政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143830

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143830

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政大典藏 > College of Social Science > Department of Public Administration > Theses > Item 140.119/143830

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/143830

Title:	探索開放政府程度與各國COVID-19期間貪腐控制下降之相關性 Exploring the Association between the Level of Open Government and Decline on Corruption Control Cross Countries During COVID-19
Authors:	莊旻煒 Chuang, Min-Wei
Contributors:	廖興中 Liao, Hsing-Chung 莊旻煒 Chuang, Min-Wei
Keywords:	開放政府 CPI全球清廉印象指數 COVID-19 貪腐開放資料 Open government Corruption Perception Index COVID-19 Corruption Open data
Date:	2023
Issue Date:	2023-03-09 18:36:07 (UTC+8)
Abstract:	CPI全球清廉印象指數在2021年的年度報告中指出，各國的貪腐控制呈現惡化的狀態，此報告及大多數國家認為COVID-19的爆發正是導致貪腐控制弱化的最大主因。然而縱貫各國公共行政的發展上，各國已推行開放政府好一陣子，大部分國家也認為開放政府所強調的透明與課責理論上可以增加貪腐控制程度，這也造成各國在COVID-19爆發後的貪腐控制呈現惡化的原因令人格外好奇。本研究提供一個全新的觀點，從COVID-19爆發的時間點切入以利了解開放政府程度、開放資料程度以及各個貪腐相關因素，對於貪腐控制的落差有無相關性。本研究首先探討貪腐的意涵，並說明貪腐指標的選擇，接著則是探討開放政府的意涵以及運作，以及說明開放政府與開放資料指標的選擇。最後則將可測量的貪腐相關因素、開放政府指標、開放資料指標以及貪腐控制製成模型。透過敘述統計與迴歸分析來探究COVID-19期間貪腐控制下降的原因。研究發現一個國家本身經濟自由程度、法律完善程度、媒體自由程度、人均GDP高低以及開放資料程度，對於COVID-19期間貪腐控制下降並無任何的相關性。然而開放政府程度越高的國家，在COVID-19爆發期間，卻可以有效的抑制貪腐，而形成更好的貪腐控制。整體而言，雖然開放政府的相關措施可以有效抑制貪腐的形成，並以此增加貪腐的風險。但是回首CPI全球清廉印象指數所提出各國貪腐控制惡化的結論，我們可以知道開放政府程度並不是完全抑制貪腐惡化的唯一解藥。也就是說，COVID-19爆發期間所造成新興或是加重舊有貪腐情形的問題，才有可能是貪腐控制惡化的主因，需從問題根本來消除，才能減低貪腐惡化的結果。 The 2021 CPI Corruption Perception Index annual report pointed out that corruption control in various countries has deteriorated. This report believe that the outbreak of COVID-19 is the biggest reason for the weakening of corruption control. However, throughout the development of public administration in various countries, countries have been promoting open government for a long time. Most countries also believe that open government emphasized transparency and accountability can theoretically increase the degree of corruption control. So the reasons for the deterioration of corruption control after COVID-19 outbreak are particularly curious. This study provides a new perspective, starting from the time point of the outbreak of COVID-19 to understand whether the degree of open government, the degree of open data, and various corruption-related factors are related to changes in corruption control. This study first explores the meaning of corruption and explains the selection of indicators of corruption. Second, explores the meaning and operation of open government and explains the selection of open government and open data indicators. Finally, measure the corruption-related factors, open government indicators, open data indicators, and corruption controls to exploring the reasons for the decline of corruption control during COVID-19 through descriptive statistics and regression analysis. The study found that a country`s own degree of economic freedom, legal perfection, media freedom, GDP per capita, and open data have no correlation with the decline in corruption control during COVID-19. However, countries with a higher degree of open government can effectively suppress corruption and form better corruption control during the outbreak of COVID-19. Although the relevant measures of open government can effectively restrain the formation of corruption, and increase the risk of corruption. But looking back at the conclusions of the CPI Corruption Perception Index on the deterioration of corruption control in various countries, we can know that the degree of open government is not the only antidote to completely curb the deterioration of corruption. In other words, the emerging or exacerbating problems of corruption during the outbreak of COVID-19 may be the main reason for the deterioration of corruption control. Only by eliminating the problems at their root can the results of corruption deterioration be reduced.
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Description:	碩士國立政治大學公共行政學系 109256020
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0109256020
Data Type:	thesis
Appears in Collections:	[Department of Public Administration] Theses

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