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The online version of this article can be found at:

DOI: 10.1177/0149206395021001011995 21: 1Journal of Management

KudischJeffrey D. Facteau, Gregory H. Dobbins, Joyce E.A. Russell, Robert T. Ladd and Jeffrey D.

Motivation and Perceived Training TransferThe influence of General Perceptions of the Training Environment on Pretraining

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Journal of Management

1995, Vol. 21, No. I, 1-25

The nf luence of General Percept ions of

the Train ing nvironment on Retrain ing

Motivat ion and Perceived Training Trans fer

Jeffrey D. Facteau

Gregory H. Dobbins

Joyce E. A. Russell

Robert T. Ladd

Jeffrey D. Kudisch

l e Un iversity of Tennessee

The present study was conducted to determine whether trainees

general beliefs about training affect

pretraining

motivation and transfer

of traini ng in a large-scale traini ng curr iculum. I n addition, the

inf luence of social support for traini ng from four organizational

constituents (top management, supervisors, peers, and subordinates)

and task constraints in the work environment on pretrain ing

motivation and training transfer were evaluated. Nine hundred six ty-

seven managers and supervisors completed a questionnaire that

assessed 14 constructs. Structural equations analysis with L ISREL VI I

indicated that the overall r eputation of traini ng, intr insic and

compliance incentives, organizational commitment, and three social

support variables (subordinate, supervisor, and top management

support) were predictive of pretraini ng motivation. I n additi on,

pretrain ing motivation and subordinate, peer, and supervisor support

were predictive of managers perceived train ing transfer. Thesef indings

suggests that previous theory and research (e.g., Noe, 1986; Noe &

Schmitt, 1986) serve as a useful heur istic for predicti ng the effects of

general beli efs about traini ng on training eff ectiveness. Implications of

the-findings for futur e research and practice are discussed.

Recently, it has been estimated that organizations spend as much as 200 billion

annually on workforce training (McKenna, 1990). In the 1970s, the average

training expenditure per employee was approximately 75 to 100. Today, some

large corporations (e.g., IBM) budget as much as 2,000 annually per employee

on formal education and training (Wexley & Latham, 1991).

Not only do organizations today rely extensively on training, there is

considerable reason to believe that the significance of training for organizations

will continue to increase in the future. Several projected changes in the U. S.

Direct all correspondence to: Jeffrey D. Facteau, The University of Tennessee, Department of Management,

408 Stokely Management Center, Knoxville, TN 379964545.

Copyright Q 1995 by J AI Press Inc. 0149 2063

I

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2

FACTEAU DOBBINS RUSSELL LADD AND KUDISCH

labor force and work place are expected to account for this increased

importance. First, it is estimated that the proportion of entry-level youth will

decline and that middle-aged workers will represent a greater percentage of the

U. S. workforce. Second, there will continue to be a decline in the manufacturing

sector of the economy with a corresponding increase in the high technology,

service, and information sectors. Also, rapid technological development will

place greater demands on workers. In addition, the increased emphasis on

improving quality of services and products due to global competition is expected

to continue to change the way work is accomplished (e.g., more self-managed

work teams). Taken together, these changes will result in greater competition

for qualified entry-level employees and a need for organizations to better utilize

available labor. As such, organizations will need to enhance their recruitment

efforts to attract qualified entry-level employees and continually train and

retrain their current employees (c.f. Goldstein & Associates, 1989; Johnston &

Packer, 1987; London, 1989). Recently, some organizations have begun to takes

these initiatives (Ford, Major & Seaton, 1991).

Training Effectiveness

Given the significance of formal training programs for organizational

effectiveness, it is imperative that organizations design and implement training

programs in the most effective manner, and that they understand the factors

that contribute to training effectiveness. This is especially important given the

finding that only ten percent of training expenditures have been shown to result

in behavioral changes back on the job (Georgenson, 1982). In addition, a

frequent criticism of training practice and research is its susceptibility to fads

and its generally atheoretical approach (c.f. Campbell, 1971). For example,

some practitioners have attempted to increase the effectiveness of training by

utilizing sophisticated training techniques without regard for their actual need.

Others have focused on arranging the best training environment (e.g., Wexley,

1984). Without a theoretical basis for studying these techniques and training

environments, however, practitioners and researchers are often at a loss to

explain why training programs are effective or to predict their effectiveness in

other settings or for other trainees (Baldwin & Ford, 1988; Noe, 1986; Wexley

& Baldwin, 1986). Recognizing this situation in the training and development

literature, Tannenbaum and Yukl called for a paradigm shift to research

designed to understand

. . .why, when, and for whom a particular type of

training is effective (1992, p. 433).

Recent attempts to understand the factors that influence training

effectiveness have suggested that pretraining motivation may influence

important training outcomes. For example, Baldwin, Magjuka and Loher

(1991) found that pretraining motivation was related to actual learning in a

training program designed to improve skills in conducting performance

appraisals and in providing feedback. Another study revealed that pretraining

motivation was related to performance in a classroom environment (Baldwin

& Karl, 1987). Finally, Mathieu, Tannenbaum, and Salas (1992) found that

JOURNAL OF MANAGEMENT VOL. 21 NO. I 1995



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PERCEPTIONS OF THE TRAINING ENVIRONMENT

3

pretraining motivation for a proofreading skills program predicted learning and

subsequent performance on a work sample test.

These studies indicate that pretraining motivation has an important

influence on the extent to which trainees actually learn the material presented

to them during a training program. Furthermore, the amount of learning that

occurs during training may influence other indicators of training effectiveness,

such as trainees behavioral changes on the job and other organizational criteria

(e.g., absenteeism, productivity) (c.f. Goldstein, 1993). Thus, because of its

relationship to these training outcomes, pretraining motivation appears to be

an important antecedent to training effectiveness.

While pretraining motivation may influence training effectiveness,

relatively little research has examined the factors which contribute to trainees

pretraining motivation. The purpose of the present study was to examine the

extent to which employees attitudes and beliefs about training influence their

pretraining motivation, and their perceptions of the extent to which they are

able to transfer training back to their job. Several predictors of these variables

were examined in the study, including training attitudes, individual attitudes,

and social support for learning and transfer.

Training Attitudes

Perceived training reputation.

Prior to actually taking a training course,

an employee often has an expectation about the quality of the course and its

job relevance. Such expectations may be based upon past experiences with a

specific training program or may actually come from comments made by

coworkers who have already completed the training. If training is perceived as

a waste of time, employees may lack pretraining motivation irrespective of the

actual quality of the training program. In other words, the reputation of a

training program or training department should affect an employees pretraining

motivation. While other researchers have acknowledged the importance of

developing an understanding of factors that affect training motivation (e.g.,

Noe, 1986; Tannenbaum, Mathieu, Salas & Cannon-Bowers, 1991), research

has not examined the influence of the general reputation of training on

pretraining motivation. The first purpose of the present study was to test the

prediction that training reputation affects pretraining motivation.

Training incentives.

Training motivation should be affected by the extent

to which training is rewarded in the organization. Noes (1986) model of training

effectiveness proposed that rewards resulting from successful completion of

training influence individuals motivation to attend training and to learn from

it. In the present study, we assessed three types of training incentives: intrinsic

incentives (the extent to which training meets internal needs or provides

employees with growth opportunities), extrinsic incentives (the extent to which

training results in tangible external rewards such as promotions, pay raises, and

higher performance evaluations), and compliance (the extent to which training

is taken because it is mandated by the organization).

Based upon the work by Noe (1986), we expected that intrinsic incentives

and extrinsic incentives would be positively associated with pretraining




5/26


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5

Support for Learni ng and Trai ni ng Transfer

No (1986)

model proposed that environmental favorability should

affect pretraining motivation and transfer of training skills. Environmental

favorability is comprised of task constraints (e.g., lack of resources) and the

perceived social support for training. The social component is concerned with

employees perceptions of the extent to which the social context at work

supports training transfer. According to Noe, a supportive social context is

one in which employees believe that others provide them with opportunities

and reinforcement for practicing skills or for using knowledge acquired in

training.

Rouillier and Goldstein (1990) (cited in Goldstein, 1991) conceptualized

transfer climate in a similar manner by suggesting that it consists of two

components. The first, situational cues, refers to the extent to which aspects of

a situation encourage employees to use what has been learned in training (e.g.,

goal-setting, reducing employees workload so that they may become familiar with

new skills). The second, consequences, refers to the degree to which employees

are rewarded for applying what has been learned in training. These two views

(i.e., Noe, 1986; Rouillier & Goldstein, 1990) suggest that the social context at

work might support training in two ways, either by eliciting trained skills via a

host of antecedent variables (e.g., opportunities, situational cues), or by rewarding

these behaviors via a host of consequent variables (i.e., reinforcement).

In addition to the type of social support that exists for transferring trained

behaviors (i.e., antecedents, consequences), a variety of different sources of

social support may exist. An examination of the training literature suggests that

there are several potentially important sources of social support for training.

These include top management, supervisors, peers, and subordinates (c.f.

Baldwin & Ford, 1988; Goldstein & Musicante, 1986; Noe, 1986; Noe &

Schmitt, 1986). It seems likely, however, that the various sources of social

support may have differential effects on important training outcomes. For

example, peer support may be more important for predicting training transfer

than is top management support. Hence, the present study will determine the

independent and possibly differential effects of subordinate support, peer

support, supervisor support, and top management support on training transfer.

The task component of environmental favorability refers to the extent to

which characteristics of the work environment (e.g., tools and equipment,

materials and supplies, financial resources, etc.) facilitate or constrain

employees ability to transfer the skills learned in training back to their job.

Mathieu et al. (1992) found that task constraints were marginally related to

training motivation. Other researchers (e.g., Noe & Schmitt, 1986; Williams et

al., 1991) have employed separate measures of social support and task

constraints, but collapsed the scales to form a single variable, which was labeled

environmental favorability. From a theoretical standpoint, it may be that task

constraints have a different effect on transfer than social constraints. For this

reason, measures of task constraints and the different facets of social support

were analyzed separately in the present study.




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6 FACTEAU DOBBINS RUSSELL LADD AND KUDISCH

The social and task support measures may also affect pretraining

motivation. If employees believe that training will not transfer back to the

job due to either nonsupportive peers, subordinates, supervisors,

management, or a lack of resources (task constraints), they should be less

motivated to attend and learn from training. Hence, the present study

examined the effects of task constraints and the four social support variables

(subordinate, peer, supervisor and top management) on training motivation

and perceived training transfer.

Overview of the Study

In summary, the present study was conducted to determine the effects of

employees attitudes and beliefs about training in general on pretraining

motivation and perceived training transfer. Training motivation was the

primary criteria since recent research has shown that trainees who enter training

with high levels of pretraining motivation learn more and are more likely to

complete training than their less motivated peers (e.g., Baldwin et al., 1991;

Hicks & Klimoski, 1987). Figure 1 summarizes the predictions of the study.

While researchers have not recognized that the general reputation of training

may exert strong effects of training motivation, we expected such a relationship

in the present study. In addition, consistent with past research, we expected

incentives, career exploration and planning, and organizational commitment

to affect pretraining motivation. Furthermore, we differentiated the social

support construct into four predictors. Specifically, new scales were developed

for examining employees perceptions of different sources of social support (i.e.,

top management, supervisors, peers, subordinates) within the organization.

These scales allowed for an examination of the possibility that different sources

of social support have unique or differential effects on employees pretraining

motivation and training transfer.

The results of the study should have important theoretical and applied

significance. From the theoretical perspective, the findings may serve to

support several links in Noes (1986) model of training effectiveness. In

addition, several additional variables (e.g., training reputation) were postulated

to predict training motivation. Finally, the study explored whether the various

social support factors differentially affect training motivation and training

transfer.

The study also has implications for organizational practices. For example,

if training reputation affects training motivation, then organizations should be

concerned about general impressions of available training programs and the

training department prior to actual training. Irrespective of the actual quality

of training, employees may not be motivated if they perceive training programs

as ineffective and irrelevant to theirjobs. Similarly, if the various support factors

have independent influences on pretraining motivation and training transfer,

then organizations may be able to target organizational development efforts

at the support factors that are most critical.

JOURNAL OF MANAGEMENT VOL. 21 NO. 1 1995



8/26


Note:

The nature of the relationship expected among constructs is indicated by a -t or -.

Figure 1. Hypothesized Model

Methods

Subj ects

Subjects consisted of 967 managers and supervisors employed by a

southeastern state government. These subjects, 61% of whom were male, held

management positions in 37 different departments within state government (e.g.,

Education, Finance and Administration, Labor, etc.). Eighty seven percent of

the subjects were Caucasian and nine percent were African-American. The

remaining four percent either represented another racial group (e.g., Native

American, Asian) or did not report their racial background. Fifty one percent

of the sample held first-line supervisory positions, while 31% and 15% of the

sample held middle-level and upper-level management positions, respectively.

Subjects average tenure with state government was 16.34 years (SIX8.16) and

average job tenure was 6.51 years (SD=5.44). Subjects average age was 45.5

years (SDx8.7). Finally, subjects responses to an item asking them to report

their highest educational attainment were as follows: high school degree (150/o),

trade/technical degree (5%), some college (20 @1), ssociate degree (5%), four




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8 FACTEAU DOBBINS RUSSELL LADD AND KUDISCH

year college degree (23%), some graduate work (90/o), nd graduate degree (18%).

The remaining subjects (5%) did not respond to this item. The median

educational level was the completion of a four year college degree.

Procedure

The current study was conducted as part of a large scale training needs

assessment to identify the training needs and curricula for all levels of

management within state government. As part of the needs assessment, a

comprehensive survey was distributed to a random sample of 1,700 supervisors

and managers. The survey requested managers to provide information about

their perceived training needs, training preferences, and their attitudes about

training, the organization, and their job. Managers completed the surveys at

work and were assured of anonymity and confidentiality of their responses.

Completed surveys were returned directly to the researchers. Of those sampled,

1,089 managers returned usable surveys (64% response rate). Because the current

research focused upon managers attitudes and perceptions of the states

management training curriculum, only those who had taken one or more of

the courses in the curriculum were included in the analyses. Based upon this

criterion, 122 managers who had not yet taken any training in the curriculum

(because they were new to their position) were eliminated from the sample.

Hence, the results of this study were based on a total sample of 967 supervisors

and managers.

Measur es

In order to test the hypotheses of interest in this study, measures of fourteen

distinct theoretical constructs were included on the questionnaire. These

constructs were measured with a total of 85 items. The number of items

comprising each scale and a sample item are presented in Table 1. Responses

to all of the items on the questionnaire were made on five point Likert-type

scales (l=Strongly Disagree,

5=Strongly Agree). Unless indicated

otherwise, higher scores indicated greater levels of the variable measured.

Many of the constructs were assessed with scales that have been used in

previous research. Four items from Porter and Smiths (1970) scale were used

to assess

Organizational Commitment. Career Exploration was

measured with

scales from Stumpf, Colarelli and Hartmans (1983) career exploration survey.

Career PZanning was

assessed with a modified version of Goulds (1979) career

planning scale.

Pretraining Motivation

was assessed with items drawn from

several scales used in previous research (Baldwin & Karl, 1987; Hicks, 1984;

Noe & Schmitt, 1986). Finally,

Task Constraints

were assessed with a scale

based upon Peters and OConnors (1980) taxonomy of the situational factors

that may constrain individual performance.

Several constructs used were measured with scales that were designed

specifically for the current study. These include measures of training reputation,

training incentives, social support for training, and perceived training transfer.

Training Reputation.

It was expected that the overall reputation of state

supervisory and managerial training would influence managers pretraining




10/26


Table 1. Description of Scales Used in the Study

9

Scale

Number of

I tems

Sample I tem

Pretraining Motivation

Perceived Training Transfer

Training Reputation 6

Intrinsic Incentives 9

Compliance

Extrinsic Incentives

Career Exploration

Career Planning

Organizational Commitment

Subordinate Support

Peer Support

Supervisor Support

Top Management Support

Task Constraints

9

9

10

5

10

I try to learn as much as I can from training

courses.

The productivity of my subordinates has

improved due to the skills that I learned in

training courses.

Most supervisory and managerial training

courses are of the highest quality.

I take training because it provides me with

skills that allow me to be more effective on

the job.

I take training because it is mandated by state

government.

I take training because it increases my job

opportunities outside of state government.

I have often tried specific work roles just to

assess my skills and abilities.

I have a strategy for achieving my career goals.

I find that my values and the organizations

values are very similar.

My subordinates allow me to get accustomed

to using my new training skills on the job.

My peers encourage my efforts to incorporate

new procedures that I have learned in

training.

My supervisor is tolerant of changes that I

initiate as a result of learning new skills in

training.

Top management believes in the importance of

training for supervisors and managers.

Inadequate financial resources hamper my abil-

ity to apply new skills learned in training

back to my job.

motivation. A six item scale was developed to assess training reputation. The

items asked subjects to rate: (1) the overall quality of supervisory and managerial

training courses; (2) whether they would recommend these courses to their peers;

and (3) the extent to which these courses developed skills necessary for success

as a supervisor or manager in state government.

Training incentives.

Trainees may perceive a number of reasons for

attending training programs (Nordhaug, 1989). Three constructs thought to be

particularly relevant in the context of this study included intrinsic incentives,

extrinsic incentives, and compliance.

Intrinsic Incentives

measured the extent

to which managers believed that a variety of intrinsic benefits or outcomes were

likely to result from successful completion of the training.

Extrinsic Incentives

measured the extent to which managers believed that training would result in

extrinsic rewards and benefits. Finally,

Compliance

assessed the extent to which




11/26

10

FACTEAU DOBBINS RUSSELL LADD AND KUDISCH

managers attended supervisory and management training in order to satisfy

organizational mandates or requirements.

Social support for training.

Social support for training and transfer of

learned skills was viewed as a multidimensional construct. The extent to which

four different organizational groups were supportive of managers training

efforts was measured. These groups included the managerssubordinates, peers,

supervisors, and top management. Items were developed based upon a review

of relevant literature (Baumgartel & Jeanpierre, 1972; Baldwin & Ford, 1988;

Clark, 1990; Goldstein & Musicante, 1986; Noe, 1986). In general, these items

assessed the extent to which these sources: (1) provided opportunities for

managers to utilize trained skills; (2) were supportive of managers efforts to

apply trained skills back on the job (e.g., were tolerant of mistakes); and (3)

reinforced managers efforts to transfer skills to their job situation.

Perceived Training Transfer.

This scale measured the extent to which

managers believed that a variety of desirable outcomes (e.g., improved

performance, reduced turnover, etc.) have occurred as a result of their ability

to transfer the skills they have learned in supervisory and management training

back to the job. Items for this measure were based upon a review of the relevant

training and development literature (Noe, 1986; Tziner, Haccoun, & Kadish,

1991; Wexley & Baldwin, 1986).

The items in the transfer measure are presented in the Appendix. They

were constructed to maximize the validity of self-reports of training transfer.

For example, Dunning, Meyerowitz and Holzberg (1989) found that self-ratings

made on ambiguous scale anchors were more inflated and less accurate than

self-ratings made on specific scale anchors. Farh and Dobbins (1989) reported

similar findings. Thus, self-report transfer items were constructed to be as

specific as possible (e.g.,

subordinates have told me that my behavior has

improved following a training course). Similarly, in order to improve the

accuracy of self-reports (and minimize potential inflation), all responses were

anonymous and all completed questionnaires were returned directly to the

researchers.

Analyses

The current research utilized a latent variable model to test the

hypothesized relationships among the constructs of interest. An advantage of

latent variable models is that they involve tests of the relationships among

constructs which are not attenuated by measurement error (c.f. Loehlin, 1987).

Analysis proceeded in two stages (Lance, Cornwell & Mulaik, 1988). First,

confirmatory factor analysis (CFA) was used to assess the fit of the

measurement model to the data. Second, the relationships among the constructs

of interest were estimated (i.e., structural model). Both of these analyses were

conducted using the LISREL VII computer program (Joreskog & S&born,

1989a).

Our primary purpose in this study was to examine the magnitude of the

relationships among the constructs of interest (i.e., path coefficients). A

secondary purpose was to determine the extent to which the data, in general,




12/26


II

conformed to our predictions. To do this, a variety of goodness-of-fit indices

were utilized. Three indices calculated by the LISREL VII program, including

chi-square, the goodness-of-fit index (GFI), and the root mean square residual

(RMSR) were used. These indices provide a measure of the extent to which

the covariance matrix estimated by the hypothesized model reproduces the

observed covariance matrix (James, Mulaik & Brett, 1982).

In addition to these indices, the normed-fit index (NFI; Bentler & Bonett,

1980), and the relative normed-fit index (RNFI; Mulaik, James, Van Alstine,

Bennett, Lind & Stilwell, 1989) were used because they have certain desirable

characteristics relative to the other fit indices. First, both NFI and RNFI assess

a models fit in relation to the worst and best fit attainable rather than as a

sole function of the difference between the reproduced and observed covariance

matrices. Second, RNFI was used because it assesses the relative lit of a

structural model independent of assessing the fit of the measurement model,

thus providing a purer indication of the fit of a structural model. This is desirable

because the other fit indices are heavily influenced by the fit of the measurement

model and, to a lesser degree, the fit of the structural model (Mulaik et al.,

1989). In general, a good fit to the data is indicated by non-significant values

of chi-square, RMSR values which approach zero, and values of GFI, NFI,

and RNFI which approach unity.

Results

M easurement M odel

Before considering the hypothesized relationships among the constructs

of interest, the accuracy of the measurement model with respect to the data

was examined. A confirmatory factor analysis of the a priori measurement

model was conducted. In this analysis, the variances for all of the factors were

fixed at unity and all of the constructs were allowed to intercorrelate.

Computation of NFI for this model required the estimation of two comparison

models. These included a most-restrictive null model in which no factors were

assumed to underlie the questionnaire items, and a least-restrictive model in

which each of the items was allowed to load on each of the hypothesized

constructs.

Table 2 presents the goodness of fit indices for the a priori measurement

model. The results reported in this table indicate that while this model provided

Table 2. Goodness-of-Fit Indices for the A Priori and Revised Measurement Models

Measurement

M odel Chi -Square

df

GFI

RMSR

NFI

A Priori

11,633.60 3,394

.I4 ,062

.86

Revised

8,294.88* 2,983

.79 .055

.92

Notes:

a GFI=goodness-of-fit index; RMSR=root mean square residual; NFI=normed-fit index.

* p < ,001

JOURNAL OF MANAGEMENT, VOL. 21, NO. 1, 1995



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