The influence of perceived high-performance work systems on innovative work behavior: Mediating role of work engagement

Abstract

Background

The principle of HRM requires employees to come up with novelty and creative ideas in work organizations. Prior research viewed high-performance work systems (HPWS) as an essential factor that promotes innovation and performance outcomes as it encourages employee creativity, risk-taking, and experimentation.

Objective

The current study investigated the influence of HPWS on innovative work behavior in medium-sized manufacturing enterprises through work engagement. Although much has been done to analyze various outcomes of high-performance work systems in large-scale manufacturing industries, little is known about its implementation amongst medium-sized manufacturing enterprises in Malaysia.

Methods

This study employed a group of 170 middle-management employees from medium-sized manufacturing businesses in Klang Valley, Malaysia. To perform the analysis, the researchers used SmartPLS 3.0 software. The list of medium-sized enterprises in the Klang Valley area was obtained from SME Corporation Malaysia. G*Power version 3.1.9.2 statistical program was used to perform power analysis in determining the minimum sample size for this study. The theory of job demands-resources (JD-R) model underpins the linkages between HPWS and IWB of employees in medium-sized manufacturing enterprises.

Results

The outcome indicated a noteworthy relationship between innovative work behavior and selective staffing, mentoring, and employee participation. Additionally, the study demonstrated that work engagement is crucial in promoting innovative work behavior with a medium effect size. Moreover, the connection between selective staffing, mentoring, and employee participation is mediated by work engagement.

Conclusions

This research expands the existing information on ways to implement HPWS in medium-sized manufacturing companies. Moreover, it offers practical guidance to decision-makers, especially in promoting innovation among staff through effective high-performance work practices.

Keywords

high-performance work systems innovative work behavior work engagement medium-sized manufacturing enterprises

Introduction

Creativity and innovation determine corporate performance based on studies for the recent decade because there has been a significant increase in their crucial role.^1–3 Though closely related, creativity and innovation play distinct and crucial roles in organizational success, as creativity involves generating new and out-of-the-box ideas, and innovation turns these ideas into practical processes.⁴ By harnessing the creative potential of their employees, these organizations can generate fresh ideas (creativity) and develop unique products, work processes, and services (innovation), hence mounting their human capital.⁵ Firms can improve their capacity for innovation by encouraging employees to innovate and come up with creative solutions for improving products and services.⁵

Recently, scholars have pinched their attention on the implementation and effectiveness of high-performance work systems (HPWS) and investigate its influence on organizations’ performance,^1,6 organizational innovation,⁷ productive and flexible work behavior,⁸ employee voice,⁹ innovative behavior of knowledge-intensive workers¹⁰ amongst others. Prior research reveals that a climate that supports innovation and HPWPs, including a set of distinct yet unified human resource practices, is associated with growth at organizational and employee levels.¹¹ Hence HPWPs, such as higher autonomy, extensive training, etc., designed to enhance employees’ skills and behavior, are more likely to promote innovative work behavior and better firm performance.¹² By implementing HPWS, employees have the opportunity and motivation to produce new ideas and figure out how to exploit their ability to demonstrate and convert all the ideas into innovation as they are provided with new ways of working that are conducive to innovation through HR practices.²

Medium-sized enterprises, despite being a significant contributor to the global economy, still lag in innovation and technology, making it difficult to meet the challenging demands of Industry Revolution 4.0.¹³ A skilled labor force that can foster innovative work behavior is crucial for SMEs to survive and thrive in an era of digitalization, automation, and artificial intelligence. However, the OECD¹⁴ reported despite the potential benefits, small and medium-sized enterprises (SMEs) lag in competition for adopting digital technology. Malaysia is a developing economy. Despite its growth, the workforce is not as advanced, in terms of education and skills, as other Southeast Asian economies.¹⁵

The Malaysia Productivity Corporation (MPC)¹⁶ reported a decline in labor productivity in the manufacturing sector from 3.8 percent in 2016 to 2.4 percent in 2018. Manufacturing employment has decreased by 20 percent in the last two decades, while employment in the service sector has increased by 27 percent.¹⁷ Additionally, SMEs in Malaysia are mainly staffed with semi-skilled workers (around 60 percent), while only 25 percent of the workforce can be classified as highly skilled.¹⁸ A low percentage of highly high-skilled workers is challenging for fostering innovative work behavior (IWB), essential for driving innovation in the Industry 4.0 era. IWB relies on the abilities and competencies of employees to generate new ideas and improve processes.¹⁹ In light of this, the shortage of skilled labor makes it difficult for SMEs to remain competitive in the new technological era.²⁰

Although existing research shows a connection between HPWS and performance,²¹ there is still limited understanding regarding the mechanism through which high-performance work practices enhance innovative behaviors in employees, especially in the setting of SMEs in developing economies like Malaysia. For example,¹⁰ studied the association between employees’ perception of HPWPs and innovative behavior in the knowledge-intensive sector, whereas²¹ measured the HPWPs and innovative behavior of employees in the services sector. Hence, this study targets small-medium enterprises in an emerging economy, Malaysia, where adapting to rapidly evolving business practices represents many challenges coupled with a lack of resources and a semi-skilled workforce.

Additionally, work engagement is studied as the mechanism linking HPWPs and IWB, as engaged employees are more inclined towards contributing to the organization.²² Thus, this study aims to understand the effect of HPWS practices, namely selective staffing, extensive training, mentoring, job security, employee participation, performance appraisal, and compensation, on innovative work behavior in medium-sized enterprises. Overall, the study intends to highlight actionable insights for SMEs to leverage HPWPs to drive employees’ engagement and innovative behavior.

Hypotheses development

Theoretical support

The job demands resource (JD-R) theory explains “the effect of workplace environment on employee well-being and performance”.²³ It attributes various workplace outcomes to the availability or lack of job resources. Linking JD-R to the proposed framework, high-performance work practices are crucial job resources to ensure employees receive adequate organizational support to handle job demands, resulting in enhanced motivation and engagement. The more engaged employees are, the more likely they are to contribute proactively and innovatively to their work.²⁴ Employing the JD-R model, this study posits that HPWPs can encourage innovative work behavior through work engagement in employees working in SMEs. Applying the JD-R model in the SME population provides a solid framework for understanding the role of HPWPs in stimulating innovative work behavior, especially given the limited resources available in small-medium enterprises.

Selective staffing, innovative work behavior, and work engagement

Selective staffing is a critical aspect of HR practices because organizations recognize the value of human capital as a determining factor for their success in today's unstable economy. Precise selection is crucial for three main reasons. Firstly, the company's success is dependent on the employees’ performance, and the manager's success is dependent on their subordinates. Secondly, the hiring process can be expensive. Thirdly, negligent hiring, which involves hiring individuals with dubious backgrounds without proper safeguards, can lead to legal implications related to inadequate hiring.

Organizations that prioritize innovation are highly discerning and conduct a comprehensive hiring process that involves selecting candidates with innovative skills.²⁵ Consequently, the shape and application of HR practices contrast between medium-sized and large organizations because the application of human resource practices in medium-sized enterprises is typically informal and less systematized.^26,27 Therefore, this study attempts to uncover the significant effect of selective staffing among medium-sized enterprises. Singh et al.²⁵ identified staffing as one of the high-involvement practices that could encourage IWB. Hence, selective staffing is expected to positively correlate with innovative work behavior.

H1a: Selective staffing has a positive relationship with innovative work behavior.

H2a: Selective staffing has a positive relationship with work engagement.

Extensive training, innovative work behavior, work engagement

Recent research studies have extensively utilized training and development.²⁸ Training is pivotal in shaping employee attitudes and influencing their psychological well-being and innovative behavior.²⁹ Various field-training interventions were demonstrated to have positive effects on employees’ IWB.³⁰ However, a controlling management structure and employee rigidity, combined with a lack of innovation culture within the organization, can act as a barrier that impedes employee innovation and makes them hesitant to engage in innovation.³¹ Xerri and Reid²⁸ further argue that the level of employee engagement is a crucial element that can impact how employees view training prospects and motivate them to innovate. Whilst organizations emphasize the positive effects of HR practices such as training to achieve positive outcomes, employees perceive the reciprocal initiative from the management and become motivated to engage in innovative accomplishments. Training and development have been identified as important predictors of work engagement.³²

The focus of extensive training is to develop and equip employees with the skills, knowledge, and competencies that they need for their work. However, engagement is also needed to accomplish a well-planned training structure to encourage innovative behavior of employees. If properly trained, employees are more likely to show innovative behavior to accomplish tasks. Hence, this study posits that:

H1b: Extensive training has a positive relationship with innovative work behavior.

H2b: Extensive training has a positive relationship with work engagement.

Mentoring, innovative work behavior, and work engagement

Recent research done by Uen et al.³² reveals that mentoring functions have a positive significant impact on employees’ innovative performance. They also stated that employee innovation performance could be fortified with task autonomy and their superior ability to utilize mentoring functions motivational role. Chang, Huang, and Choi³³ argued that creativity impeded due to a lack of autonomy indirectly weakens interest in job tasks.

Notwithstanding the increasing body of research on both sets of individuals, mentors, and protégés, studies on how mentoring affects individual innovation performance are still scarce.³⁴ Besides, very modest research has been done on middle management employees, and little is known about the intervening factor impacting the influence of mentoring on IWB. The significance of employee engagement has become a critical subject in organizations as having an engaged workforce has been linked to reported financial, attitudinal, and behavioral benefits.³⁴ It is increasingly viewed as a means to attain effective performance. As a result, managers must inspire their employees to excel in their performance, given their close relationships and proximity to their subordinates.

Organizations are now encouraging and expecting managers to cultivate employee engagement. However, there is limited knowledge of the process by which employees become engaged through observation, collaboration, and gaining knowledge from their managers.³⁵ This research aims to clarify the connection between work engagement and the perceived function of mentoring among middle-level managerial staff.

H1c: Mentoring has a positive relationship with innovative work behavior.

H2c: Mentoring has a positive relationship with work engagement.

Job security, innovative work behavior, and work engagement

Rapid changes in technology and intense market competition forcing organizations to take strategic action consist of outsourcing, mergers, downsizing, and restructuring. HR Asia³⁶ stated that for the next 10 years, 40 percent of youth across several countries believed that their job would be replaced by technology of automation or robotics. Oxford University conducted a study in 2013 of 700 jobs in the United States claiming almost half of them could be at risk of computerization and this seems to be an uncharted threat.³⁶ These conditions could develop a sense of job insecurity in the workplace. Nevertheless, HR Asia³⁶ critically again argues that human touch is still needed because humans will work in tandem with technology rather than be replaced by it.

However, to promote innovative behavior, employees should be engaged by ensuring job security.³⁷ The practice of job security is recognized as a significant predictor of employee engagement within the scope of HPWS practices.³² They also discovered a robust positive correlation between job security and employee engagement. According to previous empirical research conducted by Chen,³⁸ job security was found to have a positive correlation with work engagement. As employees feel competent when they can utilize their knowledge and skills in their work, this ultimately leads to engagement.

Several scholars have emphasized the significance of job security as a means of inspiring employees and fostering a favorable attitude towards work.^38,39 The reason is that job security promotes a long-term outlook and indicates that the organization is allocating time and resources towards the development of its workforce, which results in increased devotion towards the organization. Organizations expect employees to perform in a way that contributes profits to organizations, or else there is no guarantee of their job, therefore employees become more engaged to cope with organizations’ expectations. In line with Selenko, Mäkikangas, Mauno, and Kinnunen,⁴⁰ discovered that employees who experience job insecurity are motivated to perform well to secure their employment. Consequently, this research proposed hypotheses that established a correlation between job security, work engagement, and innovative behavior.

H1d: Job security has a positive relationship with innovative work behavior.

H2d: Job security has a positive relationship with work engagement.

Employee participation, innovative work behavior, and work engagement

Employee participation is also a part of the decentralized process of empowering individuals which transfers the authority from central administrative power to those who can make decisions for the execution of organizational activities. Employee participation serves as a motivation for employees to enhance their job performance, which can ultimately aid the corporation in attaining its goals.

The effectiveness of refreshing management approaches and employee contentment heavily relies on their active participation, which leads to a greater commitment to their work. This involvement can be broken down into three main elements, namely allowing employees to set their own goals and career development, promoting the exchange of ideas among employees, and delegating authority and responsibility to them.⁴¹

Organizations can provide job resources to employees, i.e., employee participation, which can lead to increased engagement in practical problem-solving, creativity in intriguing tasks, and enthusiasm to perform tasks beyond their designated responsibilities.²⁵ Additionally, Ma, Zhai, Zhong, and Zhang⁴² suggest that involving employees in the decision-making process can further enhance their engagement and contribution to innovative efforts. Drawing from the findings of previous research, it has been established that employee participation plays a significant role in influencing the level of innovative behavior. Taking this into account, the present research seeks to examine the relationship between employee participation, innovative work behavior, and work engagement.

This will be achieved by proposing the following hypotheses:

H1e: Employee participation has a positive relationship with innovative work behavior.

H2e: Employee participation has a positive relationship with work engagement.

Performance appraisal, innovative work behavior, and work engagement

Performance appraisal is measured as one of the high-commitment work practices that can stimulate employee motivation toward innovation by providing equitable compensation based on their performance.⁴³ In their research, Ahmed et al.⁴³ identified a noteworthy correlation between teamwork-based appraisal and innovative work behavior. They concluded that performance appraisal is a high-commitment work practice that encourages innovative behavior and enhances commitment toward generating new knowledge and fresh ideas within the organization.

Using performance appraisals as a high-performance human resource practice can have a beneficial impact on encouraging employees’ service innovation behavior.⁴⁴ Commitment from management to enforcing a well-run performance appraisal plays an intrinsic motivation for demonstrating service innovative behavior in the hospitality environment.⁴⁴ Therefore, implementation of these HR practices is vital to building an innovative climate in the organization to ensure innovative service excellence. The notion is that performance appraisal serves as an instrument and has a beneficial impact on promoting service innovative behavior, leading to increased employee engagement. Through feedback, performance-based rewards, developing performance standard compositions to reduce deficiencies, career paths, and professional development for employees, organizations can improve innovative behavior by increasing the level of engagement among employees within the organization. This study intends to look for more evidence in determining the effect of performance appraisal on work engagement and therefore, hypothesized:

H1f: Performance appraisal has a positive relationship with innovative work behavior.

H2f: Performance appraisal has a positive relationship with work engagement.

Compensation, innovative work behavior, and work engagement

Compensation can serve as an intrinsic motivator that helps to sustain employees’ enthusiasm and motivation for their work, leading to greater engagement with the organization.^45,46 Beforehand, Evans and Davis⁴⁷ reported an effective compensation system designed as motivation-enhancing also builds a perception of management support that can ensure togetherness and support each other among workers.

Despite this, many scholars have contended that the compensation system is not a significant factor in promoting innovative work behavior or work engagement. Prieto and Pérez-Santana²⁵ argued that employees did not respond innovatively to compensation or incentive systems which they studied under motivation-enhancing HPWPs in their study. Employees do not view compensation as motivation-enhancing to encourage them to become innovative in the workplace. The decision to embrace innovation, regardless of any potential rewards, was left entirely to the individual's discretion. Compensation was reducing employees’ behavior toward innovation because they perceived tangible compensation as a pressure for them to engage in innovative work behavior even though they initially enjoyed engaging with their work.⁴⁸ Aktar and Pangil³¹ also urged for more empirical research on effective compensation and incentive structures for employee innovation. They reported a non-significant relationship between effective compensation as motivation-enhancing HR practices and innovative work behavior. Therefore, this study hypothesized that:

H1g: Compensation has a positive relationship with innovative work behavior.

H2g: Compensation has a positive relationship with work engagement.

Work engagement and innovative work behavior

Empirical evidence from past literature has demonstrated a strong relationship between work engagement and favorable results, particularly in promoting innovative behavior,^49,50 job performance,⁵¹ and intention to quit^52,53 among others. A study conducted by Jung and Yoon⁴⁹ revealed that employees who demonstrated high levels of work engagement were more likely to engage in innovative behaviors. Nonetheless,²⁸ contended that innovative behavior can only be increased in the workplace if there is an increase in job engagement. More studies are trying to disentangle the drawbacks related to the slow pace of innovation in organizations and trying to relate them to work engagement because it is believed to be a significant intervention factor that boosts innovative work behavior and thus leads to increased organizational innovation performance. Rao⁵⁴ identified that when employees interact and collaborate with other employees, they actively generate suggestions for organizational development.

The process of innovation is strenuous as it requires persistence, focus, skills, and enthusiasm to complete a given task and it involves time and effort before one can see the result.⁵⁵ Inadequate resources result in fatigue and stress to complete the task.⁵⁶ Exhausted employees are more likely to lose motivation to generate creative ideas and consequently withdraw themselves from the innovation process.⁵⁰ Hence, these arguments lead to the development of the hypothesis:

H3: Work engagement has a positive relationship with innovative work behavior.

Mediating role of work engagement

Previous research has consistently highlighted the motivational process created by work engagement in connecting job resources and desired outcomes. The connection between a learning organization and innovative work behavior is fully mediated by work engagement.⁴⁹ Additionally, Ma et al.⁴² have identified various job resources such as perceived organizational and supervisor support, reward and recognition, job characteristics procedural justice, and distributive justice; and connected them to different outcomes, including organizational citizenship behavior, organizational commitment, job satisfaction, and intention to quit. The authors found that job resources and work engagement are positively related, and they reciprocally influence one another.

In a study on organizational procedural justice and innovative work behavior conducted by Marisa Salanova et al.,⁵⁷ it was found that work engagement serves as a mediator that increases employee knowledge sharing and innovative work behavior. This relationship was empirically proven. Having sufficient job resources is positively associated with high levels of work engagement and it is empirically proven that work engagement has an encouraging impact on personal initiative.⁵⁸ The atmosphere in the workplace may be influenced by individuals who experience enjoyment and have high levels of vigor and dedication, which can lead to engaging in extra-role behavior such as seeking out new challenges and effectively solving problems. Achieving high work engagement requires investing significant energy and effort into the job, demonstrating perseverance, and maintaining a strong focus on tasks. This is because high work engagement is positively related to innovative work behavior.⁵⁹ This study put forward and formulated hypotheses that work engagement mediates the relationship between job resources of high-performance work systems (HPWS) towards innovative work behavior.

H4a: Work Engagement mediates the relationship between selective staffing and innovative work behavior.

H4b: Work engagement mediates the relationship between extensive training and innovative work behavior.

H4c: Work engagement mediates the relationship between mentoring and innovative work behavior.

H4d: Work engagement mediates the relationship between job security and innovative work behavior.

H4e: Work engagement mediates the relationship between employee participation and innovative work behavior.

H4f: Work engagement mediates the relationship between performance appraisal and innovative work behavior.

H4g: Work engagement mediates the relationship between compensation and innovative work behavior.

Methods

The population for this study focused on medium-sized businesses in Lembah Klang. To determine sample size, researchers used power analysis, following recent recommendations.⁶⁰ G*Power version (3.1.9.2) was employed, setting the minimum sample at 103, based on 0.80 power and 0.15 effect size.

The study combined proportional stratified and simple random sampling. Using a list of 102 medium-sized firms from SME Corporation Malaysia, stratified sampling split the frame into non-overlapping subgroups.⁶¹ Based on Agarwal approach,⁶² each company provided three managers with team responsibilities. HR departments assisted in identifying suitable employees. To represent the population, a minimum of five middle managers were chosen from every firm. After recognizing the employees, simple random sampling was used to select the firms within each stratum.

Out of 405 distributed surveys, 182 responses came back, a response rate of 45%. After removing errors, incomplete answers, and missing data, 170 responses were usable. To measure high-performance work systems (including selective staffing, extensive training, performance appraisal, and compensation), items were adapted from,⁶³ Mentoring was studied using items from,⁶⁴ while job security and employee participation were adapted from.⁶⁵ All items used a five-point Likert scale, and data analysis employed SmartPLS 3.0.

Results

To address potential common method variance (CMV), due to single-source data collection, we conducted full collinearity testing. A dummy variable was created in Excel to regress all constructs, including the dependent variable, in our research model. Table 1 depicts that CMV was not a major concern, as all constructs fell below the recommended 5.0 threshold.

Table 1.

Full collinearity testing.

Construct	COM	EP	ET	IWB	JS	MEN	PA	SS	WE
VIF	2.377	3.472	2.819	1.472	1.741	2.621	2.797	2.561	2.286

Note: COM = Compensation, EP = Employee Participation, ET = Extensive Training, IWB = Innovative Work Behavior, JS = Job Security, MEN = Mentoring, PA = Performance Appraisal, SS = Selective Staffing, WE = Work Engagement

Measurement model

We evaluated the measurement model for convergent and discriminant validity. Convergent validity was examined by factor loadings, average variance extracted (AVE), composite reliability, and Cronbach's alpha. All factor loadings exceeded 0.5, composite reliability was above 0.7, and AVE surpassed 0.5, meeting the standards set by previous studies^66–69 (refer to Table 2). We used the heterotrait-monotrait (HTMT) method to assess discriminant validity, checking if HTMT values were below 0.85.⁷⁰ Table 3 confirms that no construct violated this threshold, establishing discriminant validity.

Table 2.

Measurement models.

Constructs	Items	Outer Loadings	Cronbach's Alpha	CR	AVE
Compensation	COM_1	0.636	0.869	0.895	0.518
	COM_2	0.666
	COM_3	0.769
	COM_4	0.667
	COM_5	0.790
	COM_6	0.817
	COM_7	0.648
	COM_9	0.742
Employee Participation	EP_1	0.805	0.911	0.931	0.694
	EP_2	0.789
	EP_3	0.836
	EP_4	0.886
	EP_5	0.883
	EP_6	0.793
Extensive Training	ET_1	0.868	0.931	0.943	0.675
	ET_2	0.846
	ET_3	0.801
	ET_4	0.809
	ET_5	0.853
	ET_6	0.863
	ET_7	0.797
	ET_8	0.725
Job Security	JS_1	0.798	0.824	0.883	0.653
	JS_2	0.820
	JS_3	0.843
	JS_4	0.770
Mentoring	MEN_1	0.644	0.915	0.932	0.607
	MEN_2	0.807
	MEN_3	0.776
	MEN_4	0.537
	MEN_5	0.738
	MEN_6	0.833
	MEN_7	0.870
	MEN_8	0.897
	MEN_9	0.839
Performance Appraisal	PA_1	0.775	0.926	0.938	0.581
	PA_10	0.712
	PA_11	0.551
	PA_2	0.808
	PA_3	0.838
	PA_4	0.858
	PA_5	0.769
	PA_6	0.820
	PA_7	0.699
	PA_8	0.730
	PA_9	0.774
Selective Staffing	SS_1	0.821	0.899	0.919	0.589
	SS_2	0.802
	SS_3	0.853
	SS_4	0.823
	SS_5	0.632
	SS_6	0.644
	SS_7	0.797
	SS_8	0.736
Work Engagement	WE_1	0.781	0.945	0.952	0.592
	WE_10	0.837
	WE_12	0.625
	WE_15	0.678
	WE_16	0.770
	WE_17	0.580
	WE_2	0.855
	WE_3	0.792
	WE_4	0.864
	WE_5	0.907
	WE_6	0.603
	WE_7	0.838
	WE_8	0.741
	WE_9	0.810
Innovative Work Behavior	IWB_1	0.805	0.935	0.946	0.660
	IWB_2	0.797
	IWB_3	0.762
	IWB_4	0.819
	IWB_5	0.757
	IWB_6	0.821
	IWB_7	0.853
	IWB_8	0.843
	IWB_9	0.847

Notes: AVE = Average Variance Extracted, CR = Composite Reliability, COM_8, WE_11, WE_13, WE_14 were deleted due to low loadings.

Table 3.

Discriminant validity.

Variable	1	2	3	4	5	6	7	8
1. Compensation
2. Employee Participation	0.672
3. Extensive Training	0.655	0.739
4. Innovative Work Behaviour	0.348	0.553	0.413
5. Job Security	0.640	0.636	0.591	0.267
6. Mentoring	0.575	0.751	0.767	0.359	0.560
7. Performance Appraisal	0.738	0.759	0.688	0.348	0.541	0.636
8. Selective Staffing	0.545	0.724	0.742	0.356	0.560	0.719	0.727
9. Work Engagement	0.519	0.711	0.597	0.489	0.551	0.664	0.576	0.662

Structural model

We tested the structural model using bootstrapping with 5000 resamples. Following Hair et al.'s⁷¹ guidelines, we reported path coefficients, t-values, p-values, and standard errors. We also considered confidence intervals and effect sizes, as recommended by Hahn and Ang.⁷² Table 4 summarizes these results, with Figure 1 illustrating the structural model. Regarding direct relationships with innovative work behavior (IWB), only employee participation showed a significant positive link (β = 0.473, t-value = 4.172, p < 0.01). Other factors like compensation, extensive training, mentoring, job security, performance appraisal, and selective staffing had no significant effects. This means only hypothesis H1e was supported. We then examine how high-performance work system (HPWS) dimensions relate to work engagement. Employee participation (β = 0.315, t-value = 3.501, p < 0.01), mentoring (β = 0.212, t-value = 2.442, p < 0.01), and selective staffing (β = 0.217, t-value = 2.306, p < 0.01) all showed positive relationships with work engagement, while other dimensions were not significant.

Figure 1.

The structural model.

Table 4.

Structural model.

Relationship	Std Beta(β)	Std Error	t-value	p-value	f²	BCI LL	BCI UL	VIF
Compensation → IWB	0.098	0.128	0.764	0.222	0.006	−0.14	0.287	2.363
Compensation → WE	0.046	0.084	0.547	0.292	0.002	−0.103	0.171	2.358
Employee Participation → IWB	0.473	0.113	4.172	p < 0.01	0.105	0.288	0.659	3.143
Employee Participation → WE	0.315	0.09	3.501	p < 0.01	0.074	0.168	0.463	2.927
Extensive Training → IWB	0.132	0.126	1.051	0.147	0.009	−0.087	0.326	2.793
Extensive Training → WE	−0.019	0.115	0.169	0.433	0.000	−0.205	0.176	2.793
Job Security → IWB	−0.145	0.102	1.424	0.077	0.018	−0.31	0.025	1.710
Job Security → WE	0.100	0.076	1.313	0.095	0.013	−0.026	0.225	1.688
Mentoring → IWB	−0.139	0.119	1.173	0.120	0.011	−0.339	0.048	2.593
Mentoring → WE	0.212	0.087	2.442	0.007	0.039	0.071	0.361	2.495
Performance Appraisal → IWB	−0.130	0.137	0.949	0.171	0.009	−0.377	0.076	2.772
Performance Appraisal → WE	−0.002	0.095	0.023	0.491	0.000	−0.156	0.153	2.772
Selective Staffing → IWB	−0.037	0.122	0.305	0.380	0.001	−0.231	0.170	2.560
Selective Staffing → WE	0.217	0.094	2.306	0.011	0.042	0.053	0.364	2.457
Work Engagement → IWB	0.272	0.140	1.947	0.026	0.050	0.032	0.497	2.177

Table 5.

Mediation assessment.

Relationship	Indirect effect beta	Std Error	t-value	p-value	BCI LL	BCI UL
Compensation → Work Engagement → Innovative Work Behavior	0.020	0.040	0.499	0.618	−0.068	0.092
Performance Appraisal → Work Engagement → Innovative Work Behavior	0.000	0.046	0.005	0.996	−0.095	0.085
Job Security → Work Engagement → Innovative Work Behavior	0.048	0.037	1.295	0.195	−0.022	0.125
Extensive Training → Work Engagement → Innovative Work Behavior	−0.008	0.054	0.152	0.879	−0.118	0.095
Mentoring → Work Engagement → Innovative Work Behavior	0.099	0.042	2.335	0.020	0.022	0.188
Employee Participation → Work Engagement → Innovative Work Behavior	0.147	0.051	2.918	0.004	0.062	0.262
Selective Staffing → Work Engagement → Innovative Work Behavior	0.099	0.047	2.109	0.035	0.011	0.195

The research also revealed a notable connection between work engagement and innovative work behavior (β = 0.272, t-value = 1.947, p = 0.026). HPWS dimensions accounted for 54.1% of work engagement variance, while work engagement explained 32% of innovative work behavior variance. Q² values for innovative work behavior (Q²= 0.198) and work engagement (Q²= 0.309) were greater than 0 suggesting that the model has good predictive relevance at the construct level. We tested mediation hypotheses using Preacher and Hayes [2008] bootstrapping method to evaluate indirect effects. Results showed in table 5 the significant indirect effects for mentoring (β = 0.099, t-value = 2.335, p = 0.020), employee participation (β = 0.147, t-value = 2.918, p = 0.004), and selective staffing (β = 0.099, t-value = 2.109, p = 0.035). These effects did not cross zero between the lower and upper bounds of the bias-corrected intervals, specifying that these mediations were significant. However, compensation, performance appraisal, job security, and extensive training showed no significant mediation effects.

Discussion

This research investigated how work engagement affects the link between High-Performance Work Systems (HPWS) and Innovative Work Behavior (IWB) in mid-sized manufacturing firms. Studying middle managers in Lembah Klang, aimed to clarify the HRM-performance connection. Out of the seven HPWS elements examined, only selective hiring, mentoring, and employee participation—through work engagement—significantly impacted IWB. While IWB research is growing, few studies have examined HPWS and IWB in medium businesses.^9,12,26 This study fills that gap, showing how HR practices can boost innovation through engaged employees.

According to the findings, three dimensions of HPWS, selective staffing, mentoring, and employee participation, appear to have a positive impact on innovative work behavior through work engagement. These findings align with previous similar research,^10,73 highlighting the role of HPWPs in fostering a conducive environment for employee performance. This suggests that medium-sized firms in Lembah Klang have smartly leveraged HPWS practices to improve IWB, clueing the significant role of strategic HR interventions in driving innovation even in under-resourced work settings.

The results suggesting the crucial role of collaborative and participatory work environments in enhancing engagement and innovation aligns with prior studies.^73,74 When employees are empowered to have a say in company matters, they feel valued and proactively engage in problem-solving and idea generation, contributing to organizational performance. In line with the JD-R model, and prior studies examining the positive effects of workplace engagement, our paper studies it as the mechanism for enhancing employees’ innovative behaviors. The results reinforce the notion that job resources stimulate engagement which boosts performance at various levels.⁵³

Interestingly, the study found no strong links between IWB and some HPWS elements—extensive training, job security, performance reviews, and compensation. The results are somewhat similar to the findings of,⁷⁵ who found weak direct correlations between HPWPs and the innovative behavior of employees in the service sector. This might be because middle managers have different needs and perceptions, as compared to early-career workers. As mid-career professionals, the staff may feel they already have enough resources and support, making engagement less important in improving IWB. This insight proposes that organizational resources may have differing effects on employees depending on their career stage, which needs further exploration. Regardless of some unsupported hypotheses, the study provides valuable insights into HPWS's role in fostering IWB.

Theoretical and practical implications

The study advances how high-performance work practices boost innovative work behavior through work engagement. The empirical findings contribute to the rhetoric of the JD-R model that job resources are particularly effective in driving engagement and innovation. Additionally, it extends the use of HPWPs to medium-sized enterprises in developing economies, highlighting how firms with limited resources can leverage strategic HR practices to foster innovation. For practitioners, the results suggest that medium-sized enterprises can enhance employee engagement and innovation by focusing on selective staffing, mentoring, and employee participation. To increase their innovative capacity, SMEs should adopt strategic HR practices and tailor them according to the organizational goals and employee career stages. The findings help us understand the variations among motivational drivers depending on the employee's career level. Therefore, companies should design their strategic HR systems considering the importance of career level.

Future research and limitations

This study has several limitations. First, the study used self-reported measures, which may introduce bias, including common method variance. It explains the influence of perceptions or social desirability on participants’ responses. Future studies should use a multi-source approach to strengthen the finding's validity. Second, the study relied on cross-sectional data, which limits the ability to establish causality or make predictions about future outcomes. Longitudinal studies could better examine the causal relationships between HPWS, work engagement, and IWB over time, offering a better understanding of these dynamics. Third, selection bias is another potential limitation of this study. Future research should employ a diverse sampling strategy to enhance the generalizability of the results. Fourth, the study did not consider the impact of external factors, such as market competition or economic conditions, on the relationship between HPWS and IWB. Future studies could explore the effect of market forces on the HPWP-IWB relationship. Lastly, future research could examine the impact of HPWS on other performance metrics, such as financial performance or customer satisfaction, to gain a broader understanding of the HRM-performance relationship in medium-sized businesses. Future studies could also consider exploring other potential mediators or moderators for the relationship between HPWS and IWB, such as organizational culture or leadership style.

Conclusion

This study examined the mediating role of work engagement in the relationship between HPWS dimensions and IWB in medium-sized companies in the manufacturing industry in Lembah Klang. The results indicated that selective staffing, mentoring, and employee participation facilitated through work engagement positively influence IWB. The study contributes to the critical field of SHRM literature on middle management employees’ IWB and the manufacturing sector literature. Future research can replicate and extend this study to other regions, industries, and performance metrics to enhance our understanding of the HRM-performance relationship in medium-sized businesses. The findings can also inform stakeholders, such as employees, medium-sized enterprise owners, SME Corp Malaysia, and the government, about the importance of high-performance work systems and work engagement in fostering innovation and competitiveness in medium-sized businesses.

Footnotes

Acknowledgements

Authors would like to thank the Editor(s) and Reviewers. Authors also thank all the participants for their contribution to this research.

ORCID iD

Muhammad Umair Javaid

Ethical approval

Universiti Malaysia Sabah (approval no: 2023/FKAL/PI1.1/2024)

Informed consent

Respondents’ confidentiality was properly maintained and kept anonymous and a consent form of participation in the study was obtained from each participant before proceeding to complete the survey.

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

Data will be available on request.

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