports the mediation analysis results, presenting the direct, indirect, and total effects for clarity. The indirect effect of EC on WC through WE is 0.10, with a 97.5% confidence interval of [0.09, 0.24], indicating that WE partially mediates this relationship, supporting H4. Similarly, the indirect effect of EC on WC through IM is 0.14, with a confidence interval of [0.09, 0.19], confirming the mediating role of IM and supporting H5. The total effect of EC on WC, considering both direct and indirect influences, was found to be 0.56, reinforcing the theoretical framework. As expected, model 3 indicates that the interaction term JC × EC significantly and positively affects WE (β = .14, p < .01, f² = 1.02), supporting H6a. JC× EC significantly and positively affects IM (β = .12, p < .01, f² = 1.02), supporting H6b.

Table 5.

Mediating Effect Test Results.

Path relationship	Direct effect	Indirect effect	Total effect	IICI	ULCI
EC→WC	0.56**		0.56**	0.47	0.75
EC→WE→WC		0.10**	0.66**	0.09	0.24
EC→IM→WC		0.14**	0.70**	0.09	0.19

Note. EC = employee curiosity; WE = work engagement; IM = intrinsic motivation; WC = work creativity.

p < .01.

Discussion and Implications

Discussion

The results and noteworthy findings in the controls merit further discussion. This study investigated the relationship between employees’ curiosity traits, work engagement, intrinsic motivation and work creativity, and also examined the moderating effect of job complexity. First, the results from testing H1 suggest that curiosity traits can foster employees’ work creativity, this finding is consistent with JD-R model. Moreover, this finding corroborates the positive correlation between curiosity and creativity across the five dimensions of curiosity. Previous research has examined how employee curiosity influences behavior through the lens of Trait Activation Theory (Huang, 2021), the Individual Creative Action Theory (Yi et al., 2019), or by invoking the concept of flow to elucidate the link between curiosity and creativity (Schutte & Malouff, 2020). However, these studies on the construct of curiosity have predominantly focused on a unidimensional or incomplete conceptualization of curiosity. Our conclusions address this gap in the existing literature, fulfilling the academic community’s expectation for a comprehensive and systematic understanding of the interrelationship between these constructs.

Second, our empirical results of testing H2 and H3 extensively illustrate the link between curiosity traits, work engagement and intrinsic motivation. Employees with a higher level of curiosity are more engaged and are intrinsically motivated to use their resources. The results regarding H4 and H5 are Statistically significant, suggesting that work engagement and intrinsic motivation mediate between curiosity traits and work creativity, and how through this pathway employee curiosity traits affect employee creativity.

Finally, testing H6a and H6b uncovers that job complexity positively moderates the relationship between curiosity traits and work engagement, as well as between curiosity traits and intrinsic motivation. In today’s complex work environments, curiosity traits facilitate employee engagement and intrinsic motivation, enhancing adaptability to challenging situations. Based on this, employees with high curiosity levels are expected to be more adaptable to complex work scenarios than those with low curiosity levels.

Theoretical Implications

This study improves the existing body of research as follows. First, we demonstrate the positive impact of the five dimensions of curiosity trait on work creativity in the management field, we are the first study to use the five dimensions of the curiosity construct empirically. No previous study has examined this relationship, and we address this gap by linking curiosity traits, work engagement, intrinsic motivation and work creativity, offering a novel perspective for management scholars examining employee personal traits.

Second, this study shows why the five dimensions of curiosity affect work creativity using the JD-R model and presents a complete structural model centered on the management field. We explain why employees with the curiosity traits in the JD-R model actively seek different job resources to reduce their job demands through the lens of employees trying to stop the loss of their own resources, we extend the application of COR theory. Additionally, we establish two mediating effects between curiosity and work creativity, contributing to the limited discussions on both antecedents and their mediating mechanisms in creativity studies.

Third, the study demonstrates that task complexity moderated the association between creative work and curiosity traits. The status of employees in complex work environments has long been a subject of ongoing debate. This study reveals that employees with a strong sense of curiosity are more proactive in seeking out job resources when confronted with complex work environments, thereby augmenting their job resources. In addition, this work adds to the body of knowledge about the regulatory emphasis of personal curiosity traits and offers a potential avenue for future research on the theoretical edge of creativity.

Managerial Implications

This study, which targets employees from Chinese enterprises and utilizes a dataset from various industries, offers insights to both individual employees and organizational management. The findings provide implications for personal development among employees as well as for strategic HRM within organizations. Firstly, within the domain of individual employees, this study clarifies that curiosity is a multidimensional personal trait, encompassing five distinct dimensions (deprivation sensitivity, joy of exploration, social curiosity, stress tolerance, and thrill-seeking), each of which can enhance the creativity of frontline sales personnel. Employees with high levels of curiosity typically exhibit greater intrinsic motivation and engagement, enabling them to navigate and make decisions to adeptly overcome work challenges. Consequently, curiosity traits enable employees to adapt and swiftly respond to the impacts of external environments. In the contemporary business context, where external resources are increasingly scarce, frontline sales personnel also face pressures from the rapid advancement of artificial intelligence, potentially affecting job security. These factors impose considerable stress on employees, affecting their performance and further complicating their ability to maintain a balanced life. Therefore, frontline sales personnel must leverage curiosity to integrate work objectives with personal traits, thereby striving to cultivate a dynamic balance between professional and personal life.

Secondly, concerning management-level factors, a shift in thinking at the organizational level is crucial. To navigate the dynamic external landscape and secure a competitive advantage, HR managers must foster the unleashing of their employees’ inherent creative potential (Trachenko et al., 2021). HR managers should recognize the significance of curiosity as a personal traits impacting employees’ work status, creativity, and performance. Organizations can provide training and support for employees with high curiosity traits, emphasizing their positive impact on creativity. Managers, particularly during recruitment, should assess candidates for high curiosity traits. Organizations can establish systematic employee training courses focusing on regulating employee curiosity and encouraging innovative behaviors.

Thirdly, our research indicates that employees with curiosity traits are more inclined to enjoy and adeptly navigate complex work environments. Without considering the role of job complexity, a more nuanced understanding of the relationship between curiosity traits and employee creativity may elude us. From the perspective of public policy, this finding holds particular significance in light of the challenges posed by recent years, including the COVID-19 pandemic, turbulence in international relations, and the swift development of artificial intelligence technologies. These factors have profoundly impacted organizational activities, exerting considerable pressure on both companies and employees. Employees who resist change may face obsolescence, failing to meet performance standards or to adapt to the impact of artificial intelligence, thereby highlighting the importance of adaptability.

Overall, in this rapidly evolving context, the importance of curiosity as a personal trait cannot be overstated. Curiosity drives employees to seek out new information, adapt to novel situations, and innovate in the face of uncertainty. For instance, in the post-COVID-19 era, where remote work and digital transformation have become the norm, curious employees are more likely to embrace new technologies and workflows. Similarly, in the face of international tensions, which can disrupt supply chains and market dynamics, curiosity enables employees to explore alternative solutions and strategies. Moreover, as artificial intelligence continues to automate routine tasks, employees with high curiosity are better positioned to upskill and reskill, thereby maintaining their relevance in the job market. Organizations should therefore prioritize the development of curiosity through targeted HRM strategies. This could include creating a culture that rewards exploration and risk-taking, offering cross-functional training programs that expose employees to diverse perspectives, and implementing mentorship schemes that pair curious employees with experienced innovators within the organization. By fostering curiosity, organizations can build a workforce that is not only resilient to external shocks but also capable of driving innovation and growth in an increasingly complex world.

Limitations and Directions for Future Research

This study acknowledges several limitations that offer opportunities for future research. Firstly, the reliance on questionnaires for data collection may introduce biases such as response set and common method variance. Secondly, the specificity of our sample hinders the generalizability of our findings. To address this, future research could conduct empirical investigations in diverse cultural contexts. Thirdly, it is crucial to recognize that excessive complexity has been shown to negatively impact performance (Okwir et al., 2018). Contemporary theoretical perspectives suggest that the moderating effect of complexity in an employee’s work may exhibit non-linearity, warranting exploration in future investigations. We encourage researchers to undertake cross-cultural studies to assess the generalizability of our findings and explore potential cultural variations in the relationship between curiosity traits and work creativity. Moreover, while earlier research has indicated that job complexity can directly enhance creativity by providing employees with greater autonomy and opportunities to solve problems (Amabile et al., 1994; Oldham & Cummings, 1996), the present study follows the theoretical framework of the JD-R model (Demerouti et al., 2001). According to this model, job complexity, as one of the external environmental factors in an employee’s job, primarily moderates the impact of job resources and job demands rather than directly generating creativity. Although this study focuses on the moderating effect of job complexity on the relationship between curiosity and creativity, future research could further explore whether job complexity can directly enhance creativity. Lastly, the five dimensions of curiosity play a pivotal role in the field of management, prompting future research initiatives to adopt a multifaceted approach to explore this subject.

Conclusion

In an era characterized by rapid change, global uncertainties, and technological advances, the imperative for organizations to innovate has become paramount for survival and competitiveness. Despite acknowledging the significance of curiosity traits and creativity in HRM, there is a scarcity of comprehensive studies exploring the intricate relationship between these elements. This study aims to enhance our understanding of the positive impact of employees’ curiosity traits on their creativity by contextualizing these traits as personal resources within the JD-R model. We elucidate the intricate relationship between the five-dimensional curiosity traits and employees’ work creativity, robustly affirming a positive correlation. Our research not only emphasizes the significance of curiosity traits but also establishes a clear pathway linking employee curiosity traits to work creativity. In conclusion, this study contributes to the growing body of knowledge and addresses a critical gap by providing a theoretical framework and empirical evidence substantiating the link between curiosity traits and creativity in human resource management.

Footnotes

Acknowledgements

The authors thank editors and referees for their helpful comments.

ORCID iDs

Booker Xu

Kuen-Hung Tsai

Ethical Considerations

Ethical approval for this study was obtained from the Ethics Review Committee of National Taipei University (Approval Reference Number: Not applicable). All procedures involving human participants were conducted in accordance with the ethical standards of National Taipei University and the 1975 Helsinki Declaration.

Consent to Participate

Participation in this study was voluntary. Informed consent was obtained in the form of implied consent: participants were informed at the beginning of the questionnaire that the survey was for academic research purposes, that participation was voluntary, and that responses would remain confidential and anonymous. Proceeding with the survey indicated their consent. This procedure is consistent with Section 8.05 of the APA Ethical Principles, which permits dispensing with written informed consent in minimal-risk, anonymous survey research conducted in organizational settings.

Author Contributions

B.X. conceptualized the study and drafted the manuscript. K.-H.T. supervised the research design and provided critical revisions. Both authors approved the final version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are openly available in figshare at http://doi.org/10.6084/m9.figshare.25808779.

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Unveiling the Link between Curiosity Traits and Work Creativity

Abstract

Keywords

Introduction

Theoretical Background and Hypothesis Development

Employees’ Work Creativity and JD-R Model

Curiosity Traits

Work Engagement

Intrinsic Motivation

The Mediating Role of Work Engagement

The Mediating Role of Intrinsic Motivation

The Moderating Role of Job Complexity

Research Methods

Measurement of Constructs

Sample and Data Collection

Ethical Considerations

Common Method Variance

Analyses and Results

Measurement Model Assessment

Structural Model Assessment

Tests of Structural Paths

Discussion and Implications

Discussion

Theoretical Implications

Managerial Implications

Limitations and Directions for Future Research

Conclusion

Footnotes

Acknowledgements

ORCID iDs

Ethical Considerations

Consent to Participate

Author Contributions

Funding

Declaration of Conflicting Interests

Data Availability Statement

References