The second volume of the book contains a series of empirical research on logistics transportation in Ho Chi Minh City, Vietnam. The study purpose is to examine which characteristics of institutions effect on logistics transport productivity and how they impact. There are ten chapters in all. People's participation at the grassroots level and the impact of public service supply on products productivity calculated on labour, passenger productivity calculated on labour, and passenger productivity calculated on capital are two of the most notable discoveries. People's accountability and public administrative procedures have an impact on goods productivity based on labour. The governmental sector's transparency and control of corruption have an impact on passenger productivity as measured by labour. Controlling corruption in the public sector has an impact on capital-based passenger productivity. (Chapter 2) examines the impact of physical infrastructure on logistics transportation development in Ho Chi Minh City, Vietnam (HCM). To assess using separable MR models, the author utilises multivariate regression (MR). The main conclusions are that road length, road quality, railway line length, and airway quality all have an impact on freight productivity/total labour. The length of the road, the quality of the road, the length of the railway line, the number of aircraft units departing internationally, the quality of the airway, and the connectivity between domestic and international airports all have an impact on passenger productivity / total labour. The length of the road, the quality of the road, the length of the railway line, the number of aircraft units departing internationally, the quality of the airway, and the link between domestic and international airports all have an impact on cargo productivity / total capital. The length of the road, the length of the railway line, the quality of the railway, the quality of the airway, and the link between domestic and international airports all have an impact on passenger productivity / total capital. PI1, PI2, PI3, PI4, PI5, PI6, PI7, and PI8 are all independent factors that have an impact on the GDP of logistics transport in HCM. (Chapter 3) assesses the influence of six independent variables of ITI on logistics transport development using multivariate regression to measure the function of information technology infrastructure (ITI) in the growth of logistics transport (MR). The major findings are that the quantity of broadband subscriptions and international internet traffic have an impact on labour productivity. The quantity of secure Internet connections and broadband subscriptions have an impact on passenger productivity. The amount of secure Internet connections and ADSL internet subscribers have an impact on capital goods productivity. The number of ADSL internet customers, international internet traffic, and mobile network subscriptions all have an impact on GDP. (Chapter 4) The key conclusions are that while government spending and foreign investment have an impact on labour productivity, the openness of the economy has little effect. While government spending and foreign investment have an impact on labour productivity, the openness of the economy has no effect. While foreign investment has an impact, government budget investment and the openness of the economy have little effect on capital goods productivity. While foreign investment has an impact, government budget investment and economic openness have no effect on capital passenger productivity. While government budget investments and foreign investment have an impact on GDP, the openness of the economy has little effect. CO2, methane, and other emission variables produce air pollution, which has an impact on labour goods production (Chapter 5). The impact of methane on passenger productivity in Labour is significant. Impact of CO2 and Methane on Gross Domestic Product. Total number of labour force, total number of female labour force, total number of labour force who have been career trained, and total number of labour force who have completed high school impact on products productivity estimated on total number of employees are some of the key results in Chapter 6. While the total number of employees and the total number of employees who have completed high school have an impact on passenger productivity, the total number of female employees and the total number of employees who have completed career training have no impact. While the total number of female workers, total number of career workers, and total number of high school graduates have an impact on goods productivity calculated on total capital, the overall number of workers has no impact on goods productivity calculated on total capital. While the total labour force and the total labour force who have completed high school have an impact on GDP, the total female labour force and the total labour force who have completed career training have no impact. (1) While total number of firms, fixed assets, and long-term investment capital have an impact, total capital for yearly company operations has no impact on products productivity, which is calculated on labour (Chapter 7). (2) While the total number of businesses and total capital for yearly business operations have an impact on passenger productivity, fixed assets and long-term investment capital have no impact on labour productivity. (3) While the total number of businesses, fixed assets, and long-term investment capital have an impact on goods productivity, total capital for yearly business operations has no impact. (4) While the total number of businesses, fixed assets, and long-term investment capital have an impact on passenger productivity, total capital for yearly business operations has no impact. (5) The impact on GDP of the total number of businesses, total capital for yearly company operations, fixed assets, and long-term investment capital. (Chapter 8) The key conclusions are that while population in rural and urban areas have an impact, female and male population have no impact on cargo productivity as measured by labour in the Logistics Transport Industry (LTI). While residents in rural and urban areas have no effect on passenger productivity, female and male passengers have an impact on LTI labour productivity. While the genders of the population have an impact on GDP, the genders of the population in rural and urban areas have no impact. The key conclusions of Chapter 9 are that, while registered FDI capital and the number of FDI projects have an impact on freight productivity calculated on labour in the logistics transport business, operating FDI capital has no impact (LTI). While the quantity of FDI projects and operating FDI capital have an influence, registered FDI capital has no impact on passenger productivity as measured by labour in LTI. While registered FDI capital and the quantity of FDI projects have an impact on freight productivity, which is computed using capital in LTI, operating FDI capital has no impact. While both registered and running FDI have an impact on GDP, the number of FDI projects has no impact. The cumulative percent of impact of the labour force on the state sector, the labour force on the outside state sector, and the labour force on the foreign investing sector ranges from 14 percent to 100 percent (Chapter 10). The lowest percentage was 10% in 2005. The greatest level in 2019 is 100 percent. Between 2006 and 2015, the cumulative percent of logistics transit development that will be impacted increased, with the lowest level being 7% and the greatest level being 100%. The cumulative percent of influence of the labour force on the state sector, the outside state sector, the foreign investment sector, and the cumulative percent of logistics transport development to be impacted are all at different levels.
Author(s) DetailsVu Thi Kim Hanh
University of Economics and Law, Vietnam National University Ho Chi Minh City, Vietnam.
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