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Student achievement and retention are two important components that indicate the quality of a university. This is in line with one of the standards of university accreditations regarding the quality of students and graduates, which are set by BAN-PT, an institution that guarantees the quality of National Education Service delivery at every university in Indonesia. The purpose of this paper is analyzing the internal and external factors that contribute to academic achievement and student retention.

This paper is a causal explanatory-based study, using multiple regression analysis among five independent variables and two dependent variables separately. Several sequential tests are conducted to maintain the proper research results, such as reliability, normality, multi-collinearity and heteroscedasticity.

This paper provides empirical facts that student motivation has a significant positive impact on the level of student academic achievement, and the quality of lecturers has a significant positive impact both on student academic achievement and retention rates.

This study is conducted within the context of a university. The generalization in the study is low. Researchers are encouraged to explore further.

This paper is expected to provide constructive feedback to university management in setting policies that are oriented toward strategic actions to optimize academic achievement and maintain their students.

This paper provides insights of good university governance concerning in higher education management.

Traditionally, Task–Technology Fit (TTF) theory has been applied to examine the usefulness of technology in the work environment. Can the same approach (based on experience rather than tasks) be applied to non-work, cultural heritage environments? This is the question the authors ask in this study. This study proposes a new variation of TTF based on the experience economy model, namely Experience–Technology Fit (ETF), for the non-work environment, in particular, in the context of cultural heritage, where visitor experience is enhanced by extended reality technology, which combines immersive technologies and artificial intelligence.

Employing a quantitative survey method, the empirical analysis seeks to determine the influence of Mixed Reality (MR) characteristics (interactivity, vividness), Voice User Interface (VUI) characteristics (speech recognition, speech synthesis) and experience economy factors (education, entertainment, esthetic, escape) on satisfaction, revisit intention and actual purchase to propose a new ETF model.

VUI, MR, and experience factors were significantly associated with ETF; when combined with MR-based experience, ETF was significantly associated with satisfaction. This study’s findings further demonstrate the relationship between users' satisfaction when engaging with MR-based experience and revisit intention, while purchase intention was significantly associated with the actual purchase.

The novel contribution of this study is the proposal of the EFT model, a new variation of TTF based on the experience economy model. Overall, this study expands the applications of TTF to an experience-oriented business, thereby broadening the authors’ understanding of technological success with a specific focus on the technology fit of Extended Reality (XR) in the context of cultural heritage.

This paper aims to explore students’ intention to use and actual use of the artificial intelligence (AI)-based chatbot such as ChatGPT or Google Bird in the field of higher education in an emerging economic context like Bangladesh.

The present study uses convenience sampling techniques to collect data from the respondents. It applies partial least squares structural equation modeling (PLS-SEM) for analyzing a total of 413 responses to examine the study’s measurement and structural model.

The results explore that perceived ease of use (PEOU) negatively affects intention to adopt AI-powered chatbots (IA), whereas university students’ perceived usefulness (PU) influences their IA positively but insignificantly. Furthermore, time-saving feature (TSF), academic self-efficacy (ASE) and electronic word-of-mouth (EWOM) have a positive and direct impact on their IA. The finding also reveals that students' IA positively and significantly affects their actual use of AI-based chatbot (AU). Precisely, out of the five constructs, the TSF has the strongest impact on students’ intentions to use chatbots.

Students who are not aware of the chatbot usage benefits might ignore these AI-powered language models. On the other hand, developers of chatbots may not be conscious of the crucial drawbacks of their product as per the perceptions of their multiple users. However, the findings transmit a clear message about advantages to users and drawbacks to developers. Therefore, the results will enhance the chatbots’ functionality and usage.

The findings of the study alert the teachers, students and policymakers of higher educational institutions to understand the positive outcomes and to accept AI-powered chatbots such as OpenAI’s ChatGPT. Outcomes also notify the AI-product developers to boost the chatbot’s quality in terms of timeliness, user-friendliness, accuracy and trustworthiness.

Zakat has succeeded in becoming one of the safety nets for welfare during the crisis. As a result, continuous improvement is a necessity, especially through strengthening technology adaptation. This study aims to explore the factors determining Muslim behavior on their intention to pay zakat by taking into consideration the adoption of digital technology using the modified Unified Theory of Acceptance and Use of Technology (UTAUT).

The data collected were 265 respondents who live in urban and suburban areas. They were processed using the partial least square structural equation modeling (PLS-SEM) design. Furthermore, the multigroup analysis (MGA) was conducted to capture the difference results between urban and suburban.

The findings show that performance expectancy, social influence, facilitating conditions, perceived security and privacy and zakat literacy significantly increase the intention of Muzakki to adopt financial technology. Perceived security and privacy has succeeded in being an important predictor of digital payment adoption for Muzakki. This paper provides a specific description of the adoption of Muzakki living in urban and suburban areas by using MGA. The research findings illustrate that there is a different urgency between the related variables. Suburban communities have more significant results regarding the research model used.

This research provides new component variables that can drive individuals’ intentions to use digital services to pay zakat online by using the redesigned UTAUT model. Further research can explore more variables related to zakat digitalization, such as social media interaction, by conducting in-depth interviews with stakeholders to improve zakat performance in this digital era.

The result of this research recommends that zakat institutions enhance their zakat literacy and education among the Muslim population to improve zakat performance. The government should pay attention to the digital ecosystem to attract the community to use a digital platform.

This research modified the UTAUT model by integrating several other important constructs to produce more comprehensive findings in investigating the factors that can influence an individual's intention to pay zakat through an online digital platform. This study also examined the indirect effect to obtain significant results by positioning perceived security and privacy as an intervening variable. The implementation of the MGA was conducted to divide research respondents into two categories (urban and suburban) and compare the test results.