Fueling Innovation from Within: The Psychological Pathways to Innovative Work Behavior in Saudi Public Authorities

Abstract

This study investigates the relationships between proactive personality, psychological capital, work engagement, work well-being, and innovative work behavior among employees in Saudi public authorities, based on the conservation of resources theory and the job demands-resources model. Using a sequential mediation model, data from 457 public employees were analyzed through structural equation modeling. The results show that a proactive personality and psychological capital significantly predict work engagement, but neither is significantly related to work well-being. Notably, while a proactive personality does not directly impact innovative work behavior, psychological capital does. Additionally, work well-being partially mediates the relationship between work engagement and innovative work behavior. These findings suggest that enhancing psychological capital and fostering engagement are key to promoting innovation. The mediating role of well-being highlights the importance of employee welfare in this process. This study provides practical implications for HR managers in the Saudi public sector and emphasizes strategies for building internal psychological resources. However, as data were collected from a single source, future research should include multiple key informants to enhance generalizability. This study builds on theory by demonstrating how proactive personality and psychological capital jointly stimulate innovative behavior through engagement and well-being, enriching the job demands-resources model with personal resource dynamics in public sector organizations.

1. Introduction

Humans are the primary source of innovation, as they are driven by a constructive process influenced by the environment, beliefs, and people, which results in ideas that can be applied. In the workplace, the notion of an employee’s efforts to generate or adopt new ideas to execute them is defined as innovative work behavior (IWB) (Lukes & Stephan, 2017). This concept has been widely examined in different disciplines such as human resources, organizational behavior, and quality management (Alessa & Durugbo, 2021; Alfy & Naithani, 2021; Blasco-Giner et al., 2023; Farrukh et al., 2022; Kwon & Kim, 2020; Srirahayu et al., 2023). Its significance lies in the wide scope of its impact on individuals, teams, and organizations. Innovative ideas are crucial to the survival and success of organizations. Human dimensions are viewed as an intangible asset that when properly invested in and continuously in a state of well-being, stimulates and fosters innovation (IWB), and then, offers the capability for sustaining competitive advantage through the exploration of new opportunities (Alessa & Durugbo, 2021; Ammirato et al., 2024). Employees’ work behaviors aid the organization in aligning its vision and models with the ongoing technological developments and dynamic operational circumstances (Anderson et al., 2014).

In the Saudi Arabian context, this is particularly relevant due to the government’s Vision 2030 initiative, which strongly emphasizes innovation and economic diversification (Alateeg & Alhammadi, 2024). Despite various reforms, significant transformation remains limited, partly due to bureaucratic structures, restrictive regulations, and cultural norms that discourage risk-taking and delay the adoption of new technologies (Grand & Wolff, 2022). Furthermore, the development of enterprises and the implementation of innovative ideas remain underdeveloped, aggravated by traditional organizational models and limited support systems (Alkhoraif, 2024).

Though human capital and innovation represent two out of six main components of the knowledge economy (Nurunnabi, 2017), the literature shows a scarcity in investigating the impact of IWB in many industries and types of organizations (Alfy & Naithani, 2021), especially in the Saudi context. Understanding the drivers of innovation in Saudi public authorities becomes paramount.

Within this context, it becomes critical to explore the personal and psychological resources that enable employees in the public sector to exhibit innovative behavior, especially under rigid institutional conditions (Khorakian et al., 2019; Srirahayu et al., 2023; Funko et al., 2023). Nevertheless, several obstacles remain to be overcome to improve organizations and promote IWB among Saudi Arabian employees according to an in-depth study in Saudi healthcare industry that shows an absence of effective strategies to enhance health care innovation performance (Alshahrani, 2024).

This study aims to investigate the relationship between employee personality-related resources (specifically proactive personality: PROACPER; and psychological capital: PSYCAP) and IWB. Additionally, it examines the mediating roles of work engagement (WORKENG) and work well-being (WWB) within the context of Saudi public authorities.

Although prior studies have confirmed PROACPER and PSYCAP as important predictors of IWB, the psychological mechanisms explaining how these resources affect behavior remain underexplored. Few studies have investigated the sequential mediating roles of WORKENG and WWB within theoretically grounded models such as the Conservation of Resources (COR) theory and the Job Demands-Resources (JD-R) model.

This gap becomes particularly salient in non-Western, high-context cultures such as Saudi Arabia, where the relevance and pertinence of such Western-based models have been insufficiently tested. Most existing studies have been conducted in Western public sectors or private firms, which differ in the socio-cultural values that can shape how personal resources are transformed into behavioral outcomes. Therefore, extending these frameworks into the Saudi public sector may reveal context-specific dynamics and boundary conditions that are theoretically insightful.

The recent literature has highlighted the significant role of personality-related resources, such as PROACPER and PSYCAP, in promoting IWB in public organizations (Srirahayu et al., 2023). However, while these direct relationships have been established, the underlying mechanisms through which these personal resources translate into IWB remain less clear. In addition, while the literature confirms PROACPER and PSYCAP as critical predictors of IWB, with WORKENG validated as a mediator, there is, however, little evidence directly testing sequential mediation involving both WORKENG and WWB within the theoretical frameworks of the Conservation of Resources theory and of the Job Demands-Resources model (Hobfoll, 2011; Xanthopoulou et al., 2007).

In doing so, we enrich the existing literature in multiple ways. First, we provide a more nuanced understanding of the pathways through which personal resources impact IWB. Second, we shed light on the critical role of WORKENG and WWB as intermediary psychological states in this process. Finally, we contextualize these relationships within the Saudi public sector, offering valuable insights for policymakers and practitioners in this unique cultural and organizational setting. The Saudi context adds a distinctive dimension to our study. As the kingdom strives to transform its economy and public sector, understanding the drivers of innovation in public authorities becomes paramount (Alateeg & Alhammadi, 2024). Our research not only contributes to the broader theoretical discourse on IWB but also provides practical implications for fostering innovation and entrepreneurial behavior in Saudi public organizations, aligning with the nation’s strategic goals (vibrant society, thriving economy, and ambitious nation) for development and modernization pronounced in the Saudi Vision 2030.

2. Theoretical Foundations, Literature and Hypothesis Development

2.1. COR Theory and Model of Job Demands-Resources (JD-R)

The Conservation of Resources theory (COR), developed by Hobfoll (2002), offers a framework for understanding how individuals strive to obtain, maintain, and protect resources. Within the context of this study, COR theory explains how PROACPER and PSYCAP serve as personal resources that can lead to increased WORKENG, WWB, and, subsequently, IWB. Individuals are motivated to acquire and protect valuable resources, such as time, skills, and energy, which are important for their well-being. They actively seek to conserve their personal resources (Hobfoll, 2011).

The model of JD-R is crucial for our study as it directly supports the relationship between PSYCAP (as a personal resource) and WORKENG. It helps explain how personal resources are antecedents that can lead to positive work outcomes (Bakker & Demerouti, 2008; Liu et al., 2024; Xanthopoulou et al., 2007). Personality-related resources are positive resources and are vital in increasing both WORKENG and IWB (Koroglu & Ozmen, 2022; Avey et al., 2011; Kwon & Kim, 2020). Since WORKENG and WWB are playing a central role in our research, this theory provides the basis for understanding how engagement mediates the relationships between personality-related resources (PROACPER and PSYCAP) and work outcomes (WWB and IWB) (Salanova & Schaufeli, 2008; Fatima & Khan, 2017). In addition, WWB can mediate the engagement and innovative behavior relationship aligning with the motivational pathway of the JD-R model.

These theoretical frameworks provide a solid foundation for explaining the relationships among main variables, focusing on how personal resources lead to WORKENG, which in turn influences WWB and IWB. They collectively offer a robust framework for understanding the complex relationships between PROACPER, PSYCAP, WORKENG, WWB, and IWB in the workplace. This shared focus on the importance of personal resources in driving positive work attitudes and behaviors and promoting employee engagement and well-being provides a unified theoretical foundation for understanding workplace dynamics and improving organizational outcomes in the context of Saudi public authorities.

2.2. Personality-Related Resources and Innovative Work Behavior

IWB refers to the ability of individuals to engage in activities related to the exploration, generation, championing, and implementation of ideas within business organizations (de Jong & den Hartog, 2008; Farrukh et al., 2022). It implies deliberate efforts to provide new products or services or even recommend new ways to perform work through effective development, promotion, and implementation of ideas (Tang et al., 2019). Therefore, the conceptualization of IWB does not limit it to innovation. Including the concepts of developing and implementing new ideas extends the understanding of this notion beyond creativity. Some have also defined IWB as the external expression of an employee’s intrinsic creativity (de Jong & den Hartog, 2008). Therefore, IWB encompasses all behavior at the personal level for generating, introducing, and applying new ideas for improving the organization. Thus, it has seen a surge in research in the past decade, with others considering its outcomes as others explored its associated antecedents (Bäckström & Bengtsson, 2019).

Personality-related resources, specifically PROACPER and PSYCAP, have been identified as significant antecedents of IWB in organizational settings (Dai et al., 2024).

PROACPER was suggested by Bateman and Crant (1993) to describe an individual’s tendency to actively seek out opportunities, demonstrate initiative, take action, and persist until they achieve closure through the enactment of change. They believed that employees with proactive personalities are less influenced by social pressures, have greater control over their work, and take more assertive actions to resolve work-related issues and achieve their goals (Caniëls et al., 2018; Li et al., 2022; Zhang & Yang, 2017).

Based on a systematic review of the literature, Alfy and Naithani (2021) mentioned that studies have used personality models in understanding how personality affects and influences IWB and concluded that there is a strong connection between them. The research has consistently shown such a relationship (Abouziad & Omar, 2023; Dai et al., 2024; Zuberi & Khattak, 2021). For example, in a study conducted in the Gulf Petrochemical Industries Company, Abouziad and Omar (2023) found a positive and statistically significant impact of PROACPER on all four dimensions of IWB: opportunity exploration; idea generation; promotion; and implementation.

The role of a PROACPER in improving IWB has also been identified by existing research that explored how this is enabled through a proactive organizational climate whereby risk-taking is promoted (Tang et al., 2019). Therefore, successful organizations in innovation promote a proactive climate whereby employees are allowed the freedom to explore and consider different opportunities and equally calculate the necessary risks. Proactive personalities are primary risk-takers and innovation thinkers (Zhang & Yang, 2017; Zuberi & Khattak, 2021). Such individuals are adaptive, anticipative, and agile in their actions. This enables them to identify and equally evaluate alternative methods and approaches to developing products. Proactiveness emerges as a central area of research consideration in IWB as it directly affects innovative behaviors.

PSYCAP (PsyCap) is defined as a positive psychological state comprising four components: self-efficacy (confidence in one’s ability and proficiency to execute their assigned tasks); hope (the energy and planning needed to achieve goals despite challenges); optimism (an expectation of favorable work outcomes); and resilience (the ability to bounce back from setbacks and stay engaged) (Luthans et al., 2007; Luthans & Youssef-Morgan, 2017; Luthans et al., 2011).

PsyCap is a crucial psychological resource that fosters positive individual attitude, behavior, growth, and performance (Avey et al., 2011; Chen et al., 2021). It has been found to stimulate employees’ innovative vitality through several mechanisms: enhancing employees’ belief in their creative abilities; fostering enthusiasm, energy, and curiosity; and encouraging openness to new ideas (Chen et al., 2021; Tang et al., 2019). Research has demonstrated that employees with high PsyCap usually tend to excel in organizational capability, organizational citizenship behavior, innovation, and performance (Chen et al., 2021; Adikara & Soetjipto, 2021). Multiple studies have established a positive relationship between PsyCap and IWB in several public settings and contexts (Adikara & Soetjipto, 2021; Alwali, 2024; Chen et al., 2021). For example, a study involving nurses in Iraqi public hospitals found that PSYCAP had a positive influence on IWB (Alwali, 2024). In addition, a field study involving a sample of 345 valid leader–subordinate pairs from various Chinese cities revealed a significant direct connection between PsyCap and IWB (Chen et al., 2021).

Based on these findings, we propose that both PROACPER and PSYCAP serve as critical personal resources (within the COR theory) that foster IWB. By enhancing these resources, employees in public organizations can be predisposed to creative and innovative behaviors. Considering the points mentioned above, the following hypothesis can be stated:

H1: 

Personality-related resources (a: proactive personality; b: psychological capital) are positively related to innovative work behavior.

2.3. Personality-Related Resources and Work Engagement

WORKENG is described as a positive and fulfilling state of mind related to work characterized by vigor, dedication, and absorption (Christian et al., 2011; Schaufeli et al., 2006). Vigor refers to the feeling of high energy and mental resilience in the workplace. Dedication involves a strong sense of involvement in one’s work, accompanied by feelings of significance and enthusiasm. Absorption is described by the feeling of full concentration, contentedly absorbed in their work (Bakker & Demerouti, 2008). This concept of WORKENG highlights the employee’s connection to their work, emphasizing how individuals engage and express themselves in physical, cognitive, and emotional ways while performing their roles (Bakker, 2017).

Personality-related resources, specifically PROACPER and PSYCAP, have been identified as significant antecedents of WORKENG. The research has consistently shown a positive relationship between PROACPER and WORKENG (Bakker et al., 2012; Caniëls et al., 2018; Hu et al., 2021; Mubarak et al., 2021). For instance, a study conducted by Hu et al. (2021) on nurses in a Chinese hospital revealed that employees with proactive personalities are more inclined to actively seek out opportunities, take positive actions and initiative in work processes, show exceptional dedication to their goals, and invest more energy and effort in their work. Similarly, a study involving 259 employees from a globally operating high-tech organization in the Netherlands found a significant and positive relationship between PROACPER with WORKENG (Caniëls et al., 2018). This relationship can be attributed to the tendency of proactive individuals to clearly define their responsibilities, quickly adapt to the work environment, and effectively integrate into their teams.

PsyCap has been found to stimulate employees’ WORKENG through several mechanisms: enhancing employees’ belief in their abilities; fostering enthusiasm, energy, and dedication; and promoting resilience in the face of work challenges.

Research has also shown that employees with high PsyCap tend to excel in terms of WORKENG (Alwali, 2024; Avey et al., 2011; Joo et al., 2016; Liu et al., 2024). For instance, a study by Joo et al. (2016) involving 599 Korean conglomerates revealed such a positive and significative relationship. Both PROACPER and PSYCAP serve as critical personal resources that foster WORKENG. By enhancing these personality-related resources, organizations can create an environment conducive to higher levels of employee engagement, potentially leading to improved behavior outcomes.

Based on these findings, the following hypothesis can be proposed:

H2: 

Personality-related resources (a: proactive personality; b: psychological capital) are positively related to work engagement.

2.4. Work Engagement as a Mediator

WORKENG has been consistently linked to IWB in organizational research (Chang et al., 2013; Waheed et al., 2023). The mediating role of WORKENG in the relationships between personality-related resources and both IWB and WWB is a crucial aspect of understanding the mechanisms through which personal characteristics influence workplace outcomes (Alwali, 2024; Bakker et al., 2012).

WORKENG with its key dimensions of vigor, dedication, and absorption has been identified as a key factor in translating personal resources (e.g., curiosity, hope, creative self-efficacy, resiliency, proactive personality, locus of control) into IWB from previous studies (e.g., AlShamsi et al., 2022; Fatima & Khan, 2017; Khan et al., 2023; Tekeli & Özkoç, 2022; Uppathampracha & Liu, 2022). Several scholars have established a connection between work/employee engagement and innovation (Almazrouei & Hilmi, 2024; Chang et al., 2013; De Spiegelaere et al., 2014; Jia et al., 2022; Uppathampracha & Liu, 2022).

Proactive individuals are more inclined to be engaged in their work due to their initiative-taking nature (Hu et al., 2021; Bakker et al., 2012). This heightened engagement, in turn, leads to increased innovative behavior, as engaged employees are more prone to generate, promote, and implement new ideas (Kong & Li, 2018; Koroglu & Ozmen, 2022).

Employees with high PSYCAP are more likely to be engaged in their work. This engagement fosters the cognitive and emotional resources necessary for innovative behaviors. The research indicates that PSYCAP positively influences IWB both directly and indirectly through WORKENG (Liu et al., 2024; Alwali, 2024; Rahmi et al., 2024)

From the above, the following hypotheses can be stated:

H3: 

Work engagement is positively related to innovative work behavior.

H4: 

Work engagement mediates the relationship between personality-related resources (a: proactive personality; b: psychological capital) and innovative work behavior.

Understanding the impact of WORKENG on WWB is vital for promoting a positive and beneficial work environment for employees and their organizations. WWB is constituted by the presence of engaged employees at work (Yu et al., 2024; Hakanen & Schaufeli, 2012; Salanova et al., 2014).

WORKENG also plays a crucial role in translating personality-related resources into enhanced WWB. In fact, proactive individuals, through their tendency to shape their work environment, are more likely to experience high levels of WORKENG. This engagement, characterized by positive emotions and high energy, contributes to overall WWB (Hao et al., 2019; Caesens et al., 2014; Yu et al., 2024). Moreover, employees with high PSYCAP are more likely to be engaged in their work, which subsequently leads to improved WWB. The positive psychological states associated with PsyCap contribute to engagement, which enhances overall occupational and WWB (Airila et al., 2014; Joo & Lee, 2017; Guo et al., 2022). For example, Joo and Lee (2017) found that WORKENG fully mediated the PsyCap and career satisfaction relationship serving as an indicator of well-being at work.

These mediating relationships suggest that while personality-related resources are important, their impact on IWB and WWB is often realized through the mechanism of WORKENG. This underscores the importance of fostering WORKENG as a key factor in translating personal resources into positive work outcomes (Airila et al., 2014). It is essential to highlight that these mediating effects may be partial rather than full, indicating that personality-related resources may also have direct effects on IWB and WWB, in addition to their indirect effects through WORKENG (Siu et al., 2015; Guo et al., 2022; Joo & Lee, 2017).

Based on the above, we can formulate the following hypotheses:

H5: 

Work engagement is positively related to work well-being.

H6: 

Personality-related resources (a: proactive personality; b: psychological capital) are positively related to work well-being.

H7: 

Work engagement mediates the relationship between personality-related resources (a: proactive personality; b: psychological capital) and work well-being.

2.5. Work Well-Being as Mediator

WWB is referred to an employee’s overall satisfaction with their work responsibilities and achievements, with real enjoyment and meaningful experience (Zheng et al., 2015). Several scholars found a significant connection between well-being and innovation (Nangoy et al., 2019; Huhtala & Parzefall, 2007).

The mediating role of WWB in the relationships between personality-related resources, WORKENG, and IWB is an important aspect of understanding the mechanisms through which these factors influence workplace outcomes. While WORKENG’s mediating role is robust, WWB as a mediator receives limited attention from scholars. This mediating role was explored here.

While an extensive body of work in the literature has explored the positive links between personality-related resources and work attitudes (work–life balance, job and life satisfaction, psychological, eudaimonic, and WWB) and between workplace resources and performance outcomes (e.g., Aloulou et al., 2023b; Culbertson et al., 2010; Siu et al., 2015; Xanthopoulou et al., 2007), few studies in the literature have directly connected WWB as a mediator between personality-related resources and IWB (e.g., Mehmood et al., 2022). In our study, the focus is to develop this underexplored role.

The research suggests that PROACPER is positively related to WWB (Hao et al., 2019). This enhanced WWB may provide the psychological resources necessary for engaging in innovative behaviors. Studies have revealed that PSYCAP positively influences employees’ positive attitudes and behaviors, including career or workplace well-being (Avey et al., 2011; Sulphey, 2022). This improved well-being may create a positive mindset conducive to innovation.

From the preceding discussion, we can propose the following hypotheses:

H8: 

Work well-being is positively related to innovative work behavior.

H9: 

Work well-being mediates the relationship between personality-related resources (a: proactive personality; b: psychological capital) and innovative work behavior.

Engaged employees are more likely to experience higher levels of WWB, which can lead to increased innovative behavior (Ibrahim et al., 2021). Research indicates that WORKENG is linked with better job performance and well-being (Shuck & Reio, 2014). This enhanced well-being may provide psychological resources necessary for innovative thinking and behavior (Nangoy et al., 2019).

These mediating relationships suggest that WWB plays a crucial role in translating personality-related resources and WORKENG into IWB. By fostering WWB, organizations may be able to enhance the positive effects of PROACPER, PSYCAP, and WORKENG on employees’ innovative behaviors. It is crucial to emphasize that these mediating effects may be partial rather than full, indicating that personality-related resources and WORKENG may also have direct effects on IWB, in addition to their indirect effects through WWB (Blasco-Giner et al., 2023).

From the above, we can state the following hypothesis:

H10: 

Work well-being mediates the relationship between work engagement and innovative work behavior.

2.6. Research Model

The hypothetical research model presented in Figure 1 illustrates how personality-related resources, specifically PROACPER and PSYCAP (distal antecedents), affect WORKENG and WWB (proximal factors). It also shows how WORKENG and WWB subsequently influence IWB (work outcomes). This model represents a sequential mediation framework that investigates both direct and indirect relationships in this study.

3. Materials and Methods

3.1. Participant and Data Collection Overview

Data collection was conducted from September to November 2023. The approach used in this research is a survey method that targets all Saudi employees in 48 Saudi authorities (Saudi National Portal, 2023). An online Google Form questionnaire spread via social media platforms (WhatsApp groups, LinkedIn profiles, etc.) was used to collect the data. Convenience sampling and snowball sampling are two non-probabilistic sampling techniques adopted due to the lack of a proper sampling frame. After data purification, no outliers were found following the recommendations of Tabachnick and Fidell (2013). A total of 457 questionnaires were thus retained for model analysis and statistical evaluation.

Table 1. Sample’s characteristics.

Characteristic	Frequency	Percent
Respondent’s age
Less than 29 years	202	44.2
Between 30 and 39	173	38.2
Between 40 and 49	57	12.6
Between 50 and 59	19	4.2
60 years and more	2	0.4
Respondent’s gender
Male	364	79.6
Female	93	20.4
Respondent’s marital status
Single	235	51.4
Married	207	45.3
Divorced and other	15	3.3
Respondent’s specialty
Applied sciences	32	7.0
Computer sciences	102	22.3
Social sciences	144	31.5
Health sciences	36	7.6
Other	140	30.6
Respondent’s Academic Level
Less than a bachelor’s degree	37	8.2
Bachelor’s degree	334	74.4
Master’s degree or higher	78	17.4
Respondent’s administrative Level
Top Level of Management	48	10.5
Middle Level of Management	196	42.6
Low Level of Management	213	46.6

Source: authors’ own work.

shows the demographic data from respondents, focusing on description in terms of age, gender, marital status, specialty, academic level, and administrative level. A significant number of respondents were below 29 years (44.2%), and the greater percentage were males (79.6%). Most of them were single (51.4%) and holding a bachelor’s degree (74.4%), while the sample is relatively young and educated. By specialty, the social sciences take the top with 31.5%, followed by others at 30.6% to indicate a wide variety of backgrounds. The administrative level is evenly spread, with 46.6% of respondents at a low level of management and 42.6% at middle management. Our sample is quite diversified in terms of age, educational background, and administrative level.

3.2. Measurement

All the study constructs were assessed using a 5-point Likert scale (from 1 “strongly disagree” to 5 “strongly agree”).

Proactive Personality: It was measured by 10 items adopted from Aloulou et al. (2023a). A sample item includes: “Nothing is more exciting than seeing my ideas turn into reality”. The scale was validated in several contexts (Abouziad & Omar, 2023; Ullah et al., 2023).

Psychological Capital: It was measured using the original 24-item PsyCap questionnaire (Luthans et al., 2007) which encompasses four dimensions, that is, hope with 4 items (e.g., “I always find several solutions around me to any problem”); self-efficacy with 7 items (e.g., “I feel confident acting on a new idea for a business when others do not”), optimism with 5 items (e.g., “I am optimistic about what will happen to me in the future”), and resilience with 8 items (e.g., “I can easily recover from failure”). The scale was validated in different contexts (Alkahtani et al., 2021; Dudasova et al., 2021; Tang et al., 2019).

Work Engagement: It was measured using 17 original items of the Utrecht Work Engagement Scale (UWES) (Schaufeli et al., 2006). It is used and validated in several studies (Lathabhavan et al., 2017; Uppathampracha & Liu, 2022). A sample item includes “I am immersed in my work”.

Work Well-Being: It was measured using 6 items from the scale of Zheng et al. (2015). For example, a sample item includes “I feel basically satisfied with my work achievements in my current job”.

Innovative Work Behavior: It was measured using 10 items from de Jong and den Hartog (2008) and validated with Uppathampracha and Liu (2022). Employees were requested to share their views on innovative work behavior. Sample items include “I systematically introduce innovative ideas into work practices” and “I contribute to the implementation of new ideas”.

The constructs’ items were carefully listed in Appendix A.

All items meet the thresholds for skewness (±2) and kurtosis (±7), indicating acceptable univariate normality with the use of SPSS (21.0 version). This indicates no serious deviation from normality (Kline, 2023)

Mardia’s multivariate skewness and kurtosis were assessed with the use of AMOS, indicating no significant violation of multivariate normality with both skewness and kurtosis values falling within acceptable thresholds (i.e., normalized kurtosis < |5|), confirming that SEM assumptions were satisfactorily met for reliable parameter estimation and the model estimation was not significantly biased by non-normal data distribution (Byrne, 2010).

3.3. Statistical Analysis of Reliability and Validity

We conducted an exploratory factor analysis by SPSS to obtain a preliminary measurement model. Further analysis was made complementary to assess the construct consistency, validity, and reliability using indices like Cronbach’s Alpha, composite reliability (CR), average variance extracted (AVE), and the square root of AVE. In the second step, confirmatory factor analysis was used by SPSS AMOS to check for the validity of scales and the structure of variables.

Internal consistency Cronbach’s Alpha coefficient and construct reliability (CR) were used to check the reliability of the constructs. The results of the exploratory factor analysis are presented in

Table 2. Convergent validity and construct reliability.

Construct	Number of Items	Factor Loadings	% Variance	KMO	Cronbach’s Alpha	CR	AVE
Dependent Variable
Innovative Work Behavior (IWB)	IWB1 * IWB2 IWB3 IWB4 IWB5 IWB6 IWB7 IWB8 IWB9 IWB10	- 0.759 0.771 0.826 0.786 0.792 0.786 0.817 0.841 0.830	64.203%	0.933	0.930	0.942	0.642
Mediators
Work Well-Being (WWB)	WWB1 WWB2 WWB3 WWB4 WWB5 WWB6	0.791 0.813 0.833 0.782 0.795 0.769	63.580	0.877	0.885	0.913	0.636
Work Engagement (WORKENG)	WENG1 WENG2 WENG3 WENG4 * WENG5 WENG6 WENG7 WENG8 WENG9 WENG10 WENG11 WENG12 WENG13 * WENG14 WENG15 WENG16 * WENG17 *	0.739 0.776 0.716 - 0.695 0.652 0.783 0.790 0.788 0.701 0.731 0.663 - 0.654 0.753 - -	52.990%	0.934	0.924	0.936	0.530
Independent Variables
Proactive Personality (PROACPER)	PROAC1 * PROAC2 PROACT * PROAC4 * PROAC5 PROAC6 PROAC7 PROAC8 PROAC9 PROAC10	- 0.705 - - 0.703 0.662 0.756 0.726 0.739 0.682	50.569	0.874	0.834	0.877	0.506
Psychological Capital (PSYCAP)	PSYCAP1 PSYCAP2 * PSYCAP3 PSYCAP4 PSYCAP5 PSYCAP6 PSYCAP7 PSYCAP8 PSYCAP9 * PSYCAP10 PSYCAP11 PSYCAP12 *	0.658 - 0.765 0.766 0.729 0.747 0.724 0.647 - 0.672 0.736 -	51.425	0.906	0.880	0.905	0.514

* Items dropped for factor loading (<0.4), single factor loading, or cross-loading. Extraction used principal component analysis with Varimax rotation and Kaiser normalization. Source: authors’ own work.

. For all constructs, internal consistency is good. Shared variance for all the items within each construct exceeded 0.647, the percentage of variance explained by the extracted factors exceeded 50.5%, and the value of KMO for each construct exceeded 0.874 which showed that the data is suited for the factor analysis. All constructs have Cronbach’s Alpha values ranging from 0.880 to 0.930 and CR from 0.877 to 0.942.

A correlation analysis was used to determine the strength and direction of linear relationships among independent, dependent, and control variables. As shown in

Table 3. Mean, standard deviations, correlations, and discriminant validity.

	Mean	S.D.	(1)	(2)	(3)	(4)	(5)
(1) PROACPER	3.816	0.686	0.711
(2) PSYCAP	4.099	0.655	0.622 **	0.717
(3) WORKENG	3.889	0.725	0.525 **	0.587 **	0.797
(4) WWB	3.782	0.754	0.511 **	0.521 **	0.757 **	0.728
(5) IWB	4.018	0.747	0.532 **	0.607 **	0.659 **	0.652 **	0.801

Note: S.D. = standard deviation; ** Correlation is significant at the 0.01 level (two-tailed); diagonal elements (italics) are the square root of the AVE. Off-diagonal elements are correlations between constructs. Source: authors’ own work.

, there were significant positive correlations at 0.01 levels among most independent and dependent variables.

3.4. Common Method Bias

We applied the Harman single-factor method to assess the potential common method bias, following the approach by MacKenzie and Podsakoff (2012). In doing so, all items from the relevant variables were included, which were independent, dependent, and control variables. The extraction of eight factors with eigenvalues exceeding 1.0 accounted for 60.946% of the total variance. Whereas the first factor explained 38.913% of the variance, the remaining factors contributed to 22.033%. We were satisfied that the level of common method bias was limited due to this finding, in that no one factor accounted for most of the variance and the individual factors were sharply differentiated.

Based on a confirmatory factorial analysis (

Table 4. Model fit indices with one and five factors.

Model Fit Indices	CMIN/DF	RMR	GFI	IFI	TLI	CFI	RMSEA
One factor	5.596	0.079	0.560	0.675	0.657	0.674	0.100
Five factors	1.951	0.045	0.866	0.939	0.929	0.938	0.046

Source: authors’ own work.

), the measurement model with five factors is found to be more satisfactory than the model with one factor and the model fit indices align with the widely accepted thresholds for a good fit, as proposed by Hair et al. (2019). Overall, the results suggest that the model under investigation is well-fitted and prepared for further analysis.

4. Results

After the measurement model was established satisfactorily, the collinearity statistics were checked: VIF between 1.632 and 2.684 < 5; condition index = 24.771 < 30. This suggests low multicollinearity. SEM analysis was conducted to evaluate the research model shown in Figure 1. First, the analysis examined direct relationships among the main variables, followed by an analysis related to mediation, to explain the indirect relationships. The path analysis results for the model are presented in

Table 5. Path analysis.

Relationship			Estimate	S_Estimate (S_E)	S.E.	C.R.	p	Hypothesis
IWB	←	PROACPER	0.118	0.085	0.083	1.416	0.157	H1a not supported
IWB	←	PSYCAP	0.314	0.243 ***	0.081	3.891	***	H1b supported
WORKENG	←	PROACPER	0.350	0.296 ***	0.086	4.079	***	H2a supported
WORKENG	←	PSYCAP	0.520	0.469 ***	0.081	6.455	***	H2b supported
IWB	←	WORKENG	0.258	0.222 *	0.114	2.268	0.023	H3 supported
WWB	←	WORKENG	0.859	0.814 ***	0.080	10.764	***	H5 supported
WWB	←	PROACPER	0.099	0.079	0.070	1.422	0.155	H6a not supported
WWB	←	PSYCAP	−0.012	−0.010	0.065	−0.183	0.855	H6b not supported
IWB	←	WWB	0.341	0.308 ***	0.099	3.444	***	H8 supported

Notes: * p < 0.05; *** p < 0.001. Source: authors’ own work.

.

Table 5 presents the results of the path analysis to provide a better explanation for the outcome of the structural equation model. Unstandardized and standardized coefficients (β), standard error (S.E.), critical ratio (C.R.), and p-values for all the hypothesized paths are presented in the table and the relationship strength and significance between the constructs included in the conceptual model are elucidated and which hypotheses are data-supported.

H1a is not supported, which means PROACPER does not affect IWB significantly in this sample (S_E = 0.085, p = 0.157). H1b is supported, which means higher levels of PSYCAP significantly improve IWB (S_E = 0.243, p < 0.001). This finding aligns with the literature that has identified psychological resources as a critical enabler of innovative capabilities. Therefore, both H2a and H2b are supported, meaning that PROACPER and PSYCAP have positive effects on WORKENG (S_E = 0.296, p < 0.001; S_E = 0.469, p < 0.001). This suggests that employees who have proactive personalities and are strong in PSYCAP will show better WORKENG and may have higher satisfaction and individual performance. Thus, H3 also forms the grounds for inference from WORKENG on IWB (S_E = 0.222, p < 0.05). One of the strongly supported hypotheses was H5; it is important because it reveals the use of engagement for improving the welfare of workers (S_E = 0.814, p < 0.001). On the other hand, H6a and H6b are not supported, which suggests that PROACPER and PSYCAP do not directly affect WWB in this context (S_E = 0.079, p = 0.155; S_E = −0.010, p = 0.855). H8, supported, indicates a positive relationship where higher WWB leads to more IWB (S_E = 0.308, p < 0.001). This influence underlines the importance of focusing on WWB to enhance the employee’s innovative potential.

We carried out a mediation analysis based on the procedures described by Collier (2020) which necessitate examining the associations between all variables in the mediation process. Bootstrapping was employed to test the indirect effects of PROACPER and PSYCAP on WWB and IWB.

For further insights into the indirect relations between the variables in our conceptual framework, the results of the mediation analysis are presented in

Table 6. Results of mediating analysis.

Hypothesis	From IV	Mediation	To DV	Direct Effect	Indirect Effect	Total Effect	Mediation Test
H4a	PROACTPER	WORKENG	IWB	0.085	0.165 * LBBC: 0.092 UBBC: 0.281	0.250 **	Full (indirect-only mediation)
H4b	PSYCAP	WORKENG	IWB	0.243 **	0.219 * LBBC: 0.115 UBBC: 0.333	0.462 **	Partial mediation (direct and indirect)
H7a	PROACTPER	WORKENG	WWB	0.079	0.241 * LBBC: 0.106 UBBC: 0.386	0.320 **	Full (indirect-only mediation)
H7b	PSYCAP	WORKENG	WWB	−0.010	0.382 ** LBBC: 0.207 UBBC: 0.540	0.372 **	Full (indirect-only mediation)
H9a	PROACTPER	WWB	IWB	0.085	0.024	0.109	No mediation
H9b	PSYCAP	WWB	IWB	0.243 **	−0.003	0.240 **	No mediation
H10	WORKENG	WWB	IWB	0.222	0.251 * LBBC: 0.034 UBBC: 0.567	0.473 **	Full (indirect-only mediation)

Notes: * p < 0.05; ** p < 0.01. Bootstrapping was conducted using 5000 samples and 95% bias-corrected confidence intervals. Source: authors’ own work.

. Here, the direct, indirect, and total effects of each postulated mediating relationship are presented along with the corresponding significance levels and type of mediation obtained (e.g., full, partial, or no mediation). Such results are crucial in determining the underlying mechanism proposed in our sequential mediation model.

H4a and H7a demonstrate full mediation, where the indirect effect of PROACPER on IWB and WWB through WORKENG is substantial. The significance of the indirect effect suggests that WORKENG fully mediates the relationship, emphasizing the importance of PROACPER in enhancing IWB and WWB.

H4b indicates partial mediation for the relationship between PSYCAP and IWB through WORKENG, with both direct and indirect effects being significant. This suggests that while WORKENG plays a crucial role, PSYCAP still has a direct influence on IWB, signifying that PSYCAP contributes to IWB even beyond its impact on WORKENG.

In H7b, the relationship between PSYCAP and WWB also shows full mediation, highlighting that WORKENG significantly facilitates the effect of PSYCAP on WWB.

H9a and H9b show no mediation effects between PROACPER and IWB, and PSYCAP and IWB through WWB, indicating that these relationships do not rely on WWB as a mediator.

Finally, H10 supports indirect effect mediation, where WORKENG influences IWB through WWB. This underscores the role of WORKENG as a pathway through which WWB impacts IWB.

Figure 2 illustrates the path diagram of the final research model showing significant and non-significant relationships and R2 for endogenous variables.

5. Discussion and Implications

5.1. Discussion

Thus, our study verified the main influence of PROACPER on IWB. The findings are inconsistent with prior research studies (Dai et al., 2024; Mubarak et al., 2021; Ullah et al., 2023; Zuberi & Khattak, 2021). Therefore, the study findings suggest that at workplaces in the Saudi public sector, PROACPER alone may not cause innovative behavior directly. This would suggest that simple proactivity alone would not be sufficient to create innovation unless coupled with good work environment conditions, e.g., autonomy, support, or psychological safety. For hierarchical or bureaucratic environments typical of Saudi business environments, proactive personality/behavior might be hampered by formal processes, reducing the visibility of proactive behavior as drivers of innovation.

This study also tested the effect of PSYCAP on IWB. This finding supports the existing literature. Previous studies have found that PSYCAP enables a positive assessment of reality, which affects the affective, cognitive, and behavioral capacity of individuals to result in innovative behavior (Alwali, 2024; Rahmi et al., 2024).

The influence of PROACPER and PSYCAP on WORKENG were found to be significant. These findings are in line with prior studies (Alwali, 2024; Bakker et al., 2012; Guo et al., 2022; Hu et al., 2021; Liu et al., 2024). For instance, research has shown that PROACPER is significantly associated with WORKENG (Bakker et al., 2012; Kong & Li, 2018; Mubarak et al., 2021). Similarly, studies have found that PSYCAP is positively related to WORKENG (Guo et al., 2022; Joo et al., 2016; Liu et al., 2024).

The two hypotheses stating that WORKENG influences WWB and IWB are supported. This result aligns with the existing literature (Jia et al., 2022). Research has shown that WORKENG is associated with better work outcomes (well-being and innovative behavior) (Caesens et al., 2014; Mubarak et al., 2021; Waheed et al., 2023; Yu et al., 2024).

However, the hypotheses stating that personality-related resources influence WWB were not supported. These findings are somewhat surprising, as the previous research has suggested positive relationships between these constructs (Culbertson et al., 2010; Hao et al., 2019).

The hypothesis stated that a significant relationship between WWB and IWB was supported. This aligns with some existing research (Huhtala & Parzefall, 2007; Jia et al., 2022; Koroglu & Ozmen, 2022).

Regarding the hypotheses of mediation, the findings revealed a full mediation of WORKENG between PROACPER and IWB and between PROACPER and WWB, and a partial mediation between PSYCAP and IWB through WORKENG. These findings are generally in line with the literature on the mediating role of WORKENG (Guo et al., 2022; De Spiegelaere et al., 2014; Tekeli & Özkoç, 2022; Kong & Li, 2018; Salanova & Schaufeli, 2008). However, the lack of mediation through WWB between personality-related resources (PROACPER and PSYCAP) and IWB is somewhat unexpected (Mehmood et al., 2022) and may warrant further investigation.

While many of our findings align with the existing literature, some results, particularly those related to the direct effects of personality-related resources on well-being, differ from previous studies. These results imply that personal resources might need conducive organizational conditions (e.g., recognition, justice, participative climate) to be able to promote employees’ well-being. The fact that there were significant indirect effects via work engagement also confirms the function of engagement as a buffer and resource transmitter according to the COR theory. Therefore, despite the theoretical assumption that well-being contributes to innovative work behavior, no mediation was evidenced through WWB alone. A possible explanation is that feeling good does not necessarily translate to behaving innovatively, if behaving innovatively implies taking risks or disrupting the status quo. Workers can be well and inactive in idea generation and implementation. These results reinforce the distinction between being good and being active in terms of behavior. Well-being can only strengthen innovation when supported by activation states like engagement.

This also suggests that the relationships between these constructs may be more complex in the Saudi public sector context and highlights the need for further research in this specific setting. This also highlights the importance of holistic strategies for employee development that address both WWB and innovative potential. Understanding these mediating work-related processes can help public organizations develop more targeted interventions to enhance both WWB and IWB by focusing on proactive strategies that boost WORKENG alongside efforts to develop employees’ proactive personalities and PSYCAP (Bakker, 2017; Bysted & Jespersen, 2014; Airila et al., 2014; Alshahrani, 2024).

5.2. Implications

This study adds to the literature on IWB in public settings. There are several important implications for both theory and practice.

This research addresses the call for empirical studies on IWB from emerging countries and in public settings. It contributes to the literature on transforming personal resources into innovative behavior through WORKENG and WWB under the COR theory and JD-R model. The full mediation of WORKENG between PROACPER and IWB/WWB emphasizes the crucial role of engagement as a mechanism through which personality traits influence work outcomes. This challenges prior research on the direct link between proactive personality and IWB, suggesting that in bureaucratic or low-autonomy environments, the expression of personality traits may require motivational activation. However, the unexpected lack of direct effects between personality-related resources and WWB suggests a more complex relationship than previously thought, calling for more nuanced theoretical models accounting for alternative pathways. More precisely, the absence of a PSYCAP→WWB relationship would indicate that the beneficial effects of psychological capital on well-being depend on intervening factors (e.g., leadership support) that are not fully framed in traditional COR applications.

Furthermore, the partial mediation where WORKENG influences IWB through WWB supports a sequential mediation model. This extends the existing theory by illustrating the dynamic interplay between motivational (WORKENG) and affective (WWB) states in guiding individual resources into innovation. This also adds to the understanding of the complex pathways that personal resources take to influence work outcomes.

From a practical point of view, WENG has a mediating role, linking personality-related resources to WWB and IWB. There are implications for public sector organizations on two fronts. First, it is essential to develop strategies focused on enhancing employee engagement to improve well-being and innovative behavior. Second, the direct effect of PSYCAP on IWB indicates that organizations could profit from initiatives aimed at developing employees’ PSYCAP. In other words, the interrelatedness of WORKENG, WWB, and IWB proposes that organizations should focus more on a holistic approach for employee development and performance management.

Practically, this implies that performance-enhancing intervention engagement activities (e.g., participative management) not only yield positive impacts on performance but are also openers of doors to more profound affective consequences like well-being. In addition, expenditure in psychological capital building programs—such as optimism, resilience, and efficacy coaching—can be more effective in driving innovation persistence than proactive hiring.

Although personality-related resources did not have a direct effect on WWB, the relation of WWB with IWB does suggest that well-being programs may foster innovation indirectly. Thus, at least here, organizations may want to prioritize PSYCAP when assessing innovative potential rather than solely relying on PROACPER traits.

Moreover, the findings suggest that well-being is not only an indirect result of favorable work experiences but also an active mediator of the innovation process—underlying the need for integrated HR practices that marry emotional well-being and innovation outcomes. By placing JD-R and COR theories into a Saudi context, this study contributes also a culturally informed perspective on how individual resources are expressed in environments that entail hierarchical systems and dynamic institutional norms.

These insights are valuable not only for researchers seeking to develop theories on work behavior but also for practitioners devising appropriate and targeted strategies to help improve WORKENG and WWB with IWB within the Saudi public sector. By contextualizing JD-R and COR theories in a Saudi context, this study also contributes a culturally informed perspective on how individual resources are expressed in such a Saudi environment. In addition, the implementation of such strategies provides a way through which organizations can create a conducive environment in which employees feel engaged and happy in their work to innovate, and this ultimately leads to improved public service delivery and enhanced societal outcomes.

6. Conclusions

This study aimed to elaborate on the clear roles of PSYCAP and WORKENG in encouraging IWB among Saudi public sector employees. Though PROACPER did not have a direct effect on innovation, PSYCAP presented a significant relation. WWB partially mediated the link between engagement and innovation, highlighting that employee welfare is very important in driving creativity. WORKENG was found to fully mediate the effect of PROACPER on IWB, confirming its central role in converting personality traits into innovative outcomes.

However, this study has some limitations. It is limited to the public sector, depends on cross-sectional and self-reported data, and does not adequately take Saudi cultural influences into consideration. WORKENG should be explored in a variety of sectors in future research, including longitudinal designs, while examining cultural factors that shape engagement, innovation, and entrepreneurial behavior in Saudi Arabia. This will address these gaps and offer an understanding that it is both more actionable and more complete to enhance innovation and employee development in the region.

Since the use of a single data source increases the risk of inflated correlations due to common method variance, future research should include multiple data sources to strengthen validity (leaders, peers, supervisors, etc.).

Due to the lack of available national demographic data, the representativeness of the sample could not be statistically verified, and potential sampling biases—such as the over- or under-representation of certain demographic groups—should be considered when interpreting the findings.