Measuring Human Capital – A meta-analytic structural equation analysis of cause and effects

Intangible resources increasingly gain in importance as critical success factors and drivers of shareholder value. One part of these resources is represented by Human Capital that encompasses knowledge, skills, abilities etc. of a company’s employees. In order to establish thorough understanding of the cause-and-effect relationships concerning this intangible esource, a theoretical framework was developed which draws on human capital theory, otivation theories, turnover models and personality systems. Constructs incorporated are, or example, employee satisfaction, performance, and turnover as well as demographic variables and organizational characteristics.

In the next step, relevant data of 123 selected meta-analytic studies encompassing 1123 bivariate meta-analyses were gathered and, if necessary, integrated via the method of metasynthesis (second order meta-analysis). Thanks to this process, a large pool of published empirical data could be incorporated avoiding a redundant primary data collection. The resulting meta-analytic correlation coefficients formed the basis for further empirical analysis by means of structural equation modelling. Thereby, three overlapping causal models were separately specified and analysed. The results indicate acceptable model fits and thus support the hypothesized cause-and-effect relationships. These relationships are regarded as a useful foundation supporting the development of efficient systems for measuring and managing Human Capital as an intangible resource, like e. g. in Balanced Scorecards or Intellectual Capital Statements.