The role of facilitating condition in enhancing user’s continuance intention

Kamarozaman, Zarina; Razak, Fahmi Zaidi Abdul

doi:10.1088/1742-6596/1793/1/012022

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…In the quest to provide a holistic approach towards ensuring the success of the mlearning application in the institution, the developers should also consider the availability of the application in all operating systems (OS) or platforms (e.g., iOS). Although this reflects the factor of facilitating condition, which was discovered as insignificant in this study, earlier studies of technology acceptance by Seethamraju et al (2018) and technology continuance use by Kamarozaman and Razak (2021) demonstrated its importance.…”

Section: Contributionsmentioning

confidence: 51%

“…Previously, Nysveen and Pedersen ( 2016) stated that a consumer who has access to a favourable set of facilitating conditions is more likely to have a greater intention to use technology. Furthermore, a recent study by Kamarozaman and Razak (2021) related to e-campus continuance use intention found that facilitating condition plays an essential contributor. Therefore, the formation of the seventh hypothesis is based on the more facilitation conditions associated with using the gamified mlearning application, the more a user will continue to use them.…”

Section: H3: Perceived Enjoyment (Penj) Has a Positive Effect On Gami...mentioning

confidence: 99%

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Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

et al. 2023

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Aim/Purpose: The main purpose of this study is to identify the factors affecting the continuance use intention of gamified m-learning applications by Higher Education Institution (HEI) learners in Malaysia. Background: Mobile learning (m-learning) has been a popular choice among learners in HEIs due to its convenient ‘on-the-go’ concept. On the other hand, embedding gamification elements in m-learning applications help in increasing the users’ interest in continuous use. Therefore, many HEIs have invested in producing their own m-learning products apart from utilizing existing m-learning applications that are widely available online. One of the challenges faced by HEIs is the low technology usage rates towards the ‘in-house’ developed applications, which affect the receptiveness of education stakeholders in investing or maintaining educational applications. Meanwhile, the lack of continuous usage had given a negative impact on their academic-related tasks and performance. Hence, it is important to understand the significant factors that influence learners’ intentions in continuance usage of a gamified m-learning application. This will serve as an insight to the HEIs management regarding the needs and design that better suits their users’ expectations. Methodology: This study employed a correlational cross-sectional research design using an online survey. The participants of the final survey involved first-year students from one of the Malaysian public universities. For the final analysis, 269 responses were analysed using the partial least square-structural equation modelling (PLS-SEM) technique, which is a powerful multivariate analysis mechanism. The Expected Confirmation Model (ECM), which is a post-acceptance model, was extended with the pre-acceptance model named Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), to form the research proposed model that describes the continuance intention in using a gamification-based m-learning application. Contribution: This research contributes to the body of knowledge and helps better understand users’ continuance intention in the post-acceptance phase of the gamified m-learning application. It exposes information at the individual level, regarding the continuance intention of using an m-learning tool that is equipped with gamification elements. This will mostly benefit the educational resource developers in the HEIs in producing effective ‘in-house’ learning tools. Findings: This research develops a theoretical enhancement of the Expectation Confirmation Model (ECM) that affects the HEIs’ m-learning resource developers and management, dealing with IT-related behaviour. Moreover, a solid continuance usage intention conceptual model, which incorporated two important models, was also introduced. Out of all ten hypotheses, only two were not supported that are related to factors facilitating conditions and social influence. Those two factors negatively influence the HEI learners’ continuance use intention. Meanwhile, the core factors for satisfaction, which are perceived usefulness and confirmation, were found to be significant. Lastly, satisfaction was proven to mediate the positive path between perceived usefulness and the continuance intention of using the gamified m-learning application. Recommendations for Practitioners: This study offers insights into strategies that the HEIs’ management should perform in securing continuance usage of the ‘in-house’ developed m-learning products. One of the strategies could be organising technology workshops that will prepare their educators in implementing the institutions’ gamified teaching and learning tools. Another highlighted issue is regarding the need for faculties to design an effective approach to entice educators and learners towards applying new learning technologies. Recommendation for Researchers: This study contributes to the micro-level analysis of the continuance use intention of gamification-based m-learning applications by fostering the understanding of the phenomenon at the individual level. It is recommended that other researchers extend the research model by incorporating other theories, as this study was only based on two models (i.e., ECM and UTAUT2). Additionally, a longitudinal study could be another approach that enables researchers to collect much richer data that includes a wide array of background characteristics or control variables. Another suggestion would be applying related factors that may contribute to the discovery of effective gamified m-learning application designs. Impact on Society: The findings of the study show the importance of confirmation made by the applications’ users towards usefulness and usage satisfaction. Confirmation and perceived usefulness also have an increasingly similar impact on users’ satisfaction with the application and their subsequent continuance use intention. It is also revealed that easy-to-use products are commonly expected nowadays, as users might be reluctant to spend much time on them. On the other hand, for a specific gamification-based product, it is also expected by the users for it to be capable of giving an ‘enjoyable’ experience, hence motivating continuance usage. As a result, an effective gamified m-learning application or product will be able to be used by Malaysian HEI learners if the developers and stakeholders develop and evaluate the usage of their products with the consideration of the information provided by this research. Future Research: Future studies could include respondents from other diploma programmes, resulting in an in-depth analysis. It is needed to support the generalizability of the findings in this study by considering larger populations from all different programmes. In addition, similar research can be done based on different circumstances; for instance, use of the gamified m-learning application during the in-campus physical classes instead of virtual classes (online), which might influence the users’ perception in terms of the social influence and facilitating condition.

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Section: Contributionsmentioning

confidence: 51%

Section: H3: Perceived Enjoyment (Penj) Has a Positive Effect On Gami...mentioning

confidence: 99%

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

et al. 2023

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“…The responses suggest that the adoption of AI technologies in the Serbian hotel industry has the potential to significantly contribute to sustainability goals. By streamlining operations, optimizing resource utilization, and enhancing service delivery, AI can help hotels minimize waste, reduce energy consumption, and mitigate their environmental impact [112][113][114][115][116]. Moreover, AI-driven analytics and predictive modeling can facilitate data-driven decision-making, leading to more efficient resource allocation and improved environmental stewardship.…”

Section: Discussionmentioning

confidence: 99%

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice

Gajić,

Vukolić,

Bugarčić

et al. 2024

Sustainability

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This study investigates the perceptions of employees in the hotel industry of the Republic of Serbia regarding the acceptance and importance of artificial intelligence (AI). Through a modified UTAUT model and the application of structural equation analysis (SEM), we investigated the key factors shaping AI acceptance. Research results show that behavioral intention and habit show a significant positive impact on AI usage behavior, while facilitating conditions have a limited but measurable impact on behavioral intention. Other factors, including social influence, hedonic motivation, performance expectancy, and effort expectancy, have minimal influence on the examined variables. The analysis reveals the crucial mediating role of behavioral intention, effectively bridging the gap between various predictors and AI usage behavior, thereby highlighting its significance in the broader context of technology adoption in the hotel industry. The primary goal of the study, which closes significant research gaps, as well as the manner in which it uses a specific model and statistical analysis to accomplish this goal, shows how innovative the work is. This method not only broadens the field’s understanding but also offers valuable insights for shaping sustainable development practices in the hospitality sector in the Republic of Serbia.

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“…Also, facilitating conditions significantly impact students' intention to interact with one another (Wut et al, 2022). While the influence of facilitating conditions on the success of information system implementation is crucial, there is a lack of empirical research in the literature concerning the relationship between facilitating conditions and continuance intention in private higher learning institutions (Kamarozaman & Razak, 2021). Furthermore, the predictive role of facilitating conditions, perceived ease of use, and perceived usefulness in Iranian EFL learners' perceptions of mobile-assisted language learning (MALL) were examined by Ebadi and Raygan (2023).…”

Section: Facilitating Conditionsmentioning

confidence: 99%

Predicting the Intention to Adopt Innovation in Supply Chain Finance

Figueiredo,

Camargo,

Ferreira

et al. 2023

Journal of Organizational and End User Computing

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Based on the mixed model unified technology acceptance and utilization theory (UTAUT) and spinner innovation model (SPINNER), a theoretical model is suggested to explain the determinant of behavioral intention to predict innovation in the context of a financial sector firm. A questionnaire was developed to collect primary data, which was subsequently processed through the artificial intelligence technique (deep learning). The constructs (performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, public knowledge, private knowledge, and innovation) supported the model, including mediating hypotheses. It was observed that the mixed methodological approach (SEM and ANN) can help to find the linear and non-linear relationships better, being that the error of the predicted model is 0.104, that is, 10.4% relatively low, which evidences that ANN can be used to predict the dependent variable innovation safely.

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The role of facilitating condition in enhancing user’s continuance intention

Cited by 8 publications

References 12 publications

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

Investigating Factors That Affect the Continuance Use Intention Among the Higher Education Institutions’ Learners Towards a Gamified M-Learning Application

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice

Predicting the Intention to Adopt Innovation in Supply Chain Finance

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