Introduction

Organizations spend enormous amounts of funds on resources, particularly for training, to equip their employees with the necessary knowledge related to their professions to enhance their performance and productivity. Studies have shown that organizations make these investments to attain certain advantages and maintain a competitive edge in the global market (Elnaga & Imran, 2013; Khan et al., 2016). According to (Harward, 2014), the money invested on training is annually increasing. It was also stated that both North America and Europe represent around 75% of that expenditure. The increasing state of this expenditure confirms the importance of this investment and its favourable return in current industries. Transfer of training is specifically considered as a vital human resource practice that can benefit people, groups and organisations in terms of a positive job attitude among employees (Bhatti et al., 2013; Saks & Burke, 2012).

Despite the large amounts of investments, research has indicated that the return of investment is low. Only small amount of what has been learnt during training was reflected in the actual job (Kontoghiorghes, 2014). Other studies have indicated that the main obstacle for transfer of training is the low percentage that is being practised in actual jobs (Burke, 2001; Grossman & Salas, 2011). Furthermore, (Saks et al., 2014) claimed that there is a decline in using of newly learnt skills and attitude (KSA) immediately after training. This probably means that as time passes, trainees become incapable of remembering or using the information gained during training activities. This may indicate that time and money spent on training is ineffective and, therefore, not worthwhile.

Over the years, organisations have been trying their best to improve employee performance and increase their revenue through professional development (Salas et al., 2012). This effort will continue to work only if employees transfer the acquired skills and knowledge into practice during their work (Hutchins, Burke & Berthelsen, 2010). During previous years, extensive investigations have been made on the transfer of training from different perspectives. (Baldwin & Ford’s, 1988) model of transfer of training is the more widely tested model. Several comprehensive studies have used their model to examine the factors influence the training transfer. Moreover, this model has been validated in various studies and meta-analyses. However, researchers continue to suggest the need for further investigations to study the following factors: the features of trainees, the design of training and the environment of the work. These factors should be examined from different angles to understand the issue of training transfer (Blume et al., 2010; Alakrash, 2021). To address these concerns highlighted by previous researchers and bridge the gap in earlier models, this study focuses on the opportunity factor as a main factor in the AMO theory. Previous theories had not considered the opportunity to perform factor as main variable that affects training transfer. They only considered it as part of the work environment.

Transfer of Training

Transfer of training is defined as the process by which newly acquired Knowledge, Skills and Attitude (KSA) acquired as a consequence of training, are applied in the workplace, which can modify the employees’ behaviour (Baldwin & Ford, 1988; Grossman & Salas, 2011; Saks & Burke, 2012). Similarly, other authors (Tannenbaum & Yukl, 1992; Ford & Weissbein, 1997) have described transfer of training as the amount of Knowledge, skills and abilities acquired by employees at the workplace. Therefore, research indicates that transfer of training is significantly associated to the employee’s overall performance (Rouiller & Goldstein, 1993). This current study will explore the moderating effect of transfer climate on transfer of training with the application of AMO theory.

The AMO Theory

The AMO abbreviation stands for (A) ability, (M) motivation and (O) opportunity to perform or practice. All of them work together to enhance an employee’s performance (Kroon et al., 2013; Knies & Leisink, 2014; Claudia, 2015). This theory has been universally accepted for clarifying the relationship between HRM and performance since its development in the year 2000. Numerous articles have been published since then, extensively investigating the association between the AMO model and HRM performance (Ehrnrooth & Björkman, 2012; Marin-Garcia & Tomas, 2016). Many scholars have considered the AMO theory as an important tool that is both comprehensive and useful.

Ability Factor

Ability is the first factor in the AMO theory which is explained by many constructs: training & development, recruitment & selection and performance evaluation. It also dente to human characteristics (related knowledge, attitudes, experience, and skills). Ability in the AMO theory is defined as, “The acquired and natural capacity that enables an individual to perform a particular task successfully” (Kim et al., 2015). In the study, self-efficacy was a construct that represents the ability factor.

Self-Efficacy

Self-efficacy helps individuals decide on how much time and effort they need to finish a specific task and how confident they are in unfavourable situations. For instance, if individuals are confident and have high self-efficacy, they will more likely be included in training courses that are extra challenging (Baeten et al., 2010). Studying self-efficacy in different research areas shows its importance for ensuring confidence in the ability to perform specific tasks. Therefore, analysing the self-efficacy construct and its relationship with transfer of training is crucial and cannot be ignored in the field of research. Thus, the first hypothesis of this paper is as follows:

H1: There is a significant relationship between self-efficacy and transfer of training.

Motivation Factors

Motivation is considered as the second main factor in the AMO theory and is explained by many sub factors or components. These include extrinsic motivation (job security, recognition, pay-for-performance, expected rewards, internal promotion, etc.) and intrinsic motivation (motivation to learn, willingness to perform and collaborative climate). The motivation factor in the AMO theory is generally known as, “the degree to which an individual wants to choose to engage in certain specified behaviours” (Kim et al., 2015). In this paper, one motivational factor is highlighted: “motivation to transfer”.

Motivation to Transfer

Motivation to transfer is a critical indicator of training transfer in comparison to all other factors such as individual characteristics, organisational influences and work-design related aspects (Kauffeld et al., 2008). Scholars who studied transfer of training argued that there is a need to examine the impact of motivation and the various types of motivation that may influence transfer of training. It was further stated that it is important to study the different kinds of motivation (such as training motivation, motivation to learn and motivation to transfer) from various aspects along with their impact on transfer of training (Grossman & Salas, 2011). Therefore, this study investigates one type of motivation: the motivation to transfer. Thus, the second hypothesis of this paper is as follows:

H2: There is a significant relationship between motivation to transfer and transfer of training.

Opportunity to Transfer

Research reveals that skills and knowledge must be directly practised and implemented after a given training program. Trained employees forget what they have been taught within a short period (Salas et al., 2012). Gyimah (2015) revealed that transfer opportunity had no significant influence on transfer of training. This may be due to either a misunderstanding of the subject matter or that employees have not seen an opportunity for skills and knowledge transfer. Therefore, this paper hypothesises that:

H3: There is a significant relationship between opportunity to transfer has a with transfer of training.

Moderator (Transfer Climate)

Several definitions of transfer climate have been proposed by various scholars. Rouiller & Goldstein (1993) mentioned that transfer climate has been widely accepted by scholars in their research due to its relationship with the positive transfer of training. According to (Holton III & Bates, 2002), transfer climate is defined as the employees’ perception of the degree of support given by the organisational system that encourages them to share skills and knowledge among colleagues. Tracey & Tews (2005) defined transfer climate as the shared perception of workers regarding organisational procedures, activities and practices that are supported and rewarded.

From previous definitions, it appears that transfer climate is crucial for any organisation to improve individual performance at the workplace. Grossman & Salas (2011) stated that supportive transfer climate presence helps motivate employees in knowledge and skills learning towards the application in work setting. Blume, et al., (2010) considered climate of transfer as key variable in the workplace since it has a strong relationship with training transfer. Therefore, the present study defines transfer climate as the employees’ perception of their work system that is supported and rewarded, which will inspire them to share knowledge and skills they newly acquired with other colleagues at the workplace. Therefore, this paper hypothesises that:

H4: Transfer climate moderates the relationship between self-efficacy and transfer of training.

H5: Transfer climate moderates the relationship between motivation to transfer and transfer of training.

H6: Transfer climate moderates the relationship between the opportunity to transfer and transfer of training.

Methodology

A survey questionnaire was employed to collect the necessary data. The respondents of this paper were employees in Yemen Public Telecom Sector (YPTS). The target population was 4450 and the sample size, according to (Krejcie & Morgan, 1970), should be 351 employees. A systematic sampling design was selected from the target population. This is the best technique to be used since the list of employees is available. Therefore, employees will have equal chances of getting selected.

Questionnaire

The questionnaire survey was translated into Arabic for respondents’ better understanding and was validated by four language experts to ensure that survey questionnaire translation from English to Arabic is reliable and free of bias.

Pilot Test

A pilot test was carried out before it was used for data collection. This was conducted to test the reliability and validity of the construct since the scale was developed from previous sources and adjusted to suit the current study’s respondents.

Table 1 shows the summary of construct validity and reliability pilot test study.

Table 1 Summary of Construct Validity and Reliability Pilot Test Study (N=99)
Latent Variable	No of Indicator	AVE	Composite Reliability
Self-Efficacy (SE)	8	0.767	0.963
Motivation to Transfer (MT)	7	0.715	0.829
Opportunity to Transfer (OT)	7	0.782	0.749
Transfer Climate (TC)	15	0.821	0.970
Transfer of Training (TT)	6	0.651	0.882

The overall number of questionnaires distributed in the pilot test was equal to 150. Only 99 questionnaires were fully answered and returned. Both the internal consistency and discriminant validity were analysed using the Partial Least Square (PLS) with the application of the Structural Equation Modelling analysis (PLS-SEM) and the SPL 3.0 software (Ringle, Wende & Will, 2005). The coefficient of the composite reliability and the “Average Variance Extracted” (AVE) were calculated using the smart PLS algorithm. The appropriate “Average Variance Extracted” (AVE) should be greater than 0.7 (Hair et al., 2011) and the “Composite Reliability” (CR) supposed to be more than 0.5. The pilot study represents the AVE and CR coefficient, as presented in Table 3, where the AVE range is from 0.651–0.821 and the composite reliability range is between 0.749 and 0.963.

Measurement

This study has three independent variables (motivation to transfer and self-efficacy, transfer opportunity), one moderator “transfer climate” and one dependent variable “transfer of training”. A 5-point Likert scale with forty-three (43) items was developed from previous studies and modified to suit the aim of the study to ensure the validity of the items (Luarn & Lin, 2005). To scale the reliability and validity of the survey, the Cronbach’s Alpha should be 0.5 and above (Hair, Ringle & Sarstedt, 2013). The self-efficacy variable has (8) items with a Cronbach’s Alpha of 0.88, adapted from (Chen et al., 2001). For the second construct (motivation to transfer), the number of adapted items is (7) with a range of 0.83-0.95; as developed by (Khasawneh et al., 2004; Noe & Schmitt, 1986). The third construct (opportunity to transfer), has (7) items, as developed by (Ford et al., 1992), with a 0.74. The scale of the moderator variable (transfer climate), was adapted from (Tracey & Tews, 2005) and measured with (15) items and a Cronbach’s alpha of 0.74. The last scale, which is the dependent variable (transfer of training), has (6) items, developed by Xiao (1996), with 0.83.

The Technique of Data Analysis

C and cleaned from all missing data. This software is used to check the respondent’s profiles and various descriptive statistic items and outliers (Pallant, 2011).

Results

To obtain the results of the analysis, the structural equation model was assessed through the structural model “Inner Model” and the measurement model “Outer Model”.

To test the hypotheses, structural equation modelling was applied using the software “SmartPLS”. 3.0. The bootstrapping technique was utilised to test all direct and indirect effects of the variables (Shrout & Bolger, 2002)

Convergent Validity

Convergent validity is established when AVE values are greater than 0.5. Fornell & Larcker (1981) stated that when the variance of extracted values is greater than 0.5, the loadings are good and termed as effective for the study. However, when the variance is less than 0.5, the loadings are termed as ineffective for the study. Table 2 displays the measurement model results.

Table 2 Measurement Model Results (Convergent Validity)
Constructs	Items	Loadings	Alpha	CR	AVE
Self-Efficacy	SE1	0.835	0.944	0.951	0.710
	SE2	0.862
	SE3	0.849
	SE4	0.814
	SE5	0.869
	SE6	0.867
	SE7	0.851
	SE8	0.790
Motivation to Transfer	MT1	0.585	0.898	0.884	0.527
	MT2	0.751
	MT3	0.776
	MT4	0.689
	MT5	0.689
	MT6	0.798
	MT7	0.832
Opportunity to Transfer	OP2	0.652	0.881	0.890	0.622
	OP3	0.891
	OP4	0.715
	OP5	0.791
Transfer Climate	TC1	0.506	0.910	0.928	0.684
	TC2	0.905
	TC3	0927
	TC6	0.900
	TC7	0.514
	TC9	0.902
	TC11	0.508
	TC12	0.909
	TC13	0.925
	TC14	0.901
	TC15	0.508
Transfer of Training	TT1	0.857	0.852	0.900	0.693
	TT2	0.862
	TT3	0.782
	TT4	0.759
	TT5	0860
	TT6	0.835

It can be seen from Table 2 that all variables have high reliability and their AVEs are more than the required values. This confirms the reliability of the measurement model and proves that the internal consistencies are adequate (Hair et al., 2011).

Figure 1 shows that the R square value is 0.095, indicating that the variation caused in transfer of training is due to self-efficacy. Self-Efficacy has a 9.5% impact on Transfer of Training. Next, the figure shows that the R square value is -0.016, indicating that the variation caused in Training Transfer is due to Motivation to Transfer. Transfer Motivation was found to have -1.6% impact on Transfer of Training, which is a negative impact. It can be seen from the figure that the R square value is 0.782, indicating that the variation caused in Transfer of Training is due to Opportunity to Transfer. Opportunity to Transfer has a 78.2% impact on Transfer of Training.

Discriminant Validity

This was acquired by comparing correlation among the latent items with AVE square root, as proposed by Fornell & Larcker (1981). When the variables have an AVE value of more than 0.5, the discriminant validity results are considered satisfactory (Chin, 2000). (Table 3)

Table 3 Discriminant Validity Matrix Using Fornell And Larcker’s Criterion (Indicating Validity and Correlations Among Constructs)
Construct	MT	OT	SE	TC	TT
MT	0.726
OP	-0.156	0.789
SE	-0.118	0.378	0.842
TC	-0.148	0.422	0.541	0.800
TT	-0.155	0.835	0.412	0.419	0.827

Structural Model (Outer Model)

The nature of the effects between exogenous and endogenous variables differs between models, with and without the moderation effect (Hair et al., 2013).

Assessment of the Direct Relationship of the Structural Model

Table 4 presents the results of the hypotheses are shown in. The independent variables (Self-Efficacy and Opportunity to Transfer) have a positive relationship with Transfer of Training since their p-values were less than 0.05. This confirms that both Self-Efficacy and Opportunity to Transfer will have a direct impact on Transfer of Training. However, the independent variable (Motivation to Transfer) did not present a positive relationship with Transfer of Training since the p-value of this variable is more than 0.580.

Table 4 Results of Hypotheses Testing (Direct Effects)
Hypotheses	Relationships	Beta.	S.D.	T-value	P-values	Decision
H1	SE -> TT	0.111	0.041	2.669	0.008	Supported
H2	MT -> TT	-0.018	0.033	0.553	0.580	Not Supported
H4	OP-> TT	0.791	0.025	31.995	0.000	Supported

The t-values and their significance are illustrated in Table 4 and Figure 2. A hypothesis is accepted if the level of significance is below 0.05 and the t-value is more 1.64. However, if the level of significance is more than 0.05 and the t-value is more 1.64, the hypothesis was rejected and a null hypothesis is accepted. Here, we see that Self-Efficacy and Opportunity to Transfer both have the t-values >1.64 with a level of significance of less than 0.05. Therefore, our hypotheses of these two variables are accepted. There is a direct impact of Self-Efficacy on Training Transfer and direct impact of Transfer Opportunity on Training Transfer. The t-value of Motivation to Transfer is less than 1.64 and the level of significance is more than 0.05, therefore, our hypothesis cannot be accepted. No direct impact of Motivation to Transfer on Training Transfer was found.

Assessment of Variance Explained in the Endogenous Latent Variable (R-Square)

This study has one endogenous variable which is the R-square, as explained in Table 5.

Table 5 Variance Explained in the Endogenous Latent Variable (R-Square)
	R-Square		R-Square Adjusted
TT	0.71		0.706

Table 5 indicates that Motivation to Transfer, opportunity to Transfer, and Self-Efficacy, explains only 71% of variables.

Moderator Analysis

Hypothesis 4 stated that the climate transfer does not moderate the relationship among transfer of training and self-efficacy. The results in Table 6 (T-value=0.71, P-value>0.05) demonstrate that H4 is not supported. Hence, there is no moderation impact of transfer climate on the relationship among transfer of training and self-efficacy.

Table 6 Test of Moderation (Interaction Terms)
Hypotheses	Relationships	S.D	T-value	P-value	Decision
H4	SE*TC -> TT	0.072	0.71	0.478	Not Supported
H5	MT*TC -> TT	0.06	1.026	0.305	Not Supported
H6	OP*TC -> TT	0.038	2.363	0.019	Supported

Hypothesis 5 stated that the transfer climate does not moderate the relationship among transfer of training and motivation to transfer. The results in Table 6 (T-value=1.026, P-value>0.05) demonstrate that H5 is not supported. Hence, there is no moderation impact of transfer climate on the relationship among transfer of training and self-efficacy.

Hypothesis 6 stated that the transfer climate moderates the relationship among transfer of training and the opportunity to transfer. The results in Table 6 (T-value=2.363, P-value<0.05) demonstrate that H6 is supported. Hence, there is a moderation impact of transfer climate on the relationship among transfer of training and the opportunity to transfer.

Discussion

The aim of the study is to shed light on the significance of applying the factors of the AMO theory on training transfer by studying the relationship between various factors of the AMO theory (ability, motivation and opportunity) and transfer of training. The transfer climate was the moderator. The framework of this study has critical factors, which were applied on Yemen Public Telecom Sector and tested with the use of SmartPLS 3.0. The results of this study show the effect of each evaluated variable. There are three direct relationships: self-efficacy, transfer climate and opportunity to transfer. Self-efficacy is one factor that is expected to affect Yemen Public Telecom Sector’s transfer of training. The findings revealed a significant relationship among transfer of training and self-efficacy. Therefore, the hypothesis (H1) was accepted since it was shown that a significant relationship exists among transfer of training and self-efficacy. This finding is consistence with other research outcomes that determined a positive effect of transfer of training (Iswahyudi, Yohana & Mardi, 2019; De Rijdt et al., 2013). The empirical evidence indicates that the greater the self-efficacy, the higher the transfer of training.

The second factor “motivation to transfer” was expected to affect training transfer, however, interestingly, motivation to transfer was found to be negatively linked to transfer of training. Therefore, hypothesis (H2) was rejected, indicating that there is no relationship between Yemen Public Telecom Sector (YPTS) and transfer of training. After consulting with those in charge in YPTS, such as the general manager, the human resource manager and the training manager, two main reasons that may hinder the transfer of training were mentioned. The first reason is that the driving factors in the public telecom sector are centralised, controlled by the government system and subject to financial legislation. They are not connected to the performance of employees. The second reason is the lack of a comprehensive motivational method due to lack of interest.

The third and last direct relationship is opportunity to transfer. It is important to know that opportunity to transfer is considered to be the second most important component influencing the transfer of training (Lim & Johnson, 2002). The results of this study did show a significant association relationship between the opportunity to transfer and transfer of training. This finding agrees with the results of (Bates & Holton, 2004; Kirwan & Birchall, 2006) who suggested that transfer of training will only be effective and employees will be motivated if they are given the opportunity to transfer the newly learned training to the workplace. The findings of this paper further demonstrate that the transfer climate does not moderate the relationship between the independent variables (self-efficacy and motivation to transfer) with the dependent variable (transfer of training). Hence, hypotheses (H4) and (H5) were rejected. On the other hand, transfer climate does moderate the relationship between the opportunity to transfer and transfer of training. This finding is consistent with previous research which stated that when individuals are in a positive transfer climate, they are more likely to apply their newly learned skills at the workplace (Saks & Belcourt, 2006; Tracey, Tannenbaum & Kavanagh, 1995; Kontoghiorghes, 2001; Lim & Morris, 2006). Therefore, hypothesis (H6) was supported.

Conclusion

Transfer of training has been found to be a potential research area due to its significant importance in the industry. Companies and organisations are urged to establish a proper approach to sustain the process of transfer of training so as to attain certain benefits for their own good. Many models and frameworks have been created to organise transfer of training. This paper discussed the applied AMO theory on the transfer of training under three main criteria: ability, motivation and opportunity. The transfer climate was used as a moderator. The paper reviewed the gaps of the AMO theory when applied to transfer of training, provided a content analysis approach (represented by Tables 1 and 2) and proposed the suggested model. This model was analysed using Smart PLS 3.0. According to the results, this study highlights the opportunity for future research and findings. Future research should examine the relationship of the AMO theory and transfer of training with the moderation effect of transfer climate in another context. Moreover, the focus of this study was on an individual level. Other researchers can apply this study on an organisational level. This study was quantitative based and applied a cross-sectional survey. The questionnaires were all distributed at one time. Other researchers may conduct qualitative research to acquire new outcomes.

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