Facilitative Conditions Research Articles

Using UTAUT model to assess the factors influencing the use of ICT in Ghanaian pre-tertiary mathematics education

As the demand for acquiring Information communication and technology has increased rapidly due to the exponential growth of technological advancement in all human endeavor, researchers are also developing theories and/or models that could be used to describe and prognosticate humans’ espousal and use of these technologies as they are being released in the markets. The present study adapted one of the powerful models for information and communication technology (ICT) integration (thus, unified theory of acceptance and technology use) to assess pre-tertiary mathematics facilitators’ intentions and actual use of ICT for mathematics instructions in Ghana. This study adopts a quantitative research approach with a questionnaire as a survey instrument for collecting 185 valid data from both junior and senior high schools’ mathematics facilitators. Descriptive statistics and an enter multiple regression were deployed to validate the proposed research questions. Using SPPS v.23 as a statistical software for analyzing the data, the result reveals that, performance expectancy, and effort expectancy had a positive and significant effect on mathematics facilitators’ intentions toward ICT adoption. Moreover, social influence was significant but had a negative impact on facilitators intentions. The impact of mathematics facilitators’ intention to use ICT and the facilitating conditions (FCs) within the school environment was also a positive and significant predictor of facilitators’ ICT use behavior. It was concluded from the findings that FCs were the better predictor for mathematics teachers’ ICT use behavior than intention. Hence, the researchers recommended that more government expenditure must be allocated to infrastructures that would improve the use of ICT as well as frequent ICT training must be undertaken to enrich teachers’ knowledge in the affordance of using ICT in mathematics classrooms.

Determinants of mobile application adoption among micro-entrepreneurs

Background: Since the onset of the global pandemic, unemployment has increased to new levels. As a consequence, the need to stimulate economic growth through the development of the micro-enterprise sector has become a central vehicle to decrease unemployment and stimulate economic growth. The problem, however, is that despite the potential benefits of digitisation, the micro-enterprise sector has been unable to effectively integrate information and communication technologies (ICTs) into the fabric of their operations.Objectives: The objective of this study was to investigate the factors that influence the adoption and use of mobile applications for micro-enterprise operations in South Africa.Method: A quantitative methodology using a survey design was used to collect data from a sample of entrepreneurs, with 221 responses.Results: Performance expectancy (PE) and effort expectancy (EE) positively influence the micro-entrepreneurs’ behavioural intention (BI) to adopt and use mobile applications, while social influence (SI) has no impact on the same. Facilitating conditions (FC) and BI are the strongest determinants of mobile application adoption and use for micro-enterprise operations.Conclusion: All the constructs of the unified theory of acceptance and use of technology (UTAUT) model showed a satisfactory level of reliability and discriminant validity, which was confirmed by testing the measurement model against two competing models. The UTAUT model is a good predictor of the intention to adopt and use mobile applications for micro-enterprise operations.Contribution: The findings provide parameters to develop a focussed strategy to catalyse the adoption and subsequent use of mobile applications among micro-entrepreneurs. It further informs initiatives to close the gap of a known reluctance in using technology among micro-enterprises.

Factors influencing the acceptance and use of a South African online bank

Background: Online banking gained prominence during the coronavirus disease 2019 (COVID-19) pandemic as an alternative to traditional banking. However, limited studies have explored online banking acceptance in South Africa.Objectives: This study investigates the factors that influence online banking acceptance among South Africans in a context where use is limited.Method: Thematic content analysis examined 113 Google user reviews from South Africans using an exclusive online bank. Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) was used as a theoretical framework, analysing factors such as performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), hedonic motivation (HM), price value (PV), trust, perceived risk (PR), habit, and social influence.Results: Seven UTAUT3 constructs influenced online banking acceptance and use in South Africa during the pandemic: PE, EE, FC, HM, PV, trust, and PR. The influence of habit and social influence was not evident.Conclusion: Understanding factors influencing online banking acceptance in South Africa is crucial for policymakers and institutions. Addressing information communication technology challenges can enhance accessibility and benefits, promoting financial inclusion, and empowerment.Contribution: This research fills the gap by examining online banking acceptance in South Africa. Findings inform interventions and policies to improve access and adoption. Practical implications extend to institutions and policymakers, fostering financial inclusion.

Acceptance of Highly Automated Vehicles: The Role of Facilitating Condition, Technology Anxiety, Social Influence and Trust

Highly automated vehicles (level 4) will be launched soon. This study explored factors affecting the acceptance of level 4 automated vehicles (AV) amongst the public. The technology acceptance model (TAM), technology anxiety (TA), social influence (SI), facilitating condition (FC) and trust (TR) were integrated to develop a level 4 AV acceptance model. A web-based questionnaire was used for data collection from 693 Chinese participants. Structural equation modelling was utilized to analyze the collected data. The results showed that TAM is applicable to explain level 4 AV acceptance amongst the public. The effects of FC on perceived ease of use and perceived usefulness (PU) are positive. TA negatively influences PU. SI positively influences PU and behavioural intention to use AVs. TR positively influences attitude towards using AVs and is positively determined by PU. Based on the results, some practical implications for increasing the use of level 4 AVs amongst the public were provided.

Factors Associated with Intention to Use Telerehabilitation for Children with Special Needs: A Cross-Sectional Study.

Background: Children with special health care needs (CSHCN) require long-term and ongoing rehabilitation interventions supporting their development. Telerehabilitation can provide continuous rehabilitation services for CSHCN. However, few studies have explored the intention of CSHCN and their caregivers to use telerehabilitation and its impact on them. Objective: The objective of this study was to identify factors that influence the intention to use telerehabilitation among CSHCN and their caregivers. Methods: This study was a cross-sectional study. Based on the unified theory of acceptance and use of technology, extended with additional predictors (trust and perceived risk [PR]), this study developed a research model and proposed 10 hypotheses. A structured questionnaire was distributed to 176 caregivers. Data were analyzed and research hypotheses were tested using partial least squares structural equation modeling to better understand the factors influencing the use of telerehabilitation. Results: A total of 164 valid questionnaires were collected. CSHCN and their caregivers were overall satisfied with this telerehabilitation medical service. The results of the structural model analysis indicated that social influence (SI), facilitating conditions (FC), and trust had significant effects on behavioral intention (BI) to use telerehabilitation, while the paths between performance expectancy (PE), effort expectancy (EE), and PR and BI were not significant. PE, EE, and SI had a significant effect on trust. Moreover, EE and SI had indirect effects on BI, with trust as the mediator. Conclusions: The results indicated that SI, FC, and trust are significant factors influencing CSHCN and their caregivers' use of telerehabilitation. Trust is also an important mediator for the intention and highly influenced by PE, EE, and SI.

Using artificial intelligence for hiring talents in a moderated mechanism

AbstractGlobally, artificial intelligence (AI) occupies a burgeoning space among recruiters as it replaces many of the recruitment and selection tasks while hiring the talents. Despite the existence and acceptance of AI being unprecedented among savvy recruiters, the study of it in developing countries’ contexts is still at a fancy stage. Particularly, the extant literature documented that very little is known about the intention and actual use (AU) of AI to hire talents with the intervening effects of voluntariness of usage (VU), tenure, and education of the recruiters elsewhere. Hence, using the doctrine of the extended unified theory of acceptance and use of technology (UTAUT), the present study aims to unpack the intention and AU of AI among hiring professionals in the context of Bangladesh, a developing country in the South Asian region. A multi-item questionnaire survey was employed to collect the data of recruiters from talent acquisition departments in both manufacturing and service organizations with a convenience sampling technique. We used partial least square-based structural equation modeling (PLS-SEM) version 4.0.8.9 to analyze the data. Results showed that performance expectancy (PE), facilitating conditions (FC), and hedonic motivation (HM) have a significant influence on the intention to use (IU) AI (p < 0.05), and IU also predicts AU of AI significantly (p < 0.05). The moderating influence of VU has an insignificant effect on the positive influence of IU on AU. Moreover, the multi-group analysis showed that there is no significant difference between young adults and old adults and highly educated and lowly educated on the association between IU and AU. The findings in this study showed important notations that contributed to advancing the knowledge and filling the gap in the extant literature. Additionally, it also provides fresh insights for developing policy interventions to hire professionals for thriving AI adoption in the context of developing countries effectively.

How Does Age Moderate the Determinants of Crowdfunding Adoption by SMEs’s: Evidences from Morocco?

In recent years, crowdfunding has emerged as a new fundraising technique for start-up ventures; however, Moroccan small and medium-sized businesses are still wary of this novel source of funding. This is confirmed by the low adoption rate of this financial innovation as well as the limited number of crowdfunding platforms in Morocco. This study aims to identify the impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and perceived risk (PR) on SMEs’s intention to use crowdfunding platforms using a research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Empirical data were collected from 241 respondents through a survey, and structural equation modelling was used to analyze the findings. The results show that performance expectancy (PE), effort expectancy (EE), and facilitating conditions (FE) affect SMEs’s intentions to use crowdfunding. However, social influences (SI) and perceived risk (PR) were not found to be significant determinants. Regarding the moderating effect of age, our study has highlighted that this variable has moderated the relationship between the three independents variables: performance expectancy, facilitating conditions and perceived risk. Finally, this paper offers recommendations for how to increase SMEs’s intention to use crowdfunding platforms.

Are Older Adults Special in Adopting Public eHealth Service Initiatives? The Modified Model of UTAUT

With rapid aging and the spread of chronic diseases, public eHealth services are helpful tools to monitor their physiological situations and develop healthy behaviors. However, the studies on older adults adopting public eHealth services have been relatively limited. We propose a modified United Theory of Acceptance and Use of Technology (UTAUT) model, considering the unique adoption patterns of older people. Our study shows that older adults adopting patterns are influenced first by social influence (SI) and facilitating conditions (FC), then influenced by performance expectancy (PE) and effort expectancy (EE). This model includes two moderating effects of performance expectancy (PE) and effort expectancy (EE) between two external constructs of social influence (SI), facilitating conditions (FC), and older adults’ behavioral intention (BI) to adopt public eHealth services. A dataset of 510 questionnaires was collected on the use of a self-monitoring telecare device (Babybot) in Hsinchu City, Taiwan. The results demonstrate that SI and FC positively influence older adults’ adoption of public eHealth services. Furthermore, PE positively moderates the relationship between FC and BI, while EE positively moderates the relationships between FC and BI, and between SI and BI. The findings reveal that PE and EE moderate SI and FC in affecting older adults’ adoption of public eHealth services. This modified UTAUT model provides insights into the unique factors that drive older adults’ adoption behavior. This study offers valuable policy and managerial implications for promoting older adults’ adoption of public eHealth services.

Adoption of Mobile Phone Based Mutual Fund Investment Applications Among Retail Investors: Empirical Evidence from UTAUT Model

Objective- This study aims to analyse acceptance of mobile phone based mutual fund applications. The objective, in other way examines how mutual fund mobile apps affect retail investors' investment decisions.
 Methodology- Under the Unified Theory of Acceptance and Use of Technology (UTAUT), the paper observed retail investor’s adoption behaviour prediction. The data was collected during April–September, 2023 using structured questionnaire. Based on total 258 viable replies, the study used multiple regression and regression coefficient analysis.
 Results– The study found that effort expectancy (EE), performance expectancy (PE), social influence (SI), facilitating condition (FC), and habit (H) influenced retail investors' mutual fund mobile app use. Hedonic motivation did not affect retail investors' mutual fund mobile application behavioural intention.

The precursors of AI adoption in business: Towards an efficient decision-making and functional performance

Artificial intelligence (AI) is a highly effective solution for enhancing decision-making efficiency and optimising the functional performance of organisations. However, there have been limited attempts to assess the consequences of implementing AI systems on the quality and efficiency of decision-making. This study proposes and empirically examines an extended model covering all aspects that would shape the successful adoption of AI by decision-makers while investigating how the successful adoption of AI enhances the efficiency of the decision-making process. This study also intends to test the validity of the integrated AI acceptance-avoidance model (IAAAM) proposed by Cao et al. (2021) using the Middle East context (i.e. Saudi Arabia). The extended model of the current study was based on the IAAAM and IS professional distinctiveness (ISPD). Two quantitative studies were conducted to achieve the research objectives. The first study was conducted to validate the IAAAM using a purposive sample of employees (non-adopters of AI applications). The second study tested the proposed model using a purposive sample of employees (actual adopters). The structural equation modelling (SEM) results of the first study (non-adopters) supported the validity of the IAAAM in Saudi Arabia. Factors (performance expectancy (PE), facilitating conditions (FC), personal well-being concern (PWC), perceived threat (PT), and attitudes (ATT)) had a significant impact on either ATT or the intention to use AI. The SEM results of actual adopters supported the impact of PE, EE, FC, PWC, and ATT on either ATT or the adoption of AI (AoAI). As an external factor, the ISPD was the most significant predictor of AoAI. The AoAI was confirmed to strongly predict decision-making efficiency, which, in turn, contributes to functional performance. This study enriches the current understanding of the main factors that contribute to the successful implementation of AI systems, offering an in-depth understanding of both AI adopters and non-adopters. It identifies factors important to non-users to enhance future adoption, whereas current AI users focus on improving decision-making quality with the AI assistance.

Facilitating conditions and institutional repository sustainability by librarians in public university libraries in Nigeria

PurposeThis study aims to investigate the facilitating conditions (FCs) and how these FC affect institutional repository (IR) sustainability practices in public universities in Nigeria.Design/methodology/approachA survey research design was adopted in this study. The study population comprised 542 librarians from public universities that have IRs across Nigeria. A sample size of 230 librarians was determined using Taro Yamane’s formula. A multi-stage sampling technique was used to select the respondents in three stages, which were purposive, stratified and purposive sampling. A structured, validated questionnaire was used for data collection. Data were analyzed using descriptive and inferential (simple and multiple regression) statistics at a 5% level of significance.FindingsThe result revealed that the availability of FCs (ßeta = 0.459, t(211) = 7.719, p = 0.000) has a positive and significant influence on IR sustainability in public university libraries in Nigeria. The F-test (1, 223) value of 59.582 shows that there is sufficient evidence to substantiate the model’s usefulness in explaining IR sustainability. The R2 (0.211) indicates that 21.1% of the variation in IR sustainability is explained by the availability of FCs in public university libraries in Nigeria. The finding suggests that the availability of FCs is a vital predictor of IR sustainability in public university libraries in Nigeria. The result also depicts that out of the eight parameters that measure the availability of FCs, it was current awareness of IR that had a positive and significant influence on IR sustainability.Originality/valueThis study concluded that ICT skills and FCs are contributory factors to IR sustainability practices by librarians in public university libraries in Nigeria. It was recommended that university administrators formulate policies that promote the sustainability of IR and provide adequate funds to support IR sustainability. Furthermore, the library management in public university libraries in Nigeria should drive content recruitment and create awareness of the IRs among students and faculty to ensure continued use.

AI-Powered Mental Health Virtual Assistants' Acceptance: An Empirical Study on Influencing Factors Among Generations X, Y, and Z.

This study aims to analyze various influencing factors among generations X (Gen X), Y (Gen Y), and Z (Gen Z) of artificial intelligence (AI)-powered mental health virtual assistants. A cross-sectional survey design was adopted in this study. The study sample consisted of outpatients diagnosed with various mental health illnesses, such as anxiety, depression, schizophrenia, and behavioral disorders. A survey questionnaire was designed based on the factors (performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioural intention) identified from the unified theory of acceptance and use of the technologymodel. Ethical approval was received from the Ethics Committee at Imam Abdulrahman Bin Faisal University, Saudi Arabia. A total of 506 patients participated in the study, with over 80% having moderate to high experience in using mental health AI assistants. The ANOVA results for performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), and behavioral intentions (BI) indicate that there are statistically significant differences (p < 0.05) between the Gen X, Gen Y, and Gen Z participants. The findings underscore the significance of considering generational differences in attitudes and perceptions, with Gen Y and Gen Z demonstrating more positive attitudes and stronger intentions to use AI mental health virtual assistants, while Gen X appears to be more cautious.

Students' Behavioural Intention towards Adoption of Online Education: A Study of the Extended UTAUT Model

Online education (o-education) is gaining significant attention from education providers, students, and policy makers. This research explored students’ behaviours and intentions towards online education. The present research utilised the Unified Theory of Acceptance and Use of Technology (UTAUT) as a model to investigate these intentions and behaviours. The study incorporated UTAUT predictors along with three additional independent variables. This study adopted a cross-sectional design and used a closed-end questionnaire to collect data from 403 respondents. The data were analysed with SPSS and AMOS by utilising structural equation modeling (SEM) techniques. The results of the SEM analysis indicate that perceived value (PV) and convenience (Cnv) have positive influences on behavioural intention (BI), while perceived risk has a negative impact on behavioural intention (BI). Additionally, facilitating conditions (FC) and behavioural intention (BI) are found to positively influence use behavior (UB). The research findings suggest that demographics, including age, education and gender, influence behavioural intention (BI). The findings of the study have theoretical and practical implications, which are elaborated in the last section of this article.

Exploring the Adoption of Blended Learning in Physical Education: A Study in Southwest China's Higher Education Institutions

This study delves into the adoption of Blended Learning in Physical Education (BLPE) within higher education institutions in Southwest China. Employing structural equation modeling (SEM) on data from 654 respondents, which are higher education students major in physical education in southwest China. The research comprehensively examines both direct and indirect effects among the Information Quality (IQB), System Quality (SQB), Satisfaction (SAB), Perceived Ease of Use (PEB), Perceived Usefulness (PUB), Attitude Towards BLPE (ATB), Hedonic Motivation (HM), Price Value (PV), Habit (HT), Intention to Use BLPE (IUB), Facilitating Conditions (FC), Performance Expectance (PE), Effort Expectance (EE), and Social Influence (SI). Significant direct relationships were identified, including IQB's and SQB's positive effects on SAB (? = 0.358 and ? = 0.505, respectively), and SAB’s influence on PEB (? = 0.597) and PUB (? = 0.384). Additionally, mediation analysis revealed key indirect effects, such as SAB mediating the relationship between IQB and PEB (effect size = 0.206), and between SQB and PUB (effect size = 0.185). Notably, HM and PV did not significantly impact IUB, suggesting unique contextual differences in BLPE adoption in Southwest China. Other variables like HT, FC, PE, EE, and SI also showed significant impacts on IUB, reflecting the multifaceted nature of BLPE adoption. The study concludes that quality of content and system, along with user satisfaction, play pivotal roles in determining the success of BLPE. Contrasting with some global trends, cultural and contextual factors significantly influence BLPE adoption in Southwest China. These findings provide essential insights for educators and policymakers, emphasizing the need for contextually tailored BLPE strategies and highlighting the critical interplay of various factors in the successful implementation of blended learning in physical education.

Investigating the unexpected determinants of cryptocurrency adoption in the UAE

PurposeFinancial inclusion provides access to financial infrastructure, facilitating money transfers. Therefore, blockchain and cryptocurrencies might boost worldwide financial acceptance. However, the UAE has one of the lowest cryptocurrency adoption rates. This study explores the UAE customer adoption and use of cryptocurrencies.Design/methodology/approachUsing a scale, the authors created a structural model and obtained 270 responses from a snowball-distributed online questionnaire, assessed by five cryptocurrency specialists.FindingsPerformance expectations (PE), price value (PV), Hedonic motivation (HM) and consumer innovativeness (CI) were the most significant predictors of behavioural intention (BI). Surprisingly, BI is not a reliable indication of actual consumption. Facilitating conditions (FC) are the most accurate predictor of cryptocurrency usage (CU), indicating that adoption might be increased by providing the necessary structures and processes to lead users.Research limitations/implicationsThis research adds to the body of knowledge by examining the adoption and implementation of cryptocurrencies in the UAE and by developing and evaluating new constructs based on current notions. The study also contributes to the current understanding of cryptocurrencies and blockchain adoption.Practical implicationsThe conclusions of the research advise marketers on how to boost the commercialisation of cryptocurrencies in the UAE market and may pave the way for other studies to assist impending developments in the UAE cryptocurrency industry.Originality/valueThis research offers novel insights into significant predictors of cryptocurrency product uptake in the financial and banking business.

Exploring Health Managers’ Views of Factors Influencing Their Acceptance of Electronic Health Services in Aseer Province, Kingdom of Saudi Arabia: A Qualitative Study

Introduction: The Kingdom of Saudi Arabia (KSA) is a country with one of the largest land masses and difficult geographical terrain in the Middle East. Health services across the country are accessible through three categories of providers. The Ministry of Health (MOH) which is the dominant health provider responsible for 60% of all health services and facilities. Private health sector and other government run health authorities are the providers for the remaining 40%. The accessibility to advanced health services, especially for people in rural areas, has been considered one of the main health challenges. Utilising Information and Communication Technology (ICT) including Electronic Health (eHealth) as an innovative approach to healthcare delivery was suggested by recent studies. This study aimed to explore the views of health managers in Aseer Province towards factors that influence their acceptance of eHealth services in the KSA. Methods: In-depth face-to-face and telephone interviews with health managers from Aseer province, KSA were conducted. The Unified Theory of Acceptance and Use of Technology (UTAUT) was employed as a theoretical framework in this qualitative study. The UTAUT model consists of four domains: performance expectancy (PE); effort expectancy (EE); social influence (SI); and facilitating conditions (FCs). All factors identified in the interviews were mapped against the UTAUT domains. Microsoft Excel and NVivo were used for the data analysis. Ethical approval had been gained. Results: Twenty-one health managers in Aseer province, KSA were interviewed. The most influential factors that influence health managers acceptance of eHealth services were clustered under four UTAUT domains. Three domains out of four showed significance: PE, SI, and FCs. Conclusion: This study confirmed the influence of some factors on health managers’ acceptance of eHealth services in Aseer province, KSA. Original findings have been generated by exploring eHealth practice in the province which is part of KSA that has not previously been explored in the published eHealth literature. Identifying key challenges in accepting eHealth services may help in clarifying the better utilization of technology and making successful and positive transformational and sustainable change to the delivery of healthcare.

The unified theory of acceptance and use of DingTalk for educational purposes in China: an extended structural equation model

With educational technology growing by leaps and bounds, synchronous online learning platforms have become a prevalent practice worldwide. Although numerous studies unraveled the behavioral intention of educational technologies with statistical methodology, there is a paucity of that of DingTalk, one of China’s most popular online platforms for synchronous learning. This study aimed to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating new constructs and examining the factors that affect users’ behavioral intention and use behavior of DingTalk. The study collected 856 valid responses from China, which were analyzed using SPSS 23.0 and Amos 24.0. The findings indicated that (1) effort expectancy (EE), performance expectancy (PE), facilitating conditions (FC), self-efficacy (SE), and received feedback (RF) could significantly impact users’ attitudes toward behavior (ATB); (2) social influence (SI), FC, RF, and ATB could be significant predictors of user behavioral intention (BI); (3) FC, RF, and BI were found to have a significant effect on use behavior (UB); (4) the extended UTAUT model could explain 60.9% of the variance of users’ behavioral intention of DingTalk in China; (5) the study identified ATB and BI as joint mediators between certain variables in the model. The study presented a robust theoretical underpinning to explain the acceptance and use of educational technologies in China and provided insights into the future enhancement of E-learning platforms.

Determining the Factors Affecting Solar Energy Utilization in Saudi Housing: A Case Study in Makkah

This research paper examines the adoption of solar energy in residential buildings throughout Saudi Arabia, with a specific emphasis on Makkah. Despite the immense global demand for energy and growing environmental concerns, the adoption of solar energy in Saudi housing remains relatively low. While previous studies have examined the potential, feasibility, and policy support for solar energy, this research uniquely approaches the issue from the perspective of customers on a national scale. The study aims to identify the factors that influence customers’ intentions to use solar energy in Saudi Arabia, contributing to the development of a sustainable circular supply chain for renewable energy. To achieve this, the research integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). An online questionnaire was distributed, garnering responses from a total of 250 participants. A regression analysis was employed to analyze the data and examine the relationships between the proposed hypotheses. The study’s findings reveal that four critical factors wield significant influence over consumer behavior and their decisions regarding the adoption of solar PV technology. These factors are: Social Influence (SI), Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC).

Assessing Antecedents of Behavioral Intention to Use e-LMS: A Case From a Private Institution in the Northern Region of India

Students' and instructors' adoption of “e-learning management systems (e-LMSs)” is critical to their success in a “virtual learning environment”. Students can use “e-learning” to obtain instructional materials to supplement “traditional classroom” instruction. This study intends to highlight important factors of e-learning adoption in higher education institutes. The aim is to determine the factors forming positive intention towards using e-LMS based on “individual characteristics” (“Instructor Quality (IQ)”, “Course Quality (CQ)”, “Learning Value (LV)”, “Social Influence (SI)”, “Facilitating Condition (FC)”, “System Quality (SQ)”, “Perceived Usefulness (PU)”, and “Perceived Ease of Use (PEOU)”). The questionnaire-based survey based on 369 responses from LMS users. The proposed research model was tested using Structural Equation Modelling (SEM). Initially, Post Adoption Behavior was required to be investigated. The original measurement model contained eight independent constructs. A modified measurement model was created after the initial model was enhanced using exploratory factor and principal component analysis. The results of this study will help practitioners and policy makers in the effective development and implementation of e-Learning Management Systems in HEI's especially in developing countries like India. From the theoretical point of view, the result of this study will further enrich the IT adoption literature.

THE APPLICATION OF UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY IN MUSICAL METAVERSE

This research study observes the musical Metaverse and applies the theories of UTAUT (Unified Theory of Acceptance and Use of Technology) and IDT (Innovation Diffusion Theory). It aims to examine the acceptance of the musical Metaverse toward the behavior intention to use (BI), which is influenced by performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), moderated by personal innovativeness (PI). The Google form data was collected from 250 Ciputra University students who familiarized themselves with the musical Metaverse, and the data was later processed using SmartPLS 4. The results showed that PE has a significant effect on BI, EE has no significant effect on BI, and SI has no significant effect on BI. FC has a significant effect on BI; PI has not been able to strengthen other factors to have the intention to use the musical Metaverse. Thus, performance expectancy and facilitating conditions influence the intention to use the musical Metaverse. Meanwhile, personal innovativeness cannot significantly moderate the relationship between PE, EE, SI, and FC