Key points are not available for this paper at this time.
Basically, there are two main goals that the company wants to achieve simultaneously, namely maximizing profits for the welfare of shareholders on the one hand and employee satisfaction on the other hand. However, the facts show that management has long placed non-financial factors in a disproportionate manner compared to the treatment of financial factors. The aim of this research is to present a perspective through analysis of the interaction of a continuum of non-financial and financial variables in creating an economic value added for the company. The population is the largest national construction companies listed on the Indonesia Stock Exchange (IDX) in 2015 - 2019. Using the purposive sampling method, more than 50 percent of the companies became the research sample. Data analysis based on panel data and processed using Eviews, as well as classic statistical tests (t test and F test). The results provide a perspective regarding the influence of training & development, and cost control on revenue, cost of goods sold, and profitability ultimately on EVA. In terms of the coefficient of determination, it suggests a solid impact from both training and development as well as cost control on the bottom line., R2 = 93 percent influence on Gross Profit, R2 = 82 percent on Net Profit, R2 = 91 percent on NOPAT, there is a significant influence of Gross Profit, Net Profit and NOPAT on EVA respectively with t test 1.96. From the interaction process of the continuum of research variables, with some luck, a combination of results obtained through measures and those based on performance indicators will emerge, starting from non-financial elements to financial elements. This finding is the result of an original approach in modeling the relationship between non-financial variables and financial variables. This research is limited to the construction companies and the research variables only select proxies for human capital elements that are linked to financial performance data.
Raharjo et al. (Mon,) studied this question.