Investigating Hospitality Student’s Acceptance in Online Learning Platform: Utilising UTAUT Model

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Introduction
At the end of 2019, the Corona Virus outbreak hit all types of industries worldwide, and WHO designated SARS-Cov-2 in March 2020. There have been over 1 million deaths worldwide (WHO, 2020). Many industries globally cannot manage the pandemic's effects. One hundred twenty countries have abandoned face-to-face studying. COVID-19 affects 1 billion pupils worldwide. Higher education dominates online learning (Shahzad et al., 2020). As an emergency effort to avert the COVID-19 pandemic, practically every government has urged public schools and higher education institutions to close. Fear of illness and casualties have impacted Malaysia's higher education scene, including the Hospitality Education Department at the Malaysian Polytechnics.
The spread of this virus and the pandemic, in general, have altered the world of education. Online classes have supplanted face-to-face activities. Education must move online. It changed one of the unwritten school regulations that all students must be in one place to learn. Traditional learning environments have been classrooms and classes. Online activism, then, has changed the norm. It has forced professors and educators to conduct lectures remotely, without face-to-face contact. Many educators have rethought the purpose of education and their connections with students (Zhao & Watterston, 2021). Less active students may miss messages to keep them on track because online activities are not part of scheduled class time (Davis et al., 2019). In this sense, online learning can lead to student isolation and monotony without classroom dynamics. This gap may worsen if teachers do not use technology to build student relationships (Lee et al., 2016). During this time, Polytechnic hospitality students had trouble studying. Many scholars say that online education is a digital revolution and educational breakthrough (Dwivedi et al., 2011(Dwivedi et al., , 2019. Individualised, computerised, enjoyable, integrated, visual, and game-based learning is common today (Bonk, 2016). The success of online learning depends on how it influences all fields of knowledge and education (Al Mulhem, 2020). Online learning in developing nations like Malaysia broadens the horizons of quality content, boosts teaching and learning standards, reduces delivery costs, and increases networking and collaboration among Malaysian academics worldwide. Malaysia's higher education system must shift from conventional teaching methods to technologyenabled innovation to deliver and customise education for all students, according to the Malaysia Higher Education Blueprint 2015-2025.
UTAUT has also been used to examine ICT applications in mobile banking (Zhou et al., 2010), mobile phone technologies (Zhou, 2011), Internet banking (Unrau & Schlackman, 2010;Riffai et al., 2012), e-government (Schaupp et al., 2010), e-recruitment (Laumer et al., 2010), and virtual learning technologies (Liu & Wang, 2009;Zhou et al., 2010). Various studies have examined the barriers to digital learning adoption globally. Abbad (2021) studied Jordanian students' use of e-learning. Performance expectation, effort expectation, behavioural intention, and facilitating condition affected online learning acceptability among students but not social influence (SI). Numerous studies have used this UTAUT theoretical framework; however, studies related to online hospitality education are currently insufficient; therefore, more study is needed. First, few studies have examined student acceptance and adoption of such systems and their teaching and learning outcomes, especially among hospitality and tourism students (Gorissen et al., 2012). Next, few studies focused on online learning systems like Microsoft Teams in Polytechnic's hospitality online education. A study like this could assist Malaysian Polytechnics in exploring online hospitality education.
The structure of this paper does include a literature review on online learning during Covid-19 in Malaysia's Higher Education System, focusing on hospitality students in Polytechnic, the online learning platform used as the medium in conveying online classes, and the construct in UTAUT, which relates to this proposed concept paper. The final section covers the study's conceptual framework and conclusions.

Literature Review Online Learning During COVID-19 Pandemic
The COVID-19 pandemic has disrupted education systems internationally, affecting 1.5 billion children and youth (UNESCO). Governments, schools, and education systems offer remote learning and instruction with minimal planning, preparation, and digital skills (Kamanetz 2020). Next, conventional assessments and high-stakes testing were abandoned, and education was allowed to adapt quickly (Zhao & Watterston, 2021).
Malaysia had 6,002 COVID-19 cases by April 30th, 2020 (Hashim et al., 2020). In response to COVID-19 infections, Malaysia issued a Movement Control Order on March 18th, 2020 (New Straits Times 2020). The Movement Control Order requires all colleges and universities to implement e-learning by December 31st, 2020 (Palansamy, 2020). Asynchronous and synchronous IT technologies and infrastructure assist higher education (Larasati & Santoso, 2018). Asynchronous learning systems don't require time-sensitive interactions from educational stakeholders (Larasati & Santoso, 2018). Students in synchronous learning environments attend live lectures, participate in real-time, and receive fast feedback. However, asynchronous learning environments lack organisation.
Learning content for e-learning is accessible through many platforms and forums than living lectures or courses. This prevents immediate input and response (Littlefield, 2018). Synchronous learning promotes social opportunities (McBrien et al., 2009). Online platforms where (a) video conferencing with at least 40 to 50 students is possible, (b) discussions with students can be held to keep classes organic, (c) internet connections are good, (d) lectures are accessible on mobile phones as well as laptops, (e) previously recorded lectures can be viewed, and (f) instant student feedback and assignments can be taken are required (Basilaia et al., 2020). Online learning platforms promote instruction, resource exchange, and simultaneous teacher-student collaboration (Zacharis & Nikolopoulou, 2022). They offer synchronous and asynchronous instruction, allowing teachers to engage with students and deliver lessons (Sayeh & Razkane, 2021).

Microsoft Teams as an Online Learning Platform
Zoom and Microsoft Teams are popular video-conferencing tools in Malaysia (Birruntha, 2020). During the COVID-19 outbreak, JPPKK ensured that teaching and learning proceeded in 36 Polytechnics and 104 Community Colleges. Jabatan Pengajian Politeknik dan Kolej Komuniti (JPPKK) proposes the Microsoft Teams Platform as an online learning platform for merging online classrooms and evaluations. As part of Microsoft Office 365's communication platform, Microsoft Teams was utilised in commercial, hybrid, and online courses (Buchal & Songsore, 2019;Ly et al., 2021). Meetings, video conferencing, and file storage are included. Microsoft Team members can build and operate virtual courses like real classrooms, allowing students to connect with peers and teachers. Online class sessions, discussions, publications, and evaluations can facilitate this relationship (Bsharat & Behak, 2020;Ly et al., 2021;Pal & Vanijja, 2020). Microsoft Teams allows students and teachers to communicate online uniquely (Pal & Vanijja, 2020;Bsharat & Behak, 2021).
Microsoft Teams is useless for lab classes and giving long essay responses . Microsoft Teams' downsides include a lack of connection between students and teachers, leading to social isolation, mental challenges, negative thinking, and a lack of selfmotivation and poor time management (Latip et al., 2020). Microsoft Teams clients may have limited internet access, invisible images, and unclear audio (Rojabi et al., 2020). It can be considered that Microsoft Teams' acceptability as an online learning tool in higher education is still at its early stage, to say at least. Venkatesh et al (2003) created the UTAUT paradigm, which has four parts (performance expectancy, effort expectancy, social factors, and facilitating conditions). Performance expectation is how much a person (in this scenario, a student) believes technology will help them achieve academic goals at a typical university. The study found that performance expectation is the model's most influential dimension (Venkatesh et al., 2003). Adjusting performance expectations suggests students will view Microsoft Team as a positive online learning environment. Effort expectation is a system's ease of use, and an effort-oriented construct is prominent at the beginning of a new habit (Venkatesh, 2003(Venkatesh, & 2012.

Unified Theory of Acceptance and Use of Technology (UTAUT)
Applying effort expectations to this study's setting simplifies Microsoft Team's online education deployment. This term refers to how one's behaviour is influenced by how they perceive others who will view them due to technology use. Social influence is how much a person considers prominent people to support the new system. Venkatesh (2003) mentioned that social components are more important in classrooms. Facilitating conditions refer to how much an individual believes a system's organisational and technological infrastructure exists (Akbar, 2013). These four features determine whether students choose Microsoft Team as their online learning platform. Applying effort expectations to this study's setting simplifies Microsoft Team's online education deployment. This term refers to how one's behaviour is influenced by how they perceive others who will view them due to technology use. Social influence is how much a person considers prominent people to support the new system. Venkatesh (2003) says social components are more essential in classrooms.

Performance Expectancy (PE)
Performance expectancy (PE) is a person's view of technology's usefulness (Venkatesh et al., 2003, Ain et al., 2016. In analysing student acceptance of online learning platforms, effectiveness for studying is considered (Decman, 2015). Lwoga and Komba (2015) characterise the level at which pupils realise the system's classroom benefits. Thus, consumers would adopt the technology if it improved efficiency. Online learning students will use technology for instruction. Several researchers evaluated the effects of a technology's Performance Expectancy (PE) on behavioural intention to utilise it in voluntary and mandatory situations and found a direct effect (Casey & Wilson-Evered, 2012;Dwivedi et al., 2011;Gupta et al., 2008;Sumak et al., 2011;Venkatesh et al., 2003;Zhou et al., 2010). Sumak et al. (2010) found that performance expectation positively affects online learning behaviour intention. The literature demonstrates that students will use online learning if they believe it will improve their performance. As a result of the review, the authors present the following proposition:

Effort Expectancy (EE)
In the study, Yoo et al. (2012) discovered that Effort Expectancy (EE) is the most influential component. The user-friendliness of technology is how much labour a person perceives to put into using it (Decman, 2015). Researchers study early technology uptake and effort expectations. Gupta et al (2008); Venkatesh et al (2003) found it directly affected Behavior Intention (BI), although Venkatesh (2000) demonstrated it became minor over time. However, Gruzd et al (2012) found a negative connection. Raman & Don (2013) concur that the link between Effort Expectation and Behavior Intention is good. A small effort to employ online learning led to a better Behavior Intention (BI). As a result of the comparison, the authors have the following proposition:

Proposition 2: Effort Expectancy (EE) positively affects behaviour intention (BI)
Social Influence (SI) Social Influence (SI) is peer reflection. Technology impacts instructors' and friends' evaluations of social intents (Venkatesh et al., 2003). SI measures a student's social acceptance of online learning. Online learning influences Behaviour Intention (BI). As technology and social networking services have advanced, the emphasis has shifted from real to virtual (Decman, 2015). Scientists found a relationship between Social influence (SI) and behaviour intention (BI) of attitudes toward technology use in voluntary and involuntary situations on necessary conditions (Gruzd et al., 2012;Gupta et al., 2008;Venkatesh et al., 2012;Venkatesh et al., 2003). Social pressure encouraged employees to use e-government services (Al-Shahrani, 2016). Fidani & Idrizi (2012) discovered that investigating elements that affect online learning platforms to social influence affects students' Behavior Intention (BI) to use the platform. The authors provide the third proposition in the review:

Facilitating Condition (FC)
Facilitating Conditions (FC) is the availability of necessary help and resources for using technology. It also focuses on technical and organisational infrastructure for online learning. Education, technical aid, and infrastructure are needed (Decman, 2015). The initial UTAUT model found that FC had a direct but modest impact on BI (Venkatesh et al., 2003). Dwivedi et al. (2011) found that the link between Facilitating Condition (FC) conditions and Behavioural Intention (BI) was the weakest. Moreover, the study indicated that restricted resources hinder pupils' acceptance of web-based technology. They rely on teachers' and technological support to positively affect their use of online learning platforms (Abdullah et al., 2020;Pal & Vanijja, 2020b;Zhang & Qin, 2018). (Ain et al., 2016). Moreover, allowing conditions can affect online learning acceptability (Toquero, 2020). It implies students' views of enabling environments predict their online learning behaviour intention (BI). Therefore the authors provide the fourth proposition based on the review.

Behavioural Intention (BI)
BI is a person's purpose of using technology for numerous tasks (Kim et al., 2021). Moreover, Kim et al (2020) defined Behavior Intention (BI) as the student's desire to undertake online learning to accomplish course objectives. Researchers have found a direct correlation between BI and technology use (Davis, 1989;Raman & Don, 2013;). Furthermore, the study also found that students' Behaviour Intention (BI) in adopting an elearning system positively corresponds to their user behaviour, leading to better grades. An individual's technology usage is called usage behaviour (Bagozzi, 1981). The authors of this study predict a positive association between online learning behavioural intention and use. The authors conclude the review with the fifth proposition:

Proposed Conceptual Framework
A conceptual framework is based on the aforementioned arguments and propositions. The framework comprises five dimensions of Venkatesh (2003) UTAUT, suggested by previous literature and past studies. The hypotheses relationship between the five dimensions of student's acceptance of online learning platforms is developed based on the propositions by the proceeding researchers. Thus the conceptual framework is presented in Figure 1.
The selected paradigms and study setting suggest a quantitative approach. This study will use cross-sectional research to examine predictor-variable relationships.

Conclusion
This investigation will develop and test a model of UTAUT's influence on hospitality students' acceptance of online learning platforms during the COVID-19 pandemic and makes substantial theoretical and managerial breakthroughs by addressing critical gaps in the existing research.

Academic Contribution
This research contributes to the existing body of knowledge on hospitality students' technological acceptance of online learning platforms. It also provides the Jabatan Pendidikan Politeknik dan Kolej Komuniti (JPPKK) with further theoretical knowledge regarding the use of Microsoft Teams as an online learning platform. In addition, this study will aid practitioners and policymakers in acquiring a better and more comprehensive understanding of the elements influencing hospitality students' acceptance and use of Microsoft Teams as their online learning platform. At the same time, it gives sufficient evidence for stakeholders to determine the efficacy of teaching and learning systems in Malaysian Higher Education. Finally, the study will contribute to the literature on hospitality online education, as little research has been undertaken on the online learning activities of hospitality students in Malaysia.

Practical Contribution
This study could aid the Department of Tourism and Hospitality at Malaysian Polytechnics in determining the efficacy of Microsoft Teams as an online learning platform for their teaching and learning process. The study provides direct information on the acceptability of Microsoft Teams among Department of Tourism and Hospitality students as an online learning platform. Therefore, the study will investigate how the UTAUT variables influence the adoption of this online learning platform, thereby encouraging students to participate actively in online classes. The collected data also will be useful for the department in developing strategies for continuous improvement to enhance the lecturers' delivery methods, enhancing the student's interest and intent to continue using Microsoft Teams as an online learning platform at Malaysian Polytechnics. It also contributes to improving the online learning experience for students. In addition, it aids the organisation in designing a strategic training strategy to enhance the lecturers' online teaching skills.