Next Article in Journal
Weak signal detecting of industry convergence using information of products and services of global listed companies - focusing on growth engine industry in South Korea
Previous Article in Journal
Enhancing green loyalty towards apparel retail stores: A cross-generational analysis on an emerging market
 
 
Journal of Open Innovation: Technology, Market, and Complexity is published by MDPI from Volume 4 Issue 2 (2018). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Springer.
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

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

1
Korea Institute of Science and Technology Information (KISTI), 66 Hoegi-ro, Dongdaemun-gu, Seoul 02456, Republic of Korea
2
Korea Institute of Science and Technology Information (KISTI), 245 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
*
Author to whom correspondence should be addressed.
J. Open Innov. Technol. Mark. Complex. 2018, 4(1), 9; https://doi.org/10.1186/s40852-018-0093-4
Submission received: 28 September 2017 / Accepted: 14 March 2018 / Published: 21 March 2018

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.
Keywords: Correlation; Linear regression analysis; R&D investment; Turnover; Publicly listed enterprises; US SIC primary code; ORBIS database Correlation; Linear regression analysis; R&D investment; Turnover; Publicly listed enterprises; US SIC primary code; ORBIS database

Share and Cite

MDPI and ACS Style

Park, J.-H.; Lee, B.; Moon, Y.-H.; Kim, G.; Kwon, L.-N. Relation of R&D expense to turnover and number of listed companies in all industrial fields. J. Open Innov. Technol. Mark. Complex. 2018, 4, 9. https://doi.org/10.1186/s40852-018-0093-4

AMA Style

Park J-H, Lee B, Moon Y-H, Kim G, Kwon L-N. Relation of R&D expense to turnover and number of listed companies in all industrial fields. Journal of Open Innovation: Technology, Market, and Complexity. 2018; 4(1):9. https://doi.org/10.1186/s40852-018-0093-4

Chicago/Turabian Style

Park, Jun-Hwan, Bangrae Lee, Yeong-Ho Moon, GyuSeok Kim, and Lee-Nam Kwon. 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, no. 1: 9. https://doi.org/10.1186/s40852-018-0093-4

Article Metrics

Back to TopTop