Statistical Study on the Impact of Digital Economy on Zambia’s Banking Sector

Digital economy is one of the important contributions to the development and growth of a country; it is because of this that Zambia sought to include digital technology in their national development plan and it has existed for over a decade.  The introduction of digital technologies in the country has given commercial banks an opportunity to embrace digital technology.  Commercial banks are investing in technology because they are inclined to the view that advancement in technology improves quality service delivery, brings about competitive advantage as well as profitability.  Among the innovative products introduced include electronic banking services such as mobile banking, ATM (credit cards), internet banking to mention but a few. It is for this reason that, this research paper focuses on the statistical study on the impact of digital economy on Zambia’s banking sector.  The study was based on the data gathered from 10 commercial banks in Zambia.  In order to access how digital technology has impacted the banking sector, customer satisfaction and bank’s financial performance were measured.  For the first analysis, a SERVPERF model was used to examine customer satisfaction on e-banking’s service quality. The spearman’s correlation coefficient was used to find out the relationship between the variables, the results indicated that there existed a negative relationship between e-banking’s service quality and customer satisfaction, and it was significant.  The second analysis used the regression analysis model to measure the financial performance of Zanaco Bank.  Zanaco bank was the first to introduce electronic banking services in the country, therefore this study aimed at analyzing how e-banking services have influenced the bank’s financial performance.  Return on assets (ROA) as a measure of financial performance was measured against the independent variables (ATM transactions, Mobile banking and internet banking.  The results of the analysis revealed that there was no significant relationship between e-banking services and financial performance. Keywords: Digital economy, E-banking, Customer satisfaction, financial performance

Comparative Analysis of e-Commerce Between China and Uzbekistan.

This research work is devoted for the purpose of showing the diverse opportunities and unravel the growing trends of e-Commerce in terms of trade between China and Uzbekistan. On-line customer research has been carried out mainly for American and European markets by academics and marketers. While e-Commerce is developing more rapidly in China with big companies raking in billions, it is somehow slow in Uzbekistan; a profound understanding of necessitating modalities is a fundamental drive into promoting further growth. This work investigates this intriguing concept in context of e-Commerce involved in inquiring about e-Business and corresponding e-Payment systems in China and Uzbekistan respectively. The article features theoretical segments through which statistical models and correlations were interpolated. The main aim being to establish segmental information and identify influential factors of e-Shopping using e-Payment models developed in the respective countries. The key findings include the geographical influence, demographic statistical analysis and internet technologies being used in the two countries

The Impact of China-Burkina Faso Trade on Burkina Faso Economic Growth

The impact of trade expansion of China on Burkina Faso's economy is analyzed in this work through these two channels: trade in goods and services, foreign direct investment. To capture the direct and indirect effects of Chinese trade, a computable general equilibrium model is used. The different simulations that have been used are gathered in groups. The first group includes an increase of the transfers from China to Burkina Faso by 10%, an increase of 5% of the stock of productive capital, an increase of 2% in the total factor productivity. The second group includes an expansion of the exports from Burkina Faso to China by 5%w; a decrease of international export prices of manufactured products plus an increase in international prices of export commodities; and a decrease of the international import prices of products from China. The simulation results show that the simulations of trade expansion have led to an increase of domestic prices, exports and imports from China. In addition, the effect on economic growth, value added and household’s welfare is low. Regarding the first group of simulations, the results show a decline of domestic prices, and an increase of exports and a decrease of imports. More FDI inflows induce a raise of economic growth equal to 1.90%, of total labor demand 0.08% and an increase of the average well-being of household by 1.41%. The majority of the population in Burkina Faso is cotton farmers and they are those who welfare raise the more 1.81. China’s trade expansion is now playing a very important role in the global economy. More especially to the increasing investment in developing countries, China has also gained an important place among the main countries providing development assistance. For the past 15 years, and especially since the establishment of the “Forum on China-Africa Cooperation” (FOCAC), China has been one of the main economic partners of Sub-Saharan Africa both in terms of trade, investment and development aid. Some researchers from Burkina Faso are also investigating to measure the impact of this expansion of Chinese presence and trade on economic growth and employment in Burkina Faso. Keywords: trade expansion, economic growth, impact, computable general equilibrium, simulation, China, Burkina Faso DOI: 10.7176/JESD/11-22-05 Publication date: November 30th 202

Study on China’s Investment In Central Asia

The article is devoted to the current topic of today - politics and the economy of China with the countries of Central Asia. The paper poses the problems of China’s interests in Central Asia, as well as the prospects for cooperation between these countries. China\u27s role in development of the modern economy is steadily increasing, and therefore the vector investment cooperation with this country is one of fundamental for the countries of Central Asia, which, in addition, are neighbors of China. For China, which has a very limited stock of natural resources, countries rich in oil, gas, and other resources become of strategic importance. The purpose of the study is to identify the results of a comparative analysis of the main interests of the PRC in the Central Asian region, namely in Kazakhstan and to determine the effect of three economic data on Chinese direct investment. To achieve this goal, the \u27\u27Kao Residual Cointegration Test\u27\u27 and the “Pooled Least Squares" method were used. The research work is using the EViews software and the Pool Least Squares method. The main results were identified and shown in schematic form. The interests and volume of investments of the People’s Republic of China in Central Asia were identified in this area. The article has practical value and can be offered for reading to a different target audience

The nexus of transport connectivity and infrastructure with trade growth in the ECOWAS region.

The impact of transport connectivity and infrastructure on trade and overall economic development in the West African region cannot be over emphasized. Generally, it has been established that poor transportation systems have negative knock-on effects on the economies of countries. Thus, this study identifies and discussed the barriers and facilitators regarding transport connectivity，performance of trade and overall economic development of member countries of the ECOWAS region. We develop a gravity model to assess the impact of transport connectivity and infrastructure on bilateral and intra-regional trade across the study region. Also, multilateral trade resistance (MTR) terms are included in the modelling structure as a variable to capture the comparative trade cost between transacting partner economies. The outcome of the analysis indicates a positive connection between transport connectivity and infrastructure along with international and intra-regional trade. This implies that transport connectivity and infrastructure impact the overall growth and performance of trade in the ECOWAS region and the level of impact is statistically significant. The analysis show that including a rail connection between trading country partners in the study area will result in an average upsurge of trade performance by 3.5 per cent. Similarly, the results also prove that a 10 per cent decrease in the distance of sea and air upsurges trade by 0.52 per cent and 0.31 per cent, respectively. Likewise, improving the rail and road density of the trading partner countries ranked as the second factor that contributes greatly to improving trade performance in the study area. Similarly, the performance of logistics (such as LPI) indicates a substantial and comparatively robust impact on the flow of international and intra-regional trades. Key words: ECOWAS, MTR, LPI, LSCI, transport connectivity, transport infrastructure, gravity model

Hyperspectral Classification of Hazardous Materials Based on Deep Learning

The identification of hazardous materials is a key measure in the prevention and control of fire and explosion disasters. Conventional techniques used to identify hazardous materials include contact detection and post-sampling laboratory testing, which cannot meet the needs of extreme environments, where personnel and equipment are not accessible for on-site detection. To address this problem, this paper proposes a method for the classification and identification of hazardous materials based on convolutional neural networks, which can achieve non-contact remote detection of hazardous materials. Firstly, a dataset containing 1800 hyperspectral images of hazardous materials, which can be used for deep learning, is constructed based on the hazardous materials hyperspectral data cube. Secondly, based on this, an improved ResNet50-based classification method for hazardous materials is proposed, which innovatively utilizes a classification network based on offset sampling convolution and split context-gated convolution. The results show that the method can achieve 93.9% classification accuracy for hazardous materials, which is 1% better than the classification accuracy of the original ResNet50 network. The network also has high performance under small data volume conditions, effectively solving the problem of low classification accuracy due to small data volume and blurred image data features of labelled hazardous material images. In addition, it was found that offset sampling convolution and split context-gated convolution showed synergistic effects in improving the performance of the network

Identification of Urban Rainstorm Waterlogging Based on Multi-source Information Fusion：A Case Study in Futian District, Shenzhen

Flood disasters have become one of the most threatening natural disasters in the world, in which waterlogging is the most common form in the context of highly urbanized megacities. The formation of flood disaster is related to many factors and involves information from multiple sources, making it difficult be predicted. This paper integrates multi-source information data, classifies the study area into different categories according to hydrological analysis results, and combines hydrodynamic theory and ArcGIS to get the quantitative prediction of the range and depth of waterlogging under different rainfall inputs. The evaluation results provide the government with accurate and timely information of waterlogging risks and locations in order to improve promptness of emergency management such as evacuation and managing traffics

Polyoxovanadate-Based Cyclomatrix Polyphosphazene Microspheres as Efficient Heterogeneous Catalysts for the Selective Oxidation and Desulfurization of Sulfides

The [V6O13]2− cluster is successfully immobilized to the polymeric framework of cyclomatrix polyphosphazene via the facile precipitation polymerization between the phenol group symmetrically modified [V6O13]2− and hexachlorocyclotriphosphazene. The structure of the as-prepared polyoxometalate-containing polyphosphazene (HCCP-V) was characterized by FT-IR, XPS, TGA, BET, as well as SEM and zeta potential. The presence of a rigid polyoxometalate cluster not only supports the porous structure of the polymeric framework but also provides an improved catalytic oxidation property. By using H2O2 as an oxidant, the as-prepared HCCP-V exhibited improved catalytic oxidation activity toward MPS, DBT, and CEES, which can achieve as high as 99% conversion. More importantly, the immobilization of POMs in the network of cyclomatrix polyphosphazene also provides better recyclability and stability of the heterogeneous catalyst

Investigation on Blending Effects of Gasoline Fuel with N-Butanol, DMF, and Ethanol on the Fuel Consumption and Harmful Emissions in a GDI Vehicle

The effects of three kinds of oxygenated fuel blends—i.e., ethanol-gasoline, n-butanol-gasoline, and 2,5-dimethylfuran (DMF)-gasoline-on fuel consumption, emissions, and acceleration performance were investigated in a passenger car with a chassis dynamometer. The engine mounted in the vehicle was a four-cylinder, four-stroke, turbocharging gasoline direct injection (GDI) engine with a displacement of 1.395 L. The test fuels include ethanol-gasoline, n-butanol-gasoline, and DMF-gasoline with four blending ratios of 20%, 50%, 75%, and 100%, and pure gasoline was also tested for comparison. The original contribution of this article is to systemically study the steady-state, transient-state, cold-start, and acceleration performance of the tested fuels under a wide range of blending ratios, especially at high blending ratios. It provides new insight and knowledge of the emission alleviation technique in terms of tailoring the biofuels in GDI turbocharged engines. The results of our works showed that operation with ethanol–gasoline, n-butanol–gasoline, and DMF–gasoline at high blending ratios could be realized in the GDI vehicle without any modification to its engine and the control system at the steady state. At steady-state operation, as compared with pure gasoline, the results indicated that blending n-butanol could reduce CO2, CO, total hydrocarbon (THC), and NOX emissions, which were also decreased by employing a higher blending ratio of n-butanol. However, a high fraction of n-butanol increased the volumetric fuel consumption, and so did the DMF–gasoline and ethanol–gasoline blends. A large fraction of DMF reduced THC emissions, but increased CO2 and NOX emissions. Blending n-butanol can improve the equivalent fuel consumption. Moreover, the particle number (PN) emissions were significantly decreased when using the high blending ratios of the three kinds of oxygenated fuels. According to the results of the New European Drive Cycle (NEDC) cycle, blending 20% of n-butanol with gasoline decreased CO2 emissions by 5.7% compared with pure gasoline and simultaneously reduced CO, THC, NOX emissions, while blending ethanol only reduced NOX emissions. PN and particulate matter (PM) emissions decreased significantly in all stages of the NEDC cycle with the oxygenated fuel blends; the highest reduction ratio in PN was 72.87% upon blending 20% ethanol at the NEDC cycle. The high proportion of n-butanol and DMF improved the acceleration performance of the vehicle