A research I have conducted during my PhD studies at Yeditepe University

1. 1
Correlation Between Proper Training /
Involvement and ERP Acceptance and
the Mediating Effects of Ability &
Willingness
KeremKöseoğlu
Yeditepe University
Abstract
This paper discusses training and project involvement as the key factors leading to user acceptance of
a new ERP system. If the users of the system received enough training and were able to interact with
it during the implementation project, they should find the system easy to use, and this perception
should increase the level of utilization of the new ERP system. However, the user’s motivation in terms
of ability and willingness is expected to havea moderating effect.
This paper adopts a quantitative study among the employees of companies using ERP, and includes
questionnairesand statisticalanalysis to see if the hypothesisweresupported ornot.
Keywords: Enterprise Resource Planning, ERP, Enterprise System, Utilization, Training, Involvement,
Ease of Use, Motivation,Ability,Willingness
Introduction
ERP implementation is a serious change for any organization (Kwahk, 2006). ERP systems provide
many benefits to an organization in operational, managerial, strategic and organizational levels
(Shang & Seddon). Despite all the advantages an ERP system may bring to an organization, it is the
people who are going to use it. And if the members of the organization are having a hard time using
the system,the whole organizationwill be affectedbythat.
In this scope, a manager may ask himself the following question: “What should I do to increase the
level of utilizationof ournewERP system?”
Many answers to this question can be found in the literature. One of the recent studies has shown us
that there is a correlation between the user’s perceived ease of use and the level of utilization
(Kwahk, 2006). This means; if the user feels that the ERP system is easy to use, he/she is going to use
it “better”. In the same article, the author has found scientific support for his hypothesis that the
perceived ease of use stands as an intervening variable between the user’s attitude towards change
and the utilization of the system. This means; if the user has a positive attitude toward change,
he/she will have an easier time evaluating the system as “easy to use”, and his/her utilization of the
systemwill increase.

2. 2
Although this model looks promising, a very important factor seems to be missing there: Training. A
new ERP system brings dramatic changes to an organization. If the users are not prepared, they can’t
be expected to use the new system efficiently. Therefore, level of training quality and involvement
shouldappearas one of the factors affectingthe utilizationof the system.
While training is important, motivation is also expected to have an effect on the utilization of the
system. Motivation can be defined with a simple formula where the level of ability is multiplied with
the level of willingness (Draffan, 2007). If a user doesn’t have the ability and/or willingness to use the
new system, you can’t expect him / her to be efficient no matter what the management has provided
to them.
Purpose of this paper is to research the correlation between training / involvement and perceived
ease of use (of the ERP system) andthe moderatingeffectsof motivation in-between.
What Is ERP
ERP stands for enterprise resource planning. Enterprise resource planning is an integrated software
solution used to manage an organization's resources. ERP systems integrate business management
and administrative functions including human resources, accounts payable, purchasing and finance
(Case WesternReserve University,2004).
ERP is not a new concept. ERP systems are being developed since more than 30 years, and
companies have been using themever since.An ERP systemis very promisingin terms of productivity
and cost reduction.
Because ERP is usually a big and complex system designed and tailored to correspond to
organizational processes, implementation of an ERP system is also a process itself and takes some
time. Therefore,eachERPimplementationisconsideredasaproject.
Usually, ERP implementation projects have two parties: The customer who has bought the system,
and a consultancy company doing the work. In Microsoft Dynamics’ Sure Step Methodology, these
partiesare dividedintothe followingroles (MicrosoftCorporation,2006).
In terms of consulting roles; a project manager will manage the project, possibly together with a
customer project manager. Engagement manager facilitates hand-over from sales, communicates
with customer throughout the implementation and manages customer engagement and customer
relations. An application consultant analyses business processes, describes requirements, facilitates
gap/fit analysis, designs modifications, tests modifications, configures the system, performs training
etc. A development consultant evaluates requirements and participates in design of modifications,
develops and unit tests modifications. A technology consultant evaluates requirements and
participatesindesignof modifications,developsandunittestsmodifications.
In terms of customer roles; a business decision maker makes business critical decisions related to
implementation project, controls budget and reviews proposed solutions and estimates. In larger
implementations the customer may have a dedicated project manager to drive customer activities in
the project. Project management is done in cooperation with the consulting project manager. An IT
manager provides information on existing infrastructure and participates in planning future
infrastructure. A key user is a domain expert who has critical knowledge of specific business

3. 3
functions, can describe business processes, helps configure & test the system and trains end users.
An endusersupportsthe systemtestandusesthe systemonce implemented.
A typical projectwill have the followingstages (Ramanathan&Bhatia):
 Business Process Study (As-Is): Regular interactions with the client grow in order to
understand the various business processes and the way they are presently carried out. This
enables the consultants to understand the processes and terminology of the customer
better.
 Pre-Implementation Training: A general training is provided to the customer project team to
make sure that they have a general understanding of basic ERP concepts. This enables the
customer team to understand the terminology of the consultants better, and have a general
insightaboutwhatthe software iscapable of.
 Requirement Analysis (To-Be): The requirements of the customers are analyzed in great
detail.Alternativesolutions are analyzed,anddevelopmentrequirementsare discovered.
 Blue Print Approval: This is the stage where the customer and the consulting company agree
on the target solution.Resultsof the analysisare documentedandsignedbybothparties.
 Implementation: Customizations and developments are carried out. Minor
misunderstandingsandchange requestsof the blue printcanbe toleratedduringthisstage.
 Testing: As customizations and developments are completed, the key users set out to test
the systemto make sure that itworksas intendedandthatit satisfiesthe requirements.
 End-User Training: End-users are trained so that they gain the skills required to use the new
system.
 Master Data Migration: Real master data of the customer is installed into the ERP system.
Thisincludes,butisnotlimitedto,material masterdata,chartof accounts,HR data, etc.
 Go-Live: The legacy system is shut down, and the new ERP system becomes available to all
users.
 Post Implementation Support: After go-live, the consultancy company usually gives live
supporton the site to make sure that everythingisrunningsmoothly.
Conceptual Background and Hypotheses
Perceived Ease of Use and Utilization
Perceivedease of use, refers to "the degree to which a person believes that using a particular system
would be free of effort." This follows from the definition of "ease": "freedom from difficulty or great
effort." Effort is a finite resource that a person may allocate to the various activities for which he or
she is responsible (Radner and Rothschild, 1975). On the other hand; utilization is reflected by the
extent to which the information system has beenintegrated into each individual’s work routines (Rai,
Lang, & Welker,2002).
Many empirical studies have suggested a significantly strong relationship between intention and
behavior. Therefore; the use of behavioral intention has been justified as a dependent variable to
surrogate actual behavior. Furthermore, IT utilization is a reflection of the acceptance of the IT by
users (Kwahk, 2006). All else being equal, we claim, an application perceived to be easier to use than

4. 4
another is more likely to be accepted by users. The more useful and the easier to use an ERP system
inenablingemployeestoaccomplishtheirtasks,the more itwill be used (Kwahk,2006).
H1: Perceived ease of use of an ERP system will have a positive effect on utilization of the ERP
system
H1.1: An increase of the perceived level of ease of use of an ERP system will increase the
level of systemutilization
H1.2: A decrease of the perceived level of ease of use of an ERP system will decrease the
level of systemutilization
Training / Involvement and Perceived Ease of Use
Being one of the key stages of an ERP implementation project, training is the phase where the users
get to know the system and how they are going to use it. As mentioned above, a typical ERP project
will have two trainings. The first training is organized at the early stages of the project. It is aimed at
key users and the project team, and the purpose is to make a general introduction of the ERP system
to the employees of the company. After this training, the consultants and users are expected to have
a common ground of understanding and communication. The second training is organized at the late
stages of the project; probably close to the go-live date. It is aimed at end users, who do not need to
understand the depths of the ERP system. The purpose of this training is simply to educate all of the
employeessothattheywill knowhowtouse the systemtoperformtheirjob-relatedtasks.
In general, there are four types of capabilities which are potentially trainable: Knowledge, observable
skills, problem solving skills and attitudes & beliefs (Anderson, Ones, Kepir Sinangil, & Viswesvaran,
2006). When ERP training is in question, all of these capabilities would be targeted. The users’
knowledge about the new system is increased. They gain observable skills of using the system. Their
problem solving skills are increased so that they know what to do when they encounter an error
message.
However, the most important factor from our point of view is the improvement of attitudes &
beliefs. The extant training evaluation literature shows that training can have large effects on
knowledge and skill acquisition, as well as attitude change (Anderson, Ones, Kepir Sinangil, &
Viswesvaran, 2006). If a proper training is provided to an end-user, he/she will gain the knowledge,
observable skills and problem solving skills required to be able to use the system. Compared to the
first moment he/she saw the GUI1
where everything seemed to be so complicated and hard; the user
will have aneasytime usingthe tool to performjob-relatedtasks.
This situation is expected to result in a change on the user’s attitude towards the ERP system. If the
user has the proper knowledge and skills to use the system, he / she would start to perceive it as
“easy to use”. In other words; if a proper training has been provided to the user, he / she will be
expected to perceive the ERP system as “easy to use”. In that context; users without a proper
trainingare expectedtoperceive the systemas“hardto use”.
H2: There is a positive correlation between the quality of the training and the user’sperceived
ease of use
1 Graphical User Interface

5. 5
H2.1: A high quality training will have a positive effect on the level of perceived ease of
use
H2.2: A low quality training will have a negative effect on the level of perceived ease of
use
While a former training is one of the most significant alternatives to arm the user with proper skills to
use the system,practice alone isanotherone.
Human brain learns in two ways. The first way is learning by training / memorizing. This is the usual
type of learning in a formal training discussed above. However; the second and generally strongest
type of learning is learning by practice (Arntz, Chasse, & Vicente, 2008). Arntz, Chasse and Vicente
provide an excellent parable of riding a bike. You can read a book on the subject the whole day, for
example. If your brother, who also has no former experience on bikes, has been riding the bike in the
backyardmeanwhile,he will be abetterrideratthe endof the day.
Although end users are provided with formal trainings, key users are involved in many details of the
ERP system since the first day of the project. They “ride the bike” among the experts: ERP
consultants. As the project advances, key users work literally side-by-side with consultants and see
how many tasks are being performed on the system. In an incremental degree, key users even start
using the system themselves to support consultants. Some of their typical duties in this scope are to
participate in the blueprint meetings, create master data, performing tests of implemented
scenarios, using the system with test data to make sure that the configuration matches the
company’s requirements, preparing end-user documentations, etc. It is also typical for a key user to
navigate & discover certain functions of the system in their spare time and ask consultants about the
details.
As the project advances, the key users gain more and more practical experience; which is
comfortably comparable to the formal training of end users in terms of experience. At the go-live
date, the key users will surely have more experience than end users. But this fact doesn’t mean that
the end users don’t interact with the ERP system until the day their training starts. There are key
users who are involved in the project since the first day, that’s a fact. There are also some end users
who don’t even see the GUI once until they are trained, that’s also a fact. However, there are many
end users who are involved in the project in some degree – usually not as much as key users of
course. Some end users with specialized knowledge about certain business processes are invited to
project meetings and they get to see and understand some parts of the ERP system. Some end users
are occasionally invited to the project to share the workload of the key users, where they gain
practical experience. There are many similar occurrences where end users get the chance to involve
the project.
Just like the formal training, practical experience also arms the user with the required skills to user
the ERP system. Within the same scope discussed in terms of training, practical experience resulting
in project involvement is expected to increase the perceived ease of use. Even if an employee has
gained the required knowledge and skills through practical experience, he/she is still expected find
the systemeasy to use. Because the level of practical experience will increase with the actual level of

6. 6
project involvement; an increase of perceived ease of use is expected as a result of an increasedlevel
of involvement.
H3: There is a positive correlation between the user’s level of involvement and perceived ease
of use
H3.1: A high level of involvement will have a positive effect on the level of perceived ease
of use
H3.2: A low level of involvement will have a negative effect on the level of perceived ease
of use
Ability and Willingness
Ability is a general term concerning the power or capacity to act financially, legally, mentally,
physically, or in some other way (Anderson, Ones, Kepir Sinangil, & Viswesvaran, 2006). In the scope
of this paper, we are going to focus on the cognitive abilities of ERP users which are related to the
level of computerliteracy.
Computer literacy is the knowledge and ability to use computers and technology efficiently.
Computer literacy can also refer to the comfort level someone has with using computer programs
and other applications that are associated with computers. As of 2005, having basic computer skillsis
a significantassetinthe developedcountries (Wikipedia,2008).
In previous studies, it was found that variables such as computer experience and computer
familiarity influenced levels of computer literacy (Zin, et al., 2000). This means; the more a person
has experience and familiarity with computers, the more comfort he / she will find using programs
and applications.
Today, many software applications have similar interfaces. Just like you know where to find the gear
and wheel in a new car, a computer literate user is expected to find out by common sense how to
perform basic tasks of a new application (Karat & Dayton, 1995). Therefore; in a typical application,
one could expect the level of computer literacy to relate directly to the level of perceived ease of
use.
However; in terms of complexity, ERP systems are not in the same league as typical desktop
applications; such as word processors, spreadsheets and Internet browsers. Understanding the logic
behind a certain ERP program will require the user to be experienced in the corresponding business
area. You can hire a bright computer engineer graduated from a top college. If he / she doesn’t know
anything about bookkeeping and finance, his / her former knowledge on computers won’t help too
much while trying to make a financial posting on the ERP system. He / she would have to be familiar
with terms like assets, liabilities, tax-accounts, etc. On the other hand; a typical accountant with a
relatively low level of computer literacy can start understanding and using the same financial
program more efficientlyafterbeingtrained.
Computer literacy alone won’t make a skilled ERP user out of an employee. However; considering
two employees with the same level of projectinvolvement and same degree of ERP training,it makes

7. 7
sense to expect that the employee with a higher level of technical abilities would learn easier and
faster.
It is obvious that former experience on computers will have a positive impact on the learning curve
of new computer software. However; in case of an ERP system, it is not expected to result directly in
an increase in the level of perceived ease of use. It is rather expected to moderate the correlation
betweenthe level of trainingquality/involvementandthe perceivedease of use.
H4: The user’s technical abilities will moderate the correlation between the quality of training
and perceived ease of use
H4.1: Users with strong technical abilities will experience a high correlation between the
qualityof training and perceived ease of use
H4.2: Users with weak technical abilities will experience a low correlation between the
qualityof training and perceived ease of use
H5: The user’s technical abilities will moderate the correlation between the user’s level of
involvementand perceived easeof use
H5.1: Users with strong technical abilities will experience a high correlation between their
levels of involvementand perceived easeof use
H5.2: Users with weak technical abilities will experience a low correlation between their
levels of involvementand perceived easeof use
Despite the fair expectations of the users’ technical abilities to mediate the correlation between
training / involvement and perceived ease of use, it is also fair to assume that if a user doesn’t really
wantto use the ERP system,he /she can’t be expectedtoperformtaskseffectively.
The central assumption made by expectancy theory is that human behavior is the result of conscious
choices made by individuals among alternative courses of action. According to this theory, such
choices are made by the individuals with the goal of maximizing the pleasure and minimize the pain
that results from their choice (Anderson, Ones, Kepir Sinangil, & Viswesvaran, 2006). This theory
suggests that trainees have preferences among the different outcomes that can result from
participation in training. Trainees also have expectations regarding the likelihood that effort invested
intrainingwill resultinmasteryof trainingcontent (Colquitt,LePine,&Noe,2000).
In our case of an ERP system, the basic outcome of the training / involvement is somewhat the same
for all the users – gaining the ability to use the system. However, when looked deeply, does the user
believe that the ability of using the ERP system will benefit him / her? Or, from a broader vision, does
the user believe that the decision of implementing the ERP system will benefit the company at all?
Answersof these questionsare expectedtohave animpacton the user’sERP experience.
Let’s assume that there are two users with the same background, who had the same level project
involvement and same training during the project. If one of the users believes that the ability of using
the ERP system will benefit his / her own carrier and the company, he / she will try hard to get the
most out of the consultants during their time in the project. Compared to the other presumably

8. 8
neutral employee, this user will end up knowing more about the ERP system, and isexpected to have
a relativelyeasytimeusingit.
Within the scope of this vision, it can be expected that a user’s willingness of using the ERP system
shouldhave a moderatingeffectonthe resultsof projectinvolvementandtrainings.
H6: The user’s willingness of using the ERP system will moderate the correlation between the
qualityof training and perceived ease of use
H6.1: Users with a strong will of using the system will experience a high correlation
between the qualityof training and perceived easeof use
H6.2: Users with a weak will of using the system will experience a low correlation
between the qualityof training and perceived easeof use
H7: The user’s willingness of using the ERP system will moderate the correlation between the
user’slevel of involvementand perceived easeof use
H7.1: Users with a strong will of using the system will experience a high correlation
between their levels of involvementand perceived easeof use
H7.2: Users with a weak will of using the system will experience a low correlation
between their levels of involvementand perceived easeof use
Methodology
The research phase of this paper is consistent of two stages: preliminary interviews, and a
quantitative study.
Purpose of the interviews was to make sure that the dimensions and sub-dimensions mentioned in
the model are accurate. Therefore, interviews have been conducted with experienced ERP
consultants.Asa resultof thisprocess,the model andsome questionswere slightlymodified.
In the quantitative stage, the questionnaire has been posted to an Internet site, and the link was sent
to ERP users of various companies. All of these companies are using SAP as their ERP solution. The
distribution took place using the snowball technique. This means; the researcher, who is also a SAP
consultant himself, has sent the link of the questionnaire to all of his customers, and also to other
SAP consultants so that they forward to their own customers. All of the messaging process was
conductedviaE-Mail.
This technique may attain criticism at the first sight. However; SAP is a computer based system.
Therefore, all of SAP users are guaranteed to spend at least half of their working time on their
computers; and they already have instinctive knowledge about E-Mail and Internet usage. There are
around 600 SAP consultants in Turkey, and approximately 70 of them were involved in the snowball
process. As a result, 198 answers were collected. After eliminating not applicable entries, a sum of
177 entrieswere left.
Ease of Use and Utilization

9. 9
To measure the perceived ease of use and its correlation with system utilization, the Technology
Acceptance Model (Davis, 1989) has been used. The Technology Acceptance Model (TAM) is an
information systems theory that models how users come to accept and use a technology. The model
suggests that when users are presented with a new software package, a number of factors influence
their decision about how and when they will use it (Wikipedia, 2008). TAM is considered as the
extensionof AjzenandFishbein’s“Theoryof ReasonedAction”(TRA).
The original TAMtool has been slightly modified to make sure that the questions match the ERP area.
The sample questions in the original tool were targeting an E-Mail system. The E-Mail related
sentenceswere replacedwithERP-relatedcontent.
Here is an exactlistof the questions,wherea6-scale Likert-Style answerwasexpected.
Ease of Use
I often become confusedwhenIuse SAP
I make errorsfrequentlywhenusingSAP
lnteractingwithSAPisoftenfrustrating
I needtoconsultthe documentationoften whenusingSAP
lnteractingwithSAPrequiresalotof mymental effort
I finditeasyto recoverfromerrors encounteredwhileusingSAP
SAPis rigid andinflexible tointeractwith
I finditeasyto get SAPto do whatI wantit to do
SAPoftenbehavesin unexpectedways
I finditcumbersome touse SAP
My interactionwithSAPiseasyforme to understand
It iseasyfor me to remember how toperformtasksusingSAP
SAPprovideshelpful guidance inperforming tasks
Overall,IfindSAPeasytouse
Utilization
I personallyuse SAPtoperformmydailytasks
I am dependentonSAP
I am satisfiedwithmydailySAPexperience
SAPhas a large,positive impactonmyeffectivenessandproductivityinmyjob
SAPis an importantandvaluable aidtome in the performance of myjob.
Training Quality
The quality of the training has been measured using a modified version of the “Kirkpatrick Model”
(Kirkpatrick, 2006). The "Kirkpatrick Model" for evaluating training programs is the most widely used
approach in the corporate, government, and academic worlds. First developed in 1959, it focuses on
fourkeyareas: reaction,learning,behavior,andresults.
Here is an exactlistof the questions,wherea6-scale Likert-Style answerwasexpected.
Contentof program waspractical
The leaderwaseffective
Schedule of sessionwasappropriate

10. 10
Facilitieswereappropriate
Size of group wasconductive forlearning
I understandhowtoapplywhatI learnedtomy job
I do notanticipate barriersinapplying whatIlearned
I was satisfiedwiththe session
I wouldrecommendthissessiontoothers
Overall,myimpressionof thiscourse wasexcellent
The course objectiveswere clearlystatedandusedunderstandable terms
Thiscourse met the definedobjectives
Both the facilityandequipmentusedmetall needsof the course
The course materialswere bothuseful andeasytofollow
The instructorsdemonstratedthoroughknowledge andunderstandingof the topic
The instructorspresentedinformationinaclear,understandable andprofessional manner
The amount of time scheduledforthiscourse wasexactlywhatwasneededtomeetthe
objectives
Thiscourse relateddirectlytomycurrentjob responsibilities
Involvement, Ability, Willingness
To measure the user’s abilities, willingness and level of involvement in the ERP implementation
project, a custom questionnaire has been developed based upon former experience on ERP projects.
This questionnaire has also been discussed among experienced ERP consultants, and was modified to
itscurrent state.
Involvement
What isyour role inthe ERP project?(N/A,User,KeyUser,ProjectManager)
To what extentdidyouparticipate the project?(None,onlytrainings,occasionally,more
than half of my workingtime at daysconsultantswere here)
Whichphasesdidyouparticipate?(As-Is,To-Be,Blue PrintPreparation,Implementation,
Tests,Trainings,Go-Live)
Are you currentlyusingSAP?(Yes/No)
Ability
Level of education(Primaryschool,Middle school,Highschool,College,Master,PhD)
Graduatedfroma technical school (Yes/No)
I have usedSAPor a similarERPsystembefore (Yes/No)
Willingness
I believethatusingSAPwill benefitmycompany(Likert-Style)
I believethatusingSAPwill benefitmyowncarrier(Likert-Style)
Results
To test the study hypotheses, linear regression analyses have been conducted. Anova and T-Test
analysistechniqueshave alsobeenused. Here isthe demographicprofile of attendedemployees.

11. 11
Gender
57 32,2 32,2 32,2
120 67,8 67,8 100,0
177 100,0 100,0
Female
Male
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent
Incom e Level (YTL)
2 1,1 1,1 1,1
7 4,0 4,0 5,1
82 46,3 46,3 51,4
58 32,8 32,8 84,2
26 14,7 14,7 98,9
2 1,1 1,1 100,0
177 100,0 100,0
< 500
500-1000
1000-3000
3000-5000
5000-10000
> 10000
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent
Marital Status
75 42,4 42,4 42,4
100 56,5 56,5 98,9
2 1,1 1,1 100,0
177 100,0 100,0
Married
Single
Divorced
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent
Graduated From
12 6,8 6,8 6,8
133 75,1 75,1 81,9
31 17,5 17,5 99,4
1 ,6 ,6 100,0
177 100,0 100,0
High School
College
Master
PhD
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent
Technical Education
115 65,0 65,0 65,0
62 35,0 35,0 100,0
177 100,0 100,0
Technical Faculty
Non-Technical Faculty
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent

12. 12
After collecting the data, answers to negative questions have been transformed into the opposite
direction of the Likert scale. As usual in linear regression analysis; at the first step, a data reduction
progress has been conducted and questions corresponding to various variables have been grouped
into factors. At this stage, the Utilization and Willingness variables have been resolved into a pair of
single factors.
Perceived ease of use has been differentiated into two factors: Confusion and User-Friendliness.
Confusion is related to the extent in which the user gets confused, makes mistakes, needs to consult
documentation, etc when using SAP. User-Friendliness is the area involving factors like the level of
easiness of error-recovery, ease of modifying SAP’s behavior, usability, understandability and the
qualityof internal guidance of the software.
Training variable has also been differentiated into two factors: Content Satisfaction and Context
Satisfaction. Content satisfaction involves questions about the employee’s satisfaction of the
transferred knowledge. It simply reflects how successful the trainer was. Context satisfaction involves
questions about the physical trainingenvironment. It reflects contextual factors such as the accuracy
of timing,suitabilityof the trainingmaterials,etc.
Variable Factor Variance Reliability
Perceived Ease of
Use
Confusion 34,8% 85,6%
User-Friendliness 27,7% 82,3%
Training Content
Satisfaction
43,9% 95,3%
Context
Satisfaction
27,3% 86,3%
Utilization SystemUtilization 100% 90%
Willingness Willingness 100% 77,5%
In terms of user-friendliness, SAP seems to have a positive impression on employees. On the 6-item
Likertscale,meanof Confusion2
is4.33 and User-Friendlinessis4.22.
2 Note that answers to negative questions had been reversed; so 6 would mean that no one is confused at all
Age Interval
29 16,4 16,4 16,4
61 34,5 34,5 50,8
57 32,2 32,2 83,1
16 9,0 9,0 92,1
7 4,0 4,0 96,0
7 4,0 4,0 100,0
177 100,0 100,0
20-26
26-32
32-38
38-44
44-50
50-56
Total
Valid
Frequency Percent Valid Percent
Cumulative
Percent

13. 13
The first hypothesis, indicating that perceived ease of use of an ERP system will have a positive effect
on utilization of the ERP system, has been supported in this research - between the factors User-
Friendliness and System Utilization (β = 0.528, R2
= 0.275). This result was also supported in former
studiesmentionedpreviously (Kwahk,2006).
The second hypothesis, indicating that there is a positive correlation between the quality of the
training and the user’s perceived ease of use, has been partly supported. The first significant
correlation that has been found is between the factors Content Satisfaction and Confusion (β =
0.272, R2
= 0.069). However, no scientific support has been found for the moderating effect of
Willingness.
Statistics
177 177
0 0
4,3376 4,2250
4,5000 4,3333
5,00 4,83
767,75 747,83
Valid
Missing
N
Mean
Median
Mode
Sum
EAS_CONF EAS_USER
Model Summ aryb
,528a
,279 ,275 ,90797
Model
1
R R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), EAS_USERa.
Dependent Variable: UTILIZATIONb.
ANOVAb
55,786 1 55,786 67,667 ,000a
144,272 175 ,824
200,057 176
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), EAS_USERa.
Dependent Variable: UTILIZATIONb.
Coefficientsa
1,926 ,331 5,822 ,000
,630 ,077 ,528 8,226 ,000
(Constant)
EAS_USER
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: UTILIZATIONa.

14. 14
The second significant correlation is between the factors Content Satisfaction and User-Friendliness
(β = 0.427, R2
= 0.182). There is also significant evidence of the moderating effect of the Willingness
in-between. The values for employees with relatively low willingness are β = 0.371, R2
= 0.123, Sig. =
0.003; and the values for employees with relatively high willingness are β = 0.314, R2
= 0.090, Sig. =
0.001. However;nosignificantcorrelationinvolvingContextSatisfactionhasbeenfound.
Model Summ aryb
,272a
,074 ,069 ,94382
Model
1
R R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), EDU_CONTENTa.
Dependent Variable: EAS_CONFb.
ANOVAb
12,503 1 12,503 14,036 ,000a
155,890 175 ,891
168,393 176
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), EDU_CONTENTa.
Dependent Variable: EAS_CONFb.
Coefficientsa
3,092 ,340 9,092 ,000
,275 ,073 ,272 3,746 ,000
(Constant)
EDU_CONTENT
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: EAS_CONFa.
Model Summ aryb
,427a
,182 ,177 ,81022
Model
1
R R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), EDU_CONTENTa.
Dependent Variable: EAS_USERb.
ANOVAb
25,571 1 25,571 38,953 ,000a
114,881 175 ,656
140,452 176
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), EDU_CONTENTa.
Dependent Variable: EAS_USERb.

15. 15
The third hypothesis, suggesting a positive correlation between the user’s level of involvement and
perceived ease of use, has been partly supported. The results of the conducted Anova tests show
that confusion level varies depending upon the employee’s role in the project. The most significant
confusion difference is observed within employees who didn’t participate the project at all, or who
had a non-standardrole atthe project;such as networkadministration.
Coefficientsa
2,443 ,292 8,370 ,000
,394 ,063 ,427 6,241 ,000
(Constant)
EDU_CONTENT
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: EAS_USERa.
Test of Homogeneity of Variances
EAS_CONF
1,856 4 172 ,120
Levene
Statistic df1 df2 Sig.
ANOVA
EAS_CONF
19,085 4 4,771 5,496 ,000
149,308 172 ,868
168,393 176
Betw een Groups
Within Groups
Total
Sum of
Squares df Mean Square F Sig.

16. 16
There is also significant relationship between ERP usage and both confusion & user friendliness.
Apparently; active ERP users find the system more user-friendly and less confusing. However; no
correlation has been found between user’s role in the project and perceived user-friendliness of the
ERP System.
Multiple Com parisons
Dependent Variable: EAS_CONF
-1,04122* ,35634 ,032 -2,0236 -,0588
-,66047 ,34676 ,319 -1,6165 ,2955
-,63942 ,37669 ,438 -1,6779 ,3991
-,02841 ,38466 1,000 -1,0889 1,0321
1,04122* ,35634 ,032 ,0588 2,0236
,38075 ,17378 ,188 -,0984 ,8599
,40180 ,22772 ,398 -,2260 1,0296
1,01281* ,24068 ,000 ,3493 1,6764
,66047 ,34676 ,319 -,2955 1,6165
-,38075 ,17378 ,188 -,8599 ,0984
,02105 ,21241 1,000 -,5645 ,6066
,63206* ,22625 ,045 ,0083 1,2558
,63942 ,37669 ,438 -,3991 1,6779
-,40180 ,22772 ,398 -1,0296 ,2260
-,02105 ,21241 1,000 -,6066 ,5645
,61101 ,26990 ,162 -,1331 1,3551
,02841 ,38466 1,000 -1,0321 1,0889
-1,01281* ,24068 ,000 -1,6764 -,3493
-,63206* ,22625 ,045 -1,2558 -,0083
-,61101 ,26990 ,162 -1,3551 ,1331
-1,04122 ,35634 ,079 -2,1509 ,0684
-,66047 ,34676 ,461 -1,7403 ,4193
-,63942 ,37669 ,579 -1,8124 ,5336
-,02841 ,38466 1,000 -1,2262 1,1694
1,04122 ,35634 ,079 -,0684 2,1509
,38075 ,17378 ,313 -,1604 ,9219
,40180 ,22772 ,541 -,3073 1,1109
1,01281* ,24068 ,002 ,2633 1,7623
,66047 ,34676 ,461 -,4193 1,7403
-,38075 ,17378 ,313 -,9219 ,1604
,02105 ,21241 1,000 -,6404 ,6825
,63206 ,22625 ,104 -,0725 1,3366
,63942 ,37669 ,579 -,5336 1,8124
-,40180 ,22772 ,541 -1,1109 ,3073
-,02105 ,21241 1,000 -,6825 ,6404
,61101 ,26990 ,279 -,2294 1,4515
,02841 ,38466 1,000 -1,1694 1,2262
-1,01281* ,24068 ,002 -1,7623 -,2633
-,63206 ,22625 ,104 -1,3366 ,0725
-,61101 ,26990 ,279 -1,4515 ,2294
(J) INV01
User
Key User
Project Manager
Other
No Participation
Key User
Project Manager
Other
No Participation
User
Project Manager
Other
No Participation
User
Key User
Other
No Participation
User
Key User
Project Manager
User
Key User
Project Manager
Other
No Participation
Key User
Project Manager
Other
No Participation
User
Project Manager
Other
No Participation
User
Key User
Other
No Participation
User
Key User
Project Manager
(I) INV01
No Participation
User
Key User
Project Manager
Other
No Participation
User
Key User
Project Manager
Other
Tukey HSD
Scheffe
Mean
Difference
(I-J) Std. Error Sig. Low er Bound Upper Bound
95% Confidence Interval
The mean difference is significant at the .05 level.*.
Group Statistics
165 4,3409 ,97260 ,07572
12 4,2917 1,09665 ,31658
165 4,2263 ,89997 ,07006
12 4,2083 ,83220 ,24023
Currently Using SAP
Yes
No
Yes
No
EAS_CONF
EAS_USER
N Mean Std. Deviation
Std. Error
Mean

17. 17
There are also some unforeseen results. Significant and direct correlation has been found between
WillingnessandUtilization(β=0.521, R2
= 0.267).
Another unexpected result is the direct correlation between Willingness and User-Friendliness (β =
0.458, R2
= 0.205).
Independent Samples Test
,134 ,715 ,168 175 ,867 ,04924 ,29327 -,52955 ,62804
,151 12,292 ,882 ,04924 ,32551 -,65811 ,75660
,182 ,671 ,067 175 ,947 ,01793 ,26785 -,51071 ,54656
,072 12,945 ,944 ,01793 ,25024 -,52292 ,55878
Equal variances
assumed
Equal variances
not assumed
Equal variances
assumed
Equal variances
not assumed
EAS_CONF
EAS_USER
F Sig.
Levene's Test for
Equality of Variances
t df Sig. (2-tailed)
Mean
Difference
Std. Error
Difference Low er Upper
95% Confidence
Interval of the
Difference
t-test for Equality of Means
Model Summ aryb
,521a
,271 ,267 ,91287
Model
1
R R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), WILLINGNESSa.
Dependent Variable: UTILIZATIONb.
ANOVAb
54,225 1 54,225 65,071 ,000a
145,832 175 ,833
200,057 176
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), WILLINGNESSa.
Dependent Variable: UTILIZATIONb.
Coefficientsa
,747 ,481 1,552 ,123
,709 ,088 ,521 8,067 ,000
(Constant)
WILLINGNESS
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: UTILIZATIONa.

18. 18
Discussion
Although not the main focus of this paper, the demographic results represent significant support that
there are more male SAP users than female ones; almost half of ERP users are single, and
approximately 75% of them are graduated from college. Most of the employees are less than 38
yearsold.
In terms of user-friendliness, SAP seems to be on a fairly good level. Approximate Ease-Of-Use score
of the systemis75%; whichcan be evaluatedas agood score for a verycomplex ERPsystem.
The correlation between user-friendliness and system utilization had been supported in previous
researches as well (Kwahk, 2006). The same result has been duplicated in this paper. This result
indicates that the more user-friendly SAP is perceived, the more it’s going to be accepted in the
company. Therefore, managers can seek ways to transform the expected resistance and hard-to-use
prophecytowardsthe ERP systemintoa climate where peoplefinditeasytouse anduser-friendly.
But how? Another result answers this question by suggesting a correlation between the employee’s
content satisfaction of the training and his / her perceived ease of use. This means; the more the
employee is satisfied with the content of the ERP training, the more user-friendly and less confusing
he / she will perceive the system. This should ring some bells for managers. In this scope, their
responsibility is to make sure that the employees get a high-quality and efficient training. Many
techniques and models have been suggested to measure and increase the training quality, which are
beyond the scope of this paper. However; as mentioned before, Kirkpatrick’s evaluation model can
Model Summ aryb
,458a
,209 ,205 ,79655
Model
1
R R Square
Adjusted
R Square
Std. Error of
the Estimate
Predictors: (Constant), WILLINGNESSa.
Dependent Variable: EAS_USERb.
ANOVAb
29,415 1 29,415 46,359 ,000a
111,037 175 ,634
140,452 176
Regression
Residual
Total
Model
1
Sum of
Squares df Mean Square F Sig.
Predictors: (Constant), WILLINGNESSa.
Dependent Variable: EAS_USERb.
Coefficientsa
1,395 ,420 3,323 ,001
,523 ,077 ,458 6,809 ,000
(Constant)
WILLINGNESS
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: EAS_USERa.

19. 19
be suggested as a good starting point (Kirkpatrick, 2006). If the manager has doubts about the quality
of the training, he / she should not hesitate to ask the consulting company to provide another one
withan increasedquality.
There is also scientific support that the employee’s actual willingness has a significant effect on the
user-friendliness perception, as well as system utilization. Employees willing to use the system tend
to perceive SAP as user-friendly more easily than employees not willing to use it. This is another
important implication for managers, suggesting that employees should be persuaded in the
usefulness of the system to the company, as well as their own careers. Some incentives upon a
successful go-live may also help. If the employees genuinely want to use the system, they will use it
and perceive itasmore user-friendly.
Another implication is the employee’s role in the project and their level of confusion. Only
employees who never participate the project (as user, project manager, key user, etc) find SAP
confusing. Employees with non-standard roles also reported the system to be confusing; however,
upon closer inspection, it came out that most of those were technical people whose responsibilities
were network administration, user authorization management, etc. Therefore, they can also be
evaluatedamongthe employeeswhodidnotparticipate the project.
The significant relationship between active ERP-Usage and level of perceived ease of use also
supports this implication. If a user sees the SAP GUI3
for the first time during a formal training one
week before go-live, it is very natural for him / her to find it confusing. The implication for managers
is; people need to be involved with SAP from time to time during the project. They don’t need to
participate meetings or decisions; but still, they can be involved in the system with scheduled get-to-
know workshops several times before the formal training. If the workshops are conducted by key
users, these organizations could allow end-users to get to know the system better before the
training, and key users will have the chance to re-study their material. During these sessions,
valuable feedback may also be collected from end-users when the company still has time to change
thingsinthe project.
Another suggestion is to make end-users participate the project with a supporting role rotatively. If
each end user joins key users a couple of times during the project, key users will be happy to share
theirworkloadandenduserswill gettohave hands-onexperience before the formal training.
Like any study, this paper is not without its limitations. First of all, the study has been made among
SAP users. Therefore, further research may be required before generalizing the results towards the
whole ERP concept. Most, if not all, of the users participating the questionnaire are living in Istanbul /
Turkey. Because socio-economic and cultural status of Turkey may have an impact on the results, the
research may need to be repeated in different countries as well – before generalizing the findings as
cross-cultural.
Some of the users declared in personal feedback that they had their training a long time ago. This
may bring the risk that they can’t evaluate the training as accurately as other people who
participated their ERP training a short time ago. In the ideal case, training evaluation should be made
3 Graphical user interface

20. 20
right after the training took place. However; because this was not possible within the scope of this
research,itturns outto be one of its limitations.
The questionnaire of ability, willingness and involvement are made of custom-developed questions.
Although they were validated by experienced ERP consultants, they did not pass through the test of
time. On the other hand; other instruments used here (such as TAM and Kirkpatrick Model) have
passed through the test of time and they had been used in various researches with success. Although
this may not be a problem, there is a possibility that the custom-developed questionnaires interfere
withthe borrowedones;andthisisanotherlimitationof thisresearch.
Acknowledging that ERP systems continue to grow with promising potential benefits, this study has
value for theoretical as well as practical development; while several avenues for future research
remain.
Bibliography
Anderson,N.,Ones,D.S.,KepirSinangil,H.,&Viswesvaran,C.(2006). Handbookof Industrial,Work
& OrganizationalPsychology (Vols.I,II).California:SAGE.
Arntz,W., Chasse,B.,& Vicente,M.(2008). What The Bleep Do We Know. (M. Sağlam, Trans.)
İstanbul,Turkey:İstanbul.
C. A.(2007). Kirkpatrick'sLearning and Training Evaluation Theory. Retrieved323, 2008, from
BusinessBalls.com:http://www.businessballs.com/kirkpatricklearningevaluationmodel.htm
Case WesternReserve University.(2004,July5). Enterprise ResourcePlanning.Retrieved42, 2008,
fromCase WesternReserve University: http://www.case.edu/projects/erp/projectdetails.html
Colquitt,J.A.,LePine,J.A.,&Noe,R.A. (2000). Towardan Integrative Theoryof TrainingMotivation:
A Meta-AnalyticPathAnalysisof 20 Yearsof Research. Journalof Applied Psychology ,85 (5),678-
707.
CoursesbyWire.(2007, 2). Evaluating Training Effectiveness - Kirkpatrick'sFourLevels. Retrieved3
23, 2008, fromCoursesbyWire:
http://www.coursesbywire.com/Articles/Evaluating%20Training%20Effectiveness%20-
%20Kirkpatrick's%20Four%20Levels.pdf
Davis,F. D. (1989). PerceivedUsefulness,PerceivedEase of Use,and User Acceptance of Information
Technology. MISQuarterly ,13 (3),319-340.
Draffan,G. (2007, February). Abilityand Willingness. RetrievedApril 27,2008, fromNatural
Awareness:http://www.naturalawareness.net/ability%20and%20willingness.pdf
Goodhue,D.L., & Thompson,R. L. (1995). Task-TechnologyFitandIndividual Performance. MIS
Quarterly (ManagementInformationSystemsResearchCenter,Universityof Minnesota),213-236.
Karat, J.,& Dayton,T. (1995). Practical Education forImproving SoftwareUsability. RetrievedJune 27,
2008, fromSIGCHI: http://sigchi.org/chi95/proceedings/papers/jk_bdy.htm

21. 21
Kirkpatrick,D.L. (2006). Evaluating Training Programs:TheFourLevels. Retrieved 323, 2008, from
ASTD: http://astd2006.astd.org/PDF's/Handouts%20-%20SECURED/M102.pdf
Kruse,K.(n.d.). Evaluating e-Learning:Introduction to theKirkpatrickModel. Retrieved323, 2008,
fromE-LearningGuru: http://www.e-learningguru.com/articles/art2_8.htm
Kwahk,K.-Y.(2006). ERP Acceptance:Organizational ChangePerspective. HawaiiInternational
Conferenceon SystemSciences,(pp.1-10). Hawaii.
MicrosoftCorporation.(2006). MicrosoftDynamicsSureStep Methodology. RetrievedApril 27,2008,
fromDiscoverDynamics:
http://discoverdynamics.co.uk/downloads/implementation/Sure_Step_Methodology_Overview_Dia
gram.pdf
Rai,A., Lang,S. S.,& Welker,R.B. (2002). Assessingthe Validityof ISSuccessModels:AnEmpirical
TestandTheoretical Analysis. Information SystemsResearch ,13 (1), 50-69.
Ramanathan,S.,& Bhatia,A.(n.d.). ERPProjectCycle. Retrieved42, 2008, from ITToolbox:
http://wiki.ittoolbox.com/index.php/ERP_Project_Cycle
Shang,S., & Seddon,P.B.(n.d.). A ComprehensiveFrameworkfor Classifying theBenefitsof ERP
Systems. RetrievedApril27,2008, fromUniversityof Melbourne:
http://www.dis.unimelb.edu.au/staff/peter/research/AMCIS2000ClassifyingTheBenefitsOfERPSyste
ms.doc
Sia,S. K.,Tang, M., Soh,C., & Boh, W. F.(2002). Enterprise Resource Planning(ERP) Systemsasa
Technologyof Power:EmpowermentorPanopticControl? TheData Basefor Advancesin
Information Systems ,33 (1),23-37.
Wikipedia.(2008,March 3). ComputerLiteracy. RetrievedJune 27,2008, fromWikipedia:
http://en.wikipedia.org/wiki/Computer_literacy
Wikipedia.(2008,2 8). Technology AcceptanceModel. Retrieved323, 2008, fromWikipedia:
http://en.wikipedia.org/wiki/Technology_acceptance_model
Zin,N.A., Zaman,H. B., Judi,H.M., Mukti,N.A.,Amin,H. M., Sahran,S., etal. (2000). Gender
DifferencesinComputerLiteracyLevelAmongUndergraduateStudentsinUniversityKebangsaan
Malaysia. The Electronic Journalon Information Systemsin Developing Countries ,1-8.