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

被引:6
|
作者
Sun, Wen [1 ]
Zhang, Xiaoling [1 ,2 ]
Hazarika, Natasha [3 ]
机构
[1] City Univ Hong Kong, Dept Publ Policy, Hong Kong 999077, Peoples R China
[2] City Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China
[3] Indian Inst Technol Guwahati, Dept Humanities & Social Sci, Gauhati, India
关键词
R&D investment risk; clean energy; SYS-GMM; threshold effect; PEAK CO2 EMISSIONS; GOVERNMENT SUBSIDIES; FIRM PERFORMANCE; ENERGY INDUSTRY; INNOVATION; IMPACT; COMPANIES; PERSPECTIVE; DYNAMICS; PROFITS;
D O I
10.1080/15435075.2021.2023883
中图分类号
O414.1 [热力学];
学科分类号
摘要
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.
引用
收藏
页码:139 / 152
页数:14
相关论文
共 6 条
  • [1] Role of Ownership Structure in Firm R&D Investment Decision: Evidence from Chinese High-tech Industry
    Usman, Muhammad
    Xiao, Shufang
    Ashraf, Rana Umair
    Lian, Fenni
    [J]. 2017 4TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ECONOMICS SYSTEM AND INDUSTRIAL SECURITY ENGINEERING (IEIS), 2017,
  • [2] R&D investment along the firm life-cycle: new evidence from high-tech industries
    Yang, Cheng
    Hua, Ye
    Hua, Zhongsheng
    [J]. INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT, 2022, 88 (2-4) : 353 - 388
  • [3] Political embeddedness, socioemotional wealth, and R&D investment in family firms: Evidence from China as a transition economy
    Meng, Shuang
    Gomez-Mejia, Luis R.
    Yi, Jingtao
    [J]. JOURNAL OF FAMILY BUSINESS STRATEGY, 2024, 15 (03)
  • [4] Long-run relationship between R&D investment and environmental sustainability: Evidence from the European Union member countries
    Paramati, Sudharshan Reddy
    Alam, Md Samsul
    Hammoudeh, Shawkat
    Hafeez, Khalid
    [J]. INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, 2021, 26 (04) : 5775 - 5792
  • [5] The Relationship Between R&D Investment and Firm Profitability Under a Three-Stage Sigmoid Curve Model: Evidence From an Emerging Economy
    Yang, Kuo-Pin
    Chiao, Yu-Ching
    Kuo, Chih-Chung
    [J]. IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2010, 57 (01) : 103 - 117
  • [6] Regional institutional environment and R&D performance: Evidence from marketization index of China's provinces and panel data of high-tech manufacturing firms
    Song, Bo
    Yuan, Kun
    Jin, Yiwen
    Zhao, Liangjie
    [J]. CHINESE MANAGEMENT STUDIES, 2024,