The Pennsylvania State University

The Graduate School

Department of Learning and Performance Systems

DIRECT AND

INDIRECT RELATIONSHIPS OF LEADER-MEMBER EXCHANGE AND

INFORMAL LEARNING WITH IN-ROLE PERFORMANCE, EXTRA-ROLE

PERFORMANCE, AND INNOVATIVE WORK BEHAVIOR IN LARGE

KOREAN ORGANIZATIONS

A Dissertation in

Workforce Education and Development

by

Ji Won Park

2018 Ji Won Park

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

August 2018

ii

The dissertation of Ji Won Park was reviewed and approved* by the following:

Judith A. Kolb

Associate Professor of Workforce Education and Development

Dissertation Co-Advisor

Co-Chair of Committee

William J. Rothwell

Professor of Workforce Education and Development

Dissertation Co-Advisor

Co-Chair of Committee

Wesley E. Donahue

Associate Professor of Workforce Education and Development

Edgar P. Yoder

Professor of Agricultural and Extension Education

Susan Land

Professor of Learning, Design and Technology

Director of Graduate Studies

*Signatures are on file in the Graduate School

iii

ABSTRACT

The main purpose of this study was to examine structural relationships among

leader-member exchange (LMX), informal learning, in-role performance, extra-role

performance, and innovative work behavior in selected major South Korean

organizations. Specifically, a direct relationship between LMX and outcome variables

used in this study (informal learning, in-role performance, extra-role performance, and

innovative work behavior) was examined, and an indirect effect—a mediating role of

informal learning on these relationships—was also investigated. A total of 382 complete

responses (i.e., 191 supervisor-subordinate dyadic responses) from major organizations in

South Korea were used for structural equation modeling (SEM) analysis. The results

showed LMX is positively related to employees’ informal learning, in-role performance,

extra-role performance, and innovative work behavior. Moreover, LMX is indirectly

positively related to employees’ in-role performance and innovative work behavior via

informal learning. The findings of this study contribute to expanding the literature on

leadership and workplace learning by empirically revealing the positive linkages among

LMX, informal learning, in-role and extra role performance, and innovative behavior in a

Korean context. Moreover, these findings point to the importance of developing

reciprocal relationships between a leader and subordinate that are based upon mutual trust

and respect and creating favorable work environments that promote employees to engage

in various informal learning activities for higher performance and innovation. More

detailed explanations of contribution to theory and practice are discussed in the text based

on findings of this study.

iv

TABLE OF CONTENTS

LIST OF FIGURES ..................................................................................................... vi

LIST OF TABLES ....................................................................................................... vii

Chapter 1 Introduction ................................................................................................ 1

Research Purpose .................................................................................................. 3

Research Questions ............................................................................................... 4

Operational Definitions ........................................................................................ 4

Chapter 2 Review of Related Literature ..................................................................... 7

Leader-Member Exchange .................................................................................... 7

Informal Learning ................................................................................................. 10

Job Performance ................................................................................................... 11

Innovative Work Behavior.................................................................................... 13

Research Model and Hypotheses .......................................................................... 15

Chapter 3 Methodology .............................................................................................. 22

Restatement of Research Purpose and Research Questions ................................. 22

Population and Participants .................................................................................. 23

Measures ............................................................................................................... 26

Measures Used in Collecting Data ................................................................... 26

Translation Procedures ......................................................................................... 31

Data Collection ..................................................................................................... 32

Data Analysis ........................................................................................................ 34

Chapter 4 Results ........................................................................................................ 39

Descriptive Statistics ............................................................................................ 39

Normality ......................................................................................................... 39

Common Method Variance .............................................................................. 40

Assessment of Model Fit ...................................................................................... 41

Item Parcels ...................................................................................................... 41

Assessment of Measurement Model Fit ........................................................... 43

Assessment of Structural Model Fit ................................................................. 45

Model Modification and Comparison .............................................................. 45

Assessment of the Final Model Fit................................................................... 47

Hypothesis Testing ............................................................................................... 48

Direct Relationship between Independent and Dependent Variables .............. 48

Indirect Relationship between Independent and Dependent Variables............ 49

v

Chapter 5 Discussion and Conclusion ........................................................................ 52

Discussion ............................................................................................................. 52

Theoretical Implications................................................................................... 56

Practical Implications ....................................................................................... 61

Limitations and Suggestions for Future Research ................................................ 64

Conclusion ............................................................................................................ 66

References .................................................................................................................... 67

Appendix A IRB Approval Letters ............................................................................. 75

Appendix B Questionnaires for Survey (English Version) ......................................... 77

Appendix C Questionnaires for Survey (Korean Version) ......................................... 89

vi

LIST OF FIGURES

Figure 2-1: The hypothesized model of the current study .......................................... 21

Figure 4-1: The structural model with standardized path coefficients. ...................... 48

vii

LIST OF TABLES

Table 3-1: Demographic characteristics of subordinates and leaders. ........................ 25

Table 3-2: The instrument items of subordinate-rated leader-member exchange. ..... 27

Table 3-3: The instrument items of supervisor-rated leader-member exchange. ....... 28

Table 3-4: The instrument items of informal learning. ............................................... 29

Table 3-5: The instrument items of in-role and extra-role performance. ................... 30

Table 3-6: The instrument items of innovative work behavior. .................................. 31

Table 4-1: Descriptive statistics and reliabilities among study variables ................... 40

Table 4-2: Overall fit of the CFA model .................................................................... 44

Table 4-3: Component fit of the CFA model .............................................................. 44

Table 4-4: Comparison of hypothesized model and alternative model ...................... 46

Table 4-5: Chi-square difference test using the SB scaled chi-square ........................ 47

Table 4-6: Bootstrap estimates of the mediating effects of informal learning ........... 50

1

Chapter 1

INTRODUCTION

In current organizations, teams are considered to be a basic building unit of

performing and producing goods and services (Stewart & Barrick, 2000). A team can be

defined as “a distinguishable set of two or more people who interact, dynamically,

interdependently, and adaptively toward a common and valued goal/objective/mission”

(Salas, Dickinson, Converse, & Tannenbaum, 1992, p. 4). In order to generate

performance greater than the sum of individual work, people coordinate and create

synergy through interactions and communications with others. Because of the significant

growth of organizations’ environmental complexity and rapid changes of business

environments, individuals who are isolated in these environments are more likely to

encounter difficulties in performing interdependent tasks (Drucker, 1999; Joo, Song, Lim,

& Yoon, 2012). Previous studies have shown the importance of leaders’ relationships

with their team members in terms of performance and innovation in organizations.

McCallum and O’Connell (2009) claimed that leaders’ social skills, such as promoting

cooperation and sharing common goals and tasks, can positively influence their

members’ performances by sharing knowledge and information. In addition, this support

from leaders can augment the employees’ innovative work behaviors by offering

favorable job resources and by promoting their psychological well-being and safety

(Hammond, Neff, Farr, Schwall, & Zhao, 2011). This notion is consistent with many

previous studies that demonstrated the positive effects of leader-member exchange

(LMX) on various outcomes of organizations, such as organizational citizenship

2

behaviors, engagement, job satisfaction, and organizational commitment (Gerstner &

Day, 1997; Harris, Wheeler, & Kacmar, 2011; Martin, Guillaume, & Thomas, 2016).

Researchers have found a variety of positive consequences of the leader-member dyadic

relationship, and strong evidence has been duplicated based on empirical studies (e.g.,

Martin et al., 2016). However, the underlying mechanisms through which the leader-

follower relationship influences outcomes, especially an employee’s discretionary

behaviors, such as extra-role performance and innovative work behavior, remain

underdeveloped and inconclusive. From the perspective of the social exchange theory

(Blau, 1964), when employees receive positive treatment from their leader, they not only

fulfill their work-related obligations but also tend to reciprocate these positive treatments

with discretionary learning behaviors, including trials to solve challenging work,

cooperation with other co-workers, and voluntary attendance at work-related training

programs (Walumbwa, Cropanzano, & Hartnell, 2009). Building on the social exchange

theory, I therefore propose to examine the mediating role of informal learning in the

influences of LMX on employees’ performance and innovative behaviors. Informal

learning, which refers to unstructured and experiential learning, generally takes place

during individuals’ daily work activities within a great range of work circumstances

(Marsick & Watkins, 1990). According to Van der Sluis (2004), moreover, individuals

receiving favorable support from their supervisor are willing to emulate them, and thus

the supervisor can act as a role model for the subordinates’ development and learning. As

such, high quality relationships among a leader and subordinates can facilitate the

subordinates’ involvement in various informal learning processes due to the reciprocity

that, in turn, is expected to have positive effects on performance and innovation.

3

The present study contributes to the literature on organizational behavior and

workplace learning in at least three important ways: First, the majority of the existing

literature on leadership has focused on the top-down influences of leaders. Many

researchers in leadership studies focus on examining the impact of particular leadership

styles on the organization (e.g., transformational leadership [Wang, Law, Hackett, Wang,

& Chen, 2005]). However, the relational approach, which focuses on the dyadic

relationship between a leader and a follower, has been in and out of favor, although it is

relevant for both individual behavior and organizational outcomes. Given the growing

significance of social capital in the recent organizational behavior literature (McCallum

& O’Connell, 2009), examining the influences of LMX on the employee’s performance

and innovative behaviors in this current study is meaningful. Second, the mechanisms of

how the leader-follower relationship influences positive outcomes in the organization,

especially how it augments the employee’s job performance and innovative behavior,

remain unclear. As mentioned above, based on the social exchange perspective, exchange

of socio-emotional resources between a leader and a follower based upon mutual trust,

respect, and obligation could encourage followers’ informal learning activities and could

consequently lead to the enhancement of performance and innovative work behavior.

Finally, because this research was conducted in Korean organizations using a quantitative

approach, the data can provide empirical evidence on how LMX influence followers’

performance and innovative endeavor in Korean contexts.

Research Purpose

The purpose of this current study is to examine structural relationships among

leader-member exchange (LMX), informal learning, in-role performance, extra-role

4

performance, and innovative work behavior in business organizations in South Korea. By

doing so, this study can empirically contribute to literature related to LMX and workplace

learning and practices in the fields of human resource development (HRD) and

organization development (OD). To achieve the purpose, this study examined the direct

relationship between LMX and other variables used in this study (i.e., informal learning,

in-role performance, extra-role performance, and innovative work behavior).

Furthermore, this study explored the mediating role of informal learning in the

relationship of LMX with in-role performance, extra-role performance, and innovative

work behavior.

Research Questions

Based on the purpose of this study, the following research questions were

established:

1. To what extent is LMX related to subordinates’ informal learning?

2. To what extent is LMX related to subordinates’ in-role and extra-role job

performance?

3. To what extent is LMX related to subordinates’ innovative work behavior?

4. To what extent does informal learning mediate the relationship between LMX

and subordinates’ in-role and extra-role performance?

5. To what extent does informal learning mediate the relationship between LMX

and subordinates’ innovative work behavior?

Operational Definitions

Key research variables in this study are defined as below:

Leader-Member Exchange (LMX)

5

Leader-member exchange (LMX) is defined as exchange of valued resources

between leader and subordinate including physical resources (i.e., budgetary support and

materials) and socio-emotional resources (i.e., respect, trust, loyalty, and affect) (Liden &

Maslyn, 1998). In this study, LMX is operationally defined as a co-created process

between leader and follower through their social interactions based on trust and

reciprocity. A leader and follower dyadic exchange was measured by Liden, Wayne, and

Stilwell’s (1993) LMX instrument from both leader and follower perspectives.

In-Role and Extra-Role Performance

Performance can include two aspects: (a) in-role performance, which is related to

one’s main activities usually described in a job description, and (b) extra-role

performance (i.e., contextual performance), which is not directly related to one’s work

responsibility, but contributes to organizational effectiveness, such as helping co-workers

and spending extra time to achieve organizational objectives (Goodman & Svyantek,

1999). These activities and efforts are both important for achieving the organization’s

shared goals. An employee’s in-role and extra-role job performance was measured by

Goodman and Svyantek’s (1999) instrument in this study.

Innovative Work Behavior

Innovative work behavior is defined as employees’ behavior to seek the

application of new ideas, products, processes, and procedures to their work and/or

organization. An employee’s innovative work behavior was measured by Janssen’s

(2000) instrument.

Informal Learning

6

Informal learning is defined as unstructured and experiential learning that takes

place within a great range of work circumstances, including learning from social

relations, self-experimental behaviors, and searching external sources and information

(Choi & Jacobs, 2011; Marsick & Watkins, 1990). Informal learning, which is identified

as a mediator between independent and dependent variables in this study, was measured

by Choi and Jacobs’s (2011) instrument.

7

Chapter 2

REVIEW OF RELATED LITERATURE

Theoretical and empirical background of this study is provided in this chapter.

The concepts of leader-member exchange (LMX), informal learning, in-role and extra-

role performance, and innovative work behavior are reviewed in the first section. In the

second section of the chapter, the research model and hypotheses are explained based on

the extant literature.

Leader-Member Exchange

According to the existing literature, leadership includes following three domains:

leaders, followers, and the relationship between leaders and followers (Graen & Uhl-

Bien, 1995). Of three domains, the leader-based perspective was a predominant approach

among scholars in the leadership studies in the past as many scholars focused on leaders’

behaviors and their traits or attitudes as a key to address many issues related to leadership

in an organization (Graen & Uhl-Bien, 1995). However, as scholars realized that

leadership effectiveness is not solely determined by leader-related factors, other two

domains (i.e., followers and relationships of the leaders and followers) have gained more

attention by scholars in the 2000s. They suggested that leadership effectiveness is

achieved when a leader has a strong will to lead his or her followers and positively

influence them, as well as when followers have a strong willingness to follow their

leader’s vision and direction (Gibb, 1954; Graen & Uhl-Bien, 1995).

8

With the significance of their willingness to be engaged in their relationship both

sides, scholars have questioned which environmental characteristics create the proper

leader and follower relationship, which personal factors influence dyadic relationship,

and how these characteristics are related to organizational outcomes. Leader-member

exchange (LMX) theory which was initially conceptualized by Dansereau, Graen, and

Haga (1975) and Graen and Cashman (1975) tends to suggest the theoretical explanations

on these questions in the leadership literature. LMX theory, which evolved from Vertical

Dyad Linkage (VDL) model—according to the VDL model, leaders develop different

vertical dyads with their followers based on the leader and follower relationships rather

than the leaders’ particular leadership styles (Dansereau et al., 1975)—suggested that

leaders form differential relationships with each of their subordinates through the

construction of work-related exchanges within their work groups (Graen & Cashman,

1975).

In its early stage (in the 1970s), theoretical developments of LMX theory evolved

various theoretical content and dimensions. Cashman, Dansereau, Graen, and Haga

(1976) contended that LMX includes the concepts of attention and sensitivity as sub-

dimensions. Graen (1976) claimed that LMX was an exchange relationship which

developed based on interpersonal skill, trust, and competence. Later, the number of

dimensions was changed or expanded depending on researchers’ perspectives and

concepts.

During the 1980s, with the strong interest in the LMX model, different

conceptualizations of the construct were developed and the state of confusion continued.

For instance, according to a comprehensive literature review on LMX theory conducted

9

by Schriesheim, Castro, and Cogliser (1999), more than 35 different sub-constructs were

developed in research articles published in the 1980s. Despite the inconsistent

explanations of leader-follower relationships, six dimensional constructs (i.e., mutual

support, liking, attention, trust, loyalty, and latitude) were regarded as major components

in the leadership research field in the 1980s (Schriesheim et al., 1999).

According to Graen and Uhl-Bien (1995), the leadership development model

assumed that leaders can develop high quality LMX relationships with all of their

subordinates by being trained. This approach shifted the LMX perspectives from LMX

differentiation (in which leaders treat subordinates differently with their favors) to the

focus on developmental relationships between leaders and subordinates. According to

Graen and Uhl-Bien (1995), developmental relationship leadership can be built through a

role-making process, following three stages: (a) stranger, (b) acquaintance, and (c)

mature partnership. The first stage is when the leaders and their subordinates view each

other as strangers. In this stage, the interactions between leaders and their subordinates

take place based on formal employment contracts and economic exchanges. Their

relationship is specified by financial exchanges, and incremental influences do not exist.

The next stage is the acquaintance stage, in which leaders and their subordinates’

relationships are not limited by contractual factors. Rather, their social exchanges

increase on both personal and work levels through sharing information and resources.

The last stage is a mature partnership exchange, in which the exchanges occur

extensively and the incremental influence is very high. Moreover, Graen and Uhl-Bien

(1995) decisively identified LMX as a relational concept and claimed that LMX includes

three dimensions: respect, trust, and obligation:

10

An offer will not be made and accepted without (1) mutual respect for the

capabilities of the other, (2) the anticipation of deepening reciprocal trust with the

other, and (3) the expectation that interacting obligation will grow over time as

career-oriented social exchanges blossom into a partnership. (p. 237)

The quality of LMX differs based on the extent to which they mutually exchange

information, support, and resources. That is, subordinates in the in-group have high

quality LMX relationships and high levels of trust, respect, and obligation. On the other

hand, subordinates in the out-groups have low-quality LMX relationships and their

exchanges and support formally follow the employment contract. They do not have much

access to information and resources from their leaders.

Informal Learning

Informal learning can be defined as “unstructured” and “experiential” learning

(Marsick & Watkins, 1990). Informal learning is mainly encouraged through one’s

experience and a variety of contexts in which particular situations happen (Marsick &

Watkins, 1990). Moreover, in the informal learning perspective, individuals can always

informally learn if they are aware of a need to learn and change (Jarvis, 1987). In the

workplace, informal or experiential learning is especially integrated into employees’

daily work activities and takes place within a great range of work circumstances, such as

teaming, meetings, mentoring, interactions with customers and colleagues, and trial-error

(Marsick & Volpe, 1999). According to Lohman (2005), informal learning includes

various types of actions, such as collaboration, information sharing, observation, and

reading work-related magazines and books. Choi and Jacobs (2011) further indicated that

these various types of informal learning activities can be categorized into three

characteristics: learning with others, self-experimentation, and environmental scanning.

11

Informal learning significantly affects organizational effectiveness, such as job

performance, creativity, and commitment (e.g., Marsick & Watkins, 1990; Park &

Jacobs, 2011). Informal learning occurs in relation to an individual’s job and across the

entire work process. It is a reflective process through which one reassesses one’s vision,

interests, and framework of work by learning informally from one’s experience (Marsick

& Volpe, 1999). Work- and organization-related outcomes are more likely to be

developed.

As mentioned above, informal learning in the workplace is interrelated with

experience (Jarvis, 1987). Specifically, many kinds of activities, such as having meetings,

interacting with others, and sharing materials, can cause employees to recognize the

differences in their prior experience and a new experience as well as existing problems or

organizational routines. These recognitions of discrepancies and current situations may

motivate employees to explore the circumstances from different perspectives and reflect

on existing work processes or frameworks. Also, becoming aware of the necessity of

personal improvement can encourage employees to develop professional knowledge and

skills in order to resolve the current problems (Watkins & Marsick, 1990). That is,

individuals’ conscious awareness of learning and external environments provides an

impetus of learning and is critical drivers of informal learning.

Job Performance

Performance is the most widely-used construct by scholars, but it has been

conceptualized in various ways. Job performance, which highlights an aspect of behavior

rather the results of the behavior, refers to an employee’s actions that affect the

organizational goals and are under the control of the individual (Rotundo & Sackett,

12

2002). With regard to the behavioral aspect, job performance can be conceptualized by

three broad behavior groups: (a) in-role performance (i.e., task performance), (b) extra-

role performance (i.e., organizational citizenship behaviors or contextual performance),

and (c) counterproductive performance (Goodman & Svyantek, 1999; Rotundo &

Sackett, 2002). In-role performance (task performance) refers to a group of behaviors or

activities that is related to the completion of tasks. These behaviors or activities are

usually described in one’s job description (e.g., producing goods or services) and

regarded as criteria for performance appraisal and payment. Thus, successful completion

of this performance is directly related to one’s task-related knowledge, skills, and ability

(KSAs) (Goodman & Svyantek, 1999). In contrast, in-role performance (organizational

citizenship behaviors or contextual performance) refers to the behaviors that are not

exactly related to a task but which still positively influence the achievement of the

organization’s goals. Employees’ discretionary behaviors fall into this group such as

actively communicating with others, helping and supporting co-workers, endorsing

organizational objectives, and voluntarily participating in non-mandatory programs in the

workplace (Martin et al., 2016; Rotundo & Sackett, 2002). The extra-role behaviors are

not directly related to one’s job features and KSAs. Rather, these can be affected by

individuals’ predisposition and volition related to intrinsic motivational characteristics or

favorable environmental factors (Goodman & Svyantek, 1999). Finally,

counterproductive performance can be conceptualized as behaviors that negatively affect

the achievement of the organization’s goals and harm the well-being of groups or group

members, such as personal deviance, personal aggression, and downtime behaviors

(Rotundo & Sackett, 2002). Absenteeism, psychological withdrawal, and social loafing

13

behaviors are also regarded as counterproductive performance (Martin et al., 2016).

Previous researchers have commonly reported that individuals’ job performance can be

influenced by various factors, including individual characteristics and environmental

contexts. For instance, it was revealed that individual characteristics, such as personality

(e.g., Big Five [Judge & Zapata, 2015]), emotional intelligence (O'Boyle, Humphrey,

Pollack, Hawver, & Story, 2011), self-efficacy (Tims, Bakker, & Derks, 2014), and

positive emotion (Kaplan, Bradley, Luchman, & Haynes, 2009) and environmental

contexts, including job resources (e.g., LMX, job security, and job crafting [Aryee &

Chen, 2006; Tims et al., 2014; Wang, Lu, & Siu, 2015]) and organizational climates (e.g.,

organizational justice [Wang et al., 2015]) are critical drivers for individuals’ job

performance in various organizations. According to Rotundo and Sackett (2002), it is

difficult to determine the relative significance of three distinct performance groups (i.e.,

in-role, extra-role, and counterproductive performance) because the significance can vary

depending on organizational and job contexts. Both in-role and extra-role performance

were considered as performance variables in this study to examine what extant LMX

influences employees to promote task-related behaviors and also discretionary behaviors

that lead to organizational effectiveness.

Innovative Work Behavior

According to West and Farr (1990), innovation is defined as “the intentional

introduction and application within a role, group or organization of ideas, processes,

products or procedures, new to the relevant unit of adoption, designed to significantly

benefit the individual, the group, the organization or wider society” (p. 9). Similarly,

Yuan and Woodman (2010) state that innovative behavior is “an employee’s intentional

14

introduction or application of new ideas, products, processes, and procedures to his or her

work role, work unit, or organization” (p. 324). Using this terminology, many researchers

have noted differences among novelty, creativity, and innovation (e.g., Joo, McLean, &

Yang, 2013; Scott & Bruce, 1994; Yuan & Woodman, 2010). An apparent aspect of

creativity that is distinguishable from novelty is the ‘usefulness’ of an idea (Joo et al.,

2013). That is, an idea produced in the workplace should be creative, not novel, in that it

may be adopted to enhance an organization’s performance. Innovation, closely related to

and often considered interchangeable with creativity (Scott & Bruce, 1994), involves

employees’ behaviors in generating and/or introducing new ideas about services,

practices, processes, and procedures, as well as developing and/or implementing them

(Yuan & Woodman, 2010). That is, creativity is the construction of novel and useful

ideas not necessarily put into practices (Mumford & Gustafson, 1988), while innovation

is the flourishing realization of those ideas in an organization (Amabile, 1996).

An employee’s innovative work behavior, however, does not have a direct

relationship to one’s creativity (King, 1995) since innovative work behavior is affected

by a variety of variables related to interior and exterior organizations (Joo et al., 2013).

Many prior studies have identified various components that affect employees’ innovative

behaviors, including an organization’s environmental factors (e.g., LMX [Atwater &

Carmeli, 2009; Gumusluoglu & Ilsev, 2009; Scott & Bruce, 1994], cohesion [Joo et al.,

2012], organization culture [Hartmann, 2006]) and personal factors (e.g., energy [Atwater

& Carmeli, 2009], expectation [Yuan & Woodman, 2010], proactive behavior [Parker,

Williams, & Turner, 2006]).

15

Researchers have found that employees’ creativity is reinforced by an

organization that provides optimal contextual conditions; employees also recognize that

their creative work can be encouraged and supported by leaders and co-workers

(Hartmann, 2006). Amabile (1995) describes optimal contextual influences, including

support from their leaders, and working groups within their organizations, as well as

identifying adequate resources, challenging tasks, and autonomy in decision-making as

important for facilitating employees’ creativity. In a similar vein, Hartmann (2006)

argues that employees’ efforts to engage in innovative work are reinforced when an

organization enables autonomy in their work, common and instant feedback on

innovative ideas, and open communication platforms (e.g., sharing implicit knowledge

with skilled colleagues).

Research Model and Hypotheses

I reviewed concepts of LMX, informal learning, in-role and extra-role

performance, and innovative work behavior in the previous section. In this section, I

propose a research model and hypotheses based on the theoretical and empirical

explanation from the literature review.

First, the large number of LMX-related studies found that LMX is closely related

to various outcomes in organizations. From the perspective of the social exchange theory

(Blau, 1964), employees who have positive feelings toward their leaders will be more

interested in being impressive to their leaders. Moreover, when they perceive their

leaders’ behaviors as positive, they feel obligated to reciprocate behaviors that are

beneficial to their leaders. The employee’s feeling of obligation is normally generated

from their intrinsic feelings of wanting to reward their leader. That is, when leaders’ treat

16

employees in a favorable manner, employees are more willing to fulfill their obligations

and perform their tasks to meet their leaders’ expectations (Wang et al., 2005). In line

with this, employees receiving sufficient information and resources from their leader and

exchanging their novel ideas and suggestions with their leader (i.e., a high quality LMX

relationship) tend to exhibit high levels of workplace learning engagement (Walumbwa et

al., 2009). According to Cerasoli et al. (2018), a supportive supervisor is one of the

imperative predictors of employees’ informal learning behaviors since a supportive

supervisor cares about their developmental needs and career advancement and helps them

to develop sense of security and self-confidence, which lead to facing the challenges of

the current work situation. Moreover, because a leader having a high quality LMX

relationship tends to show role modeling behaviors to subordinates in terms of

development and learning, these modeling behaviors can positively affect followers’

engagement of informal learning activity (Van der Sluis, 2004). Thus, based on this

notion and in line with the literature, I propose the following:

Hypothesis 1. LMX will be positively related to subordinates’ informal learning.

Furthermore, numerous previous studies empirically revealed that a high quality

of LMX has positive impacts on employees’ performance. For instance, in a longitudinal

study conducted in health care-providing organizations in the United States, Moss,

Sanchez, Brumbaugh, and Borkowski (2009) found that a high quality of LMX

relationship has positive influences on employees’ performance. LMX encourages

employees not to avoid feedback conversations with their leaders and to gain insights into

their work processes, which in turn enhances employees’ job performance. These results

17

support Malle’s (1999) argument that people with high quality LMX relationships have

both transactional exchanges and social exchanges, whereas peoples with lower-quality

LMX relationships only have transactional exchanges in organizations (i.e., contractual

aspects). Similarly, Sue-Chan, Chen, and Lam (2011) found that LMX quality is closely

related to objective and subjective performance. In Chinese manufacturing organizations,

Hui, Law, and Chen (1999) revealed that the LMX relationship positively influences

subordinates’ in-role job performance and organizational citizenship behaviors. This

result implies that a leader and subordinate relationship is not only related to task-related

performance (i.e., in-role job performance), but also to employees’ psychology-related

performance (i.e., organizational citizenship behavior or extra-role performance). That

means that a leader’s behavior, such as providing greater information and resources to his

or her subordinates and seeking reciprocal relationships, positively affect the

subordinates’ task achievements and encourage them to have active interpersonal

relations and cooperation within organizations. A recent meta-analytic study of Martin et

al. (2016) also confirmed the positive associations between LMX relationship and job

performance as well as between LMX and organizational citizenship behavior. Taken

together, I posit the following:

Hypothesis 2. LMX will be positively related to subordinates’ (a) in-role

performance and (b) extra-role performance.

Moreover, prior research has theoretically and empirically shown positive and

direct influence of a high quality of LMX on employees’ innovative work behaviors.

Since innovation is change-oriented, adopting innovations requires employees to put in a

18

lot of effort to change the status quo and to have expertise and knowledge in their fields

to think differently. In addition, innovative employees often face the organizational

climate which is resistant to change (Agarwal, Datta, Blake-Beard, & Bhargava, 2012).

Because of these difficulties, tendency to remain in current circumstances and resist

change often hampers employees’ innovation in the workplace (Agarwal et al., 2012).

According to Amabile and Conti (1999), work environments, especially leaders’ support,

can play an important role for individual and organizational innovation by affecting

components of innovation such as intrinsic motivation to innovation, expertise, and

resources. It is important for leaders to show their strong trust in their employees’

behaviors and provide task-related information and resources to facilitate the adoption of

new procedures and processes. Moreover, leaders’ recognition to their employees’

innovative work efforts can additionally increase innovative behaviors. Given the fact

that trust, respect, and obligation can be developed through exchanges of material and

social/emotional resources between leaders and subordinates (Graen & Scandura, 1987),

high quality LMX relationships can augment employees’ innovative work behaviors.

Empirical studies provided enough proof about the relationship between leaders

and subordinates as a key component of subordinates’ innovative behaviors. For instance,

Agarwal et al. (2012) found that innovative work behaviors of employees working in the

service sector were enhanced by high quality LMX relationships. That is because more

direction, information, and emotional support offered by a leader fosters employees’

psychological safety and work engagement, which in turn can encourage employees to

approach more challenging and difficult tasks and be involved in a creative problem-

solving process. In addition, a meta-analysis examining antecedents of employee

19

innovation found that high quality LMX relationships are positively related to the

creation of innovation (Hammond et al., 2011). Based on this notion and in line with the

literature, I propose the following:

Hypothesis 3. LMX will be positively related to subordinates’ innovative work

behavior.

When it comes to a mediating role of informal learning in the relationships

between LMX and organizational outcomes (i.e., in-role performance, extra-role

performance, and innovative work behavior), as mentioned previously, leaders who have

mature partnership exchanges with their employees (high quality relationships) play

important roles in enhancing employees’ performance by offering greater resources over

time (Graen & Uhl-Bien, 1995; Schriesheim et al., 1999). Because a leader and

employees extensively share social interactions based on mutual respect, trust, and

obligation, social exchanges can significantly affect employees’ work processes as well

as outcomes. Given that informal learning is more likely to occur when employees are

aware of the developmental needs of their professional knowledge and skills, a high

quality LMX can drive employees’ informal learning. That is, information, support, and

recourses offered by a leader may stimulate employees to acknowledge existing problems

or needs for their personal growth, and thus can lead employees to be engaged in

informal learning, further contributing to the improvement of their performance and

innovation. An empirical study conducted by Walumbwa et al. (2009) supports this claim

that employees are more likely to voluntarily participate in learning activities when they

have a high quality LMX relationship with their leaders. Specifically, according to

20

Walumbwa et al. (2009), because employees with a high-quality LMX tend to participate

in mentoring and job-related training, they can much take voluntary learning actions.

These behaviors lead to the improvement of job performance and citizenship

performance. Similarly, De Coninck (2011) found that LMX was positively related to

employee performance by increasing employee commitment and making them involve

active learning behaviors, such as resource and information exchanges. Similarly, given

that expertise and knowledge are regarded as basic components of innovation at work

(Anderson, Potočnik, & Zhou, 2014), these learning activities can also positively

influence the development of innovative work behaviors. Therefore, I propose the

mediating effects of employees’ informal learning will influence the relationship between

LMX and in-role and extra-role performance as well as LMX and innovative work

behavior.

Hypothesis 4. informal learning will mediate the relationship between LMX and

subordinates’ (a) in-role performance and (b) extra-role performance.

Hypothesis 5. Informal learning will mediate the relationship between LMX and

subordinates’ innovative work behaviors.

Based on these research hypotheses, a hypothesized research model has been

proposed (See Figure 2-1).

21

Figure 2-1. The hypothesized model of the current study.

22

Chapter 3

METHODOLOGY

This chapter delineates the study methodological design and procedures.

Specifically, the following aspects are described in detail: (a) restatement of the research

purpose and research questions, (b) population and partcipants, (c) measures, (d) data

collection, and (e) data analysis approach.

Restatement of Research Purpose and Research Questions

The primary purpose of this study was to examine the structural relationships

among LMX (Leader Member Exchange), informal learning, in-role performance, extra-

role performance, and innovative work behavior in major business organizations in South

Korea. To achieve the research purpose, this study was guided by the following research

questions:

1. To what extent is LMX related to subordinates’ informal learning?

2. To what extent is LMX related to subordinates’ in-role and extra-role job

performance?

3. To what extent is LMX related to subordinates’ innovative work behavior?

4. To what extent does informal learning mediate the relationships between LMX

and subordinates’ in-role and extra-role performance?

5. To what extent does informal learning mediate the relationship between LMX

and subordinates’ innovative work behavior?

23

Population and Participants

The population of interest for this study included full-time employees (supervisors

and their subordinates) working in large companies in South Korea. The data were

gathered from both supervisors and their subordinates by adopting a dyadic leadership

approach to capture the quality of LMX relationships from both perspectives. Moreover,

because employees in temporary positions (e.g., contract workers, part-time workers)

might have difficulty in developing and assessing the quality of LMX relationships due to

the short-term nature of their work (Cha & Borchgrevink, 2017), this study only included

employees in full-time positions.

According to the South Korean Fair Trade Commission (2016), a Korean large

(major) company (enterprise) can be defined as an organization that has total assets of

over 10 trillion won. A predefined criterion regarding the number of employees for

defining a large company, however, was not used, although the number of employees can

also illustrate a company’s size. Indeed, the definition of the small and medium-size

enterprises (SMEs) includes the number of workers as one of the criteria, which is less

than 300 employees (SMEs, n.d.). Thus, for this study in addition to the company’s total

assets as a criterion of a large company, this study used the number of employees as a

standard to select a major company. Specifically, companies that have more than 300

employees in full-time positions or have over 10 trillion won in total assets were

regarded as large (major) organizations in this study. Furthermore, this research excluded

public or non-profit organizations (e.g., government, education, religious group) by only

targeting private business organizations. Because features of LMX relationships would

appear to be different in organizations where they have public organizational goals

24

(aiming to successfully offer service for public and societal benefit), this study focused

on employees working in the private business sector.

Overall demographic characteristics of the study participants are presented in

Table 3-1. For the subordinate group, 67.9% of the total respondents were male and

32.1% were female. Of the total subordinate respondents, 65.3% were in their thirties and

13.0% and 16.6% were in their twenties and forties, respectively. Most of the subordinate

participants (88%) graduated from a 4-year college or higher. About one-half of the

participants worked in either the finance or IT/communications industry (finance: 27.5%;

IT/communications: 21.2%), followed by service (14.0%), energy/chemical (9.8%), and

distribution (8.8%). More than half of the subordinate participants were either assistant

managers (38.5%) or managers (25.5%), followed by staff (19.8%). Regarding their job

type, 42.5% of the respondents worked in management support, including planning, HR,

finance, and accounting, and 31.6% in marketing and sales. Most of the subordinate

respondents (75.6%) worked for their current organizations for 10 years or less (less than

1 year: 10.9%; between 1 and 5 years: 32.6%; between 6 and 10 years: 32.1%).

For leaders, most of the participants (80.2%) were male and in their forties

(56.6%). Most of the leader participants (96.4%) graduated from a 4-year college or

higher (4-year college: 65.1%; graduate school: 31.3%). Regarding their work position,

most of the leaders (75.8%) were in general managerial positions, followed by

managerial positions (17.4%) and director positions (5.3%). About 31.8% of the leader

participants worked for their current organizations more than 20 years. Other

demographic information such as industry and type of job (job area) were similar to those

reported by their subordinates.

25

Table 3-1

Demographic Characteristics of Subordinates and Leaders

Characteristic Subordinates (n = 193) Leaders (n = 193)

Frequency % Frequency %

Gender

Male 131 67.9 154 80.2

Female 62 32.1 38 19.8

Total 193 100.0 192 100.0

Not answered - 1

Age

(Years)

20–29 25 13.0 0 0.0

30–39 126 65.3 58 30.1

40–49 32 16.6 109 56.5

Over 50 10 5.2 26 13.5

Total 193 100.0 193 100.0

Not answered - -

Highest

Education

Level

High school 4 2.1 1 0.5

2-year college 19 9.9 6 3.1

Undergraduate

degree 134 69.8 125 65.1

Graduate degree 35 18.2 60 31.3

Total 192 100.0 192 100.0

Not answered 1 1

Field of

Operation

Manufacturing 10 5.2 10 5.2

IT/Communication

s 41 21.2 51 26.4

Energy/Chemical 19 9.8 7 3.6

Construction 14 7.3 16 8.3

Finance 53 27.5 52 26.9

Distribution 17 8.8 18 9.3

Service 27 14.0 28 14.5

Other 12 6.2 11 5.7

Total 193 100.0 193 100.0

Not answered - -

Current

Work

Position

Staff 38 19.8 0 0.0

Assistant manager 74 38.5 3 1.6

Manager 49 25.5 33 17.4

General manager 31 16.1 144 75.8

Director or higher 0 0.0 10 5.3

Total 192 100.0 190 100.0

Not answered 1 3

Job Area R&D 12 6.2 12 6.3

IT & Internet 1 0.5 3 1.6

26

Marketing/Sales 61 31.6 65 33.9

Manufacturing 3 1.6 3 1.6

Management

Support 82 42.5 80 41.7

Other 34 17.6 29 15.1

Total 193 100.0 192 100.0

Not answered - 1

Current

Company

Experience

by Years

Less than 1 year 21 10.9 6 3.1

1–5 years 63 32.6 20 10.4

6–10 years 62 32.1 38 19.8

11–15 years 23 11.9 40 20.8

16–20 years 9 4.7 27 14.1

More than 20 years 15 7.8 61 31.8

Total 193 100.0 192 100.0

Not answered - 1

Measures

Measures Used in Collecting Data

A series of items were developed to collect demographic information from both

subordfinates and supervisors (leaders). Responses to those items were summarized in

Table 3-1. There were five measures used to collect data for the other variables in this

study, and details regarding those measures follow. Content validity and internal

consistency (Cronbach’s alpha) are provided for each Likert type response measure. The

complete instruments used for collecting data from subordinates or supervisors (leaders)

appear in Appendix B.

Leader-member exchange. To capture both leaders’ and subordinates’

perceptions about the quality of their leader-member relationships, LMX-7 and

supervisor versions of LMX-7 scales were used (Liden et al., 1993; Scandura & Graen,

1984). The LMX-7 scales are the most consistently used instrument and psychometrically

27

the most sound measure of LMX (Graen & Uhl-Bien, 1995; Moss et al., 2009). The

LMX-7 scales use a 5-point Likert-type response scale ranging from 1 (strongly disagree)

to 5 (strongly agree). Some items originally developed as interrogative sentences (Graen

& Uhl-Bien, 1995; Liden et al., 1993) were revised as declarative sentences in a Korean

version to be more understandable, consistent, and readable in the Korean context. For

instance, an item, “How would you describe your working relationship with your leader?

(1 = extremely ineffective; 5 = extremely effective)” was revised to “I have an effective

working relationship with my supervisor (1 = strongly disagree; 5 = strongly agree).”

Such a modification makes the item more direct and easier for participants to rate the

extent to which they agreed with the statement. The LMX-7 subordinate rating measure

was completed by subordinates, and a supervisor version of the LMX-7 measure, which

was a transformed subordinate rating version of the LMX (i.e., the mirroring approach;

Bauer & Erdogan, 2015), was completed by leaders. Cronbach’s alpha (internal

consistency) values were .92 for the supervisor-rated LMX and .90 for the subordinate-

rated LMX.

Table 3-2

The Instrument Items of Subordinate-Rated Leader-Member Exchange

1. I usually know where I stand with my supervisor.

2. My supervisor understands my problems and needs.

3. My supervisor recognizes my potential.

4. Regardless of how much power he/she has built into his/her position, my supervisor

would be personally inclined to use his/her power to help me solve problems in my

work.

5. I can count on my supervisor to “bail me out” even at his/her own expense, when I

really need it.

6. My supervisor has enough confidence in me that he/she would defend and justify my

decisions if I were not present to do so.

7. I have an effective working relationship with my supervisor.

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Table 3-3

The Instrument Items of Supervisor-Rated Leader-Member Exchange

1. I usually let my subordinate know where he or she stands with me.

2. I think that I understand my subordinate's problems and needs.

3. I think that I recognize my subordinate's potential.

4. Regardless of how much power I have built into my position, I would be personally

inclined to use my power to help my subordinate solve problems in his or her work.

5. I would be willing to "bail out" my subordinate, even at my own expense, if he or she

really needed it.

6. I have enough confidence in my subordinate that I would defend and justify his or her

decisions if he or she were not present to do so.

7. I have an effective working relationship with my subordinate.

Informal learning. Informal learning refers to learning that individual employees

engage in during their daily work situations in a self-initiated manner, when they need to

perform some challenging task or to improve their work-related competencies. Lohman

(2005) developed the original instrument of informal learning, which consists of three

types of activities: knowledge exchange, experimenting, and environmental scanning.

Choi and Jacobs (2011) further extended and revised Lohman’s (2005) instrument based

on a Korean context. Informal learning of employees was measured by Choi and Jacobs’s

(2011) 12-item instrument in this research. Their instrument reflected the Korean context,

and it has been validated in the Korean context (Choi & Jacobs, 2011). The instrument is

a self-report questionnaire and contains the following three dimensions: learning with

others, self-experimentation, and external scanning. Subordinates rated each item on a 5-

point Likert-type response scale (1 = very infrequent; 5 = very frequent). Cronbach’s

alpha coefficient was .90. In this study the total scale score was used with no analysis

done utilizing the separate dimensions.

29

Table 3-4

The Instrument Items of Informal Learning

Dimension Item

Learning

With

Others

(In the past year, the frequency in which I engaged in these learning

activities was: )

1. Informal one-on-one discussion with supervisor about some work

situation.

2. Idea exchange on how to solve a problem situation with peers during a

break or lunch period.

3. Observation of how other employees dealt with a challenging work

situation.

4. Collaboration with others who shared the need to solve a particular

problem.

Self-

Experiment

ation

5. Spending time to reflect back how I dealt with a challenging work

situation.

6. Trying to solve a challenging work situation through trial and error

process by myself.

7. Spending time to reflect on what I had learned in a classroom training

program to apply that information to a challenging work situation.

8. Reading a standard operations manual or other similar texts on my own

to find an answer to a question.

External

Scanning

9. Searching the Internet for information to help solve a challenging work

situation.

10. Attendance at a non-mandatory professional conference or seminar that

might provide useful information.

11. Reading professional magazines or vender publications to be current in

some topic.

12. Having contact with someone outside the company who is able to help

solve a challenging work situation.

In-role performance and extra-role performance. To explore both the

achievement of tasks and the contributions of employees’ positive behaviors on

achievement of organization goals, two aspects (i.e., task-related and not task-related

performance) were regarded as reflecting job performance in this research (Martin et al.,

2016; Rotundo & Sackett, 2002). Job performance was measured by Goodman and

30

Svyantek’s (1999) six-item measure, which consists of three items for in-role

performance and three items for extra-role performance (Table 3-5). Regarding the

translation to Korean, the bilingual translator suggested that the meaning of the item,

“Your team member willingly attends functions not required by the organization, but

helps in its overall image,” might be a bit different from the original version of the item

when it was directly translated into Korean. That is because the word image as used in

Korean only encompasses its meaning in a narrow sense. Thus, the phrase, “help in its

overall image,” was revised into “help in the organization” in the Korean version of the

instrument based on the consensus of three members of the translation team. Instead of

self-assessment, leaders rated their subordinates’ in-role and extra-role performance on a

7-point Likert scale (1 = strongly disagree; 7 = strongly agree). Cronbach’s alpha

coefficients values were .87 for in-role performance and .77 for extra-role performance.

Table 3-5

The Instrument Items of In-role and Extra-Role Performance

Dimension Item

In-role

Performance

1. My subordinate achieves the objectives of the job.

2. My subordinate fulfills all the requirements for their job.

3. My subordinate performs well in the overall job by carrying out tasks

as expected.

Extra-role

Performance

4. My subordinate willingly attends functions not required by the

organization but helps in the organization.

5. My subordinate takes initiative to orient new employees to the

department even though not part of their job description.

6. My subordinate helps other employees with their work when they have

been absent.

Innovative work behavior. Innovative work behaviors were measured by

Janssen’s (2000) instrument. The nine-item instrument includes three items for idea

31

generation, three items for idea promotion, and three items for idea realization. To reduce

the potential bias of self-reported method, a leader assessed his or her followers’

innovative work behaviors. All items use a 7-point Likert scale (1 = strongly disagree; 7

= strongly agree). Cronbach’s alpha coefficient was .96 for the leader-related innovative

work behaviors.

Table 3-6

The Instrument Items of Innovative Work Behavior

Dimension Item

Idea

Generation

1. My subordinate is creating new ideas for difficult issues.

2. My subordinate is searching out new working method, techniques, or

instruments.

3. My subordinate is generating original solutions for problems.

Idea

Promotion

4. My subordinate is mobilizing support for innovative ideas.

5. My subordinate is acquiring approval for innovative ideas.

6. My subordinate is making important organizational members

enthusiastic for innovative ideas.

Idea

Realization

7. My member is transforming innovative ideas into useful applications.

8. My member is introducing innovative ideas into the work environment

in a systemic way.

9. My member is evaluating the utility of innovative work behaviors in

the workplace.

Demographic variables. Items to obtain demographic variables were developed.

The demographic variables included gender, age, highest education completed, industry,

current work position, job area, and total years of working in the current organization.

Translation Procedures

A process for the creation of the Korean version of the instrument was followed

since most of the instruments used for this study, except the informal learning scale, have

32

been developed in English. To guarantee the functional equivalence of the English

version and the Korean version, the following four steps were conducted based on the

backward translation procedure of Brislin (1986). First, the instrument’s original English

questionnaires (See Appendix B) were translated into Korean by a bilingual translator

who has professional knowledge of HRD with practical experience in the field of HRD

and workplace learning in Korean organizations. Second, after that, the completed

translation was translated back into English by another bilingual HRD professional who

has earned a doctoral degree in the US. Third, the two translators and I had a meeting to

compare the two versions (English and Korean) of the completed translation and discuss

discrepancies. We did not find critical discrepancies between the two versions except for

the issues noted in the Measures section above. We sought to achieve a very satisfactory

agreement even when there were minor discrepancies. Fourth, the instruments were sent

to two Korean HRD practitioners who are fluent in both English and Korean to get

feedback from people outside of the translation procedures and ensure that items were

interpretable in Korean. Their review did not suggest any noteworthy changes in any of

the items used in this research (See Appendix C).

Data Collection

After translating items into Korean, the survey questionnaires were created

through Qualtrics, an online-based survey system available through The Pennsylvania

State University. Separate questionnaires were developed to be administered to leaders

and subordinates through Qualtrics. The Institutional Review Board (IRB) approval

process was completed before conducting the data collection to ensure the protection of

33

human subjects and to fulfill the regulations of The Pennsylvania State University (See

Appendix A).

To recruit participants, I used my personal HRD professional networks and a

snowball sampling (also called referral or chain sampling) approach. First, I contacted

HRD professionals in Korean major organizations for whom I have contact information

by e-mail or phone to recruit employees working their respective organizations. The

initial contact included an explanation of the study purpose and research questions as

well as a request for permission to conduct the online survey in their organizations. When

HRD professionals had interest in this research and permitted the data collection in their

organizations, they were asked to distribute to randomly selected leaders the link to the

online form. A cover letter of the online form asking for survey participation explained

the purpose of the study and provided assurances of participant confidentiality. When

both they and their subordinates wanted to voluntarily participate in this research after

reading all the information, they were requested to insert their email addresses (leader)

and at least their two or three immediate subordinates. A leader desired to participate in

the survey was asked to select more than one subordinate because of potential selection

bias—leaders may tend to select those subordinates with whom they had amicable

relationships. Thus, among a list of multiple subordinates, I randomly chose one and

provided a survey packet. Collecting an email address was necessary in this study as it

was used to distribute the online survey packet and served as an identification code to

match a leader and a subordinate. However, no other identification information except an

email address (e.g., names and identification numbers) was collected.

34

After collecting email addresses through the online request form, I distributed

separate survey packets to leaders and their subordinates via emails. I first distributed the

survey questionnaires to the potential subordinate participants. When they completed the

subordinate instrument, the questionnaires for leaders were distributed to subordinates’

leaders. The survey packets also included the explanation of the study purpose and their

right to stop their participation any time. My contact information including my mail

address, phone number, and email address was provided for them to contact me when

they had any questions on this research and/or privacy issues. As an effort to increase the

participant response rate, a gentle reminder to complete the survey was sent twice: after

one week and three weeks. To expand the data collection to various organizations and

industries, I asked HRD professionals to introduce me to new HRD professionals in other

organizations who might be interested in this study. When someone was introduced, I

repeated my recruitment process. The response rate was approximately 78% for

subordinates (the survey was sent to approximately 280 subordinates, and a total of 219

responses were collected) and 88% for leaders (the survey was sent to 219 leaders, and a

total of 193 responses were collected). A total of 26 responses were discarded because of

the failure to match the responses between leaders and subordinates).

Data Analysis

The main aim of this study was to examine the structural relationships among

LMX, informal learning, in-role and extra-role performance, and innovative work

behaviors in major Korean organizations. To fulfill the research purpose, I employed

structural equation modeling (SEM) analysis techniques using Mplus for Windows

35

Release 8.0 and the Statistical Package for the Social Sciences (SPSS) for Windows

Release 20.0. Application of SEM analysis included the following steps: (a) model

specification, (b) model identification, (c) measure selection and data collection, (d)

model estimation, (e) model evaluation, and (f) model re-specification (Kline, 2011; Lei

& Wu, 2007).

First, model specification is to develop a sound structural equation model based

on findings in the literature and knowledge in the field (Kline, 2011; Lei & Wu, 2007). A

hypothesized model for this study was also conceptualized and represented in graphical

form based on the literature on LMX and informal learning. After that, model

identification was conducted. According to Lei and Wu (2007), as a rule, a model may be

identified if there is a unique estimate of every parameter in the model by containing

fewer parameters to be estimated than the number of variances and covariances (i.e., the

number of observations). Moreover, when a model consists of the measurement part and

latent part (structural part), the measurement part of the model satisfies the following

conditions to be identified: (a) there were no correlated errors in the measurement parts,

(b) factor complexity should be 1 (i.e., no cross loading), and (c) the number of indicators

per factor should be at least three (i.e., three-indicator rule). Additionally, for the

structural part of the model to be identified, it should satisfy the recursive rule (i.e., there

are no feedback loops or reciprocal causation and no correlations among errors) (Lei &

Wu, 2007). Based on these rules, since the hypothesized model for this study, including

both the measurement part and structural part, satisfies all aforementioned conditions, it

was said to be identified.

36

After selecting appropriate measures and collecting data, the model estimation

was performed. Specifically, I first conducted a confirmatory factor analysis (CFA) to

check the discriminant validity of the research variables (i.e., LMX, informal learning, in-

role performance, extra-role performance, and innovative work behaviors). Prior to

performing the CFA model test, preliminary data analysis (i.e., testing for mean, standard

deviation, skewness, kurtosis, and univariate and multivariate normality of the data) was

conducted by using SPSS for Windows to ensure the normality of the data, which is a

precondition for a CFA analysis. Furthermore, Harman’s single-factor test and CFA for

the single-factor model were conducted to check if issues related to a common method

bias existed in the data. The model estimation stage included two steps: the measurement

model assessment and structural model assessment. To evaluate overall fit of those

models, several goodness-of-fit indices were used along with chi-square statistics (χ2):

root mean square error of approximation (RMSEA), standardized root mean square

residual (SRMR), comparative fit index (CFI), and non-normed fit index or Tucker-

Lewis index (NNFI or TLI) (Hu & Bentler, 1999; Kline, 2011). The cut-off criteria for

acceptable fit to the data are as follows: RMSEA and SRMR values should be smaller

than .08 (Hu & Bentler, 1999) and CFI and TLI values should be greater than .90

(Bentler, 1992). For the good fit data, RMSEA values should be smaller than .06 (Hu &

Bentler, 1999), SRMR values smaller than .05 (Jöreskog & Sörbom, 1982), and CFI and

TLI values close to or greater than .95 (Bentler, 1999).

In addition to the evaluation of the overall model fit, the component model fit was

also assessed by considering signs and magnitudes of parameter estimates and reasonable

standard errors. Parameter estimates in the measurement equations should satisfy the

37

following conditions: (a) all factor loadings in the measurement equations should be at

least .50 or higher, (b) average variance extracted (AVE) should be .50 or higher, (c) the

magnitudes of parameter estimates should be less than 1 (r < 1) with no negative

variances, and (d) the standard errors of the factors should be smaller than the standard

deviations of their indicators (Hair, Tatham, Anderson, & Black, 2006). If all conditions

are satisfied, it can be concluded that the measurement model reasonably fits the data.

When the measurement model was acceptable, the overall fit of the structural

model was examined with consideration of the chi-square as well as the essential

goodness-of-fit indices (i.e., RMSEA, SRMR, CFI, and TLI). In addition to the chi-

square and goodness-of-fit indices, the component model fit was evaluated with

consideration of the parameter estimates such that (a) all path coefficients in the

structural equations (|t| values) should be larger than 1.96, (b) the magnitudes of

parameter estimates should be less than 1 (r < 1) with no negative variances, and (c) the

standard errors of the predictors should be smaller than the standard deviations of their

outcome variables.

Furthermore, a bootstrapping procedure (Preacher & Hayes, 2008) was conducted

to examine the indirect effect of LMX on followers’ in-role performance, extra-role

performance, and innovative work behaviors. Bootstrapping values were considered with

95% and 99.5% confidence intervals around the indirect effects (i.e., mediating effect of

informal learning).

In the model respecification stage, if, after conducting the model estimation and

evaluations, the model fit was poor and had statistically non-significant values, a model

respecification was developed by eliminating parameters. I also specified a model again

38

based on the results of the model estimation and compared the hypothesized model with

the revised model. Finally, the model was selected based on the results of the chi-square

difference test and theoretical relationship. The detailed results of the data analysis using

SEM appear in Chapter 4.

39

Chapter 4

RESULTS

The study demonstrates the relationships between LMX and employee

performance (i.e., in-role and extra-role performance) as well as the relationships

between LMX and innovative work behavior. Moreover, this research examined a role of

informal learning as a factor that mediates these relationships. This chapter delineates the

results of statistical data analysis including descriptive analysis, SEM analysis (i.e.,

measurement model analysis and structural model analysis), and mediating effect

analysis (i.e., a bootstrap estimate).

Descriptive Statistics

Table 4-1 presents means, standard deviations, and bivariate correlations among

the study variables and reliability (internal consistency). Pearson correlation were in the

expected directions and indicates no potential problem with multicollinearity (|r| < .85;

Lei & Wu, 2007). Cronbach’s alpha of all summated Likert scale measures indicates an

acceptable level of reliability, in that the values range from .776 to .971.

Normality

Outliers and univariate and bivariate normality were checked as a preliminary

analysis of data. I found two outliers (one was in informal learning and one in extra-role

performance) by checking Boxplots of all measures; they were removed. The result of the

univariate normality test shows that a mild form of univariate non-normality existed,

presenting that all values of skewness and kurtosis are less than |1| (i.e., skewness ranges

40

from |0.104| to |0.977|; kurtosis ranges from |0.006| to |0.917|). The multivariate normality

test shows that p-values of skewness and kurtosis were significant (p < .05), indicating

that the data did not have a normal distribution. However, the result of the relative

multivariate kurtosis shows a value of 1.076 (less than 1.0 is regarded as a multivariate

normal distribution and above 1.5 is regarded as extremely non-normal; Lei, 2015),

indicating that the data were inflated by 7.6% compared to a perfectly normal

distribution. Therefore, based on these results, I assumed that this data set has moderate

non-normality, and therefore employed robust ML estimation (Satorra-Bentler (SB)

scaled chi-square) to handle the non-normality of the data (i.e., MLR in Mplus) (Kline,

2011).

Table 4-1

Descriptive Statistics and Reliabilities among Study Variables

Variable M SD α 1 2 3 4 5

1. Leader-Member

Exchange 3.984 .460 .909 1

2. Informal

Learning 3.857 .414 .798 .490** 1

3. In-Role

Performance 5.693 .939 .899 .458** .434** 1

4. Extra-Role

Performance 5.696 .869 .776 .457** .338** .529** 1

5. Innovative Work

Behavior 5.005 1.156 .971 .491** .519** .637** .568** 1

Notes. n = 191 (dyad); α = Cronbach’s Alpha; M = mean; SD = standard deviation. **p < .01

(two-tailed). LMX Likert response scale was 1= SD through 5 = SA. In-Role and Extra-Role Job

Performance and Innovative Work Behavior Likert response scales were 1=SD through 7 =SA.

Informal Learning Likert response scale was 1 = Very Infrequent through 5 = Very Frequent.

Common Method Variance

To reduce the common method variance (CMV), I collected data from different

41

sources. LMX was rated by both leaders and subordinates, informal learning was rated by

subordinates (i.e., self-reported method), and dependent variables (i.e., subordinates’ in-

role performance, extra-role performance, and innovative work behaviors) were rated by

leaders. By obtaining data from different raters, I minimized the potential problems of

CMV. To check if the data involved a common method effect (i.e., the variance is

attributable to the measurement method rather than to the construct of interest; Podsakoff,

MacKenzie, Lee, & Podsakoff, 2003, p. 879), the following two statistical techniques

were used: (a) Harman’s single-factor test and (b) CFA for the single-factor model

(Podsakoff et al., 2003). The result of Harman’s single-factor test suggests all of the

observed items of the measurement parts do not load onto one common and major factor,

showing 44.69% of total variance explained (i.e., criterion: 50.0%). In addition, the result

of CFA of the single-factor model suggests a poor explanation given that all goodness-of-

fit indices do not meet the cut-off criteria (χ2 (152) = 1049.215, p < .001; RMSEA

= .176; SRMR = .115; CFI = .577; TLI = .524). These results led to a conclusion that

common method bias does not pose a problem in this study.

Assessment of Model Fit

Item Parcels

Before conducting the measurement model fit assessment (i.e., CFA), I employed

item parceling procedures for the multidimensional variables (i.e., informal learning and

innovative work behavior) due to the relatively small sample size in relation to the

measurement items. This method is commonly used when the number of items is large

and items within each parcel are known to measure a single factor (construct) (Kline,

42

2011). Thus, I only parceled multidimensional variables, which have many items (12

items of informal learning and nine items of innovative work behavior) by averaging

items into dimensions and treating the different dimensions as indicators of their

corresponding variables.

Informal learning. The results of the overall fit of CFA suggest the parceled

model of informal learning is proper and acceptable. According to the literature on SEM,

the exact-fit hypothesis can often be rejected based on the chi-square statistics because

the chi-square statistics are extremely sensitive to sample size and the number of

measures so that other model fit indices, such as RMSEA, SRMR, CFI, and TLI, need to

be considered to evaluate the model fit (Kline, 2011; Lei & Wu, 2007). Thus, although

the SB scaled chi-square of the CFA model of informal learning is statistically significant

(χ2 (51) = 53.314, p < .01), it was concluded that the model has a good fit with my data

as the other goodness-of-fit indices indicate the CFA model fits the data well (RMSEA

= .050; SRMR = .054; CFI = .932; TLI = .912). Regarding the component model fit, all

factor loadings are statistically significant (|t| > 1.96, p < .05) and unreasonable directions

(e.g., negative variance) and magnitudes (e.g., r > 1) of the parameter estimates are not

found. In addition, standard errors are smaller than the standard deviations, which means

they are reasonably small. All residual values of correlation are less than .10. In sum,

based on the results of the overall fit and the estimation solution, the model of informal

learning parceled adequately fits the data.

Innovative work behaviors. Regarding the results of the overall CFA model,

goodness-of-fit indices of the CFA model of innovative work behaviors indicate the

model explains the data well (RMSEA = .060; SRMR = .016; CFI = .986; TLI = .980),

43

although the SB scaled chi-square is statistically significant (χ2 (24) = 40.564, p < .01).

The component model fit is also acceptable regarding the following aspects: signs

(direction) and magnitudes of parameter estimates are reasonable as there are no negative

variance and out-of-range values (i.e., r < 1); standard errors are smaller than the standard

deviations; all values of correlation residuals are reasonable (< .10). Taken together, it is

concluded that conducting item parceling for innovative work behavior is reasonable in

this study.

Assessment of Measurement Model Fit

I first conducted a CFA of the hypothesized model. According to the overall fit

statistics as seen in Table 4-2, the results suggest that the model has a good fit to the data

(RMSEA = .060; SRMR = .053; CFI = .954; TLI = .945), except the SB scaled chi-

square (χ2 (142) = 239.642, p < .001). Moreover, the component fit of the measurement

model does not include any possible improper solutions. First, as seen in Table 4-3, all

standardized factor loadings of the measurement model are at least above .4 or mostly

above .7, which supports the convergent validity of the measures contained in this study.

Specifically, the range of factor loadings of the five measures is as follows: LMX = .654

to .837; informal learning = .681 to .766; in-role performance = .837 to .913; extra-role

performance = .663 to .870; innovative work behavior = .931 to .940. Additionally, all t

values of the factor loadings are statistically significant (|t| > 1.96, p < .05). Second,

variances of the variables are all positive, and correlations are less than 1. Third, of the

361 correlation residuals, all values are less than .10 except four values. Because they are

less than 10% of the residuals, it does not pose a potential problem. Based on these

44

results of the overall fit and component fit, the hypothesized measurement model fits the

data well.

Table 4-2

Overall Fit of the CFA Model

SB Scaled χ2 (df) RMSEA SRMR CFI TLI

Values χ2 (142) = 239.642*** .060 .053 .954 .945

Note. ***p < .000

Table 4-3

Component Fit of the CFA Model

Scale and Item Standardized

Loading SE t value & p

Leader-Member Exchange

Indicator 1

0.654

0.051

12.841***

Indicator 2 0.792 0.032 24.994***

Indicator 3 0.732 0.042 17.517***

Indicator 4 0.803 0.030 26.368***

Indicator 5 0.729 0.039 18.613***

Indicator 6 0.837 0.025 33.927***

Indicator 7 0.821 0.029 28.015***

Informal Learning

Indicator 1

0.766

0.051

14.951***

Indicator 2 0.677 0.054 12.529***

Indicator 3 0.681 0.052 13.043***

In-Role Performance

Indicator 1 0.837 0.028 29.583***

Indicator 2 0.913 0.020 46.343***

Indicator 3 0.849 0.030 28.329***

Extra-Role Performance

Indicator 1

0.708

0.077

9.214***

Indicator 2 0.870 0.041 20.985***

Indicator 3 0.663 0.088 7.508***

Innovative Work Behavior

Indicator 1

0.935

0.012

75.930***

Indicator 2 0.931 0.016 57.705***

Indicator 3 0.940 0.011 82.323***

Note. ***p < .000; SE = standard error

45

Assessment of Structural Model Fit

I further conducted a structural model assessment to examine the relationships

among latent variables based on the study hypotheses. Because the structural model (i.e.,

full model) is equivalent to the measurement model (i.e., CFA model), the results of the

overall fit of the structural model are the same as those of the CFA model (χ2 (142) =

239.642, p < .001; RMSEA = .060; SRMR = .053; CFI = .954; TLI = .945). In addition to

the overall fit, component fit of the hypothesized structural model is also identical in

terms of the estimates of factor loadings and measurement error variance and covariance.

Thus, there are no improper solutions regarding the reasonable sign (direction) and

magnitude of parameter estimates, no negative covariance, and reasonably small standard

errors and correlation residuals. Moreover, squared multiple correlations (R2) in the

structural equations indicate that all latent variables, including informal learning (R2

= .373), in-role performance (R2 = .338), extra-role performance (R2 = .268), and

innovative work behavior (R2 = .401), have a large effect size based on the Cohen's R2

(i.e., .0196 as small effect size, .1300 as medium effect size, and .2600 as large effect

size) (Kotrlik & Williams, 2003). Regarding the path coefficients, all path coefficients

are statistically significant (|t| > 1.96, p < .05); however, the direct path from informal

learning to extra-role performance is not statistically significant (t = 1.059, p > .05).

Model Modification and Comparison

Because the hypothesized structural model includes a nonsignificant path (i.e., the

path from informal learning to extra-role performance), model modification was

conducted by creating and testing an alternative model. In the alternative model, the non-

significant path was fixed to zero, which allowed the alternative model and the

46

hypothesized model to be nested. This study used robust ML estimation and the modified

model is a nested model of the hypothesized model; the chi-square difference test using

the SB scaled chi-square was conducted.

Table 4-4 represents the comparison of the overall fit indices of the hypothesized

model and alternative model. All of the goodness-of-fit indices do not change (i.e.,

RMSEA, CFI, and TLI), except SRMR. The hypothesized model yields the SRMR

of .053 and the alternative model produced the SRMR of .055.

Table 4-4

Comparison of Hypothesized Model and Alternative Model

Model SB Scaled χ2 (df) RMSE

A SRMR CFI TLI

Hypothesized Model χ2 (142) = 239.642*** .060 .053 .954 .945

Alternative Model χ2 (143) = 240.482*** .060 .055 .954 .945

***p < .001

To compare the SB scaled chi-square, I further conducted chi-square difference

test using the SB scaled chi-square with the hypothesized and alternative models (see

Table 4-5). The results of the chi-square difference test show that the difference between

the two models is not statistically significant (Δχ2 (1) = 1.02536). Therefore, based on the

parsimonious reasons, the alternative model was selected as the final model (M2) in this

study.

47

Table 4-5

Chi-Square Difference Test Using the SB Scaled Chi-Square

Hypothesized Model

(M1)

Alternative Model

(M2)

Scaling correction factor c1 1.0641 c2 1.0662

MR chi-square T1 239.642 T2 240.482

ML chi-square c1*T1 255.003 c2*T2 256.402

df (Degree of freedom) d1 142 d2 143

cd (Difference test scaling

correction)

(C1* d1)- (C2 * d2)/(d1- d2)

-1.3644

TRd (Satorra-Bentler scaled

χ2 difference test)

(c1* T1- c2*T2)/cd

1.02536

Assessment of the Final Model Fit

The measurement and structural model assessments for the final model (M2) were

performed. The results of the overall fit statistics indicate that the SB scaled chi-square is

statistically significant (χ2 (143) = 240.482, p < .001), indicating that the exact-fit

hypothesis would be rejected. However, because the chi-square statistics is sensitive to

sample size (Kline, 2011; Lei & Wu, 2007), goodness-of-fit indices were considered. As

seen in Table 4-4, all goodness-of-fit indices included in this study (RMSEA = .060;

SRMR = .055; CFI = .954; TLI = .945) meet the aforementioned cut-off criteria.

Moreover, when it comes to the component model fit, all factor loadings in the

measurement parts and all path coefficients in the structural parts are statistically

significant (|t| > 1.96, p < .05). There are no improper solutions considering the inclusion

of negative variance and abnormal correlations. Regarding correlation residuals, six of

361 correlation residuals (1.7%) were above .10, which would not be considered

problematic. Moreover, based on Cohen's R2 statistics (i.e., .0196 as small effect

48

size, .1300 as medium effect size, and .2600 as large effect size; Kotrlik & Williams,

2003), squared multiple correlations (R2) have a medium to large effect size: informal

learning (R2 = .379), in-role performance (R2 = .324), extra-role performance (R2 = .258),

and innovative work behavior (R2 = .382). Based on these results, it was confirmed that

the final model (i.e., alternative model) fits the data more adequately than the

hypothesized model.

Figure 4-1. The structural model with standardized path coefficients.

Hypothesis Testing

Given the alternative model was selected as the final model of this study, the

study hypotheses are evaluated based on the results of the alternative model evaluation.

Specifically, I primarily checked standardized path coefficients (SPC) and t value, which

indicates the magnitude and the direction of the proposed relationships in this study.

Direct Relationship between Independent and Dependent Variables

49

Hypothesis 1 posited that LMX would be positively related to subordinates’

informal learning. As seen in Figure 4-1, it was found that the relationship between LMX

and informal learning is statistically significant (SPC = .616, t = 9.965). Therefore,

Hypothesis 1 is supported.

Hypothesis 2 suggested that LMX would be positively related to subordinates’ in-

role (H2a) and extra-role (H2b) performance. The results show that positive and direct

effects of LMX on in-role performance (SPC = .326, t = 3.373) and extra-role

performance (SPC = .508, t = 6.526) are statistically significant. Thus, Hypothesis 2 is

supported.

Hypothesis 3 predicted that LMX would be positively related to subordinates’

innovative work behavior. Based on the results of SPC and t values evaluation (SPC

= .261, t = 2.692), it revealed that LMX positively influences innovative work behavior,

supporting Hypothesis 3.

Indirect Relationships between Independent and Dependent Variables

Hypotheses 4 and 5 posited a mediating effect of informal learning in the

relationship with LMX and performances (i.e., in-role and extra-role performance) as

well as the relationship with LMX and innovative work behavior. To test the mediating

effects, a bootstrap estimate approach suggested by Preacher and Hayes (2008) was used.

Bootstrapping statistical technique is the most powerful method and is commonly used to

decompose effects in the SEM results because the bootstrapping procedure is not affected

by data normality issues. I created 1,000 bootstrap samples and estimated the indirect

effects of LMX on performance and innovative work behaviors with the bias-corrected

percentile method (Efron & Tibshirami, 1993).

50

Table 4-6

Bootstrap Estimates of the Mediating Effects of Informal Learning

Effect ab

Product of

Coefficients 95% CI 99.5% CI

SE Z Lower

limit

Upper

limit

Lower

limit

Upper

limit

LMX →

Informal learning

→ In-role

performance

.189 0.074 2.536 .075 .318 .019 .426

LMX →

Informal learning

→ Innovative work

behavior

.260 0.064 4.032 .164 .383 .123 .475

Note. ab = completely standardized estimate of the mediating effect; SE = standard error;

CI = confidence interval.

Hypothesis 4 predicted that informal learning would mediate the relationship

between LMX and subordinate’ in-role (H4a) and extra-role (H4b) performance. As seen

in Table 4-6, the indirect effect of LMX on in-role performance via informal learning

is .189 with a bootstrapped 95% confidence interval (CI) ranging from .075 to .318 (p

< .05) and a bootstrapped 99.5% CI ranging from .019 to .426 (p < .005). Because both

the 95% and 99.5% CI exclude zero, it is found that the mediating effect of informal

learning in this relationship is statistically significant at p < .05. Therefore, the result

supports Hypothesis 4a. Regarding the indirect effect of LMX on extra-role performance

via informal learning, it turned out that the path from informal learning to extra-role

performance was not statistically significant (t = 1.059, p > .05). Thus, Hypothesis 4b,

predicting a mediating role of informal learning in the association between LMX and

extra-role performance, was not supported.

Hypothesis 5 suggested that informal learning would mediate the relationship

between LMX and subordinates’ innovative work behaviors. The results indicate that the

51

indirect effect of LMX on innovative work behavior via informal learning is .260 with a

bootstrapped 95% CI ranging from .164 to .383 (p < .05) and a bootstrapped 99.5% CI

ranging from .123 to .475 (p < .005), indicating that the mediating effect of informal

learning is statistically significant. Based on this result, Hypothesis 5 is supported.

52

Chapter 5

DISCUSSION AND CONCLUSION

This chapter discusses the findings of this study and its implication and

limitations. First, the study findings demonstrated in the previous chapter are interpreted

and integrated into the general body of literature on LMX and workplace learning. After

that, the theoretical contributions and practical implications are discussed. Finally,

limitations of this study and recommendations for future research are addressed.

Discussion

The results of this study reveal that LMX has a positive impact on subordinates’

informal learning. Subordinates who receive sufficient information and resources from

their leader and experience a strong sense of advocacy based on mutual trust, respect, and

obligation with the leader are expected to engage more actively in informal learning

activities compared to those who receive less support from their leaders and have low-

quality exchanges. This finding supports previous studies that an employee’s strong

feeling of being supported and encouraged for learning by management was found to be

one of the important informal learning conditions (e.g., Skule, 2004). In addition, the

result confirmed that LMX quality was a significant predictor of employees’ voluntary

workplace learning behaviors and development (Walumbwa et al., 2009). Leaders tend to

demonstrate role modeling behaviors (in terms of learning and development) to those

subordinates with whom they have mutual relationships and act as “learning champions”

53

for them. This may positively influence the subordinates to enhance informal learning

behaviors in their work (Van der Sluis, 2004). However, there is no consistent evidence

in the extant literature that LMX has a positive impact on informal learning (Cho & Kim,

2016).

The results also show that LMX positively influences subordinates’ performance,

including in-role and extra-role performance. This result is consistent with previous

research on the LMX-follower performance relationship that a high quality of LMX is

positively related to different aspects of performance (i.e., task performance and

citizenship performance) (Hui et al., 1999; Martin et al., 2016; Moss et al., 2009). That is,

a high quality of LMX, including favorable treatment the subordinate receives from the

leader, leads to not only accomplishment of employee task-related duties and

responsibility but also involvement of discretionary behaviors such as helping and

supporting other employees and actively participating in events that help to achieve

organizational goals due to strong feelings of reciprocity. In addition, in terms of

performance ratings, I also confirmed the positive relationship between LMX and

supervisory ratings of a subordinate’s job performance (Gerstner & Day, 1997).

Moreover, the study findings demonstrate the positive effect of LMX on

subordinates’ innovative work behavior. This finding extends empirical evidence of the

significant role of LMX on employee innovation including three aspects: generation of

creative ideas (initiation: Qu, Janssen, & Shi, 2017), support of innovative ideas

(promotion), and implementation of the ideas (i.e., application: Agarwal et al., 2012; Kim

& Koo, 2017). This implies that the high-quality exchange relationship between a leader

and subordinate—including showing strong trust in a subordinate’s behavior, providing

54

challenging tasks and task-related resources, and supporting and recognizing risk-taking

work behaviors—motivates a subordinate to take innovative actions in their work. As

mentioned above, a subordinate with high-quality LMX relationships is more likely to be

involved in discretionary work behaviors (i.e., innovative work behaviors) as a means of

reciprocation due to strong feelings of obligation to “pay back” the leader.

When it comes to mediating roles of informal learning in the relationships

between LMX and outcome variables examined in this study (i.e., in-role performance,

extra-role performance, and innovative work behaviors), I found that the mediating effect

of informal learning on the relationship between LMX and in-role performance was

positive and significant, whereas the mediating effect of informal learning on the

relationship between LMX and extra-role performance was not found to be statistically

significant. My review of the extant literature on leadership and informal learning found

no empirical study that investigated informal learning as a mediator in the relationship

between LMX and performance (i.e., in-role and extra-role performance), and thus it is

impossible to compare the results from this study to other studies, even though the

theoretical argument is sound and supported by relevant previous studies (De Coninck,

2011; Walumbwa et al., 2009). As predicted based on the theoretical argument and

relevant empirical studies, informal learning mediated the influence of LMX on in-role

performance. Cerasoli et al.’s (2018) recent meta-analytic study of antecedents and

consequences of informal learning supports this result, finding that supportive

supervisory behaviors encourage employees to engage in informal learning activities, and

higher engagement in informal learning activities is positively associated with higher job

55

performance. However, this study failed to find evidence of the mediating role of

informal learning in the relationship between LMX and extra-role performance.

One explanation could be that because informal learning occurs in relation to an

individual job and across one’s work processes, enhanced informal learning activities by

a high-quality LMX relationship might directly relate to a subordinate’s in-role

performance, but not affect extra-role performance. Similarly, although many informal

learning behaviors—such as interacting and sharing ideas/materials with co-workers and

attending non-mandatory professional conferences or meetings to provide useful

information—seem to be linked to extra-role performance (i.e., organizational citizenship

behavior), it was found in the previous study that an individual’s workplace experiences

and knowledge did not predict organizational citizenship behavior (Podsakoff,

MacKenzie, Paine, & Bachrach, 2000).

This prevous finding helps to explain the failure of the mediating role of informal

learning in the relationship between LMX and extra-role performance. Due to a lack of

empirical study exploring the relationships among LMX, informal learning, and extra-

role perfomance, however, it is still difficult to discuss why high informal learning

enhanced by a high-quality LMX relationship did not translate into high extra-role

performance in this study.

Lastly, a positive mediating effect of informal learning on the relationships

between LMX and innovative work behavior was found. Employees who have a high-

quality LMX relationship with a leader are more likely to be engaged in informal learning

activities, which in turn promotes their innovative work behaviors. This implies that

mutual trust based on a high-quality LMX relationship may facilitate employees and the

56

leader to exchange work-related knowledge, opinions, and suggestions, which enables

employees to generate more creative and innovative ideas (Qu et al., 2017) by motivating

them to engage in more self-directed learning and social learning activities relevant to

their work (i.e., informal learning) (Ezuijen, Dam, Berg, & Thierry, 2010).

Theoretical Implications

This study makes several important theoretical contributions to the LMX

literature and highlights opportunities and needs for future research. First, the result of

the current study indicates that LMX is a proximal predictor of informal learning, in-role

and extra-role performance, and innovative work behavior of employees. Prior research

work already showed that LMX has positive impacts on various organizational outcomes,

including job satisfaction, organizational commitment, performance, and organizational

citizenship behavior (e.g., Gerstner & Day, 1997; Harris et al., 2011; Martin et al., 2016;

Moss et al., 2009). However, the results of this study are important since few studies have

examined LMX as antecedents of employees’ informal learning and innovative work

behaviors (e.g., Agarwal et al., 2012; Cho & Kim, 2016; Kim & Koo, 2017). Specifically,

even though researchers have suggested that supportive leaders’ behaviors (e.g., offering

special consideration to the developmental needs of an employee and exchanging work-

related knowledge, skills, and opinions with an employee) are crucial for motivating

employees to voluntarily engage in learning activities at work, there is a lack of

convincing evidence supporting the positive role of LMX in terms of employee informal

learning. Thus, the results contribute to the empirical foundation of the notion that LMX

can facilitate employees to engage in various informal learning activities (i.e., learning

with others, self-experimentation, and external scanning). In light of the importance of

57

employees’ innovation-oriented endeavors and engagement in learning in the prevailing

competitive environment, the results of the current study provide meaningful empirical

proof about the effects of LMX on positive work attitudes for employees.

Moreover, the result also demonstrated that LMX plays an important role in

employees’ learning and performance in a Korean context. Although the development of

LMX and the effect of LMX on organizational outcomes may differ depending on

contextual environments including cultural contexts, a majority of the previous studies in

the LMX literature have focused on Western settings such as the U.S. and European

countries (e.g., Moss et al., 2009; Stewart & Barrick, 2000). Relatively little scholarly

attention has been paid to Asian contexts including Korea. A large power distance culture

prevails in Korean organizations. It is deeply rooted in the Confucian value system

similar to China and might inhibit a high-quality LMX relationship, thereby impeding

involvement of informal learning and innovative endeavors (Kim & McLean, 2014; Qu et

al., 2017). That is because mutual exchange of knowledge and opinions and reciprocal

cooperation between a leader and subordinate might be difficult under a large power

distance as a subordinate tends to perceive the leader’s feedback or opinions as directions

or commands that they should follow. However, the findings of this study generally

mirrored those presented in the previous studies conducted in Western settings (e.g.,

Moss et al., 2009; Stewart & Barrick, 2000), showing that LMX has significant and

positive relationships with informal learning, innovative behavior, and performance in a

Korean context. It is worth noting, however, that some earlier evidence of the relationship

between LMX and informal learning in a Korean setting is inconsistent with this result

58

(Cho & Kim, 2016), so more empirical investigations are still necessary for future

researchers.

Furthermore, the results highlight positive influences of LMX on performance

(i.e., in-role and extra-role performance) and innovative work behavior at an individual

level. This implies that employees who have a high-quality LMX relationship with a

leader are more likely to be higher performers and active innovators at work. This finding

supports assumption of the LMX and social exchange theory: a leader develops different

quality dyadic relationships with employees, and these LMX relationships significantly

influence employees’ work outcomes and attitudes based on the norm of the reciprocity.

Even though this study focused on the relationships between an individual level of LMX

(i.e., dyadic LMX) and an individual’s performance and innovative work behavior, it is

necessary to investigate how the different quality of LMX relationship within a work unit

(i.e., LMX differentiation) affects performance and innovative actions in a unit level.

Because LMX theory highlights differences in each LMX relationship between a

leader and subordinate, investigating the extent to which differentiated LMX within a

unit can hinder or promote performance and innovation of employees can further benefit

today’s organizations under the team- and project-based organizational structures. By

developing and testing cross-level models to examine the relationships between LMX

and performance/innovative behavior at different levels of organizations (e.g.,

individual/team/organization) (Henderson, Liden, Glibkowski, & Chaudhry, 2009), we

can broaden understanding of LMX as a predictor of organizational effectiveness in

relation to different levels of organizations.

59

The study also demonstrated one of the underlying mechanisms through which

the LMX influences employees’ job performance and innovative work behavior by

exploring the mediating roles of informal learning in these relationships. Workplace

learning has been highlighted as a catalyst that encourages organizational learning and

knowledge sharing, thereby leading to higher productivity and performance in the

organization in the extant literature (Cerasoli et al., 2018). However, limited attention has

been given to a mediating role of informal learning in the relationship between relational

leadership and organizational outcomes. Therefore, the current findings, that LMX

positively and significantly affects employee in-role performance and innovative work

behavior through informal learning, add to empirical evidence of the notion that an

individual’s workplace learning encouraged by LMX increases various organizational

outcomes.

These findings contribute to not only extending our knowledge on the mediating

roles of informal learning in relation to LMX and performance and innovation, but also

stimulating researchers to investigate mediating effects of informal learning on other

organizational outcomes including employee positive attitudes (e.g., job satisfaction,

organizational commitment, or work engagement) and counterproductive performance

(e.g., absenteeism, withdrawal behaviors, or resistance to change) (Cerasoli et al., 2018;

Martin et al., 2016). Furthermore, future research is necessary to test whether informal

learning mediates the influence of LMX on extra-role performance (or citizenship

performance), which was found to be statistically insignificant in this study. By testing

the proposed research model in other settings, including different industries and countries

60

and organizational sectors, more validation can be attained and the results of the study

can be generalized in different settings.

Furthermore, although it was found informal learning acts as a significant

mediator in the influences of LMX on in-role performance and innovative work behavior

in this study, other mechanisms could help the relationship between LMX and

performance outcomes. For instance, prior meta-analytic research has found that role

clarity, trust, motivation, organizational commitment, and job satisfaction are some of the

important mechanisms through which LMX influences performance outcomes (Martin et

al., 2016). Thus, future research should conduct a more exhaustive examination of

different mediators including informal learning, the aforementioned variables, and other

potential mediators such as engagement and psychological empowerment. Morever, some

researchers noted that impacts of LMX on performance and innovation can vary

depending on contextual conditions, and thus considering and investigating certain

conditions that would influence these relationships are necessary (Sui, Wang, Kirkman,

& Li, 2016). Some contextual factors that have been found by prior research include

leader and follower expectations, task characteristics, power distance, group diversity,

employee work status, and so forth (Cha & Borchgrevink, 2017; Dunegan, Uhl-Bien, &

Duchon, 2002; Lee & Chae, 2017; Sui et al., 2016; Qu, et al., 2017). Therefore, while

demonstrating the relationship between LMX and performance and innovation, future

researchers could take individual and organizational conditions including the

aformentioned factors into account as possible moderators in order to take a closer look at

the link between LMX and performance/innovative work behavior under certain

boundary conditions.

61

Practical Implications

The results of this study have some practical implications, especially in terms of

HRD/OD practices. First, the results suggest that the quality of LMX is positively

associated with employee’s performance-related outcomes (i.e., in-role and extra-role

performance and innovative work behavior). Thus, when determining how to influence

employee performance and innovative endeavors, leaders should consider the nature of

the relationships they build with their subordinates and ways to develop mutual trust and

respect, which are the foundation of the high quality of LMX. By doing so, reciprocal

relationships beyond the formal employment contract can be engendered between the

leaders and subordinates, which in turn augments subordinate performance. In line with

this, HRD and OD practitioners can consider multiple ways of intervening including one-

on-one coaching sessions and formal leadership programs to support leaders developing

the following leadership skills: caring about subordinates’ personal needs and concerns,

mutually exchanging work-related opinions and suggestions, and supporting and

recognizing subordinates’ risk-taking behaviors in their work. Furthermore, it is

important to improve interpersonal skills (e.g., strong communication skills) for

employees to develop and maintain a high quality of LMX relationships with their

supervisor. Particularly, HRD and OD practitioners’ roles would be especially critical in

an organization having a high power distance (e.g., a Korean organization), facilitating

employees to open their minds toward their supervisor and reduce a fear of having open

discussions with their supervisor. On the other hand, HRD and OD practitioners also can

encourage supervisors to understand the undesirable effects of excessive use of their

62

power and authority on the relationships with their subordinates and exhibit more

participative and supportive leadership styles rather than directive styles.

Furthermore, the results show that the quality of LMX relationships is a

mechanism that performs indirectly, through employee informal learning, to affect

employee innovative behaviors and performance. Because informal learning enhanced by

LMX seems to be predictive of employees’ innovative work attitudes and task-related

performance, HRD and OD practitioners should try to create favorable environments for

employees actively involved in informal learning activities. It is worth pointing out that,

in traditional organizations, HRD and OD practitioners have been relatively more focused

on the provision of formal learning and less on the application of informal learning when

learning and development are required for employees in the workplace. However, formal

learning programs cannot meet various learning needs of employees who are in different

job areas, groups, and positions because of an organization’s limited resources. Thus,

informal learning can instead be applied to many employees who need and want to

improve work-related knowledge, skills, and expertise. These days, work-related

knowledge, skills, and expertise required to achieve superior performance vary and

advance quickly under complex and rapidly changing work environments. Therefore,

formalizing the benchmarks and offering timely and effective learning programs to

employees might be challenging for HRD and OD practitioners. Rather, it would be

effective when HRD and OD practitioners encourage individuals to voluntarily seek out

novel and valuable information by themselves and to share those items with their

coworkers via informal learning activities.

63

Regarding specific roles of HRD and OD to increase informal learning activities,

prior research pointed out that formal and informal organizational support is an important

predictor for employees’ participation in informal learning activities (Cerasoli et al.,

2018). Therefore, HRD and OD practitioners as organizational representatives should

take action to support and encourage informal learning, such as communicating the value

and opportunities of informal learning, identifying needs of informal learning, and

removing obstacles to informal learning (e.g., lack of time and workload). Moreover,

HRD and OD practitioners can help employees become successful informal learners. For

instance, offering them specific tactics and strategies for effective informal learning can

help them proactively engage in informal learning activities. Additionally, since effective

ways of informal learning differ by individual and work characteristics, sharing different

kinds of best practices in various situations and giving detailed and practical advice for

employees who face challenges in informal learning engagement could be effective. By

teaching and supporting a leader to facilitate employees to participate in informal

learning activities and care about employees’ developmental needs and concerns,

employees’ informal learning can also increase.

In addition to an effective application of informal learning within an organization,

it would be crucial for an organization to link informal learning activities to employee

performance improvement and increase in innovative work actions. For instance, in terms

of performance appraisal, leaders need to recognize employees’ risk-taking actions,

experiments, or mistakes as learning opportunities and give insightful and constructive

performance feedback on those kinds of learning behaviors. Employees’ efforts to share

knowledge and information with their coworkers and change current work systems and

64

methods should be also promoted by positive performance appraisal. Furthermore, when

this performance appraisal process is systematically embedded within an organizational

HR system, positive impacts of informal workplace learning on performance and

innovation would be stable (Bednall, Sanders, & Runhaar, 2014).

Limitations and Suggestions for Future Research

This study suggested important theoretical and practical implications for the LMX

and informal learning literature by empirically demonstrating the relationships with LMX

and employee performance-related aspects (i.e., in-role performance, extra-role

performance, and innovative work behavior) and the mediating effects of informal

learning among these relationships. Notwithstanding the encouraging results of this

study, there are limitations that should be noted.

First, as I used a cross-sectional research design, I cannot infer the causality

among the research variables of this study. In other words, the results might be vulnerable

to opposite or bi-directional relationships due to the possibility that superior performers

might have more opportunities to build a high quality LMX relationship with their leader,

and LMX relationships could be developed for a subordinate by actively engaging in

informal learning activities or innovative work behaviors. To mitigate the possibility of

the reversed causal linking, hypotheses suggested in this study were established based on

sound theoretical reasoning from the extant literature, including LMX theory, social

exchange theory, and convincing evidence of those theories (Blau,1964; Graen & Uhl-

Bien,1995). Nevertheless, caution should be taken in the interpretation of the results. In

addition, future researchers are needed to consider a longitudinal approach (measuring

65

the research variables at several different time points) to clearly establish the causal order

among the research variables.

Second, I used different sources (supervisors and subordinates) in the data

collection to alleviate common method biases; however, common method biases cannot

completely be ruled out since the survey questionnaires included more than one measure

and were answered by supervisors and subordinates during the same period. Moreover,

since I used subjective employee performance data (measured by supervisors), the results

of this study might not be replicated when objective performance measure (e.g., sales and

productivity) are employed. Yet, Martin et al.’s (2016) meta-analytic study found that the

effects of LMX on performance tend to be lower when measures of LMX and

performance were obtained from a different source and uses of either objective or

subjective performance measures did not matter in relation to the results. Therefore,

collecting data from both a supervisor and a subordinate in this study, especially using a

dyadic approach to measure LMX relationship, should have reduced common method

bias. Moreover, because of Harman’s single-factor test and CFA of the single-factor

model (Podsakoff et al., 2003), it was found that common method bias was not

problematic in this study.

Third, this study was conducted among employees of Korean major corporations,

so it might be difficult to generalize the results to different contexts. For example, the

participants’ demographic information in Table 3-1 indicated that participants of this

study were highly educated workers, showing that 88% of subordinates and more than

95% of leaders graduated from 4-year college or higher. Regarding participant gender,

males greatly outnumbered females in both subordinate and leader groups. Since these

66

demographic characteristics might represent contexts of Korean major organizations,

generalizing results to different contexts should be done carefully. Moreover, because the

constructs of informal learning and innovative work behaviors in this study are context

specific, future research should be conducted across cultures, geographies, industries, and

jobs.

Conclusion

I attempted to extend existing knowledge on the relationship between LMX and

organizational effectiveness by exploring influences of LMX on various aspects of

outcomes in a South Korean context, including informal workplace learning, in-role and

extra-role performance, and innovative work behavior. Moreover, I broadened the focus

of previous investigations by examining one of the potential underlying mechanisms

through which the leader-follower relationship influences employees’ performance and

innovation. The results of this study point to the importance of employees’ informal

learning engagement as the linkage between a high quality LMX and superior

performance and innovation. In contrast to the previous finding of a Korean study (Cho

& Kim, 2016), this study revealed a positive impact of LMX on informal learning

activity, leading to enhancement of in-role performance and innovative work behavior.

This study will encourage further examinations of the impacts of informal learning under

a high quality LMX relationship as well as optimal contextual conditions (e.g.,

organizational cultures, work characteristics) which influence these positive relationships.

67

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Wang, H. J., Lu, C. Q., & Siu, O. L. (2015). Job insecurity and job performance: The

moderating role of organizational justice and the mediating role of work engagement.

Journal of Applied Psychology, 100(4), 1249-1258. doi:10.1037/a0038330

West, M. A., & Farr, J. L. (1990). Innovation at work. In M.A. West, & J.L. Farr (Eds.),

Innovation and creativity at work: Psychological and organizational strategies (pp.

3-13). Chichester: Wiley.

Yuan, F., & Woodman, R. W. (2010). Innovative behavior in the workplace: The role of

performance and image outcome expectations. Academy of Management Journal,

53(2), 323-342. doi:10.5465/amj.2010.49388995

75

Appendix A

IRB Approval Letters

76

77

Appendix B:

Questionnaires for Survey (English Version)

78

Leader-Member Exchange Survey (for Leaders)

Thank you for participating in the study. This study seeks to investigate the effects of

leader-member exchange on the employee performance and innovative behavior and

examine the mediator role of informal learning in their relationships in Korean

organizations.

It will take 5 to 10 minutes to respond to the survey. Please respond to all questions, so

that your complete answers can be used in the final analysis of the study.

I would like to clarify that your answers to this survey will be used only for the purpose

of scientific research and no one else except for the researchers will be able to see the

responses. All of your responses in the survey will be kept fully confidential and

anonymous.

If you have any concerns or questions about this research, you can email the investigator,

Ji Won Park. Her email address is jup268@psu.edu.

Thank you.

Investigator: Ji Won Park, Ph.D. Candidate,

Workforce Education & Development Program

The Pennsylvania State University

310 Keller Building, University Park, PA 16802, USA

Email: jup268@psu.edu

79

Section 1. Leader-Member Exchange

This questionnaire contains items that ask you to describe your relationship with one of

your subordinate using following email address: ________________. Please indicate

your level of agreement with each question.

Strongly

disagree Disagree Neutral Agree

Strongly

agree

1. I usually let my subordinate

know where he or she

stands with me.

1 2 3 4 5

2. I think that I understand my

subordinate's problems and

needs.

1 2 3 4 5

3. I think that I recognize my

subordinate's potential. 1 2 3 4 5

4. Regardless of how much

power I have built into my

position, I would be

personally inclined to use

my power to help my

subordinate solve problems

in his or her work.

1 2 3 4 5

5. I would be willing to "bail

out" my subordinate, even

at my own expense, if he or

she really needed it.

1 2 3 4 5

6. I have enough confidence in

my subordinate that I would

defend and justify his or her

decisions if he or she were

not present to do so.

1 2 3 4 5

7. I have an effective working

relationship with my

subordinate.

1 2 3 4 5

80

Section 2. Follower’s In-Role Performance

This questionnaire contains items that ask you to evaluate in-role job performance of one

of your subordinate using following email address, __________. Please indicate your

level of agreement with each statement.

Strongly

disagree Disagree

Slightly

Disagree Neutral

Slightly

Agree Agree

Strongly

agree

1. My subordinate achieves

the objectives of the job. 1 2 3 4 5 6 7

2. My subordinate fulfills

all the requirements for

their job.

1 2 3 4 5 6 7

3. My subordinate well in

the overall job by

carrying out tasks as

expected.

1 2 3 4 5 6 7

Section 3. Follower’s Extra-Role Performance

This questionnaire contains items that ask you to evaluate extra-role job performance of

one of your subordinate using following email address, __________. Please indicate your

level of agreement with each statement.

Strongly

disagree Disagree

Slightly

Disagree Neutral

Slightly

Agree Agree

Strongly

agree

1. My subordinate willingly

attends functions not

required by the

organization but helps in

the organization.

1 2 3 4 5 6 7

2. My subordinate takes

initiative to orient new

employees to the

department even though

not part of their job

description.

1 2 3 4 5 6 7

81

3. My subordinate helps

other employees with

their work when they

have been absent.

1 2 3 4 5 6 7

Section 4. Follower’s Innovative Work Behavior

This questionnaire contains items that ask you to evaluate extra-role job performance of

one of your subordinate using following email address, __________. Please indicate your

level of agreement with each statement.

Strongly

disagree Disagree

Slightly

Disagree Neutral

Slightly

Agree Agree

Strongly

agree

1. My subordinate is

creating new ideas for

difficult issues.

1 2 3 4 5 6 7

2. My subordinate is

searching out new

working method,

techniques, or

instruments.

1 2 3 4 5 6 7

3. My subordinate is

generating original

solutions for problems.

1 2 3 4 5 6 7

4. My subordinate is

mobilizing support for

innovative ideas.

1 2 3 4 5 6 7

5. My subordinate is

acquiring approval for

innovative ideas.

1 2 3 4 5 6 7

6. My subordinate is

making important

organizational members

enthusiastic for

innovative ideas.

1 2 3 4 5 6 7

7. My subordinate is

transforming innovative

ideas into useful

applications.

1 2 3 4 5 6 7

82

8. My subordinate is

introducing innovative

ideas into the work

environment in a

systemic way.

1 2 3 4 5 6 7

9. My subordinate is

evaluating the utility of

innovative work

behaviors in the

workplace.

1 2 3 4 5 6 7

Section 5. Demographic Information

Please provide the following demographic information. It will only be used to make

statistical comparisons between different groups of respondents; it will not be used to

profile individual respondents.

Gender ① Male ( ) ② Female ( )

Age

(Years)

① ~ 29 years( )

② 30~39 years ( )

③ 40~49 years ( )

④ 50 years ~ ( )

Highest

Education

Level

① High School degree ( )

② 2-year college ( )

③ 4-year college ( )

④ Graduate school ( )

Field of

Operation

① Manufacturing ( )

② IT/Communications ( )

③ Energy/Chemical ( )

④ Construction ( )

⑤ Finance ( )

⑥ Distribution ( )

⑦ Service ( )

⑧ Other ( ):_______________________

Current

Work

Position

① Staff ( )

② Assistant manager ( )

③ Manager ( )

④ General manager ( )

⑤ Director or higher ( )

83

Job Area

① R&D ( )

② IT & Internet ( )

③ Marketing / Sales ( )

④ Manufacturing ( )

⑤ Management Support ( )

⑥ Other ( ):__________________________

Current

Company

Experience

by Years

① Less than 1 year ( )

② 1~5 years ( )

③ 6~10 years ( )

④ 11~15 years ( )

⑤ 16~20 years ( )

⑥ More than 20 years ( )

Thank you so much for your participation in this study!

84

Leader-Member Exchange Survey (for Followers)

Thank you for participating in the study. This study seeks to investigate the effects of

leader-member exchange on the employee performance and innovative behavior and

examine the mediator role of informal learning in their relationships in Korean

organizations.

It will take 5 to 10 minutes to respond to the survey. Please respond to all questions, so

that your complete answers can be used in the final analysis of the study.

I would like to clarify that your answers to this survey will be used only for the purpose

of scientific research and no one else except for the researchers will be able to see the

responses. All of your responses in the survey will be kept fully confidential and

anonymous.

If you have any concerns or questions about this research, you can email the

investigator, Ji Won Park. Her email address is jup268@psu.edu.

Thank you.

Investigator: Ji Won Park, Ph.D. Candidate,

Workforce Education & Development Program

The Pennsylvania State University

310 Keller Building, University Park, PA 16802, USA

Email: jup268@psu.edu

85

Section 1. Leader-Member Exchange

This questionnaire contains items that ask you to describe your relationship with your

leader using following email address: __________. Please indicate your level of

agreement with each question.

Strongly

disagree Disagree Neutral Agree

Strongly

agree

1. I usually know where I stand

with my supervisor. 1 2 3 4 5

2. My supervisor understands

my problems and needs. 1 2 3 4 5

3. My supervisor recognizes my

potential. 1 2 3 4 5

4. Regardless of how much

power he/she has built into

his/her position, my

supervisor would be

personally inclined to use

his/her power to help me

solve problems in my work.

1 2 3 4 5

5. I can count on my supervisor

to “bail me out” even at

his/her own expense, when I

really need it.

1 2 3 4 5

6. My supervisor has enough

confidence in me that he/she

would defend and justify my

decisions if I were not

present to do so.

1 2 3 4 5

7. I have an effective working

relationship with my

supervisor.

1 2 3 4 5

Section 2. Informal Learning

The following statements in this section are about your informal learning activities in

your work. Please indicate your level of agreement with each statement.

86

In the past year, the frequency in which I engaged in these learning activities was:

Very

infrequently

Somewhat

infrequently Neutral

Somewhat

frequently

Very

frequently

1. Informal one-on-one

discussion with supervisor

about some work situation.

1 2 3 4 5

2. Idea exchange on how to

solve a problem situation

with peers during a break or

lunch period

1 2 3 4 5

3. Observation of how other

employees dealt with a

challenging work situation.

1 2 3 4 5

4. Collaboration with others

who shared the need to solve

a particular problem.

1 2 3 4 5

5. Spending time to reflect back

how I dealt with a

challenging work situation.

1 2 3 4 5

6. Trying to solve a challenging

work situation through trial

and error process by myself.

1 2 3 4 5

7. Spending time to reflect on

what I had learned in a

classroom training program

to apply that information to a

challenging work situation.

1 2 3 4 5

8. Reading a standard

operations manual or other

similar texts on my own to

find an answer to a question.

1 2 3 4 5

9. Searching the Internet for

information to help solve a

challenging work situation. 1 2 3 4 5

10. Attendance at a non-

mandatory professional

conference or seminar that

1 2 3 4 5

87

might provide useful

information.

11. Reading professional

magazines or vender

publications to be current in

some topic.

1 2 3 4 5

12. Having contact with

someone outside the

company who is able to help

solve a challenging work

situation.

1 2 3 4 5

Section 3. Demographic Information

Please provide the following demographic information. It will only be used to make

statistical comparisons between different groups of respondents; it will not be used to

profile individual respondents.

Gender ② Male ( ) ② Female ( )

Age

(Years)

① ~ 29 years( )

② 30~39 years ( )

③ 40~49 years ( )

④ 50 years ~ ( )

Highest

Education

Level

① High School degree ( )

② 2-year college ( )

③ 4-year college ( )

④ Graduate school ( )

Field of

Operation

① Manufacturing ( )

② IT/Communications ( )

③ Energy/Chemical ( )

④ Construction ( )

⑤ Finance ( )

⑥ Distribution ( )

⑦ Service ( )

⑧ Other ( ):_______________________

88

Current

Work

Position

① Staff ( )

② Assistant manager ( )

③ Manager ( )

④ General manager ( )

⑤ Director or higher ( )

Job Area

① R&D ( )

② IT & Internet ( )

③ Marketing / Sales ( )

④ Manufacturing ( )

⑤ Management Support ( )

⑥ Other ( ):__________________________

Current

Company

Experience

by Years

① Less than 1 year ( )

② 1~5 years ( )

③ 6~10 years ( )

④ 11~15 years ( )

⑤ 16~20 years ( )

⑥ More than 20 years ( )

Thank you so much for your participation in this study!

89

Appendix C

Questionnaires for Survey (Korean Version)

90

리더와 구성원 간의 교환 관계 연구 (리더용)

안녕하십니까?

바쁘신 와중에도 본 설문에 응해주셔서 진심으로 감사드립니다. 본 연구는 리더와

구성원 간의 교환 관계(Leader-Member Exchange)가 구성원의 업무 성과에 어떤

영향을 미치는지 연구하고자 합니다.

설문지는 총 5 개 섹션으로 구성되어 있으며, 설문 응답에는 약 5-10 분 내외로

소요될 것입니다. 본 연구에 귀하의 소중한 의견이 반영될 수 있도록 가능하면 모든

질문에 응답해 주시기 바랍니다.

귀하의 연구 참여에 관한 모든 사항은 비밀로 유지되며 귀하가 제공하는 개인 정보

및 응답 내용은 학술연구를 위한 통계자료로 연구 목적으로만 사용되고, 익명으로

관리될 것입니다. 귀하의 설문 응답은 자발적 참여로, 귀하는 언제든지 연구 참여를

중단할 수 있습니다.

연구와 관련하여 문의사항이나 의견이 있으시다면, 연구자 박지원에게

이메일(jup268@psu.edu)로 연락해 주시기 바랍니다.

다시 한 번 본 연구에 참여해 주셔서 감사합니다.

연구자 박지원 (박사과정)

미국 펜실베니아 주립대학교, 인적자원개발 전공

주소: 310 Keller Building, University Park, PA 16802, USA

이메일: jup268@psu.edu

91

본 연구에서는 회사 이메일 주소를 고유번호로 활용하고자 합니다. 고유번호는 절대 연구 이외의

다른 목적으로 사용되지 않을 것이며, 설문 응답 수집이 완료 된 직후 임의의 ID 로 전환되어

분석에 활용될 것입니다. 다시 한 번 비밀이 보장됨을 약속 드리며, 귀하와 해당 부하직원의 회사

이메일 주소를 기재해 주시길 바랍니다.

귀하의 이메일 주소: _______________________________________

부하직원의 이메일 주소: _____________________________________

I. 다음은 귀하의 조직생활에서 해당 부하직원과의 관계에 대하여 묻는 문항입니다. 각 문항에

대한 귀하의 동의 수준을 체크하여 주시기 바랍니다.

설문문항

전혀

그렇지

않다

그렇지

않다

보통

이다 그렇다

매우

그렇다

1. 해당 직원이 하고 있는 일들에 대해

내가 어느 정도 만족하고 있는지

그/그녀에게 대체로 알게 한다.

1 2 3 4 5

2. 해당 직원이 겪는 어려움과 요구를

알고 있다. 1 2 3 4 5

3. 해당 직원의 잠재력을 인정해준다. 1 2 3 4 5

4. 해당 직원이 업무 수행 중 문제가

발생하면, 나의 직위에 부여된 공식적

권한과 상관없이, 그/그녀가 문제를

해결할 수 있도록 많은 도움을 줄

것이다.

1 2 3 4 5

5. 해당 직원이 어려움에 처했을 때

기꺼이 희생을 감수하고서라도 해당

직원을 도와줄 것이다.

1 2 3 4 5

6. 해당 직원을 충분히 신뢰하고 있기

때문에 그/그녀가 없는 상황에서도 1 2 3 4 5

92

그/그녀가 내린 결정을 변론하거나

지지할 것이다.

7. 해당 직원과 나의 업무상 관계는 매우

효과적이다. 1 2 3 4 5

II. 다음은 해당 부하직원의 직무 성과에 대한 질문입니다. 각 문항에 대한 귀하의 동의 수준을

체크하여 주시기 바랍니다.

설문문항

전혀

그렇지

않다

그렇지

않다

약간

그렇지

않다

보통

이다

약간

그렇다 그렇다

매우

그렇다

1. 해당 직원은 직무 목표를

달성한다. 1 2 3 4 5 6 7

2. 해당 직원은 직무 수행에 필요한

모든 요건을 충족한다. 1 2 3 4 5 6 7

3. 해당 직원은 조직이 기대하는 대로

업무를 처리함으로써 전반적으로

업무를 잘 수행한다.

1 2 3 4 5 6 7

III. 다음은 해당 부하직원의 직무 이외 성과에 대한 질문입니다. 각 문항에 대한 귀하의 동의

수준을 체크하여 주시기 바랍니다.

설문문항

전혀

그렇지

않다

그렇지

않다

약간

그렇지

않다

보통

이다

약간

그렇다 그렇다

매우

그렇다

1. 해당 직원은 조직에 도움이 되는

행사에 자발적으로 참여한다. 1 2 3 4 5 6 7

2. 해당 직원은 본인의 업무가

아니더라도 새 동료가 왔을 때

조직에 적응하도록 도와준다.

1 2 3 4 5 6 7

3. 해당 직원은 동료직원이 결근한

경우, 그 사람의 일을 기꺼이

도와준다.

1 2 3 4 5 6 7

93

IV. 다음은 해당 부하직원의 혁신 행동에 대한 질문입니다. 각 문항에 대한 귀하의 동의 수준을

체크하여 주시기 바랍니다.

설문문항

전혀

그렇지

않다

그렇지

않다

약간

그렇지

않다

보통

이다

약간

그렇다 그렇다

매우

그렇다

1. 해당 직원은 업무와 관련된 어려운

문제를 해결하기 위해 새로운

아이디어를 개발한다.

1 2 3 4 5 6 7

2. 해당 직원은 업무 수행에 활용될

수 있는 새로운 기술, 도구, 방법

등을 찾으려고 노력한다.

1 2 3 4 5 6 7

3. 해당 직원은 업무와 관련해

독창적인 방법을 고안해낸다. 1 2 3 4 5 6 7

4. 해당 직원은 혁신적인 아이디어에

대한 지원을 얻어 내려고 노력한다. 1 2 3 4 5 6 7

5. 해당 직원은 혁신적인 아이디어에

대한 찬성이나 승인을 얻기 위해

노력한다.

1 2 3 4 5 6 7

6. 해당 직원은 직장의 핵심 인물들을

혁신적 아이디어에 대한 열렬한

후원자로 만든다.

1 2 3 4 5 6 7

7. 해당 직원은 혁신적 아이디어를 잘

다듬어 유용하게 쓰일 수 있도록

만든다.

1 2 3 4 5 6 7

8. 해당 직원은 체계적인 방법으로

혁신적 아이디어를 업무에

도입한다.

1 2 3 4 5 6 7

9. 해당 직원은 혁신적 아이디어의

실용적 가치를 꼼꼼하게 따진다. 1 2 3 4 5 6 7

V. 다음은 분석을 위해 필요한 연구 참여자의 인적 사항에 대한 질문입니다. 해당되는 사항에

표시해주시기 바랍니다.

94

1. 성별 ① 남자( ) ② 여자( )

2. 연령 ① 20대( ) ② 30대( ) ③ 40대( ) ④ 50대 이상( )

3. 최종학력 ① 고등학교 졸업( )

② 2년제 대학(전문대) 졸업( )

③ 4년제 대학 졸업( )

④ 대학원 졸업( )

4. 산업 ① 제조업( )

② IT/기술산업( )

③ 에너지/화학업( )

④ 건설업( )

⑤ 금융/보험업( )

⑥ 유통업( )

⑦ 서비스업( )

⑧ 기타( ):_______________________

5. 직급 ① 사원급( )

② 대리급( )

③ 과장급( )

④ 부장/차장급( )

⑤ 임원급( )

6. 현재 직무 ① 연구/개발( )

② 정보기술(IT)/인터넷( )

③ 마케팅/판매/영업( )

④ 생산/제조( )

⑤ 경영지원(기획/재무/회계/인사/교육/총무/법무/감사) ( )

⑥ 기타( ):__________________________

7. 현회사

근속기간

① 1년 미만( )

② 1-5년( )

③ 6-10년( )

④ 11-15년( )

⑤ 16-20년( )

⑥ 21년 이상( )

설문에 참여해 주셔서 진심으로 감사드립니다.

95

리더와 구성원 간의 교환관계 연구 (구성원용)

안녕하십니까?

바쁘신 와중에도 본 설문에 응해주셔서 진심으로 감사드립니다. 본 연구는 리더와

구성원 간의 교환관계(Leader-Member Exchange)가 구성원의 업무 성과에 어떤

영향을 미치는지 연구하고자 합니다.

설문지는 총 3 개 섹션으로 구성되어 있으며, 설문 응답에는 약 5-10 분 내외로

소요될 것입니다. 본 연구에 귀하의 소중한 의견이 반영될 수 있도록 가능하면 모든

질문에 응답해 주시기 바랍니다.

귀하의 연구 참여에 관한 모든 사항은 비밀로 유지되며 귀하가 제공하는 개인 정보

및 응답 내용은 학술연구를 위한 통계자료로 연구 목적으로만 사용되고, 익명으로

관리될 것입니다. 귀하의 설문 응답은 자발적 참여로, 귀하는 언제든지 연구 참여를

중단할 수 있습니다.

연구와 관련하여 문의사항이나 의견이 있으시다면, 연구자 박지원에게

이메일(jup268@psu.edu)로 연락해 주시기 바랍니다.

다시 한 번 본 연구에 참여해 주셔서 감사합니다.

연구자 박지원 (박사과정)

미국 펜실베니아 주립대학교, 인적자원개발 전공

주소: 310 Keller Building, University Park, PA 16802, USA

이메일: jup268@psu.edu

96

본 연구에서는 회사 이메일 주소를 고유번호로 활용하고자 합니다. 귀하의 고유번호는 절대 연구

이외의 다른 목적으로 사용되지 않을 것이며, 설문 응답 수집이 완료 된 직후 이메일 정보는

임의의 ID 로 전환되어 분석에 활용될 것입니다. 다시 한 번 비밀이 보장됨을 약속드리며, 귀하와

해당 상사분의 회사 이메일 주소를 기재해 주시길 바랍니다.

귀하의 이메일 주소: _______________________________________

상사의 이메일 주소: _____________________________________

I. 다음은 귀하의 조직생활에서 상사와의 관계에 대하여 묻는 문항입니다. 각 문항에 대한 귀하의

동의 수준을 체크하여 주시기 바랍니다.

설문문항

전혀

그렇지

않다

그렇지

않다

보통

이다 그렇다

매우

그렇다

1. 내가 하고 있는 일들에 대해 나의

상사가 어느 정도 만족하고 있는지

나는 대체로 알고 있다.

1 2 3 4 5

2. 나의 상사는 내가 겪는 어려움과

요구를 알고 있다. 1 2 3 4 5

3. 나의 상사는 나의 잠재력을

인정해준다. 1 2 3 4 5

4. 내가 업무수행 중 문제가 발생하면,

나의 상사는 자신의 직위에 부여된

공식적 권한과 상관없이 문제 해결에

많은 도움을 줄 것이다.

1 2 3 4 5

5. 내가 어려움에 처했을 때, 나의

상사는 자신의 희생을

감수하고서라도 기꺼이 나를 도와줄

것이다.

1 2 3 4 5

6. 나의 상사는 나를 충분히 신뢰하고

있기 때문에 내가 없는 상황에서도 1 2 3 4 5

97

내가 내린 결정을 변론하거나 지지할

것이다.

7. 상사와 나의 업무상 관계는 매우

효과적이다. 1 2 3 4 5

II. 다음은 귀하의 비공식 (회사에서 제공하는 공식적인 교육훈련 프로그램 이외의 학습 할동)에

대한 질문입니다. 각 문항에 대한 귀하의 동의 수준을 체크하여 주시기 바랍니다.

설문문항

지난 1 년동안 나는 _____________

전혀

안함

드물게

함 종종함 자주함

매우

자주함

1. 특정 업무 상황과 관련하여 상사와

비공식적인 토론을 하였다. 1 2 3 4 5

2. 휴식 시간 또는 일과 후에 동료들과

업무 상의 문제를 해결하기 위해

의견을 교환하였다.

1 2 3 4 5

3. 어려운 업무 상황에 대해 다른

사람들이 어떻게 처리하는 지를

관찰하였다.

1 2 3 4 5

4. 업무상의 문제를 해결하기 위해

다른 사람들과 협업하였다. 1 2 3 4 5

5. 새로운 상황에 처했을 때, 과거의

어려운 업무 상황을 처리했던 나의

경험을 되돌아보았다.

1 2 3 4 5

6. 스스로 시행착오를 통해 어려운

업무 상황을 해결하려 노력하였다. 1 2 3 4 5

7. 어려운 업무 상황을 해결하기 위해

공식 교육훈련 프로그램 (집합교육

등)에서 배운 것을 되돌아 보았다.

1 2 3 4 5

8. 어려운 업무 상황에 대한 해답을

찾기 위해 스스로 업무 매뉴얼 (또는

사내 작업 지침서) 등을 참조하였다.

1 2 3 4 5

98

9. 어려운 업무 상황에 대한 해답을

찾기 위해 인터넷을 통해 정보를

얻었다.

1 2 3 4 5

10. 유용한 정보를 얻기 위해

자발적으로 컨퍼런스 또는 세미나에

참석하였다.

1 2 3 4 5

11. 업무 정보 및 지식 습득을 위해

관련 서적 또는 전문 잡지를 읽었다. 1 2 3 4 5

12. 어려운 업무 상황 해결을 위한

정보 및 지식을 얻기 위해 외부의

관련 전문가들에게 연락하였다.

1 2 3 4 5

III. 다음은 분석을 위해 필요한 연구 참여자의 인적 정보에 대한 문항입니다. 해당되는 사항에

표시해주시기 바랍니다.

1. 성별 ① 남자( ) ② 여자( )

2. 연령 ① 20대( ) ② 30대( ) ③ 40대( ) ④ 50대 이상( )

3. 최종학력 ① 고등학교 졸업( )

② 2년제 대학(전문대) 졸업( )

③ 4년제 대학 졸업( )

④ 대학원 졸업( )

4. 산업 ① 제조업( )

② IT/기술산업( )

③ 에너지/화학업( )

④ 건설업( )

⑤ 금융/보험업( )

⑥ 유통업( )

⑦ 서비스업( )

⑧ 기타( ):_______________________

5. 직급 ① 사원급( )

② 대리급( )

③ 과장급( )

④ 부장/차장급( )

⑤ 임원급( )

6. 현재 직무 ① 연구/개발( )

99

② 정보기술(IT)/인터넷( )

③ 마케팅/판매/영업( )

④ 생산/제조( )

⑤ 경영지원(기획/재무/회계/인사/교육/총무/법무/감사) ( )

⑥ 기타( ):__________________________

7. 현회사

근속기간

① 1년 미만( )

② 1-5년( )

③ 6-10년( )

④ 11-15년( )

⑤ 16-20년( )

⑥ 21년 이상( )

설문에 참여해 주셔서 진심으로 감사드립니다.

VITA

Ji Won Park

Education

Ph.D. Candidate, The Pennsylvania State University, University Park (8/2013 – Present)

Workforce Education & Development, Human Resource Development /

Organization Development Emphasis

MS, Korea University, Seoul, South Korea (3/2009 – 8/2011)

Corporate Education

BA, Yonsei University, Seoul, South Korea (3/2001 – 2/2006)

Business Administration and History (double major)

Research

Park, S., Kim, J., Park, J., & Lim, D. H. (2018). Work engagement in nonprofit organizations: A

conceptual model. Human Resource Development Review, 17(1), 5-33.

Kim, W., & Park, J. (2017) Examining structural relationships among work engagement,

organizational procedural justice, knowledge sharing, and innovative work behavior for

sustainable organizations. Sustainability, 9(2), 205-221.

Kim, W., Kim, J., Woo, H., Park, J., Jo, J., Park, S. H., & Lim, S. Y. (2017). The relationship

between work engagement and organizational commitment: Proposing research agendas

through a review of empirical literature. Human Resource Development Review, 16(4),

350-376.

Cho, Y., Park, J., Ju, B., Han, S., Moon, H, Park, S., Joo, A., & Park, E. (2016). Women leaders’

work‐life imbalance in South Korean companies: A collaborative qualitative study.

Human Resource Development Quarterly, 27(4), 461-487.

Work Experience

The Pennsylvania State University, Workforce Education and Development Program.

University Park, PA (8/2014 – 5/2017). Graduate Assistant: Teaching Assistant

(Supervisor: Dr. Judith Kolb, Dr. Wesley Donahue)

Hanwha Human Resource Development Center, Seoul, South Korea (1/2006 – 6/2012). Human

Resource Development Assistant Manager