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  • Changing Support among European Union (EU) Members for the War in Ukraine

    Type:
    Dataset
    Description/Abstract:
    This is a dataset generated as a part of a research project studying the changing support among European Union (EU) members for the war in Ukraine. The dataset contains a number of conditions (variables) used to conduct fuzzy-set qualitative comparative analysis (fsQCA) to test five critical conditions that have shaped the change in public opinion that include economic growth, democratic rule, distance from the front lines, level of energy dependence from Russia and trust in social media. These conditions (or variables) include: Num: Case number in the row MEMBR: EU member state two or three-letter abbreviation WEALTH: GDP per capita in Euro (measured in purchasing power parties) as reported by Eurostat GROWTH: GDP growth in volume based on seasonally adjusted data by Eurostat DEMOCR: the overall score for each EU member’s democracy index for 2022. Data have been drawn from the Economist Intelligence Unit (EIU) 2022 report DISTAN: an average distance (in thousand kilometers) from the geographic center point of the national capital of each EU member-state to the south-western and north-eastern tips of the frontline of the war in Ukraine. I have accepted that the western tip of the frontline is Kinburnsʹka Kosa National Park (Geographic Coordinates: 46°34’37”N 31°30’44”E) and the eastern tip of the frontline is at the village of Topoli in Kharkiv Oblast (Geographic Coordinates: 49°57’52″N, 37°54′31″E). TRADE: volume of trade with Russia per capita in thousand of US Dollars. ENERGY: EU energy dependence on Russia as estmated by the European Commission (from 0 to 100 percent) for 2020. Source: Eurostat. GOVTR: Net trust in national government (difference between the sum of fully trust and partially trust responses and fully distrust and partially distrust responses). MEDIATR: Net trust in social media (difference between the sum of fully trust and partially trust responses and fully distrust and partially distrust responses). ECONSAN: Difference in support for economic sanctions on Russia, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with economic sanctions and partially disagree and totally disagree with sanctions responses). EQUIPS: Difference in support for financial support for providing military equipment for Ukraine, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with financial support for equipment and partially disagree and totally disagree with support for equipment). HUMSAN: Difference in support for humanitarian support for Ukrainians fleeing the war, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with humanitarian support for Ukrainians and partially disagree and totally disagree with humanitarian support for Ukrainians). REFUG: Difference in support for welcoming Ukrainian refugees, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with welcoming Ukrainian and partially disagree and totally disagree with welcoming Ukrainian refugees). AVCHNG: Difference in average change of the support for Ukraine and economic sanctions on Russia, Spring 2022-Spring 2024. WEALTH1: Calibrated score for national wealth (see paper for details) GROWT1: Calibrated score for economic growth (see paper for details) DEMOCR1: Calibrated score for democracy (see paper for details) DISTAN1: Calibrated score for distance (see paper for details) TRADE1: Calibrated score for trade (see paper for details) RENERG1: Calibrated score for energy dependence (see paper for details) GOVTR1: Calibrated score for trust in governance (see paper for details) RMEDIATR1: Calibrated score for trust in social media (see paper for details) ECONSAN1: Calibrated score for support for economic sanctions on Russia (see paper for details, calibration the same as AVCHNG3) MDIASAN1: Calibrated score for media sanctions on Russia (see paper for details, calibration the same as AVCHNG3) AVCHNG3: Calibrated score for average change/ decline for public opinion (see paper for details)
    Creator/Author:
    Ivanov, Ivan
    Submitter:
    Ivan Ivanov
    Date Uploaded:
    04/27/2025
    Date Modified:
    04/27/2025
    Date Created:
    5-01-2024
    License:
    All rights reserved

  • Organizational Response to Emerging Threats: Lessons from NATO and the European Union’s Responses to Peacebuilding, Cyber Threats and Energy Security

    Type:
    Dataset
    Description/Abstract:
    "Organizational Response to Emerging Threats" is a project that addresses three separate threat areas -- cybersecurity, peacekeeping and energy security. The data collection for cybersecurity and energy security has been completed. As of June 2019, the data collection for peacekeeping is ongoing. The project documents are organized around three topics, reflected in the filenames -- cybersecurity, peacekeeping and energy security. The overall purpose/rationale of this research project is to develop a framework that explains how different international organizations (IOs) respond to various emerging threats in international relations. These threats can vary and include cybersecurity, energy security, food security, environmental security, and others. For the purpose of our study we focus on two major variables explaining organizational response: (1) IOs’ capacity to acquire and deploy organizational assets (also referred to as asset fungibility), and; (2) IOs’ ability to make swift decisions in response to changing internal and external environments. Drawing from primary sources including interviews with NATO and EU officials, we suggest a new model explaining when organizations are better equipped at addressing cyber threats, when they have capacity to response more effectively, and what they could do to improve their organizational responses in this area. The QDR repository contains interviews with policy makers and senior bureaucrats conducted in 2016, 2017, 2018 and 2019 in Brussels, Belgium, and the Hague, the Netherlands. These interviews have been conducted in person or over skype. Approval to conduct interviews has been granted by the University of Cincinnati's IRB (Study ID: 2018-3371.
    Creator/Author:
    Ivanov, Ivan
    Submitter:
    Ivan Ivanov
    Date Uploaded:
    10/20/2023
    Date Modified:
    10/20/2023
    Date Created:
    2019-07-22
    License:
    Attribution-ShareAlike 4.0 International