Abstract:This paper examines the changing industrial ecosystem of smart cities in Korea using both input–output and structural path analysis from 1960 to 2015. The industry type of the input–output tables used in the Bank of Korea was reclassified into nine categories: Agriculture and Mining, Traditional Manufacturing, IT Manufacturing, Construction, Energy, IT Services, Knowledge Services, Traditional Services and other unclassified. The paper identified the changing patterns of an industrial ecosystem of smart cities… Show more
“…Studies of smart city industrial ecosystems have seen little research and progress worldwide. Most representative and qualitative research studies such as system architecture design and governance establishment were on smart city ecosystems [19,[41][42][43] and smart city innovation ecosystems [44], whereas quantitative studies were on the changes of smart city industry convergence [10,12,44].…”
Section: Previous Study Of Smart City Industrial Ecosystemmentioning
confidence: 99%
“…They join various technologies and industries such as knowledge, construction and energy. Through this, they implement a smart economy, smart environment, smart mobility, and therefore, a smart life [8,10].…”
Section: Introductionmentioning
confidence: 99%
“…Consequently, there have been more studies on the ecology of smart cities recently. Typically, studies have focused on smart city industrial ecosystems [10,12], smart city governance ecosystem [13,14], smart city service and technology ecosystems [15][16][17] and smart city data management ecosystems [18,19]. The study aims to clarify the concepts of enterprise architecture, big and open linked data analytics and smart city and how they are related to each other [18].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, these studies have added importance to the value chain in the industrial ecosystem using structural path analysis with input-output tables [10,12]. Analyzing clusters is important while performing industrial ecosystem analysis.…”
The research agenda on smart cities has increasingly extended not only on perspectives of social–economic relations between technologies and cities but also on the industrial economic ecosystem. The purpose of this study is to focus on an analytical method for the characteristics of a smart city’s ecology and industry. With that thought, we have developed a smart SPIN (Spectrum, Penetration, Impact and Network) model and applied it to analyze the ecology of the Korean smart city industry in general. This model consists of smart spectrum model, smart penetration model, smart impact path model and smart network clustering model. The smart SPIN model shows great potential as an analytical method for the smart city industry ecosystem. As a source of data for analyses from 1960, 1985 and 2015 via input–output table, we revised these data into 25 and 8 industries related to the smart city ecosystem. Additionally, we applied the 2015 GDP deflator. The results of analysis are as follows: First, spectrum, the number of smart industries is increasing. This means that the smart city industry scope and area are expanding. Second, analysis of the smart penetration model and smart ecological industry can be applied into other industries. In other words, traditional industries can crossover and utilize smart technology. Third, with the results of our analysis of the smart impact path model, production paths are increasing while parameter paths did not show a triple parameter path. This means the value chain of the smart city industry is highly divested, but the structure of the industry is weakening. Fourth, smart network analysis shows important clusters to be centered on traditional industries: the clusters do not appear in smart industry centers. This means the impact of the smart city is not strong. Our analysis shows that, today, the Korean industrial ecosystem of smart cities is interacting with existing industries and raising it to a more intelligent and smarter level. Thus, there is a need for this kind of analysis study in order to find optimized smart city industry ecosystem.
“…Studies of smart city industrial ecosystems have seen little research and progress worldwide. Most representative and qualitative research studies such as system architecture design and governance establishment were on smart city ecosystems [19,[41][42][43] and smart city innovation ecosystems [44], whereas quantitative studies were on the changes of smart city industry convergence [10,12,44].…”
Section: Previous Study Of Smart City Industrial Ecosystemmentioning
confidence: 99%
“…They join various technologies and industries such as knowledge, construction and energy. Through this, they implement a smart economy, smart environment, smart mobility, and therefore, a smart life [8,10].…”
Section: Introductionmentioning
confidence: 99%
“…Consequently, there have been more studies on the ecology of smart cities recently. Typically, studies have focused on smart city industrial ecosystems [10,12], smart city governance ecosystem [13,14], smart city service and technology ecosystems [15][16][17] and smart city data management ecosystems [18,19]. The study aims to clarify the concepts of enterprise architecture, big and open linked data analytics and smart city and how they are related to each other [18].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, these studies have added importance to the value chain in the industrial ecosystem using structural path analysis with input-output tables [10,12]. Analyzing clusters is important while performing industrial ecosystem analysis.…”
The research agenda on smart cities has increasingly extended not only on perspectives of social–economic relations between technologies and cities but also on the industrial economic ecosystem. The purpose of this study is to focus on an analytical method for the characteristics of a smart city’s ecology and industry. With that thought, we have developed a smart SPIN (Spectrum, Penetration, Impact and Network) model and applied it to analyze the ecology of the Korean smart city industry in general. This model consists of smart spectrum model, smart penetration model, smart impact path model and smart network clustering model. The smart SPIN model shows great potential as an analytical method for the smart city industry ecosystem. As a source of data for analyses from 1960, 1985 and 2015 via input–output table, we revised these data into 25 and 8 industries related to the smart city ecosystem. Additionally, we applied the 2015 GDP deflator. The results of analysis are as follows: First, spectrum, the number of smart industries is increasing. This means that the smart city industry scope and area are expanding. Second, analysis of the smart penetration model and smart ecological industry can be applied into other industries. In other words, traditional industries can crossover and utilize smart technology. Third, with the results of our analysis of the smart impact path model, production paths are increasing while parameter paths did not show a triple parameter path. This means the value chain of the smart city industry is highly divested, but the structure of the industry is weakening. Fourth, smart network analysis shows important clusters to be centered on traditional industries: the clusters do not appear in smart industry centers. This means the impact of the smart city is not strong. Our analysis shows that, today, the Korean industrial ecosystem of smart cities is interacting with existing industries and raising it to a more intelligent and smarter level. Thus, there is a need for this kind of analysis study in order to find optimized smart city industry ecosystem.
Artificial intelligence (AI) is one of the most popular and promising technologies of our time. While there is a clearer understanding on the role of AI in boosting the efficiencies at private companies, government agencies and urban management, there is ambiguity on the specific contributions of AI to environmental sustainability. In this editorial commentary: (a) the important role that AI could play in addressing global environmental sustainability challenges is discussed; (b) the need for a consolidated AI approach to support the efforts in addressing global environmental sustainability problems—e.g., meeting the global sustainable development goals, developing smart and sustainable cities and regions, and tackling the climate and biodiversity crises—is identified; (c) the emerging Green AI concept that offers a consolidated AI perspective that is an essential step towards global environmental sustainability is introduced; (d) the adoption of the Green AI approach by industry, government, and not-for-profit organizations for addressing environmental sustainability challenges of the planet and for improving the quality of lives of our societies in cities is advocated. The editorial commentary also introduces the contributions to the Special Issue on reviews and perspectives on smart and sustainable metropolitan and regional cities.
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