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The Relationship between the Enterprise Resource Planning (ERP) Systems Internal Control Procedures Hani Shaiti University of Bedfordshire & King Faisal University Yanqing Duan Syamarlah asaratnam University of Bedfordshire University of Bedfordshire Abstract There is a general perception that the effective implementation of an adequate internal control system (ICS) will normally lead to improved operations and performance. IC is a process which is designed to enhance operational efficiency, promote the reliability of financial information, and ensure compliance with the applicable laws and regulations. In recent years, IC has become the focus of attention every time a notable scandal has arisen in the corporate world. An effective ICS can prevent an organisation from committing fraud and errors, and also provide it with assurance and competitive advantages. Some researchers argue that, in order to have a robust IC system, an integrated system, such as an ERP system, is needed. This research aims to develop a contingency framework for an IC system by operationalising the support of a successful ERP system. In order to achieve the research aim, three hypotheses have been identified, which were derived from the existing literature and tested in a quantitative study. A questionnaire has been developed (containing four parts) and sent to 213 companies that have implemented ERP in Saudi Arabia. A hundred valid responses were received. Partial Least Squares Structural Equation Modelling (PLS-SEM) was adopted for the data analysis and hypotheses testing. The results suggest that the organisational structure, prospectors’ strategy, organisational culture and management support can help to explain the effectiveness of ICPs.

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Page 1: The Relationship between the Enterprise Resource … Relationship between the Enterprise Resource ... effective implementation of an adequate internal control system ... the ability

The Relationship between the Enterprise Resource Planning (ERP)

Systems Internal Control Procedures

Hani Shaiti

University of Bedfordshire & King Faisal University

Yanqing Duan Syamarlah asaratnam

University of Bedfordshire University of Bedfordshire

Abstract

There is a general perception that the effective implementation of an adequate internal control

system (ICS) will normally lead to improved operations and performance. IC is a process which is

designed to enhance operational efficiency, promote the reliability of financial information, and

ensure compliance with the applicable laws and regulations. In recent years, IC has become the

focus of attention every time a notable scandal has arisen in the corporate world. An effective ICS

can prevent an organisation from committing fraud and errors, and also provide it with assurance

and competitive advantages. Some researchers argue that, in order to have a robust IC system, an

integrated system, such as an ERP system, is needed.

This research aims to develop a contingency framework for an IC system by operationalising the

support of a successful ERP system. In order to achieve the research aim, three hypotheses have

been identified, which were derived from the existing literature and tested in a quantitative study.

A questionnaire has been developed (containing four parts) and sent to 213 companies that have

implemented ERP in Saudi Arabia. A hundred valid responses were received. Partial Least Squares

Structural Equation Modelling (PLS-SEM) was adopted for the data analysis and hypotheses

testing. The results suggest that the organisational structure, prospectors’ strategy, organisational

culture and management support can help to explain the effectiveness of ICPs.

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Introduction There is a general perception that the enforcement and application of a proper internal control

system (ICS) will normally improve an entity’s operations and performance. Internal control is a

crucial feature of an organisation’s governance system and is essential for supporting the

achievement of an organisation’s objectives.

In recent years, Internal Control (IC) has become the focus of attention every time there is a

notable scandal in the corporate world. For instance, Enron, WorldCom and Tyco in the US,

Parmalat, and Ahold in Europe have faced a breakdown in their ICS. It is an obligatory task for an

entity’s management to improve its ICS. An effective ICS can prevention an organisation from

committing fraud and errors, and provide it with assurance and a competitive advantage.

Some researchers argue that, in order to have a robust IC system, an integrated system, such as an

ERP system, is needed (Huang et al., 2008). ERP systems have the ability to control user access

and facilitate the separation of duties, which is one of the most common IC mechanisms used in

order to deter fraud within financial systems. Moreover, there are other factors that can provide

support to ensure that an IC system is effective, although the research in this area remains scarce

(Morris, 2011).

Therefore, to address this gap, it is important to investigate the factors that can improve an ICS.

For this purpose, this study will be guided by “the Contingency Theory”, which is built on the

argument that there is no one best way to organise an organisation, so the optimal course of action

depends on external or internal variables. A better organizational performance depends on a better

match between the (internal) control system and contingent factors (Fisher, 1998). The remainder

of this paper presents the literature review, theoretical framework and hypothesis development,

research method, results and discussion as well as the conclusion to the study.

Literature Review There has been a little empirical and archival research on the area of ERP systems. Kumar et al.

(2008) investigated the challenges facing an organization regarding the compliance of their ERP

systems to the IC requirements, particularly those imposed by the SOX Act. They found that the

companies faced technical, process-related, and cultural barriers regarding these requirements.

Maurizio et al. (2007) indicated the need for fully integrated systems like ERP systems to prevent

interruption to the data flow.

ERP vendors (e.g. SAP, Oracle) have taken advantage of the improvement in IC regulations by

updating the system’s reports and features. ERP systems can produce control and exception reports

which help to improve the monitoring and the segregation of duties (Turner and Owhoso, 2009).

ERP systems can provide ICPs with the tools for gathering, analyzing and reporting information

(Kumar et al., 2008). Researchers have found that companies using IT systems reported fewer IC

weaknesses than those that have not adopted IT systems (Klamm & Watson, 2009; Morris,

2009). Morris (2011) argued that the “built-in control” features and other features that ERP

systems have can help an organization to improve its ICPs and reduce its IC weaknesses.

ERP systems are able to support other frameworks such as ERM and COSO frameworks (Brown

and Caylor, 2006). ERM is a framework that can manage and reduce the different types of risk.

Ramamoorti and Weidenmier (2006) stated that the technology is associated with all of the COSO

ERM frameworks’ components. Chang and Jan (2010) designed an ERP IC framework using

COSO components and other items. They stated that the framework can help the shareholders,

managers, and auditors to assess the effectiveness of ICPs.

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Authors The Model dimensions contributions limitations

DeLone

&

McLean

(1992)

Informatio

n System

Success

Model

- System Quality

- Information Quality

- Use

- User satisfaction

- Individual Impact

-Organisational

Impact

-Measure the IS

success in different

levels

-Classification for

multitude of IS

evaluation.

-Different

stakeholders

evaluating the IS

success

- Did too much

-Inappropriateness

of the use as a

dimension.

-Overlapped of user

satisfactions

Myers,

Kappelm

-an &

Prybutok

(1997)

Comprehe-

nsive

Model for

Assessing

the ISF

-DeLone & McLean

(1992) 6components

-Service Quality

- Work Group

Impact,

-Consider the overlap

-Describes how

measures can be

determine.

-Contengency factors

-Carried some

DeLone & McLean

model problems

Gable,

Sedera &

Chan

(2003)

ERP

Success

Measurem-

ent Model

-System Quality

-Information Quality

-Individual Impact

-Organisation

Impact,

-First assessed the

ERP success and

tested.

- Eliminated two of

DeLone and

McLean’s

dimensions

-Complete set of

tested ERP measures.

-Tested data only

from Australian

public

organisations, only

SAP.

-Ignoring the

Service Quality

dimension.

Although the academic literature covers ERP systems and IC, it has paid too little attention to

studying the impact of ERP systems’ success on IC (Huang et al., 2008). According to Al-Mashari

(2003), many companies that have implemented ERP have failed to achieve the system’s estimated

benefits (e.g. cost reduction). It has been argued that companies should assess the value of the

system (Heo and Han, 2003). Basically, assessing ERP success refers to evaluating the

performance of an ERP system post-implementation. Gable et al. (2003) defined an ERP system’s

success as the utilisation of the system to achieve the organisational goals. The literature includes

several IS (ERP) success models, such as that of DeLone and McLean (1992); Myers et al. (1997)

and Gable et al. (2003) (see Table 1).

Table 1: the IS and ERP success models

Theoretical Development and Hypotheses Formulation The theoretical framework helps to determine the study’s key variables, the type of the

relationships that link the key variables and the theoretical assumptions of the related theory. It

also provides a basis for the study’s hypotheses and the selection of appropriate research method(s)

in order to address the research question(s). The theoretical framework is based on the contingency

theory. The contingency theory of an organisation is a significant theoretical lens that can be used

to view the organisation (Donaldson, 2001). It has been structured by theorists such as Burns and

Stolker (1961), Perrow (1970) and Galtung (1967) within the period of organisational theory in the

early 1960s. Basically, the term contingency means that something is true only under specific

conditions.

There has been a history of more than three decades of published research about contingency

theory and the different aspects of management accounting practices as well as information

systems (Chenhall, 2007; Otley, 1980; Hong and Kim, 2002). Otley (1980) proposes the

application of the contingency approach to management accounting practices, as “there is no

universal appropriate control system which applies to all organisations in all circumstance”

(pp413).

The core of the structural contingency theory model is that organisational effectiveness (i.e. ICPs’

effectiveness, in this study) results from fitting the organisational characteristics, such as

organisational systems, to contingencies that reflect the situation of the organisation (Donaldson,

2001). In other words, contingencies influence the effect of the organisational characteristics on the

organisational effectiveness. Thus, contingency theory can be used to examine the impact of the fit

between ERP systems and the contingency variables, such as the organisational structure, strategy

or size, on the effectiveness of ICPs.

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There are several forms of theoretical fit, according to Chenhall (2007), that have been utilised to

categorise the contingency-based research in the field of management accounting systems,

including the selection approach, system approach, fit (congruence and interaction) approach,

intervening variable approach and, more recently, the structure equation models (SEM) approach

(such as PLS-SEM). This study uses the SEM approach, which can predict the relationships

between contingencies, the success of an ERP system and the effectiveness of ICPs, and analyse

the effects into direct and indirect ones through the success of ERP systems (Smith and Lagfield-

Smith, 2004; Hall and Smith, 2009; Elbashir et al., 2011).

Figure 1 the Theoretical Framework

-Contingency Variables

The literature suggests that a number of contingency variables may affect the relationship between

the ERP system and the effectiveness of ICPs, including the external environment, organisational

structure, size, organisational strategy, management support and organisational culture (Otley,

1980; Gable et al., 2003; Rae and Subramaniam, 2008).

This study found, from the literature, sufficient clues that suggest that there exist a number of

important contingency variables when considering the relationship between an ERP system and the

effectiveness of ICPs, including the strategy, structure, size, organisational culture and

management support. Appendix 1 shows the measures of the study’s constructs.

-Hypotheses

In order to investigate the relationship between ERP systems and IC effectiveness and to

understand the relationships between the variables and the study constructs, a theoretical

framework was developed (Figure 1). The theoretical framework is based on three main

relationships, which are illustrated by the three main hypotheses as follows:

Structure,

strategy, size,

support,

culture

ERP Maturity,

Brand, Year

Implementati

on

Effectivene

ss of ICPs

Success of

ERPs

Organisational determinants

ERPs determinants

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1. Contingency Variables and ERP systems’ success

Myers et al. (1997) indicate that considering contingency theory will improve the quality and

productivity of the IS functions in order better to meet the need of an entity. A review of the

literature reveals that the organisational structure, strategy, size, management support,

organisational culture, and maturity of an ERP system affect its success. Within this group, there

are twelve hypotheses, including two mediation hypotheses. They are illustrated as follows:

H1: Organisational structure is positively associated with ERP system success

H2: There is a positive association between prospector strategy and ERP success.

H3: There is a positive relationship between organisational size and ERP success.

H4: Organisational culture positively influences the ERP success.

H5: There is a positive correlation between top management support and ERP success.

H6: There is a relationship between the ERP brand and ERP success.

H6a: There is indirect relationship between ERP brand and ERP success.

H7: The years of ERP implementation are positively associated with ERP success.

H7a: The years of ERP implementation are indirectly associated with ERP success.

H8: There is a positive correlation between the maturity of ERP functions and ERP success.

H9: The ERP brand is negatively associated with the maturity of the ERP functions.

H10: There is a positive relationship between the years of ERP implementation and the maturity of the

ERP functions.

2. Contingency Variables and the effectiveness of ICP

Several studies have investigated the relationship between the number of contingency variables and

the management control systems (Otley, 1999; Chenhall, 2007; Abdel-Kader and Luther, 2008). As

a result of reviewing the literature, the researcher came up with five important contingency factors,

including: organisational structure, strategy, size, management support, and organisational culture,

which may be related to the effectiveness of ICPs. Within this group, there are five hypotheses,

which are structured as follows:

H11: Organisational structure is associated with ICP effectiveness.

H12: There is a relationship between the strategy prospectors and ICP effectiveness.

H13: A large organisation is positively associated with ICP effectiveness.

H14: There is a positive relationship between organisational culture and ICP effectiveness.

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H15: There is a positive relationship between management support and ICP effectiveness.

3. ERP system success and ICP effectiveness

This group of hypotheses contain the main hypothesis of this research, which is the relationship

between the success of ERP systems and ICP effectiveness. Little empirical research related to the

area of ERP systems and IC has been published (Huang et al., 2008). For instance, Gupta and

Kohli (2006) investigated the benefits of ERP systems and found that SAP R/3 integrates the

processes, data, and firm elements and units within a single software package. This tight

integration feature can defend the system’s source code. Morris (2011) argues that the “built-in

control” features and other features of ERP systems can help an organization to improve its

internal control procedure. The study finds that companies that have adopted ERP systems are

reporting less internal control material weaknesses than companies that have not adopted them.

Additionally, an ERP system can play a mediation role in influencing the effectiveness of

ICPs. Therefore, there is a direct and indirect relationship between the success of ERP systems,

the contingency variables and ICP effectiveness. Accordingly, it can be hypothesised that:

H16: ERP success is positively associated with ICP effectiveness.

H16a: There is an indirect relationship between the contingency variables and ICP effectiveness.

Research Method The aim of this section is to illustrate how to achieve the study objectives. The pathway of the

research should be supported by a research philosophy. No one research philosophy is better than

another. The question of which is ‘better’ depends on how the researcher seeks to answer the study

question(s) (Saunders et al., 2009). This study will adopt the positivist paradigm that will involve

collecting quantitative data in order to address the research questions. This paradigm depends on

the assumption that the social reality is more objective and includes unbiased decisions. Because

the positivist study measurement is an essential element of the research process, the data are highly

specific and precise, and so the findings tend to be more reliable (Collis and Hussey, 2009).

Under the positivist paradigm, research is deductive. Therefore, the research was started by

developing the theoretical structure including the three main hypotheses after reviewing the

literature. The survey approach was used to collect the main data and test the study hypotheses.

-Sample and Data Collection

All Saudi companies that were found to have implemented an ERP system were included in the

study sample. However, since there was no existing database of the ERP system population relative

to the field of study, Saudi Arabia, various sources of data were used in the current study. These

include some experimental studies on Saudi Arabian companies (such as Al-Muharfi, 2010; Al-

Turki, 2011). The research contacted some of the ERP system vendors in Saudi Arabia (e.g. SAP

and Oracale) to gain the names of the companies that have implemented an ERP system in Saudi

Arabia. Additionally, some websites were used; for example, those of the top international ERP

systems’ vendors, the Minister of Commerce and Industry, and certain Saudi’s companies. Finally,

a list of the 213 companies that have implemented an ERP system in Saudi Arabia was created.

For the data collection, an initial questionnaire was developed, based on the literature review. The

questionnaire contains four sections. The first section measures the effectiveness of the internal

control procedures (EICPs). The second section measures ERP success. The third section

investigates the impact of CVs. The last section includes demographic questions. The questionnaire

was distributed to the study sample, and 110 valid responds were received (with a response rate of

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52%). After collecting the empirical data, they were analysed using two types of software: SPSS

and Partial Least Squares (PLS).

-Partial Least Squares

PLS is an approach to SEM that has been utilised for many years, especially in psychology and

social sciences researches, including many business researches (e.g. Fornell and Larcker, 1981)

and information systems researches (e.g. Vinzi et al., 2010). Regardless of the increased use of

PLS path modelling in other business disciplines (e.g. marketing), the popularity of PLS-SEM (and

other SEM modelling techniques) in the accounting discipline has slowly increased (Lee et al.,

2011). There are a few empirical studies in the field of accounting that have used PLS-SEM (e.g.

Hall 2008; Hall and Smith, 2009; Elbashir et al., 2011). According to Lee et al. (2011), the

unwillingness to use PLS-SEM in accounting research may be due to a lack of understanding about

its benefits and how to use it. PLS-SEM is a latent variable modelling technique that provides a

good opportunity for path modelling to move forward without being limited to restricted

assumptions, such as normality and a large sample size (Hall, 2008).

Results

-The Measurement Model

Before assessing the significance of the study’s variables’ relationships, it is an important to assess

the measurement model. First, the research removes all of the cases and indicators that have over

10% of missing data. Thus two cases and six indicators (two related to internal control, three to

ERP success and one to the maturity of the ERP system) were removed. Second, the factor loading

for each indicator was examined. All items load onto their respective constructs; however, seven

items (CA1, Serv.Q, Strategy6, OC4, OC5, MS2 and Maturity1) have factor loadings of less than

0.5 (Hulland, 1999), which ranks them between 0.469 for Maturity1 to 0.44 for MS2. A low factor

loading adds a few values to the model explanation, so these were removed (Hulland, 1999; Hair et

al., 2010). Table 2 shows the factor loading of the indicators.

Table 2 the Correlation Matrix of the Constructs and Indications

Brand Culture Dec. EICPs ERP Form. MS Maturity Size Strategy Team-based

Year Imp

Brand 1 -0.175 0.022 -0.179 -0.105 -0.011 -0.074 -0.186 -0.404 -0.057 0.004 0.014

Culture1 -0.233 0.838 0.269 0.486 0.29 0.435 0.441 0.15 0.097 0.339 0.357 -0.012

Culture2 -0.228 0.793 0.272 0.496 0.194 0.394 0.418 0.245 0.06 0.419 0.394 -0.038

Culture3 -0.114 0.788 0.501 0.497 0.266 0.396 0.527 0.15 -0.005 0.486 0.491 0.110

Culture6 0.051 0.636 0.418 0.461 0.222 0.299 0.623 0.166 -0.136 0.485 0.422 0.136

Structure3 0.022 0.477 1 0.511 0.238 0.549 0.609 0.201 -0.082 0.447 0.568 0.106

IE -0.119 0.483 0.468 0.739 0.221 0.492 0.588 0.327 -0.03 0.586 0.385 -0.020

RA -0.06 0.486 0.41 0.726 0.237 0.496 0.433 0.144 -0.019 0.516 0.327 0.096

CA -0.192 0.552 0.481 0.873 0.32 0.624 0.58 0.312 0.092 0.659 0.407 -0.001

InfCo -0.167 0.483 0.237 0.775 0.495 0.372 0.374 0.358 0.009 0.427 0.267 0.045

M -0.154 0.467 0.376 0.788 0.519 0.338 0.539 0.419 0.088 0.47 0.323 -0.006

SQ -0.147 0.281 0.232 0.485 0.893 0.358 0.259 0.564 0.154 0.314 0.308 0.144

IQ -0.071 0.211 0.089 0.354 0.870 0.298 0.111 0.515 0.174 0.256 0.193 0.083

IndIm -0.051 0.29 0.24 0.37 0.863 0.286 0.282 0.4 0.096 0.269 0.216 -0.074

OIm -0.077 0.316 0.257 0.329 0.804 0.279 0.178 0.486 0.081 0.266 0.182 0.164

Structure1 -0.014 0.375 0.402 0.423 0.185 0.807 0.313 0.198 0.081 0.521 0.345 0.045

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Structure2 -0.007 0.481 0.535 0.596 0.399 0.926 0.489 0.154 0.026 0.577 0.425 0.041

MS1 -0.059 0.489 0.485 0.551 0.225 0.361 0.862 0.314 0.05 0.565 0.439 0.091

MS3 -0.183 0.553 0.494 0.537 0.187 0.381 0.848 0.291 0.056 0.512 0.460 0.038

MS4 -0.029 0.628 0.596 0.584 0.226 0.405 0.890 0.189 -0.078 0.473 0.525 -0.048

MS5 0.001 0.6 0.539 0.588 0.202 0.513 0.880 0.232 -0.098 0.537 0.537 0.020

Maturity2 -0.235 0.237 0.173 0.313 0.567 0.222 0.273 0.861 0.208 0.216 0.208 0.233

Maturity3 -0.154 0.184 0.091 0.288 0.499 0.011 0.203 0.860 0.138 0.117 0.137 0.257

Maturity4 -0.094 0.147 0.135 0.379 0.413 0.157 0.257 0.794 0.097 0.307 0.267 0.180

Maturity6 -0.102 0.182 0.276 0.364 0.403 0.261 0.235 0.781 0.053 0.234 0.233 0.279

Size -0.404 0.009 -0.082 0.039 0.15 0.054 -0.023 0.158 1 0.11 -0.006 0.288

Strategy1 -0.059 0.409 0.317 0.425 0.193 0.43 0.461 0.255 0.209 0.744 0.405 0.118

Strategy2 -0.077 0.416 0.321 0.595 0.291 0.525 0.448 0.187 0.173 0.891 0.341 0.042

Strategy3 -0.067 0.46 0.375 0.581 0.226 0.486 0.528 0.151 0.108 0.903 0.508 0.081

Strategy4 0.033 0.511 0.399 0.488 0.26 0.459 0.444 0.163 0.029 0.810 0.561 0.072

Strategy5 -0.062 0.559 0.452 0.73 0.357 0.694 0.615 0.31 -0.005 0.861 0.520 0.007

Structure4 0.004 0.543 0.568 0.441 0.267 0.448 0.565 0.25 -0.006 0.553 1 0.104

Year Imp 0.014 0.063 0.106 0.026 0.1 0.048 0.027 0.288 0.288 0.068 0.104 1

Third, the Cronbach’s alpha, Composite reliability and convergent validity were assessed. As

shown in Table 3, on the value of the Cronbach’s alpha, the composite reliability for all of the

constructs is above 0.7 (Hulland, 1999; Hair et al., 2010). Additionally, the Average Variance

Extracted (AVE) values for all constructs are more than 0.5 degrees (Fornell and Larcker, 1981).

Table 3 Summary of Cronbach’s alpha, Composite reliability and convergent validity

Construct AVE Composite Reliability

R Square

Cronbachs Alpha

Communality Redundancy

Brand 1 1 1 1

Year Imp 1 1 1 1

Size 1 1 1 1

MS 0.757 0.926 0.893 0.757

Culture (Collaboration) 0.866 0.928 0.846 0.866

Culture (Coordination) 0.722 0.839 0.616 0.722

Strategy 0.708 0.923 0.896 0.708

Structure (Decentralisation) 1 1 1 1

Structure(Formalisation) 0.758 0.862 0.693 0.758

Structure(Team-based) 1 1 1 1

Maturity 0.684 0.896 0.122 0.847 0.684 0.022

ERP 0.744 0.921 0.454 0.885 0.744 -0.007

EICPs 0.612 0.887 0.668 0.840 0.612 0.097

Fourth, the discriminant validity was assessed by using the Fornell-Larcker technique (Fornell

and Larcker, 1981). Table 4 shows that all of the square roots of AVE for the study’s constructs are

higher than the correlation between each construct and another (in the same row or column).

Therefore, all of the constructs have an agreeable level of discriminant validity.

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Table 4 Square Root of AVE and Correlation Matrix of Study Constructs

Brand Culture Dec. EICPs ERP Form. MS Maturity Size Strategy Team based

Year Imp

Brand 1

Culture -0.175 0.767

Dec. 0.022 0.476 1

EICPs -0.179 0.633 0.5108 0.782

ERP -0.105 0.319 0.2375 0.454 0.858

Form. -0.011 0.499 0.5489 0.601 0.359 0.869

MS -0.074 0.653 0.6086 0.650 0.241 0.478 0.870

Maturity -0.186 0.231 0.2011 0.400 0.579 0.195 0.292 0.825

Size -0.404 0.009 -0.0819 0.039 0.150 0.054 -0.023 0.158 1

Strategy -0.057 0.563 0.4466 0.687 0.323 0.630 0.599 0.257 0.110 0.844

Team-based 0.004 0.543 0.5675 0.441 0.267 0.448 0.565 0.250 -0.006 0.553 1

Year Imp 0.014 0.063 0.1058 0.026 0.100 0.048 0.027 0.288 0.288 0.068 0.104 1

-Testing the Hypotheses

The structural model was estimated using SmartPLS software in order to test the hypotheses. The

software makes no distributional assumptions, so bootstrapping (500 samples with replacement) is

applied to test the statistical significance of each path coefficient (Hair et al., 2013). Table 5 as well

as Figure 2 illustrate the results of the significance of each path coefficient.

Table 5 the Significance of Path Coefficient

Path from Path To

Predicted sign Maturity ERP EICPs

Brand -,+ 0.190** 0.035

Year Imp +,- 0.297*** 0.113

Culture (Collaboration) +,+ 0.081 0.183*

Culture(Coordination) +,+ 0.249* 0.003

MS -,+ 0.223 0.287**

Size +,- 0.098 0.023

Strategy +,+ 0.094 0.299***

Structure (Formalisation) +,+ 0.235* 0.102

Structure(Decentralisation) -,+ 0.087 0.139

Structure(Team-based) +,- 0.033 0.157*

Maturity + 0.551***

ERP + 0.225**

R² 0.122 0.454 0.668 ***, **, and * Significant at 0.01, 0.05, and 0.1 levels respectively (two-tailed).

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Figure 2: Path Diagram with Path Coefficients-Whole Sample

Among the contingency variables, organisational structure (Team-based), management support,

organisational strategy and organisational culture (collaboration) were found to be significantly

associated with EICPs. Additionally, it was found that ERPs’ success was significantly related to

the EICPs. However, size was not significantly associated with the EICPs.

It was found that organisational culture (coordination), the maturity of the ERP system and the

organisational structure (formalisation) were significantly related to the success of ERP systems,

whereas organisational size, strategy and management support were not significantly associated

with ERP success. The results of this chapter provided evidence of the mediation effect of ERP

success on the relationship between organisational structure (formalisation), organisational culture

(coordination) and EICPs.

Discussion and Conclusion The objective of this research was to propose and validate a contingency model that explains the

role of ERP success in supporting the effectiveness of ECPs. The results from testing the

hypotheses are summarised below in Table 6:

Table 6 Summary of the study hypotheses Result

Contingencies and ERPs success H1:Organisational structure is positively associated with the ERP system

success

Partially

Accepted

H2: There is a positive association between prospector strategy and ERPs

success.

Rejected

H3: There is a positive relationship between organisational size and

success of ERP system.

Rejected

H4: Organisational culture positively influences the success of ERP

systems.

Partially

Accepted

H5: There is a positive correlation between top management support and

ERPs success.

Rejected

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H6:There is a relationship between the ERP brand and success of ERP

system

Rejected

H6a:There is indirect relationship between the ERP brand and success of

ERP system

Rejected

H7:The year of ERP implementation positively associated with the

success of ERP systems

Rejected

H7a:The year of ERP implementation indirectly associated with the

success of ERP systems

Accepted

H8:There is a positive correlation between the maturity of ERP functions

and success of ERP systems

Accepted

H9:The ERP brand is negatively associated with maturity of ERP

functions

Accepted

H10: There is a positive relationship between the year of ERP

implementation and the maturity of ERP functions.

Accepted

Contingencies and EICPs H11: Organisational structure is associated the effectiveness of ICPs. Partially

Accepted

H12:There is a relationship between the strategy prospectors and the

effectiveness of ICPs

Accepted

H13:A large size organisation is positively associated with the

effectiveness of ICPs

Rejected

H14:There is appositive relationship between the organisational culture

and the effectiveness of ICPs

Partially

Accepted

H15: There is a positive relationship between management support and the

effectiveness of ICPs.

Accepted

ERPs success and EICPs H16: Success of ERP systems is positively associated the effectiveness of

ICPs.

Accepted

H11a: There are indirect relationships between the structure

(formalisation) and the effectiveness of ICPs.

Accepted

H14a: There are indirect relationships between the culture (coordination) and the effectiveness of ICPs.

Accepted

- Contingencies and ERP success

The results indicate that organisational structure (formalisation), organisational culture

(coordination) and the maturity of the ERPs’ functions significantly predict the success of ERP

systems. Researchers, such as Gable et al. (2003), DeLone and McLean (2003) and Ifinedo (2006)

discuss the importance of contingency factors on the success of ERP systems. Contingency factors

like the structure, strategy size and organisational culture have been studied in relation to ERPs’

implementation, but few researchers have investigated these variables with regard to the success of

ERP systems (post-implementation). Ifinedo and Nahar (2009) find that organisational structure

and size influence the success of ERP systems. They point out that centralisation, specialisation

and formalisation are adequate for assessing ERP success, which is similar to the current study’s

finding, except with regard to size. Chou and Chang (2008) observe that an organisational culture

that embraces coordination influences the benefit of ERP systems.

Additionally, Saunders and Jones (1992) speculate about the importance of the maturity of IS’s

functions, but very few studies examine the effect of the maturity of ERPs’ functions. Voordijk et

al. (2003), show that the maturity of the IT infrastructure is an important factor for a successful

ERP system implementation. Dias and Souza’s (2004) study’s results point to a relationship

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between the level of maturity of the ERP systems and the potential for perceiving a competitive

advantage, so this study adds more evidence about the importance of the structure (formalisation

and centralisation), organisational culture (coordination) and maturity of ERPs’ functions in

predicting the success of ERP systems.

- Contingencies and EICPs

The results illustrated in Table 6 show that the structure (team-based), prospectors’ strategy,

management support, and an organisational culture that embraces collaboration significantly

predict the EICPs. Waterhouse (1975) observes a relationship between the organisational structure

and the effect and use of the budgets. The study’s findings, in general, agree with those of many

other researchers. For instance, Waterhouse (1975) observes a relationship between organisational

structure and the effect and use of the budgets. Rajaratnam and Chonko (1995) find empirical

evidence of the relation between organisational strategy and organisational performance. Bititci et

al. (2006) suggest the existence of a relationship between organisational culture, management style

and the performance measurement system. Moynihan and Ingraham (2004) find that the top

management matter with regard to the use of performance information in decision making and also

to the organisational effectiveness.

- Success of ERP systems and EICPs

This study confirms that the success of ERP systems significantly predicts the EICPs. The field

study findings (for the relationship between ERP systems and ICPs) are similar to those of

Maurizio et al. (2007)and Morris (2011). Maurizio et al. (2007) indicate the need for fully-

integrated systems like ERP systems to prevent interruption to the data flow. Morris (2011) argues

that the “built-in control” features and other features of ERP systems can help an organization to

improve its internal control procedure. The study finds that companies that have adopted ERP

systems are reporting less internal control material weaknesses than those that have not adopted

them.

- Conclusion

The current study’s main aim is to develop a structure model of the contingency variables and ERP

system success that can predict the effectiveness of ICPs for Saudi Arabian companies. The

structure mode was developed at the beginning of this paper, following by an assessment of the

variables that predicate the effectiveness of ICPs. The results indicate a positive role for the

success of ERP systems in predicting the EICPs. Additionally, the results show the mediation

effect of the success of ERP systems on predicting the EICPs.

Appendix

Appendix 1: The variables measures

N

o

Variables References

1

ER

P

syst

e

m

succ

e

ss

dim

e

nsi

on

s

System

quality:

refer to the

Data accuracy, Data currency, Database

contents, Ease of use, Ease of learning, Access,

User requirements, System features, System

(DeLone and McLean,

1992; Myers et al.,

1997; Gable et al.,

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enviable

characteristic

of the system

accuracy, Flexibility, Reliability, Efficiency,

Sophistication, Integration, Customization

2003)

2 Information

quality:

refer to

enviable

characteristic

of the system

output

Importance, Availability, Usability,

Understandability, Relevance, Format, Content

Accuracy, Conciseness, Timeliness,

Uniqueness

DeLone & McLean

(1992); Myers et

al.(1997); The Gable et

al. (2003)

3 Services

quality: refer to the

quality of the

support from

the IT or IS

dep.

Responsiveness, reliability, assurance,

accuracy, technical competence.

Myers et

al.(1997);(DeLone and

McLean, 2003),

(Seddon, 1997)

4 Individual

impact: refer

to the extent

of the system

contribution

to the

individual

Learning, Awareness / Recall, Decision

effectiveness, Individual productivity

DeLone & McLean

(1992); Myers et

al.(1997); The Gable et

al. (2003)

5 Organisatio

n impact : refer to the

extent of the

system

contribution

to the

organisation

Organizational costs, Staff requirements, Cost

reduction, Overall productivity, improved

outcomes/outputs, increased capacity, e-

government, Business Process Change

DeLone & McLean

(1992); Myers et

al.(1997); The Gable et

al. (2003)

6

Co

nti

ng

ency

var

iab

les

Organisation

structure

- Diversified occupational speciality

- Descriptive of the jobs.

- Participation of employees in decisions

- Relationship b/w manger and staffs

Pugh et al. (1968)

Donaldson (2001)

7 Organisation

strategy

-Supporting new products/services

- Leading to innovation

-Responds quickly to opportunity

-Competitive activities.

-Promotes long range planning/decisions

-Involving in high-risk projects

(Croteau and

Bergeron, 2001;

Chenhall, 2007)

8 Organisation

size

Total of assets Mabert et al 2003,

(Abdel-Kader and

Luther, 2008)

9 Organisation

al culture

- Employees work in project teams

- Employees willing to collaborate

- Coordination

- Controlling

- Meeting deadlines

-New ideas welcomes

(Detert et al., 2000;

Jones et al., 2006)

10 Management

support

- Supporting research and innovation

- Willing to take risks

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- Helps to provide necessary resources

- Involves employees in strategic plan.

- Providing direction and motivation.

- Delegating tasks to others

11 ERP brand The vendor of ERP systems (Wang et al., 2011)

12 Period of

ERP imp.

Number of year that ERP systems have been

implemented

(Wang et al., 2011)

13 Maturity of

the system

growth stages of the system

Nolan (1979)

14 dep.

var

Efficiency of

ICP

internal environment, objective setting, event

identification, risk assessment, risk response,

control activities, information and

communication, and monitoring

(COSO, 2004)

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