17 research outputs found

    Access and analysis of ISTAC data through the use of R and Shiny

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    [EN] The increasing availability of open data resources provides opportunities for research and data science. It is necessary to develope tools that take advantage of the full potential of new information resources. In this work we developed the package for R istacr that provides a collection of eurostat functions to be able to consult and discard the data that Eurostat, including functions to retrieve, download and manipulate the data set available through the ISTAC BASE API of the Canary Institute of Statistics (ISTAC). In addition, A Shiny app was designed for a responsive visulization of the data. This develope is part of the growing demand for open data and ecosystems dedicated to reproducible research in computational social science and digital humanities. With this interest, this package has been included within rOpenSpain, a project that aims to promote transparent research methods mainly through the use of free software and open data in Spain.Gonzรกlez-Martel, C.; Cazorla-Artiles, JM.; Pรฉrez-Gonzรกlez, C. (2018). Access and analysis of ISTAC data through the use of R and Shiny. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politรจcnica de Valรจncia. 193-200. https://doi.org/10.4995/CARMA2018.2018.8345OCS19320

    Open government data portals in the European Union: Considerations, development, and expectations

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    The goal of open government data (OGD) initiatives is to promote transparency, efficiency and public participation in public management policies. To do so, public organizations must consider which elements might help the development of their open government data portals (OGDP). This paper studies the evolution of OGDP in the 28 countries of the European Union (EU) in a multidisciplinary setting. Whereas the comparative frameworks in the literature are mostly based only on technological parameters, this exploratory research aims to uncover which factors might uphold the successful development of OGDP through the analysis of the relationships between a number of technical and socioeconomical indicators over a period of three years (2015โ€“2017), using a clustering methodology. The results show that EU countries are slowly homogenizing their OGD approaches into two currents/speeds, based mainly on economic factors and open government development status. The originality of this research lies in the sense that it provides not only a technical benchmark, but also a longitudinal and multidisciplinary perspective that will add to the current formulation of OGD policies and practices in any international setting

    Framework for Prioritization of Open Data Publication: An Application to Smart Cities

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    Public Sector Information is considered to play a fundamental role in the growth of the knowledge economy and improvements in society. Given the difficulty in publishing and maintaining all available data, due to budget constraints, institutions need to select which data to publish, giving priority to data most likely to generate social and economic impact. Priority of publication could become an even more significant problem in Smart Cities: as huge amounts of information are generated from different domains, the way data is prioritized and thus reused, could be a determining factor in promoting, among others, new and sustainable business opportunities for local entrepreneurs, and to improve citizen quality of life. However, people in charge of prioritizing which data to publish through open data portals (such as Chief Data Officers, or CDOs) do not have available any specific support in their decision-making process. In this work, a proposal of a framework for prioritization of open data publication as well as its application to Smart Cities is presented. This specific application of the framework relies on OSS (Open Source Software) indicators to help making decisions on the most relevant data to publish focused on developers and businesses operating within the Smart City context.This work was funded by (i) Ministerio de Economรญa e Innovaciรณn (Spain) TIN2015-69957-R (MINECO/ERDF, EU) project and TIN2016-78103-C2-2-R (MINECO/ERDF, EU) project, (ii) POCTEP 4IE project (0045-4IE-4-P), and (iii) Consejerรญa de Economรญa e Infraestructuras/Junta de Extremadura (Spain) - European Regional Development Fund (ERDF)- GR18112 project and IB16055 project

    Factors in the adoption of open government initiatives in Spanish local governments

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    Acknowledgements This research was carried out with financial support from the Min- istry of Science, Innovation and Universities (Spain) (Research project number: RTI2018-095344-A-100), the Centre of Andalusian Studies (Research project number PR137/19) and the Regional Government of Andalusia (Research project number PY20_00314 and B-SEJ-556-UGR- 20). Funding for open access charge: Universidad de Granada / CBUA.The Open Government Data (OGD) projects have spread rapidly in recent years, given that they involve a great transformative potential, whose aims to guarantee transparent government and stimulate the participation and citizenry engagement. It seems that there is a lack of studies analysing factors regarding both the access to OG projects and the volume and format of data published into OGD projects. Therefore, this paper seeks to identify main factors affecting both the way of accessing the OG projects and the volume and format of data published into OGD projects in larger Spanish municipalities (with >50,000 inhabitants and a sample of 145 municipalities). Our main findings seem to point out the intention of sample governments to increase their information disclosure as a way for enhancing their reputation or government's image introducing OGDPs initiatives. Also, it revels differences among analysed municipalities regarding the context in which the information is disclosed.Ministry of Science, Innovation and Universities (Spain) (Research project number: RTI2018-095344-A-100)Centre of Andalusian Studies (Research project number PR137/19)Regional Government of Andalusia (Research project number PY20_00314 and B-SEJ-556-UGR-20)Funding for open access charge: Universidad de Granada/CBU

    A rubric driven evaluation of open data portals and their data in transportation

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    In recent years, the open data movement is gaining momentum in the transportation industry with multiple State\u27s Department of Transportation (DOT) launching their own repository of datasets. The quality of data, ease of usage and availability of metadata varies from source to source. There is an imminent need to assess the quality of open data portals to provide agencies a yardstick to measure their performance and draw inspirations from higher ranking portals. We propose a data portal evaluation rubric (DPER) which can serve this purpose. DPER is designed to capture the essence of the National Open Data Policy. The DPER was used to evaluate 43 data portals at the state and national level which provide transportation datasets. DPER evaluates the quality of the portal, the openness of data, and the relevance of its content to the transportation sector. The portal of the State of New York scores the highest due to its user-friendly interface with interactive visualization tools, relevant data content, detailed data information and useful API references for application developers

    Anรกlisis multidimensional de los portales de datos abiertos autonรณmicos espaรฑoles

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    Open Government initiatives and reuse of public sector information are implemented in most countries. The destination of this data are open data portals, digital repositories that centralize information of public administrations under the premises of open formats and free licenses. In Spain, the development of regional governments open data portals is undisputed, going from 11 open portals with an approximate offer of 5.000 datasets in 2013, to 17 repositories and more than 14.000 datasets in 2019. This study evaluates these regional government open data portals, considering four complementary dimensions: number of datasets, applications developed, based on these datasets, available interaction options and observed functionality in the portal, finding important intra-community differences.Iniciativas de Gobierno Abierto y de reutilizaciรณn de la informaciรณn del sector pรบblico estรกn implementadas en la mayor parte de los paรญses. Los portales de open data, repositorios digitales que centralizan la informaciรณn en manos de las administraciones pรบblicas bajo las premisas de formatos abiertos y licencias libres, son el destino de estos datos. En Espaรฑa el desarrollo de los portales de datos abiertos autonรณmicos es innegable, pasando de 11 portales operativos y una oferta aproximada de 5.000 datasets en el aรฑo 2013, a 17 repositorios y mรกs de 14.000 conjuntos de datos en 2019. Este estudio se ocupa de valorar estos portales de datos abiertos autonรณmicos considerando cuatro dimensiones complementarias: nรบmero de datasets, aplicaciones elaboradas en base a esos conjuntos de datos, opciones de interacciรณn disponibles y funcionalidad observada en el portal, encontrando importantes diferencias intracomunitarias

    Local Municipality Public Value Co-Creation through Democratic E-Governance: A Mixed Method Analysis of Korean Municipal Government Websites

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    The use of technology in the public sector can improve the course of government by increasing efficiency and effectiveness, and bolster democratic principles in governance. The aforementioned can occur by employing transparency, accountability, and citizen engagement, thereby bringing the state-citizen relationship closer. Despite the crucial roles of local governments in promoting democratic practices in the e-government context, prior studies tend to have paid limited attention to e-government practices at the local level. Moreover, it was criticized that early e-government practices focused mainly from the providerโ€™s perspectives and lost the sense of purpose. In this respect, integrating the concept of public value creation into the discussion of digital government may help this new mode of governance live up to its premises. With the gap in the current literature, this article presents a theoretical framework that portrays how the government and its citizens can interact through technology-mediated devices in the decision-making process, namely democratic egovernance, which leads to public value co-creation. Based on the theoretical ground, we analyzed municipal government websites in Korea, as its e-government system at the national level has been internationally regarded as one of the best practices. With a mixed method approach that integrated a quantitative approach to the website evaluation and qualitative analyses of in-depth interviews, we aimed to investigate the extent to which local democratic e-governance developed, and how public value was co-created through democratic e-governance in Korea. This study contributes to the literature by sharing the link between e-government studies and public value theory with substantiated evidence, and it discovered both prospects and latent challenges of public value co-creation through e-governance at the local level

    User Perception of the U.S. Open Government Data Success Factors

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    This quantitative correlational study used the information systems success model to examine the relationship between the U.S. federal departments\u27 open data users\u27 perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. A pre-existing information system success model survey instrument was used to collect data from 122 open data users. The result of the standard multiple linear regression was statistically significant to predict the intent to use the U.S. open government data F(3,99) = 6479.916, p \u3c0.01 and accounted for 99% of the variance in the intent to use the U.S. open government data (Rยฒ= .995), adjusted Rยฒ= .995. The interdependent nature of information quality, system quality, and service quality may have contributed to the value of the Rยฒ. Cronbach\u27s alpha for this study is ฮฑ=.99, and the value could be attributed to the fact that users of open data are not necessarily technical oriented, and were not able to distinguish the differences between the meanings of the variables. The result of this study confirmed that there is a relationship between the user\u27s perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. The findings from this study might contribute to positive social change by enabling the solving of problems in the healthcare, education, energy sector, research community, digitization, and preservation of e-government activities. Using study, the results of this study, IT software engineers in the US federal departments, may be able to improve the gathering of user specifications and requirements in information system design

    Focusing on Openness of Government Information

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ(์ •์ฑ…ํ•™์ „๊ณต), 2021.8. ๊น€๋‹ค์šธ.์ง€๋ฐฉ์ž์น˜์ œ๊ฐ€ ๋ฐ”๋žŒ์งํ•˜๊ฒŒ ์ž‘๋™ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ถฉ๋ถ„ํ•œ ์ •๋ณด๋ฅผ ๊ฐ€์ง„ ์‹œ๋ฏผ (informed citizenry)์ด ์ „์ œ๋˜์–ด์•ผ ํ•˜๋ฉฐ, ์ด ์ „์ œ๋Š” ์ง€๋ฐฉ์ •๋ถ€์˜ ์ ๊ทน์ ์ธ ์ •๋ณด ๊ฐœ๋ฐฉ์„ ํ†ตํ•ด ์ถฉ์กฑ๋  ์ˆ˜ ์žˆ๋‹ค. ์‹œ๋ฏผ๋“ค์€ ์ง€๋ฐฉ์ •๋ถ€์˜ ๋‚ด๋ถ€ ํ–‰์ •ํ™œ๋™์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ํ†ตํ•ด ์ง€๋ฐฉ์ •๋ถ€์˜ ํ–‰์ •ํ™œ๋™์„ ๊ฐ์‹œํ•˜๊ณ  ๊ฒฌ์ œํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์ œ๊ณตํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ •๋ถ€๊ฐ€ ํ•ด๊ฒฐํ•˜์ง€ ๋ชปํ•˜๋Š” ์ง€์—ญ์˜ ์ˆ˜์š”์™€ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ๋‹ค. ํ˜„์žฌ ๊ตญ๋‚ด์™ธ์ ์œผ๋กœ ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด ๊ฐœ๋ฐฉ์„ ์ฆ์ง„ํ•˜๊ธฐ ์œ„ํ•œ ์ œ๋„๋“ค์ด ์‹œํ–‰๋˜๊ณ  ์žˆ์ง€๋งŒ, ์ •๋ณด ๊ฐœ๋ฐฉ ์ˆ˜์ค€์€ ์ง€๋ฐฉ์ •๋ถ€ ๋ณ„๋กœ ์ƒ๋Œ€์ ์œผ๋กœ ํฐ ํŽธ์ฐจ๊ฐ€ ์กด์žฌํ•˜๊ณ  ์žˆ๋‹ค. ์ด ๋…ผ๋ฌธ์€ ์ง€๋ฐฉ์ •๋ถ€๋“ค์ด ์ •๋ณด๊ฐœ๋ฐฉ์„ ์ด‰์ง„ํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ™์€ ์ œ๋„์˜ ์ ์šฉ์„ ๋ฐ›๊ณ  ์žˆ์ง€๋งŒ, ๊ทธ ๊ฐœ๋ฐฉ ์ˆ˜์ค€์ด ์„œ๋กœ ๋‹ค๋ฅด๋‹ค๋Š” ์ ์— ์ฃผ๋ชฉํ•˜์˜€๋‹ค. ์ด์— ๋”ฐ๋ผ ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด๊ฐœ๋ฐฉ์„ฑ ๊ฒฐ์ •์š”์ธ์„ ๊ทœ๋ช…ํ•˜๋Š” ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ฒ€ํ†  ๊ฒฐ๊ณผ, ๋‹ค์Œ๊ณผ ๊ฐ™์€ ํ•œ๊ณ„๊ฐ€ ํ™•์ธ๋˜์—ˆ๋‹ค. ์ฒซ์งธ, ๋Œ€๋‹ค์ˆ˜์˜ ์„ ํ–‰์—ฐ๊ตฌ๋Š” ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด๊ฐœ๋ฐฉ์— ๋Œ€ํ•ด ์™ธ๋ถ€ํ™˜๊ฒฝ์˜ ์˜ํ–ฅ์„ ๊ฐ•์กฐํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์ •๋ณด๊ฐœ๋ฐฉ์— ๋Œ€ํ•œ ์ง€๋ฐฉ์ •๋ถ€์˜ ๋‚ด๋ถ€์  ๋™์ธ์— ๋Œ€ํ•ด์„œ๋Š” ์ƒ๋Œ€์ ์œผ๋กœ ๊ฐ„๊ณผํ•˜๊ณ  ์žˆ๋‹ค. ๋‘˜์งธ, ๋Œ€๋ถ€๋ถ„์˜ ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ์ •๋ถ€๊ฐ€ ์ •๋ณด์— ๋Œ€ํ•œ ์ˆ˜์š”์ž์ด์ž ์‹ค์ œ ์‚ฌ์šฉ์ž๋กœ์„œ์˜ ์‹œ๋ฏผ์˜ ์ค‘์š”์„ฑ์€ ์ธ์‹ํ•˜์ง€๋งŒ, ์‹ค์ฆ์ ์œผ๋กœ ๊ทธ ์˜ํ–ฅ์„ ์ ํ•ฉํ•œ ๋ฐ์ดํ„ฐ์™€ ์‹ค์ฆ๋ถ„์„์„ ํ†ตํ•ด ๊ทœ๋ช…ํ•˜๋Š” ๋ฐ์—๋Š” ํ•œ๊ณ„๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๋‹ค. ์…‹์งธ, ๊ด€๋ จ ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์ง๋ฉดํ•˜๊ณ  ์žˆ๋Š” ๋™ํƒœ์ ์ธ ์ƒํ™ฉ์— ๋Œ€ํ•œ ๊ณ ๋ ค๊ฐ€ ๋ถ€์กฑํ•˜๋‹ค. ๋‹ค์‹œ ๋งํ•ด, ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ณต๊ฐ„์  ์š”์†Œ๋ฅผ ๊ฐ„๊ณผํ•˜๊ณ , ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด๊ฐœ๋ฐฉ์— ๋Œ€ํ•œ ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์™€์˜ ์ƒํ˜ธ์ž‘์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ๊ณ ๋ คํ•œ ์—ฐ๊ตฌ๋ฅผ ์ฐพ๊ธฐ ์–ด๋ ต๋‹ค. ์ด์ƒ์˜ ์„ ํ–‰์—ฐ๊ตฌ์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ์ด ๋…ผ๋ฌธ์€ ์ง€๋ฐฉ์ •๋ถ€์˜ ๋‚ด๋ถ€ ๊ธฐ์ˆ ์š”์ธ์„ ๊ฐ•์กฐํ•˜์ง€๋งŒ, ์ง€๋ฐฉ์ •๋ถ€์˜ ์™ธ๋ถ€ ํ™˜๊ฒฝ์š”์ธ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜๋Š” ๊ธฐ์ˆ -์กฐ์ง-ํ™˜๊ฒฝ ํ”„๋ ˆ์ž„์›Œํฌ(Technology-Organization-Environment Framework)๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด๊ฐœ๋ฐฉ์„ฑ ์˜ํ–ฅ์š”์ธ์„ ๊ฒ€์ฆํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ถ„์„์„ ์œ„ํ•ด 2015๋…„๋ถ€ํ„ฐ 2019๋…„๊นŒ์ง€์˜ ํ•œ๊ตญ์˜ 228๊ฐœ (๊ธฐ์ดˆ 226๊ฐœ, ์„ธ์ข…, ์ œ์ฃผ ํฌํ•จ) ์ง€๋ฐฉ์ •๋ถ€์˜ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€๋‹ค. ์ข…์†๋ณ€์ˆ˜์ธ ์ •๋ณด ๊ฐœ๋ฐฉ์„ฑ์€ ์ •๋ถ€ ๋‚ด๋ถ€ํ™œ๋™์— ๋Œ€ํ•œ ๊ฐ์‹œ๊ฐ€ ๊ฐ€๋Šฅํ•œ (1) ํ–‰์ •๋ฌธ์„œ์˜ ์›๋ฌธ๊ณต๊ฐœ์œจ๊ณผ ์‹œ๋ฏผ๋“ค์—๊ฒŒ ์ฐธ์—ฌ์˜ ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•˜๋Š” (2) ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ ์…‹ ์ˆ˜๋กœ ์ธก์ •๋˜์—ˆ์œผ๋ฉฐ, ๋‘ ์ข…์†๋ณ€์ˆ˜์— ๋Œ€ํ•ด ๊ฐ๊ฐ ๋‘ ๊ฐœ์˜ ๋ชจํ˜•์„ ํ†ตํ•ด ์‹ค์ฆ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ์šฐ์„ , ์—์„œ๋Š” ๊ธฐ์ˆ  ์š”์ธ(์ง€๋ฐฉ์ •๋ถ€์˜ ๊ธฐ์ˆ  ์—ญ๋Ÿ‰, ๊ธฐ์ˆ ๊ด€๋ จ ์ž์›, ๊ธฐ์ˆ  ํ™œ์šฉ ๊ณ„ํš ์ˆ˜์ค€), ์กฐ์ง ์š”์ธ(์ง€๋ฐฉ์ •๋ถ€์˜ ๊ทœ๋ชจ, ์žฌ์ • ์ž๋ฆฝ๋„, ๋‹จ์ฒด์žฅ์˜ ์ •์น˜์  ์„ฑํ–ฅ), ํ™˜๊ฒฝ ์š”์ธ(์ง€์—ญ ์ •์น˜์˜ํ–ฅ- ์ง€๋ฐฉ์„ ๊ฑฐ ์—ฐ๋„, ์ง€๋ฐฉ์˜ํšŒ์™€์˜ ์ •์น˜์  ๊ฒฝ์Ÿ์ˆ˜์ค€, ์ง€์—ญ ์‹œ๋ฏผ ์˜ํ–ฅ- ์กฐ์งํ™”๋œ ์‹œ๋ฏผ, ๊ฐœ๋ณ„ ์‹œ๋ฏผ๋“ค์˜ ์˜ํ–ฅ์ˆ˜์ค€, ๋ฒ•์ œํ™” ์˜ํ–ฅ- ์กฐ๋ก€ ์ œ์ •์—ฌ๋ถ€)์ด ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ์„ค์ •๋˜์—ˆ๊ณ , ํ†ต์ œ๋ณ€์ˆ˜๋กœ๋Š” ์ค‘์•™์ •๋ถ€์˜ ํ‰๊ฐ€ ์‹œํ–‰์—ฌ๋ถ€, ์ง€์—ญ ์ธ๊ตฌ์ˆ˜, ์ง€์—ญ ๊ณ ๋ นํ™” ์ˆ˜์ค€, ๋†๊ฐ€์ธ๊ตฌ ๋น„์œจ, ์—ฐ๋„๊ฐ€ ํ™œ์šฉ๋˜์—ˆ๋‹ค. ์˜ ์ฃผ์š” ๋ถ„์„ ๋ฐฉ๋ฒ•์œผ๋กœ๋Š” 5๊ฐœ๋…„ ํŒจ๋„๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•œ ๊ณ ์ •ํšจ๊ณผ ๋ชจํ˜•์„ ํ†ตํ•ด ๋ณ€์ˆ˜๋“ค์˜ ์˜ํ–ฅ์„ ์ถ”์ •ํ•˜์˜€๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์—์„œ๋Š” ์ •๋ณด๊ฐœ๋ฐฉ์„ฑ์— ๋Œ€ํ•œ ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์˜ ์˜ํ–ฅ์„ ์ค‘์ ์ ์œผ๋กœ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์—๋Š” ์— ํฌํ•จ๋œ ๋ณ€์ˆ˜๋“ค์„ ๋ชจ๋‘ ํฌํ•จํ•˜์˜€์œผ๋ฉฐ, ๊ฒ€์ฆ ๋ฐฉ๋ฒ•์œผ๋กœ๋Š” ๊ณต์ฐจ๋ชจํ˜•(spatial lag model)์„ ํ™œ์šฉํ•œ ํŒจ๋„ ๊ณต๊ฐ„ํšŒ๊ท€๋ถ„์„(๊ณ ์ •ํšจ๊ณผ)์„ ํ™œ์šฉํ•˜์˜€๋‹ค. ๊ณผ ์˜ ์ฃผ์š” ๋ถ„์„ ๊ฒฐ๊ณผ๋ฅผ ๊ฐ ์ข…์†๋ณ€์ˆ˜๋ณ„๋กœ ์š”์•ฝํ•˜๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์šฐ์„ , ์ง€๋ฐฉ์ •๋ถ€ ๋‚ด๋ถ€ ํ–‰์ •ํ™œ๋™์„ ๊ณต๊ฐœํ•˜๋Š” ๊ฐœ๋ฐฉ์„ฑ(์›๋ฌธ๊ณต๊ฐœ์œจ)์— ์žˆ์–ด์„œ๋Š” ๋‹จ์ฒด์žฅ์˜ ์ •์น˜์  ์„ฑํ–ฅ(์ง„๋ณด), ICT์ธ๋ ฅ, ์žฌ์ •์ž๋ฆฝ๋„(์ด์ƒ ์กฐ์ง ๋‚ด๋ถ€์š”์ธ), ์ •์น˜์  ๊ฒฝ์Ÿ, ๊ฐœ๋ณ„ ์‹œ๋ฏผ๋“ค์˜ ๋ชฉ์†Œ๋ฆฌ(๋ฏผ์› ์ œ๊ธฐ), ๊ด€๋ จ ์กฐ๋ก€ ์ œ์ • ์—ฌ๋ถ€, ์ธ์ ‘์ง€๋ฐฉ์ •๋ถ€์™€์˜ ์ƒํ˜ธ์ž‘์šฉ(์ด์ƒ ์กฐ์ง ์™ธ๋ถ€์š”์ธ)์˜ ์˜ํ–ฅ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ์›๋ฌธ๊ณต๊ฐœ์œจ์—๋Š” ์ง€๋ฐฉ์ •๋ถ€ ๋‚ด๋ถ€์™€ ์™ธ๋ถ€์š”์ธ ๋ชจ๋‘ ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ์œผ๋‚˜, ์™ธ๋ถ€ ์š”์ธ์˜ ์˜ํ–ฅ์ด ๋”์šฑ ๋‘๋“œ๋Ÿฌ์กŒ๋‹ค. ํŠนํžˆ, ์ง€๋ฐฉ์ •๋ถ€์˜ ๋‚ด๋ถ€ ํ–‰์ •ํ™œ๋™์— ๋Œ€ํ•œ ๊ฐœ๋ฐฉ ์ˆ˜์ค€์€ ์ง€๋ฐฉ์ •๋ถ€๋ฅผ ๊ฐ์‹œํ•˜๊ณ  ์ƒํ˜ธ์ž‘์šฉํ•˜๋Š” ์™ธ๋ถ€์˜ ํ–‰์œ„์ž๋“ค์˜ ๊ด€๊ณ„ ์†์—์„œ ๊ฒฐ์ •๋˜๋Š” ๊ฒƒ์œผ๋กœ ํ™•์ธ๋œ๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๋Š” ๊ทธ๋“ค์ด ์ง๋ฉดํ•˜๊ณ  ์žˆ๋Š” ์ง€์—ญ์˜ ์ •์น˜์  ํ™˜๊ฒฝ์ด ์šฐํ˜ธ์ ์ผ ๋•Œ ๊ฐœ๋ฐฉ ์ˆ˜์ค€์„ ๋†’์ด๊ณ , ์ง€์—ญ์˜ ์ •์น˜์  ํ™˜๊ฒฝ์ด ๋น„์šฐํ˜ธ์ ์ผ ๋•Œ์—๋Š” ๊ฐœ๋ฐฉ ์ˆ˜์ค€์„ ๋‚ฎ์ถ”๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ง€๋ฐฉ์˜ํšŒ์™€์˜ ์ •์น˜์  ๊ฒฝ์Ÿ์ด ๋‚ฎ์„ ๋•Œ, ๊ฐœ๋ณ„ ์‹œ๋ฏผ๋“ค์˜ ๋ชฉ์†Œ๋ฆฌ๊ฐ€ ๋†’์„ ๋•Œ ๋‚ด๋ถ€ ์ •๋ณด์— ๋Œ€ํ•œ ๊ฐœ๋ฐฉ์„ ๋‚ฎ์ท„๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๋Š” ์—ฌ์ „ํžˆ ํ–‰์ •์ •๋ณด์— ๋Œ€ํ•œ ํ†ต์ œ๋ ฅ์„ ํ–‰์‚ฌํ•˜๋ฉฐ, ๊ทธ๋“ค์˜ ์ •์น˜์  ์ดํ•ด๊ด€๊ณ„์— ๋”ฐ๋ผ ์ด๋ฅผ ์ „๋žต์ ์œผ๋กœ ์กฐ์ •ํ•˜๋Š” ๋ชจ์Šต์ด ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด์—, ์ •๋ณด ๊ฐœ๋ฐฉ๊ณผ ๊ด€๋ จํ•œ ์กฐ๋ก€์˜ ์ œ์ •๊ณผ ์ธ์ ‘ํ•œ ๋‹ค๋ฅธ ์ง€๋ฐฉ์ •๋ถ€๋“ค์˜ ๊ฐœ๋ฐฉ์„ฑ ์ˆ˜์ค€์—๋Š” ๊ธ์ •์  ์˜ํ–ฅ์„ ๋ฐ›๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ๊ทธ๋“ค์ด ์ง๋ฉดํ•˜๊ณ  ์žˆ๋Š” ์ •์น˜์  ํ™˜๊ฒฝ์— ๋”ฐ๋ผ ์›๋ฌธ๊ณต๊ฐœ์œจ์„ ์กฐ์ •ํ•˜์ง€๋งŒ, ์ง€์—ญ์— ์ •๋ณด๊ณต๊ฐœ์™€ ๊ด€๋ จํ•œ ์กฐ๋ก€๊ฐ€ ์ œ์ •๋˜์–ด์žˆ์„ ์‹œ์—๋Š” ์›๋ฌธ๊ณต๊ฐœ ์ˆ˜์ค€์ด ์ „๋ฐ˜์ ์œผ๋กœ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ, ์ง€๋ฆฌ์ ์œผ๋กœ ์ธ์ ‘ํ•œ ์ง€๋ฐฉ์ •๋ถ€๋“ค ๊ฐ„์—๋Š” ์›๋ฌธ๊ณต๊ฐœ์œจ๊ณผ ๊ด€๋ จํ•˜์—ฌ ์ •๋ถ€ ๊ฐ„ ์ƒํ˜ธ์ž‘์šฉ์„ ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚˜ ์ •๋ณด๊ฐœ๋ฐฉ์„ฑ์— ๋Œ€ํ•œ ์ง€์—ญ์  ํ™•์‚ฐํšจ๊ณผ(spill-over)์˜ ๊ฐ€๋Šฅ์„ฑ์„ ์—ฟ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ง€๋ฐฉ์ •๋ถ€ ๋‚ด๋ถ€ ์š”์ธ ์ค‘์—์„œ๋Š” ๋‹จ์ฒด์žฅ์˜ ์ •์น˜์  ์„ฑํ–ฅ์ด ์ง„๋ณด์ ์ผ์ˆ˜๋ก, ์žฌ์ •์ž๋ฆฝ๋„๊ฐ€ ๋‚ฎ์„์ˆ˜๋ก ๊ฐœ๋ฐฉ์„ฑ ์ˆ˜์ค€์„ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์žฌ์ •์ž๋ฆฝ๋„๊ฐ€ ๋‚ฎ์€ ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ฒฝ์šฐ ์ค‘์•™์ •๋ถ€์—์„œ ๊ถŒ๊ณ ํ•˜๊ณ  ์žˆ๋Š” ์›๋ฌธ๊ณต๊ฐœ์˜ ์ˆ˜์ค€์„ ๋†’์˜€์„ ๊ฒƒ์œผ๋กœ ํ•ด์„์ด ๊ฐ€๋Šฅํ–ˆ๋‹ค. ์ด ๊ฒฝ์šฐ, ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์›๋ฌธ๊ณต๊ฐœ ์ˆ˜์ค€์„ ๋‚ฎ์ถค์œผ๋กœ์จ ๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ๋น„๋ฐ€์ฃผ์˜์˜ ์ด๋“(incentives) ๋ณด๋‹ค ์›๋ฌธ๊ณต๊ฐœ์œจ์„ ๋†’์—ฌ ์ค‘์•™์ •๋ถ€๋กœ๋ถ€ํ„ฐ ์ข‹์€ ํ‰๊ฐ€๋ฅผ ๋ฐ›์•„ ์ค‘์•™์œผ๋กœ๋ถ€ํ„ฐ์˜ ์žฌ์ • ์ง€์›์— ๊ธ์ •์  ์ƒํ™ฉ์„ ๊ตฌ์„ฑํ•˜๋Š” ๊ฒƒ์ด ๋” ํฐ ์ด๋“์ด ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์œผ๋กœ ์ถ”๋ก ์ด ๊ฐ€๋Šฅํ–ˆ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ์‹œ๋ฏผ๋“ค์˜ ์ฐธ์—ฌ์˜ ๊ธฐํšŒ๋ฅผ ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต๋ฐ์ดํ„ฐ ์…‹ ๊ฐœ๋ฐฉ์—๋Š” ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ธฐ์ˆ ์  ์—ญ๋Ÿ‰, ์ •๋ณดํ™”๊ณ„ํš ์ˆ˜์ค€, ์ •๋ถ€์˜ ๊ทœ๋ชจ(์ด์ƒ ์กฐ์ง ๋‚ด๋ถ€์š”์ธ), ๊ฐœ๋ณ„ ์‹œ๋ฏผ๋“ค์˜ ๋ชฉ์†Œ๋ฆฌ, ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์™€์˜ ์ƒํ˜ธ์ž‘์šฉ(์ด์ƒ ์กฐ์ง ์™ธ๋ถ€์š”์ธ)์ด ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์˜คํ”ˆ๋ฐ์ดํ„ฐ ๋ชจํ˜•์—์„œ๋Š” ์›๋ฌธ๊ณต๊ฐœ์œจ ๋ชจํ˜•๊ณผ๋Š” ๋‹ค๋ฅด๊ฒŒ ์กฐ์ง ๋‚ด๋ถ€์š”์ธ์˜ ์˜ํ–ฅ์ด ๋”์šฑ ๋‘๋“œ๋Ÿฌ์กŒ๋‹ค. ํŠนํžˆ ๋‚ด๋ถ€ ์š”์ธ ์ค‘ ๊ธฐ์ˆ  ๊ด€๋ จ ์š”์ธ์˜ ์˜ํ–ฅ์ด ๋ช…์‹œ์ ์ด์—ˆ๋‹ค. ์กฐ์ง์˜ ๊ธฐ์ˆ ์  ์—ญ๋Ÿ‰์ด ๋†’์„์ˆ˜๋ก, ์กฐ์ง์˜ ๊ธฐ์ˆ ํ™œ์šฉ ์˜์ง€๊ฐ€ ๋†’์„์ˆ˜๋ก ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์— ๋”์šฑ ์ ๊ทน์ ์ธ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, ๊ณต๋ฌด์› ์ˆ˜๋กœ ์ธก์ •๋œ ์ •๋ถ€์˜ ๊ทœ๋ชจ ๋˜ํ•œ ๊ธ์ •์  ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ  ์žˆ์—ˆ๋Š”๋ฐ, ์ด๋Š” ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ๊ณต๊ณต๋ฐ์ดํ„ฐ๋ฅผ ๊ฐœ๋ฐฉํ•˜๊ธฐ ์ „ ๊ณต๊ณต๋ฐ์ดํ„ฐ๋ฅผ ์ƒ์„ฑํ•˜๊ณ  ์ˆ˜์ง‘ํ•  ์‹œ ์กฐ์ง์˜ ํ–‰์ •๋ ฅ์ด ์†Œ์š”๋  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•˜๋Š” ๊ฒฐ๊ณผ์˜€๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ ์ „์— ๋ฐ์ดํ„ฐ์— ํฌํ•จ๋œ ๋ฏผ๊ฐ ์ •๋ณด๋ฅผ ๋ถ„๋ฆฌ, ๋น„์‹๋ณ„ํ™”ํ•ด์•ผํ•˜๋ฉฐ ์ €์ž‘๊ถŒ ๋“ฑ์˜ ๋ฌธ์ œ๋ฅผ ๊ฒ€ํ† ํ•ด์•ผ ํ•˜๋Š” ๋“ฑ์˜ ์ ˆ์ฐจ๋“ค๋กœ ์ธํ•ด ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์—๋Š” ์ผ์ • ์ˆ˜์ค€์˜ ํ–‰์ •๋ ฅ์ด ํ•„์š”ํ•œ ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋˜ํ•œ, ๊ณต๊ณต๋ฐ์ดํ„ฐ์˜ ๊ฐœ๋ฐฉ์—๋Š” ๊ฐœ๋ณ„ ์‹œ๋ฏผ๋“ค์˜ ๋ชฉ์†Œ๋ฆฌ(๋ฏผ์› ์ œ๊ธฐ)์˜ ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์ด ๊ฒ€์ฆ๋˜์—ˆ๋Š”๋ฐ, ์›๋ฌธ๊ณต๊ฐœ์œจ๊ณผ๋Š” ๋‹ฌ๋ฆฌ ์˜คํžˆ๋ ค ์‹œ๋ฏผ๋“ค์˜ ๋ชฉ์†Œ๋ฆฌ๊ฐ€ ๋†’๊ฒŒ ํ‘œ์ถœ๋  ๋•Œ ๋ฐ์ดํ„ฐ๋ฅผ ๋” ๋งŽ์ด ๊ฐœ๋ฐฉํ•˜๋Š” ์–‘์ƒ์„ ๋ณด์˜€๋‹ค. ์ด์— ๋Œ€ํ•ด์„œ๋Š” ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ํ•ด๊ฒฐํ•˜์ง€ ๋ชปํ•˜๋Š” ์ง€์—ญ์˜ ๋ฌธ์ œ์— ๋Œ€ํ•ด ๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์„ ๋” ์ ๊ทน์ ์œผ๋กœ ์‹ค์‹œํ•จ์œผ๋กœ์จ, ์ง€์—ญ ์‹œ๋ฏผ๋“ค๊ณผ ๋ฌธ์ œ๋ฅผ ๊ณต๋™์œผ๋กœ ํ•ด๊ฒฐํ•˜๋ ค๋Š” ๋ชจ์Šต์œผ๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ, ์›๋ฌธ๊ณต๊ฐœ์œจ ๋ชจํ˜•๊ณผ ์œ ์‚ฌํ•˜๊ฒŒ ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์—๋„ ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์˜ ๊ธ์ •์  ์˜ํ–ฅ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์˜ ์šฐ์ˆ˜ํ•œ ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ ์„ฑ๊ณผ๊ฐ€ ์ง€์—ญ์˜ ์–ธ๋ก ์— ๊ณต์œ ๋˜์—ˆ์„ ๊ฒฝ์šฐ, ์ง€๋ฐฉ์ •๋ถ€๋Š” ์ด์— ๋Œ€ํ•ด ๊ธ์ •์  ์ž๊ทน์„ ๋ฐ›์•˜์„ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€๋“ค์˜ ๊ณต๋ฌด์›๋“ค์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ํ†ตํ•ด ์ด๋Ÿฌํ•œ ์ง€์—ญ์  ํ™•์‚ฐํšจ๊ณผ๊ฐ€ ์ผ์–ด๋‚ฌ์„ ๊ฐ€๋Šฅ์„ฑ์ด ์กด์žฌํ•œ๋‹ค. ์ด์ƒ์˜ ๋ถ„์„๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ด๋ก ์  ํ•จ์˜๋ฅผ ๊ฐ–๋Š”๋‹ค. ์ฒซ์งธ, ๋ณธ ์—ฐ๊ตฌ๋Š” โ€œ์—ด๋ฆฐ ์ง€๋ฐฉ์ •๋ถ€โ€์— ๋Œ€ํ•œ ๊ฐœ๋…์  ์ฐจ์›์„ ๋‘ ๊ฐ€์ง€๋กœ ๊ฐœ๋…ํ™”ํ•˜๊ณ  ์ธก์ •ํ•˜์˜€๋‹ค. ํŠนํžˆ, ํˆฌ๋ช…์„ฑ๊ณผ ์•Œ๊ถŒ๋ฆฌ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ ํ•˜๋Š” ๊ณผ๊ฑฐ ์—ด๋ฆฐ ์ •๋ถ€ ํŒจ๋Ÿฌ๋‹ค์ž„์˜ ํ•ต์‹ฌ์  ๋‚ด์šฉ๊ณผ ์‹œ๋ฏผ์ฐธ์—ฌ์™€ ํ˜‘๋ ฅ์„ ์ค‘์‹ฌ์œผ๋กœ ํ•˜๋Š” 2009๋…„ ์ดํ›„ ๋Œ€๋‘๋œ ์ƒˆ๋กœ์šด ์—ด๋ฆฐ ์ •๋ถ€ ํŒจ๋Ÿฌ๋‹ค์ž„์˜ ํ•ต์‹ฌ์  ๋‚ด์šฉ์„ ๊ฐœ๋…์  ์ฐจ์›์œผ๋กœ ๊ตฌ์„ฑํ•˜๊ณ  ์ด๋ฅผ ๊ฐ๊ฐ ๊ฒฝ์„ฑ ์ž๋ฃŒ๋กœ ์ธก์ •์„ ์‹œ๋„ํ–ˆ๋‹ค. ๋‘˜์งธ, TOE ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์—ด๋ฆฐ ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ๊ตฌ์กฐ์ ์ธ ๊ฒฐ์ •์š”์ธ์„ ๊ฒ€ํ† ํ–ˆ๋‹ค. ์…‹์งธ, ๋ณธ ์—ฐ๊ตฌ๊ฐ€ ์ œ์•ˆํ•œ TOEN ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ์ง€์—ญ ์‹œ๋ฏผ์˜ ์˜ํ–ฅ, ์ธ์ ‘ ์ง€๋ฐฉ์ •๋ถ€์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ํฌํ•จํ•จ์œผ๋กœ์จ ์ง€๋ฐฉ ์ˆ˜์ค€์˜ ์—ด๋ฆฐ ์ •๋ถ€ ์„ ํ–‰์—ฐ๊ตฌ์—์„œ ์กด์žฌํ•˜๋˜ ํ•™์ˆ ์  ๊ณต๋ฐฑ์„ ํ•ด๊ฒฐํ•˜์˜€๋‹ค. ๋„ท์งธ, ์ •๋ณด๊ฐœ๋ฐฉ์— ๋Œ€ํ•œ ํ–‰์œ„์ž๋กœ์„œ ์ง€๋ฐฉ์ •๋ถ€์˜ ์—ญํ• ์„ ์กฐ๋ช…ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋‚ด๋ถ€์ •๋ณด์— ๋Œ€ํ•œ ์ง€๋ฐฉ์ •๋ถ€์˜ ํ†ต์ œ, ๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์— ํ•„์š”ํ•œ ์กฐ์ง ๋‚ด๋ถ€์˜ ์—ญ๋Ÿ‰ ๋“ฑ ์ •๋ณด ๊ฐœ๋ฐฉ์— ๋Œ€ํ•œ ์ง€๋ฐฉ์ •๋ถ€์˜ ์ „๋žต์  ํ–‰์œ„์™€ ์˜๋„์  ๋…ธ๋ ฅ์— ๋Œ€ํ•ด์„œ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋…ผ์˜๋ฅผ ์ข…ํ•ฉํ•˜์—ฌ ๋„์ถœํ•œ ์ •์ฑ…์  ํ•จ์˜๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ง€๋ฐฉ์ •๋ถ€์˜ ๋‚ด๋ถ€ ํ™œ๋™ ์ •๋ณด์— ๋Œ€ํ•œ ๊ฐœ๋ฐฉ์ˆ˜์ค€(์›๋ฌธ๊ณต๊ฐœ์œจ)์„ ๋†’์ด๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋ฐฉ์•ˆ์ด ๊ณ ๋ ค๋  ์ˆ˜ ์žˆ๋‹ค. ์šฐ์„ , ์›๋ฌธ๊ณต๊ฐœ์œจ๊ณผ ์ง€๋ฐฉ์ •๋ถ€ ํ‰๊ฐ€์ง€ํ‘œ์˜ ์—ฐ๊ณ„๊ฐ€ ํ•„์š”ํ•˜๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์›๋ฌธ๊ณต๊ฐœ์œจ ์‹ค์ ์— ๋”ฐ๋ผ ์ง€๋ฐฉ์ •๋ถ€๊ฐ€ ์ฒด๊ฐํ•  ๋งŒํ•œ ๋ณด์ƒ ํ˜น์€ ๋ถˆ์ด์ต์„ ์ œ๊ณตํ•ด์•ผํ•œ๋‹ค. ๋˜ํ•œ, ํ˜„์žฌ ์ง„ํ–‰๋˜๋Š” ์ง€๋ฐฉ์ •๋ถ€์˜ ์ •๋ณด๊ณต๊ฐœ ํ‰๊ฐ€ ๋Œ€์ƒ ์ง‘๋‹จ์˜ ๊ตฌ๋ถ„์ด ์ง€์—ญ๋ณ„ ํ˜น์€ ๊ถŒ์—ญ๋ณ„๋กœ ์ด๋ฃจ์–ด์ ธ์•ผํ•œ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์ •๋ณด ๊ฐœ๋ฐฉ์— ๋Œ€ํ•œ ์ง€๋ฐฉ์ •๋ถ€๋“ค๊ฐ„ ๊ณต๊ฐ„์  ์ƒํ˜ธ์ž‘์šฉ์˜ ํšจ๊ณผ๋ฅผ ๊ทน๋Œ€ํ™”ํ•ด์•ผํ•œ๋‹ค. ๋˜ํ•œ ๋ณธ ์—ฐ๊ตฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด ๋‚˜์˜จ ๊ฒฐ์ •์š”์ธ๋“ค์„ ๋ฐ”ํƒ•์œผ๋กœ, ์›๋ฌธ๊ณต๊ฐœ์œจ์ด ๋‚ฎ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜๋Š” ์ง€์—ญ์— ๋Œ€ํ•œ ๊พธ์ค€ํ•œ ๋ชจ๋‹ˆํ„ฐ๋ง์ด ํ•„์š”ํ•˜๋‹ค. ์‹œ๋ฏผ๋“ค์˜ ์ฐธ์—ฌ๋ฅผ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์„ ์ด‰์ง„ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๋ฐฉ์•ˆ์ด ๊ณ ๋ ค๋  ์ˆ˜ ์žˆ๋‹ค. ์šฐ์„ , ํ–‰์ •๋ ฅ ๊ทœ๋ชจ๊ฐ€ ์ž‘์€ ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•ด ๊ธฐ์ˆ ์  ์ง€์›์„ ํ•˜๊ฑฐ๋‚˜ ๊ณต๋ฌด์›์„ ์žฌ๊ต์œกํ•˜๋Š” ๋“ฑ ์กฐ์ง ๋‚ด๋ถ€์š”์ธ์„ ์ค‘์‹ฌ์œผ๋กœ ์ง€์›ํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๋‹ค. ๋˜ํ•œ ๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ์— ์†Œ์š”๋˜๋Š” ํ–‰์ •๋ ฅ ์†Œ์š”๋ฅผ ํšจ์œจํ™”ํ•˜๋Š” ๋ฐฉ์•ˆ์„ ๊ฐ•๊ตฌํ•ด์•ผ ํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋†’์€ ๊ณต๊ณต๋ฐ์ดํ„ฐ ๊ฐœ๋ฐฉ ์ˆ˜์ค€์„ ๋ณด์ด๋Š” ์ง€๋ฐฉ์ •๋ถ€์— ๋Œ€ํ•œ ์ง€์†์ ์ธ ์„ฑ๊ณต์‚ฌ๋ก€ ๋ฐœ๊ตด๊ณผ ์„ฑ๊ณผ ํ™•์‚ฐ์„ ํ†ตํ•ด ์ž์œจ์ ์ธ ๊ฐœ๋ฐฉ์„ฑ ์ฆ์ง„ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค.One important underlying condition of a properly functioning local democracy is an informed citizenry, which can be satisfied when the active opening of government information is possible. In many countries, central governments have led initiatives to promote the release of government information and data in public organizations, including local governments. However, despite the central governmentโ€™s efforts, local governmentsโ€™ level of openness varies greatly. Therefore, this dissertation focuses on this variation at the local level and attempts to identify the determinants of openness of government information (OGI). A review of the OGI-related literature found several research gaps. Firstly, most OGI studies have emphasized the external influence of local government in explaining the determinants of OGI. Accordingly, overlooked is the importance of the internal force of local governments in OGI. Secondly, the literature recognizes the importance of local citizens but has failed to empirically verify their impact on OGI in local governments. Thirdly, previous literature fails to consider the dynamic policy environment at the local level. The extant literature neglected spatial attributes of local governments and has yet to address the possibility of interactions among neighboring local governments on OGI. To fill these gaps in the literature, this study establishes and verifies a TOEN framework based on the Technology-Organization-Environment (TOE) framework. For analysis, the author collected a five-year panel data (2015โ€“2019) of Korean local governments (226 lower-level governments, Sejong, and Jeju). The author measured the OGI, this dissertationโ€™s dependent variable, with the disclosure rate of administrative documents (DRAD) and the number of open data sets. The empirical analysis was performed through two models for each of the two dependent variables. First, comprises technology-related factors (technical capacity, information communication technology (ICT)-related resource, and the technology utilization planning level of government), organization factors (government size, financial autonomy, and political ideology of the governmentโ€™s leaders), and environmental factors (influence from local politics, a local election year, political competition, influence from local citizens, organized local citizens, and individual citizens, and local legislation). Panel linear regression with the fixed-effects model is employed to verify the influence of these factors. Next, validates the impact of neighboring local governments. includes all the variables in and also uses a panel spatial regression (spatial lag model) with fixed effects as an estimation method. The findings for each dependent variable are summarized as follows. First, in terms of the opening internal administrative activities (DRAD), the political ideology of the government leader, information communication technology (ICT) personnel, financial capability, political competition, citizensโ€™ voice (complaints), related local ordinance, and interaction between adjacent governments were significant. Notably, the DRAD is determined within the relational dynamics between local government and external actors. Local governments raise the openness level when their local political condition is favorable and decrease openness when facing unfavorable political pressure. For example, when political competition with local councils is high, and citizensโ€™ voices are high, DRAD is lowered. These findings show that local governments still exert control over their administrative information and seem to make strategic adjustments according to their political interests. On the other hand, the enactment of the local ordinance related to openness and the influence of neighboring governments positively affected the DRAD. The spatial interaction between local governments regarding the DRAD shows the possibility of a regional spill-over effect on the OGI. Among internal factors, the local government with a progressive government leader and lower financial capability actively discloses their internal administrative documents. As for the opening of public data sets that provide opportunities for citizens to participate, the technical capacity, plan for technology utilization, government size, citizensโ€™ voice, and interaction between neighboring governments were the significant determinants. Unlike the DRAD model, the effects of internal drivers are quite apparent in this model. In particular, the influences of technology-related factors are prominent. The local government with higher technical capacity and higher willingness to utilize technology in the organization are actively opening their public data to the public. Moreover, government size measured with the number of public officials positively affects the opening data. This finding implies that opening public data can accompany a certain level of administrative capacity. The local governments open more data when confronted by more citizensโ€™ voices, interpreted to mean that local governments provide open data to collaboratively address such dissatisfaction employing the local communitiesโ€™ capability. Similar to the DRAD model, the open data model identified the positive influence of neighboring governments. If local media shared the excellent performance of open data of neighboring governments, local government could be positively stimulated. These results have the following theoretical implications. First, this study conceptualized and measured two dimensions of โ€œopen government.โ€ In particular, this dissertation encompasses the core concept of the โ€œold open governmentโ€ paradigm centered on transparency and right-to-know and the core concept of the โ€œnew open governmentโ€ centered on citizen participation and collaboration. This study investigated the two concepts measured in hard data. Second, this research examined and verified systematic contexts that explain OGI at the local level. Third, the TOEN framework for the local open government, expanded from the TOE framework, filled the research gaps in the open government literature. The TOEN framework contains the influence of local citizens and neighboring governments mentioned in previous studies as limitations or for future study. Fourth, this study illuminated the role of local government as an active actor in opening government information, revealing local governmentsโ€™ strategic actions and intentional efforts to raise openness of government information. Policy implications derived from the findings are as follows. To increase the level of opening the internal administrative process of local government, consider the following measures can. First, local government needs to introduce stricter management on DRAD. The performance of local governmentsโ€™ DRAD can be reflected in the annual local government assessment so that they are provided advantages or disadvantages depending on their opening level. Second, the group subject classification to the current local governmentโ€™s information disclosure evaluation should be by region. Through this, the effect of spatial interaction between local governments on OGI can be maximized. Third, based on the key determinants from the results of this study, the areas need to be continuously monitored where the expectation is that DRAD is low. To promote data openness that can enhance citizen participation, the study suggests the following measures. First, provide technical support or retraining public officials to small local governments. Second, streamline the workload for filtering personal information and copyright issues when opening public data. Third, consistently publicize open data performance and share best practices for open data at the local level.Chapter 1. Introduction 1 1.1. Backgrounds and Purpose of This Dissertation 1 1.2. The Scope and Method of This Research 7 1.2.1. Research Subject and Scope 7 1.2.2. Research Method 8 1.3. Plan of This Study 10 Chapter 2. Theoretical Backgrounds and Literature Review 11 2.1. Openness of Government Information: Conceptual Definition and Backgrounds 11 2.1.1. Defining Government Information 11 2.1.2. Defining Government Openness: From the Open Government Perspective 14 2.1.3. Definition of Openness of Government Information in This Dissertation 25 2.2. Expected Effects of Openness of Government Information 27 2.2.1. Positive Effects of Openness of Government Information 27 2.2.2. Negative Effects of Openness of Government Information 30 2.3. What Factors Make Governments Open Their Information? 33 2.3.1. Related Theories 33 2.3.2. Prior Studies of Openness of Government Information 46 2.4. Openness of Government Information in Local Government Context 57 2.4.1. Local Government as a Social Actor 57 2.4.2. Institutional Contexts of Korean Local Governments 61 2.4.3. Relatively Neglected Influences on OGI at the Local Level 70 2.5. Summary and Review 75 2.5.1. Summary 75 2.5.2. The Limitations of Prior Studies and Significance of This Research 77 Chapter 3. Methodology 81 3.1. Research Framework 81 3.2. Research Hypotheses 88 3.2.1. Technology-related Factors 88 3.2.2. Organization Factors 91 3.2.3. Environmental Factors 95 3.2.4. Neighboring Government Factor 101 3.3. Measurements and Data Collection 104 3.3.1. Dependent Variables 104 3.3.2. Independent Variables 107 3.3.3. Control Variables 115 3.4. Analysis Plan 119 3.4.1. Model 1: Panel Linear Regression Analysis 119 3.4.2. Model 2: Panel Spatial Regression Analysis 121 Chapter 4. Results 124 4.1. Descriptive Statistics 124 4.1.1. Disclosure Rate of Administrative Documents (DRAD) 145 4.1.2. The Number of Open Data Sets 130 4.1.3. Descriptive Statistics for Independent variables 135 4.2. Determinants of DRAD 143 4.2.1. Results of 143 4.2.2. Results of 148 4.2.3. Summary and Discussion 152 4.3. Determinants of Open Data 156 4.3.1. Results of 156 4.3.2. Results of 160 4.3.3. Summary and Discussion 164 Chapter 5. Conclusion 168 5.1. Summary of This Dissertation 168 5.2. Theoretical and Policy Implications 172 5.3. Limitations and Directions for Future Study 178 Bibliography 180 Appendix 212 Abstract in Korean 214๋ฐ•
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