This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

This study aims to examine the pathways through which the user experience (UX) of ChatGPT, a representative of generative artificial intelligence, affects user loyalty. Additionally, it seeks to verify whether ChatGPT’s UX varies according to a user’s need for cognition (NFC). This research proposed and examined how ChatGPT’ UX affect user engagement and loyalty and used mediation analysis using PROCESS Macro Model 6 to test the impact of UX on web-based ChatGPT loyalty. Data were collected by an online marketing research company. 200 respondents were selected from a panel of individuals who had used ChatGPT within the previous month. Prior to the survey, the study objective was explained to the respondents, who were instructed to answer questions based on their experiences with ChatGPT during the previous month. The usefulness of ChatGPT was found to have a significant impact on interactivity, engagement, and intention to reuse. Second, it was revealed that evaluations of ChatGPT may vary according to users’ cognitive needs. Users with a high NFC, who seek to solve complex problems and pursue new experiences, perceived ChatGPT’s usefulness, interactivity, engagement, and reuse intentions more positively than those with a lower NFC. These results have several academic implications. First, this study validated the role of the UX in ChatGPT. Second, it validated the role of users’ need for cognition levels in their experience with ChatGPT.

Nowadays, customer service in telecommunications companies is often characterized by long waiting times and impersonal responses, leading to customer dissatisfaction, increased complaints, and higher operational costs. This study aims to optimize the customer service process through the implementation of a Generative AI Voicebot, developed using the SCRUMBAN methodology, which comprises seven phases: Objectives, To-Do Tasks, Analysis, Development, Testing, Deployment, and Completion. An experimental design was used with an experimental group and a control group, selecting a representative sample of 30 customer service processes for each evaluated indicator. The results showed a 34.72% reduction in the average time to resolve issues, a 33.12% decrease in service cancellation rates, and a 97% increase in customer satisfaction. The implications of this research suggest that the use of Generative AI In Voicebots can transform support strategies in service companies. In conclusion, the implementation of the Generative AI Voicebot has proven effective in significantly reducing resolution time and markedly increasing customer satisfaction. Future research is recommended to further explore the SCRUMBAN methodology and extend the use of Generative AI Voicebots in various business contexts.

This study begins the conversation on the impact that applicant CSR orientation has on a major phase of workforce development—employer attractiveness. There is also virtually no research that investigates CSRO and workforce development. Meanwhile, this present research effort provides evidence that there is some basic relationship between CSRO and employer attractiveness. The data comes from 280 participants who are interested in joining the hospitality and tourism industries in Pakistan. Structural equation modeling was used to analyze the data. The results showed that all four dimensions are significant predictors of employers‘ attractiveness. More specifically, the ethical aspect of CSR has a stronger impact on employers’ attractiveness, whereas discretionary behavior in CSR has the least impact. The implications for academicians, researchers, and managers in the hospitality industry are given in detail.

Bali is the most famous tourist destination in the world, and this popularity has led to a significant rise in the island’s economy. The rise in income has also driven an increase in demand for infrastructure. Moreover, the Bali regional competitiveness index, in the infrastructure pillar, shows a lower figure compared to the national level. So that the Bali Provincial Government focuses on building an infrastructure strategy. This research uses the Input-Output Table (IOT) model, namely the 2016 Bali Province IOT which will be released in 2021. This analysis was chosen because IOT assumes that one sector can be an input for other sectors, in terms of this this is the construction sector. With investment in strategic and monumental infrastructure marking the New Era of Bali, it will result in additional Gross Regional Domestic Product (GRDP) of IDR 18.7 trillion, or in other words Bali’s GRDP will increase by 9.71% from the condition of no investment. This shows that infrastructure development is able to boost Bali’s economy. Further research is needed to be able to qualitatively analyze development infrastructure strategies in Bali. Remembering that a qualitative approach is also important to be able to analyze in depth.

Electricity generation around the world is mainly produced by using non-renewable energy sources especially in the commercial buildings. However, Rooftop solar Photovoltaic (PV) system produced a significant impact on environmental and economical benefits in comparison to the conventional energy sources, thus contributing to sustainable development. Such PV’s system encourages the production of electricity without greenhouse gas emissions that leads to a clean alternative to fossil fuels and economic prosperity even in less developed areas. However, efficiency of rooftop solar PV systems depends on many factors, the dominant being geographical (latitude, longitude, and solar intensity), environmental (temperature, wind, humidity, pollution, dust, rain, etc.) and the type of PV (from raw material extraction and procurement, to manufacturing, disposal, and/or recycling) used. During the feasibility analysis of the environment, geographical conditions are keep in well consideration, but the pollution level of the city is always overlooked, which significantly influences the performance of the PV installations.     

Therefore, this research work focused on the performance of rooftop solar PV installed in one of the most polluted city in India. Here, the loss in power generation of rooftop solar PV has been studied for the effect of deposited dust particles, wind velocity before and after the cleaning of the panels. The actual data has been utilized for the calculation of the energy efficiency and power output of the PV systems. According to the results, it has been concluded that dust deposition, wind speed and pollution level in city significantly reduces the efficiency of solar photovoltaic panel. Hence, an overview of social and environmental impacts of PV technologies is presented in this paper along with potential benefits and pitfalls.