Dilemmas of R&D investment risks and sustainability in the clean-tech economy : Evidence from Nasdaq clean edge index components

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)139-152
Journal / PublicationInternational Journal of Green Energy
Issue number2
Online published24 Jan 2022
Publication statusPublished - 2023


Clean energy companies often require more costly investment in technology innovation than traditional energy companies, which poses higher technological risks. Therefore, many inconclusive debates have arisen concerning whether the R&D investment can generate sustained returns for such companies. This paper adopts progressive modeling steps to address the problem by using a modified Cobb-Douglas production function, System Generalized Method of Moments (SYS-GMM) approach, and fixed-effect panel threshold model. The role of R&D investment; the non-linear relationship between revenue, innovation, efficiency, and risk; as well as the corresponding threshold effects in clean and traditional energy companies are analyzed. 840 firm-year observations of clean energy companies from the NASDAQ Clean Edge Index are collected and screened, and compared with 280 firm-year observations of listed traditional energy companies in the U.S. Moreover, four types of clean energy companies, comprising green energy, wind power, water, and smart grid companies, are calculated and summarized separately. The results show that, for clean energy companies, long-term R&D intensity is beneficial to returns, shortening the cash conversion cycle (CCC) value, and reducing the financial leverage can produce a positive effect on return on assets (ROA), while different types of clean energy companies are advised with tailor-made portfolio strategies. For traditional energy companies, controlling the financial leverage while properly increasing CCC can help improve their ROAs. In this context, policy recommendations are provided for stakeholders to optimize their investment strategies in various clean and traditional energy enterprises according to the time-lag effect and threshold effect.

Research Area(s)

  • clean energy, R&D investment risk, SYS-GMM, threshold effect

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