Social Support for Training Effectiveness: Mediating Training Transfer Motivation and Moderating Transfer Design

Abstract

Organizations invest in training and development to enhance their productivity. But, evidence proved the low effectiveness of the training because of the poor training transfer. Thus, training effectiveness is a permanent issue in developing human competencies and organizational performance. This study examined the effect of social support, that is, supervisor and peer support on training effectiveness, that is, training transfer, training maintenance, and training generalization with the moderated mediation effect of training transfer design and training transfer motivation. This study followed positivist epistemology on cross-section survey data collected from banking employees using multi-stage sampling. Hayes’s approach was used to test hypotheses. The findings of the study revealed a significant positive effect of social support on training effectiveness. Results revealed that peer support is vital in comparison to supervisory support to enhance training effectiveness. Training transfer motivation mediated the effect of peer support and transfer motivation predicting training effectiveness. The study concluded that optimal positive support from peers and supervisors is essential to enhance training effectiveness; the higher training transfer motivation of trainees further supports the relationship. This study emphasizes the significance of workplace factors to increase training transfer effectiveness, providing practical and theoretical implications.

Keywords

Training effectiveness training transfer peer support social support transfer motivation

Introduction

Technological advancement has significantly influenced the nature of jobs, which has increased the demand for effective trainings to enhance human competencies. Formal trainings help employees for innovative behaviour (Tan et al., 2023) and to cope with fast-changing job characteristics (Creon & Schermuly, 2022; Kraiger, 2014; Torraco & Lundgren, 2020). Trainees must transfer the skills and knowledge learned in training effectively to cope with changing demands of their jobs and to improve organizational performance (Gil et al., 2023; Tamsah et al., 2023). Training transfer effectiveness relies on many factors, for example, social support (Suleiman et al., 2017; Reinhold et al., 2018), supervisory support (Yaghi & Bates, 2020), transfer motivation (Arasanmi & Ojo, 2019; Gegenfurtner et al., 2022; De Jong et al., 2023; Massenberg et al., 2015; Yaghi & Bates, 2020), and training effectiveness (Arasanmi & Ojo, 2019) which ultimately influence training transfer effectiveness (Bell et al., 2017).

In this study, social support is considered as an organizational factor comprising supervisory support and peer support, which is expected to influence the trainees’ motivation and propensity to transfer training skills (Baldwin & Ford, 1988; Chiaburu & Tekleab, 2005; Scaduto et al., 2008; Schindler & Burkholder, 2016; Lauzier & Mercier, 2017; Reinhold et al., 2018; Suleiman et al., 2017) leading to training effectiveness (Arasanmi & Ojo, 2019; Reinhold et al., 2018; Schindler & Burkholder, 2016). Supervisory support is the degree to which trainees’ supervisors support and reinforce the application of training skills to the job (Arefin & Islam, 2018; Ghosh et al., 2015; Suleiman et al., 2017). Supervisory support includes support in goal-setting activities, mentoring, coaching, task support, setting the action plan for skills application, accommodating opportunities to discuss and share new skills with peers, monitoring and praising practical application of training skills effectively (Schindler & Burkholder, 2016; Smith-Jentsch et al., 2001). While, peer support is colleagues’ moral and physical assistance to implement the new skills learned via training (Grossman & Salas, 2011; Massenberg et al., 2015; Yaghi & Bates, 2020). In this way, social support develops congenial learning-working environment in the organization which helps in generation, generalization, and apply the training skills. Based on this notion, we examine the role of social support for training effectiveness (Yaghi & Bates, 2020).

Training effectiveness is a significant research issue in training and development (Baldwin & Ford, 1988; Bell et al., 2017; Mathieu et al., 1992). Many research studies (e.g., Charoensukmongkol et al., 2016; Grissom et al., 2012) revealed that training to employees is one of the most cost-effective strategies specially over hiring new employees. On the contrary, some studies (e.g., Chiaburu et al., 2010; Govindarajulu, 2009; Lacerenza et al., 2017) questioned the effectiveness of training programs because of the poor performance of trainees even after receiving several trainings due to failing to transfer training skills and knowledge at work. Training effectiveness, as suggested by Baldwin and Ford (1988), Chiaburu and Tekleab (2005), and Scaduto et al. (2008), in this study, incorporates a broad range of behavioural and job outcomes through training transfer (i.e., skills and knowledge gained through training transferred to the job responsibility), training maintenance (i.e., skills and knowledge learned through a training maintained or remained influential over the period), and training generalization (i.e., trained skills and expertise generalized or used to solve other different problems and in other different contexts). We argue that incorporating training maintenance and training generalization into the training transfer concept makes training effectiveness more comprehensive and impactful.

Besides the social support, individual characteristics (Chiaburu & Tekleab, 2005; Colquitt et al., 2000; Kossek et al., 1998; Noe & Schmitt, 1986; Singh, 2017) such as transfer motivation (Grohmann et al., 2014; Nikandrou et al., 2009; Seiberling & Kauffeld, 2017) and training transfer design (Bell et al., 2017; Bhatti & Kaur, 2010; Holton III et al., 2000; Lacerenza et al., 2017; Muduli & Raval, 2018; Nikandrou et al., 2009; Velada et al., 2007) can also influence the training effectiveness. Effective transfer design comprises a set of sample examples regarding how trainees apply the skills gained through training sessions to their actual job responsibilities. Transfer design supports in understanding, memorizing, and practically implementing skills though few studies (e.g., Muduli & Raval, 2018) reject the role of transfer design in training effectiveness.

This research incorporates social support at the workplace, and training transfer motivation as individual characteristics as antecedents of training effectiveness. It analyzed the direct effect of social support, integrating supervisory and peer support, on training effectiveness in the moderated mediation model incorporating mediating effect of transfer motivation and moderating effect of transfer design. To attain research objectives, we assimilated three factors (i.e., training transfer, training maintenance, and training generalization) to measure training effectiveness. This research, thus aims to answer three questions: (a) Does social support significantly influence the training effectiveness? (b) Is it possible having a significant mediating role of training motivation in the relationship between social support and training effectiveness? (c) Does the training transfer design influence role of social support and training motivation to predict transfer motivation? In search of answers to these questions, this research selected Nepalese banking sector which is relatively matured, transparent, accountable, and a group of listed public companies in Nepal. The Nepalese banking sector is characterized with a structured human resources management department for strategic integration of human resource practices with business strategy (Gautam, 2015). This research will be significant for banks in terms of the optimal use of training budgets (there is a mandatory provision for a minimum of 3% of staff expenses on training and capacity development in Nepalese banking industry as circulated by the Nepal Rastra Bank, regulatory central bank). In addition, this research contributes to conceptualizing an integrated theoretical model of training effectiveness incorporating supports, training transfer motivation, and training transfer design.

Theoretical Background, Review of Literature and Hypothesis Formulation

Different theories are developed to measure training effectiveness, such as expectancy theory (Vroom, 1964), organization support theory (1980), transfer of training model (Baldwin & Ford, 1988), Human Resource Development (HRD) evaluation research and measurement model (Holton III, 1996), and training motivation theory (Wolfe et al., 2019). This study conjectures the extent of social support employees receive for training skills transfer, maintaining skills, and generalizing them at work through the trainee-employees’ lens to examine training effectiveness.

This study studied training motivation and training effectiveness based on the general framework of Vroom’s valence-instrumentality-expectancy theory (Mathieu et al., 1992). Moreover, researchers choose social supports as antecedents of training motivation on the basis of their theoretical relevance to examine influence on training effectiveness (Chiaburu & Tekleab, 2005; Facteau et al., 1995; Mathieu et al., 1992; Reinhold et al., 2018; Scaduto et al., 2008). Employees require the support of supervisors and peers to have transfer motivation and realize a supportive workplace learning-transfer environment, which can be understood as the organizational support theory (Eisenberger et al., 2002; Islam & Ahmed, 2019; Zumrah & Boyle, 2015). In this notion, this study followed organizational support theory to develop a comprehensive conceptual model (refer to Figure 1) and to examine the training effectiveness.

Figure 1.

Conceptual Model.

Social Support and Training Effectiveness

Social support, a comprehension of the supervisor support and peer support is one of the vital factors in the learning transfer system (Massenberg et al., 2017). Social support for the employees significantly influences the transfer of skills (Chiaburu et al., 2010; Kim et al., 2019; Lauzier & Mercier, 2017; Massenberg et al., 2015; Scaduto et al., 2008; Velada et al., 2007). Peer support and supervisor support motivate trainees to apply learned skills (Bhatti et al., 2013; El-Said et al., 2020; Muduli & Raval, 2018) to their jobs which ensures the effectiveness of training. Social support provides intrinsic rewards to retain, maintain, and transfer the skills (Schindler & Burkholder, 2016) by increasing mastery goal orientation and enhancing self-efficacy (Chiaburu et al., 2010) to uplift the training transfer motivation (Kim et al., 2019). Based on these findings, we formulated the following hypothesis:

H₁: Social support has a significant positive effect on training effectiveness.

Social Support Influencing Training Transfer Motivation

Training transfer motivation is the willpower of trainees to transfer the skills learned in a training to their job responsibilities (Muduli & Raval, 2018). Social support enhances intentions to transfer the training skills to their jobs (Kim et al., 2019; Massenberg et al., 2015, Ng, 2017). Support from supervisors and peer workers increases the self-efficacy of trainees (Chiaburu et al., 2010; Yaghi & Bates, 2020) so that trainees’ willingness and confidence to apply the skills will be high. Based on such evidences, we formulated the following hypothesis:

H₂: Social support has a significant positive influence on training transfer motivation.

Training Transfer Motivation for Training Effectiveness

Strong willpower of the trainee to transfer skills is essential to implement the training skills, which influences the effectiveness of the training (Grohmann et al., 2014; Kodwani & Prashar, 2019; Seiberling & Kauffeld, 2017). It is the established fact that the strong motivation to transfer training skills leads to higher chances of training skill transfer (Nikandrou et al., 2009). A motivated trainee feels happy not only for the application of skills at work but also to share the ideas, concepts, and skills gained through training with associates at the workplace which increases chances of high training effectiveness. With this notion, we formulated the following hypothesis:

H₃: Training transfer motivation has a significant positive influence on training effectiveness.

Mediating Role of Training Transfer Motivation

In association with social support, training transfer motivation is expected to have positive influence on transfer effectiveness (Massenberg et al., 2015). Grohmann et al. (2014) established a mediational role of employees’ motivation to transfer in the relationship between training characteristics and transfer, supporting the findings of Gegenfurtner (2011), Scaduto et al. (2008) and Chiaburu and Tekleab (2005). As training transfer motivation is the consequence of social support and a predictor of training effectiveness, we hypothesized the mediation role of training transfer motivation as

H₄: Training transfer motivation mediates the relationship between social support and training effectiveness.

Moderating Role of Training Transfer Design

Training transfer design is the systematic and scientific approach to preparing training materials so that trainees understand the training contents easily, retain examples and contents of the training while working on their actual job, and they can excel at or develop the idea in solving actual problems. Effective training transfer design comprises effective instructions, illustrations, and applications of concepts and skills in the actual job context to link the learning with job performance (Muduli & Raval, 2018; Holton III et al., 2000). Thus, training transfer design and modality is crucial for the training effectiveness (Nikandrou et al., 2009; Bell et al., 2017; Lacerenza et al., 2017; Buonsenso et al., 2023; Tamsah et al., 2023). Training timing, content delivery, sequencing training materials, linking various issues and skills, presenting and encouraging participation, and ensuring post-training application limit the degree of training transfer (Tai, 2006; Velada et al., 2007). Various training interventions influence the creative and innovative work behaviour (Tan et al., 2023) of employees to lead for training effectiveness. The social support itself may not be sufficient to increase the training effectiveness directly, but the transfer design indirectly influences the training transfer effectiveness along with the social support (Boxall, 2012; Ha & Vanaphuti, 2022). Based on this notion, we hypothesized a moderating effect of training transfer design on the relationship between social support-training effectiveness and the social support-training motivation-training effectiveness relationship.

H_5a: Transfer design moderates the relationship between social support and training effectiveness.

H_5b: Transfer design moderates the social support-transfer motivations-training effectiveness relationship.

Research Design

Epistemology of the study. This study followed a positivist epistemology to investigate role of social support to predict the training effectiveness, as well as the mediation-moderation effect of training transfer motivation and transfer design.

Population and Sampling Approach

For the study, we opted a multi-stage sampling (in two stages: selecting banks and then the respondents) procedure for the sample selection. In the first stage, 15 commercial banks out of 27 banks in Nepal during the study period were chosen randomly using a lottery method. In the second stage, we made a list of employees trained at least two years back, and then prepared their cluster based on job positions (i.e., assistant-level employees, officer-level employees, and management-level employees). A total of 510 questionnaires were distributed to prospective respondents. To avoid the chance of common method biases, we collected data from respondents in two times: first time (T1) to rate the social support, training transfer design, and training transfer motivation, and one week later (Time 2, T2), to rate training effectiveness. Respondents were matched with the respondents ID. From each selected commercial bank, at least two managers, four officers, and six assistant employees were included in sampling process. A total of 456 responses were received at time 1 (T1) out of 510 approaches, while 393 were received at time 2 (T2). Thus, this study used a sample size of 393 out of the study population of 14,955 employees working in sample banks. This size is enough to have a 95% confidence level for the true value achieved from the sample, which provides evidence of sample adequacy according to Krejcie and Morgan (1970).

Instrumentation

Self-administered questionnaire with positively coded 5-point Likert items was administered with a scale value of 1 = Strongly disagree, 2 = Disagree, up to 5 = Strongly agree. The variables were referred from: Learning Transfer Survey Instrument (LTSI) (Holton III et al., 2000), training motivation variables (Noe & Schmitt, 1986), training transfer variables (Xiao, 1996), training maintenance (Gist et al., 1991) and training generalization (Tesluk et al., 1995). Referred instruments were tested for convergent and divergent validity with supervisory support (a = 0.91, six items), peer support (a = 0.83, four items), and transfer design (a = 0.85, four items) as reported by Bookter (1999) and Holton III et al. (2000). Likewise et al. (2008) examined reliability of Xiao’s (1996) scale for the transfer of training (a = 0.83, six items), training motivation (a = 0.79, eight items), and training maintenance (α = 0.86, eight items); Chiaburu and Tekleab (2005) reporting for training generalization (a = 0.80, three items). In addition to the two-stage data collection, to confirm the absence of common method bias, we tested single-factor approach as suggested by Harman’s (1967) and Podsakoff et al. (2003).

In this study, we confirmed reliability and validity using Structural Equation Modeling (SEM) and retained six items for supervisory support, four items for peer support, four items for transfer design, six items for training motivation, five items for training transfer, five items for training maintenance, and three items for training generalizations. The outcome variable, that is, training effectiveness, was measured in terms of three variables: training transfer, training maintenance, and training generalization, whereas social support was measured with two variables: supervisory support and peer support. We used Hayes model 15 to analyze the relationship under path models.

Results

Respondent characteristics. Out of 393 respondents, 56.49% were male respondents while 43.51% females; 54.45% were assistant level employees, 37.40% were officer level employees, and 8.14% were manager level employees; 17.8% were below 25 years of age, 70.5% were between 25 and 35 years of age, and only 11.7% were above 35 years.

Confirmatory factor analysis (CFA). We used CFA to test whether any item of the instrument loaded on the intended factor using maximum likelihood estimation. Statements with a minimum loading of 0.647 were retained (>0.50) in the model as per the suggestions of Hair, Black, Babin, and Anderson (2014) for the sample size of 350. We dropped five items—‘Increasing my skills through training has helped me to obtain a salary increase’ (from training motivation); ‘There are adequate equipment for me to apply new knowledge, skill, and ability gained through training on my job’ (from transfer training); ‘I have thought about how to maintain my skills that were strong’ (from training maintenance); ‘I have practiced skills learned with a partner’ (from training maintenance), and ‘I have monitored my progress in the use of skills’ (from training maintenance) because of low factor loading.

Results revealed a good fit with Chi-square (CMIN) (656.186, df = 471, p = .000), Goodness of Fit (GFI) (0.908), Normed Fit Index (NFI) (0.898), Incremental Fit Index (IFI) (0.969), Tucker Lewis Index (TLI) (0.965), Comparative Fit Index (CFI) (0.968), Parsimony-Adjusted Measures Index (PNFI) (0.801 > 0.1), The Root Mean Square Error of Approximation (RMSEA) (0.032) indicating the model fit as a minimum of three model-fit indices fitted well to determine the model fit as suggested by Hair et al. (2014) and Hayes (2019) (refer to Table 1).

Table 1 provides evidence of the fulfilment of the convergent validity concern of measurement instruments (Average Variance Extracted [AVE] > 0.50, Composite Reliability (CR) > 0.70, AVE > 0.50, and CR > AVE) as suggested by Fornnell and Larcker (1981), and Netemeyer et al. (2003) cited in Terglav et al. (2016). Similarly, the evidence provides fulfilment of the concern of discriminant validity (AVE > MSV) to have a good model fit.

Table 1.

Model-fit Indices and Validity Concern of the Instruments.

Model-fit Indices
CMIN	656.186	p = .000
GFI	0.908
NFI	0.898
IFI	0.969
TLI	0.965
CFI	0.968
RMSEA	0.032
Validity Concern
	CR	AVE	MSV	MaxR(H)	TT	SS	PS	TD	TM	TMa	TG
Training transfer (TT)	0.846	0.524	0.378	0.850	0.724
Supervisor support (SS)	0.887	0.566	0.297	0.890	0.105	0.753
Peer support (PS)	0.807	0.514	0.297	0.822	0.247	0.545	0.717
Transfer design (TD)	0.832	0.554	0.203	0.833	0.319	0.253	0.204	0.744
Training motivation (TM)	0.868	0.524	0.378	0.873	0.615	0.172	0.230	0.403	0.724
Training maintenance (TMa)	0.846	0.525	0.328	0.853	0.573	0.221	0.295	0.409	0.489	0.725
Training generalization (TG)	0.795	0.564	0.238	0.797	0.467	0.292	0.413	0.451	0.356	0.488	0.751
Variables and retained items after validity concern
Training transfer (TT): Five items
Supervisor support (SS): Six items
Peer support (PS): Four items
Transfer design (TD): Four items
Training motivation (TM): Six items
Training maintenance (TMa): Five items
Training generalization (TG): Three items

Source: Survey data.

Notes: CMIN, Chi-square; GFI, Goodness of Fit; NFI, Normed Fit Index; IFI, Incremental Fit Index; TLI, Tucker Lewis Index; CFI, Comparative Fit Index; RMSEA, The Root Mean Square Error of Approximation.

We used the dimension reduction approach with Extraction method and Varimax with the Kaiser Normalization Rotation method to determine factor loadings and variance explained by each factor (refer to Table 2). Results revealed that a total of 64.94% of the variance had been explained by the proposed model with seven factors.

Table 2.

Total Variance Explained by the Factors Retained After SEM.

Total Variance Explained
Component	Initial Eigenvalues	Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
Component	Total	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	8.506	8.506	25.775	25.775	4.03	12.213	12.213
2	4.222	4.222	12.793	38.568	3.714	11.254	23.467
3	2.162	2.162	6.552	45.12	3.16	9.575	33.042
4	2.128	2.128	6.447	51.567	3.141	9.519	42.56
5	1.688	1.688	5.115	56.682	2.711	8.217	50.777
6	1.462	1.462	4.431	61.113	2.594	7.861	58.638
7	1.264	1.264	3.831	64.945	2.081	6.307	64.945
Extraction Method: Principal Component Analysis.
Rotated Component Matrix (Rotation Converged in 6 Iterations)
Items	1	2	3	4	5	6	7
Supervisor support (3)	0.813
Supervisor support (2)	0.813
Supervisor support (1)	0.798
Supervisor support (5)	0.789
Supervisor support (4)	0.769
Supervisor support (6)	0.735
Training motivation (21)		0.785
Training motivation (8)		0.773
Training motivation (17)		0.755
Training motivation (16)		0.755
Training motivation (20)		0.700
Training motivation (15)		0.647
Training transfer (23)			0.750
Training transfer (24)			0.745
Training transfer (25)			0.733
Training transfer (22)			0.721
Training transfer (27)			0.661
Training maintenance (30)				0.779
Training maintenance (29)				0.757
Training maintenance (31)				0.739
Training maintenance (33)				0.692
Training maintenance (28)				0.684
Training design (13)					0.803
Training design (11)					0.791
Training design (12)					0.781
Training design (14)					0.735
Peer support (8)						0.799
Peer support (7)						0.768
Peer support (9)						0.725
Peer support (10)						0.658
Training generalization (37)							0.797
Training generalization (38)							0.770
Training generalization (36)							0.735

Source: Survey data.

Notes: Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

Table 3 presents the mean, standard deviation, and correlations. Each variable carries a mean greater than three (the cut-off value of three in five-point Likert scale with a positive statement) with a low standard deviation, which provides evidence of respondents’ aggregate agreement in the statements. Components of training effectiveness, that is, training transfer, training maintenance, and training generalization, were found to have statistically significant (p < .01) positive association with supervisor support and peer support, except for training transfer with supervisor support. The correlation results indicate that all the relationships are robust enough to test the proposed hypotheses based on the facts (refer to Table 3).

Table 3.

Means, Standard Deviations and Correlations of Supervisor Support (SS), Peer Support (PS), Transfer Design (TD), Training Motivation (TM), Training Transfer (TT), Training Maintenance (TMa) and Training Generalization (TG).

	Mean	SD	SS	PS	TD	TM	TT	TMa	TG
Training generalization (SS)	3.518	0.775	1
Peer support (PS)	3.849	0.661	0.459**	1
Transfer design (TD)	3.793	0.642	0.211**	0.167**	1
Training motivation (TM)	4.160	0.539	0.132**	0.147**	0.331**	1
Training transfer (TT)	4.068	0.532	0.089	0.201**	0.268**	0.508**	1
Training maintenance(TMa)	4.042	0.565	0.186**	0.230**	0.338**	0.409**	0.495**	1
Training generalization (TG)	3.886	0.644	0.244**	0.331**	0.368**	0.283**	0.372**	0.403**	1

Source: Survey data.

Note: **Correlation is significant at the 0.01 level (2-tailed). The bold value is non-significant at 0.01 level.

For a robust test, we used Process Macro 3.5 to examine the direct, mediating, and moderating relationships to test hypotheses as suggested by Hayes (2019).

Test of direct effects. Table 4 provides the immediate effect of social support in predicting training effectiveness. As social support was measured in terms of the supervisor’s support and peer support, whereas training effectiveness was measured in terms of training transfer, training maintenance, and training generalization. We examined six direct relationships among sub-components of social support and training effectiveness along with aggregate social support and aggregate training effectiveness. Similarly, conditional direct effects of training transfer design were observed.

Table 4.

Direct Effect of Components of Social Support on Training Effectiveness.

Effect on Endogenous Variables	Priori	Direct Effect (Path Coefficient)	P Value	t Value (Bootstrap)	Percentile 95% Confidence Interval
Outcome Variable: Training Motivation
Supervisor support (R² = 0.017)	+	0.092	.017	2.405	(0.017; 0.167) Sig.
Peer support (R² = 0.021)	+	0.119	.012	2.524	(0.026; 0.213) Sig.
Aggregate social support (R² = 0.026)	+	0.142	.006	2.786	(0.042; 0.243) Sig.
Outcome Variable: Training Transfer
Supervisor support (c') (R² = 0.288)	+	–0.001	.977	−0.029	(−0.067; 0.065) N sig.
Transfer motivation (b1)	+	0.425	.000	9.232	(0.335; 0.516) Sig.
Peer support (c') (R² = 0.295)	+	0.089	.041	3.995	(0.014; 0.193) Sig.
TM(b1)	+	0.42	.000	8.921	(0.327; 0.513) Sig.
Outcome Variable Training Maintenance
Supervisor support (c') (R² = 0.235)	+	0.067	.069	1.823	(−.005; 0.139) N sig.
Transfer motivation (b1)	+	0.307	.000	5.521	(0.198; 0.416) Sig.
Peer support (c') (R² = 0.246)	+	0.121	.001	3.209	(0.047; 0.196) Sig.
TM(b1)	+	0.3	.000	5.335	(0.189; 0.410) Sig.
Outcome Variable: Training Generalization
Supervisor support (c') (R² = 0.196)	+	0.131	.002	3.06	(0.047; 0.215) Sig.
Transfer motivation(b1)	+	0.201	.003	2.961	(0.068; 0.335) Sig.
Peer support (c') (R² = 0.233)	+	0.254	.000	4.254	(0.137; 0.372) Sig.
TM(b1)	+	0.181	.006	2.752	(0.052; 0.311) Sig.
Outcome Variable: Training Effectiveness
Overall social support (c') (R² = 0.371	+	0.145	.035	4.205	(0.077; 0.213) Sig.
TM (b1)	+	0.304	.04	7.598	(0.225; 0.383) Sig.
Moderation Effect of Training Design
Supervisor support →Training transfer		0.114	.015	2.442	(0.022; 0.205) Sig.
Peer support → Training transfer		0.084	.07	1.82	(−.007; 0.175) N sig.
Supervisor support → Training maintenance		0.186	.000	3.77	(0.089; 0.283) Sig.
Peer support → Training maintenance		0.183	.000	3.644	(0.084; 0.281) Sig.
Supervisor support → Training generalization		0.253	.000	3.951	(0.127; 0.379) Sig.
Peer support → Training generalization		0.262	.000	4.341	(0.143; 0.380) Sig.
Overall social support → Training effectiveness		0.168	.000	4.496	(0.095; 0.242) Sig.

Source: Survey data.

Note: SS: Supervisor support; PS: Peer support; TT: Training transfer; TMa: Training maintenance; TG: Training generalization; TM: Training motivation; TD: Training design; S_Sup: Social support (aggregate of supervisor support and peer support); TE: Training effectiveness (Aggregate of training transfer, training maintenance, and training generalization); Sig.: A significant direct effect at 0.05; N sig.: A non-significant direct effect at 0.05.

Results revealed positive significant predicting relationships between supervisory support (coefficient = 0.092, p < .05), peer support (coefficient = 0.119, p < .05), and aggregate social support (coefficient = 0.142, p < .05) to the training motivation. Result also supported a significant relationship between supervisory support and training generalization (coefficient = 0.131, p < .05), and an insignificant relationship between supervisory support with training transfer (coefficient = − 0.001, p > .05) and training maintenance (coefficient = 0.067, p > .05). In contrast to the supervisory support, peer support revealed a significant relationship with training transfer (coefficient = 0.089, p < .05), training maintenance (coefficient = 0.121, p < .05) and training generalization (coefficient = 0.254, p < .05).

The result revealed that the aggregate social support is a significant predictor of training effectiveness (coefficient = 0.145, p < .05). This result provided to support the hypothesis H₁, that is, social support has a significant positive influence on training effectiveness.

The results also revealed that the training transfer motivation was a significant positive predictor of training transfer (coefficient = 0.425, p < .05), training maintenance (coefficient = 0.307, p < .05), and training generalization (coefficient = 0.201, p < .05) and overall training effectiveness (coefficient = 0.304, p < .05). These findings provided sufficient condition to examine the mediating effect of training transfer motivation.

Test of indirect effects. Table 5 provides evidence of existence of an indirect effect in predicting training effectiveness by social support, noted that mediated relations were examined for ±SD.

Table 5.

Indirect Effects of Components of Social Support on Training Effectiveness.

Indirect Effects (TD as Moderator)	±SD	Index of Moderated Mediation	Percentile Confidence-interval	Significance
Supervisor Support → Transfer Motivation → Training Transfer
Mediation	−0.642	0.048	(0.010; 0.094)	Sig.
	0	0.039	(0.008; 0.074)	Sig.
	0.642	0.03	(0.006; 0.057)	Sig.
Moderated mediation		−0.014	(−0.035; −0.001)	Sig.
Supervisor Support → Transfer Motivation → Training Maintenance
Mediation	−0.642	0.037	(0.007; 0.074)	Sig.
	0	0.028	(0.006; 0.056)	Sig.
	0.642	0.02	(0.003; 0.043)	Sig.
Moderated mediation		−0.013	(−0.036; 0.002)	N Sig.
Supervisor Support → Transfer Motivation → Training Generalization
Mediation	−0.642	0.019	(0.001; 0.048)	Sig.
	0	0.018	(0.002; 0.043)	Sig.
	0.642	0.018	(0.000; 0.047)	Sig.
Moderated mediation		−0.001	(−0.021; 0.020)	N Sig.
Peer Support → Transfer Motivation → Training Transfer
Mediation	−0.642	0.061	(0.015; 0.109)	Sig.
	0	0.05	(0.012; 0.090)	Sig.
	0.642	0.017	(0.010; 0.076)	Sig.
Moderated mediation		−0.016	(−0.039; 0.000)	N Sig.
Peer Support → Transfer Motivation → Training Maintenance
Mediation	−0.642	0.046	(0.010; 0.092)	Sig.
	0	0.036	(0.009; 0.069)	Sig.
	0.642	0.013	(0.003; 0.055)	Sig.
Moderated mediation		−0.017	(−0.046; 0.004)	N Sig.
Peer Support → Transfer Motivation → Training Generalization
Mediation	−0.642	0.023	(0.001; 0.060)	Sig.
	0	0.022	(0.003; 0.053)	Sig.
	0.642	0.02	(−0.001; 0.057)	N Sig.
Moderated mediation		−0.002	(−0.028; 0.026)	N Sig.
Aggregate Social Support → Transfer Motivation → Training Effectiveness
Mediation	−0.642	0.052	(0.014; 0.098)	Sig.
	0	0.043	(0.013; 0.080)	Sig.
	0.642	0.035	(0.010; 0.067)	Sig.
Moderated mediation		−0.013	(−0.038; 0.004)	N Sig.

Source: Survey data.

Result revealed a significant mediation effect of training transfer motivation in the relationship between supervisor support and training transfer, supervisor support and training maintenance, and supervisor support and training generalization. Similarly, training transfer motivation mediated the relationship between peer support and training transfer, peer support and training maintenance, and peer support and training generalization. Training transfer motivation also significantly mediated the relationship between overall social support and training effectiveness (SD = −0.642, confidence interval = 0.014–0.098; SD = 0, confidence interval = 0.013–0.080; SD = 0.642, confidence interval = 0.010–0.067). These findings supported hypotheses H₂, H₃ and H₄. But, the proposed hypothesis for moderated mediation effect of training transfer design and training transfer motivation in a relationship was subject to refute (coefficient = −0.013, confidence interval −0.038–0.004).

Discussion of Findings

The mean values of 3.518 for transfer of training, 4.042 for training maintenance, and 3.886 for generalization of training indicate that employees transfer, maintain, and use the skills gained through trainings, with the mean satisfaction score on aggregate training effectiveness (3.998) indicating the perceived effectiveness of the training.

The significant positive coefficients indicate that dimensions of social support, that is, supervisor support and peer support, enhance the training effectiveness, that is, training transfer, training maintenance, and training generalization, as supported by the previous studies (e.g., Bhatti et al., 2014; Hughes et al., 2020; Islam & Ahmed, 2019; Reinhold et al., 2018; Xiao, 1996; Yaghi & Bates, 2020) though these findings contradict with few of the previous findings (e.g., Devos et al., 2007; Velada et al. 2007). Peer support is found to be more influential in training transfer in comparison to supervisory support which is similar with the findings of Yaghi and Bates (2020). As many studies (e.g., Chiaburu & Marinova, 2005; Facteau et al., 1995; Ng, 2013; Velada et al., 2007), this study also revealed that the supervisory support is not significant for predicting the training transfer, though the social support is found to be significant positive predictor of the overall effectiveness of the training. Thus, this result suggests that supervisors should be more effective in increasing training effectiveness through active involvement and accountability (Govaerts et al., 2017) along with maintaining good peer support system at the workplace.

In aggregate, social support is found to be a strong predictor of training effectiveness, which supports the argument that organizations need to focus on encouraging supervisors, initiating necessary arrangements for training skills implementation through the working environment, and establishing a rewarding culture for the best performers. The results of the study suggest supervisors consult trained employees for new ways of doing things and help them attain their performance goals. Supervisors need to create events to encourage trained employees to share their ideas with peers. Trained employees should get opportunities to participate in solving problems. Supervisors ensure trained employee support to strengthen emotional stability, initiate creating a creative working environment, and practice acknowledging the best practices and initiatives of employees so that they will be motivated to implement the training skills.

The result suggests that peer support is the strongest predictor of training effectiveness. This result argues for maintaining a peer-supportive working environment as reported by previous studies (e.g., Bates et al., 2012; Islam & Ahmed, 2019; Yaghi & Bates, 2020). The result revealed that peer support is dominant in Nepalese banking organizations for the transfer, maintenance, and generalization of the skills learned through training (Bhatti & Kaur, 2010; Hughes et al., 2020), which helps to maintain a supportive working environment. Peers, that is, coworkers, are the immediate persons to encourage or discourage for initiating new approaches for doing the same after the training. Encouraging colleagues will be like a catalyst in the application of training skills, and generalizing these skills for other jobs, and even developing creative ideas. Peer supports not only recognize and appreciate the job outcomes but also observe, notice, and alarm for potential wrong results. Thus, the supportive working environment maintained among the peers motivates them to implement and transfer the training skills effectively.

Training transfer motivation as a psychological alignment for maximum use of skills learned from the training is found to be a strong predictor of training transfer, training maintenance, and skill generalization, as supported by previous studies (Bhatti et al., 2014; Gautam & Basnet, 2021; Hughes et al., 2020). Each employee expects to attain career goals at the earliest possible time and believes that their performance can materialize the goals. Though it is an individual factor, the supervisors need to develop a trust in personal development through performance, so the employees’ motivation to transfer the training skills will be high. Supervisors need to create a supportive working environment so that each trained employee will intend to share new ideas, principles, and practices suggested in training with their colleagues. This study emphasizes on physical setting and supporting work culture to increase the training transfer motivation of trainee employees.

Likewise, the study revealed a significant mediation effect of training transfer motivation in the relationship between aggregate social support and training effectiveness, supporting H₄. This study supports the conceptualized models for training outcomes mediating with training transfer motivation for predicting training effectiveness supporting the findings of several previous studies (e.g., Bhatti et al., 2014; Chiaburu & Tekleab, 2005; Hughes et al., 2020; Reinhold et al., 2018; Scaduto et al., 2008; Yaghi & Bates, 2020).

The study established a moderating effect of training design in all the direct relationships, that is, supervisor support—training transfer, supervisor support—training maintenance, supervisor support—training generalization, peer support—training maintenance, peer support—training generalization, aggregate social support—training effectiveness, except in the relationship between peer support—training transfer. This evidence supports accepting H_5a. Interestingly, if peer support is significant for training transfer, training design has no significant effect on training transfer, meaning that peer support is vital for effective training transfer. Peer support consists of assisting in job accomplishment or offering positive feedback (Hawley & Barnard, 2005) for implementing training skills. This situation encourages employees to be more effective in utilizing learned skills. This result justified the significance of the peer role in increasing training effectiveness.

But, results disregarded the moderating effect of training design on training effectiveness in the presence of effective social support and transfer motivation, failing to accept H_5b. This result promotes a more significant role for training transfer motivation compared to the training transfer design to increase training effectiveness. Motivated trainees who transfer training skills can be more effective, meaning that trainee motivation should be systematic and adequate. Training, if it can be linked to personal growth, can increase employees’ motivation to transfer skills. Further, the training transfer motivation of employees can be improved through strong social support through organizational procedures and policies (Chauhan et al., 2017; Chiaburu & Marinova, 2005), and systematic selection of trainees to participate in the training (Mathieu et al., 1992).

Conclusion

Based on the discussion of the findings, it is concluded that the training effectiveness can be improved through effective social support to the trainee employees. Social support for trainee employees can be increased through supervisors’ and peers’ support to participate in training, retain and maintain training skills, and transfer the skills to job responsibilities. Supervisors should create and maintain supportive working environments so that trainee employees will be motivated to gain and apply skills gained through training. Supervisors should also encourage non-trained employees to cooperate and coordinate with trained employees to implement their skills, create new ideas to solve existing problems with a new approach and assist in their initiation. A supportive working environment can be strengthened by maintaining acknowledgment and rewarding the continuous efforts of employees in implementing their training skills. Organizational social support should be effective for training transfer motivation, skill maintenance, and skill generalization. This study provides a significant concept that the training transfer design plays vital role to attain the training effectiveness, especially in the absence of effective social support. Finally, this study concludes that a comprehensive model comprising social support, trainee motivation for training transfer, and training transfer design is essential to enhance the training effectiveness.

Implications of the Study

Training cost per employee per year has been increasing significantly to improve the impact on organizational performance (Renaud & Morin, 2019) and corporate sustainability, but the results are not much more hopeful until the trained employees transfer their skills into their jobs. The conclusion of this study facilitates commercial banks to maximize training effectiveness by maintaining social support so transfer motivation can be enhanced. The results indicate that training transfer is more important to maximize training effectiveness through social support. Social support should increase peer support that should be strong and reliable for increasing training transfer, training maintenance, and training generalization. This study suggests supervisors should maintain a culture of encouragement and appreciation, and express their expectations for implementing skills learned from the training.

Results also support the essence of supervisors’ strong desire to involve trainees in problem-solving purposes after getting the training, encourage new performance goals, and provide timely and accurate feedback on their performance. Thus, supervisors and managers should evaluate performance, provide timely and adequate feedback, and involve trainee employees in the decision-making process. Improving social support at the workplace enhances the trainees’ self-efficacy and forces trainees to be more committed through mastery goal orientation.

This study also suggests that organizations should develop policies and strategies to increase employee motivation for training to improve training effectiveness. This study suggests that when designing training programs, organizations should be careful with the training content, and the post-training work environment should ensure an organizational climate of support.

Limitations and Scope for Future Research

This study was conducted in the social context of commercial banks in Nepal. The commercial banks in Nepal have a mandatory provision of a training budget of 3% of the personal expenses, that is, salary and incentives. Thus, the research design, social support, training transfer and training effectiveness may differ in another field (e.g., trading, manufacturing, and educational sector) where the training is not mandatory provision by regulatory bodies. Further research in another field than in the banking industry may have different findings, which creates a contextual gap for future research.

In this study, the training design remained non-significant in the moderation mediation model though it was found to be a significant moderator in the direct relations. Further research with extended dimensions of research design is suggested to confirm the findings of this research.

Further, this study result is based on cross-section data with the respondents who were trained at least two years back to the survey date (no systematic training-focused performance appraisal was found), which may deviate from the actual progress in training effectiveness. Further researchers are suggested to have a longitudinal research design.

Footnotes

Acknowledgements

We acknowledge the respondents for their sincere responses to each of the statements on the questionnaire. We equally acknowledge the continuous encouragement of Tribhuvan University, Nepal.

Authors’ Responsibility

The first author was entirely responsible for data analysis, interpretation and finalizing the draft; the second author conceptualized the research, research design and final approval, and the third author was responsible for conceptualizing, review of literature, and data collection. In addition, all authors were equally accountable for the literature survey and proofreading.

Declaration of Conflict of Interest

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

References

Arasanmi

C. N.

, & Ojo

A. O.

(2019). Social support, computer self-efficacy, transfer motivation and ERP training transfer. International Journal of Enterprise Information Systems, 15(2), 1–14. https//doi.org/10.4018/IJEIS.2019040101

Arefin

M. S.

, & Islam

(2018). A study on the motivation to transfer training in the Banking Industry of Bangladesh. South Asian Journal of Human Resource Management, 6(1), 45–72.

Baldwin

T. T.

, & Ford

J. K.

(1988). Transfer of training: A review and directions for future research. Personnel Psychology, 41(1), 63–105.

Bates

, Holton

E. F.

, & Hatala

J. P.

(2012). A revised learning transfer system inventory: Factorial application and validation. Human Resource Development International, 15(6), 549–569. 10.1080/13678868.2012.726872

Bell

B. S.

, Tannenbaum

S. I.

, Ford

J. K.

, Noe

R. A.

, & Kraiger

(2017). 100 years of training and development research: What we know and where we should go. Journal of Applied Psychology, 102(3), 305–323.

Bhatti

A. M.

, Ali

, Isa

M. F. M.

, & Battour

(2014). Training transfer and transfer motivation: The influence of individual, environmental, situational, training design, and affective reaction factors. Performance Improvement Quarterly, 27(1), 51–82. 10.1002/piq.21165

Bhatti

M. A.

, & Kaur

(2010). The role of individual and training design factors on training transfer. Journal of European Industrial Training, 34(7), 656–672.

Bhatti

M. A.

, Battour

M. M.

, Sundram

V. P.

, & Othman

A. A.

(2013). Transfer of training: does it truly happen? European Journal of Training and Development, 37(3), 273–297.

Bookter

A. I.

(1999). Convergent and divergent validity of the learning transfer questionnaire [Unpublished doctoral dissertation]. Louisiana State University.

10.

Boxall

(2012). High-performance work systems: What, why, how and for whom? Asia Pacific Journal of Human Resources, 50(2), 169–186.

11.

Buonsenso

, Centorbi

, Iuliano

, Di Martino

, Della Valle

, Fiorilli

, Calcagno

, & di Cagno

(2023). A systematic review of flywheel training effectiveness and application on sport specific performances. MDPI Sports, 11, 76. 10.3390/sports11040076

12.

Charoensukmongkol

, Moqbel

, Gutierrez-Wirsching

, & Shankar

(2016). The role of coworker and supervisor support on job burnout and job satisfaction. Journal of Advances in Management Research, 13(1), 4–22.

13.

Chauhan

, Ghosh

, Rai

, & Kapoor

(2017). Improving transfer of training with transfer design: Does supervisor support moderate the relationship? Journal of Workplace Learning, 29(4), 268–285.

14.

Chiaburu

D. S.

, & Marinova

S. V.

(2005). What predicts skill transfer? An exploratory study of goal orientation, training self-efficacy and organizational supports. International Journal of Training and Development, 9(2), 110–123.

15.

Chiaburu

D. S.

, & Tekleab

A. G.

(2005). Individual and contextual influences on multiple dimensions of training effectiveness. Journal of European Industrial Training, 29(8), 604–626.

16.

Chiaburu

D. S.

, Dam

K. V.

, & Hutchins

H. M.

(2010). Social support in the workplace and training transfer: A longitudinal analysis. International Journal of Selection and Assessment, 18(2), 187–200.

17.

Clark

C. S.

, Dobbins

G. H.

, & Ladd

R. T.

(1993). Exploratory field study of training motivation: Influence of involvement, credibility, and transfer climate. Group and Organizational Management, 18(3), 292–307.

18.

Colquitt

J. A.

, LePine

J. A.

, & Noe

R. A.

(2000). Towards an integrative theory of transfer motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied Psychology, 85(3), 679–707.

19.

Creon

L. E.

, & Schermuly

C. C.

(2022). A new path to training transfer: Transformational trainers and psychologically empowered training participants. International Journal of Training and Development, 26(2), 228–244. 10.1111/ijtd.12256

20.

De Jong

, Jansen in de Wal

, Cornelissen

, Lans

R. Van der

., & Peetsma

(2023). How to predict transfer of training? Investigating the application of the unified model of task-specific motivation. International Journal of Training and Development, 27(2), 242–262. 10.1111/ijtd.12297

21.

Devos

, Dumay

, Bonami

, Bates

, & Holton III

(2007). The learning transfer system inventory (LTSI) translated into French: Internal structure and predictive validity. International Journal of Training and Development, 11(30), 181–199.

22.

Eisenberger

, Stinglhamber

, Vandenberghe

, Sucharski

I. L.

, & Rhoades

(2002). Perceived supervisor support: Contributions to perceived organizational support and employee retention. Journal of applied psychology, 87(3), 10.1177/0149206315575554

23.

El-Said

O. A.

, Hajri

B. A.

, & Smith

(2020). An empirical examination of the antecedents of training transfer in hotels: The moderating role of supervisor support. International Journal of Contemporary Hospitality Management, 32(11), 3391–3417.

24.

Facteau

J. D.

, Dobbins

G. H.

, Russell

J. E. A.

, Ladd

R. T.

, & Kudisch

J. D.

(1995). The influence of general perceptions of the training environment on pretraining motivation and perceived training transfer. Journal of Management, 21(1), 1–25.

25.

Fornnell

, & Larcker

D. F.

(1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39–50.

26.

Gautam

D. K.

(2015). Strategic integration of HRM for organizational performance: Nepalese reality. South Asian Journal of Global Business Research, 4(1), 110–128.

27.

Gautam

D. K.

, & Basnet

(2021). Organizational culture for training transfer: the mediating role of motivation. International Journal of Organizational Analysis, 29(3), 69–787. 10.1108/IJOA-04-2020-2147

28.

Gegenfurtner

(2011). Motivation and transfer in professional training: A meta-analysis of the moderating effects of knowledge type, instruction, and assessment conditions. Educational Research Review, 6, 153–168.

29.

Gegenfurtner

, & Quesada-Pallarès

(2022). Toward a multidimensional conceptualization of motivation to transfer training: Validation of the transfer motivation questionnaire from a self-determination theory perspective using bifactor-ESEM. Studies in Educational Evaluation, 73, 101116. 10.1016/j.stueduc.2021.101116

30.

Ghosh

, Chauhan

, & Rai

(2015). Supervisor support in transfer of training: Looking back at the past. Industrial and Commercial Training, 47(4), 201–207.

31.

Gil

A. J.

, Rodriguez-Cavides

, & Romero-Daza

(2023). Analysis of training effectiveness from the perspective of managers and employees in the Colombian hospitality industry. Industrial and Commercial Training, 55(3), 346–354. 10.1108/ICT-11-2022-0085

32.

Gist

M. E.

, Stevens

C. K.

, & Bavetta

A. G.

(1991). Effects of self-efficacy and post-training interventions on the acquisition and maintenance of complex interpersonal skills. Personal Psychology, 44(6), 837–861.

33.

Govaerts

, Kyndt

, & Dochy

(2017). The influence of specific supervisor support types on transfer of training: examining the mediating effect of training retention. Vocations and Learning, 11(2), 265–288. 10.1007/s12186-017-9190-y

34.

Govindarajulu

(2009). Transfer climate in end-user computing: The influence of trainee characteristics and supervisory support. Journal of Advances in Management Research, 6(1), 87–98.

35.

Grissom

J. A.

, Nicholson-Crotty

, & Keiser

(2012). Does my boss’s gender matter? Explaining job satisfaction and employee turnover in the public sector. Journal of Public Administration Research and Theory, 22(4), 649–673.

36.

Grohmann

, Beller

, & Kauffeld

(2014). Exploring the critical role of motivation to transfer in the training transfer process. International Journal of Training and Development, 18(2), 84–103.

37.

Grossman

, & Salas

(2011). The transfer of training: what really matters. International Journal of Training and Development, 15(3), 103–120.

38.

, & Vanaphuti

(2022). Training transfer to the workplace: A study of corporate English language training in hospitals. Journal of Workplace Learning, 34(1), 110–131. 10.1108/JWL-08-2020-0132

39.

Hair

J. F.

, Black

W. C.

, Babin

B. J.

, & Anderson

R. E.

(2014). Multivariate data analysis (7th ed.). Pearson Education.

40.

Harman

H. H.

(1967). Modern factor analysis. University of Chicago Press.

41.

Hawley

J. D.

, & Barnard

J. K.

(2005). Work environment characteristics and implications for training transfer: A case study of the nuclear power industry. Human Resource Development International, 8(1), 65–80.

42.

Hayes

A. F.

(2019). Introduction to mediation, moderation, and conditional process analysis: A regress-based approach. The Guilford Press.

43.

Holton III

E. F.

(1996). The flawed four-level evaluation model. Human Resources Development Quarterly, 7(1), 5–21.

44.

Holton III

E. F.

, Bates

R. A.

, & Ruona

W. E.

(2000). Development of a generalized learning transfer system inventory. Human Resource Development Quarterly, 11(4), 333–360.

45.

Hughes

A. M.

, Zajac

, Woods

A. L.

, & Salas

(2020). The role of work environment in training sustainment: A meta-analysis. Human Factors, 62(1), 166–183.

46.

Islam

, & Ahmed

(2019). Mechanism between perceived organizational support and transfer of training: Explanatory role of self-efficacy and job satisfaction. Management Research Review, 41(3), 296–313. 10.1108/MRR-02-2017-0052

47.

Kim

E.-J.

, Park

and Kang

H.-S.(T).

(2019). Support, training readiness and learning motivation in determining intention to transfer. European Journal of Training and Development, 43(3/4), 306–321. 10.1108/EJTD-08-2018-0075

48.

Kodwani

A. D.

, & Prashar

(2019). Exploring the influence of pre-training factors on training effectiveness-moderating role of trainees’ reaction: A study in the public sector in India. Human Resource Development International, 22(3), 283–304. 10.1080/13678868.2019.1596012

49.

Kossek

E. E.

, Roberts

, Fisher

, & Demarr

(1998). Career self-management: A quasi experimental assessment of the effects of a training intervention. Personnel Psychology, 51, 935–962. 10.1111/j.1744-6570.1998.tb00746.x

50.

Kraiger

(2014). Looking back and looking forward: Trends in training and development research. Human Resource Development Quarterly, 25(4), 401–408. 10.1002/hrdq.21203

51.

Krejcie

, & Morgan

(1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607–610.

52.

Lacerenza

C. N.

, Reyes

D. L.

, Marlow

S. L.

, Joseph

D. L.

, & Salas

(2017). Leadership training design, delivery, and implementation: A meta-analysis. Journal of Applied Psychology, 102(12), 1686–1718.

53.

Lauzier

, & Mercier

(2017). The effect of error orientation, motivation to learn, and social support on training transfer intentions: A moderated mediation model. Canadian Journal of Administrative Sciences, 35(3), 419–428. 10.1002/CJAS.1429

54.

Massenberg

A.-C.

, Schulte

E.-M.

, & Kauffeld

(2017). Never to early: Learning transfer system factors affecting motivation to transfer before and after training programs. Human Resource Management Quarterly, 28(1), 55–85.

55.

Massenberg

A.-C.

, Spurk

, & Kauffeld

(2015). Social support at the workplace, motivation to transfer and training transfer: A multilevel indirect effects model. International Journal of Training and Development, 19(3), 161–178.

56.

Mathieu

J. E.

, Tannenbaum

S. I.

, & Salas

(1992). Influences of individuals and situational characteristics on measures of training effectiveness. Academy of Management Journal, 35(4), 828–847.

57.

Muduli

, & Raval

(2018). Examining the role of work context, transfer design and transfer motivation on training transfer: Perspective from an Indian insurance industry. European Journal of Training and Development, 42(3/4), 266–282.

58.

Netemeyer

R. G.

, Bearden

W. O.

, & Sharma

(2003). Scaling procedure: Issues and applications. Sage Publications.

59.

K. H.

(2013). The influence of supervisory and peer support on the transfer of training. Studies in Business and Economics, 8, 82–97. https://doi/10.13140/RG.2.2.25423.12962

60.

K. H.

(2017). The fundamental role of social support in cultivating motivation to improve work through learning. Industrial and Commercial Training, 49(1), 55–60. 10.1108/ICT-08-2016-0059

61.

Nikandrou

, Brinia

, & Bereri

(2009). Trainee perceptions of training transfer: an empirical analysis. Journal of European Industrial Training, 33(3), 255–270.

62.

Noe

R. A.

, & Schmitt

(1986). The influence of trainee attitudes on training effectiveness: Test of a model. Personnel Psychology, 39(3), 497–523.

63.

Podsakoff

P. M.

, MacKenzie

S. B.

, Lee

J.-Y.

, & Podsakoff

N. P.

(2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.

64.

Reinhold

, Gegenfurtner

, & Lewalter

(2018). Social support and motivation to transfer as predictors of training transfer: Testing full and partial mediation using meat-analytic structural equation modelling. International Journal of Training and Development, 22(1), 1–14.

65.

Renaud

, & Morin

(2019). The impact of training on firm outcomes: longitudinal evidence from Canada. International Journal of Manpower, 41(2), 117–131. 10.1108/IJM-05-2018-0169

66.

Scaduto

, Lindsay

, & Chiaburu

D. S.

(2008). Leader influences on training effectiveness: Motivation and outcome expectation processes. International Journal of Training and Development, 12(3), 158–170.

67.

Schindler

L. A.

, & Burkholder

G. J.

(2016). A mixed methods examination of the influence of dimensions of support on training transfer. Journal of Mixed Methods Research, 10(3), 292–310.

68.

Seiberling

, & Kauffeld

(2017). Volition to transfer: mastering obstacles in training transfer. Personnel Review, 46(4), 809–823.

69.

Singh

(2017). Trainee characteristics and transfer of training: Effect of supervisory support (A study of public managers in Nepal). Journal of Business and Management Research, 2(1), 1–13. 10.3126/jbmr.v2i1-2.18148

70.

Smith-Jentsch

K. A.

, Salas

, & Brannick

M. T.

(2001). To transfer or not to transfer? Investigating the combined effects of trainee characteristics, team leader support, and team climate. Journal of Applied Psychology, 86(2), 279–292.

71.

Suleiman

, Dassanayake

M. S.

, & Othman

A. E.

(2017). Mediation of transfer motivation on the relationship between supervisor support, peer support and transfer of training. International Journal of Business and Society, 18(3), 605–617.

72.

Tai

W. T.

(2006). Effects of training framing, general self-efficacy and training motivation on trainees’ training effectiveness. Personnel Review, 35(1), 51–65.

73.

Tamsah

, Ilyas

G. B.

, Nurung

, Jusuf

, & Rahmi

(2023). Soft skill competency and employees’ capacity as the intervening factors between training effectiveness and health workers’ performance. Cogent Business & Management, 10(1), 2199493. 10.1080/23311975.2023.2199493

74.

Tamsah

, Yusriadi

, Hasbi

, Haris

, & Ajanil

(2023). Training management on training effectiveness and teaching creativity in the COVID-19 pandemic. Education Research International, Article ID 6588234, 10.1155/2023/6588234

75.

Tan

A. B. C.

, van Dun

D. H.

, & Wilderom

C. P. M.

(2023). Lean innovation training and transformational leadership for employee creative role identity and innovative work behavior in a public service organization. International Journal of Lean Six Sigma. 10.1108/IJLSS-06-2022-0126

76.

Terglav

, Ruzzier

M. M.

, & Kase

(2016). International branding process: Exploring the role of mediators in top management’s leadership-commitment relationship. International Journal of Hospitality Management, 54, 1–11.

77.

Tesluk

P. E.

, Farr

J. L.

, Mathieu

J. E.

, & Vance

R. J.

(1995). Generalization of employee involvement training to the job setting: Individual and situational effects. Personnel Psychology, 48(5), 607–632.

78.

Torraco

R. J.

, & Lundgren

(2020). What HRD is doing: What HRD should be doing: The case for transforming HRD. Human Resource Development Review, 19(1), 39–65. 10.1177/1534484319877058

79.

Velada

, Caetano

, Bates

, & Holton

(2009). Learning transfer–validation of the learning transfer system inventory in Portugal. Journal of European Industrial Training, 33(7), 635–656. 10.1108/03090590910985390

80.

Velada

, Caetano

, Michel

J. W.

, Lyons

B. D.

, & Kavanagh

M. J.

(2007). The effects of training design, individual characteristics and work environment on transfer of training. International Journal of Training and Development, 11(4), 282–294.

81.

Vroom

V. H.

(1964). Work and motivation. Wiley.

82.

Wolfe

S. E.

, McLean

, Rojek

, Alpert

G. P.

, & Smith

M. R.

(2019). Advancing a theory of police officer training motivation and receptivity. Justice Quarterly, 39(1), 1–23. 10.1080/07418825.2019.1703027

83.

Xiao

(1996). The relationship between organizational factors and the transfer of training in the electronics industry in Shezhen, China. Human Resource Development Quarterly, 7(1), 55–73.

84.

Yaghi

, & Bates

(2020). The role of supervisor and peer support in training transfer in institutions of higher education. International Journal of Training and Development, 24(2), 89–104. 10.1111/ijtd.1273

85.

Zumrah

A. R.

, & Boyle

(2015). The effects of perceived organizational support and job satisfaction on transfer of training. Personnel Review, 44(2), 236–254. 10.1108/PR-02-2013-0029