social attributes of jobs: integrating social …potential contributors to the job characteristics...
TRANSCRIPT
SOCIAL ATTRIBUTES OF JOBS:
INTEGRATING SOCIAL SUPPORT AND MENTORING INTO THE JOB
CHARACTERISTICS MODEL
A Thesis
Presented to the faculty of the Department of Psychology
California State University, Sacramento
Submitted in partial satisfaction of the requirements for the degree of
MASTER OF ARTS
in
Psychology
(Industrial/ Organizational Psychology)
by
Ague Mae S. Manongsong
SPRING 2015
© 2015
Ague Mae S. Manongsong
ALL RIGHTS RESERVED
ii
SOCIAL ATTRIBUTES OF JOBS:
INTEGRATING SOCIAL SUPPORT AND MENTORING INTO THE JOB
CHARACTERISTICS MODEL
A Thesis
by
Ague Mae S. Manongsong Approved by: __________________________________, Committee Chair Rachel August, Ph.D. __________________________________, Second Reader Gregory Hurtz, Ph.D. __________________________________, Third Reader Kim Roberts, Ph.D. ____________________________ Date
iii
Student: Ague Mae S. Manongsong
I certify that this student has met the requirements for format contained in the University format
manual, and that this thesis is suitable for shelving in the Library and credit is to be awarded for
the thesis.
__________________________, Graduate Coordinator ___________________ Jianjian Qin, Ph.D. Date Department of Psychology
iv
Abstract
of
SOCIAL ATTRIBUTES OF JOBS:
INTEGRATING SOCIAL SUPPORT AND MENTORING INTO THE JOB
CHARACTERISTICS MODEL
by
Ague Mae S. Manongsong
Recently, Oldham and Hackman (2010) suggested the examination of social attributes of work as
potential contributors to the Job Characteristics Model (JCM). The current study examined the
integration of the social aspects (mentoring and social support from managers, coworkers, and
supervisors), as well as its effects on job satisfaction and turnover intentions, as potentially
mediated by experienced meaningfulness of work. The 137 university staff members (female =
99 and male = 38) completed an online survey. A series of regression analyses showed that
experienced meaningfulness was a partial mediator for the majority of cases. Thus, the social
attributes could be useful additions because they continued to influence the criteria. Experienced
meaningfulness was also a full mediator in a few cases. The researcher also conducted analyses
on select original core job dimensions, which provided addition support for the JCM’s continued
relevancy. Future research directions, alternative explanations, and limitations were discussed.
_______________________, Committee Chair Rachel August, Ph.D. _______________________ Date
v
ACKNOWLEDGEMENTS
I would like to take this opportunity to thank all the people who contributed to my
success at Sacramento State, as well as my professional career. Foremost, I want to express my
gratitude to my advisor, Dr. Rachel August, for her guidance, encouragement, and continued
support of my academic and career goals. In particular, she provided me with numerous
opportunities for professional development and her confidence in me provided the motivation I
needed to preserve when this process became difficult.
I want to also acknowledge the rest of my committee members for their contributions to
my success in the Master’s of Arts program. I am truly grateful to Dr. Gregory Hurtz; he made
advanced statistics less scary and more approachable. As a result, I felt confident that I could do it
on my own. I am also immensely thankful for Dr. Kim Robert’s willingness to jump on board.
Moreover, I have grown as an instructor from her feedback and advice. A special thanks to Dr.
Emily Wickelgren. She took a chance on me when I was an inexperienced researcher and
provided me with my first research assistantship. Additionally, she never hesitated to aid me in
my first semesters as an instructor.
Finally, I express my sincerest gratitude to my family and friends for their love and
support through this entire process. I want to thank my parents, Rufino and Eva Manongsong, for
all of the sacrifices they made to provide my sister and me better educational opportunities and a
better life. I hope I have made them proud. I also want to thank my sister, Aubrey Manongsong,
for being a role model I could follow for academic success. A special thanks to my friends, within
and outside of the program, for the encouragement and for the constant reminders that there is
always time to relax.
vi
TABLE OF CONTENTS
Page
Acknowledgements .................................................................................................................. vi
List of Tables ........................................................................................................................... ix
List of Figures ........................................................................................................................... x
Chapter
1. INTRODUCTION………………………………………………………………………. 1
2. BACKGROUND ................................................................................................................ 8
Review of the Job Characteristics Model .................................................................... 8
Review of Social Attributes of the Work Environment ............................................. 16
3. METHODS ....................................................................................................................... 34
Participants ................................................................................................................. 34
Materials .................................................................................................................... 36
Procedures .................................................................................................................. 41
4. RESULTS ......................................................................................................................... 43
Preliminary Analyses ................................................................................................. 43
Primary Analyses ....................................................................................................... 45
Secondary Analyses ................................................................................................... 56
5. DISCUSSION ................................................................................................................... 59
Appendix A: Consent Form ................................................................................................... 67
Appendix B: Demographic Information Questionnaire .......................................................... 68
Appendix C: Social Attributes of Work Inventories ............................................................... 70
vii
Appendix D: JCM Experienced Meaningfulness Inventory ................................................... 73
Appendix E: JCM Core Dimensions Questionnaire ............................................................... 74
Appendix F: Work Outcome Inventories ................................................................................ 76
References ............................................................................................................................... 77
viii
LIST OF TABLES Tables Page
1. Descriptive Statistics for all Variables……………….………………………………. 44
2. Correlation Matrix for all Variables………………….………………………………. 47
3. The Standardized Regression Coefficients for the Relationship between Task-related
JCM Variables and Job Satisfaction as Mediated by Experienced Meaningfulness…. 51
4. The Standardized Regression Coefficients for the Relationship between Task-related
JCM Variables and Turnover Intention as Mediated by Experienced
Meaningfulness………………………………………………………………………. 53
5. The Standardized Regression Coefficients for the Relationship between Social Attributes
of Work and Job Satisfaction as Mediated by Experienced Meaningfulness………... 54
6. The Standardized Regression Coefficients for the Relationship between Social Attributes
of Work and Turnover Intention as Mediated by Experienced Meaningfulness…….. 55
7. Effect Sizes of Key Variables for Job Satisfaction…………………………………... 56
8. Effect Sizes of Key Variables for Turnover Intentions...……………………………. 57
ix
LIST OF FIGURES Figures Page
1. Hackman and Oldham’s (1974) Job Characteristics Model…………………………. 9
2. Proposed additions to the Job Characteristics Model ..... …………………………….15
3. The standardized regression coefficients for the relationship between the predictor
variables (the four social attributes and the three JCM variables) and the criterion
variables (job satisfaction and turnover intention) as mediated by experienced
meaningfulness………………………………………………………………………. 50
x
1
Chapter 1
INTRODUCTION
The Industrial Revolution impacted every facet of life for 19th century workers.
Workers saw the introduction of innovative machinery that allowed unskilled laborers to
produce large quantities of goods with very little training. Accordingly, factories
multiplied across the United States and Europe to feed the demand for various goods,
such as textiles. The agrarian population, eager to become a part of the manufacturing
process, left the toil of the fields, in a mass migration into urban centers. This change
began a cycle of increased production through improved machinery manned by
increasing numbers of laborers (Leonard & Freedman, 2000).
Early industrial psychologists, rooted in the ideals of the Industrial Revolution,
began to research and establish principles to govern work and workers in the mass
production of goods. The dominant theory of management, developed by Frederick
Winslow Taylor in the early 20th century, was scientific management. Scientific
management focused on the analysis and simplification of work-related activities to
increase efficiency (the most effective methods to perform work tasks) and productivity.
They utilized time and motion studies to analyze specific work-related tasks for the
purposes of eliminating unnecessary movements to streamline the work process and,
thereby, increase productivity (King, 2013; Oldham & Hackman, 2010).
2
The assembly line, created by Ransom E. Olds in the early 1900s, revolutionized
the manufacturing process and embodied scientific management. The assembly line was
efficient because the set-up shortened the duration of manufacturing goods that allowed
for the mass production of even more consumer goods. Each worker on the assembly line
performed one or a few highly specialized repetitive tasks in a stationary position. For
instance, one worker placed spokes on the wheels of a car, while another was responsible
for the windows in the car. As a result, workers became interchangeable because any one
could be trained to perform the components of work (Humphrey, Nahrgang, &
Morgeson, 2007; King, 2013; Oldham & Hackman, 2010)
Consequently, many managers and highly placed officials viewed workers as
tools to reach managers’ goals (Leonard & Freedman, 2000). The perspective at the time
was that rewards, such as wages, motivated workers to perform better. However,
compensation based solely on rewards led to decreased work satisfaction, as well as
increased absenteeism and turnover among employees (Humphrey et al., 2007). Thus,
employees sought more out of their work than a pay check. Accordingly, researchers
developed several theories that moved away from scientific management. They
hypothesized that employees sought intrinsic rewards, such as stimulation and purpose in
their job, which resulted in the motivation to put more effort into their work (Jaramillo,
Mulki, & Boles, 2013). They formed a consensus that job redesign could increase
motivation through job enrichment, that is, providing employees with increased
responsibility, autonomy, and control over how to perform their job duties. One of the
3
most commonly used frameworks for job redesign was the Job Characteristics Model
developed by Hackman and Oldham (1974).
The model identified five core job dimensions: skill variety, task identity, task
significance, and feedback. The five core dimensions related to affective and behavioral
outcomes through three psychological states; in other words, the presence of the states
caused workers to be motivated to perform well. The first three dimensions related to
work outcomes through the psychological state of experienced meaningfulness of the
work. Increased autonomy led to the psychological state of personal responsibility for
work outcomes, while feedback provided information on the results of work (Hackman &
Oldham, 1974; Head & Sorensen, 1985; Jaramillo et al., 2013; Oldham & Hackman,
2010).
Although the JCM’s motivational approach proved a successful tool for job
designers to increase job enrichment, Oldham and Hackman (2010) recently called for
the exploration of additional facets of work to create a more inclusive picture of factors
that affect individuals’ motivation to work. Several researchers also supported the
examination of new components because of the stagnant status of current research on the
JCM (Jaramillo et al., 2013). Others commented that the belief the JCM was all inclusive,
due to the effectiveness of the model, led to the misconception that the pursuit of
additional components would not yield any useful information (Humphrey et al., 2007).
More importantly, organizations and researchers still encountered the same problems the
creation of JCM was supposed to address. These include employee dissatisfaction, low
4
work motivation, absenteeism, turnover (or turnover intentions), poor quality of work
products or services (Oldham & Hackman, 2010). Therefore, other factors, not included
in the original JCM, must be contributing, in part, to poor worker and work outcomes.
Oldham and Hackman (2010) suggested the examination of various social
attributes of the work environment. Originally, job design researchers overlooked them in
the creation of the JCM because, at the time, it was not commonly accepted that social
factors were important contributors to internal work motivation. Thus, job design
researchers, generally, did not carry out in-depth examinations of the quality and
potential impact of social relationships within the work place. Instead, many researchers
designed studies centered on traditional workplace topics, such as productivity and
efficiency. For instance, the Hawthorne Studies of the 1920s, initially, focused on the
effects of various lights’ brightness on employees’ productivity levels. However, they
ultimately became known for the influence of direct supervision on productivity (Izawa,
French, & Hedge, 2011).
Moreover, researchers, in recent years, have investigated structural changes to
many organizations that led to a change in the nature of the work environment, which
emphasized the pervasiveness and importance of social aspects of work. For instance, in
the past two decades jobs in manufacturing have decreased because all forms of industry
experienced a technological revolution. Many organizations began to move away from
manufacturing and towards information processing, such as e-commerce (businesses that
utilize the internet). Additionally, the advancement of machinery has replaced the need
5
for human labor in many manufacturing settings. Organizations also began to outsource
services (such as research and data entry), which left them to channel their and
employees’ energies into outcomes that focused on innovation in every industry.
Altogether, this created the need for highly skilled workers to utilize new
technology effectively and led to increased professional classes, globalization, and new
career industries, for instance genetic engineering, that required different sets of skills
from workers. Another consequence was the elimination of workers directly competing
with one another because of the lack of a corporate ladder to climb and the reliance of
team work to produce innovate products (Inayatullah, 2006; Landry, Mahesh, &
Hartman, 2005). As a result of these trends, the social dynamics between employees also
progressed.
Furthermore, with the work process controlled by both employees and
supervisors, the social dynamics between management and workers have changed. Jobs
have become less well-defined and less circumscribed with regard to the specific tasks
employees do. This, in turn, has given employees increased responsibilities and control
over their work. Workers generally have a more active role in the process of work
because they know more about job and the tasks that comprise work than their managers.
As a result, supervisors are able to take more active roles in employees’ work lives. In
particular, they can provide a supportive environment conducive for work and family
balance by reducing work conflict caused by technology’s blurring of the lines separating
an employee’s work and private life: the internet allows employees to expand and
6
maintain flexible working hours (outside the traditional office hours of 9 AM to 5 PM)
because they could access their work at any time or any place (Inayatullah, 2006; Landry,
et al., 2005).
Additionally, the broader organizational impact was on organizational structure.
Organizations across industries shifted away from a traditional command structure where
power was held by top officials to decentralization and less hierarchy that allowed for
more worker autonomy. An example is an organization arranged by department or
product rather than function. Similar to direct supervisors, upper management changed
from command and control to coordinate and cultivate the talents of their employees and
direct them to achieve organizational goals. This also fundamentally changed the
relationships between employee and his or her superiors (Landry et al., 2005).
Therefore, the primary focus of this study is to identify whether social attributes
of jobs can be integrated into Hackman and Oldham’s Job Characteristics Model (JCM)
and become a core motivational aspect in the JCM. Specifically, the researcher will
examine the effects of mentoring and various types of social support (managerial,
supervisors, co-workers) on the key work outcomes of work satisfaction and turnover
intentions, as potentially mediated by the JCM psychological state of experienced
meaningfulness. The current study may also provide additional support for the continued
relevancy of the model by also examining the job components of skill variety, task
identity, and task significance. As a result, the study will also provide information on the
relative contributions of the social attributes of jobs as compared to the task-related
7
aspects of jobs and evaluate the extent that it can contribute to positive work outcomes
beyond those of the core job dimensions.
8
Chapter 2
BACKGROUND
As stated in Chapter 1, the primary focus of the current study is to determine
whether the social attributes of jobs (managerial, supervisors, and co-workers support, as
well as mentoring) can be integrated into Hackman and Oldham’s Job Characteristics
Model (JCM). Moreover, the researcher aims to provide additional support for the
continued utilization of the model through the examination of the core job dimensions of
skill variety, task identity, and task significance. An overarching goal is to determine the
relative contributions of the social attributes of jobs and the task-related aspects of jobs.
The current study will, first, describe the components of the JCM and relevant research to
support its continued use.
Review of the Job Characteristics Model
Job design researchers used the JCM to understand the relationship between the
characteristics of jobs (essential tasks that comprise jobs) and important work outcomes.
The JCM helped researchers determine the best practices to motivate employees
(Debnath, Tandon, & Pointer, 2007). The JCM is comprised of core job dimensions or
characteristics (CJC), critical psychological states (CPS), and work outcomes, as well as
the moderator of growth needs strength (see Figure 1).
9
Core Job Characteristics Critical Psychological States Work Outcomes Skill Variety Task Identity Experienced Meaningfulness of Work High Internal Work Motivation Task Significance
High Quality Work Performance Autonomy Experienced Responsibility for the
Outcomes of the Work High Satisfaction with Work Feedback from the job Knowledge of Actual Results Low Absenteeism and Turnover
of Work Activities
Employee Growth Need Strength Figure 1. Hackman and Oldham’s (1974) Job Characteristics Model
10
The model identified five CJCs: skill variety measured the extent to which
employees used different skills and talent sets to accomplish various tasks pertinent to the
job; task identity measured the degree to which the job required doing an identifiable
piece of work from beginning to end with observable outcomes; task significance
measured the extent to which the job had an impact on others (in the organization or the
external environment); autonomy measured the degree to which the job allowed
employees control over the scheduling and procedures used to complete work activities;
and feedback measured the extent to which employees received information regarding
their performance (Hackman & Oldham, 1974).
The model’s five characteristics related to affective and behavioral outcomes
through three psychological states; the presence of these states motivated workers. The
first psychological state was experienced meaningfulness of the work: the extent that
employee experienced the job as important, valuable, and worthwhile. The second critical
psychological state was experienced responsibility for outcomes of the work: the extent
that the employee felt accountable for the results and outcomes of his or her work. The
final critical psychological state was knowledge of the results: the degree to which the
employee understood how well he or she performed his or her work (Hackman &
Oldham, 1974).
As depicted in Figure 1, the first three sets of CJC would enhance an employees’
experienced meaningfulness, while the other CJC would enhance experienced
responsibility for work outcomes and knowledge of the results, respectively. Thus, higher
11
levels of the five dimensions would result in higher levels of the corresponding critical
psychological states. In turn, when the employee experienced the three critical
psychological states, they also experienced higher levels of positive work outcomes
(internal work motivation, quality of work performance, work satisfaction) and lower
levels of negative outcomes (absenteeism and turnover) (Hackman & Oldham, 1974).
Additionally, Hackman and Oldham (1974) expected that the framework would
not apply to all individuals. Therefore, they included Growth Need Strength as a
moderator for the relationships outlined: those high in growth need (in particular,
employees that valued growth and wanted to feel accomplished) would respond
positively to “a job high in motivating potential” (Hackman & Oldham, 1974, p. 4), while
those that did not would respond negatively. Furthermore, Hackman and Oldham
developed the Job Diagnostic Survey to assess these factors.
There was considerable amount of interest in the JCM. Numerous researchers
conducted studies to determine the utility, reliability, and validity of the framework.
Hackman and Oldham (1974) provided early and strong support for the reliability and
validity of their model and its measurement. The authors collected data from 658
employees in various industries and organizations located in the east, south, and mid-west
(386 males and 272 females). They also gathered information from supervisors and
company records, as well as their own observation of the employees.
The results showed the internal consistency of the Job Diagnostic Survey was
high (between .56 and .88). The correlations between the different groups (i.e.
12
supervisors and employees, researcher observation and employees, and supervisors and
observers) were weak to strong for the majority of scales (r = - 0.13 to r = .89); negative
correlations involved absenteeism and turnover. More importantly, they found that the
relationships established by the framework were supported by the data. Subsequent
studies that involved different industries and various populations, as a whole, supported
the utility and proposed relationships outlined by the JCM (Champoux, 1991; Fried and
Ferris, 1987; Head & Sorensen, 1985; Kahn & Robertson, 1992; Khandelwal & Aleem,
1990; Suman & Srivastava, 2009).
In a more recent study that extended work on the JCM, Millette and Gagne (2008)
tested the application of the JCM on a volunteer organization, instead of paid
occupations. They studied the effects of the CJC and CPS on the outcome variables of
volunteer motivation, satisfaction, turnover intentions, volunteer performance, and
organizational citizenship behaviors (OCBs). The researchers gathered information from
124 volunteers (workers and supervisors) from a large community clinic. Supervisors
rated performance and OCBs. The researchers calculated the motivational potential score
of the volunteers and correlated the scores to the work outcomes. They then used a series
of multiple regressions to test the mediating effect of motivation. Results showed that the
components of the JCM positively correlated to satisfaction and performance.
Implications included that job designers could increase task identity and significance (i.e.
inform volunteers on how their work achieved organizational goals). The authors
13
speculated that the non-significant correlation to turnover intention was due to the
voluntary nature of the work (i.e. they sought the work out).
Other researchers chose not only to modify the JCM, but also focus on specific
portions of the model, such as the relationships between the CPS and the work outcomes.
Jaramillo et al. (2013) examined the relationship between experienced meaningfulness
and several work outcomes (performance, turnover intentions, and felt stress), as well as
the antecedents to experienced meaningfulness (ethical climate and customer
demandingness) at a top direct sales company. They examined the responses of 1450
direct sellers (directors and consultants): tenure ranged from 7 months to 35 years; age
ranged from 21 to 80 years old. They used a structural model to test their various
hypotheses. Results showed participants’ perceptions of experienced meaningfulness
influenced their performance, felt stress, and turnover intentions. They also found that the
antecedents impacted participants’ experienced meaningfulness. Thus, the results
supported the importance of experienced meaningfulness as a central facet in sales and in
job design. Similar studies yielded comparable results in regards to this CPS (Behson,
Eddy, & Lorenzet, 2000; Humphrey et al., 2007; Varga et al, 2012).
Given these prior research studies and to provide additional support for the
continued relevancy of the model, the current study will test a portion of the JCM.
Specifically, the researcher will examine the job components related to experienced
meaningfulness (skill variety, task identify, and task significance). The study will focus
on the important work outcomes of general job satisfaction and turnover intentions
14
because participants can easily report them and, more importantly, attitudes tend to lead
to certain behaviors, such as absenteeism and actual turnover (Bozionelos, 2009).
Therefore, the researcher hypothesized the following:
H1: The three core components of the JCM (skill variety, task identity, and task
significance) will positively relate to experienced meaningfulness.
H2: Experienced meaningfulness will relate positively to work satisfaction and
negatively to turnover intentions.
H3: The three core components of the JCM (skill variety, task identity, and task
significance) will relate to the two work outcomes: (a) positively relate to work
satisfaction and (b) negatively to turnover intentions.
H4: Experienced meaningfulness will act as a mediator for the relationship
between the first three core components of the JCM and the work outcomes.
Next, the review of the literature will discuss the rationale for inclusion of the
specific type of social attributes of the work environment (see Figure 2 for the proposed
additions).
15
Core Job Characteristics Critical Psychological States Work Outcomes Core Job Dimensions Skill Variety Task Identity High Satisfaction with Work Task Significance
Experienced Meaningfulness of Work Social Attributes of Work Low Turnover Intentions Managerial Support Supervisor Support Co-Worker Support Mentoring
Figure 2. Proposed additions to the Job Characteristics Model
16
Review of Social Attributes of the Work Environment
To support the inclusion of new job characteristics, researchers focused on the
employee and/or the job itself as a way to progress the JCM. For instance, Parmar (2001)
believed that positive work outcomes (work satisfaction and motivation) could increase
through meaningful manipulation of the job characteristics. The author incorporated
employees’ level of job anxiety as a moderator in the relationship between the core job
dimensions and work satisfaction. Two hundred supervisors in various public and private
organizations participated in the study. The results showed that the responses for the JCM
had stronger relationships for public sector employees (i.e. they were more satisfied).
More importantly, the job characteristics were strongly related to different types of work
satisfaction and job anxiety did moderate this relationship. Therefore, modifications and
additions to the JCM could be supported.
However, other researchers were less successful. For example, Kahn and
Robertson (1992) incorporated the use of technology to their additions to the JCM.
Specifically, they examined whether previous use of computers and extent of use of
computers in jobs could influence satisfaction beyond the core job dimensions outlined
originally in the JCM. The researchers categorized employees into two groups
(supervisors and subordinates) due to the different levels of training likely received by
the two groups. The participants came from the travel and trade industries (both used
computer based systems). The results showed that experience and training did not add to
the model (did not contribute anything extra beyond the predicted outcomes for
17
motivation and satisfaction of the JCM). Thus, the addition of two extra variables did not
significantly relate to the JCM. They concluded that other job dimensions not related to
the job itself should be explored.
As discussed in the previous chapter, Oldham and Hackman (2010) proposed
examining the social attributes of the work environment. Researchers initially paid little
attention to this emerging area of research. The catalyst for the shift was the workplace
environment changed (i.e. a pervasiveness of social interaction between the employee
and the work environment – co-workers, superiors, and clients within and outside the
workplace), but the issues did not (turnover, low satisfaction, and poor performance). To
that end, Strubler and York (2007) moved away from the assessment of individual
characteristics and towards an examination of social components within the work
environment with their study on team characteristics. The authors predicted that there
would be a difference between team and non-team members, as well as differences
between team members over time on the JCM factors (specifically, on the levels of
critical psychological states and work outcomes).
The researchers administered surveys to 500 administrators and clerical
employees at a Midwest university (50 teams and 130 non-team members responded).
The employees were involved in a job re-design process. The researchers also created
their own survey and established high reliability to extend the JCM. They found that
teams had higher levels of CPS. They also found that the CPS significantly related to
18
work outcomes (those with higher levels of CPS had more positive work outcomes)
(Strubler & York, 2007).
However, the previous study did not examine the quality of the relationships
experienced by the employees, either with their team members or superiors. Piccolo,
Greenbaum, Den Hartog, and Folger (2010) also supported the exploration of social
components. They focused on employees’ perspectives on supervisor behaviors and their
influence on work outcomes. The researchers hypothesized that task significance and
autonomy would mediate the relationship between ethical leadership and job
performance, as well as organizational citizenship behaviors (OCBs). They found that the
modified framework was supported by their field study data: high ethical leadership
linked to high job performance and OCBs when task significance and autonomy were
also high.
Another recent study of social factors was done by DeVaro, Li, and Brookshire
(2007). They tested the JCM model with the addition of a more general social factor,
contextual satisfaction (defined as a worker’s environment, which included satisfaction
with pay, job security, co-workers, and supervisors). The authors used responses from
British employees and employers, in various industries, to the 1998 Workplace Employee
Relations Survey (WERS). They used a stratified random sample of 25 participants per
establishment (n = 2,191). They focused on production and growth accomplishment as
dependent variables, skill variety and autonomy as independent variables.
19
The researchers controlled for variables such as establishment size, independent
and franchise. Overall, the predictions of the JCM were strong for performance and work
satisfaction. However, contextual satisfaction only received partial support, as it only
predicted job satisfaction; thus, the authors concluded that this factor should be defined
less broadly (DeVaro et al., 2007). Unfortunately, the issue is there are numerous factors
that can be identified as a social attribute of work.
Sources of Social Support
Various researchers attempted to identify different facets of the work environment
as a social attribute of work. Morgeson and Humphrey (2006) explored several types of
social sources and their impact on work outcomes; they sought to expand the JCM to
include the most relevant aspects of the work environment. They conducted a
comprehensive literature review to identify all work characteristic terms used in the job
design research. The researchers then sorted 107 terms into 18 work characteristic
categories, based on the similarities of definitions. They further sorted the terms into
three broad categories: motivational (composed of task and knowledge requirements that
enrich jobs), social (social support, interdependence, interaction outside the organization,
and feedback from others), and contextual (physical and environmental contexts).
They constructed a comprehensive and parsimonious measure, called the Work
Design Questionnaire (WDQ), from scales used in the literature. They edited and created
items when there was a need for construct clarification. The researchers also used a
simple five point response scale (from strongly agree to strongly disagree) and
20
distributed the questionnaire to 540 job incumbents from over 200 different industries.
They found that the data supported a 21 factor model; the scale was also reliable at an
individual level and across various jobs. More importantly, the results showed that social
support (defined as the extent to which employees have the opportunities to receive
assistance and advice from others) predicted satisfaction beyond the traditional
motivational work characteristics. Thus, increased social support (from co-workers and
supervisors) within the workplace should increase motivation to work and become a
primary characteristic in the social work environment (Morgeson & Humphrey, 2006).
Similarly, Humphrey et al. (2007) conducted a meta-analysis to examine the
effects of four social characteristics (interdependence, feedback from others, social
support, and interaction outside the organization) on work outcomes. They controlled
several JCM factors, such as autonomy. The authors searched PsycINFO and Web of
Science databases. Terms used were enrichment, characteristics, and JCM. The
researchers also reviewed abstracts that related to the study’s goals and variables, as well
as reported results that allowed for the calculation of effect size. They used a series of
regressions to analyze the data from 259 articles. Results showed that the social
characteristics explained the variance in subjective performance assessments, turnover
intentions, and satisfaction beyond the non-social characteristics (such as autonomy, skill
variety, and task significance). Most notably, social support demonstrated a relationship
with the majority of behavioral and attitudinal work outcomes. Therefore, social
21
characteristics should not only be integrated into the JCM model, but there should also be
a focus on social support from supervisors and co-workers.
A large body of studies not directly tied to the JCM investigated the relationship
between these sources of social support and the work outcomes of job satisfaction. For
instance, Ng and Sorensen (2008) examined the effects of perceived social support from
co-workers (PCS) and supervisors (PSS) in their meta-analysis. They found that PSS was
more strongly related to job satisfaction, affective commitment, and turnover intention
than PCS. They reasoned that supervisor support may be seen as more valuable than co-
worker support due to their extensive training and experience. Thus, supervisors’
capacity to be a source of emotional and career support may be more developed than an
employee’s co-workers. However, the authors concluded that future researchers should
still conduct studies on the utility of PCS because co-workers experience similar
situations as participants and could be a potential source of psychological support. The
authors also found that the sources of support were significantly related; thus, the amount
of one source of support should effect the perception of support for the other.
On the other hand, other researchers included managerial support; this was, most
likely, due to the possibility that employees formed attachments and attitudes towards
their managers that were distinct from those they had with their supervisor or co-workers.
These attachments could also impact employee work outcomes (Newman, Thanacoody &
Hui, 2012). A study by Rooney, Gottlieb, and Newby-Clark (2008) supported the
importance of upper management. They examined the relationship between managerial
22
behaviors (supportive and unsupportive) and work attitudes. The authors argued that
autonomy and perceived managerial sentiment would mediate the relationship. They
surveyed 247 employees at a non-profit child welfare agency in Canada.
Through structural equation modeling, the researchers found support for
mediation: more supportive managerial behaviors resulted in less job strain, increased
levels of job satisfaction, and lower levels of turnover intentions when employees felt
greater autonomy and perceived managerial sentiment. The authors concluded that
supportive managers communicated to employees that the organization valued them,
which resulted in positive employee outcomes. Thus, managerial support formed the
basis of organizational perspectives and could be seen as organizational support (Rooney,
Gottlieb, & Newby-Clark, 2008).
On a similar note, Tang, Siu, and Cheung (2014) explored the link between three
sources of social support (co-worker, supervisor, and organizational) to job satisfaction.
They built on social exchange theory and hypothesized that work-family enrichment
(defined as experiences in one role positively affect experiences in the other role)
mediated the relationship of interest. They used 543 Chinese participants because most of
the existing literature had samples taken from Western countries. They found that social
support was related to job satisfaction and work-to-family enrichment. When employees
perceived organizations support, they reciprocated with positive work attitudes.
Moreover, in regards to work-family enrichment, they found that work-family enrichment
did mediate the relationship between support and job satisfaction for only supervisor and
23
organizational support. The authors concluded that management, in general, set
organizational norms of whether the work environment would be conducive to work-
family balance. Therefore, organizations that support and foster a work-family culture
enjoyed beneficial outcomes.
Likewise, other studies findings contributed to a direct or indirect link between
the three sources of social support and job satisfaction, in various industries and countries
(Abualrub, Omari, & Abu Al Rub, 2009; Bennett, Lowe, Matthews, Dourali, &
Tattersall, 2001; Brough & Frame, 2004; Galletta, Portoghese, Penna, Battistelli, &
Saiani, 2011; Gillet, Gagne, Sauvagere, & Fouquereau, 2013; Ko, Hur, & Snnith-Walter,
2013; Sawang, 2010; Te Boekhorst, Willemse, Depla, Eefsting, & Pot, 2008; Ter Doest
& de Jonge, 2006).
As seen in the Ng and Sorensen (2008) study, another area greatly impacted by
the three sources of social support was turnover intentions. Newman et al. (2012) focused
on social support from the supervisor and organization. They investigated the role of
social supports’ in the relationship between network resources (web of informal
relationships used by the employee for purposes of advancement or psycho-social
support) and turnover intentions among 1,000 Chinese participants employed at five
multinational organizations.
Through structural equation modeling, the authors found POS mediated the
relationship between supervisor support and turnover intentions. They also found that
POS mediated the relationship between network resources and turnover intentions: the
24
more resources an employee had (i.e. formed more relationships within the organization),
the lower the turnover intentions when POS was high. Another important factor included
in the analysis was affective commitment; the results showed that affective commitment
mediated the relationship between perceived organizational support (POS) and turnover
intentions. The authors concluded that employees formed attachments to their
organization when they felt supported, which compelled them to remain with the
organization through a sense of loyalty (Newman et al., 2012).
Likewise, Tymon, Stumpf, and Smith (2011) examined the effects of managerial
support on employee outcomes among 28 Indian companies (n = 4,811). The results
showed a direct negative correlation between managerial support and turnover intentions,
as well as career success over the course of one year later. The relationship was also
mediated by intrinsic reward and personal commitment. The findings suggested that
managers played an important role in retention of employees due to their dissemination
of information (employees knew what the organization valued and strove to achieve those
goals to receive rewards), as well as their promotion of company loyalty.
Another study by Cuyper, Mauno, Kinnunen, and Makikangas (2010) investigated
social attachments to the organization and their influence on turnover intentions. The
researchers gathered data on perceived employability (PE), defined as the ease of finding
new employment, turnover intentions, as well as job resources (job control, supervisor
support, and co-worker support) from more than 500 university personnel and healthcare
workers in Finland at two separate times (one year apart). The results showed that PE was
25
negatively related to turnover intention when job control was low: employees had higher
turnover intentions when new employment was easy to find and their job offered little
control. However, the authors found that social support moderated the relationship
between PE and turnover. Therefore, employees had lower turnover intentions, even
when employability was high, because they had meaningful relationships with their
supervisors and, especially, their co-workers. The authors concluded that job design and
interventions should allow employees increased control over aspects of jobs, as well as
opportunities to foster interpersonal relationships with colleagues, such as teamwork
projects.
Moreover, Dysvik and Kuvaas (2013) studied the effects of job autonomy on
turnover intentions in the presence of social support. The participants were 680
Norwegian employees from different public services organizations. They found that the
employees with more job autonomy had lower intentions to leave when they experienced
high social support from supervisors. They suggested that social support made employees
feel that their contributions were valued by the organization. Supervisors provided
emotional support, recognized employees’ efforts, and facilitated work by answering
questions. All served to decrease employees’ intention to leave because they felt
comfortable and enjoyed their workplace. Similar studies yielded comparable results and
conclusions in regards to social support and turnover intentions (Bhatnagar, 2014;
Brough & Frame, 2004; DeConinck & Johnson, 2009; Gillet et al., 2013; Kim, 2014; Van
der Heijden et al, 2010).
26
The majority agreed that social support within the workplace also impacted
employees’ well-being and personal lives, further substantiating the importance of these
factors (Bennett et al, 2001; Ng & Sorensen, 2008; Seiger & Wiese, 2009; Ter Doest &
de Jonge, 2006). For example, Kitaoka-Higashiguchi et al (2003) found that social
support within the work place had a positive effect on depression with a sample of
intermediate manufacturing managers. Pomaki and Anagnostopoulou (2003) found that
high demands, low control, and low social support were related to low job satisfaction,
high burnout, and somatic complaints. Similarly, Treibera and Davis (2009) found that
among 1602 employees that experienced chronic pain at work, co-worker support was
associated with lower exhaustion, better self-reported health, and less pain; while
increased supervisor support was associated with lower exhaustion and better self-
reported health.
Mentoring
Another closely related avenue of research receiving a considerable amount of
attention is the role of mentoring in the work related outcomes assessed in the JCM.
Harris, Winskowski, and Engdahl (2007) findings suggested that active participation of
others in the career and daily work life of an employee could have beneficial effects,
especially when employees formed adviser relationships with more experienced
individuals. Mentor was loosely defined as an individual with more experience and
knowledge than the protégé, who provided support and guidance for the advancement of
an individual’s career (Hebl, Tonidandel, & Ruggs, 2012). Subsequent researchers also
27
supported the conclusion that mentoring was immensely beneficial for the employee,
either directly or indirectly. The benefits centered on higher levels of job satisfaction
and/or higher intentions to stay at their place of employment (Bedini & Anderson, 2003;
Bozionelos, 2009; Dawley, Andrews, & Bucklew, 2010; Emmerik, 2003; Lo &
Ramayah, 2011; Prevosto, 2001).
Kammeyer-Mueller and Judge (2008) conducted a meta-analysis on mentoring
practices’ impact on work outcomes. They sought to consolidate often contradictory
findings. The authors examined mentoring practices’ relationship with work and career
satisfaction outcomes. The researchers searched the PsycINFO database. They reviewed
120 articles that met their inclusion criteria (studies that had quantitative data, calculable
correlations, and those that measured the relationships of interest). They then performed
structural equation analyses. Results showed that mentoring had a substantial effect on
job and career satisfaction when covariates were held constant (such as demographics of
gender, age, and tenure). However, relationships were moderate to weak. An alternative
explanation was that those without mentors sought other social sources of information in
order to perform well and to advance (such as senior colleagues etc.).
On a similar note, Brashear, Bellenger, Boles, and Barksdale (2006) addressed the
effects of different sources of mentoring and work outcomes. They gathered longitudinal
data from 60 salespersons in the United States and Canada. The participants indicated
that they received mentoring from a senior employee, a co-worker, or an outside source.
The results showed that the participants that received mentoring from a superior had
28
higher performances and lower intentions to leave, while mentoring from a co-worker
resulted in lower performances and lower intentions to leave. Mentoring from an outside
source resulted in higher performances and higher intentions to leave. The authors
concluded that the most effective mentor was a superior within the organization. As a
result, organizations should foster or create either a formal or informal mentoring system.
Consequently, Chen, Liao, and Wen (2013) investigated the amount of formal
mentoring given to employees in China among 208 mentor-protégée relationships on
turnover intentions. They wanted to address the need for research on formal mentoring
programs used by various organizations. The researchers gathered data on the amount of
mentoring, turnover intentions, psychological safety (employees felt safe to speak up and
discuss issues), affective commitment, and power distance orientation. The results
showed that psychological safety mediated the negative relationship between mentoring
and turnover intention, and partially mediated the positive relationship between
mentoring and affective commitment. The authors concluded that organizations should
create a climate where employees feel safe to share their opinions in order to take
advantage of formal mentoring programs, which will most likely result in decreased
intentions to leave and commitment to the organization.
Moreover, Egan and Song (2007) investigated the differences between informal
and formal mentoring programs. The researchers collected data from 158 employees of a
health care organization in the United States (employed between 6 and 18 months). The
researchers created three groups through random assignment: high facilitation mentoring
29
group (greater effort expended to strengthen the relationship between mentor and
protégé, geared towards accomplishment of specific goals, as well as support throughout
the program), low facilitation (less effort to strengthen the relationship beyond the
dissemination of information), and no mentor group (this group had the opportunity to
receive formal mentoring six months later). The employees filled out pre and post
intervention surveys. The results showed that high facilitation resulted in higher levels of
job satisfaction, organizational commitment, and manager ratings on performance. Also
those that received some sort of mentoring had higher levels of these work outcomes than
those that did not. The authors concluded that even a small amount of mentoring could
have a profound impact on employees.
On a similar note, Raabe and Beehr (2003) suggested that functions of a mentor
could be performed by supervisors and co-workers due to their ability to agree on the
nature of the mentoring relationships (discussion and establishment of mentoring
relationship’s purpose, as well as appropriate goals). The researchers believed that
immediate supervisors and senior co-workers had knowledge about the mentees’ needs
and goals because of their close proximity to and familiarity with the employee;
therefore, an amicable relationship would have most likely already formed. These
relationships could be accomplished through formal or informal mentoring programs.
However, the researchers did not recommend organizations assign a mentor from upper
management (i.e. a mentor far removed from the employee).
30
Additionally, diverse individuals with diverse mentors could also experience the
positive outcomes associated with mentoring. Hebl et al. (2012) examined diversity, as
well as psychological (job satisfaction) and tangible (promotions and salary increase)
work outcomes. Specifically, the researchers examined gay/lesbian protégés paired with
non-LGBT mentors, LGBT mentors, or no mentor. They gathered data from 253
attendees of a gay-friendly businesses convention in Houston. The findings revealed that
having a mentor, regardless of orientation, related to greater satisfaction and job
involvement for the protégé. The results also showed that protégés who identified
themselves as gay/lesbian and had a gay/lesbian mentor reported higher levels of
satisfaction and job involvement compared to those that did not have a mentor. The
authors concluded that having access to a mentor would be beneficial to employees and
that having a mentor with a similar background to the employee would be preferable.
Although pairing an employee with a mentor of similar background was
preferable, parallel to studies on formal mentoring programs, any exposure to a mentor
could prove beneficial to an employee. Hoigaard and Mathisen (2009) found that,
regardless of the gender of the mentor, female protégés benefited from receiving any
form of mentoring. Specifically, the 36 female participants who had leadership roles
reported higher levels of job satisfaction, career planning, and an improvement in their
own leadership behaviors. In addition, Lo, Ramayah, and Kui (2011) found that the
presence of mentoring increased job satisfaction, regardless of gender congruence (the
mentor was the same gender as the protégé) among 156 executives from Malaysian small
31
and medium enterprises. Therefore, any amount of mentoring significantly affected job
satisfaction of the employees positively.
Conversely, other researchers focused on the emotional attachment the mentor
fostered with the employee (Craig, Allen, Reid, Riemenschneider, & Armstrong, 2012;
Lankau & Scandura, 2002; Richard, Ismail, Bhuian, & Taylor, 2008). Their results
showed that organizational commitment (an employee’s attachment and involvement to
an organization) played a role in the relationship between mentoring and turnover
intentions: mentors created a sense of trust and emotional attachment that prevented
emotional and physical detachment, as well as decreased turnover. These findings were
comparable to those of social support.
Likewise, the literature on mentoring and job satisfaction tended to favor a
positive relationship due to an emotional attachment. For instance, Baranik, Roling, and
Eby (2009) investigated the mechanisms that contributed to positive mentoring outcomes.
They believed that mentoring consisted of career-related (sponsorship, coaching, and
visibility) and psycho-social (friendship, role modeling, and counseling) support
behaviors. They proposed that perceived organizational support (POS) mediated the
relationship between mentoring and job satisfaction, as well as affective organizational
commitment. The researchers recruited substance abuse counselors from 27 different
Community Treatment Programs (n = 733) across the United States. The results showed
that mediation was only partially supported: employees that experienced visibility, role
modeling, and exposure had higher levels of job satisfaction and organizational
32
commitment when they perceived organizational support. The authors concluded that
when mentors “advertised” employees’ accomplishments to others, employees felt that
the organization cared about them.
Additional evidence suggested that mentoring also benefited the organization as a
whole. Allen, Smith, Mael, O-Shea, and Eby (2009) hypothesized that mentoring would
lead to better organizational performance, job satisfaction, citizenship behaviors, and
learning. They surveyed 589 employees from 39 different substance abuse treatment
agencies. The results supported their hypotheses for those organizations with a greater
number of mentors. They concluded that organizations should devote their resources and
time to the development of a mentoring system for these benefits and the potential of
gaining a competitive edge.
Given the extensive evidence supporting relationships between the social
attributes of jobs and various work-related outcomes, the primary focus of this study is
the integration of social attributes of work into the JCM. Specifically, the researcher will
examine the effects of various types of social support (managerial, supervisors, co-
workers) and mentoring on the work outcomes of satisfaction and turnover intentions.
Furthermore, based on previous researchers’ findings on the importance of experienced
meaningfulness as a mediator (Humphrey et al. 2007; Jaramillo et al., 2013), the
researcher will explore its relationship to social attributes of the job (as seen in Figure 2).
The researchers, therefore, hypothesized the following:
33
H5: The four social attributes of jobs (a) managerial support of work-family
balance, (b) supervisor support, (c) co-worker support, and (d) mentoring will
positively relate to experienced meaningfulness.
H6: The social attributes of jobs (managerial support of work-family balance,
supervisor support, co-worker support, and mentoring) will relate to the two work
outcomes: (a) positively relate to work satisfaction and (b) negatively to turnover
intentions.
H7: Experienced meaningfulness will mediate the relationship between the social
attributes of jobs and the work outcomes.
34
Chapter 3
METHODS
Participants
The participants were employees at a large metropolitan state university. The
study focused on staff members; therefore, faculty members were excluded. The human
resources department released the names of the approximately 1,300 staff members to the
research team for recruitment purposes. The data collected from the staff were used to
evaluate the hypotheses of a separate larger study and also by each of the research team
members for their respective related studies. The researcher of this study and her team
members linked the staffs’ names with their corresponding e-mail addresses using the
online university directory. Through this process, the team excluded those that did not
have a viable e-mail address listed and narrowed the potential participant pool to 893.
Once the research team identified potential participants and sent the invitations for the
larger study, they did not continue to use the participants’ contact and other identifying
information (i.e. the responses could not be linked to a specific participant during data
collection and subsequent analyses).
The researcher further narrowed down the potential participant pool through the
exclusion of incomplete surveys. A final sample of 137 (male = 37, female = 98, missing
= 2) ultimately returned completed surveys. The majority of the sample identified as
Caucasian (61%). The remainder of the sample identified as Asian (4.4%), Black/African
35
American (7.4%), Hispanic (10.9%), and Pacific Islander (2.2%). A small minority
identified themselves as “other” and those that indicated more than one ethnicity were
also included into this category (10.9%). Four participants did not indicate an ethnicity.
Furthermore, the age for the sample ranged from 23 to 61 years of age with an
average of 26.93 years of age. The bulk of the sample also indicated that they were
married (58.4%), while 21.9% were single, 8% were divorced, 5.8% lived with a partner,
2.9% were widowed, 1.5% were separated, and 1.5% declined to state their marital status.
The majority also indicated that they had families (59% reported that they had raised
children), earned an income between $41,000 and $60,000 annually, and worked for the
university for more than ten years. Additionally, most of the sample reported that they
were administrative staff (29.9%); several others indicated that they were trained
professionals (19.7%), support staff (18.2%), middle management (13.9%), junior
management (8.8%), upper management (4.4%), researcher (1.5%), as well as a skilled
laborer (0.7%) to a lesser degree. Four declined to state their role at the university.
Additionally, in order to increase the chances of voluntary participation, the
researcher team informed the participants that they would have the opportunity to win a
$30 gift card to the university bookstore. The researchers treated the participants in
accordance with the APA ethical guidelines: with assurances of anonymity and
confidentiality, as well as that the data collected from the inventories would likely pose
no more than minimal risk to the participants.
36
Materials
The materials used in the larger study were an electronic device capable of
internet access (computer, laptop, tablet, etc.), an e-mailed invitation to participate in a
survey, and the online survey. The invitation contained the URL that redirected potential
participants interested in the study to the online survey. The online site SurveyMonkey
sent the invitations and distributed the survey. The survey had a consent form, a
demographic questionnaire (both created by the research team), and fourteen inventories.
The first screen of the online survey was a greeting that acted as the consent form (see
Appendix A). The consent form briefly described the purpose of the study, the
procedures, the potential benefits of participation, and emphasized that the survey should
not take more than 10 to 15 minutes to complete.
In addition, the consent form assured the employees that participation was
completely voluntary, no personal information (such as their name or e-mail address)
would be collected, and that their anonymity would be insured as far as allowed by the
technology employed, as well as the absence of known risks to participation in this study.
At the bottom of the screen, participants either clicked “Agree” or “Decline”. If they
declined to participate, then the survey closed out. If they agreed, then that denoted
electronic consent to participate. The participants also learned that they had the option of
entering their e-mail into a lottery upon completion of the survey. Since the site did not
allow the researchers to track the responses back to the original survey, participants used
a different site for a chance to win a $30 gift card from the university bookstore.
37
Furthermore, the demographic items covered gender, age, marital status, parental
status, ethnicity, and personal yearly income, as well as career related items, such as job
title and stage of career (see Appendix B). The inventories measuring various
psychological characteristics were chosen because of their strong psychometric properties
and common usage in the collection of information on employees’ work lives. The
researcher only used 10 of the 14 inventories to evaluate the hypotheses presented earlier.
The researcher downloaded the data from SurveyMonkey for use in the analyses.
Social Attributes of Work
The social attributes of work consisted of four inventories that measured
managerial support, supervisor and coworker support, and mentoring (see Appendix C).
Managerial support measured the extent employees felt managers supported their efforts
for work-family balance. The 11 item questionnaire was a subscale of the Work-Family
Culture Inventory developed by Thompson, Beauvais, and Lyness (1999) through a
literature review and consultation of subject matter experts. The full inventory originally
consisted of 21 items that measured respondents perception of the extent their
organization facilitated their efforts to balance work and family responsibilities on three
subscales: managerial support, career consequences (negative outcomes from the
utilization of work-family benefits), and organizational time demands (work demands
that could interfere with non-work responsibilities).
Responses to the managerial support subscale ranged from (1) disagree strongly
to (7) agree strongly. The reliability for the full inventory was .91; alphas for managerial
38
support items ranged from .46 to .78. The researcher summed the items on the subscale as
per original scale directions: higher scores indicated more supportive managers and lower
scores indicated a lack of a managerial supportive culture. A sample item was “In
general, managers in this organization are quite accommodating of family-related needs”.
Additionally, Caplan, Cobb, French, Harrison, and Pinneau’s (1975) inventory
assessed the extent of social support. The full inventory consisted of 21 items and
measured the extent of social support and assistance the responder received from their
supervisors, co-workers, and subordinates regarding issues related to both work and
personal matters. The current study only used items that dealt with supervisor and co-
worker support for the online survey. Items included “How much can you rely on your
immediate supervisor when things get tough at work?” and “How much do other people
at work go out of their way to do things to make your work life easier for you?”,
respectively. The items were only modified slightly to fit the format of SurveyMonkey.
Responses ranged from (0) don’t have such a person to (4) very much: larger scores
corresponded to a greater degree of the specified type of social support and smaller scores
corresponded to a lesser degree of support. The coefficient alpha for the complete
inventory was .91. The researcher averaged the items for each subscale to obtain a score
for supervisor support and a score for co-workers support.
Next, Dreher and Ash (1990) created a global mentoring inventory, modeled after
previous research, to measure mentoring practices for various careers and psychosocial
functions. The inventory contained 18 items. The inventory’s internal consistency was
39
high (coefficient alpha of .95). Respondents considered their work history and influential
figures in their careers when they answered the questions. The inventory then asked them
to consider the extent to which a mentor has, for instance, “Given or recommended you
for challenging assignments that present opportunities to learn new skills?” and “Gone
out of his/her way to promote your career interests?” Responses ranged from (1) not at all
to (5) to very a large extent. The researcher calculated the mean of the 18 items for each
participant. Possible range for scores were between one and five: higher scores indicated
the presence of mentoring and lower scores represented a lack of mentoring.
Core Job Dimensions and Critical Psychological State
The Job Diagnostic Survey (JDS), developed by Hackman and Oldham (1980),
measured aspects of the respondents’ job in regards to the five core dimensions,
psychological states, and work outcomes that composed the Job Characteristics Model
described earlier. The inventory had α levels that ranged from .56 to .88. The researcher
assessed the responses from the Experienced Meaningfulness subscale (see Appendix D).
This portion of the JDS had four items that measured the degree to which participants’
believed their work to be valuable. Participants responded to the inventory using a 7-
point Likert type scale, (1) disagree strongly through (7) agree strongly to questions such
as “The work I do on this job is very meaningful to me”. Negatively worded items were
re-coded during the analysis. The researcher averaged the responses for the four items to
yield a summary score.
40
Furthermore, the researcher analyzed the responses for the Task Identity, Task
Significance, and Skill Variety subscales (see Appendix E). Each subscale contained three
items. Sample questions included “The job is arranged so that I do not have the chance to
do an entire piece of work from beginning to end” (for task identity), “This job is one
where a lot of other people can be affected by how well the work gets done” (for task
significance) and “The job requires me to use a number of complex or high-level skills”
(for skill variety). The responses scale for each item differed, somewhat, for each
subscale. For the first question, the participants’ indicated (1) very little presence of that
dimension, (4) a moderate presence of that dimension, and (7) a high degree of that
dimension. For the last two questions in each subscale, participants responded on a Likert
scale with (1) very inaccurate to (7) very accurate. The researcher averaged the items to
obtain a summary score for each participant for each variable.
Work Outcomes
Finally, the researcher examined participants’ job satisfaction and turnover
intentions (see Appendix F). Judge, Bono, and Locke (2000) employed a five item scale
created by Brayfield-Rothe (1951) to assess overall job satisfaction: the extent that
employees were happy and content with their jobs. The scale had an alpha coefficient of
.89. Participants responded to each item using a 7-point scale: (1) disagree strongly to (7)
agree strongly. Items included “I feel fairly satisfied with my present job” and “I find real
enjoyment in my work”. The researcher averaged the items to indicate the degree of
41
satisfaction. Possible responses ranged from one to seven: lower scores indicated low
levels of satisfaction and higher scores suggested higher satisfaction with their job.
Additionally, Adams and Beehr (1998) constructed a scale to measure turnover
intentions: an individual’s level of intention to leave their position or organization. The
survey contained three questions and had an internal reliability of .88. For the items,
individuals used a 7-point Likert response scale: began with (1) disagree strongly and
ended with (7) agree strongly. Lower scores indicated little intention for employees to
leave, high scores suggested higher intentions to leave. A sample item was “I am
planning to leave my job for another in the near future”.
Procedures
The research team began data collection on September 25, 2013. The window for
participation ended on November 1, 2013. Once the research team selected the potential
participants for the study (staff members with identifiable e-mail addresses), the potential
participants received invitations via e-mail, sent from the lead researcher’s faculty
account on SurveyMonkey. The e-mails were blind carbon copies (“BCC”) to ensure
anonymity; participants did not see other potential participants’ information. The e-mail
message contained a URL hyperlink that brought the participants to the survey located on
the SurveyMonkey website, if they were interested. The first screen of the survey
contained a greeting/consent form. Once the individuals read through the information,
they had the opportunity to decline or agree to participate. If the individual declined to
participate, then the survey thanked them for their time and closed out. If they agreed
42
then they would start the survey.
The survey consisted of fourteen inventories presented on several screens; each
set of questions referred to the variables of interest of the larger study. Participants
responded to all the items on scales that were in closed-ended format, with the exception
of one demographic item (the participants’ clicked “other” then typed in a specific
response, not given as an option). Upon completion of the survey, the participants had the
option to enter their e-mail address (on a separate page) into a lottery for the chance to
win a $30 university bookstore gift card. The winners were notified once the window of
participation closed and responses complied.
To encourage more individuals to participate, the research team indirectly sent a
brief reminder e-mail to those that neither declined nor agreed to participate. In
particular, SurveyMonkey’s programming maintained an internal database that contained
the information of those who did and did not participate. As part of the options, the
research team chose to have SurveyMonkey send the reminder e-mails. Thus, the
research team did not have direct access to the contact information of those that did not
participate (they remained anonymous). Furthermore, the URL in the e-mail message,
again, redirected those interested in the study/participation to the survey when clicked.
The individuals read through the original greeting and had the same decline or agree to
participate options. If they agreed, then they took the original survey.
43
Chapter 4
RESULTS
Preliminary Analyses
Descriptive Statistics
The researcher calculated descriptive statistics for the variables outlined in the
hypotheses, displayed in Table 1 below. The researcher calculated the confidence
intervals for each skewness and kurtosis statistics; absolute values less than one were not
greatly skewed or different from a normal distribution, values between one and two were
becoming very skewed or different from normal, and values greater than two were
extremely skewed or different than normal. The distributions of the variables displayed
varying degrees of skewness and kurtosis. Overall, the majority of the variables had
slightly negatively skewed distributions, but they were not very kurtotic (the statistical
values and confidence intervals’ for both were lower than two in most cases). Violations
of the assumption of normality would not be problematic because the distributions did
not deviate, tremendously, from normal. Also the current study did not utilize norm
referenced samples in the evaluation of the hypotheses.
44
Table 1
Descriptive Statistics for all Variables
*Variables M SD
Skewness Kurtosis
Statistic 95% CIs Statistic 95% CIs
1. JS 5.03 1.50 -1.04 [-1.45, -0.63] 0.37 [-0.44, 1.18]
2. TI 3.49 1.88 0.27 [-0.14, 0.68] -1.18 [-1.99, -0.37]
3. MS 51.32 11.77 -0.91 [-1.32, -0.50] 0.67 [-0.14, 1.48]
4. SS 2.87 1.04 -0.72 [-1.13, -0.31] -0.40 [-1.21, 0.41]
5. CWS 2.90 0.81 -0.50 [-0.91, -0.09] 0.15 [-0.66, 0.96]
6. Mentoring 2.95 1.10 -0.01 [-0.42, 0.40] -1.12 [-1.93, -0.31]
7. EM 5.16 1.23 -0.77 [-1.18, -0.36] 0.49 [-0.32, 1.30]
8. Task ID 5.17 1.53 -0.85 [-1.26, -0.44] 0.34 [-0.47, 1.15]
9. TS 5.97 1.25 -1.51 [-1.92, -1.10] 1.91 [1.10, 2.72]
10. SV 5.39 1.49 -0.94 [-1.35, -0.53] 0.22 [-0.59, 1.03] Note. n = 137; Standard Error of Skewness = 0.21; Standard Error of Kurtosis = 0.41;
95% CIs = 95% Confidence Intervals; *JS = Job Satisfaction, TI = Turnover Intentions,
MS = Managerial Support, SS = Supervisor Support, CWS = Co-Worker Support, EM =
Experienced Meaningfulness at Work, Task ID = Task Identify, TS = Task Significance,
SV = Skill Variety.
45
Reliability
The researcher examined the internal consistency for each scale used in the study
to identify any potentially problematic items. The four social attributes of work had
strong internal consistency: managerial support (α = .89), supervisor support (α = .91),
co-worker support (α = .87), and mentoring (α = .97). The measures from Hackman and
Oldham’s (1974) JCM had weaker, but still acceptable reliability levels: Cronbach’s
alpha for experienced meaningfulness of work was .83; task identity had an alpha of .72,
while task significance was .74, and skill variety was .80. In regards to the criterion
variables, the alpha levels were strong for both job satisfaction (α = .92) and turnover
intentions (α = .91). The results also showed that several scales had stronger alpha levels
than originally reported.
Primary Analyses
Correlations
As a part of the mediation analyses, the researcher conducted correlational
analyses to examine the relationships between the social attributes of work and portions
of the JCM. Altogether, the results fully supported hypotheses 1 through 3, as well as
hypotheses 5 and 6. As seen in Table 2, all eight variables were significantly positively
correlated with the criterion variable job satisfaction at the .01 alpha levels. The majority
of the variables were also significantly negatively correlated with turnover intentions at
the .01 alpha level (co-worker support was related at the .05 alpha level). Thus, high
46
scores on the social attributes and JCM scales were associated with both high scores on
job satisfaction and low scores on turnover intentions.
Following the suggested guidelines offered by Cohen for the interpretation of the
magnitude of r (absolute values of .10 to .29 corresponded to a weak correlation, .30 to
.49 corresponded to a moderate correlation, and .50 to 1.0 equated to a strong
correlation), overall, the strength of the relationships between the criterion variables and
both social attribute variables and the JCM variables mostly ranged from moderate to
strong.
Furthermore, the proposed mediator, experienced meaningfulness at work, was
significantly positively correlated with the proposed predictor variables of three of the
four social attributes of work and all three JCM core dimensions at the .01 alpha level.
The fourth social attribute of work, co-worker support, was correlated with experienced
meaningfulness at a .05 alpha level). The relationship strengths ranged from weak to
moderate.
47
Table 2
Correlation Matrix for all Variables
Variables 1 2 3 4 5 6 7 8 9 10
1. JS ______ .71** .52** .53** .29** .56** .64** .38** .48** .53**
2. TI
______ -.36** -.45** -.21** -.46** -.45** -.24** -.37** -.35**
3. MS
______ .60** .42** .60** .37** .47** .29** .19**
4. SS
______ .39** .63** .28** .41** .24** .15*
5. CWS
______ .47** .21** .28** -.01* .09*
6. Mentoring
______ .46** .30** .32** .33**
7. EM
______ .30** .52** .53**
8. Task ID
______ .27** .15n
9. TS
______ .49**
10. SV ______
48
Note. n = 137; ** Correlation is significant at the 0.01 level (2-tailed); *Correlation is significant at the 0.05 level; JS = Job
Satisfaction; TI = Turnover Intentions; MS = Managerial Support; SS = Supervisor Support; CWS = Co-Worker Support; EM
= Experienced Meaningfulness at Work; Task ID = Task Identify; TS = Task Significance; SV = Skill Variety.
49
Mediation
After identifying relationships between the variables of interest, the researcher
conducted a series of simple regressions to test mediation for each pathway outlined in
hypotheses 4 and 7. The analyses followed the steps proposed by Baron and Kenny
(1986). In each set of analyses, the “enter” method for the mediation analyses controlled
for key demographic variables of gender, age, ethnicity, and tenure. The researcher chose
these demographic variables because they were commonly accounted for within the
literature.
For the first set of regression analyses, the researcher produced the direct beta
weights (denoted β in Tables 3 to 6) between the predictors (the three CJS and the four
social attributes) and criteria (job satisfaction and turnover intention). These analyses
established which relationships could be mediated. In the next set of analyses, the
researcher treated the mediator (experienced meaningfulness of work) as a criterion
variable. As seen in Figure 3, Path A demonstrated the association of the predictors to the
mediator. The last set of analyses involved the predictors, mediator, and criteria. Path B
established that the mediator affected the criteria, while Path C showed whether or not
the mediator explained the relationship between the predictors and criteria (beta weights
denoted β’).
50
Figure 3. The standardized regression coefficients for the relationship between the predictor variables (the four social
attributes and the three JCM variables) and the criterion variables (job satisfaction and turnover intention) as mediated by
experienced meaningfulness.
51
Full mediation occurred when, after taking into account the demographics, Path A
and B were significant, while Path C was non-significant. In regards to Path C, the beta
weights between the predictors and criteria when the mediator was accounted for (β’)
were smaller than the beta weights between the various predictors and criteria (β).
Therefore, experienced meaningfulness fully attenuated the relationship between the job
characteristics and the work outcomes. However, when Path C remained significant (but
reduced in size in comparison to β), along with Path A and B, this satisfied the criterion
for partial mediation. Thus, the predictors influenced the criteria directly and through the
mediator. Overall, the results for H4 showed that the relationship between the three core
job dimensions and job satisfaction were all partially mediated by experienced
meaningfulness of work.
Table 3
The Standardized Regression Coefficients for the Relationship between Task-related JCM
Variables and Job Satisfaction as Mediated by Experienced Meaningfulness
Path C
Variables Path A Path B β β' 95% CIs
1. Task ID 0.32** 0.54** 0.40** 0.23** [0.08, 0.37]
2. TS 0.49** 0.49** 0.50** 0.26** [0.11, 0.50]
3. SV 0.50** 0.45** 0.58** 0.35** [0.19, 0.53] Note n = 122; ** significant at the 0.01 level; beta weights for Path C analyses without
mediator; β’ = beta weights for Path C analyses with mediator; Task ID = Task Identity;
52
TS = Task Significance; SV = Skill Variety; 95% CI = 95% Confidence Intervals (upper
and lower bounds).
In particular, as shown in Table 3, Path A (the standardized regression
coefficients between the three task-related JCM components and experienced
meaningfulness) was statistically significant, as was Path B (the standardized regression
coefficients between experienced meaningfulness and job satisfaction) and Path C (the
standardized regression coefficients between the three task-related JCM components and
job satisfaction when the mediator was accounted for). Thus, experienced meaningfulness
and the core job dimensions were positively associated with the levels of job satisfaction
among employees. The 95% confidence intervals for each analysis (upper and lower
bounds) did not include zero.
Moreover, the results showed that when the demographics were controlled, the
relationship between the three core job dimensions and turnover intentions were either
partially or fully mediated by experienced meaningfulness. Therefore, the results
provided partial support for H4.
53
Table 4
The Standardized Regression Coefficients for the Relationship between Task-related JCM
Variables and Turnover Intention as Mediated by Experienced Meaningfulness
Path C
Variables Path A Path B β β' 95% CIs
1. Task ID 0.32** 0.39** -0.25** -0.13 [0.37, 0.05]
2. TS 0.49** 0.32** -0.38** -0.23* [0.61, 0.05]
3. SV 0.50** 0.33** -0.38** -0.21* [0.52, 0.02] Note n = 122; ** significant at the 0.01 level; * significant at the 0.05 level; beta weights
for Path C analyses without mediator; β’ = beta weights for Path C analyses with
mediator; Task ID = Task Identity; TS = Task Significance; SV = Skill Variety; 95% CI
= 95% Confidence Intervals (upper and lower bounds).
Table 4 refers to the pathways leading to turnover intentions. Paths A, B, and C
were statistically significant for task significance and skill variety. Thus, experienced
meaningfulness partly explained the relationship between both task significance and skill
variety and turnover intentions. These task-related variables also directly impacted
turnover intentions. The 95% confidence intervals did not include a zero. On the other
hand, experienced meaningfulness fully mediated the relationship between task identity
and turnover intentions because the beta weight for Path C was non-significant after
54
experienced meaningfulness was taken into account. The confidence interval did include
zero.
For H7, the researcher employed the same procedures as H4, but used the social
attributes variables as predictors. The results for H7 showed that when the demographics
were controlled, the relationship between the four social attributes of work and job
satisfaction were all partially mediated by experienced meaningfulness.
Table 5
The Standardized Regression Coefficients for the Relationship between Social Attributes
of Work and Job Satisfaction as Mediated by Experienced Meaningfulness
Path C
Variables Path A Path B β β' 95% CIs
1. MS 0.33** 0.51** 0.50** 0.33** [0.03, 0.06]
2. SS 0.26* 0.51** 0.52** 0.39** [0.38, 0.79]
3. CWS 0.21* 0.58** 0.30** 0.18* [0.06, 0.63]
4. Mentoring 0.46** 0.42** 0.58** 0.39** [0.34, 0.75] Note n = 122; ** significant at the 0.01 level; * significant at the 0.05 level; beta weights
for Path C analyses without mediator; β’ = beta weights for Path C analyses with
mediator; MS = Managerial Support, SS = Supervisor Support, CWS = Co-Worker
Support, 95% CI = 95% Confidence Intervals (upper and lower bounds)
55
As displayed in Table 5, Path A, B, and C were statistically significant. Thus,
experienced meaningfulness partially mediated the relationship between the social
attributes and job satisfaction. The social attributes also directly impacted levels of job
satisfaction among employees. The 95% confidence intervals for each analysis did not
include a zero.
Furthermore, the results revealed that the relationship between the social
attributes and turnover intentions were either partially or fully mediated by experienced
meaningfulness. Thus, the results provided partial support for H7.
Table 6
The Standardized Regression Coefficients for the Relationship between Social Attributes
of Work and Turnover Intention as Mediated by Experienced Meaningfulness
Path C
Variables Path A Path B β β' 95% CIs
1. MS 0.33** 0.29** -0.40** -0.29** [0.08, 0.02]
2. SS 0.26* 0.32** -0.49** -0.41** [1.06, 0.47]
3. CWS 0.21* 0.40** -0.20* -0.12 [0.70, 0.12]
4. Mentoring 0.46** 0.21* -0.53** -0.43* [1.04, 0.45] Note n = 122; ** significant at the 0.01 level; * significant at the 0.05 level; beta weights
for Path C analyses without mediator; β’ = beta weights for Path C analyses with
56
mediator; MS = Managerial Support, SS = Supervisor Support, CWS = Co-Worker
Support, 95% CI = 95% Confidence Intervals (upper and lower bounds)
Table 6 refers to the pathways leading to turnover intentions. Path A, B, and C are
significant at the .01 level for managerial support, supervisor support, and mentoring. As
a result, experienced meaningfulness partially mediated the relationship between those
three social attributes and turnover intention. The 95% confidence intervals for each
analysis did not include a zero. On the other hand, experienced meaningfulness fully
mediated the relationship between co-worker support and turnover intention.
Secondary Analyses
Table 7
Effect Sizes of Key Variables for Job Satisfaction
Variables Constant R R2 Adjusted R2 ∆R2 F
1. Demographics 5.55 (0.68) 0.29 0.09 0.06 0.09* 2.75*
2. Core JCM 0.26 (0.78) 0.70 0.49 0.46 0.41** 15.76**
3. SAOW -0.90 (0.82) 0.78 0.60 0.56 0.12** 15.07**
4. EM -1.26 (0.79) 0.80 0.64 0.60 0.04** 15.98** Note n = 122; ** significant at the 0.01 level; * significant at the 0.05 level; Core JCM =
Core Dimensions of the Job Characteristics Model (Task Identity, Task Significance, and
Skill Variety), SAOW = Social Attributes of Work (Managerial Support, Supervisor
57
Support, Co-Worker Support, and Mentoring), EM = Experienced Meaningfulness of
Work; Constant = b (standard error).
Table 8
Effect Sizes of Key Variables for Turnover Intentions
Variables Constant R R2 Adjusted R2 ∆R2 F
1. Demographics 3.53 (0.84) 0.27 0.07 0.04 0.07 2.34
2. Core JCM 8.13 (1.17) 0.51 0.26 0.22 0.19** 5.80**
3. SAOW 9.21 (1.21) 0.65 0.42 0.37 0.16** 7.33**
4. EM 9.47 (1.22) 0.66 0.43 0.37 0.01 6.97** Note n = 121; ** significant at the 0.01 level; * significant at the 0.05 level; Core JCM =
Core Dimensions of the Job Characteristics Model (Task Identity, Task Significance, and
Skill Variety), SAOW = Social Attributes of Work (Managerial Support, Supervisor
Support, Co-Worker Support, and Mentoring), EM = Experienced Meaningfulness of
Work; Constant = b (standard error).
For the follow-up exploratory analyses, the researcher employed the “enter”
method to control for the demographic variables (gender, age, ethnicity, and tenure) and
core job dimensions (task identity, task significance, and skill variety) to ascertain the
relative contributions of the social attributes of jobs as compared to the task-related
58
aspects of jobs. The results revealed that social attributes of work contributed
significantly to both job satisfaction and turnover intentions above the variance accounted
for by the participants’ demographics and their levels of core job dimensions, p < .01.
The job components of skill variety, tasks identity, and task significance
explained 49% of the variability in job satisfaction, when taking into account
demographics. The social attributes of work added an additional an additional 12%.
Furthermore, the job components of skill variety, tasks identity, and task significance
explained 26% of the variability in turnover intentions, when taking into account
demographics. The social attributes of work added an additional 16%.
59
Chapter 5
DISCUSSION
Oldham and Hackman (2010) called for an expansion of their original enrichment
and motivational Job Characteristics Model. Based on prior research, the current study
focused on the integration of social attributes of work (managerial support, supervisor
support, co-worker support, and mentoring), as well as their influence on employees’
psychological state (experienced meaningfulness of work) and work outcomes (job
satisfaction and turnover intentions). The researcher hypothesized that the social
attributes, as well as the core JCM dimensions related to experienced meaningfulness and
work outcomes. The findings either partially or fully supported the seven hypotheses
outlined by the researcher. Specifically, the findings supported H1, H2, H3, H5, and H6;
therefore, as employees’ level of core dimensions increased, their job satisfaction also
increased, while their turnover intentions decreased. The various sources of social
support and mentoring had the same results.
Furthermore, H4 and H7, which involved the use of experienced meaningfulness
as a mediator for the relationships between the work characteristics (predictors) and work
outcomes (criterions), were partially supported. In particular, the multiple regression
analyses revealed that experienced meaningfulness explained relationships between the
work characteristics and work outcomes, but the predictors continued to exhibit an
influence on the criteria. Thus, both work characteristics and experienced meaningfulness
60
predicted job satisfaction and turnover intentions. However, experienced meaningfulness
fully mediated the relationship between employees’ levels of task identity and turnover
intentions, as well as the relationship between co-worker support and turnover intentions.
Therefore, co-worker support and task identity predicted turnover intentions, and did so
entirely through the development of experienced meaningfulness of work.
These findings demonstrated that, at least in this sample, experienced
meaningfulness fully mediates the relationship between some features of work life (co-
worker support and task identity) and turnover intentions. A possible explanation could
relate to the transitional and temporary natures of many of the positions surveyed (such as
student employees, who most likely did not view their work as a part of their ultimate
career goals). In particular, perhaps without the expectations of a long-term relationship
with the organization, support from co-workers only functions to create experienced
meaningfulness and not impact work outcomes directly. The same explanation may also
apply for task identity – completed tasks, in a somewhat temporary employment
situation, may not improve work outcomes; thus, task identity derives significance
through the vehicle of experienced meaningfulness.
However, a more plausible alternative explanation could be that support from
supervisors had a stronger influence on work outcomes than co-worker support:
supervisor support contributed to positive work outcomes separately and through
experienced meaningfulness. In particular, given the demographics of the sample (age,
tenure, family life), the employees established relationships with their supervisors (who
61
were more likely to remain with the university). As a result, employees relied on their
supervisors for support at work and with work-family balance.
Additionally, in all cases, experienced meaningfulness contributed to job
satisfaction and decreased turnover intentions, similar to previous research (Behson et al.,
2000; Humphrey et al., 2007; Jaramillo et al., 2013; Morgeson & Humphrey, 2006; Ng &
Sorensen, 2008; Rooney et al., 2008; Varga et al, 2012). Thus, experienced
meaningfulness was an important factor in people’s work. Specifically, employees
needed to do something that matters to them, something valuable, in order to garner
positive work outcomes. This was not surprising because the majority of the sample most
likely served the student population at the university. Staff members facilitated the
students’ educational experience through a variety of activities, such as preparing
financial aid documents and advising students’ of how to meet their general education
requirements. These activities could contribute to experienced meaningfulness through
the core job dimensions of task identity, task significance, and skill variety, as well as the
social attributes of the work environment of support from employees’ superiors, co-
workers, and mentors.
An alternative explanation of the results was that there could be multiple
unmeasured factors that influenced key outcome variables, and they may covary with
experienced meaningfulness. For instance, organizational commitment might explain the
relationship between the work characteristics and work outcomes. Within the literature,
researchers found that socially supportive and enriched work environments fostered
62
organizational and affective commitment, which, in turn, led to better work outcomes
based on social exchange theory (Newman, et al., 2012; Rooney et al., 2008; Tang et al.,
2014; Tymon et al., 2011). Therefore, employees felt personally committed to and valued
by the organization when the organization provided them with a socially inclusive and
motivating environment. On a similar note, various sources of social support and mentors
could create other forms of emotional bonds between the employees and their superiors,
as well as the organization, such as trust (Craig et al., 2012; Lankau & Scandura, 2002;
Richard et al., 2008).
There were several limitations that could have influenced the results of the study.
One possible limitation was the decision to test only a portion of the Job Characteristics
Model. Although there was an ample amount of research that supported the relationships
between the CJC, CPS, and work outcomes identified in the hypotheses, perhaps different
psychological states (e.g., experienced work responsibility, etc.) better explained the
relationships between the aspects of work and work outcomes outlined in the JCM.
Another limitation was that the data was cross sectional in nature, which prevented casual
conclusions. However, the theoretical model for the JCM, supported by previous studies,
suggested that the CJC preceded the CPS, which, ultimately, influenced the outcomes.
Moreover, the participants were limited to employees at a northern California college,
which could prevent generalizability due to location and history. For instance, the
majority of the sample, most likely, had day-to-day and personal dealings with the
population of students they provided services for. They may have been, at least
63
somewhat, aware of their impact on the students, alerting them to the meaning of
measures such as task identity and task significance.
For future studies, researchers should address these limitations. They should also
investigate the potential benefits of social support and mentoring beyond those found and
discussed in the current study, in addition to the proposed utility and addition of
organizational/affective commitment. Researchers found that social support in a variety
of forms has benefits related to and beyond the job, such as decreased burnout, somatic
complaints, family conflict, and depression (Bennett et al, 2001; Kitaoka-Higashiguchi et
al., 2003; Ng & Sorensen, 2008; Pomaki & Anagnostopoulou, 2003; Seiger & Wiese,
2009; Ter Doest & de Jonge, 2006). Chen et al. (2013) also found that mentoring
increased the perception of psychological safety among employees in terms of their
ability to freely share their opinions.
There are several practical implications for the findings of the present study. The
results suggested that due to the positive work outcomes associated with task identity,
task significance, and skill variety, employees valued these work characteristics.
Therefore, organizations should provide opportunities for training with regard to these
core job dimensions. Greater awareness of the meaning of their tasks is likely to relate to
increased positive work outcomes. Prior research also recommended the incorporation of
a mentoring program to foster supportive work environments and mutually beneficial
relationships, which positively influence job attitudes and work outcomes (such as
organizational commitment, job satisfaction, performance, turnover intentions, and actual
64
turnover). Any form of mentoring (direct, indirect, formal, or informal) could have a
profound impact on employees (Bedini & Anderson, 2003; Dawley et al., 2010; Egan &
Song, 2007; Emmerik, 2003; Lo & Ramayah, 2011; Prevosto, 2001; Bozionelos, 2009).
In addition, mentors with similar backgrounds (ethnicity, gender, sexual
orientation, etc.) to their mentees are preferable, as well as those close in proximity
(direct supervisors and/or senior colleagues with knowledge of the employee’s
performance, needs, and goals) are preferable. However, any exposure to mentoring was
better than none (Brashear et al., 2006; Hebl et al., 2012; Hoigaard & Mathisen, 2009;
Kammeyer-Mueller & Judge, 2008; Lo et al., 2011; Raabe & Beehr, 2003).
This study further illustrates the importance of mentoring in creating positive
work outcomes, as well as demonstrates that it operates by generating a sense of
meaningfulness at work. Moreover, this study underscores the importance of supportive
workplaces, in general. Organizations can utilize the support from co-workers,
supervisors, and managers to promote a work-family balanced climate. As with
mentoring, these variables operate in a way that they create a sense of meaningfulness for
employees, which, in turn, can lead to positive work outcomes.
Specifically, supervisors and management help shape work culture. They must
take active steps to promote a sympathetic social climate for working parents. For
instance, to promote a work environment conducive to work-family balance,
organizations can design policies that allow for maternity and paternity leave, as well as a
process to re-integrate the employee once he or she returns, for a seamless transition.
65
Moreover, interventions that help shape work culture, focused on developing emotional
intelligence, coping strategies, as well as training in stress management for both
employers and employees could act as representations of social support. This could lead
to reductions of conflict between the employee’s work and family lives. In this case, the
supervisor or manager acts as a buffer for the employee.
Other, more cost effective, strategies center on reducing the job demands (or
perceptions of demand) include finding solutions to alleviate time pressures attached to
tasks and providing positive feedback and compliments when warranted. In addition,
social gatherings sponsored by the organization, such as annual company picnics, provide
numerous opportunities for management and employees (with their families) to develop
amicable relationships and foster social support. Consequently, co-workers and superiors
may function and provide the same support that friends or family give.
Researchers should take these considerations into account and continue to
investigate the influence of the social attributes of the work environment, as well as the
JCM in job design for various industries. Managers and human resource agents can also
use the results from this study to better inform policies within organizations. Specifically,
these results support the allocation of resources to foster socially supportive and enriched
work environments where employees have both increased control over the various
aspects of their job and opportunities to develop positive interpersonal relationships. This
is a reasonable and useful strategy for creating positive outcomes for the employee and
66
the organization. Organizations are likely to see improved levels of job satisfaction and
decreased levels of turnover intention.
Likewise, new workforce entrants and recent work trends suggested that
employees expect a supportive work environment where they feel comfortable sharing
their ideas and feel valued (Bhatnagar, 2014; Brough & Frame, 2004; DeConinck &
Johnson, 2009; Dysvik & Kuvaas, 2013; Gillet et al., 2013; Kim, 2014; Van der Heijden
et al, 2010). If management subscribes to the notion that work happens in a social
vacuum then they must undertake the potential risks and expenses associated with poorer
psycho-social health and potential turnover. However, if they give employees what they
expect and need, organizations are likely to reap many benefits.
67
APPENDIX A
Consent Form (Email Greeting)
You are invited to participate in a survey about your work life, being conducted by a faculty member in the Psychology Department at [a large metropolitan university] and her team of research assistants. We are conducting the research as a way of better understanding people’s needs and the conditions of their work lives. If you choose to participate, you are asked to complete an online survey which will take approximately 10 – 15 minutes of your time. At the end of the survey, you will have the option of entering your name and e-mail address into a lottery for a $30 gift card from the university bookstore. This lottery is not connected to the survey and your individual responses. There are no known risks associated with completing this study. There are many potential benefits, such as researchers better understanding what men and women, uniquely, desire in the workplace and being able to develop better interventions to improve work lives. Your participation in this study is entirely voluntary and you may withdraw from the study at any time. Your email address was obtained via the online university directory. Your responses will be kept confidential to the degree permitted by the technology used. However, no absolute guarantees can be given for the confidentiality of electronic data. Your responses will never be directly associated with your email. For the survey, we do not collect identifying information such as your name, email address, or IP address. Though the Human Resources Department is aware this project is being conducted, they will not have access to the data in either raw or aggregate form. The results of this study will be used for scholarly purposes only. If you have any questions about this research, please feel free to contact the faculty member. Thank you for your time. We look forward to your responses. By clicking on the “Agree” button below, you indicate that you have read the above information and that you voluntarily agree to participate. You will be automatically directed to the survey. If you do not wish to participate, please decline participation by clicking on the “Disagree” button.
o Agree – Electronic consent to participate o Disagree
68
APPENDIX B
Demographic Information Questionnaire
1. Which of the following would you say best describes you and your career (please check one): o I am in the early stages of my career o I am in the middle stages of my career o I am in the later stages of my career
2. What is your age? _________ (drop down menu with all ages possible)
3. Please fill in your gender: O Female O Male
4. What is your ethnicity? o Asian o Black/African American o Hispanic o Native American (American Indian, Alaskan) o Pacific Islander o White/Caucasian o Other ___________ (please describe)
5. Please fill in your current marital status: o Divorced o Living with a partner o Married o Separated o Single o Widowed
6. Are you currently raising children? O Yes O No If yes, what ages are your children currently? _____, _______, _______, _______
7. Have you ever raised children? O Yes O No
8. Are you currently caring for a family member who is not a child? O Yes O No
9. If yes, please provide who (e.g. a parent, a sibling, aunt/uncle, etc.) ____________________
69
10. Please fill in your estimated annual household income: o $0 - $20,000 o $21,000 - $40,000 o $41,000 - $60,000 o $61,000 - $80,000 o $81,000 - $100,000 o $101,000 +
11. How long have you worked at this University? _____________
12. What is the number of years you have worked over the course of your lifetime? ____________
13. Which of the following best describes your role in the workplace? o Upper management o Middle management o Junior management o Administrative staff o Support staff o Student o Trained professional o Skilled laborer o Consultant o Temporary employee o Researcher o Self-employed o Other: _________________________
70
APPENDIX C
Social Attributes of Work Inventories
Managerial Support of Organizational Work-Family Culture (Thompson, Beauvais, & Lyness, 1999) Participants responded on the following rating scale to the statements:
1= disagree strongly 2 = disagree 3 = disagree slightly 4 = neutral 5 = agree slightly 6 = agree 7 = agree strongly
1. In general, managers in this organization are quite accommodating of family-
related needs. 2. Higher management in this organization encourages supervisors to be sensitive to
employees’ family and personal concerns. 3. Middle managers and executives in this organization are sympathetic toward
employees’ child care responsibilities. 4. In the event of a conflict, managers are understanding when employees have to
put their family first. 5. In this organization employees are encouraged to strike a balance between their
work and family lives. 6. Middle managers and executives in this organization are sympathetic toward
employees’ elder care responsibilities. 7. This organization is supportive of employees who want to switch to less
demanding jobs for family reasons. 8. In this organization it is generally okay to talk about one’s family at work. 9. In this organization employees can easily balance their work and family lives. 10. This organization encourages employees to set limits on where work stops and
home life begins. 11. In this organization it is very hard to leave during the workday to take care of
personal or family matters (reverse)
Social Support from Supervisor (Caplan, Cobb, French, Harrison, & Pinneau, 1975) Participants responded on the following rating scale to the statements:
0 = don’t have such a person 1 = not at all
71
2 = a little 3 = somewhat 4 = very much
1. How much does your immediate supervisor go out of their way to do things to make your work life easier for you?
2. How easy it is to talk with your immediate supervisor? 3. How much can you rely on your immediate supervisor when things get tough at
work? 4. How much is your immediate supervisor willing to listen to your personal
problems? Social Support from Coworkers (Caplan, Cobb, French, Harrison, & Pinneau, 1975) Participants responded on the following rating scale to the statements:
0 = don’t have such a person 1 = not at all 2 = a little 3 = somewhat 4 = very much
1. How much do other people at work go out of their way to do things to make your
work life easier for you? 2. How easy it is to talk with other people at work? 3. How much can you rely on other people at work when things get tough at work? 4. How much are other people at work willing to listen to your personal problems?
Mentoring (Dreher & Ash, 1990) Participants responded on the following rating scale to the statements:
1 = not at all 2 = to a small extent 3 = to some extent 4 = to a large extent 5 = to a very large extent
Consider your career history since you began working in your current position, and the degree to which influential managers have served as your formal or informal sponsor or mentor (this need not be limited to one person). To what extent has a mentor…
1. Given or recommended you for challenging assignments that present opportunities to learn new skills?
72
2. Given or recommended you for assignments that required personal contact with managers in different parts of the company?
3. Given or recommended you for assignments that increased your contact with higher level managers?
4. Given or recommended you for assignments that helped you meet new colleagues?
5. Helped you finish assignments/tasks or meet deadlines that otherwise would have been difficult to complete?
6. Protected you from working with other managers or work units before you knew about their likes/dislikes, opinions on controversial topics, and the nature of the political environment?
7. Gone out of his/her way to promote your career interests? 8. Kept you informed about what is going on at higher levels in the company or how
external conditions are influencing the company? 9. Conveyed feelings of respect for you as an individual? 10. Conveyed empathy for the concerns and feelings you have discussed with
him/her? 11. Encouraged you to talk openly about anxiety and fears that detract from your
work? 12. Shared personal experiences as an alternative perspective to your problems? 13. Discussed your questions or concerns regarding feelings of competence,
commitment to advancement, relationships with peers and supervisors or work/family conflicts?
14. Shared history of his/her career with you? 15. Encouraged you to prepare for advancement? 16. Encouraged you to try new ways of behaving on the job? 17. Served as a role model? 18. Displayed attitudes and values similar to your own?
73
APPENDIX D
JCM Experienced Meaningfulness Inventory Experienced Meaningfulness (Hackman & Oldham, 1980): Participants responded on the following rating scale to the statements:
1= disagree strongly 2 = disagree 3 = disagree slightly 4 = neutral 5 = agree slightly 6 = agree 7 = agree strongly
1. The work I do on this job is very meaningful to me. 2. Most of the things I have to do on this job seem useless or trivial. 3. Most people on this job find the work very meaningful. 4. Most people on this job feel that the work is useless or trivial.
74
APPENDIX E
JCM Core Dimensions Questionnaire
Task Identity (Hackman & Oldham, 1980) On question #1, participants respond on the following rating scale:
1 = My job is only a time part of the overall piece of work; the results of my activities cannot be seen in the final product or service. 4 = My job is a moderate-sized “chunk” of the overall piece of work; my own contributions can be seen in the final outcome. 7 = My job involves doing the whole piece of work, from start to finish; the results of my activities are easily seen in the final product or service.
On questions #2 and #3, participants respond on the following rating scale:
1 = Very inaccurate 2 = Mostly inaccurate 3 = Slightly inaccurate 4 = Uncertain 5 = Slightly accurate 6 = Mostly accurate 7 = Very accurate
1. To what extent does your job involve doing a whole and identifiable piece of
work? That is, is the job a complete piece of work that has an obvious beginning and end?
2. The job is arranged so that I do not have the chance to do an entire piece of work from beginning to end.
3. The job provides me the chance to completely finish the pieces of work I begin. Task Significance (Hackman & Oldham, 1980) On question #1, participants respond on the following rating scale:
1= Not very significant; the outcomes of my work are not likely to have important effects on other people. 4 = Moderately significant 7 = Highly significant; the outcomes of my work can affect other people in very important ways.
On questions #2 and #3, participants respond on the following rating scale: 1 = Very inaccurate 2 = Mostly inaccurate
75
3 = Slightly inaccurate 4 = Uncertain 5 = Slightly accurate 6 = Mostly accurate 7 = Very accurate
1. In general, how significant or important is your job? That is, are the results of
your work likely to significantly affect the lives or well-being of other people? 2. This job is one where a lot of other people can be affected by how well the work
gets done. 3. The job itself is not very significant or important in the broader scheme of things.
Skill Variety (Hackman & Oldham, 1980) On question #1, participants respond on the following rating scale:
1 = Very little; the job requires me to do the same routine things over and over again. 4 = Moderate variety 7 = Very much; the job requires me to do many different things, using a number of different skills and talents
On questions #2 and #3, participants respond on the following rating scale: 1 = Very inaccurate 2 = Mostly inaccurate 3 = Slightly inaccurate 4 = Uncertain 5 = Slightly accurate 6 = Mostly accurate 7 = Very accurate
1. How much variety is there in your job? That is, to what extent does the job
require you to do many different things at work, using a variety of skills and talents?
2. The job requires me to use a number of complex or high-level skills. 3. The job is quite simple and repetitive.
76
APPENDIX F
Work Outcome Inventories
Participants responded on the following rating scale to the statements: 1= disagree strongly 2 = disagree 3 = disagree slightly 4 = neutral 5 = agree slightly 6 = agree 7 = agree strongly
Job Satisfaction (Judge et al. 2000):
1. I feel fairly satisfied with my present job. 2. Most days I am enthusiastic about my work 3. Each day at work seems like it will never end. 4. I find real enjoyment in my work. 5. I consider my job to be rather unpleasant.
Turnover Intentions (Adams & Beehr, 1998):
1. I am planning to leave my job for another in the near future. 2. I often think of quitting this job and finding another. 3. I would like to quit this job and find another in the near future.
77
References
Adams, G.A. & Beehr, T.A. (1998). Turnover and retirement: A comparison of their
similarities and differences. Personnel Psychology, 51(3), 643 – 665.
Allen, T.D., Smith, M.A., Mael, F.A., O’Shea, P.G., & Eby, L.T. (2009). Organization-
level mentoring and organizational performance within substance abuse centers.
Journal of Management, 35(5), 1113 – 1128. doi: 10.1177/0149206308329969
Abualrub, R.F., Omari, F.H., & Abu Al Rub, A.F. (2009). The moderating effect of social
support on the stress–satisfaction relationship among Jordanian hospital nurses.
Journal of Nursing Management, 17, 870–878. doi: 10.1111/j.1365-
2834.2009.01007.x
Baranik, L. E., Roling, E.A., & Eby, L.T. (2010). Why does mentoring work? The role of
perceived organizational support. Journal of Vocational Behavior, 76, 366 – 373.
doi: 10.1016/j.jvb.2009.07.004
Baron, R.M. & Kenny, D.A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic, and statistical considerations.
Journal of Personality and Social Psychology, 51(6), 1173 – 1182.
Bedini, L.A. & Anderson, D.M. (2003). The benefits of formal mentoring for
practitioners in therapeutic recreation. Therapeutic Recreation Journal, 37(3), 240
– 255.
78
Behson, S.J., Eddy, E.R., & Lorenzet, S.J. (2000). The importance of the critical
psychological states in the job characteristics model: A meta-analytic and
structural equations modeling examination. Current Research in Social
Psychology, 5(12), 171 – 189.
Bennett, P., Lowe, R., Matthews, V., Dourali, M., & Tattersall, A. (2001). Stress in
nurses: Copping, managerial support and work demand. Stress and Health 17, 55
– 63.
Bhatnagar, J. (2014). Mediator analysis in the management of innovation in Indian
knowledge workers: The role of perceived supervisor support, psychological
contract, reward and recognition and turnover intention. International Journal of
human Resource Management, 25(10), 1395 – 1416. doi:
10.1080/09585192.2013.870312
Bozionelos, N. (2009). Expatriation outside the boundaries of the multinational
corporation: A study with expatriate nurses in Saudi Arabia. Human Resource
Management, 48(1), 111 – 134. doi: 10.1002/hrm.20269
Brashear, T.G., Bellenger, D.N., Boles, J.S., & Barksdale Jr., H.C. (2006). An
exploratory study of the relative effectiveness of different types of sales-force
mentors. Journal of Personal Selling and Sales Management, 26(1), 7 – 18.
Brough, P. & Frame, R. (2001). Predicting police job satisfaction and turnover
intentions: The role of social support and police organizational variables. New
Zealand Journal of Psychology, 33(1), 8 – 16.
79
Caplan, R. D., Cobb, S., French, Jr., J. R. P, Van Harrison, R. & Pinneau, Jr., S. R.
(1975). Job demands and worker health. Ann Arbor, MI: University of
Michigan Institute for Social Research NIOSH
Champoux, J.E. (1991). A multivariate test of the job characteristics theory of work
motivation: Summary. Journal of Organizational Behavior, 12(5), 431 – 446.
Chen, C., Liao, J., & Wen, P. (2013). Why does formal mentoring matter? The mediating
role of psychological safety and the moderating role of power distance orientation
in the Chinese context. The International Journal of Human Resource
Management, 25(8), 1112 – 1130. doi: 10.1080/09585192.2013.816861
Craig, C.A., Allen, M.W., Reid, M.F., Riemenschneider, C.K., & Armstrong, D.J. (2012).
The impact of career mentoring and psychosocial mentoring on affective
organizational commitment, job involvement, and turnover intention.
Administration and Society, 45(8), 949 – 973. doi: 10.1177/0095399712451885
Dawley, D.D, Andrews, M.C., & Bucklew, N.S. (2010). Enhancing the ties that bind:
mentoring as a moderator. Career Development International, 15(3), 259 – 278.
doi: 10.1108/13620431011053730
Debnath, S.C., Tandon, S., & Pointer, L.V. (2007). Designing business school courses to
promote student motivation: An application of the Job Characteristics Model.
Journal of Management Education, 31(6), 812 – 831. doi:
10.1177/1052562906290914
80
DeConinck, J.B. & Johnson, J.T. (2009). The effects of perceived supervisor support,
perceived organizational support, and organizational justice on turnover among
salespeople. Journal of Personal Selling and Sales Management, 29(4), 333 –
350. doi: 10.2753/PSS0885-3134290403
De Cuyper, N., Mauno, S., Kinnunen, U., & Makikangas, A. (2010). The role of job
resources in the relation between perceived employability and turnover intention:
A prospective two-sample study. Journal of Vocational Behavior, 78, 253 – 263.
doi: 10.1016/j.jvb.2010.09.008
DeVaro, J., Li, R., & Brookshire, D. (2007). Analysing the job characteristics model:
New support from a cross-section of establishments. International Journal of
Human Resource Management, 18(6), 986 – 1003. doi:
10.1080/09585190701321211
Dreher, G.F. & Ash, R.A. (1990). A comparative study of mentoring among men and
women in managerial, professional, and technical positions. Journal of Applied
Psychology, 75(5), 539-546. doi: 10.1037/0021-9010.75.5.539
Dysvik, A. & Kuvaas, B. (2013). Perceived job autonomy and turnover intention: the
moderating role of perceived supervisor support. European Jounal of Work and
Organizational Psychology, 22(5), 563 – 573. doi:
10.1080/1359432X.2012.667215
81
Egan, T.M. & Song, Z. (2008). Are facilitated mentoring programs beneficial? A
randomized experimental field study. Journal of Vocational Behavior, 72(3), 351
– 362. doi: 10.1016/j.jvb.2007.10.009
Fried, Y. & Ferris, G.R. (1987). The validity of the job characteristics model: A review
and meta-analysis. Personnel Psychology, 40, 287 – 322.
Galletta, M. Portoghese, I., Pietronilla Penna, M., Battistelli, A., & Saiani, L. (2011).
Turnover intention among Italian nurses: The moderating roles of supervisor
support and organizational support. Nursing and Health Sciences, 13, 184 –
191.doi: 10.1111/j.1442-2018.2011.00596.x
Gillet, N., Gagne, M., Sauvagere, S., & Fouquereau, E. (2013). The role of supervisor
autonomy support, organizational support, and autonomous and controlled
motivation in predicting employees’ satisfaction and turnover intentions.
European Journal of Work and Organizational Psychology, 22(4), 450 – 460. doi:
10.1080/1359432X.2012.665228
Hackman, J.R. & Oldham, G.R. (1974). The Job Diagnostic Survey: An instrument for
the diagnosis of jobs and evaluation of the job redesign process (No. 4 AD – 779
828). Arlington, VA: National Technical Information Service: U.S. Department of
Commerce.
Hackman, J.R. & Oldham, G.R. (1980). Work redesign. Reading, MA: Addison-Wesley
Publishing Company.
82
Harris, J.I., Winskowski, A.M., & Engdahl, B.E. (2007). Types of workplace social
support in the prediction of job satisfaction. Career Development Quarterly, 56,
150 – 156.
Head, T.C. & Sorensen Jr., P.F. (1985). A multiple site comparison of job redesign
projects: Implications for consultants. Organization Development Journal, 3(3),
37 – 44.
Hebl, M.R., Tonidandel, S., & Ruggs, E.N. (2012). The impact of like-mentors for
gay/lesbian employees. Human Performance, 25, 52 – 71. doi:
10.1080/08959285.2011.631645
Hoigaard, R. & Mathisen, P. (2009). Benefits of formal mentoring for female leaders
International Journal of Evidence Based Coaching and Mentoring, 7(2), 64 – 70.
Humphrey, S.E., Nahrgang, J.D., & Morgeson, F.P. (2007). Integrating motivational,
social, and contextual work design features: A meta-analytic summary and
theoretical extension of the work design literature. Journal of Applied Psychology,
92(5), 1332–1356. doi: 10.1037/0021-9010.92.5.1332
Inayatullah, S. (2006). Eliminating future shock: The changing world of work and the
organization. Foresight, 8(5), 3-14. doi: 10.1108/14636680610703054
Izawa, M.R., French, M.D., Hedge, A. (2011). Shining new light on
the Hawthorne Illumination Experiments. Human Factors, 53(5), 528-547.
doi:10.1177/0018720811417968
83
Jaramillo, F., Mulki, J.P., & Boles, J.S. (2013). Bringing meaning to the sales job: The
effect of ethical climate and customer demandingness. Journal of Business
Research, 66, 2301–2307. doi:10.1016/j.jbusres.2012.03.013
Judge, T.A., Bono, J.E., & Locke, E.A. (2000). Personality and job satisfaction: The
mediating role of job characteristics. Journal of Applied Psychology, 85(2), 237 –
249. doi: 10.1037//0021-9010.85.2.237
Kahn, H. & Robertson, I.T. (1992). Training and experience as predictors of job
satisfaction and work motivation when using computers: A correlational study.
Behavior and Information Technology, 11(1), 53 – 60.
Kammeyer-Mueller, J.D. & Judge, T.A. (2008). A quantitative review of mentoring
research: Test of a model. Journal of Vocational Behavior, 72, 269–283. doi:
10.1016/j.jvb.2007.09.006
Khandelwal, P. & Aleem, S. (1990). A study of factor structure of the job characteristics
model. Psychological Studies, 35(2), 124 – 128.
Kitaoka-Higashiguchi, K., Nakagawa, H., Morikawa, Y., Ishizaki, M., Miura, K., Naruse,
Y., Kido, T., & Sukigara, M. (2003). Social support and individual styles of
coping in the Japanese workplace: an occupational stress model by structural
equation analysis. Stress and Health, 19, 37 – 43. doi: 10.1002/smi.953
Kim, N. (2014). Employee turnover intention among newcomers in travel industry.
International Journal of Tourism Research, 16, 56 – 64. doi: 10.1002/jtr.1898
84
King, L.A. (2013). The science of psychology (3rd edition). McGraw-Hill Higher
Education: Boston, MA.
Ko, J., Hur, S., & Smith-Walter, A. (2013). Family-friendly work practices and job
satisfaction and organizational performance: Moderating effects of managerial
support and performance-oriented management. Public Personnel Management,
42(4), 545 – 565. doi: 10.1177/0091026013505503
Landry, B.J.L., Mahesh, S., & Hartman, S. (2005). The changing nature of work in the
age of e-business. Journal of Organizational Change Management, 18(2), 132-
144. doi: 10.1108/09534810510589561
Lankau, M.J. & Scandura, T.A. (2002). An investigation of personal learning in
mentoring relationships: Content, antecedents, and consequences. Academy of
Management Journal, 45(4), 779 – 790.
Leonard, H.S. & Freedman, A. M. (2000). From scientific management through fun and
games to high-performing teams: A historical perspective on consulting to team-
based organizations. Consulting Psychology Journal: Practice and Research,
52(1), 3-19. doi: 10.1037//1061-4087.52.1.3
Lo, M.C. & Ramayah, T. (2011). Mentoring and job satisfaction in Malaysian SMEs.
Journal of Management Development, 30(4), 427 – 440. doi:
10.1108/02621711111126891
85
Lo, M.C. & Kui. (2011). Mentoring and job satisfaction in Malaysia: A test on small
medium enterprises in Malaysia. International Journal of Psychology: A Bio-
psychosocial Approach, (13), 69 – 90. doi: 10.7220/1941-7233.13.4
Morgeson, F.P & Humphrey, S.E. (2006). The work design questionnaire (WDQ):
Developing and validating a comprehensive measure for assessing job design and
the nature of work. Journal of Applied Psychology, 91(6), 1321–1339. doi:
10.1037/0021-9010.91.6.1321
Millette, V. & Gagn, M. (2008). Designing volunteers’ tasks to maximize motivation,
satisfaction and performance: The impact of job characteristics on volunteer
engagement. Motivation and Emotion, 32, 11–22. doi: 10.1007/s11031-007-9079-
4
Newman, A., Thanacoody, R., & Hui, W. (2012). The effects of perceived organizational
support, perceived supervisor support and intra-organizational network resources
on turnover intentions: A study of Chinese employees in multinational
enterprises. Personnel Review, 41(1), 56 – 72. doi: 10.1108/00483481211189947
Ng, T.W.H. & Sorensen, K.L. (2008). Toward a further understanding of the
relationships between perceptions of support and work attitudes: A meta-analysis.
Group & Organization Management, 33(3), 243 – 268. doi:
10.1177/1059601107313307
86
Oldham, G.R. & Hackman, J.R. (2010). Not what it was and not what it will be: The
future of job design research. Journal of Organizational Behavior, 31, 463–479.
doi: 10.1002/job.678
Parmar, N.R. (2001). Job anxiety as a moderator variable in the relationship between job
characteristics and individual, as well as organizational outcomes. Journal of the
Indian Academy of Applied Psychology, 27(1 – 2), 75 – 81.
Piccolo, R.F., Greenbaum, R., Den Hartog, D.N., & Folger, R. (2010). The relationship
between ethical leadership and core job characteristics. Journal of Organizational
Behavior, 31, 259 –278. doi: 10.1002/job.627
Pomaki, G. & Anagnostopoulou, T. (2003). A test and extension of the demand/ control/
social support model: Prediction of wellness/ health outcomes in Greek teachers.
Psychology and Health, 18(4), 537 – 550. doi: 10.1080/0887044031000147256
Prevosto, P. (2001). The effect of "mentored" relationships on satisfaction and intent to
stay of company-grade U.S. Army Reserve nurses. Military Medicine, 166(1), 21
– 26.
Raabe, B. & Beehr, T.A. (2003). Formal mentoring versus supervisor and coworker
relationships: Differences in perceptions and impact. Journal of Organizational
Behavior, 24(3), 271 – 293. doi: 10.1002/job.193
87
Richard, O.C., Ismail, K.M, Bhuian, S.N, & Taylor E.C. (2009). Mentoring in
supervisor–subordinate dyads: Antecedents, consequences, and test of a mediation
model of mentorship. Journal of Business Research, 62(11), 1110 – 1118. doi:
10.1016/j.jbusres.2008.09.007
Rooney, J.A., Gottlieb, B.H., & Newby-Clark, I.R. (2009). How support-related
managerial behaviors influence employees: An integrated model. Journal of
Managerial Psychology, 24(5), 410-427. doi: 10.1108/02683940910959744
Seiger, C.P. & Wiese, B.S. (2009). Social support from work and family domains as an
antecedent or moderator of work-family conflicts?. Journal of Vocational
Behavior, 75(1), 26 – 37. doi: 10.1016/j.jvb.2009.03.001
Strubler, D.C. & York, K.M. (2007). An exploratory study of the team characteristics
model using organizational teams. Small Group Research, 38(6), 670 – 695. doi:
10.1177/1046496407304338
Suman, S. & Srivastava, A.K. (2009). The measurement of job characteristics in context
to Indian work scenario. Journal of Indian Academy of Applied Psychology,
35(Special Issue), 142 – 147.
Sawang, S. (2010). Moderation or mediation? An examination of the role perceived
managerial support has on job satisfaction and psychological strain. Current
Psychology, 29, 247 –256. doi: 10.1007/s12144-010-9083-9
88
Tang, S., Siu, O., & Cheung, F. (2014). A study of work–family enrichment among
Chinese employees: The mediating role between work support and job
satisfaction. Applied Psychology: An International Review, 63(1), 130 –150. doi:
10.1111/j.1464-0597.2012.00519.x
Te Boekhorst, S., Willemse,B., Depla, M.F.I.A., Eefsting, J.A. & Pot, A.M. (2008).
Working in group living homes for older people with dementia: the effects on job
satisfaction and burnout and the role of job characteristics. International
Psychogeriatrics, 20(5), 927–940. doi:10.1017/S1041610208007291
Ter Doest, L. & de Jonge, J. (2006). Testing causal models of job characteristics and
employee well-being: A replication study using cross-lagged structural equation
modelling. Journal of Occupational and Organizational Psychology, 79, 499–
507. doi:10.1348/096317905X55271
Thompson, C.A., Beauvais, L.L., & Lyness, K.S. (1999). When work–family benefits are
not enough: The influence of work–family culture on benefit utilization,
organizational attachment, and work–family conflict. Journal of Vocational
Behavior, 54(3), 392-415. doi: 10.1006/jvbe.1998.1681
Treiber, L.A. & Davis, S.N. (2012). The role of ‘workplace family’ support on worker
health, exhaustion and pain. Community, Work and Family, 15(1), 1 – 27. doi:
10.1080/13668803.2011.580123
89
Tymon, W.G., Stumpf, S.A., & Smith, R.R. (2011). Manager support predicts turnover of
professionals in India. Career Development International, 16(3), 293 – 312. doi:
10.1108/13620431111140174
Van Emmerik, H. (2003). For better and for worse: Adverse working conditions and the
beneficial effects of mentoring. Career Development International, 9(4), 358 –
373. doi: 10.1108/13620410526157
Van der Heijden, B.I.J.M., Kummerling, A.K., Van Dam, K., Van der Schoot, E., Estryn-
Be´har, M., & Hasselhorn, H.M. (2010). The impact of social support upon
intention to leave among female nurses in Europe: Secondary analysis of data
from the NEXT survey. International Journal of Nursing Studies, 47, 434 – 445.
doi: 10.1016/j.ijnurstu.2009.10.004
Varga, K., Tóth, A., Roznár, J., Oláh, A., Betlehem, J., & Jeges, S. (2012). Is
“meaningfulness” a general mediating factor: The salutogenic revolution of
question-setting in health science and occupational psychology. European
Journal of Mental Health, 7, 72–89. doi: 10.5708/EJMH.7.2012.1.4