The rise of internet-based pharmacies has transformed the healthcare sector, giving patients access to medications, information, and direct interaction with pharmacists. While online pharmacies have become popular around the world, there are challenges hindering their widespread use in developing countries due to a limited understanding of the factors affecting their acceptance and usage. To bridge this knowledge gap, a study utilized a model combining the unified theory of acceptance and use of technology (UTAUT 2) with the technology acceptance model (TAM) to explore the drivers behind online pharmacy usage in Oman. Through this framework, twelve hypotheses were. A survey involving 378 individuals familiar with online pharmacies was conducted. Structural equation modeling (SEM) was applied to analyze the data and test these hypotheses. The results indicate that factors such as perceived expectancy effort expectancy and facilitating conditions hedonic motivation, habit perceived risk, technology trust, and technology awareness play roles in influencing the adoption of online pharmacies in Oman. The findings suggest that personal innovation plays a moderating role in the connection between perceived risk and behavioral intention, while it has a negative moderating influence on the relationship between technology trust and behavioral intention. Word of mouth was identified as a moderator in enhancing the correlation between behavioral intention and online pharmacy adoption. This research emphasizes the moderating relationship of personal innovation and word of mouth on shaping consumer attitudes towards online pharmacies and their acceptance. In summary, these results add to the existing knowledge on pharmacy adoption and in developed areas such as provide practical insights for online pharmacy providers to improve their offerings and attract a larger customer base.

Since 2007, Peru has implemented results-based budgeting in order to ensure the quality of public spending in State entities and that the population receives goods and services in a timely manner; However, the demands of the current legal and regulatory context require a progressive application to budget processes such as that of the National Penitentiary Institute, which is basically focused on the allocation of resources by the central government, the collections it receives for penitentiary work. and the TUPA; Likewise, it requires strategic programming based on results, refining the procedures for programming, formulation, execution and evaluation of the budget. The objective of this research work is to describe the relationship between results-based budget management and the quality of spending in the Altiplano-Puno Regional Directorate of the National Penitentiary Institute in the period 2019. To achieve the objective, the descriptive explanatory method was used; in addition, the questionnaire and documentary analysis were used as a data collection instrument to determine the relationship between the study variables. Finally, it is concluded that the results-based budget is significantly related to the quality of spending, which means that the entity managed to apply the results-based budgeting methodology efficiently, obtaining an improvement in the quality of spending, consequently focusing on the optimization of the use of financial resources to achieve the strategic objectives of the penitentiary administration in this region. This approach seeks not only to guarantee the correct execution of spending, but also to maximize its positive impact on the management and conditions of penitentiary centers. In this way, a results-based budget approach must be implemented and ensuring the quality of public spending will allow the Office Regional Altiplano Puno of the INPE use its resources more effectively, achieving the objectives of prison security and rehabilitation and improving conditions in penitentiary centers. The adoption of efficient and transparent management practices will contribute significantly to a more responsible and results-oriented public administration.

During and after the Covid-19 outbreak, people’s precautionary measures of not visiting public venues like cinema halls or multiplexes were replaced by watching treasured videos or films in private settings. People are able to watch their favourite video contents on a variety of internet-connected gadgets thanks to advanced technologies. As a result, it appears that the Covid-19 outbreak has had a substantial impact on people’s inclination to continue using video streaming services. This study attempted to establish an integrated framework that describes how people change their health behaviours during pandemic conditions using the health belief model (HBM), as well as the mediating effect of HBM constructs over ECM constructs such as continuous intention to subscribe to OTT video streaming services among subscribers. The study looked at the impact of three perceived constructs, susceptibility, severity, and self-efficacy, on the confirmation/adoption of over-the-top (OTT) video streaming services during the lethal pandemic (Covid-19). The study focused on new OTT video streaming service subscribers, and 473 valid replies were collected. Path analysis and multivariate analytical methods, such as structural equation modelling (SEM), were used to estimate construct linkages in the integrated framework. Perceived severity has been identified as the most influential factor in confirmation/adoption, followed by perceived susceptibility. The results also showed that satisfied users/subscribers are more likely to use OTT video streaming services. The mediators, confirmation/adoption, perceived usefulness, and satisfaction were used to validate the influence of perceived susceptibility on continuance intention. Furthermore, contactless entertainment enhances security for users/subscribers by allowing them to be amused across several internet-based venues while adhering to social distance norms.

Tourism plays a crucial role in driving economic development, and there is a growing demand to integrate sustainability into the sector, particularly in the financial practices of governments. This study introduces the Quintessence Sustainable Tourism Public Finances (QSustainableTPF) model, which combines five established financial models commonly used in the tourism industry. The research aims to identify statistically significant relationships between these models and assess their impact on sustainability and financial performance in tourism. A quantitative methodology was employed, with data collected from financial reports and budget documents of both local and central governments, along with a survey of 2099 citizens and visitors conducted during the 2023–2024 period. Statistical analysis was performed using SPSS and AMOS, incorporating exploratory factor analysis (EFA), reliability testing using Cronbach’s alpha, and confirmatory factor analysis (CFA). The findings underscore the essential role of public finance in supporting tourism sustainability, particularly through transparent budgetary practices, efficient allocation of resources, and targeted investment in local tourism initiatives. The analysis reveals key insights into the benefits of financial transparency, citizen-centred budgeting, and the promotion of innovation in tourism finance. The interconnectedness of the five models highlights the importance of responsible public financial management in fostering tourism growth, enhancing investment, and ensuring long-term financial sustainability in the sector. The study offers practical implications for policymakers, advocating for the adoption of transparent and innovative financial practices to boost tourism development. It also recommends further research to broaden the scope across different regions, integrating additional public finance dimensions to strengthen sustainable tourism growth.

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.