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Since the introduction of the outstanding web AI chat system, ChatGPT, it has caused a significant impact in both academia and the business world. Many studies have started to explore its potential applications in various fields. However, there is a lack of research from the perspective of user experience. To fill this theoretical gap and provide a theoretical basis for the operation and design of related services, this study plans to develop a set of evaluation scales for AI chat system user experience and explore the relationship between various factors and user satisfaction.

This study obtained 41 evaluation indicators through literature review and user research. Subsequently, these indicators were used as questionnaire items, combined with satisfaction metrics. A total of 515 questionnaires were distributed, and factor analysis and linear regression were employed to determine the specific elements influencing user experience and the user satisfaction model.

This study found that the factors influencing user experience are usefulness, accuracy, logical inference, interactivity, growth, anthropomorphism, convenience, credibility, ease of use, creativity, and security. Among these factors, only accuracy, anthropomorphism, creativity, and security indirectly influence satisfaction through usefulness, while the rest of the factors have a direct positive impact on user satisfaction.

This study provides constructive suggestions for the design and operation of related services and serves as a reference for future theoretical research in this area.

Nuclear energy investments contribute significantly to the energy independence of countries. This situation helps countries to develop both economically and socially. Therefore, countries need to develop strategies to increase their nuclear energy investments. However, radioactive waste generated in nuclear reactors is one of the most important disadvantages of this type of energy. Due to this situation, the wastes generated must be disposed of effectively for nuclear energy investments to be effective. In this study, it is aimed to create optimal strategies for the effective waste managements generated in nuclear power plants. Within this framework, four different balanced scorecard perspectives are considered as the criteria. In the analysis process, Analytical Hierarchy Process (AHP) methodology is taken into consideration. It is identified that learning and development is the most critical factor for the effective radioactive waste management created in nuclear power plants. On the other side, internal factors are the second most important criterion in this framework. Hence, it is understood that nuclear energy investors should give priority to the technological development for effective waste management in nuclear power plants. With the help of these technological improvements, the wastes can be disposed more successfully. As a result, environmental sustainability can be provided much easily.

The purpose of this study is to analyze the nonlinear relationship between electricity consumption (EC) and electricity transmission losses (ETL) in Ghana. Also, we examined how ETL moderate the effect of EC on economic growth in Ghana from 1980 to 2021.

We used timeseries data from 1980 to 2021 within an autoregressive distributed lag framework to analyze the links among ETL, EC and economic growth in Ghana.

Findings show the existence of an asymmetric long-run relationship between EC and ETL. Also, the negative effects of ETL on EC are bigger in the long run. In addition, ETL and EC combine to reduce economic growth, in the long run, providing evidence for the energy-led growth theory in Ghana. Population and inflation were also found to have a significant effect on economic growth in Ghana.

We examined the nonlinear nexus of EC and ETL, which extant studies have ignored in discussing the link between EC and economic growth. Again, we showed that ETL reduces EC causing a reduction in economic growth.

This paper aims to examine the effects of oil price uncertainty on corporate investment of Islamic stocks during the COVID-19 pandemic.

The study uses a panel data set that covers 398 listed Islamic stocks from seven major Asia Pacific countries over the period of five years from 2017 to 2021, yielding 1,990 observations. Specifically, this paper investigates the said association by combining the real options theory regarding investment and the panel data-based econometric method that captures the dynamic relationship, the generalized method of moments estimators.

The findings show that the relationship between the oil price volatility and corporate investment of Islamic stocks is significant and nonlinear in nature, suggesting the presence of both the growth options and the waiting options. Overall, the results reveal that corporate investment of Islamic stocks is hindered during the unprecedented corona crash, when oil price increases at exponential rates.

The findings suggest that considering the information caused by unprecedented events like the COVID-19 pandemic is crucial for investment decisions of Islamic stocks. Therefore, policymakers and regulators should incorporate the impact of oil price uncertainties caused by unprecedented events like the COVID-19 pandemic on firm’s investment expansion and diversification strategies.

To the best of the authors’ knowledge, this paper is the first to examine the relationship between the investment of Islamic stocks and the oil price uncertainty under compound options theory in top Asian oil-importing countries.

This paper aims to investigate the relationship between oil price shocks and world food prices between 1974 and 2018.

The authors use the SVAR model to disentangle the oil price into supply, aggregate demand and oil-specific demand shocks and apply the detrended cross-correlations analysis to measure the association between oil price shocks and food returns/volatility and analyze contagion effects between oil and food markets.

The results show that the correlations between oil and food prices depend on whether oil prices changes are driven by supply or demand shocks. Particularly, food returns (volatility) are positively (negatively) more dependent on the oil price changes driven by aggregate demand (oil specific demand) shocks. Further analysis dealing with contagion analysis between oil and food markets shows a contagion effect during the food crisis of 2006–2008. Oil-specific demand shocks are the main source of this phenomenon.

This study differentiates itself from the previous literature by simultaneously disentangling oil price into supply, aggregate demand and oil-specific demand-driven shocks and evaluating the cross-correlations between each shock type and food returns/volatility. Specifically, this study has the originality of detecting the main source of contagion effects between oil and food markets over the food crisis of 2006–2008.

The results of this study are important for policymakers and investors. They should account for the oil price fluctuations differently depending on whether the oil price shocks are driven by the demand or supply side. Moreover, they should anticipate an increase (decrease) in food prices due to a positive (negative) oil shock. In addition, special attention should be accorded to the world oil demand. Finally, when a food crisis occurs, markets operators should focus more on the specific oil-demand shocks, as it is the most contributor to possible contagion effects between oil and food markets.

This study differentiates itself from the previous literature by simultaneously disentangling oil price into supply, aggregate demand and oil-specific demand-driven shocks and evaluating the cross-correlations between each shock type and food returns/volatility. Specifically, this study has the originality of detecting the main source of contagion effects between oil and food markets over the food crisis of 2006–2008.

This research investigates how subsidy programs in Vietnam's residential electricity market affect consumers' well-being.

Two perspectives are employed: cash transfer and quantity-based subsidy. The effectiveness of cash transfer is measured in three ways: benefit incidence, beneficiary incidence and materiality. The quantity-based subsidy is established under the increasing block rate pricing, with the first two block rates being lower than the marginal cost. To improve the quantity-based subsidy, the research examines the consumer surplus under four proposals.

The results show that both types of subsidies are ineffective in supporting the poor.

In order to achieve a more equal distribution among households, the subsidy program should remove all subsidized blocks and reflect the full marginal cost. Changes should be made to the price structure regarding both marginal price and intervals.

To mitigate the impact of the quantity-based subsidy, the government should improve the cash transfer by reducing extortion and improving targeting efficiency, especially for poor households living in rented houses.

This paper is the first to discuss the welfare effect of the electricity subsidy in Vietnam. First, it comprehensively evaluates the cash transfer subsidy in Vietnam. Second, it suggests a modification in the residential electricity tariff.

This study aims to examine the relationship between TQM practices and teachers' job satisfaction in Qatar, visualizing this relationship through a path causal model.

A cross-sectional survey from different schools in Qatar was conducted, using a questionnaire administered to 359 teachers. Factor analysis was used to establish the construct validity of the questionnaire, using two statistical tests: Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy, and Bartlett's test of sphericity.

The TQM practices measured were information, professional development, teachers' involvement in decision-making, teamwork and salary. Regression analyses showed that only four of the five constructs were significant in predicting teachers' job satisfaction. The path causal model's results revealed that each explanatory variable's direct effect was strengthened via the effect of the other independent variables.

Teachers who are highly satisfied with their jobs are willing to give their best. This study proposes a conceptual causal model for TQM adoption in the Qatar educational system. The proposed causal model will help policymakers and decision-makers in Qatari schools to draw strategies based on the antecedents and consequences of teachers' involvement in decision-making.

Empirically, this article has employed the concepts of TQM and job satisfaction to construct a causal model, demonstrating the effect of TQM practices on teachers' job satisfaction in schools in Qatar, thus bridging the gap between the two fields. To the best of the researcher's knowledge, no prior studies have examined this relationship within Qatari schools.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

The use of three-dimensional virtual worlds (3DVWs) is increasingly becoming a common practice in language education to provide digital learning environments for second-language (L2) communicative classes. This study aimed to identify the key factors underlying communication in 3DVWs that can improve the communication skills of L2 learners.

To achieve this, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to validate the identified factors affecting communication in 3DVWs. A self-reported questionnaire with 47 items on a five-point Likert scale was administered to 513 pre-service teachers, teachers and lecturers in the field of language education.

The results of the EFA revealed four factors that contribute to communication in 3DVWs, namely learner motivation, interaction pattern, language development and learner autonomy. CFA results provided support for the updated model, with statistically significant Chi-square results (χ² (df = 83) = 181.049, p < 0.001) indicating a good fit between the model and the data.

The findings suggest that the four EFA-derived parameters are valid and can assist instructional designers and L2 instructors in creating 3DVWs that enhance L2 learners' communication abilities. This study provides valuable insights for educators, instructional designers and researchers in the field of language education and technology-enhanced learning.