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The Impact of Practical Relevance on Training Transfer. Evidence from a Service Quality Training Program for German Bank Clerks. Susanne Liebermann and Stefan Hoffmann Susanne Liebermann (Dipl. Psych.) Personnel Specialist Schindler Deutschland Holding GmbH Human Resources Development Ringstr. 54 12105 Berlin Germany Tel. +49 30 7029 2349 Fax +49 30 7029 1006 E-Mail: [email protected] Stefan Hoffmann (Dipl. Psych.) Research Assistent Technical University of Dresden Department of Business Management and Economics Chair of Marketing, Prof. Dr. Stefan Müller 01012 Dresden Germany Tel. +49 351 463 32334 Fax. + 49 351 463 37176 E-Mail: [email protected] This is the accepted version of the following article: “Liebermann, S.; Hoffmann, S. (2008). The Impact of Practical Relevance on Training Transfer. Evidence from a Service Quality Training Program for German Bank Clerks, International Journal of Training and Development, 12 (2), 74-86.”, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/j.1468-2419.2008.00296.x/abstract © Wiley, Blackwell 2008; DOI: 10.1111/j.1468-2419.2008.00296.x

The Impact of Practical Relevance on Training Transfer. Evidence from a Service Quality Training Program for German Bank Clerks.

Management literature provides a variety of recommendations on how to improve customer orientation. Crucial factors in the process of transferring the contents of service quality training programs to practice, however, have not yet been sufficiently analyzed. This study proposes and tests a model of transfer motivation and training transfer via structural equation modeling, validating Baldwin and Ford’s framework and Kirkpatrick’s levels of evaluation. Following the recommendation of Alliger et al., the present study analyses the relationship between Kirkpatrick’s levels of evaluation, paying attention to the specificity of the measures on each level. The article states that trainee satisfaction needs to be conceptually distinguished from perceived practical relevance. The latter is claimed to be the main driving force for transfer motivation and transfer. The survey collects data from 213 German bank employees who attended a training program aimed at improving service quality. As assumed, perceived practical relevance of the training exerts strong influence on the reaction of the participants and has a substantial total effect on the motivation to transfer and on actual transfer.

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The Impact of Practical Relevance on Training Transfer. Evidence from a Service Quality Training Program for German Bank Clerks.

In view of the increasing similarity of product characteristics, service quality has become crucial in keeping ahead of competitors in various branches of industry. Marketing researchers therefore advise managers to increase the level of market (Homburg & Pflesser, 2000; Kohli et al., 1993; Narver & Slater, 1990), customer (Hartline et al., 2000), and service (Homburg et al., 2002) orientation. Deshpandé et al. (1993) define customer orientation as the strategy of developing a durably profitable enterprise by putting customers’ interests first. Previous research has shown that on the long term a corporate strategy focusing on customers’ needs fosters success (Goff et al., 1997; Peters & Waterman, 1982). Due to the high level of face-to-face contact with the customer, customer orientation is particularly important for service companies (Kelley, 1992). Marketing literature provides a variety of recommendations on how to improve customer orientation, which range from the adaptation of processes, structures, and incentive systems, to the implementation of formal and informal control mechanisms (Hartline et al., 2000; Slater & Narver, 1995; Deshpandé et al., 1993). Frontline employees are responsible for transferring the customer-oriented strategy into service quality which is visible for the customer (Thomas et al., 2001). Therefore, Berry et al. (1988) advise companies to conduct training programs for this target group.

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The question of how to ensure that service quality training programs actually lead to better service performance has not yet been sufficiently analyzed. The finding that, in general, trainees only apply about 30 percent (Robinson & Robinson, 1995) of the training content draws special attention to the importance of monitoring and evaluating the transfer process. Although the number of publications addressing training transfer has increased since Baldwin and Ford published their theoretical framework in 1988, there is still a lack of studies explaining how transfer can be optimized (Hawley & Barnard 2005; Holton & Baldwin 2000). In particular, the specific challenges of assuring the transfer of service quality training have not been analyzed. This study aims at closing this gap and discovering crucial influencing factors in the transfer process of service quality training. The article suggests a model that combines Baldwin and Ford’s (1988) theoretical framework of training transfer and Kirkpatrick’s (1960) levels of training evaluation. As Alliger et al.’s (1997) meta-analysis shows that studies still conceptualize Kirkpatrick’s first level inconsistently, the present article offers a clear concept of trainee satisfaction, which is conceptually distinguished from perceived practical relevance of the training as a non-evaluative measure. The study tests the suggested model in the field of financial services in Germany, where the level of required service quality has increased in the last years.

Training evaluation criteria Facing the challenge of assessing the complexity of training outcomes, Kirkpatrick (1960; 1987; 1998) outline the four levels reaction, learning, transfer, and result for evaluating training programs. On the first level (reaction), the trainees give feedback on how they feel about

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the training program. On the second level (learning), acquired knowledge, new skills, and attitudinal changes are examined. The third level (transfer) analyzes the trainees’ application of the training content in their working environment. The fourth level evaluates organizational results, e.g. in terms of return on training investment. According to Alliger and Janak (1989), Kirkpatrick’s concept dominates evaluation research activities because of its simplicity. Although Kirkpatrick (1960) did not explicitly propose a causal relationship between the four levels, many researchers assume the four levels to be causally and hierarchically interdependent - or at least positively correlated (e.g. Newstrom, 1978; Hamblin, 1974). Based on a review of studies using the four-level concept, Alliger and Janak (1989) conclude that the supposed relationships can not be found consistently in empirical research. Consequently, they propose a modified model which assumes no correlation between the first and the second level. More recently, meta-analyses reveal at least modest relationships between the first two levels (Colquitt et al., 2000; Alliger et al., 1997). Alliger et al. (1997) argue that studies which could not assert correlations measured the two criteria on different levels of specificity. Thus, the weak relations may partly be a result of statistical artifacts. The authors recommend that further research on the structure of Kirkpatrick’s criteria needs to be conducted, paying attention to the specificity of the criteria on each level. Accordingly, the present study measures the three evaluation criteria on the same level of specificity, expecting hierarchical relations. H1 The better the trainees’ reaction to the training program, the more they learn in the training program.

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H2 The more the trainees learn in the training program, the more of the training contents they transfer to their jobs. Alliger et al. (1997) reveal in their meta-analysis, that the cited studies use varying concepts for the construct of reaction. One group of studies asked about the general satisfaction with the training (affective reaction), while other studies used criteria estimating the utility of the training contents for the work situation (utility reaction). Alliger et al. (1997) found positive correlations between the other three levels and both concepts of reaction. Furthermore, the two reactions correlated with each other. The authors suggest that, in future, these two forms of reaction need to be distinguished as two sub-categories of the level of reaction (see also Morgan & Casper, 2000). The relation between the levels of evaluation should be further analyzed with a clear explicit concept and operationalization of the level of reaction. On this level, the present study uses criteria of the affective reaction for evaluating the training program. However, instead of ascertaining the utility reaction as a subjective evaluation variable, the study analyzes the variable perceived practical relevance. This construct is conceived as an objective measure for the practicability of the training. Its influence on Kirkpatrick’s levels and on the transfer process is discussed in the section Training Design.

Factors influencing the transfer process From a managerial point of view, the investment in training programs is not worthwhile unless trainees succeed in translating training contents into actual performance (Kozlowski & Salas, 1997; Kuchinke 1995). The debate on the process of transfer has changed substantially over the last decades. Whereas classical theories (Thorndike & Woodworth, 1901; Judd,

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1908) focus on the training design, current theories consider ways of enhancing the transfer process and avoiding transfer barriers (Baldwin & Ford, 1988; Holton, 1996). Baldwin and Ford (1988) propose a theoretical framework for conducting research on training transfer. The authors analyze the transfer process on three levels: training input, training output and conditions of transfer. Three types of input variables - work environment, trainee characteristics, and training design - influence two output variables - learning and retention. The degrees of two conditions of transfer - maintenance and generalization - depend on trainee characteristics and the work environment, as well as on learning and retention. Holton (1996) proposes that the input variables motivation to transfer, transfer climate and transfer design have a mediating effect on the relation between learning and transfer. In the following, we discuss crucial input variables that are supposed to exert influence on the transfer process and mediate the relations between Kirkpatrick’s levels of evaluation.

Trainee characteristics In a meta-analytic path-analysis, Colquitt et al. (2000) identify several trainee characteristics as being significant predictors for training motivation and training outcomes. The authors reveal that cognitive ability (e.g., Kanfer & Ackerman, 1989), as well as personality traits like achievement motivation (e.g., Mathieu, Martineau & Tannenbaum, 1993), internal locus of control (e.g., Noe, 1986; Noe & Schmitt, 1986) and self-efficacy (e.g., Martocchino & Webster, 1992; Gist et al., 1991; Quinones et al., 1995) have a positive impact. Furthermore,

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commitment both to the organization and to one’s own career (e.g., Blau, 1988, Mowday et al., 1982) is a crucial precondition for training success. The authors confirm the postulated negative influence of anxiety and age (Martocchino, 1994; Webster & Martocchio, 1993; Gist et al., 1988). The impact of the trainee’s motivation on training output has often been proven empirically (Wexley & Latham, 1991). Some authors explicitly distinguish between motivation to learn and motivation to transfer (Kontoghiorghes, 2002; Ruona et al., 2002). The motivation to learn is defined as the trainee’s desire to achieve a high degree of learning (Noe, 1986). Thus, it is assumed to have an impact on Kirkpatrick’s (1960) second level of training evaluation. The transfer motivation, indicating the trainee’s desire to apply and use the training contents in the job (Noe & Schmitt, 1986), relates to the third level of Kirkpatrick’s concept. Holton (1996) proposes that transfer motivation is the most crucial precondition for the trainee to apply training contents to the workplace. However, as the meta-analysis by Colquitt et al. (2000) shows, transfer motivation has not been included in most evaluation studies. The present study suggests a positive relation between transfer motivation and transfer. H3 The higher the transfer motivation, the higher the transfer of training contents to the job. Consequently, if H3 is confirmed it is important to understand which factors influence the transfer motivation. According to Vroom (1964), a person is motivated to show a specific behavior when the person expects this behavior to help him achieve his goals. Noe (1986) adapts this concept to the transfer motivation and shows that the fulfillment of the trainee’s need for personal development influences the transfer motivation. Tannenbaum et al. (1991)

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show that the fulfillment of expectations also promotes the trainee’s motivation. Accordingly, the present study presumes that trainees’ reaction to the training, measured via the fulfillment of expectations and need for personal development, influences the transfer motivation. H4 The better the trainees’ reaction to the training, the higher their transfer motivation. Noe (1986) states that learning outcome directly influences the transfer motivation. In accordance, Tannenbaum et al. (1991) discover that the trainees’ performance during the training program positively influences post-training motivation. Thus, the present study proposes that the more trainees learn and understand the training contents, the more they are motivated to apply new skills in their job. H5 The more trainees learn in the training program, the higher their transfer motivation.

Training transfer design Olsen (1998) claims that the main goal for training designers should be to foster the trainees’ motivation to use new skills on the job. Therefore, characteristics of training transfer design have to be monitored closely, as they are supposed to have an impact on the transfer motivation (Yamnill & McLean, 2001). Even if trainees acquire new knowledge during the training session, transfer might still not occur because they do not learn how to apply the knowledge in their working environment (Holton, 1996). Recent studies in cognitive psychology show that performance can already be automated during the training if the trainee has the possibility to practice new behavior (Goldstein & Ford, 2002; Shiffrin & Schneider, 1977). May and Kahnweiler (2000) recom-

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mend that the trainer should provide opportunities to practice, in order to show the trainee the practical relevance of the training contents and to ensure transfer. Laker (1990) distinguishes two types of transfer. Far transfer indicates that the learned knowledge is applied in dissimilar working situations, while near transfer refers to working situations similar to the training program. According to Clark and Voogel (1985), near transfer is more likely to occur when trainers emphasize the practical relevance of the training contents. In accordance with this, empirical research has shown that the perceived similarity between job requirements and training content is crucial for the transfer process (Garavaglia, 1993; Vosniadou & Ortony, 1989). Moreover, the trainee’s belief that the training will improve job performance or lead to a higher perception of competency and/or to a higher salary influences transfer motivation (Colquitt & Simmering, 1998; Mathieu et al., 1992). For that reason, we expect that motivation will increase when the trainee perceives that the training is of practical relevance for his work situation. H6 The higher the perceived practical relevance, the higher the transfer motivation. Furthermore, we expect that participants will be more satisfied with the training when they perceive that the training is relevant for their job. According to the Confirmation/Disconfirmation Model (Oliver, 1980), customer satisfaction is the result of a cognitive comparison between the expected and the perceived characteristics of a product or a service. If the perceived characteristics fulfil or overfill the expectations, customers are satisfied. If the expectations are not fulfilled, customers are not satisfied. Adopting the Confirmation/Disconfirmation Model to the evaluation of trainings, we draw the following conclusion:

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participants in service quality trainings attend the training in order to improve their working skills. Thus, they expect the training to be of practical relevance. The trainee compares this expectation to his actual perception of the training. If the perceived practical relevance matches or exceeds his expectation, he will be satisfied. If the training is less relevant, he will be less satisfied. H7 The higher the perceived practical relevance, the more positive the trainees’ reaction to the training event.

Working environment Besides individual characteristics and the training transfer design, a supporting transfer climate is crucial for transfer motivation (Holton et al., 1997; Goldstein & Ford, 2002; Forehand & Gilmer, 1964). A positive transfer climate provides adequate resources and opportunities to apply the new knowledge, as well as cues to remind the trainee of lessons learned (Tracy et al. 1995; Rouiller & Goldstein, 1993; Karl et al., 1993; Noe & Wilk, 1993; Ford et al., 1992). Particularly the support of managers, supervisors (Clarke, 2002; Russ-Eft, 2002; RichmanHirsch, 2001; Birdi et al., 1997; Facteau et al., 1995; Clark et al., 1993) and peers (Hawley & Barnard, 2005; Bates et al., 2000), through feedback and reinforcement, is a decisive factor in transfer. The present study expects a positive relation between the supervisor support and the transfer motivation. H8 The higher the degree of supervisor support in the working environment, the higher the transfer motivation.

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Data and method Design and sample The present article evaluates a service quality training program for German bank employees, which aims at developing a customer-oriented organizational culture (Gherson & Moore, 1987). We chose the German financial sector as our field of research because of its density of counseling and the high demands on service quality. In this sector, the required qualifications of employees have changed substantially over the past years. Since most of the traditional work is carried out by machines and via online banking, the main task of bank employees today is to inform and advise customers (Althaus, 2002; Grote, 2001; Evers & Klaschik, 2000). Consequently, the number of trainings in social and interactive skills has increased. The human resource managers of the bank agreed on two main training goals. Firstly, the employees are to learn that customer-oriented behavior is of importance for the success of the bank. They are supposed to recognize their own responsibility to ensure a high level of service quality. Secondly, the trainees are to be encouraged to transfer the training content to their work environment. Approximately twelve weeks after the training, all of the 346 training participants were invited to answer an online questionnaire. With 265 trainees taking part in the survey, the response rate was 79 percent. In a retrospective self-estimation, the respondents evaluated the directly perceived changes. As structural equation modeling does not accept missing data, we excluded participants that did not answer all of the questions. These missing values occur randomly. They do not follow a systematic pattern. After data cleansing, 213 questionnaires

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were used for further analysis. No statistically significant differences were found between the participants of the study and the complete sample of the trainees, with regard to gender, age and job experience.

Criteria Criteria for evaluating the training effects are directly derived from the training goals and structured on the first three levels of Kirkpatrick’s (1960) concept. The three criteria are measured on the same level of specificity (Alliger et al., 1997). Reaction was measured on three six-point Likert-type scales. Subjects reported the degree to which the training content matched their personal needs of development (‘needs’), the fulfillment of their expectations (‘expectations’) and their overall satisfaction (‘satisfaction’). Items used to measure the learning effects were directly derived from the training goals defined by the human resource management. The participants stated the degree to which they were aware of the management’s expectations in terms of customer orientation (‘demands’). In addition, the subjects indicated how responsible they felt for selling the bank’s products (‘responsibility’) and whether they had the necessary knowledge to cope with their job tasks (‘competence’). All items were measured on six-point Likert-type scales, retrospectively judging the direct changes. To examine the training effects on the transfer level, the participants estimated their improvement on bipolar five-point Likert scales. Indicators are based on three crucial factors which the management of the bank had previously defined: sales performance (‘sale’), ap-

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pointment rate (‘schedule’), number of times the customer is actively addressed (‘canvassing’) and quality of customer consultancy (‘quality’).

Influencing factors The items measuring the perceived practical relevance of the training are derived from the suggestions of Goldstein and Ford (2002), Clark and Voogel (1985) as well as of May and Kahnweiler (2000). On six-point Likert-type scales, subjects stated if they were given the opportunities to practice new behavioral patterns during the training (‘practice’) and whether they were able to relate the discussed topics to their everyday work (‘own work’). The supervisor support was assessed via six-point Likert scales, measuring the participants’ perception of the supervisor’s interest in the training contents (‘interest’) and his support for the transfer (‘support’) (Richman-Hirsch, 2001; Tracy, 1998; Tracey et al., 1995). The transfer motivation was assessed as proposed by Holton (1996) and Noe (1986). On six-point Likert-type scales, the subjects reported their effort to transfer the contents to the workplace (‘intention’) as well as the perceived degree to which their work would be made easier (‘make easier’) and improved by the application of the training content (‘improvement’).

Method Structural equation modeling (LISREL 8.7) is applied to test the suggested model. As some indicators do not follow the normal distribution, ULS is used (Jörskog & Sörbom, 2001; Bollen, 1989). Consequently, inference statistics like chi-square have to be interpreted with res-

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ervations (Browne, 1984). All indicator variables are standardized, to assure the comparability between the path coefficients (Long, 1993).

Reliability and validity Confirmatory factor analysis (CFA) shows that all factor loadings and path coefficients are statistically significant. The t-values are above the required value of 1.96. All factor loadings are above .60 (Bagozzi & Yi, 1988). These high and significant factor loadings indicate good convergence validity (Bagozzi et al., 1991). Chi-square-difference tests are conducted to assure discriminate validity. For all factors, chi-square difference exceeds the critical value of χ²diff = 3.84 (p < .05; df = 1; Homburg & Dobratz, 1992; Anderson & Gerbing 1988; Bentler & Bonett, 1980) by far. Thus, statistically significant differences between the base model and the restricted models, as well as discriminate validity of the measurement scales can be assumed.

Results Global fit measures of the complete model indicate a good fit. The quotient of chi-square and the degrees of freedom is well below the critical value of 2 (χ²/df = 1.65; χ² = 171.3; df = 104; Byrne, 1998; Jöreskog & Sörbom, 1982). The GFI (.993) reveals that the model excellently fits the empirical data (Bagozzi & Yi, 1988). The AGFI (.989), which corrects the goodness of fit index (GFI) by the complexity of the model (degrees of freedom), also shows a high fit of the model, as it exceeds the critical value of .90 (Jöreskog & Sörbom 1982). The RMSEA value of .055 (with the 90%-confidence-interval ranging from .045 to .073) also indicates a good fit (Browne & Cudeck, 1993).

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Additionally, measures of local fit support the suggested model. The reliability of all indicators is higher than .40 (Table 1). The values of the factor reliability exceed the required level of .60. The extracted average variance of all factors lies above the critical value of .50 (Bagozzi & Yi, 1988). 73.5 percent of the variance of reaction is explained by the perceived practical relevance. 25.1 percent of the variance of learning is explained by reaction. Taken together, perceived practical relevance, reaction, and learning account for 91.0 percent of the variance of transfer motivation. 61.5 percent of the variance of transfer is explained by learning and transfer motivation.

Put Table 1 about here

With one exception, all structural paths are statistically significant. No statistically significant direct correlation can be found between perceived practical relevance and transfer motivation (t < 1,96; Hair et al. 2006). We will discuss this path later. First, we will analyze the magnitude of the parameters of the significant paths, in order to evaluate which direct antecedents are most important for the transfer process. As H1 postulates, the trainee is more likely to learn training contents, the more satisfied he is with the training program (Figure 1, β = .50). Subsequently, the more the trainee has learned about job requirements, the more likely he is to apply the trained skills (β = .40, H2). As assumed, transfer motivation has a positive impact on transfer (γ = .49, H3). Furthermore, perceived practical relevance is identified as a crucial influencing factor on trainee reaction (γ = .86, H7). Transfer motivation is mainly af-

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fected by reaction (β = .63, H4). Both learning (β = .18, H5) and supervisor support (γ = .29, H8) exert influence on this endogenous variable. However, the magnitude of these antecedents’ effects is lower than the effect of reaction (Figure 1).

Put Figure 1 about here In contrast to hypothesis H6, the relationship between perceived practical relevance and transfer motivation was not found to be statistically significant (γ = .20, t < 1.97). However, practical aspects of the training indirectly lead to transfer motivation. Accordingly, the perceived practical relevance has a strong total effect on the transfer motivation. In sum, its direct and indirect effect on transfer motivation is .817 (Table 2). Its total effect on transfer is .566. Reaction, hence the trainees’ satisfaction with the training design, exerts a total effect of .715 on transfer motivation and a total effect of .545 on transfer. However, perceived practical relevance accounts for 73 percent of reaction (Figure 2). Therefore, reaction mediates the influence of perceived practical relevance on transfer motivation. Supervisor support, on the other hand, does not exert considerable influence on transfer motivation (effect = .287). Whereas reaction seems to play an important role in motivating the participants to transfer the learned behavior to practice, learning was found to have a stronger direct effect on transfer (effect = .396), while its influence on transfer motivation is rather low (effect = .176).

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Put Table 2 about here.

Directions for further research The present article sheds light on the discussion of the relations between Kirkpatrick’s (1960) levels of evaluation, revealing positive relations between the first three levels. As Alliger et al. (1997) recommended, the data was collected on the same level of specificity for each evaluation level, so that existing relations could be found without statistical artifacts distorting the results. Learning was found to have a direct impact on transfer. Reaction, however, exerted a stronger indirect effect on transfer, mediated by transfer motivation. This factor needs to be considered in further studies and included in future models of training evaluation. The main contribution of the article is to show that a full understanding of training evaluation can only be achieved if the perceived characteristics of the training are assessed. Perceived practical relevance is introduced as a crucial influencing factor in the transfer process. The article shows that perceived practical relevance, not as an evaluative but as an observed picture of the practicability of the training contents, is a crucial influencing factor on the affective reaction, accounting for 73 percent of its variance. In future studies, the reaction needs to be operationalized as a pure evaluative concept and explicitly distinguished from the perceived characteristics of the training program. It is of high importance to reveal factors influencing the reaction, in order to understand why trainees are satisfied with trainings and to design trainings accordingly. Therefore, authors should analyze the relation between practical relevance and affective reactions and apply Oliver’s (1980) Confirmation/Disconfirmation

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theory on the evaluation of trainings. Furthermore, future studies should try to identify further factors that have an impact on the trainee reaction. The present paper examines only one training program, which was initiated in one German bank. To achieve a broader understanding of the crucial factors for service quality training and to assure external validity of the findings, researchers should simultaneously analyze different branches of industry as well as different kinds of trainings. As the present paper states, the perceived characteristics of a training are important to understand trainees’ affective evaluation of the training and their motivation to transfer. Presumably, the importance of different characteristics varies between different trainings. While in service quality trainings practical relevance was found to be crucial, training other skills may require more general principals to assure far transfer (Laker, 1990). With the antecedents accounting for 61% of the variance of transfer, the postulated model shows an excellent fit. Thus, the most relevant influencing factors seem to be included in the model. However, in the present study, some previously discussed influencing factors, like personality traits, cognitive ability, and career commitment are neglected. Including those factors could further improve the explanation of the transfer process. As proposed by Colquitt et al. (2000), future research should also focus on the interactions of individual and situational factors, since in previous studies they were also identified as vital. This implication reflects the ‘aptitude X treatment’ discussion (Kanfer & Ackerman, 1989), as well as the ‘person X context’ debate in leadership literature (Howell et al., 1986).

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Managerial implications The present study offers practical hints on how to optimize the training process. The findings confirm that service quality trainings should be close to the practical settings of the trainees and suitable to the trainees’ needs in order to ensure that the content is applied to the job. Trainers and human resources managers are well advised to analyze trainees’ demands and expectations in the very early stages of developing the training design. Berry et al. (1988) emphasize the importance of training the frontline employees as a means of improving service quality. This study confirms that service quality trainings can promote employees’ customer orientation. However, companies should not merely send their employees on training programs, hoping they will come back perfectly customer-oriented. Rather, training should be planned thoroughly and be tailored to the specific training goal and working environment. An adequate degree of perceived practical relevance is a crucial factor for guaranteeing acceptance as well as transfer success.

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26

Table 1: Local fit measures indicators

t-value

indicator reliability

squared multiple correlation

construct reliability

reaction

need expectations satisfaction

17.91 18.28

.762 .606 .685

.735

.866

learning

demands responsibility competence

14.85 15.37

.561 .692 .795

.251

.865

transfer

canvassing quality sale schedule

16.79 16.82 15.71

.608 .652 .705 .474

.615

.861

transfer motivation

make easier improvement intention

19.02 16.92

.722 .683 .405

.910

.818

perceived practical relevance

practice own work

14.64

.452 .588

-

.791

supervisor support

support interest

5.46

.741 .769

-

.860

27

Figure 1: Complete model (standardized) practice

own work

.67

interest

.77

support

.88

perceived practical relevance

.86

supervisor support H6 .20 (0.76)

H8 .29 (6.20) .91

H7 .86 (6.66)

transfer motivation

.87 needs

.78 expectations

.83 satisfaction

.85

.25

.75 demands

learning .83

intention

improvement make easier

H3 .49 (8.83)

H1 .50 (11.23)

reaction

.83

H5 .18 (2.80)

H4 .63 (2.80) .73

.64

transfer .78

.89

responsibility

.61

H2 .40 (6.17)

competence

canvassing

.81 quality

.84

.69 sale

schedule

t-values in brackets. Squared multiple correlations are displayed in bold. Error terms excluded.

28

Table 2: Summary of effects transfer motivation

transfer

direct

indirect

total

direct

indirect

total

perceived practical relevance

.204

.613

.817

-

.566

.566

supervisor support

.287

-

.287

-

.139

.139

reaction

.627

.088

.715

-

.545

.545

learning

.176

-

.176

.396

.085

.481

-

-

-

.485

-

.485

transfer motivation

29