European Journal of Training and Development

Does supervisor support make a difference in employees’ training and job performance? An empirical
study of a professional development program
Sunyoung Park, Hye-Seung (Theresa) Kang, Eun-Jee Kim,
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Sunyoung Park, Hye-Seung (Theresa) Kang, Eun-Jee Kim, "Does supervisor support make a difference in employees’
training and job performance? An empirical study of a professional development program", European Journal of Training and
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 1

Does supervisor support make a difference in employees’ training and job performance?

An empirical study of a professional development program

Introduction

As organizational paradigms shift from traditional job-based training to a more strategic-

developmental approach (Ellinger et al., 2005; MacNeil, 2004), training programs are viewed as

a strategic function of human capital management. Developing employees’ competencies to not

only overcome daily problems but also support the development and growth of the organization
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is a critical aspect to leverage the competitive edge of organizations (DeSimone et al., 2002).

Organizations expect that the knowledge and skills gained from training will be transferred to the

workplace and thus result in improved job performance. However, training transfer only occurs

when a variety of individual and environmental factors such come together and interact with one

another (Baldwin and Ford, 1988; Baldwin et al., 2017; Holton et al., 2000).

The relationship between training transfer and work performance can perhaps be

explained best by the support that trainees receive at work when using their newly acquired

knowledge and skills (Blume et al., 2010; Clarke, 2002). Support is regarded as the most

consistent and important factor predicting training transfer in the broad category of work

environment (Lau and McLean, 2013). In particular, support from both the organization and the

supervisor plays a key role in creating an organizational climate that is conducive to training

transfer (Hawley and Barnard, 2005; Kirwan and Birchall, 2006; Lau and McLean, 2013).

Supervisors play a particularly crucial role in that they can influence their subordinates on

whether or not to participate in training programs (Blanchard and Thackers, 2007; Ismail et al.,

2010; Noe, 2008). However, both scholars and practitioners in Human Resource Development
 2

(HRD) recognize that having some level of support from a supervisor does not guarantee training

transfer or a link to job performance (Burke and Hutchins, 2007; Lim and Morris, 2006).

The training literature indicates that individual-level factors such as motivation function

as antecedents of behavioral outcomes (Colquitt et al., 2000; Yelon et al., 2014). Employees’

motivation to participate in training programs and to transfer what they learned to the workplace

are positively related to training transfer (Colquitt et al., 2002; Tziner et al., 2007). The success

of training also tends to be affected by trainees' readiness (Kulik et al., 2007; Noe, 2010), defined
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as “the extent to which individuals are prepared to enter and participate in training” (Holton et

al., 2000, p.342). Specifically, having knowledge and expectations of the training before training

begins may either positively or negatively impact the training process and motivation to transfer

the new knowledge to the workplace (Bates et al., 2007; Bhatti et al., 2013).

Another factor from a motivational perspective is employees’ developmental needs

awareness, defined as employees’ personal efforts to identify their own needs and opportunities

to develop knowledge, skills, and ability (Noe and Wilk, 1993; Noe, 2008). This awareness is

also expected to help researchers understand the mechanism of training transfer in the workplace.

Developmental needs awareness involves self-assessment of one’s own strengths and

weaknesses as well as one’s own efforts to explore available opportunities to develop and

enhance professional skills, knowledge, and attitudes through either formal or informal training

(Jiandani et al., 2016; Noe, 2002). Employees’ self-assessment of their developmental need to

improve performance could explain their level of participation and the outcomes of training in

that they personally identify the need for development, for themselves and the organization.

However, despite the significance to the effectiveness of training, to date, limited empirical
 3

research has focused on the role of individual-level factors such as developmental needs

awareness and readiness for training in the relationship between the training transfer process and

outcomes. Hence, further empirical examination is called for and is the motivation for the

researchers to further explore the dynamics of this mechanism of training transfer.

The purpose of this study is to examine the relationships among supervisor support,

employees’ developmental needs awareness, motivation to learn, training readiness, motivation

to transfer, and job performance. The overall research questions guiding the study are (a) What
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are the relationships among supervisor support, employees’ developmental needs awareness,

motivation to learn, training readiness, motivation to transfer, and job performance? and (b) Do

employees’ developmental needs awareness and motivation to learn mediate the relationship

among supervisor support, training readiness, motivation to transfer, and job performance?

The significance of the study is that our findings will add to the academic work on

training transfer by empirically examining how both individual and environment factors

influence transfer outcomes and through which mechanisms. The present study investigates the

impact of supervisor support and individual-level factors (training readiness and motivation) on

job performance. By testing the individual-level factors as mediators in the model (i.e.,

developmental awareness and motivation to learn), this study will help HRD scholars and

practitioners make an informed decision regarding training transfer. For instance, from a

practical point of view, exploring the role of developmental awareness in relation to supervisor

support and job performance may help organizations incorporate an effective support system as a

mechanism to link support from supervisors to training transfer and performance outcomes. This

attempt to expand our understanding of the transfer process and outcomes may also add to the
 4

training literature from a theoretical perspective, by adopting the conceptual model of a learning

transfer system.

Literature Review

The constructs of this research were adopted from the conceptual model of learning

transfer (Holton et al., 2000; Holton, 2005) by focusing on the elements of motivation,

environment, and outcomes in training transfer. Specifically, we selected six variables (i.e.,

supervisor support, developmental needs awareness, motivation to learn, training readiness,

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motivation to transfer, and job performance) to investigate their relationships in a professional

development context.

Supervisor Support for Training and Transfer

How employees perceive the support they receive from their organizations and

supervisors has been studied as a critical explanatory framework for understanding and

predicting job-related attitudes and behaviors of employees (Chiang and Hsieh, 2012). There is

considerable empirical backing for the notion that perceived organizational support has a positive

correlation with employees’ favorable performance outcomes (Chen et al., 2005; Chiang and

Hsieh, 2012; Muse and Stamper, 2007; Pazy and Ganzach, 2009). According to social exchange

theory, employees who experience a high level of organizational support are expected to work

harder to improve their work performance. In other words, employees are motivated when they

feel that the organization supports them and, in turn, they reciprocate with high quality output

(Armeli et al., 1998; DeConinck and Johnson, 2009). The meta-analysis by Rhoades and

Eisenberger (2002) confirmed this positive relationship between perceived organizational

support and job performance.

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Training, along with other support, is an important organizational investment in

employees that results in higher perceived organizational support and outcomes (Kim et al.,

2009; Wayne et al., 1997). Training and development support from supervisors includes

encouragement, feedback, helping employees identify opportunities to acquire new knowledge,

skills, and attitudes, and promotes application of these competencies in the workplace

(Elangovan and Karakowsky, 1999). Specifically, supervisors are expected to play a role in

encouraging the employees to attend training programs, support them before, during and after
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training in terms of budgetary support, opportunities, and resources, involve employees in

decision-making, and guide them in applying competencies that they have learned in the

workplace (Chiaburu and Tekleab, 2005; Ismail et al., 2007). Support from supervisors has been

suggested as a powerful tool to enhance employees’ attitudes and behaviors including training

transfer and improved job performance (Baldwin and Ford, 1988; Elangovan and Karakowsky,

1999; Nijman et al., 2006). In addition, support from supervisors is mostly believed to affect

transfer outcomes directly or indirectly by means of the trainees' motivation to transfer or various

factors in the transfer climate (e.g., Cromwell and Kolb, 2002).

Although we know much about supervisor support in general, less research has taken into

account the role of supervisor support for training, which reflects how organizations value their

employees with respect to development, and the potential influence of development on such

relationships. Several studies have reported a positive association between perceived support

from supervisors and job performance (e.g., Settoon et al., 1996; Wayne et al., 2002), but the

empirical evidence is mixed. In addition, there is a dearth of empirical research in the training

literature pertaining to mechanisms that may link support from supervisors to training transfer
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and performance outcomes. Therefore, more empirical research is warranted on whether and how

supervisory support influences employees’ training and training transfer and through which

mechanisms.

Developmental Needs Awareness and Training Transfer

Developmental needs awareness refers to identifying the needs and researching

opportunities to develop employees’ knowledge, skills, and abilities through the available

channels within and beyond the organization (Park, 2004; Noe, 2002; Rothenbach, 1982). In
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particular, developmental needs awareness includes self-assessment and researching

opportunities such as training, promotion possibilities, career exploration, and job rotations

(Mihal et al., 1984; Noe, 2002).

Studies have reported that employees with high developmental needs awareness identify

the gaps between their current and required level of knowledge, skills, and abilities, and they

tend to plan to close these gaps by proactively finding opportunities. Recognizing their own need

for development and the challenges they face in their current situation helps employees learn

new skills, reconsider their attitudes, or change their behaviors as members of the organization

(Chen et al., 2004; Ismail et al., 2010; Noe and Wilk, 1993). Scholars also suggest that the more

employees engage in development activities, the greater their rate of participation in applying

what they acquired and transferring that knowledge to their workplace (Chen et al., 2004; Jiang

and Klein, 2000). In other words, employees’ self-identification of needs for development is

positively associated with exploring and participating in training and developmental activities,

resulting in higher performance and career satisfaction (Jiang and Klein, 2000; Sabharwal,

2011). Based on the motivation-maintenance theory, by exploring developmental needs and

 7

interests further, it is likely that there are positive relationships and influences among learning

motivation (Baldwin et al., 1991; Granrose and Portwood, 1987), training readiness, motivation

to transfer and, thus, commitment, job performance, or career satisfaction (Chen et al., 2004; Loi

and Ngo, 2010).

Motivation to Learn and Training Transfer

Motivation to learn and motivation to engage in learning activities are closely related to

work motivation. According to Noe (1986), motivation to learn is defined as one’s desire to learn
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the content of training and development activities. Noe and Wilks (1993) found that “motivation

to learn, motivation to transfer, and evaluation of previous development experiences have a

direct effect on employee’s participation in development activities” (p. 292). A few studies have

also confirmed that a trainee’s motivation before training influences cognitive and skill-based

learning outcomes as well as training transfer (Chiaburu and Marinova, 2005; Facteau et al.,

1995; Quinones, 1995; Tziner et al., 2007). In addition, several studies have reported that

transfer motivation is positively related to training transfer (Baldwin et al., 2017; Bhatti et al.,

2013; Blume et al., 2010; Grohmann et al., 2014). Other studies have indicated that individual

characteristics and situational constraints on trainees’ motivation to learn influence actual

performance (Mathieu et al., 1992; Tannenbaum et al., 1991). Thus, it is expected that

motivation to learn functions as a positive element in the relationships between the variables in

this study.

Training Readiness and Training Transfer

Training readiness or learner readiness refers to “the extent to which individuals are

prepared to enter and participate in training” (Holton et al., 2000, p.342). Specifically, training
 8

readiness includes knowledge of a program, expectations from training, and understanding of

expected outcomes at the beginning of the training (Bates et al., 2007).

According to Sanders and Yanouzas (1983), individuals enter training with certain

attitudes and expectations that may either positively or negatively impact their learning process.

Scholars have discussed the role of training readiness in diverse outcomes such as self-efficacy,

training transfer, and motivation to transfer (Bhatti et al., 2013; Hung, 2016; Kirwan and

Birchall, 2006). For instance, trainees who have prior knowledge about training programs are
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more likely to be motivated to apply such knowledge, transfer learning to practice, and show

strong self-efficacy in communication and application (Bhatti et al., 2013; Hung, 2016). Thus,

training effectiveness will be examined in this study given that this construct can be largely

affected by trainees’ readiness for training (Noe, 2010) and that the success of training tends to

be largely affected by trainees' readiness (Kulik et al., 2007).

Motivation to Transfer and Training Transfer

Motivation to transfer, also called transfer motivation, is defined as trainees’ desire to use

the knowledge and skills mastered in the training program on the job (Noe, 1986, p. 743).

Transfer motivation includes the direction, intensity, and persistence of efforts toward utilizing

skills and knowledge acquired from training programs (Holton et al., 2000). Earlier literature

reports that motivation to transfer plays a central role in conceptual models of training transfer

(Noe, 1986; Tannenbaum et al., 1991). Based on these models, research has shown that trainees’

motivation to transfer positively affects the application of new skills and knowledge gained in a

training context to the trainee’s job and the workplace (e.g., Axtell et al., 1997; Bates et al.,

2007; Grohmann et al., 2014). Motivation to transfer was found to be the most important
 9

predictor of training transfer when compared with other individual, organizational, and training-

related variables (e.g., Bates et al., 2007; Grohmann et al., 2014). According to Noe (1986,

2008), motivation to transfer must be present for learning to result in changing the employee’s

behavior in the workplace. Thus, it is expected that motivation to transfer functions as a positive

element in the relationship of the variables in this study.

These arguments suggest that the supervisor’s support would positively and significantly

relate to developmental needs awareness, motivation to learn and transfer, training readiness, and
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job performance. Based on the literature review, this study suggests the following five

hypotheses among the variables of the study as antecedents of motivation to transfer and job

performance (Figure 1).

Hypothesis 1: Supervisor support for training is related to developmental needs

awareness, motivation to learn, training readiness, motivation to transfer, and job

performance.

Hypothesis 2: Developmental needs awareness is related to motivation to learn, training

readiness, motivation to transfer, and job performance.

Hypothesis 3: Motivation to learn is related to training readiness, motivation to transfer,

and job performance.

Hypothesis 4: Training readiness is related to motivation to transfer and job

performance.

Hypothesis 5: Motivation to transfer is related to job performance.

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Figure 1 around here

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Methods

Samples

We distributed an invitation letter to participate in this study and an online survey

questionnaire via email to approximately 1,000 employees in educational organizations who had
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participated in professional development workshops in the Midwest and southern areas of the

United States. Of the 1,000 questionnaires sent out, 227 employees voluntarily participated in the

survey. Among the collected data, 11 cases were not fully completed. After eliminating these

cases, the remaining 216 were used as the final cases for further data analyses. The final response

rate was 21.6%. The four demographic variables included (a) gender, (b) age, (c) teaching

experience, and (d) workshop experience. With regard to sample demographic distribution,

29.2% were male and 70.8% were female. The majority of respondents were in their 50s (46.8%)

and 40s (28.2%). Most participants had more than 20 years of work experience (43.1%) and an

additional 20.8% had between 15 and 19 years (20.8%) of experience. The vast majority (81.5%)

had attended a workshop before attending the most recent professional development workshop.

Measures

All six constructs were measured with 29 items (excluding six demographic items). We

used the survey questionnaire with a 5-point Likert-type scale ranging from 1 (strongly disagree)

to 5 (strongly agree). The Cronbach’s α reliability of each measure ranged from .77 to .91 (see

Table 2).
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Supervisor Support for Training. Nine items were used to measure supervisor support

for training (Burke & Baldwin, 1999). In this study, the reliability of nine items was .91. A

sample item was: “My supervisor expects me to apply the knowledge and skills I gain in training

to my job.” We selected this measure because the items emphasize the important role of

supervisors before and after training to create a supportive climate of training attendance and

transfer.

Developmental Needs Awareness. Five items were adopted to measure developmental

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needs awareness from Rothenback (1982). In this study, the reliability of the items was .80. A

sample item was: “‘I know what is necessary for my career development for the next five years.”

We selected this measure because the items focus on identifying developmental needs and

searching for developmental opportunities.

Motivation to Learn. Four items were selected to measure motivation to learn (Noe and

Schmitt, 1986). The reliability in this study was .91. A sample item was: “I am motivated to

learn the skills emphasized in the training program.” We selected the items based on the

relevance with Noe’s (1983) model, one of our theoretical frameworks, and our focus on

motivation in this study.

Training Readiness. To measure training readiness, this study used three items

developed by Holton and colleagues (2000). The reliability of the items was .85 in this study. A

sample item included: “I knew what to expect from this training before it began.” We selected

this measure based on Holton’s (2005) model, another theoretical framework in this study.

Motivation to Transfer. Three items were selected to measure motivation to transfer

(Bates et al., 2012). The reliability in this study was .79. A sample item was: “When I leave this
 12

training, I can’t wait to get back to work to try what I learned.” We selected this measure based

on Holton’s (2005) model, another theoretical framework in this study.

Job Performance. Five items were selected to measure job performance (Podsakoff and

MacKenzie, 1989). The reliability in this study was .77. A sample item was: “I perform tasks that

are expected of me.” We selected this measure because it has been commonly used to measure

in-role job performance of individuals in management, psychology, and related fields (e.g.,

Janssen and Van Yperen, 2004).

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Control Variables. Gender, age, work experience, and workshop attendance experience

before attending this workshop were included as control variables.

Data Analysis

We analyzed the collected data using the following procedures. First, exploratory factor

analysis (EFA) and confirmatory factor analysis (CFA) were conducted to confirm the validity of

the measurement scale. Second, descriptive statistics and correlation analysis were performed

using SPSS. Maximum likelihood estimation was selected as an appropriate statistical estimation

method because the variables fit the normal distribution. The goodness of fit indices used for this

study were chi-square, Tucker-Lewis index (TLI), comparative fit index (CFI), standardized root

mean square residual (SRMR), and root-mean-square error of approximation (RMSEA).

Structural equation modeling (SEM) was conducted to examine the structural

relationships between supervisor support, employees’ developmental needs awareness,

motivation to learn, training readiness, motivation to transfer, and job performance by evaluating

the measurement model and the structural model. We selected SEM to analyze the data because

it can analyze the integrated relationships among all of the variables in this study, and to estimate
 13

the relations among the variables that have been corrected for biases attributable to random error

and construct-irrelevant variance (Tomarken and Waller, 2005). In addition, SEM provides more

accurate estimates of the relationship between the latent variable and the criterion than does

standard multiple regression (McCoach et al., 2007).

Results

The results of the study are reported in two parts. First, the results of the descriptive

statistics, correlations, and reliabilities are reported. Second, the results of the hypothesis testing
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are presented based on the structural equation model.

Descriptive Statistics and Correlations

Table 1 presents the correlations among the six constructs and the descriptive statistics.

The relationship between motivation to learn and motivation to transfer was the highest (r = .77),

followed by the relationships between training readiness and performance (r = .38), and between

training readiness and motivation to transfer (r = .37). The results of skewness and kurtosis show

that there were no serious multicollinearity issues among the variables used in the data (Table 1).

To identify potential multicollinearity problems, we also examined variance inflation factor

(VIF) values. All VIF values for our models ranged from 1.06 to 2.60, far below the

conventional threshold maximum value of 10 (Kline, 2005).

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Table 1 around here

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Reliability and Construct Validity

For reliability, Cronbach’s alpha and composite reliability (CR) were examined. The
 14

Cronbach’s alpha coefficients ranged from .77 to .91. In addition, the composite reliability (CR)

of the latent variables was between .87 and .91, which was higher than .70, the minimum critical

value for good internal consistency (Fornell and Larcker, 1981). Our validity analysis involved

both convergent and discriminant validity. The standardized factor loadings of all the elements

measured were between .56 and .87. The average variance extracted (AVE) values were

between .54 and .74. Table 2 demonstrates that all variables have good convergent validity.

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Table 2 around here

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Measurement Model Assessment

An overall confirmatory factor analysis (CFA) was performed to estimate the convergent

and discriminate validity of the indicators of the six constructs. CFA is most suitable to confirm

whether or not the construct measures load on their respective a priori-defined constructs

(Browne and Cudek, 1993). As a result of the overall CFA, all factor loadings were over 0.60,

and the measurement model indicated a good fit to the data (χ2 =342.30; df = 201; χ2 /df = 1.70;

TLI = .93; SRMR=.06; CFI = .94; RMSEA = .06).

Structural Model Assessment

Since the fitness index of the measurement model satisfied the fitness index criteria and

the estimate possibility of the structural model was theoretically confirmed, the fitness of the

initial research model was estimated through the maximum likelihood estimation method. The

initial structural model provided a good fit to the data (χ2 =345.46; df = 202; χ2 /df = 1.71; TLI

= .93; SRMR=.07; CFI = .94; RMSEA = .06).

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Hypotheses Testing

To test the hypotheses, the statistical significance of the path coefficient among the

variables was examined. Except for two paths (supervisor support for training → developmental

needs awareness; motivation to transfer → job performance), all path coefficients were

statistically significant (t > 1.96, p < .05). Thus, Hypothesis 1 was partially supported:

Supervisor support for training directly affected motivation to learn (β = .23, t = 3.26, p < .01)

and indirectly affected training readiness, motivation to transfer, and job performance through
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motivation to learn, while supervisor support had no direct and significant effect on

developmental needs awareness. In addition, supervisor support had an indirect effect on training

readiness, motivation to transfer, and job performance through motivation to learn (see Table 3).

Thus, Hypotheses 2, 3, and 4 were all supported: (a) developmental needs awareness had direct

and significant effects on motivation to learn (β = .22, t = 2.91, p < .01), training readiness (β

= .20, t = 2.59, p < .05), motivation to transfer (β = .33, t = 2.11, p < .05), and job performance (β

= .32, t = 3.56, p < .01), (b) motivation to learn had direct and significant effects on training

readiness (β = .33, t = 4.34, p < .01), motivation to transfer (β = .76, t = 14.67, p < .01), and job

performance (β = .43, t = 2.30, p < .05), and (c) training readiness directly affected motivation to

transfer (β = .23, t = 3.26, p < .01) and indirectly affected job performance through motivation to

transfer. Finally, Hypothesis 5 was not supported. Motivation to transfer had no significant

influence on job performance.

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Table 3 around here

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Discussion and Implications

The purpose of this study was to examine the relationships among supervisor support,

employees’ developmental needs awareness, learning motivation, training readiness, transfer

motivation, and job performance. The results of this study indicated that individual-level factors

in the training context could play a significant role in the influence of supervisor support on job

performance. The findings support previous studies on the relationship between the supervisor’s
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role and transfer (Chiaburu and Tekleab, 2005; Ismail et al., 2007). The findings of the current

study provide further evidence that (a) supervisor support for training directly affected

motivation to learn, (b) both developmental needs awareness and motivation to learn had direct

and significant effects on training readiness, motivation to transfer, and job performance, (c)

developmental needs awareness directly affected motivation to learn, and (d) training readiness

directly affected motivation to transfer.

The findings indicate, however, that supervisor support for training does not significantly

affect developmental needs awareness. The reason for this insignificant effect might be related to

the sample demographic of this study. The majority of the respondents were senior-level

employees in their 50s (46.8%) and 40s (28.2%) with more than 20 years of work experience

(43.1%). In this context, we can speculate that some of the respondents were supervisors

themselves or that they were relatively unconstrained by supervisory support in their current,

somewhat senior-level positions.

As expected, however, developmental needs awareness had direct and significant effects

on motivation to learn, training readiness, motivation to transfer, and job performance. These

findings confirm the results from previous literature suggesting that individuals’ self-assessment
 17

and preparation for further development could enhance learning motivation, training readiness,

motivation to transfer, and job performance (Baldwin et al., 1991; Jiang and Klein, 2000;

Sabharwal, 2011). Awareness of developmental needs was also found to play a mediating role in

the relationship between supervisor support for training and other variables: motivation to learn,

training readiness, motivation to transfer, and job performance. Since the effect of developmental

needs awareness has not yet been studied in relation to supervisory support in the training

context, future studies should be conducted to better understand the variable and its relationship
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with other constructs.

Implications for Research

This study enriches the literature in several ways. First, this study investigated how

supervisor support contributes to motivation, training, and job performance. The results of the

study indicate that the level of supervisor support not only relates to learning motivation but also

influences training readiness and job performance. In other words, supervisor support could

encourage employees to learn the skills and knowledge needed in the workplace while fostering

learning motivation, which has a positive influence on employees being prepared for training and

improving their job performance. This finding emphasizes the role of supervisors in learning

motivation, training participation, and job performance. This study also contributes to the

literature on the critical role of supervisor support before and after training to enhance

participants’ motivation.

This study attempted to bridge the gap in the literature by investigating the relationships

among supervisor support, developmental needs awareness, learning motivation, training

readiness, transfer motivation, and job performance. Previous studies have only focused on
 18

examining motivation and outcomes in training and have little paid attention to how to improve

motivation by providing more opportunities to develop employees’ knowledge, skills, and

abilities. We need more studies that look into developmental needs awareness as a strong

antecedent of learning motivation. This study expands our knowledge on motivation related to

transfer by adding developmental needs awareness to the relationships of participants’

motivational factors in professional development contexts in the U. S.

Another key finding is that motivation to transfer was not found to be significant in
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predicting job performance. It may be that participants in this study did not receive enough

information about the professional development program beforehand and therefore did not place

a high value on the expected outcomes of the program. This interpretation emphasizes the notion

that understanding the value participants place on training and its potential outcomes may be an

important factor when implementing professional development programs (Maurer and Tarulli,

1994). Another possible explanation is that participants could pay more attention to acquiring

new skills and knowledge rather than focusing on applying and practicing what they learn

because of their workplace environments (e.g., limited support from the organization, heavy

work load, and administrative restrictions). Further investigation is needed on how to enhance

motivation to transfer after participants complete professional development programs.

Implications for Practice

From the findings of this study, organizations including HRD practitioners could assess

the effectiveness of professional development programs in several ways. By conducting a needs

analysis of participants in advance, HRD practitioners can reflect on what participants want and

need when designing and implementing professional development programs. For instance,
 19

participants can include interactive learning activities related to their individual practice needs

during a program based on information from the needs analysis. Participants also can share

challenges with each other and encourage discussion on possible solutions by applying

knowledge and skills learned through the professional development opportunity. It would also be

helpful for participants to clarify learning objectives and program content before a workshop so

they can prepare for professional development participation.

Finally, HRD practitioners could collaborate with participants’ supervisors to prepare for
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interventions to improve the quality and practicality of existing professional development

programs. By obtaining support and useful information from supervisors, organizations could

provide more professional development opportunities that meet participants’ needs and demands.

Additionally, organizations could enhance the strengths of professional development programs

by providing best cases and examples of using professional development opportunities and

demonstrating how to apply knowledge and skills to practice in an appropriate way.

Limitations and Recommendations

While this study offers relevant insights for professional development programs, there

are some limitations that are worthy of further investigation. One limitation of our study lies in

its self-report design, which could lead to common method bias that may influence the

relationships between the variables examined in this study. Second, this study focused on four

individual and motivational factors, but it did not cover other factors that could affect job

performance. Third, the findings from this study cannot be generalized and might reflect the

regional characteristics of specific areas because we collected data from the Midwest and

southern areas in the U.S. Finally, the findings of this study cannot be applied to other
 20

employment contexts because of the specific characteristics of the participants and training in an

educational setting. For instance, behavioral dynamics among supervisors, trainees, and other

organizational variables may be different in other industries or business settings.

Future research could explore more diverse factors influencing job performance. Beyond

self-evaluation on performance after the training, obtaining data from multiple sources (e.g.,

colleagues, supervisors, or subordinates) would be useful to ascertain the level and improvement

in job performance. Different motivational factors, including learning goal orientation, self-
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efficacy, and intention to transfer could also be investigated to analyze their effect on job

performance. Including more demographic characteristics such as participants’ jobs (e.g.,

marketing versus engineering) and other regions will also help researchers and practitioners

better understand the needs of professional development training programs. Additional future

research is essential to verify how support from organizations influence professional

development participation and positive performance. Researchers could also explore a similar

research model in different cultural contexts or settings to compare with the findings in this

study.
 21

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Biographies:
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Dr. Sunyoung Park is an Assistant Professor in the School of Leadership and Human Resource
Development at Louisiana State University, USA.
Dr. Hye-Seung (Theresa) Kang is an Associate Director in East Asian Studies Center at Indiana
University, USA.
Dr. Eun-Jee Kim is a Research Assistant Professor at the Korea Advanced Institute of Science
and Technology (KAIST), South Korea.
 Training
readiness

Developmental
needs
awareness
Motivation to
Supervisor transfer
support
Motivation to
learn
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Job
performance

Figure 1. Hypothesized model

 Table 1

Descriptive Statistics and Correlations

Variables 1 2 3 4 5 6 7 8 9 10
1. Gender -
2. Age .01 -
3. Work -.06 .74** -
4. Attendance .02 -.10 -.10 -
5. SS -.14* .04 .04 -.08 -
6. DN .09 .04 .08 .06 .10 -
7. ML -.06 -.01 -.01 .42** .22** .24** -
8.TR .07 -.08 -.08 .24** .14* .26** .35* -
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9. MT -.07 .04 .02 .44* .16* .31** .77* .37** -

10. JP .08 .10 .11 .08 .05 .31** .23 .08 .15** -
Mean 1.71 3.17 6.73 1.19 2.92 4.56 4.42 3.56 4.35 4.78
Standard .46 .92 1.51 .39 .83 .45 .73 .83 .66 .36
Deviation
Skewness -.92 -.74 -1.25 1.63 -.22 -1.48 -1.55 -.31 -1.28 -2.18

Kurtosis -1.16 -.57 1.03 .67 -1.22 4.16 2.69 -.22 2.62 5.59
Note. n=216. *p<.05. **p<.01. Supervisor support (SS), Developmental needs awareness (DN), Motivation to learn
(ML), Training readiness (TR), Motivation to transfer (MT), and Job performance (JP).
 Table 2

Factor Loading, Cronbach’s Alpha, Composite Reliability, and Average Variance Extracted
(AVE)

Cronbach’s Composite
Construct Factor Loading AVE
Alpha Reliability
SS1 0.78 .91 .91 .54
SS2 0.82
SS3 0.76
Supervisor SS4 0.79
support for SS5 0.78
training SS6 0.65
SS7 0.60
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SS8 0.76
SS9 0.64
DN1 0.84 .80 .87 .58
DN2 0.83
Developmental
DN3 0.86
needs awareness
DN4 0.66
DN5 0.56
ML1 0.87 .86 .90 .74
Motivation to ML2 0.87
learn ML3 0.85
ML4 0.87
TR1 0.85 .84 .88 .71
Training
TR2 0.88
readiness
TR3 0.79
MT1 0.84 .79 .88 .70
Motivation to
MT2 0.81
transfer
MT3 0.86
JP 1 0.77 .77 .87 .57
JP 2 0.83
Job Performance JP 3 0.83
JP 4 0.72
JP 5 0.59
 Table 3

Hypothesis Testing: Direct and Indirect Effects of Path Estimates

Paths Direct effect Indirect effect

H1 Supervisor support → Dev. Needs awareness .11
→ Motivation to learn .23**
(through ML) → Training readiness .11*
(through ML) → Motivation to transfer .22*
(through ML) → Job performance .08*
H2 Dev. Needs awareness → Motivation to learn .22**
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→ Training readiness .20*

(through TR) → Motivation to transfer .33* .20*
(through ML) → Job performance .32** .00
H3 Motivation to learn (ML) → Training readiness .33**
(through TR) → Motivation to transfer .75** .05**
→ Job performance .43*
H4 Training readiness → Motivation to transfer .23*
H5 Motivation to transfer (MT) → Job performance .29

Note: * p < .05, ** p < .01