The literature has shown that open innovation (OI) can be a winning strategy in improving firm performance. However, in order to adopt and implement it, managers need to resolve practical problems, such as understanding the role played by OI capacities and openness on firm performance. In response to these needs, this study aims to investigate the hierarchical relationships between openness, OI capacities and performance using a structural equation model approach. This paper also attempts to compare the levels of openness between firms in different industries to discover similarities and differences in OI phenomena. The analysis of data obtained from a survey of Korean firms shows significant interrelations between openness, OI capacities and firm performance. Our results go further in developing understanding of the building blocks on which successful OI is built and particularly suggest that desorptive capacity which underpins the out-bound OI process, is in turn strongly supported by knowledge management capacity. It is hoped that the results of this study can enrich our understanding of the OI mechanism and provide managerial and policy implications. ARTICLE HISTORY

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Credit scoring models are usually formulated by fitting the probability of loan default as a function of individual evaluation attributes. Typically, these attributes are measured using a Likert-type scale, but are treated as interval scale explanatory variables to predict loan defaults. Existing models also do not distinguish between types of default, although they vary: default by an insolvent company and default by an insolvent debtor. This practice can bias the results. In this paper, we applied Quantification Method II, a categorical version of canonical correlation analysis, to determine the relationship between two sets of categorical variables: a set of default types and a set of evaluation attributes. We distinguished between two types of loan default patterns based on quantification scores. In the first set of quantification scores, we found knowledge management, new technology development, and venture registration as important predictors of default from non-default status. Based on the second quantification score, we found that the technology and profitability factors influence loan defaults due to an insolvent company. Finally, we proposed a credit-risk rating model based on the quantification score.

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The number of students graduating from accredited programs has been increasing annually since the first students graduated from accredited engineering programs in Korean universities in 2004. In this paper, we evaluate the effect of engineering education accreditation by the Accreditation Board for Engineering Education of Korea (ABEEK). We developed performance evaluation indices based on the balanced scorecard concept and applied the proposed indicators to graduates, faculty, and industry employers to see if there are significant differences between accredited and non-accredited groups. Overall, regardless of survey object, engineering education accreditation was perceived to contribute to the elevation of engineering and science and the level of national growth. However, the differences between accredited and non-accredited groups for some key performance indicators were statistically insignificant. The results of this paper are expected to provide crucial feedback information for the improvement of engineering education accreditation in Korea.