Do external risk factors increase or decrease country-level R&D efficiency: focused on air pollution and job insecurity?

ABSTRACT

The national resources that can be used in the national innovation system are limited. Therefore, interest in R&D efficiency is increasing in terms of how well-limited resources are utilised to achieve innovation. This study analyzed the effects of external risk factors on a country's R&D efficiency using the DEA-Tobit regression model. Air pollution was set as an environmental risk, and job insecurity was selected as a social risk. The results showed a positive correlation between R&D efficiency and both risk factors. In the case of environmental risks, long-term R&D investments or technology development due to strong regulations have affected R&D efficiency. Social risks have served as motivation for high performance. This study provides implications that policymakers should consider the impact of risk on performance and manage it through organisation and monitoring.

KEYWORDS:

• R&D efficiency
• air pollution
• job insecurity
• DEA-Tobit

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No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

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Notes on contributors

Sangpil Yoon

Sangpil Yoon is a Ph.D. candidate at Korea Advanced Institute of Science and Technology (KAIST). He received his master’s degree from KAIST. His research interests are technology commercialisation, performance management, and R&D efficiency. His research papers have been published in global leading journals such as Technovation and Science & Public Policy.

Yanghon Chung

Dr. Yanghon Chung is a full professor at Korea Advanced Institute of Science and Technology (KAIST). He received his Ph.D. from Georgia State University and has expertise in performance management issues in the context of sustainable R&D, environmental innovation, alternative energy development, and government policy.

Seunghun Han

Dr. Seunghun Han is a full professor at Korea Advanced Institute of Science and Technology (KAIST). He received his Ph.D. from University of Central Florida and has expertise in finance in the context of corporate governance, valuation, and intellectual property management.

Chungwon Woo

Dr. Chungwon Woo is a head of Research Project Planning Team at the Science and Technology Policy Institute. His research interests are R&D performance management and IT management by using artificial intelligent and blockchain.