Strategic HRM and Firm Performance: Mediating Role of Knowledge Management Capacity and Innovation Performance

Abstract

The purpose of the current study is to investigate the linkage between strategic HRM (SHRM) and firm performance through knowledge management capability and innovation performance. Primary data were gathered from 624 employees working in 252 Indian firms. Using Model 6 of PROCESS macro, a serial mediation model was estimated to analyse the proposed relationships between SHRM, knowledge management capability, innovation performance and firm performance. The study has revealed that the use of SHRM practices which include selection, training, appraisal, rewards and empowerment results in enhanced knowledge management capability, improved innovation performance and heightened firm performance. Further, the results establish that knowledge management capability and innovation performance act as sequential mediators in linking SHRM to firm performance.

Keywords

Strategic HRM firm performance knowledge management capability innovation performance India

Introduction

In today’s highly dynamic business environment of cut-throat competition, organizations are facing a big challenge to enhance their performance while some are struggling to even cope with their current pace (Islami et al., 2020). Firm performance is a term that is difficult to define. Scholars interchangeably use it with terms such as productivity, efficiency and effectiveness (Delaney & Huselid, 1996; Cappelli & Neumark, 2001). A critical factor that can contribute to higher firm performance is effective knowledge management capability of an organization (Tseng & Lee, 2014). Knowledge management capability of a firm refers to the organizational mechanism that enables the processes that adapt and apply the knowledge within the system (Gold et al., 2001). Researchers have pointed out that the critical players for firm performance are the variabilities in their knowledge base and their capacity to develop and utilize that knowledge (Grant, 1996; Lin & Kuo, 2007; Spender & Grant, 1996). Another critical factor that is seen to contribute to firm performance is the innovation performance of firms (Mahmoud et al., 2018). Innovation performance is largely defined as the enactment of inventions and the procedures through which a novel outcome, be it new a product, system or process, comes into existence (Williams, 1999). Canh et al. (2019) have stated that continuous innovation in products and processes helps in enhancing the market share of a firm. Atalay et al. (2013) have also empirically verified that innovative firms perform better than non-innovative firms. Extant literature has proved that innovation performance is the largest contributor towards firm performance (Cho & Pucik, 2005; Prajogo, 2006).

Given the fact that knowledge management capability and innovation performance are imperative for higher firm performance, the critical question that arises is how knowledge management capability and innovation performance can be strengthened in an organization. The answer lies in the strategic management of the organization’s human resources. Other resources of the organization are also important, but they are mostly passive in nature and need human resources for their active application in order to generate value for the firm (Çalişkan, 2010). Studies of Kengatharan (2019, 2021) have revealed that it is human capital that is highly effective in enhancing productivity and firm performance. High levels of competition, globalization and a dynamic business environment have compelled HRM to discontinue its traditional style and undertake more strategic approaches to manage people (Legge, 2008). Numerous studies have demonstrated that strategic HRM (SHRM) significantly improves knowledge management capability (Figueiredo et al., 2016; Lin & Kuo, 2007; Tan & Nasurdin, 2011) and innovation performance (Jiang et al., 2012; Wang & Zang, 2005). What needs to be discovered is the role knowledge management capability and innovation performance play in linking SHRM to firm performance.

It is evidently clear from the above discussion that SHRM can help an organization perform well if it enhances the knowledge management capability and innovation performance of the organization. Extant literature provides the empirical evidence that SHRM is a big contributor to firm performance (MacDuffie, 1995; Ngo et al., 2008; Wan et al., 2002). Most studies are in unanimous agreement that SHRM makes positive impact on firm performance, but they differ on how this impact is achieved (Iqbal, 2019; Petrovic et al., 2018). Guest (2011) emphasizes that it is more important to continually identify the processes by which HRM makes a positive impact on firm performance. These arguments affirm that despite the well-established relationship between SHRM and firm performance, firms are not fully aware of what drives this relationship. The current study is an attempt to uncover the underlying mechanisms in the linkage between SHRM and firm performance. Our unique contribution lies in exploring the serial mediating effect of knowledge management capability and innovation performance in the relationship between SHRM and firm performance.

Literature Review and Hypotheses Formulation

Strategic HRM and Knowledge Management Capability

Human resource is considered the most crucial factor for building knowledge management capability, the reason being that the collection, utilization and exchange of knowledge are effected by human beings (Kianto et al., 2017). Employees, in general, are unlikely to indulge in activities that strengthen knowledge management capability unless they are motivated by effective HR practices (Lin & Kuo, 2007). The cooperation of employees in knowledge management initiatives can be ensured only through effective HRM policies and practices (Gourlay, 2001). Employee skillset and expertise in the acquisition and utilization of knowledge can be enhanced through effective programmes (Chen & Huang, 2009).

Several empirical investigations have demonstrated that SHRM plays a critical role in building knowledge management capability of an organization (Figueiredo et al., 2016; Lin & Kuo, 2007; Sung & Choi, 2018; Tan & Nasurdin, 2011). Figueiredo et al.’s (2016) empirical enquiry on the relationship of HRM and knowledge management in the Portuguese banking sector has revealed that strategically oriented HRM practices are more effective for knowledge management processes than traditional HRM practices. Gope et al. (2018) have explored the relationship of HRM practices with knowledge management capability through four case studies in four different Indian IT companies. They have concluded that HRM practices significantly contribute to building knowledge management capability within an organization. They urge researchers to further explore the effect that SHRM can wield upon knowledge management capability in different industrial setups. Considering the above arguments, the following hypothesis is proposed:

H₁: SHRM is positively related to knowledge management capability of a firm.

Strategic HRM and Innovation Performance

Although the relationship between SHRM and innovation is very old, it is only now the literature on this relationship is growing at a fast pace (Seeck & Diehl, 2017). Through training and development practices, a climate for learning and innovation can be created in an organization that may eventually facilitate higher innovation performance (Sung & Choi, 2018). In a study of 106 Chinese firms, Jiang et al. (2012) have found that four practices of SHRM, namely hiring and selection, job design, reward and teamwork have a positive influence on innovative performance by producing more creative employees. Yet another organizational study by Kundu and Gahlawat (2016) in the Indian context has revealed that development and empowerment related HR practices have a positive influence on innovation performance. Jiménez-Jiménez and Sanz-Valle (2008) argue that innovation performance of an organization largely depends upon the creativity and imagination of its employees and this can be developed through strategic HR practices. Wang and Zang (2005) have compared the effects of functional and SHRM practices among Chinese organizations and have found that SHRM practices are more effective in leading to innovation than functional HRM practices. Hence, we propose:

H₂: SHRM is positively related to innovation performance.

Knowledge Management Capability, Innovation Performance and Firm Performance

From the discussions in the previous sections, it is clear that SHRM does have a positive effect on knowledge management capability. What needs to be ascertained is the extent to which knowledge management capability is important. However, there is little doubt how essential knowledge management capability is for innovation performance as knowledge is the basic input used in innovation (Cavusgil et al., 2003; Fachrunnisa et al., 2020). The stock and flow of knowledge together create a synergistic effect and lead to innovation in an organization (Sung & Choi, 2018). Shujahat et al. (2019) have inferred that the creation and application of knowledge enhances innovation by having a positive impact on the productivity of workers. There are academic scholars who argue that effective knowledge management capability enhances the flexibility of the organization, thereby enabling the organization to adapt to environmental changes which contribute to higher innovation performance (Carrasco-Hernández & Jiménez-Jiménez, 2016; Martínez-Sánchez et al., 2008).

The other variable that is strongly affected by knowledge management capability is firm performance. Improved knowledge management capabilities can significantly enhance the performance of an organization (Luxmi, 2014). Birasnav (2014) has demonstrated that the application of knowledge through transformational leadership leads to greater firm performance. Kostopoulos et al. (2011) have found that the organizational capacity of absorbing external knowledge enhances financial performance. Similarly, Al-Sa’di et al. (2017), having studied manufacturing organizations in Jordan, provided empirical evidence regarding the positive influence knowledge management processes have on operational performance. In the Indian scenario a study by Saini (2018) reveals that knowledge performance is a significant predictor of a firm’s productivity. Even Lin and Kuo (2007) have found a positive effect of knowledge management capability on firm performance among financial training centres in Taiwan. Considering the aforementioned findings, we set to test the following two hypotheses:

H₃: Knowledge management capability is positively related to innovation performance.

H₄: Knowledge management capability is positively related to firm performance.

Apart from knowledge management capability, innovation performance is another variable that contributes to firm performance. Cho and Pucik (2005) have found that innovativeness is positively associated with three main indicators of firm performance which include profitability, growth and market value. Prajogo (2006) has found a positive effect of process innovation on sales growth, market share and profitability among Australian manufacturing firms. The author have established that the innovative activities of an organization enhance its innovation performance that further contributes to firm performance. It is observed that creation of new and unique products and services enhances the satisfaction level of customers generating a higher growth rate of sales and profitability for an organization (Mahmoud et al., 2018). In addition, high innovation performance provides the first-mover advantage to an organization and assists in keeping rivals out of competition. This further helps the organization reap higher returns (Andreeva & Kianto, 2012). Masa’deh et al.’s (2013) study of telecommunication companies has also established that enhanced innovation capabilities of an organization contribute to higher firm performance. Hence, we propose:

H₅: Innovation performance is positively related to firm performance.

Mediation of Knowledge Management Capability and Innovation Performance

Over three decades ago, empirical investigations determined the relationship between SHRM and firm performance. MacDuffie’s (1995) study of automotive assembly plants has identified that strategic HR practices make a stronger contribution to manufacturing performance when used as a bundle of interrelated practices rather than a standalone. Huselid’s (1995) study of US firms has also highlighted that a bundle of SHRM practices contributes to higher financial performance. Based on a sample of Singaporean organizations, Wan et al. (2002) have found that a set of strategic HR practices including selection, training, empowerment and performance appraisal are positively related with financial performance. Ngo et al.’s (2008) study in the Chinese context has indicated that SHRM contributes to two important indicators of firm performance, namely operational and financial performance. Recent studies also show a positive relationship between SHRM and firm performance. Nigam et al.’s (2011) study of Indian service firms has stressed upon the point that SHRM has a positive effect on firm performance but this relationship is not universal; it depends on business strategy. The study of Ho and Kuvaas (2020) has revealed a greater synergistic effect of a bundle of strategic HR practices on firm performance over individual practices. Through a sample of foreign MNCs and domestic firms operating in India, Gahlawat and Kundu (2019) have also reported similar findings which suggest that a bundle of progressive HRM practices leads to enhanced firm performance. Foreign MNCs especially in the IT and ITeS sectors were found to have used exclusivist HR strategies that enhance performance (Sarkar, 2009).

From the above empirical evidence, it is clear that SHRM has a strong association with firm performance. But this association is not direct; several studies have successfully demonstrated the indirect linkage of SHRM with firm performance through mediating variables (Cabello-Medina et al., 2011; Chang & Huang, 2005; Paul & Anantharaman, 2003). In this regard, Heffernan et al. (2016) have pointed out that the mechanisms through which the relationship of SHRM and firm performance are established are still in the developing stage and need further empirical investigation. One such underlying mechanism is knowledge management capability (Chen & Huang, 2009; Lin & Kuo, 2007). Lin and Kuo (2007) have demonstrated that HRM creates a positive effect on organizational productivity by developing organizational learning and knowledge management capability. SHRM practices reinforce creation, sharing and optimum utilization of knowledge that contribute to higher firm performance (Chen & Huang, 2009; Gope et al., 2018). Therefore, the following hypothesis is raised to test the mediation:

H₆: Knowledge management capability mediates the relationship between SHRM and firm performance.

Another variable that works as a connecting link between SHRM and firm performance is innovation performance (Cabello-Medina et al., 2011). Cabello-Medina et al. (2011) have demonstrated that the HRM practices of employee selection and empowerment contribute to firm performance by developing unique human capital which in turns leads to innovation performance. Several scholars are of a similar opinion that it is the innovation capability of the firm built with the strategic use of HRM practices, that always contributes to higher firm performance (Atalay et al., 2013; Diaz-Fernandez et al., 2017). Thus, we propose:

H₇: Innovation performance mediates the relationship between SHRM and firm performance.

Apart from their individual contribution as a parallel mediator in the SHRM-firm performance relationship, knowledge management capability and innovation performance can exert a mediating effect through their own interrelationship. We cannot ignore the possibility that knowledge management capability and innovation performance may sequentially mediate the relationship between SHRM and firm performance. Therefore, one more hypothesis is proposed to be tested:

H₈: Knowledge management capability and innovation performance sequentially mediate the relationship between SHRM and firm performance.

Research Methodology

Description of the Sample

To test the proposed hypotheses, primary data were collected through the survey method. To begin with, a list of 600 firms was created using the informational databases of the Federation of Indian Chambers of Commerce and Industry and related corporate magazines. Senior HR managers of these firms were contacted and invited to participate in the survey. We were able to garner consent for participation from 212 organizations of which, 3 to 4 personnel from different departments were randomly chosen by our primary researchers. This mix provided a varied perspective on the presumed relationships. During the data collection phase, we assured the respondents that their involvement in the survey was voluntary in nature and that their responses would be assessed without any disclosure of identity. Finally, of the 1200 questionnaires distributed, we received 624 usable responses of which 224 belonged to domestic Indian organizations and 400 worked with foreign MNCs operating in India. Among the respondents, 263 held the designation of managers while the rest held non-managerial positions. The age-wise distribution was such that the highest number of 203 belonged to the 31–40 years category, followed by 169 of the 41–50 years category, 26–30 years (117) and so on. The average work experience of all the respondents was 6.9 years. As far as their level of education is concerned, 252 were under graduates while 372 were post graduates.

Measures

All survey items were assessed on a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree).

Table 1.

Sample Characteristics

Variables	Categories	Number	%	Average
1. Ownership	Indian	224	35.9
	Foreign MNCs	400	64.1
	Total	624	100.0
2. Designation	Managerial	263	42.1
	Non-managerial	361	57.9
	Total	624	100.0
5. Age of the employees (in year)	Under 25	39	6.3
	26–30	117	18.8
	31–40	203	32.5
	41–50	169	27.1
	51–60	74	11.9
	Above 60	22	3.5
	Total	624	100.0
6. Work experience				6.9
7. Education	Undergraduates	252	40.4
	Postgraduates	372	59.6
	Total	624	100.0

Source: The authors.

Strategic HRM

In order to assess the perceptions on the use of strategic human resource practices in organizations, we utilized a 16-item scale developed by Chen and Huang (2009). This scale reflected the five main aspects/practices of SHRM that included staffing, training, performance appraisal, compensation and participation. The related items are presented in Table 2.

Table 2.

Measurement Scales and Their Properties

Measurement Scales	Loadings	CR	AVE	MSV	ASV
A. CFA Results for SHRM Scale
Selection		0.846	0.647	0.517	0.353
Selection for expertise and skills	0.865
Firm is selective in hiring	0.792
Selection for future potential is preferred	0.752
Performance appraisal		0.866	0.684	0.517	0.367
Performance appraisal is developmental focussed	0.880
Results-based appraisal is used in the organization	0.824
Behaviour-based appraisal is used in the organization	0.777
Training		0.916	0.733	0.375	0.289
Training for new hires	0.903
Comprehensive training policies and programmes	0.866
Training for problem-solving ability	0.828
Formal training activities	0.825
Rewards		0.911	0.773	0.230	0.178
Provision of incentive pay	0.913
There is a link between performance and reward	0.879
Availability of profit sharing	0.845
Empowerment		0.822	0.606	0.415	0.310
Employees suggesting improvements into work	0.816
Employees’ voices are given recognition by the organization	0.776
Employees are allowed to make decisions	0.742
B. CFA Results for SHRM, Knowledge Management Capability, Innovation Performance and Firm Performance
SHRM (Second order construct)		0.855	0.548	0.537	0.407
Selection	0.891
Performance appraisal	0.812
Empowerment	0.710
Training	0.696
Rewards	0.622
Knowledge management capability		0.841	0.641	0.503	0.364
Knowledge is obtained from employees at all levels	0.865
Knowledge is freely shared between employee at all levels	0.856
Effectively utilizing knowledge into practical use	0.665
Innovation performance		0.898	0.746	0.534	0.385
Incorporating technologies into new products	0.901
Developing new technologies	0.872
Facilitating new processes to improve quality and cost	0.816
Firm performance		0.885	0.608	0.183	0.154
Return on equity	0.889
Market share	0.804
Financial strength	0.784
Profitability	0.782
Customer service	0.615

Source: The authors.

Notes: Factor loadings were significant at 0.001 level.

Model fit statistics for A: χ²/df = 3.58; CFI = 0.962; TLI = 0.954; RMSEA = 0.062.

Model fit statistics for B: χ²/df = 3.75; CFI = 0.922; TLI = 0.914; RMSEA = 0.067.

Knowledge Management Capability

Basing on the work of Chen and Huang (2009), we picked a three-item scale to examine the extent of knowledge management capability in the sampled organizations. Individually, these three items resonated the level to which knowledge is acquired, shared and applied in these organizations.

Innovation Performance

Innovation performance was assessed with a perceptual scale of three items, developed by Ibarra (1993) in a study on how organizations are involved in innovation practices.

Firm Performance

In academic circles, there is constant debate on whether the use of subjective or objective indicators is better to assess firm performance. Several scholars advocate that objective measures provide a more realistic picture of performance indicators (Andreeva & Kianto, 2012; Berrone et al., 2007). But there are others who favour subjective measures under certain circumstances (Haque, 2021; Kengatharan, 2019; Sharabati et al., 2010). On the one hand, objective measures appear less suitable in the context of developing economies due to the presence of factors such as ambiguous financial reporting and lack of market-based monetary reporting (Hoskisson et al., 2000). On the other hand, subjective measures are reported to be less prone to response bias (Sharabati et al., 2010). Further, high positive association has been observed between subjective and objective indicators of firm performance (Venkatraman & Ramanujam, 1986). Considering these arguments, a five-item perceptual scale by Khandwalla (1977) and Som’s (2008) studies to evaluate the performance of the sampled firms, were put to use. The participants were asked to compare the performance of their companies with other firms in the same industry on five indicators over the last three years.

Control Variables

Demographics such as ownership of the firm, employee’ designation and work experience were chosen to put statistical control on the proposed relationships. Ownership of the firm was recorded as domestic Indian = 0 and foreign MNCs = 1. Employee’ designation was categorized under managerial = 0 and non-managerial = 1. Work experience in present the firm was recorded as a continuous variable.

Results

Validation of the Measures

In order to establish the validity and reliability of the study constructs, we ran a Confirmatory Factor Analysis (CFA) thrice. Initially, a first order CFA was executed via AMOS22 on 16 items related to SHRM to establish the unidimensionality of five representative HR practices (selection, performance appraisal, training, rewards and empowerment). Section A of Table 2 reveals the details related to the SHRM scale. The model fit indices presented an acceptable fit: χ²/df (Chi-square to degrees-of-freedom ratio) = 3.58 less than the acceptable value of 5 (Harrison & Rainer, 1996); CFI = 0.962 and TLI = 0.954 higher than the tolerable value of 0.90 (Hu & Bentler, 1999); RMSEA = 0.062 less than the threshold value of 0.80 (Hu & Bentler, 1999). Standardized factor loadings related to the items were statistically significant (p ≤ .001) with values greater than 0.50. The composite reliability value was greater than 0.70 and the average variance extracted was higher than 0.50 (Hair et al., 2010) for each of the five practices. In addition, both, the maximum shared variance (MSV) and the average shared variance (ASV) values were found smaller than the AVE values for each construct. When combined, these statistics established good convergent and discriminant validity for strategic HR practices.

The next step was to create a summative index of SHRM so as to represent the organizations’ simultaneous adoption of strategic HR practices. Accordingly, we ran a second order CFA constituting the aforementioned five HR practices. The CFA results yielded a reasonable fit (χ²/df = 3.51; CFI = 0.937; TLI = 0.931; RMSEA = 0.059), and thus, the appropriateness of using SHRM index as a higher order factor in further analysis was established. Finally, a first order CFA was re-executed on four latent variables: SHRM index, knowledge management capability, innovation performance and firm performance. The CFA results offered an acceptable fit with indices: χ²/df = 3.75; CFI = 0.922; TLI = 0.914; RMSEA = 0.067. Section B of Table 2 reveals the reliability and validity values related to the final four variables. Overall, the statistics represented good convergent and discriminant validity for the study variables.

Addressing Common Method Bias

As the data on the study variables were collected through a single instrument, we could not disregard the probability of common method bias which could affect the study findings. Although we took remedial measures during the data collection phase such as assuring confidentiality to the participants about their responses and not placing the independent and dependent constructs together, we found it apt to use Harman’s single factor method prior to the final data analysis. All the 27 items were loaded on one factor and a first order CFA was executed using AMOS. The model fit statistics presented a very poor fit model (χ²/df = 17.22; CFI = .412; TLI = .414; RMSEA = 0.177), thus, eliminating the probability of the study results being polluted with common method bias to any serious extent.

Descriptive Statistics

Table 3 summarizes the mean, standard deviation and correlation statistics of the proposed variables. The mean scores highlighted the fact that the sampled employees perceived a moderate level of adoption of strategic HR practices in their respective organizations (x̅ = 5.69) and the knowledge management capability (x̅ = 6.07) of the sampled firms showed improvement. The correlation values were found in favour of the proposed linkages between independent and dependent variables. Looking at the high correlations, we attempted to check for multicollinearity between the predictor variables. Multicollinearity diagnostics revealed the variance inflation factor (VIF) statistics to be between 1.12 and 1.28 (far smaller than the problematic value of 10, Hair et al., 2010) and tolerance values with 0.58 being the lowest (greater than the alarming value of 0.20). Overall, these statistics flagged the absence of multicollinearity in our regression models.

Table 3.

Means, Standard Deviations and Correlations (N = 624)

Variables	Mean	SD	1	2	3	4	5	6
1. Designation	–	–	–
2. Ownership	–	–	–0.01	–
3. Work experience	6.9	7.04	0.09**	0.16***	–
4. SHRM	5.69	0.73	–0.04	–0.03	–0.06	–
5. Knowledge management capability	6.07	0.82	–0.17***	–0.01	0.01	0.61***	–
6. Innovation performance	5.98	0.79	–0.12***	–0.01	0.05	0.60***	0.65***	–
7. Firm performance	5.55	0.80	0.02	0.12**	0.06	0.43***	0.35***	0.38***

Source: The authors.

Note: ***p ≤ .001, ** p ≤ .01.

Hypotheses Testing

In order to test the proposed hypotheses, we opted for the conditional process analysis through PROCESS, a macro syntax designed for SPSS by Hayes (2013). Specifically, we used Model 6 which is identified for testing multiple mediations where the path coefficients are estimated using OLS regression and the confidence intervals for direct and indirect paths are generated using 5000 bootstrap samples. It also calculates the effect sizes for the estimated direct and indirect paths. The presence of significant mediation, here, is observed through the non-inclusion of zero in the upper and lower limit of a confidence interval (Hayes, 2013). On the contrary, the inclusion of zero in a confidence interval indicates non-significant mediation in assumed relationships. The path coefficients and confidence intervals predicted through OLS regression and bootstrap procedure via PROCESS are presented in Tables 4 and 5 respectively.

Table 4.

Mediation Results Estimated Through OLS Regression Using PROCESS

Independent Variables	Coefficient	Standard Error	Lower CI	Upper CI
Model 1: Dependent Variable = Knowledge Management Capability (R² = 40.2%)
Designation	–0.298***	0.060	–0.417	–0.178
Ownership	0.010	0.063	–0.113	0.134
Work experience	0.005	0.003	–0.001	0.012
SHRM	0.716***	0.037	0.644	0.788
Model 2: Dependent Variable = Innovation Performance (R² = 49.2%)
Designation	–0.085	0.070	–0.224	0.052
Ownership	–0.254*	0.072	–0.166	–0.115
Work experience	0.008*	0.003	0.001	0.014
SHRM	0.470***	0.053	0.366	0.573
Knowledge management capability	0.545***	0.045	0.455	0.634
Model 3: Dependent Variable = Firm Performance (R² = 21.7%)
Designation	0.087	0.081	–0.072	0.247
Ownership	0.281***	0.084	0.116	0.446
Work experience	0.007	0.004	–0.001	0.015
SHRM	0.611***	0.049	0.516	0.707
Model 4: Dependent Variable = Firm Performance (R² = 24.1%)
Designation	0.148	0.082	–0.011	0.309
Ownership	0.282***	0.083	0.121	0.446
Work experience	0.007	0.004	–0.001	0.015
SHRM	0.426***	0.065	0.298	0.553
Knowledge management capability	0.084	0.059	–0.031	0.199
Innovation performance	0.146***	0.046	0.054	0.237

Source: The authors.

Notes: CI represents 99% bias-corrected bootstrapped confidence intervals.

Model 3 highlights the total effect of SHRM on firm performance and Model 4 highlights the mediated direct effect of SHRM on firm performance.

***p ≤ .001, * p ≤ .05.

Table 5.

Indirect Effects of SHRM on Firm Performance Through Mediators

Indirect Effects	Effect	Boot SE	BootLLCI	BootULCI
Total effect	0.185	0.046	0.094	0.278
SHRM ® KMC ® FP	0.060	0.046	–0.028	0.152
SHRM ® KMC ® IP ® FP	0.057	0.021	0.022	0.103
SHRM ® IP ® FP	0.069	0.027	0.022	0.127

Source: The authors.

Note: KMC: Knowledge management capability; IP: Innovation performance; FP: Firm performance; BootLLCI: Bootstrapped accelerated lower limit confidence interval; BootULCI: Bootstrapped accelerated upper limit confidence interval.

The regression results in Table 4 offer four models to explain the statistically significant relationships among the study variables. Considering the control variables first, the significant effect of designation (in Model 1 for knowledge management capability), work experience (in Model 2 for innovation performance) and ownership of the firms (in Models 3 and 4 for firm performance) highlighted the importance of these demographics in exerting control over the proposed relationships. We then began examining the significant effects for our main study variables. H₁ predicted a positive relationship between the SHRM and the knowledge management capability of a firm. In Model 1, the path coefficient of SHRM (β = 0.716, p ≤ .001) was positively significant for knowledge management capability, thus, supporting H₁. In Model 2, we found significant positive effects of SHRM (β = 0.470, p ≤ .001) and knowledge management capability (β = 0.545, p ≤ .001) on innovation performance, hence, supporting H₂ and H₃. Model 3 depicted the significant total (including both direct and indirect) effects of SHRM (β = 0.611, p ≤ .001) on firm performance. Coming to Model 4, we did not find any significant effect of knowledge management capability (β = 0084, not significant) on firm performance, which implies that it could not support H₄, but there were indications of a positive and significant effect of innovation performance (β = 0.146, p ≤ .001) on firm performance, supporting H₅. We could easily see the traces of traditional partial mediation in Model 4 as the path coefficient of SHRM was reduced (from β = 0.611, p ≤ .001 to β = 0.426, p ≤ .001) but remained significant. Overall, these four models hinted at the existence of both direct and indirect paths in the relationship between SHRM and firm performance.

In order to establish the mediation hypotheses, we put into account the calculated effect sizes and confidence intervals derived at 99% significance level with the help of the bootstrap procedure. Table 5 presents the mediated or indirect effects of knowledge management capability and innovation performance in the relationship between SHRM and firm performance. The total indirect effect constituting all the indirect/mediated paths was significant with an effect size = 0.185 as zero was not present in the calculated confidence interval (BOOTLLCI = 0.094, BOOTULCI = 0.278). Following the single mediated paths, we did not find knowledge management capability acting as a mediator in the SHRM-performance relationship as zero existed in the related confidence interval (BOOTLLCI = –0.028, BOOTULCI = 0.152), and hence, could not support H₆. But we observed innovation performance to be significant mediator in the SHRM-performance relationship, indicated by the absence of zero in the attached confidence interval (BOOTLLCI = 0.022, BOOTULCI = 0.127), thus, providing support for H₇. We further found significant evidence of a sequential mediated path via knowledge management capability and innovation performance on the SHRM-performance relationship (BOOTLLCI = 0.022, BOOTULCI = 0.103), confirming the H₈. Overall, the results provided evidence for one significant direct path and two significant indirect (partially mediated) paths in the relationship between SHRM and firm performance. Figure 1 displays the final multiple mediation model that includes both, the direct and indirect paths with their effect estimates.

Figure 1.

Source: The authors.

Supplementary Analyses

Based on the knowledge that the practices/components in the SHRM bundle may have diverse effects, we decided to check if the direct and indirect effects vary when we replace the SHRM bundle/index with individual HR practices. A similar bootstrap procedure, as explained in the previous section was applied five times, taking individual HR practice as an independent variable. Table 6 presents the direct and indirect effects of five strategic HR practices that include selection, training, appraisal, rewards and empowerment on firm performance. The analyses led to some remarkable observations. Taking into account the effect sizes related to the total (both direct and indirect) effects of all five HR practices, we found that selection (β = 0.409, p ≤ .001) emerged as a prominent practice in exerting a positive effect on firm performance, followed by appraisal (β = 0.400, p ≤ .001) and rewards (β = 0.371, p ≤ .001). In the case of direct effects, all HR practices excluding empowerment, had a positively significant relationship with firm performance. This is indicative of full mediation in the case of empowerment practice. Interestingly, all the three indirect paths (i.e., first via knowledge management capability, second via innovation performance and third via both knowledge management capability and innovation performance in sequence) were significant for all the five HR practices constituting the SHRM bundle as none of the calculated confidence intervals for the indirect effects contained a zero (see Table 6). Summing up, we find two inferences from these analyses. They are mediation effects of empowerment on firm performance and singular mediated effects of knowledge management capability on HR practices-performance relationships. We did not observe the same in our estimated mediation model. These supplementary results established that individually, strategic HR practices exert a differential direct and indirect effect on firm performance.

Table 6.

Direct and Indirect Effects Relating Individual Strategic HR Practices to Firm Performance

Nature of Effects		Selection	Appraisal	Training	Rewards	Empowerment
Total Effect (direct + indirect)	Effect	0.409***	0.400***	0.274***	0.371***	0.280***
	SE	0.039	0.046	0.038	0.027	0.051
Direct effect	Effect	0.203***	0.166**	0.091*	0.289***	0.020 (n.s.)
	SE	0.052	0.054	0.042	0.029	0.055
Total indirect effect size	Effect	0.207	0.234	0.182	0.081	0.260
	Boot SE	0.035	0.034	0.028	0.018	0.033
	BootLLCI	0.140	0.170	0.132	0.051	0.199
	BootULCI	0.278	0.305	0.245	0.122	0.329
KMC indirect effect size	Effect	0.089	0.096	0.079	0.031	0.121
	Boot SE	0.035	0.035	0.029	0.016	0.039
	BootLLCI	0.026	0.031	0.027	0.003	0.048
	BootULCI	0.162	0.171	0.141	0.066	0.205
IP indirect effect size	Effect	0.076	0.070	0.036	0.019	0.041
	Boot SE	0.026	0.023	0.014	0.008	0.019
	BootLLCI	0.027	0.031	0.013	0.006	0.010
	BootULCI	0.131	0.124	0.070	0.040	0.086
Sequential indirect effect size (both KMC and IP)	Effect	0.041	0.068	0.068	0.032	0.097
	Boot SE	0.015	0.019	0.017	0.010	0.022
	BootLLCI	0.016	0.035	0.039	0.014	0.059
	BootULCI	0.074	0.110	0.107	0.056	0.147

Source: The authors.

Notes: ***p ≤ .001, ** p ≤ .01, * p ≤ .05.

n.s.: Non-significant

Discussion

The present study is an endeavour to understand the ways by which SHRM provides valuable benefits and creates a strategic advantage for the firm. The outcomes of this study reveal that SHRM creates this advantage by significantly contributing to knowledge management capability, innovation performance and firm performance.

This study draws attention to a broad spectrum of predictors. The results demonstrate that SHRM practices including selection, performance appraisal, training, rewards and empowerment have a positive influence on knowledge management capability. As Gope et al. (2018) have rightly expressed, being concerned with only the technical aspects of the business do not contribute much to knowledge management capability of the organizations; human aspects need to be given equal importance. Lei et al. (2021) have also advocated the need for HRM practices to develop the knowledge management capacity of an organization. Through effective HRM practices, an environment of knowledge acquisition and transfer can be created in the organization (Özbağ et al., 2013). Further, the results reveal that SHRM is a significant predictor of innovation performance. This study builds upon and strengthens the concept of ‘best practices’ as given in previous studies which postulates that strategically adopting a universal set of human resource practices can enhance innovation performance in an organization (Diaz-Fernandez et al., 2017; Shipton et al., 2005).

As has been substantiated, innovation performance mediates the relationship of SHRM and firm performance. Al-Sa’di et al.’s (2017) study of manufacturing organizations has also reported similar findings, wherein the effects of knowledge management on operational performance were found to be mediated by process innovation. A longitudinal study of Diaz-Fernandez et al. (2017) has observed that two practices of HRM, language training and overall compensations and benefits have a positive effect on firm performance through innovation performance measured along the line of new patents. Thus, Bondarouk and Looise (2005) have rightly stated that HRM can significantly contribute to innovation in organizations. However, this source is yet to be optimally utilized in organizations.

As we probe further, we also encounter contrasting results. One surprising finding is that knowledge management capability does not exert direct effect on firm performance, nor does it individually mediates the relationship between SHRM and firm performance. This finding contradicts previous pioneering previous studies which have shown knowledge management capacity to be direct contributor to higher firm performance (Birasnav, 2014; Lee & Lee, 2007; Lin & Kuo, 2007). In support of our finding, a few scholars such as Zack et al. (2009) and Darroch (2005) have previously mentioned that well developed knowledge management practices alone might not lead to better firm performance. Our sequential mediation results strengthen this viewpoint. Here, we have found the presence of statistically significant sequential mediation through knowledge management capability and innovation performance. Henceforth, the study results do not deny the significance of knowledge management capability in enriching firm performance; they only reflect that the nature of this relationship might be different. The study reinforces the findings of previous studies demonstrating that knowledge management proves effective for firm performance when transformed into innovation (Aboelmaged, 2014; Gürlek & Çemberci, 2020). Extending the discussion, Sung and Choi (2018) advocate that SHRM should facilitate the flow of knowledge management activities towards organizational innovation. HRM practices are the key predictor in motivating employees to acquire and share knowledge and to utilize that knowledge for innovating products and production technology (Shipton et al., 2005) that would potentially contribute to higher firm performance.

To gain further understanding of the direct and indirect effects of individual SHRM practices on firm performance, let us reflect on the supplementary analyses. These analyses reveal that among the five SHRM practice, ‘selection’ proves to be most effective in contributing towards firm performance. Chand and Katou (2007) have also revealed that, among HRM practices ‘recruitment and selection’ has the highest correlation with organizational profitability. Another interesting finding of the analyses is that ‘empowerment’ does not have a direct impact on firm performance, instead it indirectly affects firm performance through complete mediation of knowledge management capability and innovation performance. One more surprising inference from the supplementary analyses is that knowledge management capability mediates the effect of all five individual SHRM practices on firm performance. Conversely, this mediated path did not exist when we studied the relationship between the SHRM bundle and firm performance. All of these additional findings highlight the importance of each individual practice in the SHRM bundle, proving the effectiveness of each practice in relation to the outcome variables.

Implications of the Study

The study presents some noteworthy theoretical and practical implications. This study is an effort to theoretically uncover the ‘black-box’ of the linkage between HRM and firm performance by throwing light on the new mediating mechanisms under this well-established relationship. Although prior research has proved SHRM to be significant contributor to firm performance (Chand & Katou, 2007; Ngo et al., 2008), the inclusion of knowledge management capability and innovation performance as mediators broadens our understanding of how SHRM indirectly affects firm performance. The current study show how the effects of SHRM on firm performance are attenuated through serial and parallel mediation of knowledge management capability and innovation performance. Further, the study contributes to the literature on knowledge management by providing new insights on the relationship between knowledge management capability and firm performance. The results of this study do not support the well-established belief that knowledge management capability is direct contributor to firm performance (Al-Sa’di et al., 2017; Lin & Kuo, 2007; Tseng & Lee, 2014). Instead, our findings reveal that the same is effective in improving firm performance only when it is utilized for innovation performance. One possible reason for this may lie in the nature of the knowledge transfer that take place in foreign MNCs and domestic firms (Lai & Sarkar, 2017). The knowledge that firm acquire through transfer of knowledge from the parent firm in the home country of a multinational to the firm in the host country (India) is largely dependent on the quality of employees in the host nation. The employees, thus, become the key source of transferring, interpreting and utilizing the knowledge in a manner they find pertinent. This is perhaps the reason we see differential effects of knowledge management capability in our study. The study also contributes to the literature on innovation by revealing its antecedents and outcomes. The results exhibit that innovation performance gets enhanced through SHRM and knowledge management capability. Innovation performance thus enhanced, becomes a big contributor for firm performance (Chen & Huang, 2009).

The results present several implications for practitioners too. HR practitioners should put to use HRM practices that strengthen knowledge management capability and innovation. HR managers should manage their employees by putting to good use SHRM practices such as selection, performance appraisal, empowerment, training and rewards. The selection process should aim to fill the existing knowledge gaps by selecting employees with relevant knowledge capabilities (Brelade & Harman, 2001). Selecting candidates who have innovation capability will lead to the reinforcement of innovation performance (Robertson & Hammersley, 2000). The training programmes expedited by the organization must target filling the gaps in existing knowledge (Arunprasad, 2016). Such training programmes that help build the intrinsic capabilities and creativity of employees can enhance innovation performance in organization. A robust organizational reward system should aim to provide individual or group incentives to employees that would motivate them to actively engage in knowledge management initiatives (El-Farr & Hosseingholizadeh, 2019). Similarly, innovation and risk-taking behaviour of employees should also be given recognition (Yahya & Goh, 2002).

Employees need to feel empowered so they can take on the ownership of their job and freely acquire the knowledge required and share it with colleagues without restrictions (Cabello-Medina et al., 2011). This sense of ownership motivates them to break free from routine and try new and innovative ideas. Performance appraisal can also ensure effective knowledge management and innovation performance by the timely measurement of actual innovation and knowledge behaviour (Tan & Nasurdin, 2011). The top management should also recognize the critical role SHRM plays in firm performance. HR practitioners must be allowed to play a pivotal role in building knowledge management and innovation strategies. The results demonstrate that knowledge management capability does not have any direct effect on firm performance unless it is transformed to innovation performance. Thus, organization must create strategies to exploit its knowledge management capability by obtaining, sharing and utilizing knowledge aimed at innovations.

Limitations

The present study has several limitations that future studies can improve upon. One major limitation of the study lies in its cross-sectional research design. It is difficult to conclude that the higher performance of the firm is a result of SHRM. This is due to the fact that usually it is the past performance of the organization which is a good predictor of its current performance (Guest, 2011). Several authors have emphasized that longitudinal research designs provide a more accurate picture of reality where innovation or firm performance is concerned (Chen & Huang, 2009; Diaz-Fernandez et al., 2017). An examination of reverse causality will also provide a clearer picture about the relationship between SHRM and firm performance. Another limitation of the study is its dependence on a single source of information for all variables of the study. Gathering information from multiple sources will present a more accurate picture. In the present study, five practices were considered to form a bundle of SHRM. It would be of greater value to extend the study by adding a few more human resources practices which could enhance knowledge management capability, innovation and firm performance. Moreover, it would be interesting to collect information about the adoption of SHRM directly from HR managers instead of focusing on employees’ perceptions of SHRM practices. Another limitation is the fact that only internal variables have been used to assess the effectiveness of SHRM without taking external factors into consideration. Incorporating the effect of external factors such as economic, political, cultural and social factors could provide more clarity on the relationships explored in the study.

Conclusions

The main purpose of this study was to analyse the impact of SHRM on firm performance through knowledge management capability and innovation performance. The study took a step further by uncovering the ‘black box’ of the linkage between HRM and firm performance by demonstrating the channels through which SHRM influences firm performance. The study found SHRM and innovation performance to be critical determinants in enhancing the performance of an organization while knowledge management capability was not found to have any direct impact on firm performance. However, it was observed that knowledge management capability and innovation performance serially mediate between SHRM and firm performance. This study provides a deeper understanding of how organizations could manage human resources and increase the organizational knowledge in order to enhance innovation and firm performance.

Footnotes

Declaration of Conflicting Interests

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

Funding

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

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