İktisadi ve İdari Bilimler Fakültesi / Faculty of Economics and Administrative Sciences

Permanent URI for this collectionhttps://hdl.handle.net/11727/1399

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    An Econophysics Perspective on Green Bonds and Stock Market Nexus: Can Green Finance be an Investment Option for Emerging Stock Markets?
    (Başkent Üniversitesi İktisadi İdari Bilimler Fakültesi, 2024-03-28) Acikgoz, Turker
    Green bonds are one of the most fascinating financial innovations that offer a solution to climate change and sustainable development from the financial point of view. In this study, we employ methods from statistical physics to examine the multifractal features of cross-correlations between green bonds and emerging stock markets. Utilizing multifractal detrended cross-correlation analysis (MFDCCA) on return and volatility series, our findings reveal significant cross-correlations between green bonds and emerging stock markets. The MFDCCA results uncover multifractal features and long-range cross-correlations between the two assets. Notably, volatility cross-correlations exhibit persistent behavior, while return cross-correlations vary across small and large fluctuation periods. These findings hold practical implications for policymakers and investors involved in green bonds and emerging stock markets.
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    AI Pair Programming Acceptance: A Value-Based Approach with AHP Analysis
    (2024 10TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES, 2024) Caldag, Murat Tahir
    The emergence of Artificial Intelligence ( AI) tools is transforming every aspect of life with new opportunities and risks. An impact of AI tools can be seen in AI pair programming which is defined as a generative and creative support tool with real-time interaction. The goal of this study is to explore the AI pair programming acceptance. To identify, describe, categorize, and rank the factors affecting the acceptance of AI pairs a literature review, a research model proposal based on an extension of the Value-based Adoption Model (VAM) framework, and an Analytic Hierarchy Process (AHP) analysis is conducted. The proposed model consists of six main factors and twenty-two sub-factors which are validated with an AHP analysis including eleven experts' judgments. The findings presented the most essential factors as productivity, code accuracy, complexity, personal development, and innovativeness. The least significant factors were inspiration, motivation, intellectual property violation, AI interaction, and trust. This study provides insight to AI tool developers and producers in the context of programming on the key factors to consider for success.
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    A Configurational Approach for Analyzing Cultural Values and Performance in Global Virtual Teams
    (INTERNATIONAL BUSINESS REVIEW, 2024) Sahin, Faruk; Taras, Vas; Cetin, Fatih; Tavoletti, Ernesto; Askun, Duysal; Florea, Liviu
    Although there have been decades of research on the effect of cultural values on team effectiveness outcomes, knowledge of the interdependencies of team cultural values for explaining team performance remains nascent. Using a configurational qualitative approach, this study explores how cultural values combine and collectively contribute to the effectiveness of Global Virtual Teams (GVTs). We perform a fuzzy-set qualitative comparative analysis on a data set of 1847 individuals nested within 396 GVTs who participated in an international business consulting project. The results demonstrate that cultural values work together to achieve high levels of team performance rather than function independently. The results also show that different cultural value configurations could be equally effective at producing the same outcome, and that the presence of gender egalitarianism and the absence of power distance are the most important for producing the outcome. We discuss implications for practice and future research.
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    Causal Effect of Obesity on the Probability of Employment in Women in Turkey
    (ECONOMICS & HUMAN BIOLOGY, 2023) Pekkurnaz, Didem
    This study aims to investigate the causal effect of obesity on the employment probability of women in Turkey via the instrumental variable approach by using data from the 2018 Turkey and Demographic Health Survey. Obesity prevalence in the area of living and the overweight status of the oldest child, which are the most common types of instruments seen in the literature, are used as instruments. Consistent with the OLS result, the 2SLS estimate indicates that obese women are statistically significantly less likely to be employed when the overweight status of the child is used as an instrument. On the other hand, the statistically significant effect of obesity disappears when the area level obesity prevalence is used as the instrument. In addition, obesity in women decreases the likelihood of employment in the services sector and full-time jobs and employment with social security. Although the results of this study do not indicate the source of the effect found, the presence of a causal relationship for women should not be ignored when the economic burden of obesity for Turkey is considered.