Managerial finance subject requires its students to apply accounting and complex mathematical skills (Brunstein et al., 2019; Marriot et al., 2015; Shum & Chan, 2011; Grover et al., 2010; Ishaq et al., 2008) . Unfortunately, most of these sets of skills are seemingly challenging to the majority of its students. Employees who are pursuing their study in business study programme are facing the difficulties of the subject. However, past studies have revealed that employees in management level that possess limited skills in managing the company fund may cause the organization to face these financial managerial issues (Hussien et al., 2018; Adomako, et al., 2016; Karadag, 2015) . Thus, the issue of improving the level of knowledge in this subject needs to be addressed well through continuous educational programme and training.
The learning process through traditional approach requires students to apply abstract reasoning in translating finance theories, formulas and calculation in building their understanding. In practice, the teaching and learning finance process includes the traditional face-to-face teaching and learning (Ismail et al., 2013) ; reflection and transformative training for managerial finance (Brunstein et al., 2019) ; online training for financial management (Ary & Brune, 2011) ; on job training (Ahmad et al., 2010; Wang & Taylor, 2016) ; computerized simulation of stock market (Marriot et al., 2015) ; blended learning approach for mature and part-time students in finance (Burgess, 2008) ; integrated case study and interactive simulation assignment (Thom, 2019) ; and interactive games for Islamic finance (Hakimah et al., 2018) . However, for this study, online training approaches through the Massive Open Online Courses (MOOC) were selected as the learning approach to facilitate employees to acquire the knowledge of basic managerial finance.
MOOC is an online educational environment primarily produces by educational institution that, i.e. the effort of transformative learning process of providing the quality education to the unlimited learners (Crosslin, 2018; Nordin et al., 2018) . The consideration of using MOOC as an alternative for corporate training will be supporting the process of lifelong learning (Fischer 2016) . Training through online approach sharing the same purpose with the traditional approach of corporate training is a program of skilling or re-skilling for employees carrier enhancement (Salas & Canon-Bowers, 2017) . MOOC benefited in corporate training context with the potential capacity to improve employment:
· For employees, the platform may influence the approach of communication and knowledge development through active learning participation.
· For facilitator, MOOC as supportive platform to the teaching and learning process that can stimulate the active learning environment.
· For developer, the traditional approach of facilitator-centered-learning to connectivism community needs them to reshape the learning environment that supports self-pace learning.
This study is to analyze the factors that reflected the behavior of use and the behavior intention among the Malaysian employees accept the MOOC as an approach for corporate training. For that purpose, this research is to identify the critical factors that influence the acceptance of online training via massive open online courses among the employee that having minimal exposure with online technology for academic purposes. The online training sets to teach and improve on several basic financial management practices in organization. The critical fragment in an organization is finance department. The process of managing the financial will ensure the smooth running business. Suggest each employee especially in management, sales and operation should understand the organization’s financial to ensure the business operation can be exercise smoothly. Thus, they are suggested to have basic financial management skills.
2. Literature Review
2.1. Online Training for Lifelong Learning
The agenda of empowering employees in higher education institution through lifelong learning programme context is supporting the effort of knowledge creating company. The Human Resource Department (HRD) policies that mold the culture of learning in commercial sectors might change the culture of empowered employees through education and training. Having a continuous, flexible and updated knowledge in respective skills by employees seems to be a challenge for some organization (Mohammed et al., 2016) . The challenges such as fund to provide employees training in SME (Johnson, 2002) ; effort and time constrain of employees (Boyer et al., 2014) , supports from top management and organization (Ramdhani et al., 2017) inhibit the lifelong learning process. But, those employees need to be strengthened and supports for their carrier enhancement through the skilling programme.
The changing climate in business force organization to adapt the technology in many aspects including in the training approaches for employee’s empowerment (Salas & Canon-Bowers, 2017) . Employees need specific training to enhance their capabilities in executing task. Thus, to spur the training activities in transferring the knowledge and respective skills, the organization need to create the supportive learning environment physically or virtually for each employee. This need online technology that promote self-efficacy online learning that can improve personal engagement (Beach, 2017) . The advent of the online corporate training in this era supports the self-paced or self-learner (Song et al., 2018; Song & Bonk, 2016) . The past study confirmed that e-Learning supports the achievement and improve learning engagement (Wang, 2017; Sedrakyan et al., 2018; Salas & Cannon-Bowers, 2017) . Thus, the online training seems to be applicable to assist employees in improving their knowledge and skills (Norman et al., 2015) .
This study is to recognize the employees’ acceptance towards online learning using Massive Open Online Courses (MOOC) and outline the significant factors affect employees’ intention to use MOOC for basic managerial finance training.
2.2. Unified Theory of Acceptance and Use of Technology
This study adapted the model of modified Unified Theory of Acceptance and Use of Technology (UTAUT). This model suggests the factors of prospect user, based on their past experience using media and educational material based Internet, in accepting MOOC as their learning platform alternatives.
The factor of Performance Expectancy pertaining to the employees believes that online training through MOOC will contribute positive effect on its performance in daily career activities. The second factor is Effort Expectancy is to identify the employee’s ability to use of technologies. The focus on this factor is to measure employees’ capabilities and ease of using the online learning platform. The third factor is Social Influence measure the influence of community that the employees should benefit the online learning technologies. The forth factors is Facilitating Condition that measure how the existing technology device and facilities support their learning activities. While the rest independence factors such as Behavior Intention and Use of Behavior to use online learning technology in the near future. Figure 1 illustrated the modified UTAUT model from the model suggested by Venkatesh et al. (2003) . Modification made due to this study was not measured the mediating variable as per model suggested.
The online questionnaire was used in the survey. The online questionnaire was administered over two month started 18 August 2017 until 13 September 2017 to the employees in commercial administration and operation departments. Majority of the respondents were the ex-students for subject Principles of Managerial Finance. The population of the study is based on the number of students enrolled in 2014/2015 with the total of 246 students. One of the courses to be taken in completing the Business Studies Degree program is the Principle of Managerial Finance which is a core subject in fulfilling the requirements of a degree. Purposive sampling with simple random selection of respondent selected as the method of sample selection. The study survey was based on previous study Venkatesh et al. (2003) and Harris (2016) . The validity and reliability test has conducted on the survey instrument and reported in pilot test section. The survey through email were administered and 94 was successfully returned. The items represent the online technology acceptance factors as per shown in Table 1.
Data Analysis Method
The data from the survey was analyzed through correlation and regression analysis. The study setting the hypothesis as per below:
1) H1cThe factors of Performance Expectancy (PE), Effort Expectancy (EE) and Social Influence (SI) have positive correlation with employees’ Behavior Intention (BI) to accept the online training via MOOC.
2) H2—The factor of Facilitating Condition (FC) has positive correlation with employees’ Use Behavior (UB) to participate with MOOC.
3) H3—PE is positive predictor for the employees’ BI in using MOOC.
4) H4—EE is positive predictor for the employees’ BI in using MOOC.
5) H5—SI is positive predictor for the employees’ BI to participate online training via MOOC.
6) H6—FC is positive predictor for the employees’ UB towards online training via MOOC.
7) Important. The suggested factor is confirmed accepted when the null hypothesis was rejected by p-value is less than .05.
Figure 1. The employees’ acceptance for online training framework.
Table 1. Items of the survey.
4. Results and Findings
As illustrated in Figure 2, majority of respondent is Female (67%) and the participants are from different department background: 16 percent from Account and Finance department; 21 percent from Human Resource Department; 26 percent from Administration and Procurement Department; and 37 percent were in Operation Department (Figure 3).
Figure 4 indicates that majority of the respondents’ finance result were C to C+ at 46 percent and as shown in Figure 5, seem that 51 percent of respondents had no experience in attending the online training.
Figure 2. Participant by gender.
Figure 3. Participant by department.
Figure 4. Initial finance result.
Figure 5. Experience online training.
4.1. Correlation Analysis
This study measured the convergence validity using Pearson Correlation Analysis. As denoted by Hair et al. (1998) the loading factor should greater than .50 or stricter criterion as per Fornell (1982) i.e. .70 of the correlated value. Table 2 shows the factors result of correlation analysis with acceptable convergence validity test value.
The Correlation value shows a positive and significant relationship between all factors. The result in Table 2 express positive and significant relationships between the factor of Behavior Intention (BI) and Performance E (r = .617, p < .000), EE (r = .590, p < .000), SI (r = .470, p < .000). While, UB and BI (r = .562, p < .000) and between UB and FC (r = .441, p < .01). Thus, H1 & H2 were accepted. It seems that factors have shown the positive correlation between workers’ PE, and EE with BI (strong relationship) and FC with UB (weak relationship). The data shows, there is an intention that online training via MOOC is accepted but the developer needs to supports in terms of facilitating the respondents due to lack of experience and guidance.
4.2. Regression Analysis
The analysis as illustrated in Table 3 indicated that the factor of influence of performance expectancy (PE), effort expectancy (EE), and social influence (SI) towards behavioral intention (BI).
Table 2. Correlation of the factors.
**. Correlation is significant at the .01 level (2-tailed).
Table 3. The regression for the influence of PE, EE, SI on Behavior Intention (BI).
Table 3, the factor of performance expectancy have the most significant influence on employees’ intention with F(90) = 24.637, β = .406, p < .004 & SI F(90) = 24.637, β = .251, p < .005. The value of R-square is .451 indicates that the Perceive Expectancy and Social Influence explained 45.1 percent of the variance in workers’ intention to use MOOC as their medium to acquire the training. The performance expectancy of employees is the most positive predictor to workers’ intention to improve their finance skills through online training via MOOC. The value of R square were relatively low and indicated that model explain the variability of response data were not supported. Unfortunately, the value enough for the context of the study. Occasionally, the attempt to prognosis human behavior is hard to predict compare to the physical study (Dass 2015; Frost 2014) . The result shows that H3 and H5 were accepted while H4 was failed to be accepted.
The squared partial correlation shown in Table 3 shows uniqueness of respective factors, which is the amount of variance that cannot be explained by other variables entered in the equation. Performance Expectancy explained the largest amount of unique variance i.e. 22.9 percent in satisfaction compared with the EE and SI. As denoted in Table 3 the effort expectancy with 22.3 percent and the social influence with 7.6 percent of the unique variance in employee behavior intention to use MOOC as training approach.
In determining the rejection or acceptance the H6 the analysis of regression were conducted as per Table 4. Both, Behavior Intention (BI) and Facilitating Condition (FC) towards Use of Behavior (UB) shows a statistical significant. The results are shown as per Table 4.
Table 4 shows that the BI have significant influence on employees UB towards online technology with the value of F(91) = 24.159, β = .406, p < .000 and the factor of facilitating condition with F(91) = 24.159, β = .139, p < .039. The R square of .347 indicated that the behavior intention of the workers’ explained 40.6 percent of the variance in employees’ use of behavior. This means the determination towards online training of employees in this study was significantly affected by the factor. In order to determine the uniqueness of a factors which is the total of variance that cannot be explained by other variables, the squared partial correlation are referred. The higher the better. As denoted in Table 4, the factor of behavior intention to use online training via massive open online courses explained the largest amount of unique variance with 39.1 percent in satisfaction compared to facilitating condition factor with 17.8 percent of the unique variance in use behavior of the employees to use massive open online courses as a training platform.
4.3. Pilot Study
Items of the instrument were validated by three experts consist of two experts in e-Learning and an expert from finance education. Two round validation was conducted. The instrument was measured by percentage of agreement. Abdullah & Leow (2017) in suggesting the validation approach stated that the elimination of item should be done if the agreement is below 60 percent. Thus, all the factors accepted to be used in the second validation and the result as per Table 5.
The piloting on instrument continues with the reliability values by 30 employees led some changing to improve the Cronbach’s Alpha value before the actual survey conducted. The reliability value was above the suggested reliability value i.e. higher than .70 (Sekaran, 2006) . Table 6 shows the alpha value of all apart from is equal or more than .70.
Table 4. The regression for the influence of BI and FC on UB.
Table 5. Experts validation on instrument.
Table 6. Cronbach’s Alpha of all factors.
This study is regarding the acceptance of Massive Open Online Courses as a medium of employee online training. This study shows that the respondent’s intention behavior towards MOOC in having a training on the basic Managerial Finance depends on its performance expectancy and social influence. The internal factors such as initiative to increase productivity and improve knowledge together with the external supports from organization and community lead to increasing the usage of online corporate training among the employees. Employees are expected to have additional supporting for such facilities from their superior or organization to embrace MOOC as a new initiative in training approach. Developers of online training should consider employees’ awareness by promoting convenience, ease of use and motivation towards using online medium for academic purposes, especially for those who are not competing with the online training. The approach might improve the employee’s educational opportunity with educational enjoyment in supporting their lifelong learning process.
Financial support for this publication has been provided by Faculty of Education, Universiti Kebangsaan Malaysia with the Grant number AP-2017-004/1 and MRUN-RAKAN RU-2019-003/1. The views in this publication do not necessarily reflect the views of the faculty on teaching and learning.