Sürdürülebilir Kalkınma Amaçları
Yazarlar
Yayınlar
- MakaleYalnız künye2024Nexus between good governance and financial sustainability: evidence from microfinance sector of India
Maeenuddin, M.; Hamid, Shaari Abdul; Nassir, Annuar Md; Fahlevi, Mochammad; Aljuaid, Mohammed; Jermsittiparsert, Kittisak
Purpose: Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs). Design/methodology/approach: A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018. Findings: The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India’s microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India. Originality/value: To the best of the authors’ knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs).
- MakaleAçık Erişim2024Measuring the Financial Sustainability and its Influential Factors in Microfinance Sector of Pakistan
Maeenuddin; Hamid, Shaari Abd; Nassir, Annuar MD; Fahlevi, Mochammad; Aljuaid, Mohammed; Jermsittiparsert, Kittisak
Financial sustainability is one of the major issues in the development process, particularly in developing countries. Microfinance started with two basic objectives of poverty reduction and women empowerment. However, unsustainable microfinance providers cannot assist the poor for a longer period of time, due to uncertainty about their existence. This study investigates that how financial sustainability of Pakistan’s microfinance sector is affected by various factors. A new financial sustainability index has been developed to measure the financial sustainability. Generalized Method of Moments (GMM) approach is employed to analyze the panel data from 34 Pakistani MFPs, yielding 344 MFI-years of observations from 2006 to 2018. The findings reveal that increase in loan size, female borrowers, liquidity, and leverage significantly enhances the financial viability of Microfinance Providers in Pakistan. However, the total borrowers and the operating cost per borrower negatively affect the financial sustainability of MFPs in Pakistan. MFIs needs to be financially independent, with less or no support from government or donor agencies. Financially sustainable MFPs contributes in the achievement of the 8 out of 17 Sustainable Development of Goals (2030 SDGs) of the United Nation. The data for 2018 onwards is seriously affected by COVID-19, which cannot be included in the current data set. Hence, researchers in future analyze the data from the pre-COVID-19 and post-COVID-19 periods to compare the analysis and examine the pandemic’s impact.
- MakaleAçık Erişim2022Autonomous Energy Management by Applying Deep Q-Learning to Enhance Sustainability in Smart Tourism Cities
Suanpang, Pannee; Jamjuntr, Pitchaya; Jermsittiparsert, Kittisak; Kaewyong, Phuripoj
Autonomous energy management is becoming a significant mechanism for attaining sustainability in energy management. This resulted in this research paper, which aimed to apply deep reinforcement learning algorithms for an autonomous energy management system of a microgrid. This paper proposed a novel microgrid model that consisted of a combustion set of a household load, renewable energy, an energy storage system, and a generator, which were connected to the main grid. The proposed autonomous energy management system was designed to cooperate with the various flexible sources and loads by defining the priority resources, loads, and electricity prices. The system was implemented by using deep reinforcement learning algorithms that worked effectively in order to control the power storage, solar panels, generator, and main grid. The system model could achieve the optimal performance with near-optimal policies. As a result, this method could save 13.19% in the cost compared to conducting manual control of energy management. In this study, there was a focus on applying Q-learning for the microgrid in the tourism industry in remote areas which can produce and store energy. Therefore, we proposed an autonomous energy management system for effective energy management. In future work, the system could be improved by applying deep learning to use energy price data to predict the future energy price, when the system could produce more energy than the demand and store it for selling at the most appropriate price; this would make the autonomous energy management system smarter and provide better benefits for the tourism industry. This proposed autonomous energy management could be applied to other industries, for example businesses or factories which need effective energy management to maintain microgrid stability and also save energy.