Training is an area of significant practitioner and academic interest. While it is proposed that training has an impact on financial performance the literature suggests a variety of explanatory processes and pathways. In this paper we integrate the significant body of literature to understand the mechanism that mediates the relationship between training and financial performance.
The purpose of this study is to identify and test the mediating mechanisms through which training influences financial performance. We utilise four theory-driven mechanisms to understand this relationship- human capital, affective, resource and social exchange mechanisms. We selected these four mechanisms for two reasons. First, each mechanism has strong theoretical support within the literature therefore we can enrich the theoretical foundations of training research. To date researchers have investigated a diverse set of mediators however, many were not always strongly based in theory. Second, the four mechanisms have the potential to show how training influence the collective level of employees’ knowledge, skills and abilities (KSAs), their motivational state which inspire employees to feel confident that their efforts will contribute to financial performance, and their resource value which leads to enhanced operational performance and their social exchange with the organisation which influences their desire to stay or leave the organisation. These four mechanisms point to the potential changes that training elicits employees and their value to the organisation.
We used meta-analysis data from 115 studies (including 116 independent studies) to test these mechanisms. We included a combination of studies that included both subjective and objective measures of financial performance thus potentially reducing the problems posed by common method bias. Overall the investigation of four theoretically mediating mechanisms helps to enhance the theoretical foundations of the relationship and to illuminate different ways in which training is converted to financial performance. We cannot however demonstrate causality given that the majority of studies pooled in the meta-analysis used cross-sectional research designs (see Wright, Gardner, Moynihan and Allen, 2005).
First, we created correlation matrices among training, mediating mechanisms and financial performance for each proposed model. Results were presented in Table 1-4 for each respective mediation model. Second, we used the correlation matrices in SEM. Given that sample sizes for different correlations were not identical, we calculated the harmonic mean of the correlation sample sizes (Wiswesaran and Ones, 1995) for mediation analysis (n = 3,656). In order to evaluating the proposed model, we used four established model fit statistics – chi-square (χ2), the root-mean-square error of appromixation (RMSEA), and the comparative fit index (CFI), and the stardardised root-mean-square residual (SRMR) to test the viability of the structura models (Kline, 2005).
Using meta-analytic structural equation modelling (SEM), we identified four core mediating mechanisms: human capital, affective, resource and social exchange to explain the relationship between training and financial performance, with affective outcomes played a crucial role in this mediation process evidenced by its strongest magnitude with training. Of the remaining three mechanisms, the resource mechanism had the strongest positive mediation effects, as results suggested that only labour productivity and innovation was associated with improved financial performance. The data, to be presented in the full conference paper, supported the proposition that training influenced financial performance through human capital, affective, resource and social exchange mechanisms, with affective outcomes played a crucial role in this mediation process evidenced by its strongest magnitude with training (β=0.30, p<0.001). Of the remaining three mechanisms, the resource mechanism had the strongest positive mediation effects, as results suggested that only labour productivity and innovation was associated with improved financial performance. Evidence indicated that human capital and social exchange mechanisms were also important in terms of shaping the training-financial performance linkage, but in a rather ‘undesirable’ way, i.e. as accumulative level of human capital increases or voluntary employee turnover decreases, financial performance was worse off.
The implications of this study provide evidence lending support to the human capital mechanism suggesting that training, general or specific human capital and financial performance are closely and positively associated. However, once the affective mechanism is introduced as an additional motivator that mediates the effect of training on human capital which in turn is related to financial performance, human capital does not affect financial outcome in a way as anticipated, i.e. financial performance decreases as human capital enhances. One possible explanation is that affect mechanism may mediate the effect of training on specific and general human capital in different way. Netherveless, due to a lack of sufficient empirical studies been conducted, we were unable to examine the meta-analysis of the relationship between specific human capital and other variables, and between general human capital and other variables specified in correlation matrix. Hence, future research is encouraged to make some careful distinctions between specific and human capital development, and compare the mediating role of affective mechanism in the impact of training on specific and general human capital that is subsequently linked to financial performance.
