Total factor productivity (TFP) is essential for disentangling the determinants of economic growth, productivity, and the standard of living. Understanding the variations in TFP, however, is greatly challenging because of the many assumptions that comprise the theoretical growth framework. In this paper, we aim to explore the determinants of TFP growth for countries at different stages of information and communication technology (ICT) development. To address the endogenous nature of the associated growth variables, we implement a three-stage-least (3SLS) square panel regression to improve the efficiency and asymptomatic accuracy of the estimators. We find that transmission channels, such as financial openness and trade globalization, have contributed substantially to growth in both advanced and developing countries. However, we also discover that greater financial openness can undermine a country’s TFP growth if the financial system is not sufficiently developed. When time horizons are decomposed into pre-ICT development and post-ICT development periods, a significant crowding-out effect is observed between ICT investment and financial openness in the pre-period, implying that the allocation of resources is critical for countries in the developing stage. Trade and finance policies that are adopted by advanced and developed countries might not be ideal for underdeveloped countries. Discretion in choosing adequate policies regarding financial integration and trade liberalization is advised for these emerging countries.
This study aims at predicting the interrelationship between among Chat GPT with its six dimensions, tourist’s satisfaction and Chat GPT usage intention as perceived by tourist, and as well as to examine the moderating effect of traditional tour operator services on the relationships between all the variables. Data were collected from 624 tourists. The study hypotheses were tested and the direct and indirect effects between variables were examined using the PLS-SEM. The SEM results showed that Chat GPT’s six dimensions have a positive and significant direct impact on tourist’s satisfaction, and emphasis the moderating role of Traditional Tour Operator Services “TTOS” on the relationship between GPT’s six dimensions and “TS”, and on the relationship between ‘TS” and Chat GPT usage intention. These findings yield valuable insights for everyone interested in the use of IT in the tourism industry, and provide effective strategies for optimizing the use of technological applications by traditional tour operators.
The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machine learning models to analyze the risk for the management decision policies of developed organizations. The performance of the chosen model Neural Network (MLP) was improved after applying the tuning process which increased the Test R2 from −0.37686 before tuning to 0.195637 after tuning. The Support Vector Machine (SVM), Ridge Regression, Lasso Regression, and Random Forest (Tuned) models did not improve, as seen when Test R2 is compared to the experiments. No changes in Test R2’s were observed on GBM and XGBoost, which retained same Test R2 across different tuning attempts. Stacking Regressor was used only during the hyperparameter tuning phase and brought a Test R2 of 0. 022219.Decision Tree was again the worst model among all throughout the experiments, with no signs of improvement in its Test R2; it was −1.4669 for Decision Tree in all experiments arranged on the basis of Gender. These results indicate that although, models such as the Neural Network (MLP) sees improvements due to hyperparameter tuning, there are minimal improvements for most models. This works does highlight some of the weaknesses in specific types of models, as well as identifies areas where additional work can be expected to deliver incremental benefits to the structured applied process of risk assessment in organizational policies.
The following paper assesses the relationship between electricity consumption, economic growth, environmental pollution, and Information and Communications Technology (ICT) development in Kazakhstan. Using the structural equation method, the study analyzes panel data gathered across various regions of Kazakhstan between 2014 and 2022. The data were sourced from official records of the Bureau of National Statistics of Kazakhstan and include all regions of Kazakhstan. The chosen timeframe includes the period from 2014, which marked a significant drop in oil prices that impacted the overall economic situation in the country, to 2022. The main hypotheses of the study relate to the impact of electricity consumption on economic growth, ICT, and environmental sustainability, as well as ICT’s role in economic development and environmental impact. The results show electricity consumption’s positive effect on economic growth and ICT development while also revealing an increase in pollutant emissions (emissions of liquid and gaseous pollutants) with economic growth and electricity consumption. The development of ICT in Kazakhstan has been revealed to not have a direct effect on reducing pollutant emissions into the environment, raising important questions about how technology can be leveraged to mitigate environmental impact, whether current technological advancements are sufficient to address environmental challenges, and what specific measures are needed to enhance the environmental benefits of ICT. There is a clear necessity to integrate sustainable practices and technologies to achieve balanced development. These results offer important insights into the relationships among electricity consumption, technology, economic development, and environmental issues. They underscore the complexity and multidimensionality of these interactions and suggest directions for future research, especially in the context of finding sustainable solutions for balanced development.
The Belt and Road Initiative (BRI) aims to enhance connectivity and collaboration among 60 countries and beyond in Asia, Africa and Europe. Information and communications technology (ICT) is an indispensable component of the initiative, critical in providing fundamental communication channels for global financial transactions, trade exchanges and transport and energy connectivity, and socio cultural collaboration and scientific exchanges between people, organizations and countries along the BRI corridors. Previously constrained by infrastructure deficits in ICT, the Asia-Pacific region is accelerating its efforts to provide reliable and affordable broadband networks throughout the region, to contribute to successful implementation of the Sustainable Development Goals (SDG).
Within the BRI corridors, this study which has been undertaken as part of the research programme of the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) on promoting regional economic cooperation and integration, focuses on the China-Central Asia Corridor (China, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan), giving attention to the sub-region’s specific challenges, namely limited international transit opportunities and an increase in bandwidth requirements that is expected to grow exponentially, as the fourth industrial evolution centered on automation and artificial intelligence gathers momentum. The sub-region is characterized as highly dependent on the ease and costs of connecting to neighboring countries for transit, as many countries in the sub-region are landlocked developing countries (LLDC). Because of the geographical features and other factors, the development potential of Central Asia and its integration into globalization, continues to be stymied by insufficient international bandwidth and high transit costs to access international links. Therefore, improved ICT connectivity in Central Asia through the BRI corridor could result in improved availability and affordability of broadband networks and services in the sub-region.
For the purpose of this study, a gap analysis is the methodology that underpins the proposed topology for the China-Central Asia Corridor. The analysis included examining the current state of the optic infrastructure, such as existing and planned fiber-optic networks, existing Internet Exchange Points (IXPs) and international gateways. The study also identifies the key factors that determine the desired future state of infrastructure deployment for the BRI initiative. A topology that consists of connecting Almaty (Kazakhstan) and Urumqi (China), as core nodes, is proposed based on a partial mesh topology. Over and above this core finding, the study concludes that digital infrastructure connectivity has a tendency of lagging behind the rapid opportunities evolving, and the study therefore advocates for sub-regional and regional approaches, including the BRI and Asia-Pacific Information Superhighway (AP-IS) in further expanding regional broadband networks. A key recommendation of the study is co-deployment of broadband infrastructure along passive infrastructure, as an additional cost effective means of achieving fast and affordable broadband connectivity for all.
Road construction and maintenance are key interventions that support economic potential in the country. However, the deplorable state of some roads in Nigeria, and in Cross River and Akwa Ibom states draws research concerns. This paper seeks to examine the impact of the Niger Delta Development Commission Intervention on road construction and economic activities in Cross River and Akwa Ibom States, Nigeria. Using the Sustainable Development Framework, a survey research design was employed, gathering data from 400 respondents across both states. The chi-square statistical technique was used to test the hypothesis that the Niger Delta Development Commission Intervention has no significant impact on road construction in Akwa Ibom and Cross River States. The result of the data analysis showed the calculated value X2 = 1592 > 16.92. By this result, the null hypothesis was rejected (16.92) at 0.05 level of significance and 9 Degrees of Freedom, and the alternate was accepted. The study concludes that NDDC road projects have positively influenced economic activities and livelihoods in the states. However, it highlights the need for further improvements, particularly on the Calabar-Itu federal highway.
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