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This research aims to analyze how a firm's technological diversification strategies influence its financial performances, in terms of 'technological diversification' in broad technology sectors and 'technological concentration' on its own core technology, especially in the case of Korean large firms. The data used in the analysis were panel data encompassing the years between 1990 and 2006, which linked Korean firms' patent information registered in the United States Patent and Trademark Office to the financial data of those firms collected from Korea Investors Service, Inc. (Kis-Value). For the estimation of the panel data, a fixed effect model, which considers the individual firms' own effect on the financial performance, was used. Tobin's q was used as a dependent variable representing firm performance, while 'broad technology diversity' and 'core technology diversity' were used as the focal explanatory variables. The results show that a firm seeking to have more technological assets should invest in a broad technological diversification strategy in its search for new business opportunities; it should likewise concentrate on the core technology in order to maintain its financial performance.patent, technological diversification, technological concentration, fixed effect model, Tobin's q,

A copper-embedded reduced graphene oxide (CRGO) fiber-based sensor exhibited chemical sensitive/temperature insensitive or chemical insensitive/temperature sensitive characteristics, depending on the Cu concentration in the CRGO.

It is well known from previous research activities that R&D collaboration among economic actors for knowledge production is very important. An accompanying analysis of the impact of R&D collaboration on innovative performance has to be conducted for transferring knowledge to the globalized knowledge-based economy. When we first investigated previous research concerning R&D collaboration, we found some limitations in the analysis methodology. In order to overcome these limitations in previous research, we applied a Bayesian network for analyzing the impact of R&D collaboration in Korean firms on their innovative performance.