1. Central Michigan University
Master of Science in Administration (MSA) Program
Course Title: MSA 699
Submitted to: Dr. Shaikh
Submitted by: Jason Leiter
5110 N. Wolcott Ave
Chicago, IL 60626
Home/Cell Phone: 989-412-3994
Email: leite1j@cmich.edu
Course Location: MSA699 Online
Submission Date: January, 28, 2014
Research Project Title:
Performance Motivation in Young Workers: A Comparison of Two Types of Policy
CERTIFICATE OF AUTHORSHIP:
I certify that I am the author of this paper and that any assistance I receive in its preparation is fully
acknowledged and disclosed in this paper. I have also cited any sources from which I used data, ideas, or
works, either quoted directly or paraphrased. I also certify that this paper was prepared by me specifically
for this course.
Student’s E-Signature: Jason Leiter
Instructor’s Comments:

2. MOTIVATION POLICY LEITER iii
Performance Motivation in Young Workers: A Comparison of the Effectiveness of Two Types
of Policy
MSA 699: Applied Research Project in Administration
Submitted by:
Jason Leiter
Project Instructor:
Dr. Shaikh
January 28, 2014

3. MOTIVATION POLICY LEITER iii
Executive Summary
Managers are consistently looking for ways to improve worker productivity. One of the ways of
doing this is by having a highly motivated workforce. The most common method is by
employing a pay for performance (PFP) system of motivation. While this seems logical, these
types of policies do not always work as intended. There are other alternative methods that can be
used including an employee involvement in organizational leadership (EIOL) method. Due to
younger workers preferences for social connectedness, this could be a worthwhile choice.
Additionally, there are cases where employees are not fully aware of the details of the motivation
policy. Uncertainty can cause frustration and decrease motivation.
This study investigates into the relationship between type of motivational policy, level of
information and worker motivation in 18-25 year olds. An experimental study was conducted
for this purpose. Participants' Results showed that there is a significant difference in motivation
level between workers who were given a hypothetical PFP policy versus those given an EIOL
policy with EIOL policies being favored, in particular by female participants. The results also
showed that the level of information given can have a significant effect on the motivation level
generated by PFP policies. The results of this study lead to recommendations of implementing
EIOL motivational policies over ones based upon PFP, in particular in organizations employing
young women. It is also recommended to keep employees well informed of the details of the
policy to avoid uncertainty and frustration.

4. MOTIVATION POLICY LEITER iv
Table of Contents
Page Number
Executive Summary iii
Chapter 1 Problem Definition 1
Chapter 2 Literature Review 7
Chapter 3 Research Methodology 21
Chapter 4 Data Analysis 25
Chapter 5 Summary, Conclusions, and Recommendations 26
References Pages 31-33
Appendix A Permission to Conduct Study
Appendix B Background Questionnaire
Appendix C Potential Policy Examples and Manipulation Check Questions.
Appendix D Shouksmith (1989) Work Motivation Scale
iii

5. MOTIVATION POLICY LEITER
Chapter 1
Problem Definition
Administrative Problem
Background
In a modern organization there are many challenges faced by management. Among the
more important of these is the task of fostering their employees' motivation to improve their
performance on the job. (Ryan & Deci, 2000; Chen, Sharma, Edinger, Shapiro, & Farh, 2011;
Joseph, Emmett, & Louw-Potgieter, 2012; Wong, Gardiner, Lang, & Coulon, 2008; Montana &
Petit, 2008). Motivation, in this context, refers to being moved to do something (Ryan & Deci,
2000), it has also been defined using more specific language as getting people to perform their
best work, despite difficult or demanding circumstances (Nohria, Groysberg, & Lee, 2008).
These both imply generating an emotional reaction within the individual worker that makes them
want to improve their job performance. Motivated employees have been shown to have
increased job performance (Springer, 2011; George & Brief, 1996) as well as being more likely
to share information with each other (Lam & Lambermont-Ford, 2010) leading to the
development of a learning organization.
The catalyst for this emotional response, also known as a motivator or a motivational
lever, can be many different things, depending on the worker in question (Chen, et. al., 2011;
Wegge, Jeppson, Weber, Pearce, Silva, Pundt, Jonsson, Wolf, Wassenaar, Unterrainer, & Piecha,
2010; Montana & Petit, 2008). As new graduates enter the workplace, learning what can be used
to motivate younger workers becomes an important goal for a manager. The community of
1

6. 2
researchers has not overlooked the importance of a person's age or generation on their
motivational levers as this topic has been the subject of much study (Chen, et. al., 2011; Wong
et. al., 2008; Montana & Petit, 2008). Significant differences in motivators between age groups
have been seen in these studies. A person's emotional state, gender (Shekhar & Devi, 2012), as
well as cultural differences between workers in China compared to the United States has also
been studied in terms of motivation techniques, again showing some differences (Sakurai & Jex,
2012; Chen, et. al 2011). These studies will be examined in greater detail in chapter 2. These
types of studies show that a one-size-fits-all method for supervisors to use in order to foster
employee motivation may not be the best solution for an organization. Management is then left
with the dilemma of how to tune their motivation techniques to the employees that they have
available to them at a given point in time.

7. 3
Many different models for motivating employees have been proposed over the years,
many of which have had some measure of success. Among the most popular of these are
monetary compensation based upon the level of performance, or a pay-for-performance (PFP)
system. This seems to be the most logical solution on the surface due to the fact that the most
common reason that an individual will seek employment in the first place is for reasons of
monetary compensation. This type of system might include a bonus payout for reaching a target
sales number, or a percentage of sales as commission, or = cash bonuses for other measurable
performance indicators. However, these systems do not always work as intended (Joseph,
Emmett & Louw-Potgieter, 2012). Employees in these types of systems often feel extra stress
and pressure to perform which can lead to decreased output. These types of systems may also
not always be practical for the organization in discussion due to cost factors or the inability to
assess an individuals personal contribution to the organization's outcomes. The precise details of
this type of system would have to be determined on a case-by-case basis after examining the
relevant factors.
A technique that differs from PFP systems that attempts to utilize the effects of
organizational climate is one that is based upon employee involvement in organizational
leadership (EIOL). Organizational climate can have an effect on the motivation of workers
(Dachler, 1974) and in many cases can outweigh the effect of monetary compensation. An EIOL
system attempts to motivate workers by having a greater impact on the organizational climate
and therefore improving their perception of the organization. This system may include workers
having an influence over their schedule, having a vote in organizational decisions that are usually
reserved for management only, or having some input on the hiring of new workers for their

8. 4
department. Having increased input into the decisions surrounding their jobs can lead an
employee to become more engaged in their work, and therefore be more productive (Shuck &
Herd, 2012). This can be problematic as well, depending on the level of control involved. Some
employees may find the decisions they are allowed to make to be trivial, and therefore not have
the desired motivational effect, or management may not wish to give up any of their authority
due to the nature of the organization or the industry in which they operate. The specifics
involved with this type of system would be greatly dependent upon the specifics of the
organization in question.
For any system management employs, there will be some level of information given to
employees regarding its implementation. How well informed an employee is as to the inner
workings of a policy has been shown to have an impact on how well received that policy is
(Joseph, Emmett &Louw-Potgieter, 2012; Muga & Jenkins, 2007; Smith & Rupp, 2004). This
seems to be common sense, yet there are still occasions where full disclosure of policy is not
given by management or is not sought by employees. There could also be cases where
management's interpretation of the level of knowledge employees possess is not consistent with
fact. Simply ensuring workers have relevant knowledge seems like it could be an easy way for
management to improve the reception of their motivation policy and potentially increase
employees' willingness to participate with full effort.
Research Problem
Managers are consistently searching for the best way to motivate their workers. As new
graduates enter the workforce, it becomes urgent to understand what might work as a motivation
policy for these younger workers specifically. Management should be aware that the policies

9. 5
they have been employing successfully for older workers may not have the same effect upon
younger ones. Supervisors must also be aware of how a lack of information regarding the policy
can affect the reception of it by workers. Specifically, the questions that are in need of answers
are the following:
 Is a pay for performance system better or worse at improving younger employee's
performance motivation than a system that allows its workers to be more involved in
the management of their daily activities?
 Does the level of instruction as to the exact workings of the motivation policy have an
effect upon its success?
Research Objective
The purpose of the current research is to investigate into the effectiveness of methods of
motivating young (age 18-25) employees. Specifically, to compare the motivational benefit of a
pay-for-performance policy versus a policy based upon EIOL. The study also sought to examine
the mediating factor of level of information given to workers regarding the motivation policy.
Scope/Delimitations
This study attempts to gain some insight into motivational factors of individuals either
starting out in the workforce or soon to be, specifically, a comparison of two different types of
motivational policy. The results should be generalizable to Americans of typical university age
(18-25) who will be new to the workforce, or nearing entry into it. These results will most likely
not generalize as well to older workers. However, due to the subject matter of this study this is
not a major issue. This study did not attempt to compare all possible types of motivational

10. 6
policies, but is limited to two types. One of which is the seemingly 'common sense' pay for
performance (PFP) method and the other is based upon newer ideas that seem to be gaining
ground, the employee involvement in organizational leadership (EIOL) method.

11. 7
Chapter 2
Review of the Related Literature
Introduction to the Literature
There has been a large amount of research conducted in the area of employee motivation
over the years. Specifically, age, generational differences, gender differences, as well as cultural
differences regarding motivational factors have been researched. Some significant differences
between age groups have been found in this area of study. Additionally, various methods that
could be used to motivate workers have been investigated, in particular interest to the present
study are those, involving a pay-for-performance (PFP) policy and studies examining the
theoretical basis of an employee involvement in organizational leadership (EIOL) policy have
been examined below. The following section is comprised of a review of past literature related
to these topics of interest in the area of performance motivation on young workers.
Age-related differences in motivation
As the present study sought to investigate motivation specific to younger workers
entering the workforce, it is important to note how this type of worker may differ compared to
those of previous generations. This sub-section highlights some findings related to age in terms
of performance motivation.
Montana and Petit (2008) investigated into some of the generational differences in
motivating and managing employees. The study included 200 male and female participants from
Fordham University Schools of Business. Recent graduates and executive MBA students were

12. 8
classified as Generation X ranging in age from 25-40. Current undergraduates were classified as
Generation Y, ranging in age from 18-24. The study participants ranked twenty-five
employment conditions as principal workplace motivators. The researchers took care to
distinguish between motivators, as factors that can satisfy workers and encourage future high
performance, from maintenance factors, which are those that have the potential to dissatisfy the
workers leading to a decrease in productivity. The researchers compared these lists of factors
with lists obtained from managers in the 1970s (classified as pre-Baby Boomers) as well as lists
obtained from company representatives in the 1980s (classified as Baby Boomers). They found
the most popular motivators of the older two generations to be identical, and nearly so for
generation X. For Generation Y however they report 'getting along well with others on the job'
to be emergent as one of the top motivating factors where it did not make the top six factors of
any other generation. Generation Y also saw 'feeling my job is important' drop off the list
whereas it was present for the previous three generations. This implies an increasing tendency
towards social connectedness in the workplace, as well as cultural shift towards inclusion.
In addition to these findings, Wong, Gardiner, Lang and Coulon (2008) conducted a
study in Australia in order to find significant differences between generations in terms of
motivational drivers. In their study they used 3,535 managers and professionals who had
completed the OPQ32 (occupational personality questionnaire) as well as 294 professionals who
had completed a motivational questionnaire (MQ). The participants were classified based upon
their age into one of three categories; those over 40 were placed into the category of baby
boomers (n=1005 for OPQ, 110 for MQ). Those between 24 and 40 at the time of the study were
placed into the Gen X category (n=2089 for OPQ, 140 for MQ). Participants 23 or younger were

13. 9
placed into the Gen Y group (n=441 for OPQ, 33 for MQ). One-way ANOVA testing was
completed in order to look into the differences between these groups based upon six motivational
drivers. Analyses showed a significant difference for three of these drivers, though they were
not different in the expected direction. Specifically the motivational drivers of affiliation
(F=3.28, p<.05), power (F=14.89. p<.01) and progression (F=5.4, p<.05) showed significant
differences between the generations. Gen Y participants showed higher motivation towards
progression than baby boomers, more motivation from being in an affiliated workplace than baby
boomers and less motivated by power than either baby boomers or Gen Xs, who scored highest
on this measure. The authors propose that these results indicate that there may be age-related
differences in motivators on the job. One of the limitations of this type of testing is its cross-
sectional nature however. This makes it difficult to determine if the differences seen are
generational, or a result of the stage of life of the participant in question.
Methods for Motivating Workers
This section highlights some of the findings related to management policy in regards to
employee motivation. In particular this review will examine studies related to the two primary
methods being investigated in the present study, pay-for-performance (PFP) and employee
involvement in organizational leadership (EIOL) systems.
PFP systems are often one of the first ideas someone has to improve motivation.
Emmett, and Louw-Potgieter (2012) investigated into the motivating factors in a pay-for-
performance system in South Africa. In their study they administered a customized
questionnaire to university staff to which 391 members responded. The respondents included

14. 10
managers and administrative staff of both genders and the age of participants ranged from 21-65.
The objective of the study was to look into whether the PFP system recently introduced was
effective in performance improvement and to be able to generalize these findings to other similar
organizational settings. The design of the study was primarily descriptive in nature, collecting
quantitative as well as quantitative data to answer the evaluation questions. An exploratory
factor analysis (EFA) was conducted on the test items in order to break them down into separate
independent variables with the goal to see how they effected employees' disposition towards the
PFP system. These test items were then classified into the variables of guidance, support and
training; employee understanding; and employee motivation to work harder. The model
explained 49.3% of the variance seen and they also reached statistical significance using
ANOVA (P<.005). Cronbach's alpha was used as a reliability analysis and the result was .91 on
this measure indicating high internal consistency. The researchers surmised that the employees
who were part of the PFP system were not well disposed to it, despite how well trained they were
in the system and their understanding of it, whereas the members of management were much
more positive on the system. In the qualitative portion of the study, the members of the staff
were interviewed and consistently reported feeling extra pressure for achievement and found it
more difficult to meet deadlines due to this pressure. The researchers conclude that these types
of systems may not be the best way to improve motivation despite the 'common sense' nature of
paying for extra performance.
In 2005, Van Herpen, Van Praag, and Cools studied the effects of performance
measurement and compensation on motivation in Dutch workers. The research took place in a
the publishing division of a Dutch company with 302 workers participating in the study. A

15. 11
questionnaire was designed in order to measure the effects of specific aspects of the company's
motivational policy. The aspects under study were transparency, fairness, and controllability of
the reward and how they effected both intrinsic and extrinsic motivation. The researchers
compared the effects of these three factors on motivation by synthesizing the results of the
questionnaire into factor scores that can be compared to each other using regression analysis.
What they found was that the controllability of a PFP system had a significant effect (p<.01) on
extrinsic motivation with a factor score of .17. They did not find a significant effect due to
transparency or fairness regarding the monetary compensation, but they did find significant
effects of those factors for the company's promotion policy. Regarding the promotion
opportunities policy, transparency did show an effect on extrinsic motivation with a factor score
of .13 (p<.01) and intrinsic motivation with a factor score of .10 (p<.01). Fairness and
controllability were also significant in the determination of extrinsic motivation with factor
scores of .13 and .16 respectively. What this study shows is that fairness of a system is the most
important factor. While the transparency of a system, in other words worker knowledge, can
have an effect on some aspects of a policy, it is unclear as to its impact overall.
In a Vietnamese study, Nhat and Nguyen (2013) looked into the effects of motivating
factors among construction workers. The study involved 109 employees of the three branch of
the Petro Vietnam An Construction Corporation (PVC) representing 64.2 percent of the branch.
Participants were asked to rank order a number of motivational factors. Participants ranked pay
and promotion as the most important factor consistently, followed by good working conditions
and job security.

16. 12
As has been shown, pay for performance systems have had mixed results in the literature.
While they can be motivating for workers, they can also add stress and extra pressure to perform.
It is important to look at the effects of different types of policy in order to determine if a PFP
system is the right system for a particular organization.
Dachler (1974) conducted some early work in motivation regarding alternate
motivational levers to financial compensation. He proposed that researchers concentrate more
upon the environmental variables surrounding an individual rather than those variables
emanating from within the person. Dachler claims that interactions between employees and the
rest of the organization make up the foundation for workforce motivation and it is in the
organizational climate that one should find the keys to motivating employees.
In 2000, James, Taveira, Alvaro, Lund, and Sainfort investigated into the perceptions of
workers regarding their organization from a perspective of their involvement in a quality
management program. The study was conducted within the city government of Madison,
Wisconsin. Ninety-four employees completed the survey that attempted to discern the impact of
quality management training, and quality management project involvement on five workforce
outcome factors. The 14 factor items were were classified into five factors as general job effects,
workload effects, job communication, growth and development and task clarity. Participants
who had received training in quality management scored higher than those who did not receive
training, suggesting that more knowledgeable workers have better outcomes. This study also
showed that those who were involved in quality management directly had better outcomes on
their five factor outcomes. This shows a potential for worker involvement in management
decision making to have a positive effect on worker outcomes.

17. 13
More recently Wegge, Jeppson, Weber, Pearce, Silva, Pundt, Jonsson, Wolf, Wassenaar,
Unterrainer, and Piecha (2010) conducted a comprehensive meta-analysis in order to determine
the effectiveness of an employee involvement in organizational leadership (EIOL) system
regarding the motivation of workers. In their study they examined the results of 26 meta-
analyses regarding traditional work practices such as goal setting, feedback, work design and
financial incentives. The authors used correlational data to investigate a relationship between
these work practices with job satisfaction as well as organizational commitment. When looking
at work design, the authors found that workplaces with more autonomy tended to be significantly
correlated with job satisfaction (r=.58) and organizational commitment (r=.34). Higher levels of
procedural justice also produced significant correlations with job satisfaction (r=62) and
organizational commitment (r=.52) as well. Financial incentives also had a significant impact on
performance (r=.34) and also had a negative correlation with voluntary turnover (r=-.17) . Based
upon the results of these analyses, the authors propose that employee becoming more involved in
leadership can have a major impact in their level of performance motivation. Financial
incentives can also be motivating, but it is not the only, nor necessarily the best way to motivate
workers according to the authors. This supports Dachler's idea of the climate being a
motivational factor, as employees involved in an EIOL-based policy will have more impact on
the overall climate of their organization than those in a PFP system.
The effect of knowledge
Smith, and Rupp (2004) investigated into workers' knowledge. Specifically, in this study
the workers' perceptions of how their performance ratings would increase their merit pay

18. 14
increases. In a PFP system such as discussed by Smith and Rupp, it is important to workers to
understand where they stand in terms of their performance rewards. Using qualitative case-study
methodology Smith and Rupp studied 53 workers regarding their performance evaluations and
their merit pay increases. In several cases the performance scores did not equate to what would
seem to be the correlating merit increase meaning that high performance scores did not
necessarily relate to higher bonuses. In their interviews, Smith and Rupp found that workers who
had inconsistent merit increases to their performance scores to be frustrated and have lowered
motivation for future work. This indicates that there was a lack of knowledge on the part of the
employees as to the precise mechanism of their pay increases.
Hsiu (2011) investigated the relationship between motivation and knowledge. In this
study the author proposes a link between both intrinsic and extrinsic motivation with knowledge
management. The study used survey data from 243 senior executives in large corporations in
Taiwan intended to measure motivation and knowledge management practices. A partial least
squares analysis was conducted in order to determine the relationship. They found a significant
correlation between intrinsic, as well as extrinsic motivation with knowledge management
implementation level with coefficients of .85 and .88 respectively. While this study aimed to
show the effects of motivation on knowledge management, as it is done as a correlation it cannot
be said for sure if the higher implementation level of knowledge management was caused by, or
was the cause of increased motivation. While this does relay a relationship between knowledge
and motivation, it does not definitively show the inner workings of that relationship.

19. 15
Some Other Considerations Related to Employee Motivation
The following section reviews studies related to motivation that have not been discussed
in the previous sections yet are relevant to the topic of employee motivation. Investigating into
the role that a person's culture may play in motivation as well as some of the emotional
considerations that should be made at the individual level.
Chen, Sharma, Edinger, Shapiro and Farh (2011) looked into the motivating and
demotivating factors in workplace activities. The purpose was to compare these factors cross-
culturally between workers in the United States (USA) and those in the People's Republic of
China (PRC). The participants in this study were primarily within the typical university age of
18-24. The researchers involved 57 students enrolled in management courses in the USA and 79
students enrolled in such courses in the PRC. Participants were randomly assigned to one of four
conditions. In each of the conditions, participants read a scenario comprising elements of high or
low empowering leadership and high or low relationship conflict. They hypothesized that
empowering leadership would positively influence psychological empowerment and affective
commitment, while relationship conflict would negatively influence psychological empowerment
and affective commitment. The data was analyzed using regression analysis. The validity of the
measures was checked using confirmatory factor analyses in LISREL. The results showed
strong support for the two hypotheses among the USA participants (b=.49, .50 respectively,
p<.05) in the predicted directions. These results also supported the findings within the PRC
when controlling for nationality differences. Essentially this study supports the idea that
individuals with more empowerment, or control of their daily workday tend to have more

20. 16
commitment to their workplace. This commitment should translate into a higher level of
motivation towards performance.
Sakurai and Jex (2012) looked into the role that emotion and incivility plays in the
development of counterproductive work behaviors (CWBs). These include lack of motivation.
They hypothesized that negative emotional states, such as sadness or frustration, contribute to
behavioral disengagement including inattentiveness and reduced effort. They also hypothesize
that co-worker incivility is a contributing factor to negative emotional states and thusly,
disengagement in work. In this study, Sakurai and Jex utilized 856 university employees in the
U.S. across two different measurement periods. The demographic makeup for the study was
comparable to the local population. The researchers utilized descriptive statistics and zero-order
correlations for several variables, including work time, CWBs, job type, job autonomy, negative
emotions, coworker incivility and supervisor social support. They found that there was a
relationship between worker incivility and target's negative emotions, finding a significant
positive correlation (.86). They also found negative emotions to be correlated with CWBs (.46).
These findings support the authors' hypotheses.
Shekar and Devi (2012) investigated into the differences in achievement motivation
across gender and scholastic subject. Their study utilized 80 undergraduate students in India,
with 40 being male and 40 female. The participants were given an achievement motivation test,
the scores of which were used to conduct a t-test analysis. This study found that the mean scores
of males (128.75) were significantly lower than those of females (141.02) in the achievement
motivation among students. This study also investigated the different levels of motivation
between arts and science students with students of the sciences (mean=140.8) having

21. 17
significantly higher levels of achievement motivation than students of the arts (mean=128.93)
with a t-value of 15.64, p<.01. This study showed that not only can there be gender differences
in motivation, but motivation can also differ depending on the subject.
Summary of the Literature Review and Hypotheses
These studies highlighted above show that management's goal of increasing the
motivation of employees is not as simple an act as it may at first appear. There are a large
number of intrinsic and extrinsic factors that can influence an individual employee's job
motivation including their age, emotional state, the workforce climate, part of the world they live
in, and the type of policy being employed. Specifically relevant to the present study is the idea
that a policy based upon financial compensation for performance and a policy based upon
employee involvement in organizational leadership have been shown to have some effect on
motivation. The younger generation now entering the workforce has been noted to show an
increased affinity towards cooperation, progression and affiliation within an organization, it
seems plausible that a policy based upon EIOL should be highly motivating to younger workers.
This is something that the present study attempts to address.
Additionally, it has been discussed that the amount of knowledge that an individual has is
correlated with motivation level. It has also been discussed that greater knowledge involving a
policy can make an employee less frustrated with how it is enacted. It could be concluded that
increased knowledge regarding a motivational policy may make an individual more likely to 'buy
in' to that policy. This is also something that the present study attempted to address.
Due to the younger generation's affinity toward social involvement, the positive
motivational effects of impacting an organization's climate and the improved outcomes of

22. 18
workers who are more involved in decision making, it is predicted that 18-25 year old workers
who are under a policy based on EIOL will be more motivated to increase their performance at
work than those under a policy based upon PFP. Additionally, due to the effects of increased
knowledge on policy adoption and its correlation with motivation, it is predicted that individuals
who receive a higher degree of knowledge regarding their company's motivational policy will
show evidence for higher work motivation than those who receive less knowledge about the
policy.

23. 19
Chapter 3
Research Methodology
Research Approach
In order to determine the better choice between PFP and EIOL policies in motivating
young workers, an experimental design has been chosen. This approach will make it easier to
determine the effect of the policy than simply interviewing participants. The results will show to
what effect the policy and level of knowledge each have independent of other factors. It can also
reveal any potential interactions between the two variables. Reviewing existing data for this
purpose is problematic as there has been very little study in regard to the effect of an EIOL
policy for younger workers, therefore new data must be collected for this study.
Data Collection Approach and Procedures
Participants.
This study utilized 237 people living in the United States aged between 18 and 25 who
were recruited as part of a paid panel at www.surveymonkey.com. The hosting website handled
the criteria screening and study distribution as well as participant recruitment. Participants were
to be of any race, ethnic background, or gender. The number of participants allowed for each
group to contain at least 50 members after dropouts or those screened due to incorrect
completion of test items were accounted for. Considerations were made as to the potential size
of the participant pool as well as the number of participants needed to achieve statistically
significant results. There were 17 participants who did not complete the survey correctly or
opted out before finishing. Any results from these participants were not included. There were 6

24. 20
participants who elected to not include all of their demographics information. Their data was
used to test the main hypotheses but were not considered when analyzing data related to
demographics. Participants were requested to give informed consent before participation and all
participants were be treated in accordance to CMU ethical standards. This study posed no risk to
the subject population. Participants completed the survey anonymously.
Apparatus.
Participants received either the EIOL policy description, or the PFP policy description.
Each policy description had two versions, the high information, and low information versions.
The high information version of each policy included a greater amount of detail as to the
specifics of the policy relating to their hypothetical position, whereas the low information
version contained only the most basic information. The high and low information versions of the
PFP and EIOL policies are included in Appendix C.
For measuring work motivation, the Shouksmith (1989) work motivation scale has been
used for this study. The scale contains 10 evaluative statements regarding the participants'
potential job. The scale has been validated using a factor analysis comparing it to nine other
similar scales. The scale items have been included in Appendix D. There are 10 items on this
scale and each item is to be rated 1 through 7 by participants. The sum of these items will be
considered the participants' motivation score and this score will be used as the dependent
variable for analysis purposes.
A demographics questionnaire was also used in order to determine the age, gender, race,
nationality and region of the country of each of the participants. While this study was primarily
focused on the differences between the policy types, other comparisons including race, gender,

25. 21
and region of the country were also made for the sake of gaining greater accuracy in the
description of the phenomena.
The Survey Monkey website also includes their own questionnaire at the end of all of
their surveys which includes demographic information such as age, gender, household income,
and region of the country. The results of this questionnaire were not used in the present study.
Procedure.
All of the testing for this project was administered online. According to Aust,
Diedenhofen, Ullrich and Musch (2008) online surveys can be a valid research tool. Upon being
asked to participate in the survey as part of a panel, participants were asked for their informed
consent (Appendix A). They were next asked to complete the background information
questionnaire (Appendix B) although responding to the individual items was optional. The
Survey Monkey website screened participants for the correct age range of 18-25 and all
participants live in the United States.
After answering the demographics questions, participants were shown one of the four
policies to look over. Participants were not allowed to see more than one of the policies or to
complete the study more than once. Participants were not aware of which group they were
assigned to nor were they aware of the purpose of the testing. The only title they saw was "work
survey" at the top of the page.
They were then asked two simple questions regarding the policy as a manipulation check.
Participants unable to answer these two questions were not included in the results (n=8). The
four policies and manipulation check questions have been included in Appendix D. Participants
were then given the Shouksmith motivation scale to complete. Participants were instructed to

26. 22
complete the items as if the policy they were given was true for a potential job in their chosen
field. After completing the scale, participants were given the Survey Monkey questionnaire.
This was a part of their agreement with Survey Monkey and the results of this questionnaire were
not used in this study. Survey Monkey compensated participants in accordance with their
corporate policy regarding study panel participation.

27. 23
Chapter 4
Data Analysis
Approach for Data Analysis and Synthesis
The results of the Shouksmith motivation scale were analyzed using the combined score
of all ten of its items as the dependent variable. This is meant to represent an individual's work
motivation for the hypothetical job that they were asked to imagine themselves in. The scores
ranged from 15 to 75 with an overall mean score of 47.73 taken from the 212 participants who
completed the scale correctly. For analysis purposes, participants were grouped together based
upon which version of the policy statement they had been given. A 2 (EIOL versus PFP policy)
x2 (high versus low level of instruction) factorial ANOVA was conducted in order to determine
the presence of a significant difference between these groups. Post-hoc testing using a series of t-
tests analyses was also done in order to determine more specifically where the differences are
occurring within these variables. Demographic information was also used in the series of t-tests
in order to gain a clearer view of the makeup of the phenomenon, for the results based on gender,
the scores of 6 participants were omitted due to their election to not reveal their gender in the
demographics questionnaire. The study aimed to achieve a significance level of less than .05 for
all of the testing. Basic descriptive statistics such as mean scores and number of participants in
each condition will also be reported.
Primary Analysis
The ANOVA (EIOL vs. PFP) x (High vs. Low information) was intended to test whether
there was a difference in motivation score between the two levels of the two policy types. The

28. 24
results of this ANOVA F(3,208) = 8.1 revealed a significant difference between groups (P<.01).
As far as the specific group scores are concerned the group receiving the EIOL High Instruction
level policy (N=52) had a mean work motivation score of 48.8. The group that received the
EIOL low instruction level policy (N=55) had a mean work motivation score of 51.7. The group
that received the PFP high instruction level policy (N=50) had a mean work motivation score of
50.1. Finally, the group that received the PFP low instruction level policy (N=52) had a mean
work motivation score of 40.5. This significant ANOVA result shows that there was a
significant difference due to the difference in policy.
Post-hoc testing using a series of t-test analyses was done in order to reveal the specific
nature of the difference. This testing showed that there was no significant difference between the
high and low instruction versions of the EIOL Policy. There was also no significant difference
found between the high instruction versions of the EIOL and the PFP policies when compared
against each other and not considering the low instruction versions. There was also no
significant difference found between the high instruction version and the low instruction versions
of the policies when the specific policy type is not taken into consideration. However, there was
a significant difference found between the EIOL policy type, n=107, mean=50.31 and the PFP
policy type (n=105, mean=45.01) t(210)=2.81, p<.01. This confirms the main hypothesis that
there was a difference in motivation for EIOL type policies compared to PFP policies in young
workers. Furthermore, there was also a significant difference found between the two instruction
levels of PFP, with the high instruction level, mean=n=50, mean=50.12 showing significantly
higher values than the low instruction level, n=55, mean=40.54, t(103)=3.7. This seems to be the
most likely explanation for differences between EIOL and PFP. This is a partial confirmation of

29. 25
the second hypothesis in that the level of instruction would have a significant effect, although in
this case it only affects one policy type. Therefore the significant ANOVA test in the earlier
section was due to an interaction effect between the instruction level and policy type
manipulations.
Other t-tests were also conducted based upon responses from the demographics
questionnaire. This was done in order to further understand the workings of the phenomena and
to avoid any potential problems with generalizing results to greater numbers of people. The
variable of race did not result in significant t-tests for either policy type or for level on
instruction.
Gender Based Analysis
Some of the t-tests based upon gender did garner significant results in work motivation
scores. Female participants scored significantly higher on the work motivation scale when given
the EIOL policy, n=60 mean=50.0, compared to those given the PFP policy, n=56, mean=43.7
t(114)=-2.4, p<.01. For males there was no significant difference between the EIOL, n=44,
mean=50.7, versus the PFP, n=46, mean=48.1, policy types, although there is a trend towards
significance with EIOL being favored. This indicates a gender-based preference for EIOL
policy. The means for overall motivation scores across all of the four policy types for male
participants, n=89, were 49.3 and for female, n=116, the overall score was 46.9. These scores
were not significantly different from each other.
These results show that there is a significant difference in the motivation scores generated
by the two types of policy. Specifically, the differences occur in instruction level of PFP policies

30. 26
and across the two policy types within the group of female participants. The hypothesis stated
that there would be a significant difference between the two policy types and that there would be
a significant difference between the two levels of instruction. Both have been shown to be true,
although the phenomenon does not seem to occur equally across both policy types nor for both
genders.

31. 27
Chapter 5
Summary, Conclusion and Recommendations
Summary
In this study two different types of organizational policy designed to increase employee
workforce motivation have been discussed and tested. A pay for performance (PFP) system is
the more traditional of the two where employees are compensated financially based upon their
level of performance. As money is an important motivator, this seems to be a logical method for
managers. The other system tested was one based upon the newer idea of employee involvement
in organizational leadership (EIOL). This type of system seeks to motivate workers by having
them more involved in the decision making process, thus making them more mentally engaged in
their workplace with the goal of increasing their commitment to the job. As social factors tend to
be highly motivating to younger workers, a system with EIOL in mind could be a good idea for
an organization employing many young people. The results presented in the preceding section
begin to answer to the original research question: is a PFP system better or worse at improving
younger employee's performance motivation than a system incorporating EIOL? The results
then seek to answer the second research question: Does the level of instruction regarding a
policy make a difference as to the impact of that policy?
Conclusion
The results reported above have indicated that an EIOL based policy generates an overall
significantly better workforce motivation score than does a PFP based system. This is taken

32. 28
across the full sample regardless of demographics or the amount of detail given about the
implementation of the policy. This score should translate to work performance motivation in the
real world according to Shouksmith (1989). This finding is consistent with the findings of
Wegge et al (2010) who proposed EIOL methods of motivation and would also be consistent
with Dachler (1974) relating to the contributions an individual makes on the organizational
climate having a motivating effect. Granted, these results do not demonstrate this effect across
all conditions or across all demographic groups. Women tended to show a significant preference
for EIOL systems over PFP while males did not show a significant difference. This is in line
with Shekar and Devi (2012) who demonstrated a differential motivation mechanism for males
and females. It may indicate a stronger preference for women to be motivated by systems
involving a higher level of social interaction, such as EIOL as opposed to one that is more based
upon the person alone.
Despite the fact that EIOL policies do not have a significant advantage over PFP across
all potential workers, it would still indicate an advantage for managers to develop EIOL policies
overall. The primary advantage comes from the gender differences in response to the two types
of policy. While male participants did not show a significantly different level of work
motivation between PFP and EIOL policies, female participants did show a significant
difference. Therefore there is nothing lost in choosing an EIOL policy over a PFP policy but
there is potentially much to gain. If a manager is working in an organization that employs a
large number of young women, they should see a significant improvement in employee
motivation if using a policy including EIOL.

33. 29
This study also shows that providing a greater amount of information to employees
regarding a motivational policy would have a positive affect on the motivational effects of the
policy. This is much as Emmett and Louw-Potgieter, (2012) would predict based upon their
research discussed above. The results of this were not even across both policies making the
exact effect of this still unclear as was found by Van Herpen et al., (2005). The differences seen
in the present study regarding the impact of a PFP-based policy due to information level is
consistent with Smith and Rupp's (2004) results. Workers under a PFP policy seem to become
frustrated due to the uncertainty of the policy implementation. As the group who received the
low information version of the PFP policy showed the lowest scores of the four policy types, this
seems to be the case. With only the PFP policy type showing significant effect from level of
information, there is still an advantage to keeping workers well informed regardless of policy
type. The same advantage is there as in the previous paragraph in that there is no harm in
increasing the knowledge an employee has regarding a motivation policy and a large potential
gain.
Recommendations for future study
This study's results bring about other questions that could be answered by future research.
The most glaring of these is gender difference. Gender differences in workforce motivations
would be an excellent area for future study. Perhaps if only to verify that the gender differences
found with this research are indeed a real occurring phenomenon and if that is the case, what
emotional or cultural factors are at the root of the difference? A study similar to this one with

34. 30
gender differences under consideration from the outset of design would be an excellent way to
fill this gap in knowledge.
Another potential future study would involve the study of workers from more than one
age bracket in order to compare several motivational methods across several age categories.
This would also be done similar to the current study with the age exception. This study would
also have to control for other variables such as work experience as exposure to one type of policy
may effect an individual's perception of an alternative policy.
In this same vein, a study related to the specific industry in question may lead to greater
understanding. Shekar and Devi's (2012) study showed a differential level of achievement
motivation between students of the arts and students of the sciences. This difference could
potentially translate to different industries in a workplace setting. It would be conducted in much
the same way as the present study excepting that industry would be included in the comparisons.
Additionally, another study involving workers from different parts of the world may
bring some new information to light. As was discussed in Chapter 1, there were some
differences between Chinese and American workers in employee motivation. In their study in
Vietnam, Nhat and Nguyen (2012) showed that pay was the highest motivator for the workers in
their study. Their study did not include any type of EIOL-related questions. It would be
interesting to see if differences would be seen in these countries making the types of
comparisons made in the present study.
Methodological Limitations
This study does not come without limitations however. Generalizing the results of this
study is limited to those fitting within the 18-25 age range and those that are from the United

35. 31
States. It will also be difficult to generalize results to workers who do not answer online surveys.
The study is further limited by the fact that only two motivational methods have being tested, as
well as only two different versions of policy based upon these methods. There could potentially
be many more ideas for policy as well as different methodology to implement similar policies.

36. 32
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39. 35
Appendices
Appendix A Permission to Conduct Study
Dear Participant:
Thank you for your participation in this study. Your data will assist current and future managers to make
informed decisions regarding work policy.
The individual data collected from these surveys will remain strictly confidential. No one other than the
researcher will see any answers associated with your personal demographic or personal data. Personal
information is not required for participation. Once all of the data is collected and analyzed, any
identifying data will be removed and results will be available to all participants to review. There is no
known risk to you, emotional or otherwise, for participating in this study.
The study consists of a few background questions followed by a short example work policy. Please
imagine yourself at a future job in your chosen field and the policy you are given is applicable to that
organization. Following this, there is a short survey of 10 questions to be completed. The entire study
should not take more than 10 minutes.
Thank you in advance for your participation and if you have any questions, please contact me at the e-
mail listed below.
Jason Leiter
Central Michigan University
Masters of Science in Administration Candidate
leite1j@cmich.edu
Please indicate your consent to participate in this project. If you are unwilling, please do not continue.
I have read the instructions and am willing to consent to participation in this project of my own free will.
Digital Signature_____________________

40. 36
Appendix B Background Questionnaire
Please complete the following questions about yourself. Please try to answer honestly.
Year of birth_______
For the following, please select the most appropriate answers.
I classify myself as
Male Female
I classify myself as (more than one can be chosen)
Caucasian African-American Asian Native American Other classification _______
(text box)
I classify myself as
Latino Not Latino

41. 37
Appendix C Policies.
PFP Policies.
Low Information.
Your financial compensation will be based upon your performance at your job. You will
not have much input in management decisions.
High information
This organization believes firmly in a pay-for-performance system of compensation.
Management has decided that employees should be rewarded directly for their personal
contribution. For every sale you make, or new client brought in, you will be compensated a
significant percentage of the profit. With that being said, there will be supervisors monitoring
your performance and giving you advice or guidance when you are not meeting goals.
EIOL Policy
Low Information
You will be allowed to participate in some of the leadership decisions at this
organization. Your compensation is not based upon your performance metrics.
High Information
This organization firmly believes in a system where workers are involved in the
leadership decision-making. Management has decided that employees should have some
personal input into the daily operation of their own workplace. For major decisions, there will be
voting taking place where workers are allowed to have input. Your compensation is not based
upon your performance metrics. There will be some oversight by management as to your daily
work, but they tend to be open to communication.
Manipulation Check Questions:
1. Does this policy mention being financially compensated based upon your job performance?
Yes No
2. Does this policy mention having input into work-related leadership decisions? Yes No.

42. 38
Appendix D Shouksmith (1989) Work Motivation Scale
Based upon the information given to you. How would you feel about this potential job situation?
Please rate the following items with a 1-7. A rating of 1 indicates a strong disagreement, a rating
of 7 indicates a strong agreement. A rating of 4 indicates neither agreement nor disagreement.
(these will be radio boxes in the online version.)
This job:
1. Has supervisors and leaders who are helpful and fair 1 2 3 4 5 6 7
2. Gives you status and prestige 1 2 3 4 5 6 7
3. Provides satisfactory material rewards 1 2 3 4 5 6 7
4. Allows you to reach and develop your full potential 1 2 3 4 5 6 7
5. Means working with pleasant and helpful workmates 1 2 3 4 5 6 7
6. Is a secure one 1 2 3 4 5 6 7
7. Provides good physical working conditions 1 2 3 4 5 6 7
8. Is a challenging and exciting job 1 2 3 4 5 6 7
9. Is one where your good work and effort is appreciated 1 2 3 4 5 6 7
10. Taken all round and considering its aspects, is good. 1 2 3 4 5 6 7