social support

Tilburg University

Social support in the workplace and training effectivenessChiaburu, D.; van Dam, Karen; Hutchins, H. M.

Published in:International Journal of Selection and Assessment

Document version:Publisher final version (usually the publisher pdf)

Publication date:2010

Link to publication

Citation for published version (APA):Chiaburu, D., van Dam, K., & Hutchins, H. M. (2010). Social support in the workplace and training effectiveness:A longitudinal analysis. International Journal of Selection and Assessment, 18(2), 187-200.

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

Users may download and print one copy of any publication from the public portal for the purpose of private study or research You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portalTake down policyIf you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

Download date: 16. Jun. 2015

Social Support in the Workplace and TrainingTransfer: A longitudinal analysis

Dan S. Chiaburu*, Karen Van Dam** and Holly M. Hutchins***

*Mays School of Business, Texas A&M University, College Station, TX 77843-4113, [email protected]**Department of Social Psychology, Tilburg University, Warandelaan 2, 5037 AB Tilburg, The Netherlands***College of Technology, University of Houston, 4800 Calhoun Drive, Houston, TX 77018, USA

Training transfer is crucial for workplace effectiveness, yet some of its social support

antecedents are not well investigated. We examine the extent to which two forms of social

support (from the organization and the supervisor) predict training transfer and propose

several related processes explaining these influences. First, social support enhances training

self-efficacy, increases trainees mastery (learning) goal orientation, and their motivation to

transfer. In turn, we propose that these individual factors are positively related to training-

related cognitions. We test and confirm our model in a longitudinal study based on a sample

of 111 employees. The results contribute to a better understanding of organization- and

supervisor-based social support as predictors of transfer, and clarify several important

related mechanisms.

1. Introduction

Ensuring that training investments yield performanceimprovement continues to be a vexing problem fororganizations. Training transfer, commonly understood as

the generalization and application of new knowledge and

skills to the work setting (Baldwin & Ford, 1988), could

be considered the Achilles heel of the training design

process. That is, when trainees fail to use their new

knowledge to improve performance, resources dedicated

to training are wasted and business results go unrealized.

Such outcomes are particularity unwelcome to organiza-

tional executives demanding a positive return on training

investments, which in the United States accounts for over

130 billion dollars annually (Paradise, 2007).

Extant research on training transfer points to several

strategies at the learner, training design, and organiza-

tional level for increasing transfer. Learner attributes such

as cognitive ability (Colquitt, LePine, & Noe, 2000),

motivation (Axtell, Maitlis, & Yearta, 1997), self-efficacy

(Chiaburu & Lindsay, 2008), and perceptions of job utility

(Lim & Morris, 2006) have demonstrated both indirect

through learning and direct effects on transfer out-

comes. Research has also demonstrated the resilience of

certain training design factors on skill application, namely

the use of learning principles (identical elements, stimulus

generalization, and practice) and instructional methods

on transfer performance (e.g., learner control, practice

variability; Holladay & Quinones, 2003; Orvis, Fisher, &

Wasserman, 2009; van Merrienboer, 1997). However,

current research has overwhelming favored some ele-

ments of support originating in the organizational setting

to positively influence individuals training transfer. Long-

standing factors such as providing the opportunity to

apply new learning and receiving supervisor support (i.e.,

asking questions about training, holding trainees accoun-

table, participative goal-setting) have been found to be

some of the most consistent predictors of transfer

outcomes (Burke & Hutchins, 2007).

An emergent aspect that accounts for a broader view

of organizational support for training transfer is trainees

perceptions of organizational support. Perceived organi-

zational support (POS) is defined as an employees belief

about how much the organization cares about them and

values their contributions to the organization (Aselage &

Eisenberger, 2003; Rhoades & Eisenberger, 2002).

Although important for performance and discretionary

behaviors, support from the organization is less examined

in connection to transfer. Indeed, extant research has

focused on specific antecedents (e.g., manager, peer

support) for general work performance and training

transfer (Rodgers & Hunter, 1991; Russell, Terborg, &

& 2010 Blackwell Publishing Ltd.,

9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main St., Malden, MA, 02148, USA

International Journal of Selection and Assessment Volume 18 Number 2 June 2010

Powers, 1985), but less so on the perceived support

emanating from the organization. However, support from

the organization may bolster employees self-esteem and

give the employee the feeling that the employer values

them. Organizational support increases employees satis-

faction and commitment (Ng & Sorensen, 2008) and is

reciprocated by employees feelings of obligation toward

the organization, leading further to increased work

engagement (e.g., Salanova, Agut, & Peiro, 2005). Extra-

polating these outcomes to a training transfer context,

employees who perceive high levels of organizational

support may also demonstrate their commitment

through being more motivated in a training context and

applying the new learning on the job (Pidd, 2004; Russell

et al., 1985; Tansky & Cohen, 2001).

To date, research examining the relationship between

POS and training transfer has been limited, despite the

fact that organizational support is correlated with a

number of work aspects which have been related either

theoretically or empirically to training transfer (e.g.,

affective commitment, job satisfaction, job involvement;

Rhoades & Eisenberger, 2002). Examining the role of

support originating from the organization in training

transfer would begin to elucidate possible differential

effects of support as behaviors originating from man-

agers, coworkers, and other stakeholders (Cromwell

& Kolb, 2004) versus support as work characteristics

or broader organizational features (e.g., Clarke, 2002).

Given existing evidence for POS as an antecedent to

positive attitudes toward work and to performance, and

positive correlations between aspects of the work en-

vironment including support from the organization and

proximal aspects of transfer such as declarative knowl-

edge (e.g., Tracey, Hinkin, Tannenbaum, & Mathieu, 2001),

we expect organizational support to positively influence

training transfer. In addition, this relationship is explored

because organizational context factors are less examined

as predictors of training transfer and, when examined,

they yield mixed results (Cheng & Ho, 2001).

Typically, POS and supervisor support are parallel

constructs (e.g., Kottke & Sharafinski, 1988; Rhoades &

Eisenberger, 2002). In a training transfer context, suppor-

tive supervision can include both a more general view of

employee development as an important aspect of the

managers jobs (Yarnall, 1998), coupled with more im-

mediate and practical aspects, such as providing the

subordinate time for skill practice and offering reminders

aiding skill implementation (Chiaburu & Tekleab, 2005).

To best explore POS as a predictor of training transfer,

supervisory support (a longstanding transfer predictor)

must also be considered for examination within the same

model. This need is consistent with studies situated both

in a broad organizational context (see Ng & Sorensen,

2008, for a recent meta-analysis of the two forms of

support) and with research where support is conceptua-

lized in a training transfer domain (Burke & Hutchins,

2007). Testing both organization- and supervisor-based

types of support will offer more information on each

factors unique contribution to training transfer and to

aspects leading to it.

We also attempt to elucidate intervening processes

between support and training transfer. Specifically, we

expect POS and supervisory support to affect training

transfer indirectly through influencing individual factors.

We focus specifically on trainee perceived self-efficacy

(Gaudine & Saks, 2004; Stevens & Gist, 1997), learning

(or mastery) goal orientation (Fisher & Ford, 1998; Silver,

Dwyer & Alford, 2006), and motivation to transfer

(Axtell et al., 1997). Trainees who perceive support

from both distal (POS) and proximal (supervisor) sources

will have increased perceived ability that they can transfer

skills (self-efficacy), high levels of learning goal orienta-

tion, and will reciprocate through increased motivation

(to transfer). In turn, these also influence how trainees

think about their training transfer, or engage in training

cognitions related to the skills acquired and to training

transfer. In this study, we suggest that training-related

cognitions mediate the relationship between individual

factors and training transfer.

1.1. Theory developmentand hypotheses

Perceived support from the organization (POS) repre-

sents employees global beliefs regarding how much the

organization cares about their well-being (Eisenberger,

Armeli, Rexwinkel, Lynch, & Rhoades, 2001; Eisenberger,

Huntington, Hutchison, & Sowa, 1986). These can be

manifested by specific actions, including considering

employees goals and values, and offering help when

employees need it. In turn, employees reciprocate

through performance, citizenship behaviors, and more

involvement with their organizations (Aselage & Eisen-

berger, 2003; Coyle-Shapiro, 2002; Turnley, Bolino, Les-

ter, & Bloodgood, 2003). This may include engaging in

acquiring new skills and transferring knowledge and skills

to a work situation, as part of employees felt obligation

to help the organization reach its goals (Shore, Barksdale,

& Shore, 1995).

We propose that POS influences performance through

individual-level factors found to have a positive impact on

training transfer, including trainees self-efficacy, learning

goal orientation, and motivation to transfer (Burke &

Hutchins, 2007). In more concrete terms, POS implies

assurance that aid will be available from the organization

when it is needed to carry out ones job effectively and to

deal with stressful situations (Rhoades & Eisenberger,

2002, p. 698). In a training transfer context, organiza-

tional support (in the form of rewards given to trainees

for transfer) positively impacts skill transfer, a relation-

ship mediated by trainees self-efficacy (Tracey et al.,

188 Dan S. Chiaburu, Karen Van Dam and Holly M. Hutchins

International Journal of Selection and Assessment

Volume 18 Number 2 June 2010 & 2010 Blackwell Publishing Ltd.

2001). More generally, based on sociocognitive and social

support theories, when various contingencies in the

work context are taken care of, including the assurance

of overall support from the organization, employees are

more likely to set and achieve challenging performance

goals (Bandura, 1986, 1997; Viswesvaran, Sanchez, &

Fisher, 1999). We examine similar outcomes of support

in a training transfer context, and focus next on trainees

self-efficacy, learning goal orientation, and motivation to

transfer.

Training self-efficacy is generally described as a trainees

judgment about their ability to succeed in training, and

has specifically been found to be positively related to

training generalization and maintenance across multiple

studies and settings (Ford, Smith, Weissbein, Gully, &

Salas, 1998; Gaudine & Saks, 2004; Latham & Frayne,

1989; Stevens & Gist, 1997; Tannenbaum, Mathieu, Salas,

& Cannon-Bowers, 1991). That is, trainees are more

likely to overcome obstacles that may delay the applica-

tion of new learning when they believe in their ability to

learn and to use their knowledge and skills on the job. A

positive link between strategies that increase self-efficacy,

such as goal-setting, mastery experiences, supportive

feedback, and verbal guidance, have also been found to

influence transfer (Brown & Morrissey, 2004; Chiaburu &

Lindsay, 2008; Gist, 1986; Richman-Hirsch, 2001) suggest-

ing that self-efficacy can be influenced as a way to increase

learning and subsequent transfer success. Although the

research largely supports the role of supervisory support

in influencing training self-efficacy, it is also expected that

such influence may emanate from the larger organiza-

tional context in addition to or instead of a discrete and

proximal source (i.e., supervisor or peer).

Specifically, when estimating their levels of self-efficacy,

individuals take into account both individual and situa-

tional resources and constraints (Gist & Mitchell, 1992),

such as support existing in their organizational environ-

ment. For example, Tracey et al. (2001) found that

trainees who perceived a supportive work environment

(comprised of support from manager, on the job, and

from the organization) reported higher levels of pretrain-

ing self-efficacy and pretraining motivation (which then

predicted transfer). These findings suggest that the

process by which trainees are prepared for training can

influence trainee attitudes and motivation toward apply-

ing their knowledge and skills in the work setting.

Learning (or mastery) orientation is grounded in the

theory of achievement motivation, and explains individual

behavior and motivation in achievement settings (Ames &

Archer, 1988; Dweck & Leggett, 1988). Trainees with a

learning (sometimes referred to as mastery goal orienta-

tion) orientation are concerned with developing compe-

tence through training, and are more likely to take on

challenging tasks that will further support learning acqui-

sition. Although learning orientation is a predictor of

training knowledge (Fisher & Ford, 1998) and transfer

(Silver et al., 2006), it influences transfer outcomes

through some intervening mechanism. For example,

mastery goal orientation has been found to influence

transfer through pretraining motivation (Chiaburu &

Marinova, 2005), metacognitive activity (Ford et al.,

1998; Schmidt & Ford, 2003), and deeper (rather than

superficial) cognitive processing strategies and effort

(Dupeyrat & Marine, 2005).

Determinants of learning orientation are thought to

originate out of situational cues or factors in the larger

performance context, which can be altered (Dragoni,

2005; Dweck, 1989). In terms of training transfer, learning

orientation may be influenced by how employee applica-

tion of training knowledge is valued and supported by the

organization. For example, Chiaburu and Marinova

(2005) suggest that contextual factors such as organiza-

tional reward structures might be used to influence

aspects of the environment that are likely to deemphasize

a learning orientation (and favor a performance orienta-

tion). That is, rewards that are based on effort rather

than results (e.g., sales quotes) may increase trainees

goals toward learning rather than just performance. The

existence of feedback and support, opportunities to

perform, and holding trainees accountable for applying

their training on the job may also increase trainees

leaning goal orientation (Kontoghiorghes, 2001; Lim &

Morris, 2006; Tracey, Tannenbaum, & Kavanagh, 1995).

Motivation to transfer is the trainees intended effort to

utilize skills and knowledge learned in training setting to a

real world work situation (Noe, 1986), and has been

found to directly influence transfer outcomes (Axtell

et al., 1997; Chiaburu & Lindsay, 2008; Nijman, Nijhof,

Wognum, & Veldkamp, 2006). Interestingly, research

connecting motivation to transfer directly with specific

transfer outcomes has overall been limited (Konto-

ghiorghes, 2002; Machin & Fogarty, 2004; Seyler, Holton,

Bates, Burnett, & Carvalho, 1998), compared with fairly

strong support for pretraining motivation and motivation

to learn (Burke & Hutchins, 2007; Pugh & Bergin, 2006).

For example, Kirwan and Birchall (2006) examined the

relationship of individual and work environment factors

in Holton, Bates, and Ruonas (2000). Learning Transfer

System Inventory, a diagnostic survey that assesses

trainees perceptions of individual, training design, and

situational factors known to influence transfer.

One of the more important findings to the current

study is that work support factors known to influence

transfer directly (opportunity to use, manager support,

manager sanctions, peer support, feedback, and coaching)

were strongly related to motivation to transfer. Addi-

tionally, results indicated that motivation to transfer was

significantly influenced by peer support, opportunity to

use, and feedback/coaching. Even though the influence of

POS (separate from supervisory support) on motivation

to transfer and transfer outcomes is less clear, there is

some empirical support for the role of learning culture in

Social Support and Training Transfer 189

& 2010 Blackwell Publishing Ltd.


Volume 18 Number 2 June 2010

motivation to transfer (Egan, Yang, & Bartlett, 2004) and

of the work environment on transfer dimensions (Noe,

1986; Tracey et al., 2001). Thus, elucidating the source

mechanism (i.e., POS, supervisory support) for influen-

cing individual factors on transfer outcomes will help

tease out the specific contributions of each on training

transfer.

Hypothesis 1: POS is positively related to trainees (a)

training self-efficacy, (b) learning goal orientation, and

(c) motivation to transfer.

As discussed, the antecedents of individual factors that

influence performance often lie with situational cues:

these can originate not only from the organization, but

can also come in the form of supervisor support (Burke &

Baldwin, 1999; Clarke, 2002; Nijman et al., 2006). To

summarize, based on theories mentioned previously,

supervisors are well positioned to positively influence

their subordinates self-efficacy (Axtell & Maitlis, 1997;

Guerrero & Sire, 2001; Tracey et al., 2001), goal orienta-

tion (Dragoni, 2005; Janssen & Van Yperen, 2004), and

training motivation (e.g., Facteau, Dobbins, Russell, Ladd,

& Kudisch, 1995; Guerrero & Sire, 2001), which may

result in increased performance and training transfer.

Hypothesis 2: Supervisor support is positively related to

trainees (a) training self-efficacy, (b) learning goal orien-

tation, and (c) motivation to transfer.

Research suggests that training transfer increases

when trainees have high expectations of their ability to

perform, focus on learning as an outcome, and are

motivated to use their skills on the job. However, it is

possible that these individual factors actually influence

how trainees engage in cognitive elaboration about how

they will use their learning acquired in training (i.e.,

thinking about when they will transfer, considering po-

tential obstacles to transfer, and identifying needed sup-

port and resources). All these increase the likelihood that

trainees will transfer their learning to the work setting by

engaging in mental elaboration concerning skill transfer.

For example, an individuals level of self-efficacy will

influence the choice of activities and environments, and

will often dictate decisions on how much effort will be

invested into accomplishing goals despite obstacles or

stressful conditions (Tai, 2006).

The process of thinking about specific aspects of skill

utilization and how training will be applied (transferred) is

known as training-related cognitions (Dupeyrat & Marine,

2005; Gist, Stevens, & Bavetta, 1991). This type of

cognitive engagement parallels affective- and skill-based

outcomes of training (Ford, Kraiger, & Merritt, 2009) and

has both reflective and active aspects, such as thinking

about how to achieve goals and identifying obstacles to

skill transfer, respectively.

Although training-related cognitions focus on the

mental process of training and transfer, research suggests

that such cognitive processes can be predicted by in-

dividual difference aspects. For example, individuals with

learning goal orientations have more inclinations toward

being self-motivated (using an intrinsic mode of motiva-

tion; Hirschfeld, Thomas, & McNatt, 2008), which may

dispose them to think more of the skills acquired in

training, and elaborate more on how they can be main-

tained and used in a work setting. Empirical research in

educational setting indicates that learning orientations

are correlated to cognitive strategies, deep information

processing and persistence (Elliot, McGregor, & Gable,

1999; Wolters, 2004), and facilitate access to information

acquired during the training stage (Graham & Golan,

1991). Similarly, persons who consider themselves highly

efficacious are more likely to set difficult goals and adjust

them based on their progress, will take a proactive role in

reducing stress or disruptions in their environment that

may inhibit performance (Gist & Mitchell, 1992). Overall,

individuals who are likely to perceive they can succeed in

training, are more focused on mastering the training

content, and are motivated to transfer, will likely be

more inclined to consider how they can apply the

knowledge than trainees who are less active in these

areas.

Hypothesis 3: Trainees (a) training self-efficacy, (b) learn-

ing goal orientation, and (c) motivation to transfer are

positively related to training cognitions.

Transferring skills to a work context is an iterative

process involving transactions between declarative,

working, and procedural memory (Anderson, 1982).

Even though employees may have retained (and repeated

several times) behavioral checklists in a classroom setting,

they still need to recall, rehearse, utilize, and perhaps

optimize them in a work setting. Research on self-

management strategies, such as goal-setting and relapse

prevention techniques, suggests that having trainees

consider how they will use their new skills and knowl-

edge on the job has positively influenced transfer out-

comes (Brown, 2005; Burke & Baldwin, 1999; Frayne &

Latham, 1987; Gist, Bavetta, & Stevens, 1990; Latham &

Frayne, 1989; Richman-Hirsch, 2001). Self-management

skills not only include participants considering how new

learning will be applied, but also in how to mitigate

potential obstacles that may interfere (e.g., deadlines,

work pressure, interpersonal conflicts) with positive

training transfer.

For example, Ford et al. (1998) found that participants

engaging in monitoring learning, identifying which areas

they had problems, and adjusting behavior accordingly

reported greater knowledge and higher transfer perfor-

mance in the training program. Likewise, experimental

work in educational settings has connected cognitive




activities (e.g., deep processing, persistence) with higher

levels of performance (e.g., Dupeyrat & Marine,

2005; Elliot et al., 1999). Similarly, cognitive engagement

consisting in thinking about the skills acquired in training

and ways to incorporate into day-to-day work activities

will enhance effectiveness in a training context. Thus,

it is also expected that engaging in thinking about how

training will be used will be related to actual training

transfer.

Hypothesis 4: Training cognitions are positively related to

training transfer.

Engaging in thinking about skill transfer has also been

found to mediate the relationships between individual-

level variables and training transfer (e.g., Schmidt & Ford,

2003). For example, participants with a mastery of

learning orientation reported more use of self-regulatory

behaviors (i.e., thinking about the training content, prior-

itizing tasks and resources for learning) during learning,

which then predicted performance on a skill-based

training assessment (Ford et al., 1998; Wolters, 2004).

The authors suggested that learners who were more

concerned with mastering the training content rather

than focusing on outperforming others engaged in

more cognitive processes relative to using and general-

izing their new learning to the work setting. Similarly,

Enos, Kehrhahn, and Bell (2003) suggested that thinking

about how training would be used may work to increase

performance and help participants achieve goals despite

the level of support in the work environment. In a training

setting, Stevens & Gist (1997) found that trainees with

high levels of learning goal orientation engaged more in

skill maintenance activities, including thinking about what

skills to use and how to maintain them. The results are

consistent with recent meta-analytic work: mastery-

oriented trainees go beyond memorizing the material

and look at conceptual implications and connections

with other areas (i.e., through cognitive activities; Mes-

mer-Magnus & Viswesvaran, 2007), which can increase

transfer.

The utility of trainees considering how they will apply

their new knowledge and skills in the work setting is

consistent with Burke and Baldwins (1999) study of

relapse prevention. Specifically, engineering professionals

were more likely to use cognitive strategies (i.e., setting

skill maintenance goals, identifying obstacles, developing

cognitive strategies to mitigate obstacles) when they

perceived less support for training transfer. Although

relapse prevention was not tested as a mediator, the

study did show how using cognitive strategies in con-

sidering how training would be used is influenced by

trainees perception of support in the work setting. The

conclusions parallel those in educational settings, where

students with high levels of self-efficacy engage in more

cognitive activities (e.g., rehearsal, elaboration, and

organizational strategies), which lead to better perfor-

mance (e.g., Pintrich & De Groot, 1990). Given the role

cognitive processes play in supporting training transfer,

we suggest that training cognitions will mediate the

relationship between the individual factors and training

transfer.

Hypothesis 5: Training cognitions will mediate the rela-

tionships between (a) training self-efficacy, (b) learning

goal orientation, and (c) motivation to transfer and

training transfer.

2. Method

2.1. Survey design and procedure

We conducted the longitudinal field study in a large

organization in the Mid-Atlantic region of the United

States. Employees attended training as part of changes

related to their positions, as a result of a company effort

to institutionalize a climate of service to external custo-

mers and of responsiveness toward other employees

(e.g., colleagues in their and other units) inside the

organization. We surveyed 750 employees, and obtained

372 surveys with usable data at time one, 223 at time

two, and 111 at time three. A total of 111 participants

provided information on all scales. The demographic

profile of these participants is as follows: 79% were

men, 76.8% had some college education, 89% were 30

years or older, and 86.3% had worked for the organiza-

tion for 41 year. Previously published scales were usedin our questionnaire, with the measures anchored on a

5-point Likert-type scale (from 1 strongly disagree to5 strongly agree).

We minimized question order effects and common

source measurement biases by following current sugges-

tions (e.g., Podsakoff, MacKenzie, Lee, & Podsakoff, 2003;

Schwarz, Knauper, Oyserman, & Stich, 2008). When the

sources of predictor and criterion variables cannot be

separated, one available procedural remedy is separating

the measurement of predictor and criterion variables in

time. We did so, by having the participants respond to

our questions at different times. Thus, the social context

and individual factors were assessed at time one (during

the training program). Training cognitions were measured

at time two, 1 month after the training program. Finally,

training transfer was measured at time three, 23 months

after the training took place. Longitudinal designs are also

more appropriate than crosssectional ones for causal

inferences based on preexisting theory and empirical

data.

2.2. Social context predictors

POS was measured using seven items from the POS scale

(Help is available from the organization when I have a





problem, a .86, Eisenberger et al., 1986). Supervisorsupport was measured using five items (Chiaburu &

Tekleab, 2005; Yarnall, 1998; My supervisor provides

me with the time I need to practice the skills learned in

training, a .78).

2.3. Individual difference predictors

Training self-efficacy was measured with Noe and Wilks

(1993) eight-item scale (e.g., When I take training

courses in unfamiliar areas. I expect to be able to do

well at them, a .84). Learning goal orientation wasmeasured with Elliot and McGregors (2001) three-item

scale adapted for a training context (e.g., I want to learn

as much as possible from the training, a .84). Motivationto transfer was measured with five items developed by

Noe (1986) (I believe my job performance will likely

improve if I use the knowledge and skills acquired in

training, a .75).

2.4. Training cognitions

Thinking about skill transfer was assessed using questions

designed to probe how trainees maintain their skills (six

items, Gist et al., 1991), Since the training session, I have

thought about how to achieve the training objectives,

a .83).

2.5. Training outcomes

We used the training transfer scale (six items, Xiao, 1996;

Using the new knowledge from training has helped my

work, a .76) to determine the extent to which traineestransferred skills acquired in training into their daily

activities.

2.6. Analyses

Structural equations modeling (SEM) with maximum

likelihood estimation was used to test the hypotheses

and the fit of the overarching model. Multiple fit indices

were used to assess the adequacy of the estimated

model: the Tucker-Lewis index (TLI), the comparative-

fit-index (CFI), and the root mean squared error of

approximation (RMSEA). It is generally suggested that

the TLI and CFI should exceed .90 or even .95 for the

model to be considered of good fit (Hu & Bentler, 1999);

similarly, a value of .06 or less for the RMSEA reflects

good fit (Browne & Cudeck, 1993). Finally, a chi-squared

difference test was conducted for choosing among com-

peting models. These analyses were performed with the

AMOS 6.0 software package (Arbuckle, 2006).

To investigate the mediating effect of training cogni-

tions, we examined whether Baron and Kennys (1986)

three conditions for mediation were met (1) a signifi-

cant relationship exists between the independent vari-

able and the dependent variable; (2) a significant

relationship exists between the independent variable

and the mediator, and (3) a significant relationship

exists between the mediator and the dependent vari-

able while holding the independent variable constant. In

case of full mediation, the independent variable has no

significant relationship with the dependent variable

when the mediator is added to the analysis. Sobels

(1982) test for mediation was used to establish the

significance of the mediated effect of the independent

variable on the dependent variable.

3. Results

3.1. Preliminary results

Although we sought to control for age, gender, educa-

tional level, organizational tenure and job tenure, pre-

liminary analyses showed that none of the control

variables was significantly related to training transfer.

Therefore, they were not included in the analyses. In

addition, we tested whether respondents and nonre-

spondents were significantly different in terms of gender,

race, education, age, tenure with the organization, and

time in the current position, with no statistically signifi-

cant differences found. Table 1 presents the means,

standard deviations, reliabilities, and intercorrelations of

the study variables.

3.2. Model fit and hypotheses tests

Based on our hypotheses, and especially our mediating

hypothesis, the proposed model showed a modest fit:

w2(df 10) 23.93, po.01; w2/df 2.39; CFI .93;TLI .86; RMSEA .11. The standardized residuals sug-gested that model fit might be improved by including

direct relationships between training self-efficacy, motiva-

tion to transfer and training transfer. This would imply

that training cognitions would only partially mediate the

relationship between training self-efficacy, motivation to

transfer and transfer. Because previous studies have also

found direct relationships of training self-efficacy (e.g.,

Chiaburu & Marinova, 2005), and motivation to transfer

(e.g., Colquitt et al., 2000) with transfer, a full mediation

model might be too stringent. Therefore, we revised our

model including direct paths from training self-efficacy

(e.g., Chiaburu & Marinova, 2005), and motivation to

transfer (e.g., Colquitt et al., 2000) to training transfer.

Conversely, learning goal orientation is more likely to be

connected to training transfer through employee cogni-

tions (Mesmer-Magnus & Viswesvaran, 2007). The re-

vised model had very good fit: w2(df 9) 12.19, p .20;w2/df 1.36; CFI .99; TLI .96; RMSEA .05. A chi-squared difference test indicated that the extended

model provided a significantly better description of the

data than the original model (Dw2/Ddf 11.74, po.001).




Based on the existing theory and research, we decided to

use the extended model for testing our hypotheses. The

standardized regression coefficients for this model are

presented in Figure 1.

In the first two hypotheses, we connected our social

context factors (POS and supervisor support) with

trainees self-efficacy, goal orientation, and motivation

to transfer. The results show that POS was significantly

related to training self-efficacy (b .34, po.001) andmotivation to transfer (b .16, po.05), but did notreach significance in its relationship to learning goal

orientation (b.06, NS). Therefore, Hypotheses 1(a)and 1(c) were supported. Supervisor support showed

significant relationships with all three individual difference

variables: training self-efficacy (b .42, po.001), leaninggoal orientation (b .32, po.001), and motivation to

transfer (b .49, po.001). The findings fully supportedHypotheses 2(a)(c).

In the next set of hypotheses, we proposed positive

relationships between training self-efficacy [Hypothesis

3(a)], learning goal orientation [Hypothesis 3(b)], and

motivation to transfer [Hypothesis 3(c)] and training

cognitions. Our data show significant relationships be-

tween training self-efficacy (b .16, po.01), leaning goalorientation (b .31, po.01), motivation to transfer(b .21, po.05), and cognition. Therefore, all threecomponents of our Hypothesis 3 were supported.

Finally, we tested whether training cognitions are a

positive predictor of training transfer (Hypothesis 4) and

a mediator of the relationships between training self-

efficacy [Hypothesis 5(a)], learning goal orientation [Hy-

pothesis 5(b)], and motivation to transfer [Hypothesis

OUTCOME

SOCIALCONTEXT

POS

SupervisorSupport

INDIVIDUALFACTORS

PROCESS

Training Self-Efficacy

Learning GoalOrientation

Motivation toTransfer

Training-Related

Cognitions

TrainingTransfer

.34***

.41***.06ns

.16*

.42***

.32***

.49***

.18**

.16**

.31**

.21*

.19*

Figure 1. Final model with results. Note. Paths with dotted lines (from training self-efficacy to training transfer, and from motivation to transfer totraining transfer) are part of the revised model. *po.05; **po.01; ***po.001.

Table 1. Means, standard deviations, reliability estimates, and intercorrelations of study variables

Variable M (N 111) SD M SD 1 2a 3a 4a 5b 6b 71. Perceived organizational support 3.06 .84 3.10 .76 (.86) .15 .45 .09 .31 .25 .262. Supervisor support 3.86 .58 3.89 .61 .20 (.78) .48 .45 .38 .39 .293. Training self-efficacy 3.76 .60 3.78 .61 .42 .49 (.84) .28 .41 .48 .394. Learning goal orientation 4.17 .73 4.13 .74 .00 .44 .21 (.84) .42 .51 .305. Motivation to transfer 3.58 .51 3.58 .50 .24 .56 .42 .56 (.75) .47 .446. Training cognitions 3.62 .66 3.67 .73 .23 .38 .31 .46 .45 (.83) .467. Training transfer 3.61 .59 3.61 .59 .26 .29 .39 .30 .44 .46 (.76)

Note. Means and standard deviations in the first two columns and correlations below the diagonal are based on the sample of N 111 used in thestructural equations modeling analyses; for r |.19|, po.05; for r |.23|, po.01; for r |.31|, po.001. Means and standard deviations in the third andfourth column and correlations above the diagonal are based on the larger samples of N 372 (denoted by a) and N 223 (denoted by b). Reliabilityestimates (as) are on the diagonal in parentheses (based on N 111).





5(c)], and training transfer. Training cognitions were

indeed a positive predictor of transfer (b .41,po.001), supporting Hypothesis 4. Sobels test for med-iation showed that training cognitions mediated the

effects of the individual factors. The indirect effects

were 2.54 (po.01) for training self-efficacy; 2.82(po.01) for learning goal orientation; and 2.00 (po.05)for motivation to transfer. However, in addition to these

hypothesized relationships, the data also revealed direct

relationships for training self-efficacy (b .18, po.01),and motivation to transfer (b .19, po.05) with trainingtransfer and indirect relationships from goal orientation

to training transfer (through training cognitions). The fact

that our revised model fitted the data better than the

fully mediated model (as discussed above), leads to the

conclusion of partial mediation, and thus support of

Hypothesis 5(b), but not of Hypotheses 5(a) and (c).

In addition to testing the full model on the responses

of 111 participants, we tested the hypotheses by examin-

ing parts of the model with exploratory regression

analysis using the larger samples. Using the full sample

of 372 participants, significant relationships were found

between POS and training self-efficacy (b .38, po.001),and motivation to transfer (b .26, po.001); the rela-tionship with learning goal orientation did not reach

significance (b .03, NS). Similarly, supervisor supportshowed significant relationships with all three individual

difference variables: training self-efficacy (b .43,po.001), leaning goal orientation (b .44, po.001),and motivation to transfer (b .34, po.001). Using thesample of 223 participants, significant relationships were

found between training self-efficacy (b .21, po.01),leaning goal orientation (b .32, po.001), motivationto transfer (b .21, po.01), and training related cogni-tions. In conclusion, these post hoc analyses on the larger

samples confirmed the outcomes of the SEM analyses.

4. Discussion

Few studies have examined the contribution of support

from both supervisors and from the larger organizational

context in the context of training transfer. Much of the

research testing work environment factors as an ante-

cedent to training transfer have focused on the role of

supervisors in providing support, resources, opportu-

nities to perform, and consequences for behavior (Burke

& Hutchins, 2007). Similarly, studies examining the role of

transfer climate (Tracey et al., 2001) or transfer system

(Holton et al., 2000) have grouped various work factors

together as an aggregate assessment of support. Con-

sistent with the idea that various forms of support may

have different magnitudes of relationships with aspects of

the training transfer process (Cheng & Ho, 2001) and

with the need to focus more on aspects of the trainees

work environment (Ford & Weissbein, 1997), we extend

previous research by examining how two forms of social

support influence training transfer. To determine the

influence of social context on skill transfer, we also

examined individual outcomes of support, including

trainee self-efficacy, learning goal orientation and motiva-

tion to transfer, and training cognitions both as a med-

iator between individual factors and training transfer. Our

study revealed several important findings concerning the

role of support within the broader organizational context

and the utility of individual (cognitive and motivational)

factors for training transfer.

4.1. Support from the organizationand the supervisor

As expected, we found that both supervisory support

and POS were positively related to trainee self-efficacy

and motivation to learn, suggesting that influences on

these individual factors could stem from either support

source. An exception was in the relationship between

POS and learning goal orientation. While supervisor

support was positively related to learning goal orienta-

tion, organizational support was not. This seems to

suggest that the main drivers of trainees goal orientation

originate from a more proximal source (such as ones

supervisor) rather than from the larger organizational

context. That is, even when trainees perceive rewards

and other support incentives in the organizational setting

(e.g., Chiaburu & Marinova, 2005) that are tied to training

transfer, they may need direct or additional reinforce-

ment from a direct supervisor (or a source close to

them) to influence goal orientation. This finding is con-

sistent with research showing that the quality of relation-

ship with ones supervisor influences subordinates

learning goal orientations (e.g., Janssen & Van Yperen,

2004) and extends prior research where other aspects of

the work environment, including culture and climate

were connected to training transfer (Chiaburu & Tekleab,

2005; Rouiller & Goldstein, 1993; Tracey et al., 2001;

Tziner, Fisher, Senior, & Weisberg, 2007).

In addition, supervisor support positively influences

motivation to transfer and does so to a greater extent

than organizational support. The same is true, to a lesser

extent, for training self-efficacy. When comparing the

more distal and diffuse entity (the organization) and the

proximal and concrete one (the supervisor) aspects of

social support (correlated .20 in our study), supervisors

seem to matter slightly more for their sub-

ordinates self-efficacy, goal orientation, and training

motivation. Extending other studies where different

entities forming the social context were compared

qualitatively (e.g., Hawley & Barnard, 2005), or where

other sources of support were compared (e.g., co-

workers, supervisors; Chiaburu & Marinova, 2005; van

der Klink, Gielen, & Nauta, 2001), we directly compared

the influence of organizational and supervisor support.




4.2. The importance of training-related cognitions

Our finding that trainee efficacy, motivation, and goal

orientation were related to training cognitions, and that

thinking about how to use training in the work setting

was a strong predictor of training transfer sheds some

light on the interplay between how trainee cognition and

motivational factors influence performance. These find-

ings suggest that trainees are more likely to consider how

they will apply their training on the job when they feel

confident, motivated, and interested in acquiring know-

ledge, which can lead to enhanced training transfer.

Interestingly, learning goal orientation had the strongest

relationship with training cognitions and was the only

factor mediated by training cognitions in relation to

training transfer (see later discussion). This finding is

not completely surprising: individuals with high levels of

learning goal orientation have been found to engage in

cognitive strategies such as task-oriented practice, re-

hearsal, and elaboration techniques (Elliot & McGregor,

2001; Ford et al., 1998; Pintrich, 2000; Wolters, 2004).

Although the majority of these studies were based in

educational settings, our study confirms similar findings in

a corporate setting.

Finally, training cognitions also functioned to partially

mediate the relationship between both trainee self-

efficacy and motivation to transfer and training transfer.

Our revised model resulted in a direct relationship

between self-efficacy and motivation to transfer and

training transfer, in addition to the direct relationships

between these individual variables and training cogni-

tions; however, training cognitions did mediate the re-

lationship between learning goal orientation and training

transfer. These results suggest that although trainees with

high self-efficacy and motivation to transfer may engage

more in thinking about transferring their skills, their

heightened affective and motivational states could be

sufficient to successfully apply their learning in a work

setting. That is, training cognitions might not be a

necessary step for trainees that are confident in their

task performance and are motivated to apply their

training on the job. However, the predictive power of

learning goal orientation is realized through its impact on

training-related cognitions.

Theoretical arguments exist for the idea that skill

development is continuous and with time trainees de-

velop more elaborate strategies and approaches (e.g.,

Anderson, 1982). Moreover, this result is in line with

several lines of research: trainees with a learning goal

orientation are interested in developing competency

(rather than outperforming others), and thus are more

willing to consider how they may increase their know-

ledge and ability for a given task (Schmidt & Ford, 2003).

Meta-analytic work also shows that goal orientation is

positively correlated with both learning strategies and

feedback seeking (Payne, Youngcourt, & Beaubien, 2007).

According to our results, this type of cognitive elabora-

tion is enhanced through trainees learning goal orienta-

tion. It remains to be determined whether other types of

mediators (e.g., of a more affective or motivational rather

than of cognitive nature) would intervene between self-

efficacy and training motivation, respectively, and training

transfer.

4.3. Limitations

The results presented above need to be seen in the light

of the study limitations. First, strong causal inferences are

tentative, given the nonexperimental nature of the study,

although the longitudinal nature of the data mitigates this

concern to some extent. Our results can be further

supported by studies replicating the results using other

longitudinal studies, or using (quasi-) experimental de-

signs. Second, we collected the data from one organiza-

tion, which makes us cautious about proposing broad

generalizations of the findings until the results are

replicated and extended in other settings. Third, we

adjusted the original model to include direct relationships

between some of the individual factors and transfer.

Although direct relationships have been observed in

previous studies (e.g., Colquitt et al., 2000), the decision

for adjustment was also based on the outcomes of

statistical analysis. Therefore, the final model should be

replicated in another sample.

Finally, we collected data from one source: the employ-

ees attending training, reporting on their social context,

on individual factors, their cognitions, and engagement in

skill transfer. Despite the fact that single-source bias may

be less problematic than commonly believed (e.g., Spec-

tor, 2006), we collected data at three different time

periods and used current best practices (e.g., providing

confidentiality, having respondents complete the ques-

tionnaire for the criterion, and predictor variables in

different settings; Podsakoff et al., 2003) to mitigate such

issues. Furthermore, research that has compared self-

report and objective outcome measures have shown

these to yield similar results. In a meta-analysis examining

the relationship between training and organizational out-

comes (human resource, organizational performance,

and financial data), Tharenou et al. (2007) found similar

bivariate correlations and effect sizes between training

outcomes and self-report and objective measures of

organizational factors. Even though we recognize that

perceptual scores may inflate the overall effect (as

compared with objective measures), the longitudinal

design of the current study lessens this chance compared

with self-report data collected at a single time. Future

studies, however, may use multisource data (e.g., includ-

ing data on training transfer obtained from supervisors,

peers, or customers, if these have the opportunity to

observe the employee engaging in the respective skills,

and archival data).





4.4. Significance and implications to practice

Despite these limitations, the study has practical implica-

tions related to the support of training transfer. First, and

consistent with extant literature, supervisory support

had a strong relationship with individual factors which

then influenced training transfer. Supervisors can show

their support for trainee transfer of training by providing

feedback on performance, opportunities to perform,

consequences and accountability goals, and assistance

with managing workload during training (Burke & Bald-

win, 1999; Lim & Morris, 2006; Smith-Jentsch, Salas, &

Brannick, 2001; Taylor, Russ-Eft, & Chan, 2005). How-

ever, many managers are either unaware of or not

required to support trainee performance after training,

which supports the myth that the training experience is

sufficient for performance to occur. Broad (2005) sug-

gests that managers be involved before, during, and after

the training experience to influence training transfer,

which may require training professionals to coach man-

agers on how to best support trainee performance.

Although the direct supervisor often represents a central

source of support for trainees, other colleagues to whom

trainees have a closer relationship might also influence

training transfer. In Burke and Hutchins (2007) compre-

hensive review of transfer literature, several studies

found peer support equal to or more important than

supervisor support to training transfer. Our results

suggest that managers continue to be strong influence

on trainee performance, and thus should understand how

to support training transfer. This is important, when

attempting to apply our findings to practical situations,

especially when considering the difficulties practitioners

can have in determining the main predictors of transfer

(Burke & Hutchins, 2008).

Supervisors also play a major role in influencing trai-

nees goal orientation, which has been found to be a

consistent predictor of training transfer in the transfer

literature (Silver et al., 2006). Our results indicated that

only supervisory support was related to learning goal

orientation, suggesting that the relationship between

supervisors and employees may influence goal orienta-

tion. This is consistent with research linking leader-

member exchange, goal orientation, and performance.

Specifically, Janssen and Van Yperen (2004) suggested that

supervisors may influence employees learning orientation

though assigning challenging opportunities, delegating

responsibility and autonomy in carrying out tasks, and

assisting individuals with overcoming barriers to perfor-

mance. Other strategies supervisors can use to influence

learning goal orientation include rewarding employee

effort and task mastery (rather than strictly performance),

encouraging personal development and experimentation,

and supporting enhanced cognitive engagement, including

self-evaluation opportunities to reflect on performance

(Ames, 1992; Stevens & Gist, 1997).

Finally, our study suggests that individual factors may

influence training transfer differently, and thus should be

considered in applying interventions to support training

transfer. Training cognitions mediated the relationship

between learning goal orientation and transfer exclu-

sively, indicating that learning goal orientation operates

through its impact on training-related cognitions. An

exception would be if the trainees already have high

self-efficacy and/or motivation to transfer as evidenced

by their direct relationship with training transfer in our

study. In empirical studies, several authors found that

cognitive or mental rehearsal and behavioral practice

strategies during training are positively correlated with

transfer (Ford & Kraiger, 1995; Holladay & Quinones,

2003; Warr & Allan, 1998). These include cognitive

rehearsal and elaboration (Schmidt & Ford, 2003), goal-

setting (Brown, 2005; Locke & Latham, 2002), and other

self-management techniques (such as relapse prevention;

Burke & Baldwin, 1999) that help trainees consider how

they can generalize and apply their training knowledge to

the work setting. In the light of our findings, these are

most beneficial for trainees with high levels of learning

goal orientation, who may benefit from being guided into

engaging in maintenance activities.

4.5. Future research

The current study can also open new venues of investiga-

tion. First, we conceptualized POS without differentiating

support originating from the organization, work unit, or

ones team, which may not match the way employees

think about their workplace. Levels of proximity can be

embedded further by distinguishing between support

originating from the organization, unit, and immediate

team. Such differences may help produce more refined

models: it is possible for self-efficacy to be a factor of

work unit or team support, given the importance of

vicarious learning and mastery originating from within the

proximal workgroup (Bandura, 1997). Additional aspects

of support, such as the extent to which training is offered,

employees have autonomy, and are provided the requisite

technology (Salanova et al., 2005) can be tested in future

studies. Along the same line of thought, support can

originate not only from the organization and the super-

visor, but also from ones coworkers (e.g., Chiaburu &

Harrison, 2008; Pidd, 2004). These may have an even

stronger effects on proximal outcomes, including focals

employees self-efficacy, motivation, and goal orientation.

Moving from predictors to processes, even though we

uncovered one mediating mechanism in the form of

trainee cognitions, additional explanations may be found

if other processes are explicitly theorized. Considering

their focus on the task to be executed, trainees with high

levels of self-efficacy and motivation to transfer may be

helped in reaching training transfer by reaching high

performance levels in intermediate stages of transfer




(1 month after training) or through motivational rather

than cognitive actions and states, in the light of evidence

suggesting that motivational aspects are more likely to

mediate the relationship between self-efficacy and per-

formance (Chen, Gully, & Eden, 2004).

Finally, it is worth examining how the present model

generalizes to a range of different skills and tasks to be

performed on the job. The current skill set involved

engagement in behaviors directed at internal or external

customers. Skills and their uses may be considered

episodic (Baldwin & Magjuka, 1997), with employees

having periods of time when the skills would not be

used, punctuated by interactions where skill utilization is

necessary. This intermittent structure may have played a

role in enhancing training transfer for employees who

engaged more in training cognitions and maintained their

skills. It could be useful to test the model on skills used in

a more or less permanent manner, to determine whether

the advantage of cognitive engagement remains un-

changed. In addition, given existing evidence that self-

efficacy has a stronger relationship with performance for

skills of lower complexity (Chen, Casper, & Cortina,

2001), the model can be tested on a variety of skills

varying from simple to more elaborate.

5. Conclusion

Training transfer continues to be a problem for organiza-

tions seeking to maximize training effectiveness.

Although research has identified factors at the individual,

training, and work/organizational level as influencing

transfer, the extent to which trainees perceive support

in the work setting continues to be a consistent predictor

of training transfer. Our study contributes to the current

knowledge base by testing a model of social support on

training transfer, and demonstrating how support ema-

nating from supervisors and the organization influence

trainee self-efficacy, motivation, and goal orientation in

different ways. Our results suggest new venues of

investigation, including testing models involving skills

from simple to complex and focus on mediators to

explain the intervening processes. In addition to refocus-

ing on social context factors as predictors of transfer, we

offer targeted suggestions to influence training transfer

optimization in organizational settings.

Note

1. The authors contributed equally to this paper.

References

Ames, C. (1992). Classrooms: Goals, structures, and student

motivation. Journal of Educational Psychology, 84, 261271.

Ames, C., & Archer, J. (1988). Achievement goals in the class-

room: Students learning strategies and motivation processes.

Journal of Educational Psychology, 80, 260267.

Anderson, J.R. (1982). Acquisition of a cognitive skill. Psycholo-

gical Review, 89, 369406.

Arbuckle, J. (2006). Amos 7.0 users guide. Spring House, PA:

Amos Development Corporation.

Aselage, J., & Eisenberger, R. (2003). Perceived organizational

support and psychological contracts: A theoretical integra-

tion. Journal of Organizational Behavior, 24, 491501.

Axtell, C.M., & Maitlis, S. (1997). Predicting immediate and

longer-term transfer of training. Personnel Review, 26, 201213.

Axtell, C.M., Maitlis, S., & Yearta, S.K. (1997). Predicting

immediate and longer term transfer of training. Personnel

Review, 26, 201213.

Baldwin, T.T., & Ford, J.K. (1988). Transfer of training: A review

and directions for future research. Personnel Psychology, 41,

63105.

Baldwin, T.T., & Magjuka, R.J. (1997). Training as an organiza-

tional episode: Pretraining influences on trainee motivation.

In J.K. Ford, S.W.J. Kozlowski, K. Kraiger, E. Salas, & M.S.

Teachout (Eds.), Improving training effectiveness in work organi-

zations (pp. 99128). Mahwah, NJ: Lawrence Erlbaum Associ-

ates.

Bandura, A. (1986). Social foundations of thought and action: A

social cognitive. Englewood Cliffs, NJ: Prentice Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. New

York, NY: WH Freeman.

Baron, R.M., & Kenny, D.A. (1986). The moderatormediator

variable distinction in social psychological research: Concep-

tual, strategic, and statistical considerations. Journal of Person-

ality and Social Psychology, 51, 11731182.

Broad, M.L. (2005). Beyond transfer of training: Engaging systems to

improve performance. San Francisco, CA: John Wiley.

Brown, T. (2005). Effectiveness of distal and proximal goals as

transfer of training intervention: A field experiment. Human

Resource Development Quarterly, 16, 369387.

Brown, T.C., & Morrissey, L.M. (2004). The effectiveness of

verbal self guidance as a transfer of training intervention: Its

impact in presentation performance, self-efficacy, and anxiety.

Innovations in Education and Teaching International, 34, 276

285.

Browne, M.W., & Cudeck, R. (1993). Alternative ways of

assessing model fit. Sociological Methods and Research, 21,

230259.

Burke, L.A., & Baldwin, T.T. (1999). Workforce training transfer:

A study of the effect of relapse prevention training and

transfer. Human Resource Management, 38, 227243.

Burke, L.A., & Hutchins, H.M. (2007). Training transfer: An

integrative literature review. Human Resource Development

Review, 6, 263296.

Burke, L.A., & Hutchins, H.M. (2008). A study of best practices

in training transfer and proposed model of transfer. Human


Chen, G., Casper, W.J., & Cortina, J.M. (2001). The roles of self-

efficacy and task complexity in the relationships among

cognitive ability, conscientiousness, and work-related perfor-

mance: A meta-analytic examination. Human Performance, 14,

209230.





Chen, G., Gully, S.M., & Eden, D. (2004). General self-efficacy

and self-esteem: Toward theoretical and empirical distinction

between correlated self-evaluations. Journal of Organizational

Behavior, 25, 375395.

Cheng, E.W.L., & Ho, D.C.K. (2001). A review of transfer of

training studies in the past decade. Personnel Review, 30, 102118.

Chiaburu, D.S., & Harrison, D.A. (2008). Do peers make the

place? Conceptual synthesis and meta-analysis of coworker

effects on perceptions, attitudes, OCBs, and performance.

Journal of Applied Psychology, 93, 10821103.

Chiaburu, D.S., & Lindsay, D. (2008). Can do or will do? The

importance of self-efficacy and instrumentality for training

transfer. Human Resource Development International, 11, 199

206.

Chiaburu, D.S., & Marinova, S.V. (2005). What predicts skill

transfer? An exploratory study of goal orientation, training

self-efficacy and organization supports. International Journal of

Training and Development, 9, 110123.

Chiaburu, D.S., & Tekleab, A.G. (2005). Individual and contex-

tual influences on multiple dimensions of training effective-

ness. Journal of European Industrial Training, 29, 604626.

Clarke, N. (2002). Job/work environment factors influencing

training effectiveness within a human service agency: Some

indicative support for Baldwin and Fords transfer climate

construct. International Journal of Training and Development, 6,

146162.

Colquitt, J.A., LePine, J.A., & Noe, R.A. (2000). Toward an

integrative theory of training motivation: A meta-analytic

path analysis of 20 years of research. Journal of Applied

Psychology, 85, 679707.

Coyle-Shapiro, J.A.M. (2002). A psychological contract perspec-

tive on organizational citizenship behavior. Journal of Organi-

zational Behavior, 23, 927947.

Cromwell, S.E., & Kolb, J.A. (2004). An examination of work-

environment support factors affecting transfer of supervisory

skills training to the workplace. Human Resource Development

Quarterly, 15, 449471.

Dragoni, L. (2005). Understanding the emergence of state goal

orientation in organizational work groups: The role of

leadership and multilevel climate perceptions. Journal of

Applied Psychology, 90, 10841095.

Dupeyrat, C., & Marine, C. (2005). Implicit theories of intelli-

gence, goal orientation, cognitive engagement, and achieve-

ment: A test of Dwecks model with returning to school

adults. Contemporary Educational Psychology, 30, 4359.

Dweck, C.S. (1989). Motivation. In A. Lesgold & R. Glaser (Eds.),

Foundations for a psychology of education (pp. 87136). Hills-

dale, NJ: Lawrence Erlbaum Associates.

Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach

to motivation and personality. Psychological Review, 95, 256

273.

Egan, T.M., Yang, B., & Bartlett, K.R. (2004). The effectives of

organizational learning culture and job satisfaction on motiva-

tion to transfer learning and turnover intention. Human


Eisenberger, R., Armeli, S., Rexwinkel, B., Lynch, P.D., &

Rhoades, L. (2001). Reciprocation of perceived organizational

support. Journal of Applied Psychology, 86, 4251.

Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D.

(1986). Perceived organizational support. Journal of Applied


Elliot, A., & McGregor, H. (2001). A 2X2 achievement foal

framework. Journal of Personality and Social Psychology, 80, 501

519.

Elliot, A., McGregor, H., & Gable, S. (1999). Achievement goals,

study strategies, and exam performance: A mediational

analysis. Journal of Educational Psychology, 91, 549563.

Enos, M.D., Kehrhahn, M.T., & Bell, A. (2003). Informal learning

and the transfer of learning: How managers develop profi-

ciency. Human Resource Development Quarterly, 14, 369387.

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

transfer of training. Journal of Management, 21, 125.

Fisher, S.L., & Ford, J.K. (1998). Differential effects of learner

effort and goal orientation on two learning outcomes.

Personnel Psychology, 51, 397420.

Ford, J.K., & Kraiger, K. (1995). The application of cognitive

constructs and principles to the Instructional systems model

of training: Implications for needs assessment, design, and

transfer. In C.L. Cooper & I.T. Robertson (Eds.), International

review of industrial and organizational psychology (10, pp. 148).

Chichester, UK: Wiley.

Ford, J.K., Kraiger, K., & Merritt, S.M. (2009). An updated review

of the multidimensionality of training outcomes: New direc-

tions for training evaluation research. In S.W.J. Kozlowski & E.

Salas (Eds.), Learning, training, and development in organizations.

Mahwah, NJ: SIOP Frontiers Book Series.

Ford, J.K., Smith, E.M., Weissbein, D.A., Gully, S.M., & Salas, E.

(1998). Relationships of goal orientation, metacognitive ac-

tivity, and practice strategies with learning outcomes and

transfer. Journal of Applied Psychology, 83, 218233.

Ford, J.R., & Weissbein, D.H. (1997). Transfer of training: An

updated review and analysis. Performance Improvement Quar-

terly, 10, 2241.

Frayne, C., & Latham, G.P. (1987). Application of social learning

theory to employee self-management of attendance. Journal of

Applied Psychology, 72, 387392.

Gaudine, A.P., & Saks, A.M. (2004). A longitudinal quasi-experi-

ment on the effects of posttraining transfer interventions.

Human Resource Development Quarterly, 15, 5776.

Gist, M.E. (1986). The influence of training method on self-

efficacy and idea generation among managers. Personnel


Gist, M.E., Bavetta, A.G., & Stevens, C.K. (1990). Transfer

training method: Its influence on skill generalization, skill,

repetition, and performance level. Personnel Psychology, 43,

501523.

Gist, M.E., & Mitchell, T.B. (1992). Self-efficacy: A theoretical

analysis of its determinants and malleability. Academy of

Management Review, 17, 183211.

Gist, M.E., Stevens, C.K., & Bavetta, A.G. (1991). Effects of self-

efficacy and post-training intervention on the acquisition and

maintenance of complex interpersonal skills. Personnel Psy-

chology, 44, 837861.

Graham, S., & Golan, S. (1991). Motivational influences on

cognition: Task involvement, ego involvement, and depth of




information processing. Journal of Educational Psychology, 83,

187194.

Guerrero, S., & Sire, B. (2001). Motivation to train from

the workers perspective: Example of French companies.

International Journal of Human Resource Management, 12,

9881004.

Hawley, J.D., & Barnard, J.K. (2005). Work environment char-

acteristics and implications for training transfer: A case study

of the nuclear power industry. Human Resource Development

International, 8, 6580.

Hirschfeld, R.R., Thomas, C.H., & McNatt, D.B. (2008).

Implications of self-deception for self-reported intrinsic and

extrinsic motivational dispositions and actual learning perfor-

mance: A higher-order structural model. Educational and

Psychological Measurement, 68, 154173.

Holladay, C.L., & Quinones, M.A. (2003). Practice variability and

transfer of training: The role of self-efficacy generality. Journal

of Applied Psychology, 88, 10941103.

Holton, E.F., Bates, R., & Ruona, W.E.A. (2000). Development of

a generalized learning transfer system inventory. Human


Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in

covariance structure analysis: Conventional criteria versus

new alternatives. Structural Equation Modeling, 6, 155.

Janssen, O., & Van Yperen, N.W. (2004). Employees goal

orientations, the quality of leadermember exchange and

the outcomes for job performance and job satisfaction.

Academy of Management Journal, 47, 368384.

Kirwan, C., & Birchall, D. (2006). Transfer of learning from

management development programmes: Testing the Holton

model. International Journal of Training and Development, 10,

552268.

Kontoghiorghes, C. (2001). Factors affecting training effective-

ness in the context of the introduction of new technology A

US case study. International Journal of Training and Development,

5, 248260.

Kontoghiorghes, C. (2002). Predicting motivation to learn

and motivation to transfer learning back to the job in a

service organization: A new systemic model for training

effectiveness. Performance Improvement Quarterly, 15, 114

129.

Kottke, J., & Sharafinski, C.E. (1988). Measuring perceived

supervisory and organizational support. Educational and Psy-

chological Measurement, 4, 10751079.

Latham, G.P., & Frayne, C.A. (1989). Self-management training

for increasing job attendance: A follow-up and a replication.


Lim, D.H., & Morris, M.L. (2006). Influence of trainee character-

istics, instructional satisfaction, and organizational climate on

perceived learning and training transfer. Human Resource

Development Quarterly, 17, 85115.

Locke, E.A., & Latham, G.P. (2002). Building a practically useful

theory of goal setting and task motivation: A 35-year odyssey.

American Psychologist, 57, 705717.

Machin, M.A., & Fogarty, G.J. (2004). Assessing the antecedents

of transfer intentions in a training context. International Journal

of Training and Development, 8, 222236.

Mesmer-Magnus, J., & Viswesvaran, C. (2007). Inducing maximal

versus typical learning through the provision of a pretraining

goal orientation. Human Performance, 20, 205222.

Ng, T.W.H., & Sorensen, K.L. (2008). Toward a further under-

standing of the relationships between perceptions of support

and work attitudes: A meta-analysis. Group Organization

Management, 33, 243268.

Nijman, D.J.M., Nijhof, W.J., Wognum, A.A.M., & Veldkamp, B.P.

(2006). Exploring differential effects of supervisor support on

transfer of training. Journal of European Industrial Training, 30,

529549.

Noe, R.A. (1986). Trainee attributes: Neglected influences on

training effectiveness. Academy of Management Review, 11,

736749.

Noe, R.A., & Wilk, S.L. (1993). Investigation of the factors that

influence employees participation in development activities.


Orvis, K.A., Fisher, S.L., & Wasserman, M.E. (2009). Power to

the people: Using learner control to improve trainee reac-

tions and learning in web-based instructional environments.


Paradise, A. (2007). U.S. learning and development expenditure

rises to $129.6 billion. T&D, 61, 6066.

Payne, S., Youngcourt, S., & Beaubien, J.M. (2007). A meta-

analytic examination of the goal orientation nomological net.


Pidd, K. (2004). The impact of workplace support and identity

on training transfer: A case study of drug and alcohol safety

training in Australia. International Journal of Training and Devel-

opment, 8, 274288.

Pintrich, P. (2000). Multiple goals, multiple pathways: The role of

goal orientation in learning and achievement. Journal of

Educational Psychology, 92, 544555.

Pintrich, P.R., & De Groot, E. (1990). Motivational and self-

regulated learning components of classroom academic per-

formance. Journal of Educational Psychology, 82, 3350.

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.


Pugh, K.J., & Bergin, D.A. (2006). Motivational influences on

transfer. Educational Psychologist, 41, 147160.

Rhoades, L., & Eisenberger, R. (2002). Perceived organizational

support: A review of the literature. Journal of Applied Psychol-

ogy, 87, 698714.

Richman-Hirsch, W.L. (2001). Posttraining interventions to

enhance transfer: The moderating effects of work environ-

ments. Human Resource Development Quarterly, 12, 105120.

Rodgers, R., & Hunter, J.E. (1991). Impact of management by

objectives on organizational productivity. Journal of Applied


Rouiller, J.Z., & Goldstein, I.L. (1993). The relationship between

organizational transfer climate and positive transfer of train-

ing. Human Resources Development Quarterly, 4, 377390.

Russell, J.S., Terborg, J.R., & Powers, M.L. (1985). Organizational

performance and organizational level training and support.


Salanova, M., Agut, S., & Peiro, J. (2005). Linking organizational

resources and work engagement to employee performance

and customer loyalty: The mediation of service climate.


Schmidt, A.M., & Ford, J.K. (2003). Learning within a learner

control environment: The interactive effects of goal orienta-





tion and metacognitive instruction on learning outcomes.


Schwarz, N., Knauper, B., Oyserman, D., & Stich, C. (2008). The

psychology of asking questions. In E.D. de Leeuw, J.J. Hox,

& D.A. Dillman (Eds.), International handbook of survey meth-

odology (pp. 1834). New York, NY: Lawrence Erlbaum

Associates.

Seyler, D.L., Holton, E.F. III, Bates, R.A., Burnett, M.F., &

Carvalho, M.A. (1998). Factors affecting motivation to trans-

fer training. International Journal of Training and Development, 2,

1617.

Shore, L.M., Barksdale, K., & Shore, T. (1995). Managerial

perceptions of employee commitment to the organization.

Academy of Management Journal, 38, 15931615.

Silver, L.S., Dwyer, S., & Alford, B. (2006). Learning and

performance goal orientation of salespeople revisited: The

role of performance-approach and performance-avoidance

orientations. Journal of Personal Selling and Sales Management,

36, 2738.

Smith-Jentsch, K.A., Salas, E., & 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, 279292.

Sobel, M.E. (1982). Asymptotic confidence intervals for indirect

effects in structural equation models. In S. Leinhart (Ed.),

Sociological methodology 1982 (pp. 290312). San Francisco,

CA: Jossey-Bass.

Spector, P.E. (2006). Method variance in organizational research.

Organizational Research Methods, 9, 221232.

Stevens, C.K., & Gist, M.E. (1997). Effects of self-efficacy and

goal orientation training on negotiation skill maintenance:

What the mechanisms? Personnel Psychology, 50, 955978.

Tai, W.-T. (2006). Effects of training framing, general self-efficacy

and training motivation on trainees training effectiveness.

Personnel Review, 35, 6165.

Tannenbaum, S.I., Mathieu, J.E., Salas, E., & Cannon-Bowers, J.A.

(1991). Meeting trainees expectations: The influence of

training fulfillment on the development of commitment,

self-efficacy, and motivation. Journal of Applied Psychology, 76,

759769.

Tansky, J.W., & Cohen, D.J. (2001). The relationship between

organizational support, employee development, and organi-

zational commitment: An empirical study. Human Resource

Development Quarterly, 12, 285300.

Taylor, P.J., Russ-Eft, D.F., & Chan, D.W.L. (2005). A meta-analytic

review of behavior modeling training. Journal of Applied


Tharenou, P., Saks, A.M., & Moore, C. (2007). A review and

critique of research on training and organizational-level out-

comes. Human Resource Management Review, 17, 251273.

Tracey, J.B., Hinkin, T.R., Tannenbaum, S., & Mathieu, J.E. (2001).

The influence of individual characteristics and the work

environment on varying levels of training outcomes. Human


Tracey, J.B., Tannenbaum, S.I., & Kavanagh, M.J. (1995). Applying

trained skills on the job: The importance of the work

environment. Journal of Applied Psychology, 80, 239252.

Turnley, W.H., Bolino, M.C., Lester, S.W., & Bloodgood, J.M.

(2003). The impact of psychological contract fulfillment on

the performance of in-role and organizational citizenship

behaviors. Journal of Management, 29, 187206.

Tziner, A., Fisher, M., Senior, T., & Weisberg, J. (2007). Effects of

trainee characteristics on training effectiveness. International

Journal of Selection and Assessment, 15, 167174.

van der Klink, M., Gielen, E., & Nauta, C. (2001). Supervisory

support as a major condition to enhance transfer. International

Journal of Training and Development, 5, 5263.

van Merrienboer, J.J.G. (1997). Training complex cognitive skills:

A four-component instructional design model for technical

training. Englewood Cliffs, NJ: Educational Technology

Publications.

Viswesvaran, C., Sanchez, J.I., & Fisher, J. (1999). The role of

social support in the process of work stress: A meta-analysis.

Journal of Vocational Behavior, 54, 314334.

Warr, P.B., & Allan, C. (1998). Learning strategies and occupa-

tional training. In C.L. Cooper & I.T. Robertson (Eds.),

International review of industrial and organizational psychology

(pp. 83121). Chichester, UK: Wiley.

Wolters, C.A. (2004). Advancing achievement goal theory:

Using goal structures and goal orientations to predict stu-

dents motivation, cognition, and achievement. Journal of

Educational Psychology, 96, 236250.

Xiao, J. (1996). The relationship between organizational factors

and the transfer of training in the electronics industry in

Shenzhen, China. Human Resource Development Quarterly, 7,

5573.

Yarnall, J. (1998). Line managers as career developers: Rhetoric

or reality? Personnel Review, 27, 378395.




social support

Documents