• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.49-59
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• 2022

The relationship between income inequality and capital account openness is empirically investigated in this study, where macroeconomic variables have opposing effects. Panel data used in the study from the KAOPEN Index and World Bank consists of 28 Asian countries and has been examined; it contains annual observations from 1970 to 2018. The data is examined using a random-effect model based on GMM estimates. Income inequality and capital account openness are positively and significantly related, according to our findings. Overall, the findings imply that increasing income gaps reduced capital investment in nations with large discrepancies. The growing economic discrepancy is being caused by the rich's increasing income share at the expense of the poor. In Asia, inward capital account openness exacerbates income inequality, while outward capital account openness exacerbates it. As a result, income inequality slows economic growth, leading to inflation, unemployment, and increased government spending in several Asian countries. Our control factors, GDP, and other secondary school enrolments, all had a statistically significant negative relationship with income inequality. Income disparity has a positive and statistically significant association with government spending, inflation, population, trade openness, and unemployment. Income disparity has a negative association with capital account openness, gross domestic product, and secondary school enrollment.

• Journal of Distribution Science
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• v.20 no.11
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• pp.79-88
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• 2022

Purpose: The purpose of this study was to determine the effect of agricultural exports and imports on economic growth in Bangladesh and propose an upgraded and customized model of the supply chain for agribusiness growth in Bangladesh to achieve plain sailing and systematic operation and financial gains at home and abroad. Research design, data, and methodology: All data in the research have been collected from secondary sources. Gross domestic product was used as the dependent variable and exports and imports of agricultural products were used as independent variables. Pairwise Granger causality was utilized to see the impact of the variable responsible for the economic growth in Bangladesh and the causal relationship between the variables analyzed was measured using Johansen co-integration test. Results: From the empirical analysis, the researchers observed that agricultural commodity imports and exports have a unidirectional impact on economic growth in Bangladesh and a long-run causal link with economic growth in Bangladesh. The suggested supply chain model of agribusiness aids in achieving smooth operations, systematic management, and monetary gains both domestically and internationally. Conclusions: This paper contributes to the development of a more effective and profitable agribusiness supply chain in Bangladesh systematically through their theoretical and practical implications.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• SUVANNABHUMI
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• v.15 no.1
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• pp.255-275
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• 2023

Trade between South Korea and Malaysia has been steadily increasing since the conclusion of the multilateral Free Trade Agreement (FTA) between the Association of Southeast Asian Nations (ASEAN) and South Korea. Bilateral FTAs such as Singapore-South Korea, Vietnam-South Korea, and Indonesia-South Korea came into effect to enhance the economic cooperation between South Korea and major ASEAN countries. However, the bilateral FTA between South Korea and Malaysia, known as Republic of Korea-Malaysia FTA, is still under negotiation. Therefore, this study aims to analyze the economic impact of a possible FTA between these two countries. To examine the economic effects of bilateral FTAs, this study analyzes the trade structure and change in the value of trade between Malaysia and South Korea using panel data analysis. Two significant findings were identified by the analysis. First, the Republic of Korea-Malaysia FTA is expected to promote trade and have a positive effect on the Gross Domestic Product (GDP) of South Korea. Second, the result of the calculated price elasticity based on substituting figures such as tariff, demand elasticity, and export value is that the value of manufacturing exports is expected to considerably get an increase. Therefore, an early FTA between South Korea and Malaysia would be beneficial for both national economies.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• Journal of Distribution Science
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• v.22 no.3
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• pp.59-70
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• 2024

Purpose: This study aimed to develop a strategic business conceptual model for large state plantations in West Java Province and Banten Province, Indonesia. The model was built through causal relationships and interrelationships between marketing strategies and business strategies that affect business performance on large state plantations. The plantation sector provides the largest contribution to gross domestic product and is an important part of national food distribution efforts. Research design, data, and methodology: This study used a literature review adapted from Pret and Logan (2019), which followed the guidelines of Tranfield et al. (2003), derived from the Scopus website with Q1/Q2 quartiles and inclusion/exclusion criteria published from 2012 to 2021. Results: Based on a systematic literature review approach, we constructed the strategic business conceptual model for large state plantations based on a combination of four causal and interrelationship variables that affect business performance, namely, industry attractiveness, unique capabilities, innovation management, and collaboration strategy. Conclusions: This research explains the relationship between industry attractiveness variables and unique capability as independent variables that can affect business performance through collaboration strategy and innovation management as intervening variables in the plantation sector, especially large state plantations, which have not been found in previous studies.

• Smart Media Journal
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• v.12 no.11
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• pp.95-102
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• 2023

Road accidents not only caused loss of human lives but also costed 3% of gross domestic product in most of the countries. The road accidents pose significant challenges to public safety and urban transportation management. There is a need to identify the high-risk area of accidents along with the critical day of week and vulnerable time period in order to implement effective preventive measures and optimizing the resource allocation. We collected 5,012 accident data from 대구교통종합정보. This study identified the high-risk locations, days of week, and time periods for accidents in Daegu and estimated the conditional probabilities of accidents occurring based on combinations of location, day of the week, and time period. The result is visualized in the form of dashboard in Tableau. This study holds substantial practical significance for urban planners, transportation authorities, and policymakers in Daegu to strategically allocate resources for traffic management, law enforcement, and targeted safety campaigns.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.19-28
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• 2024

Purpose: In the era of global economic integration, China's doors of openness have widened, leading to increasingly frequent economic and trade exchanges between countries. Exchange rates, as a crucial economic lever for regulating foreign markets, play a vital role in the balanced development of a nation's international trade. Therefore, the relationship between exchange rate fluctuations and foreign trade has garnered widespread attention. Research design, data and methodology: This study utilizes import and export trade data between China and five ASEAN countries from 1998 to 2019. It employs regression analysis to examine the specific impact of the real effective exchange rate of the Renminbi on China's import and export trade with these ASEAN nations. Results: The empirical analysis yields the following conclusions: Firstly, the real effective exchange rate of the Renminbi exhibits a long-term stable relationship with China's import and export trade with the five ASEAN countries. Renminbi appreciation contributes to an increase in export trade volume but is detrimental to import trade. While this conclusion may deviate from classical trade theories, it aligns with the practical realities of China's foreign trade. Secondly, the coefficients before Gross Domestic Product (GDP) all display positive values, indicating that the growth of total economic demand has a stimulating effect on China's import and export trade.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.47-54
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• 2009

These clays, because of world economy recession, exports decreased rapidly and manufacturing industry growth fell into negative. Industrial power consumption has been reduced about 7[%] that forms 53[%] of total load demand in Korea. And also, daily load pattern has been changed in several ways because of power consumption decrease influenced by domestic demand recession and heating power load decreased by the rise in temperature. This research analyzes, by analyzing maximum load demand, average load demand, load pattern based on relative factor, and load sensitiveness in accordance with temperature, that maximum load demand is more sensitive to atmospheric temperature than GDP growth rate and average load demand tends to be reduced according to GDP growth rate. I suppose KPX could operate the network system economically and safely by forecasting load demand in winter and summer seasons based on the results.

• Journal of Navigation and Port Research
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• v.37 no.6
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• pp.719-725
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• 2013

Northeast Asia region is becoming the hub of world trade with China as the center. Integration of this region's economy is now visualized, domestic trade and international division of labor will be more invigorated. Especially on electrical and electronics industry is a large proportion of the trading volume between Korea and China and now, Present condition of electrical and electronics trading industry can effect on whole trading industry. In this study, conducting analysis of the current Korea-China electrical and electronics industry trading and advanced research, and find out the implication to trading volume with the panel analysis. As the results Korean/Chinese GDP, revealed comparative advantage, and foreign direct investment have an effect on the trading volume.