An analysis on the importance of motivation to transfer learning in VUCA environments

Article history: Received: June 24 2019 Received in revised format: July 28 2019 Accepted: September 3, 2019 Available online: September 3, 2019 In this VUCA world, much can be achieved when one is open to learning. The purpose of this study is to analyze the impact of organizational learning culture, employee commitment, and job satisfaction towards motivation to transfer learning. The data are collected by distributing 200 questionnaires for employees working in Jakarta area. The method used to do the analysis is by using a multilinear regression. Based on the result, organizational learning culture and job satisfaction had significant impacts to motivation to transfer learning. Meanwhile, employee commitment does not have significant effect on motivation to transfer learning, however, it has an impact on the gender, age, and length of work. © 2020 by the authors; licensee Growing Science, Canada


Introduction
There are increasingly aspects of rising digital economy because of the current expansion of the global business environment and the advancement of technology.The uncertain yet highly disruptive economic environment also continually pressures incrementally organizations "to understand the future and to plan responses" (Raghuramapatruni & Kosuri, 2017).In a volatility, uncertainty, complexity and ambiguity (VUCA) world, multinational enterprises have pressured themselves to become global organizers of economic systems incorporating knowledge-seeking motives (Cantwell, 2016).The value is not just acquiring it but how the "dissatisfaction of knowledge" causes the idea of transferring the learning (Millar et al., 2018).To deal with VUCA, it would require an effective approach of a better understanding of and coordination between management innovation at the level of functional level (organizational learning culture) and individual level (e.g.job satisfaction, employee commitment) (Singh & Chand, 2018;Horney et al., 2010).
A lot of literature has discussed various attributes and qualities of learning transfer in the context of staff development.Some of the literature has yielded a result based on qualitative method, e.g.collaborative teaching assistants in an intensive Spanish course (Stepp-Greany, 2004), university-level instructional development (Medsker, 1992), among college science professors (Fedock, 1996), and professional development of Canadian educators (Chitpin, 2011).Other studies utilized quantitative method, e.g.how learning transfer inventory dimensions differ across individual variables (Velada & Caetano, 2009), and the relationship between learner utility reactions and predicted learning transfer (Ruona et al., 2002).Even though some studies define the transfer of learning in employee development, the causal linkage has resulted in different indications, i.e. partial or no indication of transfer (Addy & Blanchard, 2010;Gibbs & Coffey, 2004;Stes et al., 2010;Dixon & Scott, 2003;Nasmith et al., 1995;Rothman & Robinson, 1977;Sheets & Henry, 1984).
To fill the gap, this study aims to enrich such literature by investigating the interaction among organizational learning culture, employee commitment, and job satisfaction on motivation to transfer learning, notably in terms of quantitative research.Although motivation to transfer learning has been emphasized previously as important to the success of organizational learning and performance, the current study on motivation to transfer learning in employee development context is still limited (Egan, Yang, & Bartlett, 2004).More specifically, the following research questions guided the study:  Does organizational learning culture have an impact on employee commitment? Does organizational learning culture have an impact on job satisfaction? Does organizational learning culture have an impact on motivation to transfer learning? Does employee commitment have an impact on motivation to transfer learning? Does job satisfaction have an impact on motivation to transfer learning?

VUCA
Volatility, Uncertainty, Complexity and Ambiguity, the acronym VUCA, originated in the U.S. military to define conditions military leaders encounter on the battlefield (Whiteman, 1998).VUCA is a concept to know the definition of a competitive environment in relation to digital economy that can be rectified by appropriate technology adaptation to thrive in environmental change at proper time and right stages (Bennett & Lemoine, 2014).In current VUCA environment, organizations should focus on learning organizations by being co-creative and work collaboratively outside the boundaries of the organization (Dhir, 2019;Baltaci & Balci, 2017).Dhir and Mital (2013) propose that organizations must continually take advantage of evolving market opportunities and react quickly to any change or evolutions in market.

Motivation to Transfer Learning
Knowledge required for technological innovation is deemed to be highly tacit in nature (Mudambi & Swift 2012;Dhir & Dhir 2017).Every business leader should focus on learning how to disseminate new knowledge and facilitate effective collaboration, teamwork, and conflict management (Millar et al., 2018).To cope with changes in a VUCA world, an organization needs to focus on the technology-enabling knowledge transfer (Kenney, 2009).In a transfer of learning context, motivation is defined as "a learner's desire to apply skills, knowledge and/or attitudes mastered in an intervention" (Noe, 1986).Motivation to transfer involves the drive or inspiration of an individual to reassign knowledge gained from formal or informal learning to a job-specific context (Egan et al., 2004).

Employee Commitment
Lo and Ramayah (2009) observed that employees with a sense of commitment are less likely to participate in retirement behaviors and more ready to accept change.Therefore, these values may have severe implications for a core of committed people who are the subject of organizational life.Committed employees are people who are extremely encouraged to contribute their time and energy to the achievement of organizational objectives, thus they are increasingly recognized as the organization's critical asset (Hunjra, et al., 2010).There are several methods that can be used in order to increase the level of employee commitment such as recognition at work, reward, and better work environment (Pangaribuan & Febriyanto, 2019).The relationship between employee commitment and workers' performance has been studied in the past.For example, Khan et al. (2010) investigated the impact of employee commitment on employee job performance and found a positive relationship between them.

Organizational Learning Culture
Companies are facing the condition where they need a learning and development of employees in order to compete with the other companies in the competitive market.Therefore, it is not only an individual in organizations that need to learn and grow but it is important also for the company to apply a learning culture (Skerlavaj & Dimovski, 2011). Yang et al. (2004) define organizational learning culture as the culture that promotes information acquisition, distribution and transfer practices for learning-based application and recognition.Organizational learning is a complex process which requires endless period of time that refers to new knowledge development and has the potential for behavioral change (Murray & Donegan, 2003).As knowledge is increasingly becoming a key productivity factor, it has also become a competitive success measurement.Understanding factors contributing to organizational learning and knowledge transfer to the workplace environment is essential for the development of human resources (Swanson et al., 2001).

Job Satisfaction
Job satisfaction is defined as affective reactions of an employee to a job based on a comparison of desired results with actual results (Egan et al., 2004).Therefore, in general many employees measure their level of job satisfaction based on the compensation that the company give to them, the purpose of work, motivation, leadership style and acknowledgment.It is important to maintain the level of job satisfaction of the employees, because it has an impact to their performance in general.Job satisfaction is important to organizations because employees who are satisfied with their job can put more effort into their work (Broome et al., 2009).

Hypothesis Development
Employee commitment may be defined as the degree to which the employee feels dedicated to his organization (Akintayo, 2010).Furthermore, Ongori (2007) explains that level of employee commitment or loyalty to the organization is based on what company offer to them like job enrichment, employee empowerment, and compensation.Based on Tharanganie's (2013) study, employee career commitment negatively affects motivation to transfer learning.However, the findings are contradicting with the study by Cheng and Ho (2001) where employee commitment has a significant impact to motivation transfer learning even though the relationship is weak.Hence the hypothesis: H1: There is an influence of employee commitment towards motivation to transfer learning.
According to Banerjee et al.'s (2017) study, organizational learning culture could help the transfer of learning and training, and also improve the performance of the employee.In an organization, a climate of knowledge transfer may depict flexibility and openness of the management to radical changes, which would create a positive attitude among the employees to generate ideas and innovative solutions (Banerjee et al., 2016).Organization learning culture which reflects the values and beliefs about the importance of learning at work has been found to be positively related to transfer motivation (Zubairy et al., 2015;Egan et al., 2004).Lee et al. (2014) found that employees' level of self-efficacy and organizational commitment had significant effects on motivation to learn, while supervisor and peer transfer support had significant effects on motivation to transfer.Therefore, we posited that: H2: There is an influence of organizational learning culture towards motivation to transfer learning.
Job satisfaction was defined as an employee's affective reactions to a job based on a comparison between desired results and actual results (Egan et al, 2004).Job satisfaction should be considered by organization managers in policy making and as an instrument of competitive advantage.Because if the employee's satisfaction rate were high, it would be better for the organizational performance (Ahmad et al., 2014).A positive relationship was identified between job satisfaction and learning climate (Mikkelsen et al., 2000).Since job satisfaction and organizational learning culture have a powerful connection with job performance, reinforcing them by implementing the correct human resource policies is very important.If the employee is highly happy with his/her jobs, policies, employees, oversight and achieves a high level of general job satisfaction with his/her work, his/her commitment to the organization seems to be more probable than if he/she is not satisfied.(Emami et al., 2012).A correlation between job satisfaction and transfer of learning has been discussed in previous studies (Kontoghiorghes, 2004;Nair, 2007).Therefore, based on the aforementioned discussion, it can be hypothesized that: H3: There is an influence of job satisfaction towards motivation to transfer learning.

Research Methodology
The method used in this research is a descriptive research using a non-probability sampling.The survey started in January until June 2019 which was administered by utilizing online questionnaire platform comprises of set of questions in Likert scale measurement.The population of the current study includes employees whose offices were located in the city.From 215 distributed questionnaires using Google Form link, only 200 responses are valid resulting in a response rate of 93%.The survey was built based on prior research which uses currently validated scales with the range of response options from "1=strongly disagree" to "5=strongly agree".The original items were in English and were translated into Bahasa Indonesia.The dimensions are adapted from previous studies (Marsick & Watkins, 2003;Hsu, 2009;Irefin & Mechanic, 2014;Ruona et al., 2002).The proposed structural model can be seen in

Results and discussion
A pretest was conducted based on 30 respondents' data to examine the validity and reliability of the questions.The value of KMO that is greater than 0.5 is barely accepted, below 0.5 unacceptable, between 0.7 and 0.8 good, between 0.8 and 0.9 great, and greater than 0.9 superb.For the anti-image correlations, the values should be above 0.5.In conducting the reliability test, the result of the Cronbach's Alpha value will be a number between 0 and 1 and the test can be accepted if the values are 0.7 or higher.The value of the alpha that is lower than 0.7 is unacceptable and considered unreliable.The summary of the validity and reliability of each questionnaire questions can be seen in Table 1.For demographic profile, the respondent's age (see Fig. 2) is categorized into 4 classifications: 21-30 years old (141 respondents), 31-40 ( 24), 41-50 ( 17), and 51-60 ( 18).The majority of the respondents comes from those who are in the 21-30 years of age range with the total respondents of 141 or 70.5% of the total.For the place of residents, majority comes from Jakarta with the total respondents of 122 or 61%.The respondent's monthly allowance is categorized into three classifications and most of the respondents (45.5%) spent in between 5,000,000 to 10,000,000 rupiahs (equivalent of approximately USD350 to USD700).Out of the three options of length of work that has been presented, majority of the respondents (58.5%) has worked less than 2 years.Based on Table 2, the tolerance values for all variables are greater than 0.1 and the VIF values are smaller than 10.Therefore, it can be concluded that the variables are free of multicollinearity, indicating that the correlation between independent variables would not cause any instability in the following regression analysis.The multiple R (R) from the regression test (Table 3) describes the strength of the overall linear relationship.Since the result of the coefficient of determination is close to 0.5, it means that the linear relationship is strong.Besides, the model summary also shows the R Square ( ) which measures the proportion of variation in dependent variable towards the independent variable.The result of R Square is 0.729 which illustrates that 72.9% of MTL can be described through EC, OLC, and JS.The significance threshold for this study is set at p ≤ 0.05.Moreover, the results of the implementation of ANOVA test yields F-Value of 176.057(Sig.= 0.000) which confirms the regression equation having linear relationship.According to the t-test's rule of thumb, to reject the null hypothesis (H0), the p-value should be less than the alpha of 0.05 and the value of t-test should be higher than the t-table.The result of H1 signifies that the p-value of OLC is 0.000 which is lower than α of 0.05, then it can be concluded that the variable is significant.The value of t-test is 8.304 and the t-table is 1.980.The value of t-test is higher than the t-table, which indicates that the null hypothesis (H0) is rejected.Overall the variable of OLC is significant and null hypothesis (H0) should be rejected while H1 should be accepted.Therefore, it can be implied that OLC has a positive influence on motivation to transfer learning (MTL).The result of H2 signifies that the p-value of EC is 0.198 which is greater than α of 0.05, then it can be concluded that the variable is not significant.The value of t-test is 1.291 and the t-table is 1.980.The value of t-test is lower than the t-table, which indicates that the null hypothesis (H0) is accepted.
Overall the variable of EC is non-significant and null hypothesis (H0) should be accepted while H2 should be rejected.Therefore, it can be implied that EC does not have any influence on motivation to transfer learning (MTL).The result of H3 signifies that the p-value of JS is 0.000 which is lower than α of 0.05, then it can be concluded that the variable is significant.The value of t-test is 5.729 and the t-table is 1.980.The value of t-test is higher than the t-table, which indicates that the null hypothesis (H0) is rejected.Overall the variable of JS is significant and null hypothesis (H0) should be rejected while H3 should be accepted.Therefore, it can be implied that JS has a positive influence on motivation to transfer learning (MTL).

Conclusion
The main conclusion of this study is that organizational learning culture, job satisfaction, and employee commitment are important antecedents of motivation to transfer learning.However, from the proposed model, one can conclude that the relationship between employee commitment and motivation was not statistically significant.This finding is against the discovery in prior studies (Cheng & Ho, 2001;Lee et al;2014).The result may give an indication that the employees do not believe that application of new skills and knowledge can lead to job performance and desired/valued outcomes.
Although organizational learning culture seems to be the most important predictor of motivation, one can see that job satisfaction also plays a major role when conserving the effect of the dependent variable as motivation to transfer learning.The confirmation of the positive influence of organizational learning culture on motivation to transfer learning is consistent with the findings of prior studies (e.g., Banerjee et al., 2016;Zubairy et al., 2014;Egan et al., 2004).The research also found that the positive influence of job satisfaction on motivation to transfer learning aligns with prior studies (Kontoghiorghes, 2004;Nair, 2007).
It is important as well to make sure that the organization prepares the working environment that motivates the employees to transfer their knowledge gained while in training to the workplace.To satisfy these professionals, HRD practitioners need to provide an effective learning organization as well as culture of knowledge sharing.Organizations can emphasize organizational learning and knowledge sharing in various ways, e.g.building an effective learning organization, sharing vision with their employees, encouraging team learning in organizations, creating cross-functional work teams and peer discussion groups, and promoting knowledge acquisition and sharing (Hsu, 2009).Internal knowledge of an organization might be combined with those from external to the organization involving the dissemination of learning through meetings or computerized communication networks (Basten & Haamann, 2018;Lichtenthaler, 2016).In a VUCA world, despite the existence of all kinds of risks outside the boundaries, organizations need to do something against the threats and continually explore VUCA environments (Baltaci Balci, 2017).
Although our proposed structural model was conceptualized in terms of causal relations, this approach using the regression technique does not allow for conclusions to be drawn on causal implication.The fact that the sample for this study comes from participants in certain profession may limit further the generalizability of the findings.Therefore, more research using different sampling approaches and in other industries with different groups of employees is needed.

Fig. 2 .
Fig. 2. Personal characteristics of the participants