Person environment fit and new employees’ innovation behavior

Person environment fit (PEF) provides a unique perspective on how work environments motivate new employees’ innovation behavior (IB). Previous studies have more often examined the link between PEF and new employees’ job satisfaction, work attitudes, team performance, ability to adapt to a new organization, and employee turnover [8, 9]. As research on PEF becomes more in-depth, scholars pay more attention to new employees’ IB. PEF is a multidimensional concept that involves the degree of interaction and fit between the individual and the environment [10].

Individual organization fit refers to aligning an individual’s values, skills, and goals with those of the organization. Individuals perceive a strong match between themselves and the organization. They are more likely to experience a sense of belonging and commitment, which leads to increased motivation and intensity in innovative activities [11]. Social Exchange Theory states that individuals are more inclined to give back positively to an organization when they feel recognized, cared for, assisted, and respected by the organization [12]. The principle of reciprocity, which is central to Social Exchange Theory, emphasizes that individuals should give back to those who have helped them [13]. In the process of social exchange, resources are circulated through the mechanism of reciprocity, where the giver of positive behavior expects a positive response from the other [14]. Thus, when one party provides a valuable material or spiritual resource in social interactions, the beneficiary tends to reciprocate the resource giver with a corresponding return behavior. The benefits that employees derive from PEF help to satisfy their psychological needs, ensure the fulfillment of their personal values, and promote career development. As a result, when employees perceive encouragement and support, they are more likely to bring value to the organization by going the extra mile, such as giving back to the organization by demonstrating innovative behaviors [15].

Additionally, according to self-determination theory, employees who satisfy basic needs (e.g., when working with a sense of autonomy and control at work, possessing the skills needed for good performance, and working in a positive and supportive atmosphere) are more likely to pursue self-actualization, which includes innovative and creative work activities [16]. Empirical research suggests that PEF significantly promotes positive employee attitudes and behavioral performance [17]. In this area, Person organization fit (POF) and person job fit are the core embodiments of the concept of person environment fit, although other forms of employee fit properties exist in the workplace [18, 19]. POF and person job fit are important at all stages of an employee’s career, including the onboarding, permanent employment, and exit stages [20]. POF refers to the congruence between an employee’s values, personality, or goals and the work environment’s values, norms, or goals [21]. Person job fit is a combination of two job-related factors combinations of two job-related factors, including needs supplies fit (NSF) and demands abilities fit (DAF) [22, 23]. DAF describes the degree of fit between the demands of the work environment and the knowledge, skills, and attitudes that employees use to satisfy those demands [23]. In contrast, NSF reflects employees’ subjective evaluations of the organization’s provision of resources to meet their psychological needs [24]. Although innovation is an extra-role behavior for employees [25], organizations with higher POF tend to exhibit this behavior more frequently [26]. In addition, Goetz suggests that job-related expertise is one of the key factors influencing employee creativity and that the greater the fit between employees’ knowledge and skills in the workplace, the higher their level of IB [27]. That is, when employees’ abilities match the requirements of their jobs, they are more likely to feel confident and competent, which enhances their ability to solve problems and meet challenges. Competence and self-confidence are key drivers of innovative behavior because they motivate employees to try new approaches and take risks associated with innovation [28]. Afsar further confirmed the positive correlation between POF and a person’s job fit (including NSF and DAF) and an employee’s IB. That is, the employees who felt a high level of organizational Employees who are highly matched to the organization are more likely to engage in innovation [1]. Based on the above theoretical analysis and empirical research evidence, this study concludes that POF and person job fit positively contribute to employees’ IB. Therefore, we propose the following hypothesis:

The role of employee engagement

Employee engagement is an individual’s simultaneous investment of body and mind endeavor to perform their work positively and fully [29]. It is widely accepted that employee engagement can increase an organization’s competitive advantage [30, 31]. Employee engagement is a state of full self-activation and an important mechanism for transforming inducements into organizationally desired employee attitudes and behaviors [32–34]. Empirical studies have emphasized that employee engagement is the basis of employees’ work attitudes and a key characteristic of positive work behavior. It encompasses three different types of inputs: emotional engagement (EE), behavioral engagement (BE), and cognitive engagement (CE) [35]. Employee engagement’s multifaceted nature distinguishes it from concepts such as job satisfaction, job engagement, and organizational commitment.

PEF is often considered a positive prerequisite for employee engagement [36]. Specifically, POF, NSF, and DAF influence employee engagement by shaping employees’ psychological state and behavioral performance, which affects employee engagement [37]. When POF is high, employees feel a stronger sense of belonging and identification, and this match also motivates employees at work, thus showing higher employee engagement [38, 39]. Furthermore, when employees’ values align with the organization and act authentically in their work environment, they perceive more autonomy, competence, and, as a result, more self-confidence, which positively contributes to their IB [40]. NSF focuses on the correspondence between employees’ personal needs and the resources provided by the organization. When employees feel that the organization can meet their development and growth needs, employee engagement and job satisfaction will significantly increase. On the other hand, needs-competence matching emphasizes the fit between employees’ skills and job requirements, and employee engagement and motivation are enhanced when employees feel that their competence is sufficient to cope with the challenges of the job [41].

Employee engagement is a core factor in creating a positive work environment, enhancing task performance, and stimulating key organizational outcomes such as IB [37, 42]. Research has shown that employee engagement significantly predicts their IB [37, 43–45], which stems from emotional engagement, behavioral engagement, and cognitive engagement synergy [46, 47]. Specifically, when employees are cognitively engaged in their work, they can revisit their experiences, broaden their horizons, and generate new ideas; affective engagement allows employees to be enthusiastic and optimistic about their work; and behavioral engagement is reflected in the employees’ proactive approach to challenges and difficulties, and their sustained investment of effort [41]. These input behaviors are closely related to the active participation of employees in innovation activities, thus promoting the innovation process within the organization [48]. Therefore, employee engagement reflects individual performance and significantly predicts organizational innovation capability. Based on the above analysis, we infer that POF, NSF, and DAF not only act directly on employee engagement but also can indirectly promote IB by enhancing employee engagement. Above all, we propose the following hypothesis:

Ethics methods

This study was conducted by the Declaration of Helsinki and approved by the Ethics Committee of the Southwest University of Political Science and Law. We conducted the survey using an electronic questionnaire platform. The first page of the questionnaire was the informed consent form. Subjects were informed about the purpose of the study, the process, and data privacy. They were allowed to proceed with the questionnaire only if they clicked on consent to conduct the study.

Participants

According to the definition of new employees in most previous empirical studies, the term “new” is used to refer to the length of time after the employee has been in the organization and employees who have worked in the organization for the first nine months or one year are referred to as new employees [49]. Therefore, the population of our study is recent college graduates who have been in the workplace for nine months to one year.

From March to April 2024, the research team sent recruitment advertisements to the QQ and WeChat contact groups of graduates with the help of counselors and career service teachers at three universities in Chongqing, China. At the same time, we recruited participants from 8 companies in Chongqing to include new employees willing to participate in this study. The first page of the e-questionnaire described the purpose of the study, the procedures, and the privacy of the participants, who had the right to withdraw from the study at any time. Informed consent was obtained from all subjects involved in the study. We promised that participants’ confidentiality was guaranteed throughout the survey. To encourage employees to participate actively in our survey, we randomly rewarded them with no more than 5 RMB after each completion of the questionnaire.

893 valid questionnaires were collected (questionnaires with missing values and logical errors were excluded, with a validity rate of 95.406%). The mean age of these was 24.141 (SD = 1.146) years. There were 477 (53.415%) male and 416 (46.585%) female participants. In terms of industry, participants were mainly from IT (20.941%), education (18.029%) and manufacturing (15.677%).

Person environment fit

This was measured using the Subjective Fit Perceptions Scale (SFPS), which consists of three dimensions, including POF, NSF, and DAF, each containing three items [22]. All items were measured on a 7-point Likert scale, where 1 = “strongly disagree” and 7 = “strongly agree.” In this study, the Cronbach’s α of this scale is 0.841.

Employee engagement

The Employee Engagement Scale (EES) was used to measure employee engagement. The scale consists of 12 items and 3 dimensions (EE, BE, and CE), each including 4 items [50]. The scale was validated in the Chinese context [51]. A 5-point Likert scale was used for all the items, with 1 = “ strongly disagree” and 5=” strongly agree.” In this study, the Cronbach’s α of this scale is 0. 803.

Innovative behavior

A 6 items Innovative Behavior Scale was used to measure new employees’ innovative behavior [52]. Sample items are“ Generates creative ideas “and” Promotes and champions ideas to others. “ The scale was validated in the Chinese context [53]. In this study, the Cronbach’s α of this scale is 0.855.

Preliminary analysis

Table 1 shows that new employees who scored high levels of IB were more likely to have high levels of NSF (r = 0.566, p < 0.01), DAF (r = 0.504, p < 0.01), and POF (r = 0.451, p < 0.01). Similarly, new employees’ IB positively correlates with EE (r = 0.388, p < 0.01), BE (r = 0.500, p < 0.01), and CE (r = 0.488, p < 0.01).

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Table 1. Descriptive Statistics and Correlation Analysis.

https://doi.org/10.1371/journal.pone.0326161.t001

Structural equation model analysis

Structural Equation Modeling (SEM) is a multivariate statistical analysis technique that combines the features of factor analysis and multivariate regression analysis. SEM allows the researcher to examine the relationships between multiple dependent and independent variables simultaneously [54]. The path coefficient indicates the relationship between the variables, and the relationship is significant when the p-value is less than 0.05. In H1abc~H4abc, we hypothesized the relationship between new employees’ PEF (3 dimensions), employee engagement (3 dimensions), and IB. We created a structural equation model (SEM) to test the above hypothesis. The fit indices showed the model fit well to the data (χ²/df = 2.885, CFI = 0.983, TLI = 0.964, GFI = 0.987, RMSEA = 0.046).

The results of the SEM are shown in Table 2 and Fig 1. In the relationship between PEF and employee engagement, NSF (β = 0.197, P < 0.001) and POF (β = 0.206, P < 0.001) have a significant positive association with EE; NSF (β = 0.211, P < 0.001), DAF (β = 0.258, P < 0.001), and POF (β = 0.163, P < 0.001) all have positive associations with BE; Only DAF (β = 0.426, P < 0.001) has a significant associated with CE.

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Table 2. The result of the structural equation model.

https://doi.org/10.1371/journal.pone.0326161.t002

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Fig 1. The result of the structural equation model (Standardized Estimate).

Note: *** p < 0.001, ** p < 0.01, * p < 0.05; The dotted line means not significant.

https://doi.org/10.1371/journal.pone.0326161.g001

Moreover, in the relationship between PEF and IB, NSF (β = 0.216, P < 0.001), DAF (β = 0.065, P < 0.05), and POF (β = 0.060, P < 0.05) all have positive associations with IB. Finally, in the relationship between employee engagement and IB, EE (β = 0.090, P < 0.01), BE (β = 0.123, P < 0.001), and CE (β = 0.227, P < 0.001) all have positive associations with IB as well.

Effects test with bootstrap method

To avoid bias due to sample distribution, we tested the effect’s significance using the 5000-times Bootstrap method. The effect is significant when the 95% Bootstrap CI of the effect does not contain zero [55].

As shown in Table 3, the estimate of direct effect shows the significant effect between NSF (Effect = 0.055, BootCI= [0.028, 0.083]), DAF (Effect = 0.132, BootCI= [0.099, 0.176]), and POF (Effect = 0.041, BootCI= [0.015, 0.068]) with IB, H1a ~ H1c supported. The estimate of the indirect effect of EE shows that NSF (Effect = 0.018, BootCI= [0.005, 0.035]) and POF (Effect = 0.019, BootCI= [0.005, 0.037]) can influence IB via EE, H2a and H2c supported. The estimate of the indirect effect of BE shows that NSF (Effect = 0.026, BootCI= [0.013, 0.045]), DAF (Effect = 0.032, BootCI= [0.013, 0.055]), and POF (Effect = 0.020, BootCI= [0.008, 0.038]) can influence IB via BE, H3a~H3c supported. The estimate of the indirect effect of CE shows that only DAF (Effect = 0.097, BootCI= [0.069, 0.128]) can influence IB via CE, H4b supported.

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Table 3. The result of testing the effects with the Bootstrap method.

https://doi.org/10.1371/journal.pone.0326161.t003

Theoretical implication

This study reveals the direct effects of POF, NSF, and DAF on the new employees’ innovative behavior and the multidimensional mediating mechanism of employee engagement (EE, BE, and CE). The findings suggest that organizations need to pay systematic attention to the fit between the organization, job, and employee, which not only directly affects the innovative behavior of new employees but also plays an indirect role through different dimensions of employee engagement. Specifically, the significant effect of NSF suggests that organizations need to go beyond traditional compensation incentives to satisfy the diverse needs of employees through non-monetary support (e.g., career development opportunities, learning resources, psychological security, etc.) to stimulate their motivation to innovate. On the other hand, POF emphasizes the importance of values and cultural identity, and organizations can enhance employees’ sense of belonging by strengthening organizational culture, communication, and values alignment activities. In addition, DAF affects innovation through cognitive and behavioral engagement. Organizations should optimize the training system for new employees, especially in the early onboarding stages, to provide precise support for skill enhancement to increase their competency confidence, promoting innovative behaviors. These findings provide a theoretical basis for organizations to design more targeted management strategies and promote the transition from single incentives to multi-dimensional fit management models.

Practical implication

This study provides important practical insights for organizations to cope with the challenges of managing new generation employees. First, organizations should build a demand-driven support system to accurately grasp the core demands of new employees (e.g., career development, job autonomy) through a dynamic demand identification mechanism (e.g., regular surveys, one-on-one communication), and design personalized support programs, such as mentorship or cross-departmental program participation, to strengthen the perception of NSF. Second, in terms of values integration and cultural adaptation, organizations need to communicate organizational values during the recruitment and onboarding stages, and use case studies, role modeling, and other methods to help new hires understand their fit with their personal goals, to enhance their willingness to innovate driven by POF. Third, to address the key role of DAF, organizations should establish a dynamic demand-ability assessment mechanism, combined with stage-by-stage skills training (e.g., digital tools workshops, innovation methodology courses) and real-world task assignments, to ensure that employees’ abilities match job requirements. Finally, based on the multi-dimensional mediating effect of employee engagement, organizations need to develop differentiated engagement activation strategies, such as enhancing EE by establishing a recognition culture, empowering challenging tasks to promote BE, and providing an innovative knowledge base to support CE, to form a complete chain of driving innovative behaviors. Particularly noteworthy is that the study warns organizations to avoid the problem of training lag, suggesting that learning resources (e.g., instant feedback tools) should be organically embedded into the daily workflow to meet the new generation’s special requirements for immediacy and adaptability. These practices effectively enhance organizational innovation output and help build a sustainable employee-organization symbiotic relationship, giving organizations an edge in the fierce competition for talent.

Limitation

The present study has limitations in several areas that must be further strengthened in future research. First, we used a cross-sectional design, which precludes making explicit causal inferences about the relationships between variables, though appropriate for our current study. We will attempt to use longitudinal data next to confirm our findings further. Second, our samples were all from China, limiting the findings’ breadth. In future studies, we will try to include new employees from more regions in the study. Finally, all variables were derived from new employees’ self-reports, and in future studies, we will consider including other relevant variables, such as business leaders’ style and coworkers’ support.