Relation of R & D expense to turnover and number of listed companies in all industrial fields

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Abstract

In this research, we studied the relation of research and development (R & D) investment to turnover and number of listed companies by using the financial information of publicly listed enterprises in all industrial fields of the world from 2007 to 2015. First of all, the present condition (as of 2017) of number and distribution of publicly listed enterprises was investigated. Secondly, the industrial areas having top 10 average turnovers and R & D expenses during 9 years (2007 ~ 2015) were analyzed by using their descriptive statistics and CAGR values. Finally, the analyses of correlation and linear regression were performed by using average R & D expense (independent variable) and average turnover or the number of listed enterprises (dependent variables). In other words, two models with different combination of independent and dependent variables (Model A: R & D expense and turnover, Model B: R & D expense and number of listed firms) were developed for the statistical analyses. As a result, it was confirmed that both the turnover and the number of listed companies were influenced by the R & D investment because the coefficients of determination for Model A and Model B were 0.686 and 0.612, respectively (both pvalues < 2.2 × 10-16). From the results of this study, it is expected that the unlisted firms (e.g., start-up companies) can build the basis of their growth and innovation when they invest in R & D higher inducing the increases in (1) turnover and (2) probability of becoming a listed firm. Thus, the financial information of enterprises can be utilized effectively as the quantitative evidence in order to develop the research model and methodology related to their growth and innovation.

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Park, J. H., Lee, B., Moon, Y. H., Kim, G. S., & Kwon, L. N. (2018). Relation of R & D expense to turnover and number of listed companies in all industrial fields. Journal of Open Innovation: Technology, Market, and Complexity, 4(1). https://doi.org/10.1186/s40852-018-0093-4

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