Correlation Between Proper Training / Involvement and ERP Acceptance and the Mediating Effects of Motivation

Correlation Between Proper Training / Involvement and ERP Acceptance and the Mediating Effects of Ability & Willingness Kerem Köseoğlu

Yeditepe University

AbstractThis 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 have a moderating effect.

This paper adopts a quantitative study among the employees of companies using ERP, and includes questionnaires and statistical analysis to see if the hypothesis were supported or not.

Keywords: Enterprise Resource Planning, ERP, Enterprise System, Utilization, Training, Involvement, Ease of Use, Motivation, Ability, Willingness

IntroductionERP 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 organization will be affected by that.

In this scope, a manager may ask himself the following question: “What should I do to increase the level of utilization of our new ERP 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 system will increase.

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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 should appear as one of the factors affecting the utilization of 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) and the moderating effects of motivation in-between.

What Is ERPERP 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 Western Reserve University, 2004).

ERP is not a new concept. ERP systems are being developed since more than 30 years, and companies have been using them ever since. An ERP system is very promising in 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, each ERP implementation is considered as a project.

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 parties are divided into the following roles (Microsoft Corporation, 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 participates in design of modifications, develops and unit tests modifications.

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

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functions, can describe business processes, helps configure & test the system and trains end users. An end user supports the system test and uses the system once implemented.

A typical project will have the following stages (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 insight about what the software is capable of.

Requirement Analysis (To-Be): The requirements of the customers are analyzed in great detail. Alternative solutions are analyzed, and development requirements are discovered.

Blue Print Approval: This is the stage where the customer and the consulting company agree on the target solution. Results of the analysis are documented and signed by both parties.

Implementation: Customizations and developments are carried out. Minor misunderstandings and change requests of the blue print can be tolerated during this stage.

Testing: As customizations and developments are completed, the key users set out to test the system to make sure that it works as intended and that it satisfies the 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. This includes, but is not limited to, material master data, chart of 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 support on the site to make sure that everything is running smoothly.

Conceptual Background and Hypotheses

Perceived Ease of Use and UtilizationPerceived ease 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 been integrated 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

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another is more likely to be accepted by users. The more useful and the easier to use an ERP system in enabling employees to accomplish their tasks, the more it will 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 system utilization

H1.2: A decrease of the perceived level of ease of use of an ERP system will decrease the level of system utilization

Training / Involvement and Perceived Ease of UseBeing 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 employees so that they will know how to use the system to perform their job-related tasks.

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 an easy time using the tool to perform job-related tasks.

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 training are expected to perceive the system as “hard to use”.

H2: There is a positive correlation between the quality of the training and the user’s perceived ease of use

1 Graphical User Interface

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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 is another one.

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 backyard meanwhile, he will be a better rider at the end of 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 system easy to use. Because the level of practical experience will increase with the actual level of

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project involvement; an increase of perceived ease of use is expected as a result of an increased level 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 WillingnessAbility 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 computer literacy.

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 skills is a significant asset in the developed countries (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 efficiently after being trained.

Computer literacy alone won’t make a skilled ERP user out of an employee. However; considering two employees with the same level of project involvement and same degree of ERP training, it makes

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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 between the level of training quality / involvement and the perceived ease 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 quality of training and perceived ease of use

H4.2: Users with weak technical abilities will experience a low correlation between the quality of training and perceived ease of use

H5: The user’s technical abilities will moderate the correlation between the user’s level of involvement and perceived ease of use

H5.1: Users with strong technical abilities will experience a high correlation between their levels of involvement and perceived ease of use

H5.2: Users with weak technical abilities will experience a low correlation between their levels of involvement and perceived ease of 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 want to use the ERP system, he / she can’t be expected to perform tasks effectively.

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 in training will result in mastery of training content (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? Answers of these questions are expected to have an impact on the user’s ERP 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

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neutral employee, this user will end up knowing more about the ERP system, and is expected to have a relatively easy time using it.

Within the scope of this vision, it can be expected that a user’s willingness of using the ERP system should have a moderating effect on the results of project involvement and trainings.

H6: The user’s willingness of using the ERP system will moderate the correlation between the quality of training and perceived ease of use

H6.1: Users with a strong will of using the system will experience a high correlation between the quality of training and perceived ease of use

H6.2: Users with a weak will of using the system will experience a low correlation between the quality of training and perceived ease of use

H7: The user’s willingness of using the ERP system will moderate the correlation between the user’s level of involvement and perceived ease of use

H7.1: Users with a strong will of using the system will experience a high correlation between their levels of involvement and perceived ease of use

H7.2: Users with a weak will of using the system will experience a low correlation between their levels of involvement and perceived ease of use

MethodologyThe 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. As a result of this process, the model and some questions were slightly modified.

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 conducted via E-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 entries were left.

Ease of Use and Utilization

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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 extension of Ajzen and Fishbein’s “Theory of Reasoned Action” (TRA).

The original TAM tool 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 sentences were replaced with ERP-related content.

Here is an exact list of the questions, where a 6-scale Likert-Style answer was expected.

Ease of UseI often become confused when I use SAPI make errors frequently when using SAPlnteracting with SAP is often frustratingI need to consult the documentation often when using SAPlnteracting with SAP requires a lot of my mental effortI find it easy to recover from errors encountered while using SAPSAP is rigid and inflexible to interact withI find it easy to get SAP to do what I want it to doSAP often behaves in unexpected waysI find it cumbersome to use SAPMy interaction with SAP is easy for me to understandIt is easy for me to remember how to perform tasks using SAPSAP provides helpful guidance in performing tasksOverall, I find SAP easy to use

UtilizationI personally use SAP to perform my daily tasksI am dependent on SAPI am satisfied with my daily SAP experienceSAP has a large, positive impact on my effectiveness and productivity in my jobSAP is an important and valuable aid to me in the performance of my job.

Training QualityThe 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 four key areas: reaction, learning, behavior, and results.

Here is an exact list of the questions, where a 6-scale Likert-Style answer was expected.

Content of program was practicalThe leader was effectiveSchedule of session was appropriate

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Facilities were appropriateSize of group was conductive for learningI understand how to apply what I learned to my jobI do not anticipate barriers in applying what I learnedI was satisfied with the sessionI would recommend this session to othersOverall, my impression of this course was excellentThe course objectives were clearly stated and used understandable termsThis course met the defined objectivesBoth the facility and equipment used met all needs of the courseThe course materials were both useful and easy to followThe instructors demonstrated thorough knowledge and understanding of the topicThe instructors presented information in a clear, understandable and professional mannerThe amount of time scheduled for this course was exactly what was needed to meet the objectivesThis course related directly to my current job responsibilities

Involvement, Ability, WillingnessTo 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 its current state.

InvolvementWhat is your role in the ERP project? (N/A, User, Key User, Project Manager)To what extent did you participate the project? (None, only trainings, occasionally, more than half of my working time at days consultants were here)Which phases did you participate? (As-Is, To-Be, Blue Print Preparation, Implementation, Tests, Trainings, Go-Live)Are you currently using SAP? (Yes / No)

AbilityLevel of education (Primary school, Middle school, High school, College, Master, PhD)Graduated from a technical school (Yes / No)I have used SAP or a similar ERP system before (Yes / No)

WillingnessI believe that using SAP will benefit my company (Likert-Style)I believe that using SAP will benefit my own carrier (Likert-Style)

ResultsTo test the study hypotheses, linear regression analyses have been conducted. Anova and T-Test analysis techniques have also been used. Here is the demographic profile of attended employees.

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Gender

57 32,2 32,2 32,2

120 67,8 67,8 100,0

177 100,0 100,0

Female

Male

Total

ValidFrequency Percent Valid Percent

CumulativePercent

Income 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


CumulativePercent

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


CumulativePercent

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


CumulativePercent

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


CumulativePercent

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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


CumulativePercent

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 quality of 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 training environment. It reflects contextual factors such as the accuracy of timing, suitability of the training materials, etc.

Variable Factor Variance ReliabilityPerceived Ease of Use

Confusion 34,8% 85,6%

User-Friendliness 27,7% 82,3%Training Content

Satisfaction43,9% 95,3%

Context Satisfaction

27,3% 86,3%

Utilization System Utilization 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 Likert scale, mean of Confusion2 is 4.33 and User-Friendliness is 4.22.

2 Note that answers to negative questions had been reversed; so 6 would mean that no one is confused at all

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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

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 studies mentioned previously (Kwahk, 2006).

Model Summaryb

,528a ,279 ,275 ,90797Model1

R R SquareAdjustedR Square

Std. Error ofthe 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

Model1

Sum ofSquares df Mean Square F Sig.

Predictors: (Constant), EAS_USERa.


Coefficientsa

1,926 ,331 5,822 ,000

,630 ,077 ,528 8,226 ,000

(Constant)

EAS_USER

Model1

B Std. Error

UnstandardizedCoefficients

Beta

StandardizedCoefficients

t Sig.

Dependent Variable: UTILIZATIONa.

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.

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Model Summaryb

,272a ,074 ,069 ,94382Model1



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

Model1



Dependent Variable: EAS_CONFb.

Coefficientsa

3,092 ,340 9,092 ,000

,275 ,073 ,272 3,746 ,000

(Constant)

EDU_CONTENT

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: EAS_CONFa.

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; no significant correlation involving Context Satisfaction has been found.

Model Summaryb

,427a ,182 ,177 ,81022Model1




Dependent Variable: EAS_USERb.

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ANOVAb

25,571 1 25,571 38,953 ,000a

114,881 175 ,656

140,452 176

Regression

Residual

Total

Model1




Coefficientsa

2,443 ,292 8,370 ,000

,394 ,063 ,427 6,241 ,000

(Constant)

EDU_CONTENT

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: EAS_USERa.

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-standard role at the project; such as network administration.

Test of Homogeneity of Variances

EAS_CONF

1,856 4 172 ,120

LeveneStatistic df1 df2 Sig.

ANOVA

EAS_CONF

19,085 4 4,771 5,496 ,000

149,308 172 ,868

168,393 176

Between Groups

Within Groups

Total


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Multiple Comparisons

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) INV01User

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) INV01No Participation

User

Key User

Project Manager

Other

No Participation

User

Key User

Project Manager

Other

Tukey HSD

Scheffe

MeanDifference

(I-J) Std. Error Sig. Lower Bound Upper Bound

95% Confidence Interval

The mean difference is significant at the .05 level.*.

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.

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 SAPYes

No

Yes

No

EAS_CONF

EAS_USER

N Mean Std. DeviationStd. Error

Mean

16

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 variancesassumed

Equal variancesnot assumedEqual variancesassumedEqual variancesnot assumed

EAS_CONF

EAS_USER

F Sig.

Levene's Test forEquality of Variances

t df Sig. (2-tailed)Mean

DifferenceStd. ErrorDifference Lower Upper

95% ConfidenceInterval of the

Difference

t-test for Equality of Means

There are also some unforeseen results. Significant and direct correlation has been found between Willingness and Utilization (β = 0.521, R2 = 0.267).

Model Summaryb

,521a ,271 ,267 ,91287Model1



Predictors: (Constant), WILLINGNESSa.


ANOVAb

54,225 1 54,225 65,071 ,000a

145,832 175 ,833

200,057 176

Regression

Residual

Total

Model1




Coefficientsa

,747 ,481 1,552 ,123

,709 ,088 ,521 8,067 ,000

(Constant)

WILLINGNESS

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: UTILIZATIONa.

Another unexpected result is the direct correlation between Willingness and User-Friendliness (β = 0.458, R2 = 0.205).

17

Model Summaryb

,458a ,209 ,205 ,79655Model1





ANOVAb

29,415 1 29,415 46,359 ,000a

111,037 175 ,634

140,452 176

Regression

Residual

Total

Model1




Coefficientsa

1,395 ,420 3,323 ,001

,523 ,077 ,458 6,809 ,000

(Constant)

WILLINGNESS

Model1

B Std. Error


Beta


t Sig.

Dependent Variable: EAS_USERa.

DiscussionAlthough 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 years old.

In terms of user-friendliness, SAP seems to be on a fairly good level. Approximate Ease-Of-Use score of the system is 75%; which can be evaluated as a good score for a very complex ERP system.

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 prophecy towards the ERP system into a climate where people find it easy to use and user-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

18

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 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 with an increased quality.

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 it as more 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 evaluated among the employees who did not participate 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 things in the 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 their workload and end users will get to have hands-on experience 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

19

right after the training took place. However; because this was not possible within the scope of this research, it turns out to 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 with the borrowed ones; and this is another limitation of this research.

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.

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Documents

Correlation Between Proper Training / Involvement and ERP Acceptance and the Mediating Effects of Motivation