Performance indices for quantitative measurement of R&D results in private construction companies

Abstract

As the investment in Research and Development (R&D) projects is increasing in private construction companies in Korea, the necessity to evaluate the effects of the investment in terms of company's finance is growing. However, there has not been an applicable system to properly and quantitatively measure the result and effectiveness of R&D efforts in Korea. In order to evaluate R&D results, R&D performance indices and their monetarily performance are required. Therefore, the purpose of this study is to develop performance indices capable of measuring the R&D performance quantitatively in private construction companies. To accomplish this purpose, development direction of performance indices has been established, through the analysis on current R&D measurement standards in major Korean private construction companies and through carrying out questionnaire survey. The development of performance indices has been implemented through the applicability evaluation of public R&D performance indices, the analysis on evaluation criteria in major Korean private construction companies, and the analysis on actual data of R&D projects of a Korean private construction company. 20 Performance indices are proposed by 5x5 matrix with performance areas (such as productivity, knowledge accumulation, application, publication, and standardization) and R&D purposes (such as product development, construction process/method development, specification development, standardization development, and others). The effectiveness of proposed performance indices was verified to be appropriate for R&D projects in private construction companies in Korea, through questionnaire survey with evaluation criteria such as comparability, measurability and validity. The primary contribution of this study is to establish private R&D performance indices essential to convert the R&D efforts into monitory term. As a result, they can help company executives to make decision to invest on R&D based on the reliable quantitation of R&D outcome.