Academic journal article Innovation: Organization & Management

The Impact of Efficiency Parameters on Firms' Innovative Activities: Evidence from Korean Firm-Level Data

Academic journal article Innovation: Organization & Management

The Impact of Efficiency Parameters on Firms' Innovative Activities: Evidence from Korean Firm-Level Data

Article excerpt

(ProQuest: ... denotes formulae omitted.)

INTRODUCTION

With the premise that patent data are reliable indicators of innovative output, the empirical analysis of R&D-patents relationship is useful for monitoring the efficiency of innovative activities. However, the R&D-patents relationship should be cautiously analyzed because the difference in patent counts (or patents per R&D expenditure) can be interpreted to reflect variations not only in R&D productivity but also in the propensity to patent. People with a skeptical view of the usefulness of patent data as an indicator of innovative output argue that patent counts reflect variations in the propensity to patent to a greater degree than variations in R&D productivity. That is, patents cannot capture all of the results of R&D efforts undertaken by a firm, and patent applications may be the product of firms' strategic choice (e.g., Kondo 1999; Hagedoorn & Cloodt 2003; Tsai 2005; Beneito 2006).

Therefore, with any factors that influence a firm's patenting performance, it is necessary to distinguish their effect on the firm's propensity to patent from their effect on the firm's R&D productivity. We can obtain a significant implication as to improving a firm's innovative output if we identify factors that are more closely associated with a firm's R&D productivity and that are subject to change in a relatively short period through a firm's investment or government support.

Therefore, we ask two main questions: What are the main sources of heterogeneity in firms' patenting performance? And, among all the factors that affect firms' patenting performance, which factors are more closely linked to a firm's R&D productivity than the propensity to patent, and can they be changed by a firm's investment or government support in a relatively short period?

As our response, we conduct a two-step analysis. First, using a data set from 1255 firms with non-zero R&D expenditures (including 727 firms with non-zero patents) in Korea, we estimate general R&D-patent relationship. We especially focus on the factors that may be changed in a relatively short period as explanatory variables in our estimation model. In second analysis, using empirical model inspired by Rassenfosse and van Pottelsberghe (2009), we identify distinctive impacts of the factor on propensity to patent and R&D productivity. In this paper, we define the factors that potentially influence firm's innovative output through 'R&D productivity' rather than 'propensity to patent' as 'efficiency parameters'.

The empirical results show that the difference in firms' patenting performance is attributable to not only the factors associated with the propensity to patent but also those affecting R&D productivity, and 'in-depth patent searches' and 'revenue splitting policy for employee-inventors' play important roles in enhancing R&D productivity.

This paper extends the research on the relationship between R&D spending and patent counts by considering efficiency parameters, and provides much information on R&D-patent relationship and policy implications about firm's innovation activity.

The rest of this paper is organized into four sections. In the first part, we present our review of previous literature using patent data including studies on the R&D-patent relationship. Second, we present the hypotheses used in this study, and describe the data and estimation model used. In the next section, we offer the main findings gained through the estimation model. Finally, we conclude with a discussion of the policy implications of the findings.

LITERATURE REVIEW

Although patent data is subject to a longstanding debate regarding its usefulness, it has been frequently used as a resource for studies on technological change and innovation (Griliches 1990). In addition, patent data contains a variety of useful information on the inventor, assignee, international patent classification (IPC) and much more. …

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