Technological Forecasting & Social Change 170 (2021) 120855 Available online 24 May 2021 0040-1625/© 2021 Elsevier Inc. All rights reserved. Network analysis of robot ecosystems using national information systems Dohoon Kim * School of Management, Kyung Hee University, 26 Kyungheedaero Dongdaemoongu, Seoul 02447, Korea A R T I C L E INFO Keywords: Robot ecosystems National IO data National patent database Network analysis Macroscopic analysis Mesoscopic analysis ABSTRACT The robot sector in many countries has thrived recently thanks to government supports and innovations in various industries. This study, using the patent database to defne the robot sector, reconfgures IO (Input- Output) data to analyze the relationships among various sectors. In particular, we consider the internal description of the robot sector (mesoscopic view) as well as the relationship between the robot and the non-robot sectors (macroscopic view), so that we can not only understand robot ecosystems in various dimensions, but also develop policy insights. For the sake of systematic analysis of the intra- and inter-sector relations as well as the meso-macro links, this study constructs network models and employs several network measures. Our model and analysis present a good case study of Korea to understand the nature of the robot sector and the overall business ecosystem there. This novel approach also contributes to fnding out a promising path that leverages the strengths of intra-sector relations and spreads the impact of the robot sector across the macro relations. 1. Introduction Technological progress propels economic growth and long-term in- dustry changes. Despite burgeoning literature (e.g., Acemoglu et al., 2016; Brynjolfsson and Hitt, 2000; and many), our understanding of how progress in one area is linked to other felds and spread throughout the economy is not perfect, particularly when new technology emerges (e.g., sharing economy platforms like Uber and Airbnb). Robots are also closely related to various economic activities, but our understanding of their impacts on and relationships with other areas is still lacking. Since robots, together with artifcial intelligence and big data, are regarded as a key element in the Industry 4.0 and receive full supports from many governments, it is timely and necessary to conduct study for deeper understanding of robot’s business ecosystem. The potential of robots may be inherent in its innate nature as gen- eral purpose technology (GPT, Bresnahan and Trajtenberg, 1995; Kretschmer, 2012). GPT is characterized by a catalyst for a broad range of technological improvement as well as an enabler of nationwide in- novations. As GPT, robots are expected to promote knowledge creation and diffusion by establishing strong links between frms and their users and suppliers. Accordingly, the robot sector creates value by developing more effcient processes. 1 Indeed, robotics and automation are dramatically reshaping the global economy and building its own business ecosystems around the world (Atkinson, 2019; McKinsey, 2018; MOITE, 2019). With the pro- liferation of new production methods and innovations such as Industry 4.0, the demand for robots has increased signifcantly around the world in the last few years. The demand for industrial robots seems to have already exceeded 500,000 units by the end of 2018, and this trend will lead to increased demand for service robots (IFR, 2017; MOITE, 2019). Especially in Asian nations, including China, Japan, and South Korea, the demand for robots overwhelms other regions (about 60% of the world’s robots are populated in those countries, Atkinson, 2019; Bank of Korea, 2018(BOK, 2018); Korean Ministry of Industry, 2019(MOITE, 2019)). For example, Japan has six out of the top 10 (in terms of sales revenue) industrial robot manufacturers. In Korea, the number of robots per thousand workers is 60, which is more than twice that of Japan and Germany (in this index, Korea ranks frst in the world; the global average is less than 90). There is also a survey report demonstrating that robot industries are contributing around 3% of GDP growth in OECD countries (BOK, 2018; MOITE, 2019). The current situations and trends suggest that, in the Industry 4.0 era, appropriate policies developed based on a more holistic and detailed understanding of the robot ecosystem will have a greater impact on the entire economy. In these backgrounds, the purpose of this study is to develop a framework for analyzing the structural properties of a newly emerging techno-economic sector like the robot sector, thereby suggesting insights into an effective development path. To achieve this goal, we frst * Corresponding author. E-mail address: dyohaan@khu.ac.kr. 1 Our research focuses on the industrial robots. Refer to Table 1 in section 4.1 for the defnition of the robot sector. Contents lists available at ScienceDirect Technological Forecasting & Social Change journal homepage: www.elsevier.com/locate/techfore https://doi.org/10.1016/j.techfore.2021.120855 Received 27 November 2019; Received in revised form 29 April 2021; Accepted 30 April 2021