“Measuring ERP success: evaluation

and selection criteria by North Greek

SMEs”

Supervisor: Dr A. Mandilas

MSc student: MARIA KATSWNI

Kavala 2011

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Special thanks to Dr A. Mandilas

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Table of Contents

Abstract ...................................................................................................................................... 5

Introduction .............................................................................................................................. 6

1.1 Aims and objectives ........................................................................................................... 6

1.2 Dissertation structure ......................................................................................................... 6

Literature Review ..................................................................................................................... 9

2.1 Introduction ........................................................................................................................ 9

2.2 Enterprise Resource Planning systems (ERP) - Overview ................................................ 9

2.3 ERP systems in the services sector .................................................................................. 11

2.4 ERP software evaluation and selection ............................................................................ 14

Methodology ........................................................................................................................... 16

3.1 Introduction ...................................................................................................................... 16

3.2 Similar methodologies ..................................................................................................... 16

3.3 Conceptual Framework .................................................................................................... 20

3.4 Hypotheses ....................................................................................................................... 21

3.5 Questionnaire ................................................................................................................... 23

3.6 Summary .......................................................................................................................... 25

Data Analysis .......................................................................................................................... 26

4.1 Introduction ...................................................................................................................... 26

4.2 Descriptive statistics ........................................................................................................ 26

4.3 Factor analysis and reliability analysis ............................................................................ 42

4.4 Linear regression .............................................................................................................. 43

4.5 Discussion of the results .................................................................................................. 45

4.6 Summary .......................................................................................................................... 45

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Conclusions ............................................................................................................................. 47

5.1 Description of the research .............................................................................................. 47

5.2 Implications, Limitations and further research ................................................................ 49

References ................................................................................................................................ 50

Appendix A .............................................................................................................................. 53

Appendix B .............................................................................................................................. 56

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Abstract

An ERP (Enterprise Resource Planning) is a wide information system aiming to

integrate and combine all the important business functions of an enterprise. These functions

could range from inventory control to sales management and human resources. In this study

we illuminate the selection criteria that North Greek SMEs (Small and Medium sized

Enterprises) have when it comes to the crucial decision of choosing the suitable ERP system.

Confirmatory factor analysis and linear regression were conducted in order to test whether

‘ERP product’, ‘vendor credibility and service’ and ‘knowledge and involvement’ affect ERP

success perception. Finally, the results indicate that the most important factor is the ‘ERP

product’. Analytically, functionality, cost, reliability and compatibility mostly concern SME

representatives for their selection. Less but also significant for the implementation decision

are ‘vendor credibility and service’ and ‘knowledge and involvement’.

Key words: ERP system, SMEs, ERP product, vendor credibility and service, knowledge and

involvement.

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Chapter 1

Introduction

1.1 Aims and objectives

E.R.P. stands for Enterprise Resource Planning and is a term that has been used wider

and wider the last decade. An ERP is a wide information system aiming to integrate and

combine all the important business functions of an enterprise. These functions could range

from inventory control to sales management and human resources. In today’s corporate

environment, the stake for companies is not only to maximize their profits but also to decrease

their costs and expenses. Therefore, enterprises are implementing ERP systems in order to

achieve better customer-order integration, faster production process, less inventories, smaller

preparation time and accurate information about their human resources (Yazgan et al., 2009).

In this study we aim to illuminate the selection criteria that SMEs have, when it comes to the

crucial decision of choosing the suitable ERP system. Is it the ERP system itself as a product

more significant than supplier’s reputation and support? Would SMEs choose their ERP

system just because it is easy for employees to use it and understand it? Which one of the

following criteria is most important for SMEs: functionality, cost, reliability, compatibility,

technical support, supplier’s position, supplier’s name, supplier’s methodology, user

involvement or system understanding? All these are questions that triggered this research. The

answers lie in the following pages.

1.2 Dissertation structure

The present study is divided into five chapters. Each chapter presents different aspects

of the research but altogether consist a unified approach concerning the ERP evaluation and

selection criteria of SMEs. In the following chapter we provide the reader with a clear picture

of relevant to ERP implementation studies. A complete review of the literature was attempted

by referencing the main studies surrounding the topic of ERP implementation and selection

decision, starting with what an ERP system is. According to Wylie (1990), the term ERP was

introduced in the early 1990s by the software enterprise Gartner group. The term ERP was

created in order to describe the new software which was able to integrate procedures across

and within all the functional platforms. Then, a brief history of the ERP systems was

presented by discussing the study of Jacobs and Weston (2006). Additionally, since we

realized that ERP implementation is well documented in the private sector, while it is not in

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the public sector, we presented the study of Griffin and Dempsey (2008) concerning an

implementation procedure and a vendor’s tender offer of a computerized integrated system in

Cork County Council of Ireland. The last section of literature review dealt with the ERP

evaluation procedure and the acquisition planning, discussing the studies of Yazgan et al.

(2009), Verville et al. (2007) and Motwani et al. (2005). Verville et al. (2007), present a

complete ERP acquisition planning based on six important activities, while Motwani et al.

(2005), conducted a research in order to identify the most critical factors of ERP

implementation.

In the methodology chapter, relevant methodological approaches were presented and

our own methodological path was marked. The conceptual framework of this dissertation was

mainly based on three studies. The first one is conducted by Wu and Wang (2005) and aims to

measure ERP success from the users’ viewpoint. What was found is that stakeholders’

satisfaction is related to systems’ success and they identified the constructs that comprises the

users’ satisfaction evaluation and thus the success of the system. The second study was the

one of Law and Ngai (2007) about the organizational factors of ERP systems success.

Specifically, in their study the authors examined the relationship of the success of ERP

incorporation, the business operations improvement and its overall organizational

performance. Through the testing of their research framework they provided validating

evidence for their initial research purpose. That is, they confirmed relationships among ERP

success, Business Performance and Organizational performance. Also with their results they

stressed the attention should be paid in planning, implementation strategies and managerial

change when adopting an ERP system. Last but not least, the study of Valsamidis et al.

(2009) was used as a compass to illustrate the effect on small and medium sized enterprises

(SME) by the adoption of an ERP system.

In chapter four the analysis of primary data, collected through the questionnaires, was

developed. The sample was constituted by 217 SMEs located in the regions of Serres, Drama,

Kavala and Xanthi. After the presentation of the descriptive statistics we conducted

confirmatory factor analysis in order to classify the questionnaire items in factors. Finally,

three factors were created (ERP product, Vendor credibility and service, Knowledge and

involvement) each one having strong factor loadings. Accordingly, we incorporate these three

factors into a linear regression model and the analysis proved that all three factors affect the

affect positively the ERP success perception of SMEs. Lastly, what this research has revealed

is that when the owner or the director of a SME in North Greece (Serres, Drama, Kavala and

Xanthi region) has to make the choice of an ERP system, the product itself is the most

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important factor for the decision. Therefore, we can conclude that functionality, cost,

reliability and compatibility mostly concern SME representatives for their ERP selection.

Less but also significant for the implementation decision are ‘vendor credibility and service’

and ‘knowledge and involvement’.

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Chapter 2

Literature Review

2.1 Introduction

Reviewing the literature, the first thing to be explained is what an Enterprise Resource

Planning system (ERP) is. According to the recent study of Yazgan et al. (2009) an ERP is a

wide information system aiming to integrate and combine all the important business functions

of an enterprise. These functions could range from inventory control to sales management and

human resources. In today’s corporate environment, the stake for companies is not only to

maximize their profits but also to decrease their costs and expenses. Therefore, enterprises are

implementing ERP systems in order to achieve better customer-order integration, faster

production process, less inventories, smaller preparation time and accurate information about

their human resources. This section reviews the literature that surrounds the notion of ERP

systems. More specifically we seek answers on specific questions such as: what exactly an

ERP system is?, in what extend does an ERP increases the productivity of an enterprise?, how

does an ERP contribute to the growth of an enterprise?, what elements do the evaluation and

selection procedure implies?, which are the most significant ERP evaluation and selection

drivers based on the relevant literature?

2.2 Enterprise Resource Planning systems (ERP) - Overview

Jacobs and Weston (2006), in their study provide the literature with a brief history of

the ERP systems. Their throwback starts at 1960s, were the first computers showed up, it is

continued with the predecessors of ERP systems (MRP and MRP 2) and it is finishing by

predicting the future changes of the information systems. In the 1960s, along with the first

computers and software systems, MRP (Material Requirements Planning) and MRC (Material

Requirements Control), were initiated. As was mentioned before, MRP is the predecessor of

MRP 2 and the ERP. It was created by the cooperation of J.I. Case, a truck manufacturer, and

IBM. It was a reliable software system for developing and scheduling materials for the

construction of complex engines. IBMs MRP was an excellent choice for inventory and

production control. On the other hand, the first MRP solutions had two significant

disadvantages as well. MRP systems were big and expensive. The installation of the Material

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Requirements Planning system required higher capacity disks than the IBM 360s and 370s

that existed then. Moreover, the installation procedure required an expanded technical staff

and advanced skills by the users.

The mid 70s was the period when many companies that today are the biggest software

vendors, were created. Oracle Corporation, J.D. Edwards and Lawson software are some of

the companies that were established around that period of time. Emphasis was given on two

matters, more sophisticated marketing strategies and complete integration. In the early 80s,

J.D. Edwards created a software compatible with the IBM 38 system. The new system was

much cheaper than the previous one, due to the fact that it offered flexibility at the disk

drivers. This way, even small and medium size enterprises were able to install it. Finally, the

new system was called MRP 2. According to Wylie (1990), the term ERP was introduced in

the early 1990s by the software enterprise Gartner group. The term ERP was created in order

to describe the new software which was able to integrate procedures across and within all the

functional platforms. In 1992 the SAP Corporation introduces the R/3 product. The significant

about R/3 was that it used client-server architecture. This way the system was able to run on

various computer platforms such as UNIX and Windows NT. Moreover, the architecture of

SAPs R/3 was allowing the third-party companies to develop other software that could

integrate with R/3. This fact along with the decline in the hardware costs boosted the sales of

the ERP systems. By the end of the decade IBM was not in sector’s leading position. The

following statistics of 1999 are indicatory of the situation in the sector:

J.D Edwards has more than 4700 customers located in more than 100 countries

Oracle counts more than 41,000 customers around the world. From them 16,000 are in

the USA

SAP becomes the world’s fourth largest software enterprise employing more than

20,500 employees.

Baan enterprise had installed more than 4,800 ERP systems in clients around the

world.

According to Jacobs and Weston (2006) at the beginning of 2000, after the break

down of the ‘dot.com’ companies, software enterprises were seeking ways to increase their

market share against the competition. At this situation, various software-vendor

consolidations, mergers and acquisitions took place. By 2002 SAP, Oracle, PeopleSoft and

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J.D. Edwards were the major players in the sector. Baan Enterprise was led to bankruptcy. As

the years passed software companies, vendors and users have reached a significant level of

maturity. Today, all the interested parties understand the demands of the system concerning

human resources, costs and technical infrastructure. Unfortunately, today’s ERP systems

execute the old logic faster and in an on-line basis. In the future it is essential for software

companies to produce more sophisticated products. This can only be achieved if users and

vendors have a complete cooperation.

2.3 ERP systems in the services sector

As it is generally known, the economic activity is divided into three sectors. The first

sector is referred to the agriculture and the primary resources. The second sector covers the

industrial transformation of primary sources and products into finished goods. And the third

sector deals with services in general. When ERP systems were introduced in the early 1990s,

enterprises from the first and the second sector started to adopt them with enthusiasm. On the

other hand, enterprises from the services and administration activities sector did not show the

same enthusiasm, due to the nature of their function. Lately though, service enterprises have

also turned into keen ERP systems adopters, with significant benefits in their performance.

Genoulaz and Millet (2005), conducted a case study research on six enterprises from

six different industries. The enterprise pattern were a bank, a hospital, a non-profit

organization in the health sector (hospital), a software enterprise, an insurance and financial

services provider and an enterprise dealing with telecommunication and internet services. It

was found that in all cases the adopted ERP systems, did not achieve a complete cooperation

of all the enterprise’s departments. Moreover, all the participated companies mentioned that

only a complete integration could produce important benefits and a return on investment

(ROI) increase. Figure 2 below, depicts the level of the ERP integration among the six

enterprises. The initials for the departments are the following: HR: Human resources, FI-CO:

Finance and control, PL: Planning, OP: Operations, SD: Sales and distribution, CRM:

Customer Relationship Management, PDM: Product Data Management, MM: Material

Management.

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Figure 2 Integration levels of ERP systems among companies

Finally, Genoulaz and Millet’s (2005) findings indicate that the goal of a fully

integrated ERP system cannot be achieved in the services sector. It is suggested that service

enterprises should focus more on CRM (customer relationship management) and HR (human

resources) management software rather than on software systems for the design and

production of services. The reason for that is due to the nature of services, where materials are

frequently handled as indirect costs. The human factor is of major importance in services and

a software system should be human-oriented, in order to meet the needs of services

companies. Figure 3 below presents the difference between the required procedure of an ERP

system in the cases of a services and a manufacturing enterprise. As it can be seen, the needs

for the two sectors significantly differ. We could simply imply that there are different

priorities between the two sectors. Once the priorities are served by the ERP systems, both

sector companies will operate effectively. Finally, the ultimate target for every organization is

one, full integration.

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Figure 3 ERP structure

Griffin and Dempsey (2008), claim that, while private sector’s ERP implementation is

well documented, the implementation of ERP systems in the public sector has not been

examined properly. Therefore, the implementation procedure and vendor’s tender offer of a

computerized integrated system in Cork County Council of Ireland is examined. Cork County

Council is a local branch on the national government authority and its mission is to provide

the habitats of County Cork with water, electricity, roads, rents, annuities and development

contributions. Problem’s very root was that Cork County Council was divided into three sub-

divisions: North Cork, South Cork and West Cork. Each one of the three sub-divisions had its

own billing system and receipting procedures. As a result the three sub-divisions had

variations in the billing and receipting techniques. Moreover, the debtor’s legacy systems that

had been used were not linked to the General Ledger system. To solve the problem, the head

manager decided to acquire and implement an integrated and centralized Corporate debtors

system that could combine the three debtors systems to a single one General Ledger. Moving

forward, the most interesting, concerning Griffin and Dempsey’s (2008) study, is the

procedure that was followed in order for Cork County Council to choose the right supplier for

the ERP system. Due to the fact that the required system was very complex Cork County

Council decided to conduct a restricted competition instead of an open one. For that purpose,

an assessment team was formulated. In the restricted competition the potential vendors had to

answer to a pre-questionnaire. The assessment team gave emphasis on three specific vendors’

characteristics: a) economic standing, b) staff resources and c) track record and experience on

similar projects. In simple words, the assessment team mostly evaluated the financial standing

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of the suppliers (debts and capabilities), the number of employees that were employing by

that time and last but not least what similar systems had implemented in the past. As a result,

only a few vendors made it through the pre-questionnaire phase. Finally, on 21 September

2006 Cork County Council signed a contract with the vendor that mostly fulfilled the three

criteria set by the assessment team.

2.4 ERP software evaluation and selection

Since ERP systems are fundamental for the operation of an enterprise and the

cooperation between its departments, the selection of the ERP system is a vital and complex

task. Studying the ERP evaluation and selection literature it is obvious that various selection

models exist. There are numerous studies presenting the ERP evaluation procedure and the

acquisition planning, such as Baki and Cakar (2005), Uta et al. (2007) and Yazgan et al.

(2009). For example, Yazgan et al. (2009) propose the analytical network process (ANP) as

the most suitable tool for ERP software selection. The ANP method has several advantages

such as consideration of tangible and intangible factors, pair comparisons, transformation of

qualitative data into quantitative data and general stakeholders’ motivation to participate in

the process. On the other hand, the study of Wu and Wang (2005) provides with a better

approach to examine the relation between key user satisfaction and ERP system success. This

section discusses the factors that lead to a successful ERP implementation, by presenting the

findings of several academics.

Verville et al. (2007), present a complete ERP acquisition planning based on six

important activities. Apart from evaluation and selection criteria there were five more

activities identified. These were the formation of a project team, requirements engineering,

marketplace analysis, selection of acquisition strategy and anticipated acquisition issues.

Analytically, concerning the formation of an acquisition team, Verville et al. (2007), highlight

the importance of putting a person in charge of the whole procedure. This person could be the

IT director, the CEO, or a skilled manager who will designate a project team (steering

committee) with participants of all the enterprise departments. The first task of the project

team was to define both the technical and the functional requirements. The third and most

crucial step in the acquisition planning is the establishment of the evaluation and selection

criteria. There criteria are numerous and depend on enterprise’s needs and priorities. Wu and

Wang (2005) stress on functionality, cost, reliability, compatibility, technical support,

supplier’s position, supplier’s name, methodology, user involvement and system

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understanding. Verville et al. (2007) also mention ‘functionalities required to increase

revenues’ (p.54). Additionally, the following step is the analysis of the marketplace. This

activity simply implies to make a list of vendors (both big and small players in the market)

that could be the suppliers of the ERP system. The fifth activity is the acquisition strategy. A

common enterprise practice concerning the acquisition strategy is to present the requirements

to the supplier before the demonstration sessions. Finally, the anticipated acquisition issues

are what if scenarios in case something goes wrong.

Motwani et al. (2005), conducted a research in order to identify the most critical

factors of ERP implementation. Their study was based on four case studies conducted in four

US enterprises that used ERP systems designed from the same vendor. Primary data were

retrieved directly from the corporations with personal interviews, observations and

questionnaires. The first enterprise (Enterprise A) was a pharmaceutical enterprise which also

produces nutritional products. Enterprise A needed to upgrade its inventory control.

Therefore, a new ERP system was adopted. Enterprise B was a leading footwear enterprise of

casual shoes. This enterprise was using AS/400 system for the sales and marketing operations.

A significant delay in the procedures was noticed, due to the fact that the system required a 6-

8 hour process in order to conduct a simple transaction. This delay led the enterprise to

implement the new ERP. Enterprise C was a huge energy enterprise having revenues of over

50 billion dollars. Prior to the ERP implementation, enterprise C had implemented various

legacy systems. The lack of data visibility and software’s poor cost control forced the

enterprise to implement the specific ERP system. Enterprise D is a big automobile enterprise

owning 28 construction facilities in America. Enterprise D was formatted by the merger of

two Japanese automobile organizations. The enterprise was using a Japanese software system

that was owned by one of the parent companies. The problem was that this system had a

decentralized orientation and could not meet the needs of the new enterprise. As the enterprise

was growing in size, a new ERP system implementation was completely necessary. Finally,

the analysis showed that an ERP implementations should be accompanied by a cautious and

bureaucratic implementation procedure. The factors that are highlighted are the change

management, network relationships and cultural readiness.

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Chapter 3

Methodology

3.1 Introduction

Our study aims to reveal the evaluation and selection criteria, for a successful ERP

implementation process based on a survey of the northern Greek small and medium

enterprises (SMEs). Our research methodology follows the rationale of Wu and Wang (2005),

Law and Ngai (2007) and Valsamidis et al. (2009). The conceptual model of our research is

presented in figure 2.2 below. As shown in the figure we retrieve[u1] ten success

implementation factors from a quite extended literature review. Namely the factors are:

functionality, cost, reliability, compatibility, technical support, vendor’s position, vendor’s

name, methodology, user involvement, system understanding. Each one of the proposed

factors constitutes one section in our research questionnaire[u2]. We expect these factors to

constitute three basic/major [u3]constructs namely ERP product, Vendor Credibility &

Service, Knowledge & Involvement. These constructs are going to be tested for effectiveness

and success of an ERP system implementation. In this section we review the three most

seminal methodologies that our research follows plus the Umble, Haft and Umble’s (2003)

methodology. With their extended literature review they have provided a large list of

success[u4] factors when implementing an ERP system. Moreover, we indicate our

conceptual framework and the hypotheses that our research is based on. Finally, we elaborate

on the questionnaire we use elaborating on each item we finally include through our literature

review[u5].

3.2 Similar methodologies

Umble et al. (2003) conducted a relevant study where they identify [u6]success factors

and procedures for the correct and effective selection of software and its implementation. In

their study they note the pitfalls of the ERP implantation process and the most common

mistakes in selecting the right software. Through a fairly extended literature review they

examine the most critical factors of successful ERP systems. Finally, the authors base their

statements on a case study for Huck Int. a manufacturer of proprietary commercial, industrial,

and aerospace fastening systems. This enterprise successfully implemented an ERP system in

1999 and the authors examine the degree of adherence to the prior proposed in literature

success factors. The authors identified ten categories of reasons why some ERP systems

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might fail. They elaborated on the strategic goals of the enterprise and the benefit that would

occur by the implementation of an ERP system. Their case study presents the commitment of

top management highlighted by the decisiveness of the CEO to move forward with the

implementation. Moreover, the authors examine some technical issues such as the project

management and the incorporation of all running operations into a single system and the

necessary managerial changes to support it. They present the implantation team, the test that

the enterprise runs for data accuracy and the necessary training of all stakeholders. They

analyze the performance measures, the implementation process, post implementation audit

and ultimately they provide an implementation evaluation to conclude that the enterprise

succeeded to adopt a new ERP system sticking to the principals.

Additional to Umble’s et al. (2003) research that highlights the most critical success

factors for the implementation of ERP systems, we base our research on three other studies.

The first one is conducted by Wu and Wang (2005) and aims to measure ERP success from

the users’ viewpoint. Authors proposed a satisfaction measure built on two phases. At the first

phase, they consider a list of ERP satisfaction items and characteristics retrieved from

literature. Then, they submitted this list of items to five interviews of stakeholders to see if the

items are clear and concrete in meaning. At the second phase, and after revising their initial

collection of items, they conducted a pilot test with thirty key users. This way they had a

widely revised instrument for a large scale survey of stakeholders from the top 1000

companies in Taiwan. However, authors ended up in a sample of 617 companies from the list

of 1000 that were actually had implemented an ERP system. After collecting 205 valid

responses achieving a response rate of 28 per cent they submitted them to exploratory and

confirmatory factor analysis that produced a concrete satisfaction model for measuring ERP

success. Finally, they concluded that stakeholders’ satisfaction is related to systems’ success

and additionally it is a measure of systems’ success. Also, they identified the constructs that

comprises the users’ satisfaction evaluation thus the success of the system. In This way they

actually provide to vendors and managers a diagnostic tool for assessing the implementation

of an ERP system to an enterprise. Finally, they also provided some useful managerial

implications stressing the importance of users’ and stakeholders involvement and knowledge

for the success of the system.

Law and Ngai (2007) also conducted study about the organizational factors of ERP

systems success. Specifically, in their study the authors examined the relationship of the

success of ERP incorporation, the business operations improvement and its overall

organizational performance. The authors also examined the relationships of these elements

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and organizational factors such as strategic intent, senior management support, and the status

of the IT function within the enterprise. The authors conducted interviews with the IT

executives of three different companies that use ERP systems to identify their objective when

deciding to adopt an ERP system as well as to discuss and distinguish the most common

organizational issues when implementing an ERP system. After this process they concluded

on their conceptual model as follows:

Figure 2.1: Law and Ngai (2007): Conceptual Model

The set of hypotheses they examined in order to reach their conclusions includes

seven hypotheses which are the following:

H01. ERP success as measured by user satisfaction is positively associated with the

perceived performance of organizations.

H02. The perceived extent of BPI is positively associated with the perceived

performance of organizations.

H03. The perceived extent of BPI is positively associated with ERP success, as

measured by user satisfaction.

H04a. Perceived senior management support of BPI initiatives is positively associated

with the perceived extent of BPI.

H04b. Perceived senior management support of IT initiatives is positively associated

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with ERP success as measured by user satisfaction.

H05a. CEO-IT distance is negatively associated with the perceived extent of BPI.

H05b. CEO-IT distance is negatively associated with ERP success as measured by

user satisfaction.

H06a. CEO-IT distance is negatively associated with the perceived support of senior

management for BPI initiatives.

H06b. CEO-IT distance is negatively associated with the perceived support of senior

management for IT.

H07a. There is a difference in the perceived level of ERP success, as measured by the

mean ERP user satisfaction indices, across [u7]enterprises with different strategic intents for

ERP.

H07b. There is a difference in the extent of BPI, as measured by the mean BPI indices,

across enterprises with different strategic intent s for ERP.

H07c. There is a difference in the perceived level of organization performance, as

measured by the mean organizational performance indices, across enterprises with different

strategic intents for ERP.

The authors conducted a survey aiming 1000 companies in Hong Kong from a

database of 3200. Through the testing of their research framework they provided validating

evidence for their initial research purpose. That is, they confirmed relationships among ERP

success, Business Performance and Organizational performance. Also with their results they

stressed the attention should be paid in planning, implementation strategies and managerial

change when adopting an ERP system.

Finally, the study of Valsamidis et al. (2009), aims to illustrate the effect on small and

medium sized enterprises (SME) by the adoption of an ERP system. For that reason, they

identified fifteen critical factors pooled from literature on which SMEs base their selection of

an ERP system. These factors are the following: “functionality of the system, technical

support offered by the supplier, cost of the system, service and support that the supplier

provides, supplier’s name (reputation), system’s reliability, compatibility with other systems,

adjustment (ease of customization), supplier’s position at the market, better fit with

organizational structure (match), domain knowledge of the supplier, reference of the supplier,

implementation time of the system, methodology proposed by the vendor and consultancy

offered by the supplier to facilitate the selection and the implementation process”. Then the

authors examine the relationships of these factors with the characteristics of SMEs in the

region of research. To do that, they implement a survey of one stakeholder in each one of

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thirty two SMEs in the region of East Macedonia. The practical implications of their research

are that flexibility and functionality are the most distinguished selection factors when

choosing an ERP system followed by the reliability and the service support. Also, the specific

research reveals that cost is of the lowest importance when selecting an ERP system

implementation highlighting the anticipation by the executives of generating higher value in

the future by the implementation of the system.

3.3 Conceptual Framework

In this section we present the conceptual framework of our research which refers to

success factors of an ERP selection by a SME. We will [u8]review the constructs that we use

in our research retrieved from relevant literature. Specifically functionality refers to the proper

use of the variety of ERP modules for each enterprise. That is to use exactly the modules

needed to cover all the enterprises’ operations. Cost refers to the cost of obtaining the system,

installing the system and to primarily setting the system to function. An ERP system is

reliable when it is stable, fast and meets all the technical requirements of an enterprise.

Compatibility is another important feature referring to the ease of the system compliance with

other systems and other exogenous systems and protocols such as with the General Secretariat

of Information Systems or the International Financial Reporting Standards. Technical Support

refers to the availability of the vendor to provide any kind of help regarding the function of

the ERP system. Suppliers’ position indicates the position that the supplier maintains in the

market. When a supplier maintains a large market share for an extended period of time or

manages some respected client accounts it is considered of high reliability and

trustworthiness. Suppliers’ name refers to the vendor’s fame in the market for providing high

expertise and quality services. Methodology refers to the procedure the vendor follows to

implement the system into an enterprise specifically to the effectiveness, the speed of

implementation and the convenient cost – effectiveness rate. User involvement refers to the

way and the degree stakeholders will interact with the system. An effective system means that

the users are highly involved and the vendor should provide training and support to increase

involvement. Finally system understanding has to do with the training on the system by the

vendor. The last two characteristics are highly related to knowledge which is a fundamental

component of a good ERP system.

After performing a principal components factor analysis using Varimax Rotation in

our survey data we ended up into grouping these ten items retrieved from literature into three

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distinct constructs that will be used as the independent constructs on our regression research

that will follow. The three constructs resulting by the factor analysis are the following: a) ERP

products that occurred by four items, functionality, cost, reliability and compatibility, b)

Vendor Credibility and Service that occurred by four items, technical support, suppliers’

position, suppliers’ name and methodology and c) Knowledge and Involvement that occurred

by two items, user involvement and system understanding. In the next chapter we will

elaborate on the factor analysis statistics and the loadings of all items. The conceptual model

of our research is presented diagrammatically in the following figure.

Figure 2.2: Figure Conceptual model

3.4 Hypotheses

The aim of our research is to examine whether the three constructs presented earlier:

“ERP product”, “Vendor Credibility & Service” and “Knowledge and Involvement” are

H3

H2

H1

22

prerequisites for a successful selection and implementation of an ERP system. To perform this

test we will analyze a set of hypotheses using a two of the most widely accepted correlation

measures, Pearson’s and Spearman’s. Furthermore, we perform a linear regression analysis to

investigate the pattern that the three constructs we conceived, form and effect the dependent

variable of our model. We expect that the model that will emerge can be used as an index for

measuring an ERP implementation and selection success. Specifically, we are going to test

how and to what extend the three main factors (ERP product, Vendor credibility and service,

Knowledge and involvement) affect the ERP selection procedure. Our first hypothesis is

formed as follows:

H1: A cautious assessment of ERP product leads to a successful ERP package selection.

This hypothesis is based on the four items that produced the factor ERP product,

“Functionality”, “Cost”, “Reliability” and “Credibility”. According to this hypothesis if an

enterprise carefully assess a system’s functionality, effectively evaluate the cost – effect rate

and assess the reliability and credibility of both the system and the vendor it is highly likely

that the performance of the system will meet the requirements at a satisfactory level.

The second hypothesis of the research concept is formed as follows:

H2: A cautious assessment of vendor’s credibility and future service leads to a successful

ERP package selection.

This hypothesis is based on the four items that produced the factor “Vendor’s

Credibility and Service”, “Technical Support”, “Supplier’s Position”, “Supplier’s Name”, and

“Methodology”. According to this hypothesis if the executives of an enterprise give emphasis

on the quality of the vendor’s after sales service and technical support and take into account

the fame and the experience of the vendor then the selection and implementation of the ERP

system will most likely be successful.

Finally, the third hypothesis of the research framework we propose is formed as

follows:

H3: A cautious assessment of user’s knowledge and future involvement leads to a

successful ERP package selection.

The third hypothesis is formed with the remaining two items that produced the third

construct “User’s knowledge and involvement”. The items are “User Involvement” and

“System understanding”. This hypothesis assumes that the highest the quality of users’

knowledge on the implemented system and the highest the involvement of users, the higher

the performance, thus the success of the system.

23

3.5 Questionnaire

In order to test the hypotheses of our research framework and provide implications for

the ERP users we conducted a survey of Small and Medium Enterprises in Eastern

Macedonia. At this point it is crucial to decide when an enterprise should be considered small

and medium. Valsamidis et al. (2009), clarify in their analysis when an enterprise should be

considered small or medium enterprise following the definition of the European

Commission1. According to that definition small and medium are the enterprises that make

sales and revenues of a specific range, employ a number of employees that lies into a

specified range and own a total value of assets of a specific range. Enterprises are classified

into micro, small and medium-sized as shown on the following Table 3.1.

Table 3.1 Enterprise classification

The data collection has been achieved through distribution of questionnaires. The

questionnaires have been distributed to 860 SMEs of North Greece. That is the prefectures of

Serres, Drama, Kavala and Xanthi. In this region numerous SME’s are located. The contact

has been achieved with the help of the local chambers of commerce and industry.

Our study is based on the studies of Valsamidis et al. (2009) and Wu and Wang

(2005) and is divided into two sections. The first section investigates general enterprise

characteristics, while the second section includes the ten proposed items from which we build

the three proposed constructs. The first question refers to the location of each responding

enterprise to provide a variance of locations in the examined geographic area in order to

1 http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme-definition/index_en.htm

Last accessed 24 August 2011

Enterprise category Headcount Turnover OR Balance sheet

total

Medium-sized <250 ≤50

million

≤43 million

Small <50 ≤10

million

≤10 million

Micro <10 ≤2 million ≤2 million

24

reduce bias and maintain representativeness. The second question refers to the number of

employees of the responding enterprises and helps us with the determination of which of the

responding enterprises are small or medium. The number of employees can lie between 0 and

250 employees in order to meet the specific criterion. The third question refers to the last

year’s annual turnover, again for the determination of the small and medium criterion. The

fourth question refers to the years of operation in order to maintain representativeness. Fifth

question refers to for the ERP selection, implementation and installation costs. The second

section of the questionnaire examines whether functionality, cost, reliability, compatibility,

technical support, suppliers position, suppliers name, methodology, user involvement and

system understanding are significant criteria for a successful ERP selection. The questions in

this section are classified according to the three factors of the research model. Therefore,

‘ERP product’ is examined in four questions that examine the functionality, the cost, the

reliability and the compatibility of the ERP system. The following four questions of the

questionnaire comprise the factor ‘Vendor credibility and service’ where technical support,

suppliers’ position, suppliers name and methodology are questioned. Finally, the last two

questions examine user’s involvement and system understanding in order to form the

‘knowledge and involvement’ factor. Respondent executives[u9] have to choose from a five

point scale the significance of each criterion for the successful selection and implementation

of the system. The options of the scale are “Not at all significant”, “Enough Significant”,

“Fairly significant”, “Much significant”, “Very much significant”.

Our survey was conducted through the distribution of questionnaires. Specifically we

obtain a list of all the enterprises operating in the examined geographic region (Eastern

Macedonia) from the Chamber of Commerce. Some of the enterprises did fall in the definition

of small and medium so they were discarded from the beginning of the process.

Questionnaires were finally distributed to 860 enterprises through post or attached to an e-

mail message. Questionnaires either distributed by post or e-mail were escorted by a letter

with the request to be answered by the IT executive of each enterprise or the most involved

executive in the enterprise. E-mails and printed questionnaires were sent out in June 2011 and

a reminder phone call was made in late July so as to avoid the general absence of executives

for the August summer break. Finally, we managed to collect a total of 232 completed

questionnaires, fifteen of which were discarded because the enterprises did not fall in the

definition of small or medium. The final dataset consisted of 217 valid responses and was

encoded initially with the use of Microsoft’s Excel 2007 in order to be entered in SPSS v.19

for further analysis.

25

3.6 Summary

In this chapter we presented the methodological approach of our research. Initially we

presented four methodologies of other researchers based on which we built our own research

framework. Then we presented the conceptual framework after introducing the items and the

constructs this is based on. After that we elaborated on the hypotheses that will support our

research claims. Finally, we presented and analyzed the surveying methods that we used to

collect data as well as the instrument we use to do so. In the next we will show our results

after submitting our data in an extended statistics analysis. We will present several statistic

measures guaranteeing for the items and constructs validity as well as for the sample size

adequacy. Finally, we will provide several practical implications that will be further discussed

in the last chapter, five.

26

Chapter 4

Data Analysis

4.1 Introduction

In this chapter we present the statistical analysis of the collected data through the

distribution of questionnaires. As was mentioned in the previous chapter we managed to

collect 217 valid questionnaires that were encoded initially with the use of Microsoft’s Excel

2007 in order to be entered in SPSS v.19 (Statistical Platform for Social Sciences). This

chapter is structured as follows: section 4.2 presents the descriptive statistics of the analysis

through tables and graphs, section 4.3 deals with the factor analysis and reliability analysis of

data and section 4.4 describes the steps of the linear regression analysis. The findings indicate

that SMEs pay greater attention on the ERP product itself, rather than ‘vendor’s credibility’ or

‘employees’ knowledge and involvement’.

4.2 Descriptive statistics

In this section, descriptive statistics of the questionnaire items are presented. For the

visualization of the results, tables and graphs were added in the analysis. The first question of

section A of the questionnaire is about the location of the SMEs. As was discussed in the

previous section the answers vary among Serres, Drama, Kavala and Xanthi as these are the

prefectures that the original research has been conducted. In our research, 48 companies from

Serres, 69 from Drama, 55 from Kavala and 45 from Xanthi, participated. The answers and

the cumulative percentages are depicted in the following Table 4.1.

Table 4.1 Location (Prefecture)

Frequency Percent

Serres 48 22.1

Drama 69 31.8

Kavala 55 25.3

Xanthi 45 20.7

Total 217 100.0

27

Graph 4.1 Location (Prefecture)

The next question of the questionnaire concerns the number of employees in each enterprise

of the research. It was extracted that, most of the enterprises have 0-5 employees (57.1%).

Table 4.2 and graph 4.2 summarizes the results.

Table 4.2 Number of employees

Frequency Percent

0-5 124 57,1

6-12 73 33,6

13-30 14 6,5

31-100 6 2,8

Total 217 100,0

28

Graph 4.2 Number of employees

The following question concerns the operation years of each enterprise. Most of the

enterprises operate for 6-10 years and a few operate for more than 15 years. Table 4.3 and

Graph 4.3 depict the respondents’ answers.

Table 4.3 Years of operation

Frequency Percent

0-5 74 34,1

6-10 87 40,1

11-15 39 18,0

Over 15 17 7,8

Total 217 100,0

29

Graph 4.3 Years of operation

Question 4 examines the annual turnover (in thousand Euros) of each enterprise. Luckily, all

enterprises that participated in the research answered the specific question even though

traditionally it is a question that businessmen avoid to answer in academic researches. The

answers can be shown in Table 4.4 and Graph 4.4. Most enterprises reported annual turnover

up to 300 thousand Euros.

Table 4.4 Annual turnover (in thousand Euros)

Frequency Percent

Up to 300 124 57.1

300-800

71 32.7

800-1.300

16 7.4

1.300-1.600

6 2.8

Total 217 100.0

30

Graph 4.4 Annual turnover (in thousand Euros)

In question 5 we seek answers concerning the implementation cost of the ERP system that

each enterprise had employed. Choices vary across a range of ‘up to 4,000 €’ to ‘over 25, 000

€’. As can be seen in the table and the graph that follow, in most cases the cost was limited

below 4,000 Euros since most enterprises were small and therefore had limited demands of

their ERP system. Table 4.5 and Graph 4.5 depict the answers.

Table 4.5 Cost of ERP implementation

Frequency Percent

Up to 4000

102 47.0

40001-8000

76 35.0

8001-12000

13 6.0

12001-16000

9 4.1

16001-20000

5 2.3

20001-25000

9 4.1

Over 25000 3 1.4

31

Total 217 100,0

Graph 4.5 Cost of ERP implementation

In question 6 (How much were you influenced by the Functionality of the ERP system, for

your selection?) most SMEs reported that were fair influenced by system functionality for

their implementation decision.

Table 4.6 Functionality

Frequency Percent

Not at all 39 18.0

Enough 27 12.4

Fair 52 24.0

Much 48 22.1

Very Much 51 23.5

Total 217 100.0

32

Graph 4.6 Functionality

Question 7 (How much were you influenced by the Cost of the ERP system, for your

selection?) examines the importance of cost when it comes to an ERP installation procedure.

It was expected that cost would be a significant determinant for the implementation decision,

but the results indicate that cost has a medium importance for enterprises.

Table 4.7 Cost

Frequency Percent

Not at all 36 16.6

Enough 47 21.7

Fair 50 23.0

Much 45 20.7

Very Much 39 18.0

Total 217 100.0

33

Graph 4.7 Cost

In question 8 (How much were you influenced by the reliability of the ERP system, for your

selection) we examine the importance of reliability of the ERP system for the enterprise.

Table 4.8 and Graph 4.8 below indicate that most enterprises consider suppliers’ reliability a

medium factor for the implementation decision.

Table 4.8 Reliability

Frequency Percent

Not at all 26 12.0

Enough 50 23.0

Fair 59 27.2

Much 41 18.9

Very Much 41 18.9

Total 217 100.0

34

Graph 4.8 Reliability

Question 9 (How much were you influenced by the Compatibility of the ERP system with

your previous software, for your selection?) investigates whether compatibility of the new

ERP with the existing software, concerns the enterprises. In most cases enterprises were much

interested in compatibility. All respondents’ answers can be seen in the following table (Table

4.9). Moreover, Graph 4.9 depicts the frequency trend concerning compatibility of the new

system with the existing systems.

Table 4.9 Compatibility

Frequency Percent

Not at all 29 13.4

Enough 40 18.4

Fair 45 20.7

Much 53 24.4

Very Much 50 23.0

Total 217 100.0

35

Graph 4.9 Compatibility

In question 10 (How much were you influenced by your supplier’s future technical support,

for your ERP system selection?) we examine enterprises’ beliefs concerning the suppliers’

technical support. Only 31 enterprises (14.3 per cent) reported that are ‘not at all’ interested in

supplier’s future technical support, while 51 enterprises were ‘fair’ interested. Table 4.10 and

Graph 4.10 summarize all the responds.

Table 4.10 Technical support

Frequency Percent

Not at all 31 14.3

Enough 49 22.6

Fair 51 23.5

Much 44 20.3

Very Much 42 19.4

Total 217 100.0

36

Graph 4.10 Technical support

Question 11 (How much were you influenced by your Supplier’s position, for your ERP

system selection?) examines the influence of supplier’s position in the market for the

implementation decision. The responds were almost equally allocated among the options. All

answers are presented in the following Table 4.11 and Graph 4.11.

Table 4.11 Supplier’s position in the market

Frequency Percent

Not at all 39 18.0

Enough 48 22.1

Fair 43 19.8

Much 41 18.9

Very Much 46 21.2

Total 217 100.0

37

Graph 4.11 Supplier’s position

In the same sense, question 12 (How much were you influenced by the supplier’s name, for

your ERP system selection?) examines the influence that supplier’s name has on the

implementation decision. In most cases enterprises reported that are much interested in

supplier’s reputation.

Table 4.12 Supplier’s name

Frequency Percent

Not at all 34 15.7

Enough 43 19.8

Fair 46 21.2

Much 49 22.6

Very Much 45 20.7

Total 217 100.0

38

Graph 4.12 Supplier’s name

Question 13 (How much were you influenced by the supplier’s Methodology, for your ERP

system selection?) is the last question to form ‘vendor credibility and service’. With this

question we seek answers concerning the influence of supplier’s methodology in the acquiring

choice. Table 4.13 and Graph 4.13 highlights the fact that enterprises are enough concerned

about the methods of the supplier.

Table 4.13 Supplier’s Methodology

Frequency Percent

Not at all 42 19.4

Enough 51 23.5

Fair 45 20.7

Much 38 17.5

Very Much 41 18.9

Total 217 100.0

39

Graph 4.13 Supplier’s Methodology

Question 14 and question 15 deal with the factor ‘knowledge and involvement’. It is shown

that an ERP which is easily understood and requires minimum user involvement is attractive

for enterprises. The following tables and graphs present the trend concerning these questions.

In question 14 (How much were you influenced by the degree of User involvement, for your

ERP system selection?) most enterprises answered that are enough concerned. In the same

sense, in question 15 (How much were you influenced by the degree of System understanding

by your employees, for your ERP system selection?) most enterprises reported that are fairly

interested in system understanding by their employees.

Table 4.14 User involvement

Frequency Percent

Not at all 51 23.5

Enough 72 33.2

Fair 43 19.8

Much 31 14.3

Very Much 20 9.2

Total 217 100.0

40

Graph 4.14 User involvement

Table 4.15 System understanding

Frequency Percent

Not at all 35 16.1

Enough 46 21.2

Fair 66 30.4

Much 41 18.9

Very Much 29 13.4

Total 217 100.0

41

Graph 4.15 System understanding

Question 16 (In what extend do you consider that the ERP selection was the suitable for your

enterprise?) examines the degree to which enterprises were satisfied with their choice of the

ERP system. By looking at Table 4.16 becomes obvious that the satisfaction level of most

enterprises is relatively high. Graph 4.16 depicts this trend.

Table 4.16 Success

Frequency Percent

Not at all 21 9.7

Enough 38 17.5

Fair 56 25.8

Much 59 27.2

Very Much 43 19.8

Total 217 100.0

42

Graph 4.16 Success

4.3 Factor analysis and reliability analysis

In this section of the empirical results we conduct confirmatory factor analysis and

reliability analysis on the sample. Using the KMO and Barlett’s test of sphericity we examine

the extent to which the sample is suitable for statistical analysis (Kim and Mueller, 1978). As

it can be seen in table 4.17 below, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy is

.637 which is considered to be acceptable, since it is well above 0.5. Moreover, the

significance level of Bartlett's Test of Sphericity is .000 (significance level 95%) and

therefore we can proceed on the statistical analysis (Harris and Peers, 1980).

In order to examine whether the items of the questionnaire can be classified into the

three factors created, based on the theory. Following the studies of Wu and Wang (2005),

Law and Ngai (2007) and Valsamidis et al. (2009) the model of our research implies that

functionality, cost, reliability and compatibility constitute the factor ‘ERP product’.

Moreover, technical support, supplier’s position, supplier’s name and methodology constitute

‘vendor credibility and service’. Finally, the last two items, user involvement and system

understanding create the factor ‘knowledge and involvement’. For that purpose, we conducted

confirmatory factor analysis, since the constructs are tested from previous researchers. Table

4.18 below, depicts the factor loadings of the three factors that were created.

43

Table 4.17 KMO and Bartlett's Test

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

0.637

Bartlett's Test of

Sphericity

Approx. Chi-Square 943.323

df 45

Sig. .000

Table 4.18 Factor analysis

FACTOR ERP

product

Vendor

credibi

lity

and

service

Knowle

dge and

involve

ment

Functionality .648

Cost .873

Reliability .882

Compatibility .831

Technical support .765

Supplier’s position .848

Supplier’s name .823

Supplier’s Methodology .729

User involvement .902

System understanding .899

As it can be seen in table 4.18 above, three factors were created (ERP product, Vendor

credibility and service, Knowledge and involvement) each one having strong factor loadings

(above 0.6). Principal component analysis was used as the extraction method and Varimax

with Kaiser normalization was used as the rotation method. In the following section, we

incorporate the three factors into a linear regression model in order to examine the importance

of each one on the ERP selection decision.

4.4 Linear regression

Since the factors were successfully created, we incorporate them into a linear

44

regression model. The linear regression equation of the analysis has the following form:

ERP success perception = α + β1 (P) + β2 (VCS) + β3 (KI) + ε (1)

Where (P) is the ERP product, (VCS) is vendor credibility and service and (KI) is knowledge

and involvement. Therefore, in order to find out the impact of each factor to the model, we

examine the values of β1. β2. β3 of the equation (1). In the following table (4.19) model’s

predictive power is presented (model summary). The adjusted R square figure indicates the

predictive power of the model. In our case it is .767 and therefore the independent variables

describe 76.7 per cent of the model, which is relatively adequate (Neter et al., 1996).

Table 4.19 Model summary

Model R R Square Adjusted R

Square

Std.

Error of

the

Estimate

Durbin-Watson

1 .878 .770 .767 .650 1.378

The following table (4.20) presents the results of the linear regression analysis

conducted with SPSS. The unstadardized beta values are the β1. β2. β3 figures of the equation

discussed above (Chen et al., 2005). The constant in the equation is the (α) variable and its

value is 3.018. On the other hand, the coefficients of ERP product, vendor credibility and

service and for knowledge and involvement are 1.176, 0.110 and 0.062 respectively. All

coefficients’ values are significant at 95 per cent level of significance. Based on the beta

values that the linear regression generated we can extract several findings. Firstly, it is notable

that all three factors affect the model positively, which means that as each factor grows, ERP

success perception also grows proportionately. Secondly, we notice that ‘ERP Product’ factor

has the biggest beta figure, which means that it is the one that mostly affects ERP success

perception. Moreover, ‘vendor credibility and service’ and ‘knowledge and involvement’ also

affect ERP success perception with a slight weight (Keppel, 1991).

Table 4.20 Coefficients

Unstandardized Standardized Sig.

45

Constructs Beta

Std.

Error Beta

Constant 3.018 .044 .000

P 1.176 .044 .873 .000

VCS .110 .044 .081 .014

KI .062 .044 .046 .016

4.5 Discussion of the results

Based on the previous analysis and mostly on the final table (table 4.20), we can

extract several conclusions concerning the ERP selection decision and ERP success

perception. The confirmatory factor analysis revealed that our items were able to be classified

on three main factors. Thus, functionality, cost, reliability and compatibility constituted the

factor ‘ERP product’. Moreover, the items of technical support, supplier’s position, supplier’s

name and supplier’s methodology were classified into the factor ‘vendor credibility and

service’. Finally, the last two items user involvement and system understanding created the

factor ‘knowledge and involvement’. These three factors were incorporated into a linear

regression model the results indicated that all three factors affect positively the ERP success

perception. Though. ERP product was proved to be the most important factor of the ERP

selection decision. After ERP product comes ‘vendor credibility and service’ and ‘knowledge

and involvement’ with a smaller effect on ERP selection decision and ERP success

perception.

What this research has revealed is that when the owner or the director of a SME in

North Greece (Serres, Drama, Kavala and Xanthi region) has to make the choice to select an

ERP system, the product itself is the most important factor for the decision. Therefore, we can

conclude that functionality, cost, reliability and compatibility mostly concern SME

representatives for their ERP selection. Less but also significant for the implementation

decision are ‘vendor credibility and service’ and ‘knowledge and involvement’.

4.6 Summary

In this chapter we presented the empirical results of our research. In the first section of

the present chapter various descriptive statistics, tables and graphs were presented. The next

section dealt with the confirmatory factor analysis among the items of the questionnaire.

46

Finally, in the last section we conducted linear regression analysis in order to find the

factor(s) that mostly affect the ERP selection decision. What has been found is that Greek

SMEs pays greater attention on the ERP product itself, rather than ‘vendor’s credibility’ or

‘employees’ knowledge and involvement’. The following chapter concludes the whole study.

Apart from concluding remarks we discuss the limitations of our research and we cite our

thoughts for further examination of the ERP selection factors and state implications for

enterprises and academic researchers.

47

Chapter 5

Conclusions

5.1 Description of the research

In the previous chapters, a complete research concerning the measurement of ERP

success by SMEs and their evaluation and selection criteria was presented. In the second

chapter we provided the reader with a clear picture of relevant to ERP implementation

studies. A review of the literature was attempted by referencing the main studies surrounding

the topic of ERP implementation and selection decision, starting with what an ERP system is.

According to Wylie (1990), the term ERP was introduced in the early 1990s by the software

enterprise Gartner group. The term ERP was created in order to describe the new software

which was able to integrate procedures across and within all the functional platforms. Then, a

brief history of the ERP systems was presented by discussing the study of Jacobs and Weston

(2006). Additionally, since it was revealed that ERP implementation is well documented in

the private sector and not in the public sector, we presented the study of Griffin and Dempsey

(2008) concerning an implementation procedure and a vendor’s tender offer of a

computerized integrated system in Cork County Council of Ireland. The last section of the

literature review dealt with the ERP evaluation procedure and the acquisition planning,

discussing the studies of Yazgan et al. (2009), Verville et al. (2007) and Motwani et al.

(2005). Verville et al. (2007). presented a complete ERP acquisition planning based on six

important activities, while Motwani et al. (2005), conducted a research in order to identify the

most critical factors of ERP implementation.

In the methodology chapter relevant methodological approaches were presented and

our own methodological path was marked. The conceptual framework of this dissertation was

mainly based on three studies. The first one is conducted by Wu and Wang (2005) and aims to

measure ERP success from the users’ viewpoint. What was found is that stakeholders’

satisfaction is related to systems’ success and they identified the constructs that comprises the

users’ satisfaction evaluation and thus the success of the system. The second study was the

one of Law and Ngai (2007) about the organizational factors of ERP systems success.

Specifically, in their study the authors examined the relationship of the success of ERP

incorporation. the business operations improvement and its overall organizational

performance. Through the testing of their research framework they provided validating

48

evidence for their initial research purpose. That is, they confirmed relationships among ERP

success, Business Performance and Organizational performance. Also with their results they

stressed the attention should be paid in planning, implementation strategies and managerial

change when adopting an ERP system. Last but not least, the study of Valsamidis et al.

(2009) was used as a compass to illustrate the effect on small and medium sized enterprises

(SME) by the adoption of an ERP system.

In chapter four the analysis of primary data, collected through the questionnaires, was

developed. The sample was constituted by 217 SMEs located in the regions of Serres, Drama,

Kavala and Xanthi. Table 5.1 below shows the classification of valid questionnaires among

the four prefectures of the research.

Table 5.1 Research classification among the prefectures

Frequency Percent

Serres 48 22.1

Drama 69 31.8

Kavala 55 25.3

Xanthi 45 20.7

Total 217 100.0

After the presentation of the descriptive statistics we conducted confirmatory factor

analysis in order to classify the questionnaire items in factors. Finally, three factors were

created (ERP product, Vendor credibility and service, Knowledge and involvement) each one

having strong factor loadings. Accordingly, we incorporate these three factors into a linear

regression model and the analysis proved that all three factors affect the affect positively the

ERP success perception of SMEs. Lastly, what this research has revealed is that when the

owner or the director of a SME in North Greece (Serres, Drama, Kavala and Xanthi region)

has to make the choice of an ERP system, the product itself is the most important factor for

the decision. Therefore, we can conclude that functionality, cost, reliability and compatibility

mostly concern SME representatives for their ERP selection. Less but also significant for the

implementation decision are ‘vendor credibility and service’ and ‘knowledge and

involvement’.

49

5.2 Implications, Limitations and further research

The implications of this research have a double orientation, towards academics and

towards businessmen and enterprises. In what concerns the academic community, hopefully

we added a small piece in the construction of technology implementation research. It was

shown that the product itself is the most important factor for the implementation decision by

SMEs. Universities and Institutes of Technology should focus more on producing computer

scientists that will be able to design and create more sophisticated resource planning systems.

For that reason the enhancement of the Greek educational system is essential. On the other

hand, concerning software suppliers and vendors the research has shown that work should

focus on four axes. They should be able to provide their customers with software systems and

ERPs of higher functionality, lower costs, increased reliability and higher compatibility.

As all studies do, the present study faced some limitations, mostly due to the fact that

in a student dissertation there is a serious time pressure. Significant difficulty also was the fact

that several enterprises were reluctant in completing our questionnaire. This fact led to a

smaller than the expected sample of only 217 respondents. The sample size was satisfactory

for our analysis though a bigger sample would result in safer findings and conclusions.

Moreover, it proved to be very difficult to fulfill the planning of conducting interviews with

enterprises in order to provide with additional information and case studies of the SMEs that

participated in the research. For further research we suggest that our work should be expanded

both geographically and technically. The geographical expansion could include all Greek

SMEs or the SMEs of a larger geographical area. Moreover, the research could include

foreign companies located in the Balkan countries or other European countries. A comparison

between foreign and Greek SMEs would be very interesting. The technical expansion

concerns an expansion concerning the business size. It would very interesting to examine the

selection attributes of large enterprises with many employees and massive revenues.

50

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53

Appendix A

Questionnaire

A. COMPANY CHARACTERISTICS

1. Location (Prefecture)

SERRES DRAMA KAVALA XANTHI

2. Number of employees

0-5 6-12 13-30 31-100

over 100

3. Years of operation

0-5 6-10 11-15 over 15

4. Annual turnover (in thousand Euros)

up to 300 300-800 800-1.300 1.300-1.600

over 1.600

5. Cost of ERP implementation

up to 4000 4.001-8000 8.001- 12.000 12.001-16.000

16.001-20.000 20.001-25.000 over 25.000

B. SELECTION CRITERIA

ERP PRODUCT

6. How much were you influenced by the Functionality of the ERP system. for your

selection?

1 Not at all

2 Enough

3 Fair

4 Much

54

5 Very much

7. How much were you influenced by the Cost of the ERP system. for your selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

8. How much were you influenced by the Reliability of the ERP system. for your selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

9. How much were you influenced by the Compatibility of the ERP system with your

previous software. for your selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

VENDOR CREDIBILITY & SERVICE

10. How much were you influenced by your supplier’s future Technical support. for your

ERP system selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

11. How much were you influenced by your Supplier’s position. for your ERP system

selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

12. How much were you influenced by the Supplier’s name. for your ERP system selection?

1 Not at all

55

2 Enough

3 Fair

4 Much

5 Very much

13. How much were you influenced by the Supplier’s Methodology. for your ERP system

selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

KNOWLEDGE & INVOLVEMENT

14. How much were you influenced by the degree of User involvement. for your ERP system

selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

15. How much were you influenced by the degree of System understanding by your

employees. for your ERP system selection?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

SUCCESS

16. In what extend do you consider that the ERP selection was the suitable for your

enterprise?

1 Not at all

2 Enough

3 Fair

4 Much

5 Very much

56

Appendix B

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.637

Bartlett's Test of

Sphericity

Approx. Chi-Square 943.32

3

df 45

Sig. .000

Communalities

Initial

Extract

ion

6. How much

were you

influenced by the

Functionality of

the ERP system.

for your selection?

1.000 .457

7. How much

were you

influenced by the

Cost of the ERP

system. for your

selection?

1.000 .770

8. How much

were you

influenced by the

Reliability of the

ERP system. for

your selection?

1.000 .779

57

9. How much

were you

influenced by the

Compatibility of

the ERP system

with your

previous software.

for your selection?

1.000 .710

10. How much

were you

influenced by

your supplier’s

future Technical

support. for your

ERP system

selection?

1.000 .588

11. How much

were you

influenced by

your Supplier’s

position. for your

ERP system

selection?

1.000 .736

12. How much

were you

influenced by the

Supplier’s name.

for your ERP

system selection?

1.000 .691

13. How much

were you

influenced by the

Supplier’s

Methodology. for

your ERP system

selection?

1.000 .539

14. How much

were you

influenced by the

degree of User

involvement. for

your ERP system

selection?

1.000 .824

58

15. How much

were you

influenced by the

degree of System

understanding by

your employees.

for your ERP

system selection?

1.000 .817

Extraction Method: Principal

Component Analysis.

Total Variance Explained

Componen

t

Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 2.737 27.372 27.372 2.737 27.372 27.372 2.668 26.681 26.681

2 2.614 26.139 53.511 2.614 26.139 53.511 2.557 25.569 52.250

3 1.560 15.604 69.115 1.560 15.604 69.115 1.686 16.865 69.115

4 .886 8.864 77.979

5 .793 7.929 85.908

6 .383 3.828 89.736

7 .348 3.481 93.217

8 .276 2.760 95.977

9 .212 2.121 98.098

10 .190 1.902 100.000

Extraction Method: Principal Component Analysis.

60

Rotated Component Matrixa

Component

1 2 3

6. How much were you

influenced by the

Functionality of the

ERP system. for your

selection?

.648

7. How much were you

influenced by the Cost

of the ERP system. for

your selection?

.873

8. How much were you

influenced by the

Reliability of the ERP

system. for your

selection?

.882

9. How much were you

influenced by the

Compatibility of the

ERP system with your

previous software. for

your selection?

.831

10. How much were

you influenced by your

supplier’s future

Technical support. for

your ERP system

selection?

.765

61

11. How much were

you influenced by your

Supplier’s position. for

your ERP system

selection?

.848

12. How much were

you influenced by the

Supplier’s name. for

your ERP system

selection?

.823

13. How much were

you influenced by the

Supplier’s

Methodology. for your

ERP system selection?

.729

14. How much were

you influenced by the

degree of User

involvement. for your

ERP system selection?

.902

15. How much were

you influenced by the

degree of System

understanding by your

employees. for your

ERP system selection?

.899

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 4 iterations.

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Durbin-

Watson

1 .878a .770 .767 .650 1.378

a. Predictors: (Constant). REGR factor score 3 for analysis 2. REGR factor

score 2 for analysis 2. REGR factor score 1 for analysis 2

b. Dependent Variable: 16. In what extend do you consider that the ERP

selection was the suitable for your enterprise?

62

ANOVAb

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 301.949 3 100.650 238.264 .000a

Residual 89.977 213 .422

Total 391.926 216

a. Predictors: (Constant). REGR factor score 3 for analysis 2. REGR factor score

2 for analysis 2. REGR factor score 1 for analysis 2

b. Dependent Variable: 16. In what extend do you consider that the ERP selection

was the suitable for your enterprise?

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 3.018 .044 68.412 .000

REGR factor score 1

for analysis 2 1.176 .044 .873 26.584 .000

REGR factor score 2

for analysis 2 .110 .044 .081 2.478 .014

REGR factor score 3

for analysis 2 .062 .044 .046 1.391 .166

a. Dependent Variable: 16. In what extend do you consider that the ERP selection was the

suitable for your enterprise?

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value .54 5.23 3.02 1.182 217

Residual -1.993 1.776 .000 .645 217

Std. Predicted

Value -2.096 1.874 .000 1.000 217

63

Std. Residual -3.066 2.732 .000 .993 217

a. Dependent Variable: 16. In what extend do you consider that the ERP

selection was the suitable for your enterprise?