Professor of Department of Southeast Asian Studies, Wenzao Ursuline University of Languages, Kaohsiung,
Taiwan, R.O.C.
Email: 100202@mail.wzu.edu.tw
Cambodia experienced robust economic growth in the 2010s, but the COVID-19 pandemic caused a significant economic contraction in 2020. Despite a strong vaccination campaign and subsequent economic recovery, poverty remains a critical issue, with a significant portion of the population living in or vulnerable to poverty. Microfinance has been promoted as a key tool for poverty alleviation; however, Cambodia’s microfinance sector faces challenges such as high interest rates, collateral requirements, and over-indebtedness among borrowers. This paper explores the history and current state of microfinance in Cambodia, highlighting the discrepancies between its implementation and the original principles of microfinance as envisioned by Muhammad Yunus. It calls for reforms to lower interest rates, adopt more humane debt collection practices, and integrate microfinance with social security systems to better support those in need. These measures are essential to ensure that microfinance can effectively contribute to poverty reduction and sustainable economic growth in Cambodia.
DOI: https://dx.doi.org/10.53106/270308882024101701001
Associate Professor of Department of Business Administration, Shu-Te University, Kaohsiung city, Taiwan, R.O.C.
* Corresponding author: thchen@stu.edu.tw
Graduate School of Business and Administration, Shu-Te University, Kaohsiung city, Taiwan, R.O.C.
Associate Professor of Department of Business Administration, National Pingtung University of Science and
Technology, Ping-Tung, Taiwan, R.O.C.
Associate Professor of School of Innovation, Design and Technology, Wellington Institute of Technology,
Wellington, New Zealand.
Assistant Professor of Department of Business and Commerce, Zhejiang Industry Polytechnic College, Shaoxing,
Zhejiang, China.
This paper primarily explores the challenges associated with Moderated Multiple Regression Models, particularly how a moderator variable (m) influences the direction or strength of the relationship between an independent variable (x) and a dependent variable (Y). A significant issue arises when there is a high correlation between the independent variable and the moderator, leading to severe multicollinearity. That complicates the accurate estimation of the independent variables’ effects on the dependent variable (Myers, 1990).
We develop five moderated multiple regression models with purpose of mitigating the multicollinearity in the analysis. Our empirical findings indicate that three of them perform good tested by the variance inflation factor and condition index. We finally suggest a process of standardizing both independent variable and moderator and taking the cross multiplication by those two standardized variables before conducting moderated multiple regression analysis.
DOI: https://dx.doi.org/10.53106/270308882024101701002
Professor of Department of Business Administration, National Pingtung University of Sci. & Tech., Taiwan,
R.O.C.
* Corresponding author: bear419@mail.npust.edu.tw
An Officer of Air-force R.O.C. and graduate student of Department of Business Administration National Pingtung
University of Sci. & Tech., Taiwan, R.O.C.
The Russia-Ukraine war broke out on February 24, 2022, shaking the international community. To understand the behavior of both Russia and Ukraine in this war, as well as how military and economic aid from the United States, the European Union, and NATO influences Ukraine’s actions, this paper explores the interaction between Ukraine and the U.S.-EU alliance through the viewpoint of welfare game theory. The discussion focuses on how these interactions affect the progress of the Russia-Ukraine war. International political and military activities are based on national interests. The U.S.-EU alliance’s support for Ukraine in resisting the Russian invasion must consider the mutual interests, losses, and related conditions between the U.S., EU, and Ukraine.
DOI: https://dx.doi.org/10.53106/270308882024101701003