earticle

영어

This paper describes industrial sector efficiency comparison by technology level through input oriented DEA methodology and shows a differentiated cause-effect relationship by independent variables in each technology level (OECD industrial classification of R&D intensity: low, medium-low, medium-high, and high). In Korea manufacturing industry, sectoral DEA approach of technical efficiency by technology level was un-precedent and could guide productivity improvement idea in a different technology level sector. In the efficiency comparison, medium-high technology sector is more efficient than medium-low and low technology sectors, but high technology sector’s is lower than medium-high sector due to more diverse employee and researcher structure. In a low technology sector, firms could improve efficiency through R&D investment. The other insight is that R&D investment, employee & researchers does not always improve efficiency especially in inefficient firms, which indicated that firms have to optimize their input factors effectively, sometimes reducing or transferring resources such as R&D investment according to its technology level. R&D investment would improve technical efficiency only in low-technology firms. In a cause and effect of efficiency, high tech. firms would have to choose a production scale to improve their scale efficiency. So far, “technology regime” topic of Marlerba & Osenigo(1996, 1997) has been researched with STEPI’s business innovation survey outcome by many researchers and indicated that R&D investment could induce a different outcome based on innovation condition and knowledge basement. In the meantime, Efficiency related research has focused on only firm-level studies without level-up to technology level. Thus, a combination of the both would be a new approach, which would be able to give a benchmarking idea to inefficient firms by technology level. For a future study, it would be meaningful to study an innovation and knowledge basement condition role with sub-industries categorized by sectoral innovation system. But, I also have to acknowledge that R&D investment and revenue at a same year could be a statistical issue of multi-collinearity though it comes from a survey data sample’s restriction.