Studies in Business and Economics

THE INFLUENCE OF SUPERVISORY AND PEER SUPPORT ON THE TRANSFER OF TRAINING

NG KUEH Hua University Malaysia Sarawak, Malaysia

Abstract:
The burgeoning literature investigating the effect of supervisory support on the transfer of training is characterized by inconsistent findings. Also, to date, research examining peer support is still lacking, despite earlier studies show support emanating from co-workers has a significant influence on the transfer of training. Hence, this study attempts to rectify the inadequacies in the literature by examining the effects of supervisory and peer support on the transfer of training. Based on a cross-sectional method, quantitative data was collected from 100 employees working in one of the Malaysian state health departments, with a response rate of 48 percent. The results of multiple regression analysis revealed that supervisory support was not significantly associated with transfer of training, whereas peer support exerted a significant and positive influence on transfer of training. This study responded to the pressing calls for more studies to elucidate the relationship between social support and the transfer of training. The findings contributed to the body of literature by clarifying the nature of relationships between supervisory support, peer support and transfer of training, particularly from the Malaysian workplace perspective.

Key words: Supervisory support, peer support, transfer of training

1. Introduction Over the years, organizations increasingly invest on training and development to improve employees’ work performance. It is estimated that organizations in the United States spend approximately $130 billion annually on training and development (Paradise, 2007). Unfortunately, only a small portion of learning is actually transferred to the job (Pham, Segers & Gijselaers, 2010). As a result, it is not surprising that human resource practitioners often questioning to what extent employees are able to change their behaviour after attending training (Blume, Ford, Baldwin & Huang, 2010). Practitioners have been experimenting with various organizational interventions that are proven by training researchers as effective and reliable in promoting the transfer of knowledge, skills and attitudes (KSA) on the job (Ford & Weissbein, 1997; Cheng &

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Ho, 2001). However, this method is often costly, time-consuming and required a lot of efforts, though generally do not generate desirable results (Cheng & Ho, 2001). Transfer of training is often regarded as the extent to which employees effectively apply the KSA gained in the training context on the job (Baldwin & Ford, 1988; Chiaburu & Tekleab, 2005). Over the past two decades, there has been a considerable research examining transfer of training after Baldwin and Ford (1988) proposed a comprehensive model of training effectiveness (Ford & Weissbein, 1997; Burke & Hutchins, 2007; Weissbein, Huang, Ford & Schmidt, 2011). Basically, Baldwin and Ford’s (1988) model posited the need to examine transfer of training from various angles, namely training design, work environment and trainee’s characteristics in order to advance our general understanding regarding the issue. Despite progress has been made to expand our knowledge on transfer of training, the extant literature is characterized by vague and unexpected findings (Chiaburu & Tekleab, 2005; Blume et al., 2010; Pham et al., 2010). Additionally, there is a lack of research on the transfer of training in the context of developing nations. Subedi (2004), after reviewing the literature, concluded that “transfer of training, as a domain of concern for human performance, was not researched (thoroughly) before in the context of developing countries.” (p. 598). Consequently, there is a pressing need for more research in varying contexts to reach a mature understanding on the effect of social support on the transfer of training (Cheng & Ho, 2001; Al-Eisa, Furayyan & Alhemoud, 2009). One of the important work environment factors that can enhance transfer of training is supervisory support (Elangovan & Karakowsky, 1999; Merriam & Leahy, 2005). Although research on supervisory support often found promising results (e.g., Clarke, 2002; Chiaburu & Tekleab, 2005; Ng, Ahmad & Ismail, 2011), some studies (e.g., Awoniyi, Griego & Morgan, 2002; Chiaburu & Marinova, 2005; Nijman, Nijhof, Vognum & Veldkamp, 2006; Velada, Caetano, Michel, Lyons & Kavanagh, 2007) found mixed findings. Thus, further examination on the role of supervisory support in transfer of training is warranted. This is in line with the research calls (e.g., Colquitt, LePine & Noe, 2000; Burke & Hutchins, 2007; Cheng & Hampson, 2008) for more studies on supervisory support to clarify the relationships between the two variables. Surprisingly, to date, research on peer support is neglected (Bates, Holton, Seyler & Carvalho, 2000; Chiaburu, 2010; Van den Bossche, Segers & Jansen, 2010). According to Bates et al. (2000, p. 20), “researchers appear to have overlooked the possibility that there may be work situations in which co-worker support is equally or more important than that provided by supervisors.” Therefore, it is important to note that peer support has its own unique and significant contributions to the transfer of training (Facteau, Dobbins, Russell, Ladd & Kurdisch, 1995; Bates et al., 2000; Burke & Hutchins, 2007), which has confirmed by several studies (e.g., Chiaburu & Marinova, 2005; Hawley & Barnard, 2005; Chiaburu, 2010). The inconsistent findings of supervisory support and the lack of studies on peer support, especially in the developing countries, indicate that more research is needed to extend our understanding on how these variables interact with transfer of training in

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Studies in Business and Economics differential contexts. Hence, this study investigates the influences of supervisory and peer support on the transfer of training in the context of Malaysian workplace in order to clarify and broaden our knowledge on such relationships as well as to spur more research in this area. It contributes to the literature by adding and empirical evidence from the perspective of developing countries and provides sound guidance to the practitioners on how to enhance transfer of training. 2. Literature Review 2.1 Supervisory Support and Transfer of Training Supervisory support is often defined as the extent to which supervisors encourage employees to attend training and apply the training on the job (Facteau et al., 1995; Switzer, Nagy & Mullins, 2005). The burgeoning literature suggests that support emanating from the supervisors play an important function in promoting transfer of training (Baldwin & Ford, 1988; Elangovan & Karakowsky, 1999; Nikandrou, Brinia & Bereri, 2009). A recent meta-analytic review by Blume et al. (2010) involving 89 studies on training transfer found that supervisory and peer support have strong relationships with transfer of training. Further analysis confirmed that supervisor support had a stronger effect on the transfer of training than peer support. Colquitt et al. (2000), in their quantitative review on factors affecting training motivation and transfer outcomes based upon 106 articles published since 1975, found similar result. They posited that the extent to which supervisors provided sufficient support had robustly correlated with the employees’ ability to transfer what they learned on the job. The meta-analytic study was fully supported by other comprehensive reviews of training transfer literature (e.g., Elangovan & Karakowsky, 1999; Cheng & Ho, 2001; Merriam & Leahy, 2005; Burke & Hutchins, 2007). The ability of supervisors in encouraging employees to attend training and reinforcing the use of new learning in the workplace has been found significantly predict transfer of training. This was demonstrated by Ng et al. (2011), which found the ability of supervisors to allocate sufficient guidance and time to apply training resulted in positive transfer of training among 706 employees in the East Malaysian city-based local governments. Festner and Gruber’s (2008) study with 131 employees attended an occupational health and safety training program in Germany, found work environment factors (i.e., supervisory support, peer support, working conditions, and general workplace affordance) were strongly correlated with the degree to which employees’ apply KSA in the workplace. Supervisory support was found among the strongest factors in enhancing transfer of training. In their qualitative study, Lim and Johnson (2002) discovered that the salient work environment factors affecting transfer of training was supervisory support. More specifically, in their study involving 10 Korean human resource practitioners in performance improvement technology training program, the extent to which supervisors discussed the application of new learning, actively involved in the training

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Studies in Business and Economics program and provided positive feedbacks had improved employees’ ability to make use of new learning in the workplace. Consistently, Clarke (2002) examined factors that influenced the transfer of training in a human service agency and discovered the lack of supervisory support, in term of little or no feedback and the refusal of supervisors to sanction work practice changes, was a major hindrance to the transfer of training. Also, Xiao (1996) conducted a quantitative study on transfer of training based on a sample of 1023 women employees working in four electronic manufacturing companies located at Shenzhen, China. Through the analysis of survey results, the researcher discovered that support from supervisors was the most influential factor that correlated with transfer of training. In other words, they found the extent to which supervisors encouraged employees to apply what they have learned from training on the job significantly influenced employees’ degree of training transfer. In an early study by Tracey, Tannenbaum and Kavanagh (1995), they found support for the association between supervisory support and transfer of training. In their study that involved 505 supermarket managers, they found social support was the strongest predictor of transfer of training. Particularly, supervisor support in the form of encouragement of independent and innovative thinking was found to facilitate the managers’ ability to apply the supervisory skills learned from training back to the workplace. Likewise, Rouiller and Goldstein (1993) investigated about employees’ transfer behaviours learned from training to their job situations based on a sample of 102 managers from 102 fast-food franchises who attended a training program. Drawing on social learning theory, the researchers examined the concept of organisational transfer climate and whether it affects the degree to which employees transfer the learning on the job. This study found organizational transfer climate (i.e., supervisory support) affected the extent to which employees transfer what they have learned from training programs on the actual job. Other early studies found consistent findings (e.g., Mathieu, Tannenbaum & Salas, 1992; Brinkerhoff & Montesino, 1995). Hypothesis 1: Supervisory support significantly influences transfer of training. 2.2 Peer Support and Transfer of Training Peer support is generally understood as the co-workers’ encouragement to use new learning in the workplace (Bates et al., 2000; Van den Bossche et al., 2010). Support originating from peers has been found to exert a significant influence on employees’ ability to apply training in the workplace (Bates et al., 2000; Chiaburu, 2010). After comprehensively reviewed 170 studies on the predictors of the transfer of training, Burke and Hutchins (2007) concluded that peer support had more consistent relationship with transfer of training than supervisory support. This conclusion was supported by other similar qualitative reviews (e.g., Cheng & Ho, 2001; Merriam & Leahy, 2005). It implies there is a wide agreement on the importance of co-workers in supporting employees to apply training, despite the lack of studies in this area

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(Facteau et al., 1995; Bates et al., 2000; Chiaburu, 2010; Van den Bossche et al., 2010). Indeed, a number of empirical studies posited the central role of co-workers in elevating positive training transfer. For example, in the recent quantitative study by Chiaburu (2010), which involved 440 respondents from one organization in the United States, found that co-workers’ support was the strongest predictor of transfer of training and transfer maintenance. Statistical results demonstrated support from coworkers was more important that that coming from the organization and supervisors. It was believed that co-workers wielded a greater influence on transfer of training and training maintenance due to the proximal relationship with employees, as opposed to the organization and supervisors, which were more distal and diffused. Comparable findings were established by Chiaburu and Marinova (2005). After empirically tested the work environment factors and training transfer involving 186 employees from an organization, they found interesting results regarding the interactions between social support and transfer of training. Peer support appeared as a predictor of the transfer of training through pre-training motivation, whereas supervisory support had no association with transfer of training.
Another study by Bates et al. (2000) on 73 production operators in a chemical manufacturing company supported the notion of the importance of co-workers in transfer of training. Peer support appeared to explain a significant variance over and above of that explained by supervisory support. Although supervisory support was found significantly related to transfer, employees reported having a better transfer ability when they perceived their peers encouraged them to use new learning and discussed the ways to apply training on the job.

This is in keeping with the qualitative research by Hawley and Barnard (2005), who explored the effect of peer support on transfer of training among HRD professionals in the nuclear power industry. The outcomes of the research pinpointed networking with co-workers and knowledge-sharing about the training contents had assisted the employees to transfer skills six months after training. Based on a sample of 81 employees from 15 sister companies of a Korean conglomerate, Lim and Morris (2006) investigated the effects of employees’ characteristics, instructional satisfaction and organisational climate on perceived learning and transfer of training. The time-series-based repeated-measures study found peer support strongly correlated with transfer of training. The researchers concluded that organisational climate in term of co-workers encouragement to apply training and provision of feedbacks positively influenced employees’ ability to apply training on the job immediately and three months after training. In line with Lim and Morris’ (2006) study, Van den Bossche et al.’s (2010) study that based upon 35 academic employees in the Netherlands discovered co-workers’ support, in the form of feedback was indeed important in determining employees’ ability to apply what they learned on the job. Even though the hypothesis that maintained peer feedback has more effect on transfer of training than supervisory feedback was not confirmed, this study found the frequency and helpfulness of feedback emanating from co-workers significantly associated with motivation to transfer and transfer of training.

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Facteau et al. (1995), in their study examining the effect of social support on transfer of training, also found positive results. In their analysis with samples of 967 managers and supervisors involved in a management training program, it was revealed that peer support was positively related to perceived transfer of training. Supportive co-workers were found to exert a greater influence on employees’ perception on training transfer than supervisory support. Other empirical studies (e.g., Maurer, Mitchell & Barbeite, 2002) maintained similar findings.

Hypothesis 2: Peer support significantly influences transfer of training. 3. Conceptual Framework Based on the literature review, the conceptual framework was developed as shown in Figure 1: Figure 1: Conceptual framework

Supervisory support

Transfer of training

Peer support

4. Methodology 4.1 Location and Respondents

This study was conducted in one of the state health departments in Malaysia. A total of 100 employees working in the organization were targeted to take part in this study. Only 48 employees responded to the questionnaires, yielding a 48 percent response rate. Table 1 shows the respondents’ profiles. Majority or 66.7 percent of the respondents were female, 39.6 percent aged between 26 to 35 years old, 45.8 percent had a Bachelor’s degree and 37.5 percent had served in the organization for more than ten years.

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Table 1: Respondents’ profiles
Profile Gender Age Sub-Profile Male Female 16 - 25 26 - 35 36 - 45 46 - 55 > 56 LCE MCE STPM Diploma Bachelor’s Degree Master’s Degree < 1 year 1 - 5 years 6 - 10 years > 10 years Percentage 33.3 66.7 12.5 39.6 25 20.8 2.1 2.1 31.3 8.3 8.3 45.8 4.2 2.1 37.5 10.4 50

Educational level

Length of service

n = 48 LCE = Lower Certificate of Education MCE = Malaysian Certificate of Education STPM = Malaysian Higher School Certificate

4.2

Procedure

4.2.1 Stage 1: Discussion The purpose of the discussion was to ensure the measurement scales were understandable as well as relevant to the nature of supervisory and peer support practices in the studied organization. The author approached the human resource manager and one supervisor and engaged in face-to-face discussion to get their opinions regarding the self-report questionnaire. Overall, they agreed that the selfreport questionnaire was comprehensible, free from sensitive issues and reflected the nature of supervisory and peer support practices within the organization. 4.2.2 Stage 2: Pilot test At this stage, pilot test was conducted to ensure the research instrument was reliable for this study. Based on a simple random sampling method, a total of 20 respondents participated in the pilot study. Reliability analysis revealed the Cronbach’s alphas for the variables of interest exceeded .70 thresholds. 4.2.3 Stage 3: Actual survey The self-report questionnaires were randomly distributed to 100 respondents. The respondents were given seven days to answer the self-report questionnaire. Only 48 respondents completed and returned the self-report questionnaire. The data collected via the self-report questionnaire was used for hypotheses testing.

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4.3 Research Instrument Design In this study, self-report data collection was used to assess the variables under investigation. Self-report questionnaire is a suitable method for collecting data because employees are capable to accurately assess their own KSA not observable by their supervisor, peers or subordinates (Facteau et al., 1995; Chiaburu & Tekleab, 2005). The self-report questionnaire consisted of closed-ended questions both in English and Malay language. All items were assessed by using a five-point Likert-type scale (i.e., 1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, and 5 = strongly agree). Demographic background (i.e., gender, age, educational level and length of service) was collected from the respondents. The self-report questionnaire had three sections to measure the variables under investigation. 4.3.1 Supervisory support Supervisory support was measured by using the measurement scales adopted from Facteau et al. (1995), Xiao (1996), Bates et al. (2000) and Chiaburu and Tekleab (2005). A sample item was “My supervisor insures me about the opportunity to use the new skills in the workplace.” 4.3.2 Peer support Peer support was measured with the existing measurement scales adopted from Facteau et al. (1995) and Bates et al. (2000). A sample item was “My co-worker encourages me to apply what I have learned from the training program.” 4.3.3 Transfer of training Transfer of training was measured with the existing scales adopted from Facteau et al. (1995), Xiao (1996) and Chiaburu and Tekleab (2005). A sample item was “I am able to apply the new skills acquired from the training program on my job.” 4.4 Psychometric Properties of the Research Instrument The latest Statistical Package for the Social Sciences (SPSS) was used for all analyses. Psychometric analysis was conducted to measure the validity and reliability of the research instrument. Validity is the degree to which the self-report questionnaire measures the attribute to which it is supposed to measure (Easterby-Smith, Thorpe & Lowe, 2002; Sekaran, 2003; Cooper & Schindler, 2006; Fraenkel & Wallen, 2006). Factor analysis with Direct Oblimin rotation was used to test the validity of the selfreport questionnaire. The rationale of employing an oblique rotation technique in factor analysis is due to its capability to allow factors to be correlated with each other (Conway & Huffcutt, 2003). Costello and Osborne (2005) maintained that an oblique rotation is ideal in the social science because there is “...some correlation among factors, since behavior is rarely partitioned into neatly packaged units that function independently of one another.” (p. 3). In other words, an oblique rotation technique precisely reflects the

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Studies in Business and Economics complexity of the variables under investigation because in practical, constructs are usually correlated to each other (Conway & Huffcutt, 2003). The self-report questionnaire is valid if the factor loadings for the variables under investigation reached ± .40 thresholds (Hair, Black, Babin, Anderson & Tatham, 2006). Kaiser-Mayer-Olkin (KMO) test and Bartlett’s test of sphericity were conducted to ensure the adequacy of the sample size (Rasli, 2006). The sample is adequate if the value of the KMO is .60 (Coakes & Steed, 2003). On the other hand, Bartlett’s test of sphericity was used to check the intercorrelation between variables to ensure they were worthy of factor analysis (Child, 2006). Field (2000) maintained that Bartlett’s test of sphericity must be significant to determine the relationship between variables under investigation is not an identity matrix. Additionally, the rationale of conducting Cronbach’s alpha was to determine the reliability of the self-report questionnaire (Coakes & Steed, 2003). Since the self-report questionnaire contained interrelated items in measuring underlying constructs, it is crucial to determine whether or not the same set of questionnaire would elicit the same responses if the questionnaire is re-administered to the same respondents (Santos, 1999). The reliability of a questionnaire is acceptable if the alpha value is between .70 and above (Kline, 2000; Fraenkel & Wallen, 2006). Table 2 depicts the psychometric properties of the research instrument. First, validity analysis demonstrated supervisory support, peer support and transfer of training variables had the factor loadings of more than .40. Second, KMO and Bartlett’s test analyses revealed all the variables under investigation were more than the value of .60 and significant. Third, all variables under investigation had eigenvalue of 1.0. Lastly, reliability analysis demonstrated the Cronbach’s alpha for all variables under investigation were exceeded the value of 0.7. The results indicated that the research instrument employed in this study was valid and reliable (Kline, 2000; Hair et al., 2006). Table 2: Psychometric properties of the research instrument
Variables Supervisory support Item 1 2 3 4 5 6 7 1 2 3 4 5 6 1 2 3 1 -.15 .29 .23 -.08 .32 .25 .08 .79 .90 .74 .84 .86 .40 .00 -.03 .16 Factor 2 .39 .25 .14 .25 .04 -.18 -.37 .27 -.04 .12 .20 .05 -.08 .74 .83 .85 3 .65 .55 .59 .58 .70 .74 .61 .02 .20 .29 .13 .16 -.34 .02 .04 -.04

Peer support

Transfer of training

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4 Kaiser-Meyer-Olkin Bartlett’s Test of Sphericity Eigenvalue Variance Explained Cronbach’s Alpha .19 .72 66.15, p=0.000 2.49 62.19 .89 .46 .80 267.01, p=0.000 4.26 70.96 .78 .02 .77 143.09, p=0.000 3.56 50.78 .83

n = 48 5. Results 5.1 Construct Analysis

Table 3 reports the means, standard deviations and correlation coefficients of the variables under investigation. The Pearson correlation coefficients between the independent variables (i.e., supervisory and peer support) were less than .90, which indicated they were free from severe collinearity (Hair et al., 2006). Table 3: Means, standard deviations and correlations of the variables under investigation Variables Mean SD Pearson correlation 1 2 3 1 .54** 1 .39** .38** 1

Supervisory support 3.60 .63 Peer support 3.65 .77 Transfer of training 4.00 .53 n = 48 Correlation value ** is significant at the .01 level (2 tailed) 5.2 Result of Multiple Regression Analysis

The respondents’ demographic background served as a control variable, whereas supervisory and peer support as the independent variables. The relationship between supervisory and peer support had tolerance values of .61 and .59, respectively. On the other hand, the variance inflation factors (VIFs) for both independent variables were 1.64 and 1.68, respectively. The tolerance values were above .20 and the VIFs were less than 10.0, which indicated that the independent variables were free from multicollinearity (Tabachnick & Fidell, 2012). Table 4 demonstrates the result of the multiple regression analysis. The respondents’ demographic background was entered in step one, which revealed the length of service had a significant association with transfer of training (β = .41, p < .05). It had explained 12 percent of variance on the dependent variable. In step two, length of service remained significant (β = .48, p < .01). Supervisory support had no significant relationship with transfer of training (β = .18, p = .29), while peer support

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Studies in Business and Economics was found significantly and positively associated with the transfer of training (β = .37, p < .05). It had explained 35 percent of variance on the dependent variable. Table 4: Result of multiple regression analysis Variable Dependent Variable (Transfer of Training) Step 1 Step 2 Control Variables Gender .11 .17 Age -.32 -.27 Educational level .11 .19 Length of service .41* .48** Independent Variables Supervisory support .18 Peer support .37* 2 R .12 .35** 2 Adjusted R .04 .25** 2 R Change .12 .22** F 1.52 3.63** 2 F Change R 1.52 6.99** n = 48 Level of Significance = *p < .05; **p < .01 6. Discussion This study investigated the influences of supervisory and peer support on transfer of training in the context of the Malaysian workplace. The result of multiple regression analysis demonstrated mixed findings. That is, there was no significant association between supervisory support and transfer of training. However, peer support appeared to exert a significant and positive influence on transfer of training. The significant and positive relationship signified that as peer support increase, employees’ transfer of training will be elevated. Hence, hypothesis 1 (i.e., supervisory support significantly influences transfer of training) was rejected, whereas hypothesis 2 (i.e., peer support significantly influences transfer of training) was accepted. Contrary to expectation, there was no significant relationship between supervisory support and transfer of training. This finding contrasted the previous studies (e.g., Xiao, 1996; Lim & Johnson, 2002; Blume et al., 2010; Ng et al., 2011) that found significant association between supervisory support and transfer of training. Nevertheless, the finding supported a number of studies (e.g., Chiaburu & Marinova, 2005; Velada et al., 2007) that postulated insignificant correlation between supervisory support and transfer of training. One possible explanation for the insignificant relationship is that although supervisors had a close relationship with employees (Chiaburu & Tekleab, 2005), support emanating from them was characterized by

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Studies in Business and Economics inconsistency and intermittency. That is, support from supervisors was limited to before and after training, which was likely to weaken its influence on the employees’ ability to apply training on the job (Chiaburu, 2010). Additionally, peer support was found significantly and positively influenced transfer of training. This finding was in keeping with previous studies (e.g., Bates et al., 2000; Chiaburu & Marinova, 2005; Burke & Hutchins, 2007) that found similar results. Co-workers were believed to be more proximal than supervisory support and always in contact with other employees of similar status in the organization (Chiaburu, 2010). Therefore, support from the co-workers was much stronger than that of the supervisor due to “…the continuous flux of information and other critical resources originating laterally (from colleagues)” (Chiaburu, 2010, p. 53). 7. Theoretical and Practical Implications From a theoretical point of view, the findings of this study did not support the often suggested strong relationship between supervisory support and transfer of training. Also, the inconsistent findings imply the pressing need to identify the key components within supervisory support or other potential mechanisms that notably enhance the transfer of training. On the other hand, peer support exerted a stronger influence on transfer of training than supervisory support. This contradicted to the unambiguous endorsement from the literature that support emanating from supervisor is more important than that from co-workers. Indeed, this study clearly proves that coworkers play an important role in the transfer of training. Thus, it could spur more research on peer support for theoretical development of the existing training transfer model. From a practical standpoint, this study provides empirical evidence to practitioners regarding the importance of peer support in enhancing transfer of training in the organization. Practitioners are therefore should allocate more attention in designing strategies to improve peer support. Indeed, training programs aimed to enhance co-workers’ awareness and supportive skills may be introduced in the hope to create a supportive work environment that could improve transfer of training. 8. Limitations and directions for future research

This study has some methodological limitations. Firstly, under cross-sectional design, data collection on a one-time basis may limit our understanding on transfer of training, which occurs in varying period of times. Secondly, this study only measures employees’ perception towards transfer of training. Data collected from a single source might be affected by factors associated with social desirability. Thirdly, due to the low sample size, it is possible that the findings do not represent the population of this study. Finally, respondents are selected from one particular government department and thus, limit the generalizability of the results to other sectors.

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Future research should employ a longitudinal design that measures transfer of training in varying times. Also, future research should leave little room for a single source data collection and put more attention to design a data collection technique that utilizes multiple sources of data collection. The number of samples in future studies should be increased by involving different groups of employees from various departments to provide more representative results. Aside from that, future research ought to consider gathering data from multiple organizations to increase the generalizability of research findings. 9. Conclusion

The findings yield an inconsistent result in regard to supervisory support. The result implies that supervisory support is not always the case to increase transfer of training. Future works should identify the underlying elements of the supervisory support that have unique contributions to transfer of training. In contrast, this study found peer support significantly correlated with the level of training transfer. It contributes to the existing literature by providing important empirical evidence that supports the consistent relationship between peer support and transfer of training from a developing country’s perspective. Certainly, more research is needed to refine the existing training transfer model in order to reach a mature understanding on the transfer of training. Note: The author would like to thank Nur Fatihah Mat Yusoff for her guidance and contributions during the research phase. 10. References

Al-Eisa, A. S., Furayyan, M. A., Alhemoud, A. M. (2009), An empirical examination of the effects of self-efficacy, supervisor support and motivation to learn on transfer intention, Management Decision, Vol. 47, no. 8, pp. 1221-1244. Awoyini, E. A., Griego, O. V., Morgan, G. A. (2002), Person-environment fit and transfer of training, International Journal of Training and Development, Vol. 6 no. 1, pp. 25-35. Baldwin, T. T., Ford, J. K. (1988), Transfer of training: A review and directions for future research, Personnel Psychology, Vol. 41, no: 1, pp. 63-105. Bates, R. A., Holton, E. F. III, Seyler, D. L., Carvalho, M. A. (2000), The role of interpersonal factors in the application of computer-based training in an industrial setting, Human Resource Development International, Vol. 3, no. 1, pp. 19-42. Blume B. D., Ford, J. K., Baldwin, T. T., Huang, J. L. (2010), Transfer of training: A meta-analytic review, Journal of Management, Vol. 36, no. 4, pp. 1065-1105. Brinkerhoff, R. O., Montesino, M. U. (1995), Partnerships for training transfer: Lessons from a corporate study, Human Resource Development Quarterly, Vol. 6, no. 3, pp. 263-74. Burke, L. A., Hutchins, H. M. (2007), Training transfer: An integrative literature review and implications for future research, Human Resource Development Review, Vol. 6, no. 3, pp. 263-296.

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