Developing Instruments for Enterprise Resources Planning (ERP) Post-Implementation Failure Model

Abstract

Implementing Enterprise Resource Planning (ERP) projects in many organizations are faced with failure concept in recent years. Researchers focused to implement ERP projects successfully by proposing the success model. However, through these attentions to get ERP benefits, the ERP failure measurement model is required. Therefore, the aim of this study is to develop the instruments for ERP post-implementation failure measurement model. To achieve this outcome, the study firstly evaluates the suitability of Technology-Organization- Environment framework for the proposed conceptual model. Constructs were used for this model included two formative and six reflective constructs. A questionnaire was developed to test the validity and reliability of instrument items. A survey was conducted among Iranian industries to collect data and data analyzed by Smart PLS software. The results indicated that all instruments items included 37 critical risk factors (CRFs) as measurement were acceptable for the ERP post-implementation failure model.

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68 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
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 Keywords:CriticalRiskFactors(CRFs),ERPFailureDimensions,ERPPost-Implementation,
ERPProjects,ERPSystemFailureMeasurementModel
ABSTRACT
ImplementingEnterpriseResourcePlanning(ERP)projectsinmanyorganizationsarefacedwithfailure
conceptinrecentyears.ResearchersfocusedtoimplementERPprojectssuccessfullybyproposingthesuccess
model.However,throughtheseattentionstogetERPbenets,theERPfailuremeasurementmodelisrequired.
Therefore,theaimofthisstudyistodeveloptheinstrumentsforERPpost-implementationfailuremeasure-
mentmodel.Toachievethisoutcome,thestudyrstlyevaluatesthesuitabilityofTechnology-Organization-
Environmentframeworkfortheproposedconceptualmodel.Constructswereusedforthismodelincluded
twoformativeandsixreectiveconstructs.Aquestionnairewasdevelopedtotestthevalidityandreliability
ofinstrumentitems.AsurveywasconductedamongIranianindustriestocollectdataanddataanalyzedby
SmartPLSsoftware.Theresultsindicatedthatallinstrumentsitemsincluded37criticalriskfactors(CRFs)
asmeasurementwereacceptablefortheERPpost-implementationfailuremodel.
Developing Instruments
for Enterprise Resources
Planning (ERP) Post-
Implementation Failure Model
MaliheMotiei,DepartmentofInformationSystem,FacultyofComputing,Universiti
TeknologiMalaysia(UTM),Johor,Malaysia
NorHidayatiZakaria,DepartmentofInformationSystem,FacultyofComputing,Universiti
TeknologiMalaysia(UTM),Johor,Malaysia
DavideAloini,DepartmentofEnergy,Systems,LandandConstructionsEngineering,Pisa
University,Pisa,Italy
MohammadAkbarpourSekeh,DepartmentofComputerEngineering,IslamicAzad
University,ShirvanIran
DOI: 10.4018/IJEIS.2015070105

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 69
1. INTRODUCTION
Enterprise resource planning (ERP) can be defined as a software system to integrate processes
for all major business functions across an organization such as production, distribution, sales,
finance, and human resources management (Sumner, 2000). It has been proved that ERP sys-
tems provide significant benefits, efficiency, productivity and service quality and reduction in
service costs (Ngai, 2008). However, reports have indicated that majority of ERP systems after
implementation are failed or cancelled (Amin Amid et al., 2012; Jiwat Ram, 2013). Current lit-
erature on ERP research has focused on software selection, implementing processes and critical
success factors (CSFs) of implementation rather than the success of ERP post-implementation.
Whereas, the actual benefits and performance improvements are gained at post-implementation
(Jiwat Ram, 2013; Young et al., 2013).
Organizations need to define ERP post-implementation review (PIR) to measure success
of system (Musaji, 2005). Such evaluation can offer improvements to overcome the risks, but
in large organization is not easy. There are several success models proposed by researchers for
evaluating the ERP system’s success (Ifinedo, 2007; Princely Ifinedo, 2010). By reviewing the
recent research, we found that there is lack of ERP post-implementation failure measurement
model. It means that apart from concentrating on the success model, proposing effective failure
model is essential. Because, by attention to failure model, the current risks are identified and risk
management as a popular approach can help managers to control risks. Therefore, risks could be
evaluated and monitored properly. These efforts generate an effective strategy toward to success.
Thereby, proposing ERP system failure measurement model is the research gap.
This study theoretically develops a comprehensive conceptual model that determines risk
dimensions on ERP post-implementation failure. The proposed conceptual model was made based
on Technological, Organizational and Environmental theory. An extensive systematic review and
semi-structured interviews were conducted at the early stage of the research to determine the
measuring instruments. With the result of this stage, the taxonomy of critical risks was determined
through the review of the literature. We conducted a field survey among manufacturing sectors
in Iranian industries to empirically test the validity of instruments. To achieve this outcome,
internal consistency reliability was used via the partial least-square (PLS) method for validating
the measuring instruments.
This paper is structured as follows: Section two describes the theoretical background. This
review serves the basis for ERP failure model based on theoretical background and measure-
ments items. Section three discusses instruments development. Section four indicates the research
methodology. Subsequently, the measurements items were examined at section five. Section six
is conclusions.
2. THEORETICAL BACKGROUND
2.1. ERP Post-Implementation Failure Issues
Several ERP failure reasons have been reported. ERP failure has been attributed these reasons:
inadequate implementation of ERP (Edith Galy, 2014), manager reluctant to use the system
(Nunes, 2009), lack of vendor’s support (El Sayed, 2013), user resistance (Garg et al., 2013;
Haider, 2013), replacement of users after training (Amin Amid et al., 2012), lack of employee
morale and motivation (Edith Galy, 2014). Particularly, all failure definitions are referred to user’s
unwillingness to work with ERP system. Most studies have noted that the user’s performance to
work with the system is strongly related to success/failure of ERP system. Moreover, Salermon

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70 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
stated that ERP maintenance is key activities for ERP post-implementation. ERP maintenance
covers user’s relationships and roles, software maintenance evolution and drives the user’s sup-
ports. Hence, if the maintenance activities performed inadequate, the failure will be occurred
(Jose L. Salmeron et al., 2010).
2.2. ERP System Failure Measurement Model
The significant research gap is to propose an ERP failure model. To propose the failure model,
measuring instruments should be determined. Particularly, the risk factors affect the ERP
post-implementation failure. Therefore, the risk factors should be identified through the risk
assessment articles at post-implementation stage. The main keywords to find the articles were
“ERP post-implementation”, “risk factors”, “risk assessment”, and “risk affecting”. The articles
include a great number of risk factors through implementation and post-implementation phases.
Hence, the articles were systematically and critically analysed and compared based on “content
analysis” procedures (Patton, 1990) in order to identify any possible risks which occur during
use, maintain or enhance of ERP systems in the organizations (Harris, 2003).
Peng (Peng et al., 2009) proposed risk ontology in ERP post-implementation in 2009. In the
proposed risk ontology, four main categories listed as Operational risks (OR), Analytical risks
(AR), Organisation-wide risks (OWR), and Technical risks (TR) were introduced. Operational
risks refer to risks that lead to perform daily business activities by users. Analytical risks (AR)
refer to managerial risks. Organisation-wide risks (OWR) refer to using and maintaining ERP
systems. Technical risks (TR) refer to unpredictable technological changes and technological
readiness. Later, the authors in (Nunes, 2009) assessed risk factors among Chinese SOEs (State-
Owned Enterprises). Afterwards, other authors used the Peng ontology to assess the ERP post-
implementation risks in their studies (El Sayed, 2013; Khaleel Ahmad, 2012; Jose L Salmeron et
al., 2012). Singh assessed human risks in ERP post-implementation based on Peng risk ontology
content (Singh et al., 2010). Salmeron assessed risks in ERP maintenance and stated the ERP
maintenance is a key action for post-implementation (Jose L. Salmeron & Lopez, 2010). They
(Jose L. Salmeron & Lopez, 2010) presented a general risk taxonomy that affected performance
of ERP maintenance in which the risk factors were examined through assessment process.
In 2012, Amid and Moalagh (Amin Amid et al., 2012) identified and classified the critical
failure factors (CFFs) in Iranian industries. In addition, Moalagh and Zare developed a practical
framework to assess ERP post-implementation success among Iranian industries (Morteza Moalagh,
2012). The other papers with different titles were related to assess the ERP post-implementation
risks (Edith Galy, 2014; El Sayed, 2013; Haider, 2013; Jiwat Ram, 2013; Morteza Moalagh,
2013; Woosang Hwang, 2013).
These CRFs should be categorized based on risk dimensions. Accordingly, the risk dimen-
sions refer to technological risks (information technology), organizational risks (organizational
transformation) and external risk (pressures and vendor’s supports) (Haider, 2013; Sumner,
2000; Yan Zhua, 2010). The aforementioned three dimensions can adapt within Technology-
Organization-Environment (TOE) theory. This theory describes how technological innovation
adoption occurs at firm level (Tornatzky, 1990). This theory contends that the assimilation of IS
in an organizational including the implementation and post-implementation is affected by fac-
tors related to technology, organization, and environment. Many early studies used this theory
to investigate the adoption of IS. Afterwards, researchers began to apply this theory to examine
the ERP post-adaption issues (Haider, 2013; Hassan Elnaby, 2012; Yan Zhua, 2010).

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 71
3. RESEARCH MODEL AND INSTRUMENTS DEVELOPMENT
The research model was developed based on TOE theory (Haider, 2013; Yan Zhua, 2010). Since,
TOE theory provides general context to examine the ERP post-implementation (Yan Zhua, 2010),
it should be extended into formative and reflective constructs (Ehie et al., 2005; Huang et al.,
2004; Peng & Nunes, 2009). Reflective constructs and formative constructs were determined
based on risk ontology and TOE components respectively. Decision rules to specify formative
and reflective constructs were adapted from Jarvis (Cheryl Burke Jarvis, 2003). Hence, two
formative constructs and six reflective constructs were chosen for ERP system failure measure-
ment model. Inadequate implementation and poor organizational decision making as formative
constructs and operational risks, technical risks, top management risks, managerial risks, lack
of external supports and user’s inefficiency as reflective constructs were facilitated for this ex-
amination. The figure 1 shows the proposed conceptual research model.
3.1. Formative Constructs
3.1.1. Inadequate Implementation
Implementation does play a very important role, because it can determine the quality of the in-
stallation and affect the atmosphere of the organisation (Young & Ahn, 2013). Inadequate imple-
mentation points out the problems such as lack of integration and conflicts between implemented
modules. These problems decrease the ERP performance, business operational efficiency and
ERP acceptance (El Sayed, 2013; Nunes, 2009). Indeed, ERP implementation depends on how
the employees use the system. Unwillingness among employees to use the newly-implemented
ERP system is one of the most commonly cited reasons for ERP failures (Khaleel Ahmad, 2012;
Pan et al., 2011; Singh et al., 2010).
Figure1.Proposedconceptualresearchmodel

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72 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
3.1.2. Poor Organizational Decision Making
Organizational risks refer to poor decision making from managers and top management to provide
the system needs and gather sufficient resources for the system operations (Kim, 2009; Kwak,
2009). Many risky issues are involved within the organization which pervious work emphasis that
core issues to success of failure come from organizational body (Chou, 2014; Joseph Nwankpa,
2014). The organization context covers the informal decision making and communication process
between employees (Joseph Nwankpa, 2014). For example, top managements are not experts in
information technologies (IT), and also they are not users who use the ERP system extensively
in their daily work. Therefore they typically lack sufficient experience of operational situations
and technical knowledge to make appropriate decisions on IT solutions on their own (Pan &
Peng, 2011; Yu, 2005).
3.2. Reflective Constructs
3.2.1. Operational Risks
Operational risks are related to user’s performance to use the ERP system (Nunes, 2009). ERP
systems are mainly designed to integrate and automate transaction processing. These activities
required extremely high data accuracy to work effectively (Chou, 2014; Edith Galy, 2014; El
Sayed, 2013). Users with low performance can generate the risky issues for ERP post-imple-
mentation (Chou, 2014; Joseph Nwankpa, 2014). For example, inventory record is one of the
most important elements of organizational data which is stored in ERP systems. If users store
inventory records inadequately, the ERP system may be mismatched with actual stock (Nunes,
2009; Peng & Nunes, 2009).
3.2.2. Technical Risks
Technical risks refer to inadequate technology capabilities to work with ERP system (Nunes,
2009). These capabilities are defined within poor ERP system capability and inadequate configura-
tion according to organization’s planned requirements. Poor-quality of technical implementation
affects negatively the system to support managerial and operational performance (Nicolaou,
2004). Low integration of ERP modules, poor dashboard user-interface design and complexity
of ERP system characteristics decrease the amount of user’s interest before actual usage. These
characteristics negatively influence user’s attitude to have unrealistic expectation about system
features (Amin Amid et al., 2012; El Sayed, 2013).
3.2.3. Top Management Risks
Top management always provide the necessary resources such as financial to improve the sys-
tem and maximize its benefits (Hoch, 2013). Lack of emotional supports from top management
influence on employee morale and motivation (Edith Galy, 2014). This is considered as one of
the most important risk factors in ERP post-implementation (Amin Amid et al., 2012; Davide
Aloini, 2012; El Sayed, 2013). In fact, top managements make regular meeting and discussion
within ERP team members to solve the problems while their experience in operational situations
and technical knowledge are not enough to make effective decisions. Therefore, one of the main
failure issues related to top management is insufficient support for ERP maintenance (A. k. Amin
Amid, 2014; Chou, 2014; El Sayed, 2013). Hence, decision by top managers without the advice
or involvement of the IT managers is a risk that may frequently occur in IT projects (Häkkinen
et al., 2008; Musaji, 2005; P. Ifinedo, 2007; Yu, 2005).

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 73
3.2.4. Managerial Risks
Installing ERP system is not merely a computer project and there are variable issues are involved
(Aloini et al., 2012; Musaji, 2005). Frequently, Managers do not manage the risks involved
in these projects properly (Aloini et al., 2007). Front-line managers are key users of the ERP
system and they are crucial actors in the systems (Hoch, 2013). Managers must pay attention to
some main activities include the involvement of business units, business process reengineering
needed. However, due to reluctance to change and insufficient training program, managers may
often refuse to use the ERP system in real practice (Chou, 2014; Edith Galy, 2014). Therein,
they may not be able to use the system to improve planning and forecasting activities and the
exploitation of ERP system became less.
3.2.5. Lack of External Supports
The ERP post-implementation failure is also influenced within external risks by various resources
of organization (Hassan Elnaby, 2012). The business environment refers to entities that exist in
their industry such as clients, suppliers, competitors in industry, obligations from government
regulatory bodies and other external pressures (Woosang Hwang, 2013).
3.2.6. User’s Inefficiency
Unwillingness among employees to use the newly-implemented ERP system is one of the most
commonly cited reasons for ERP failures (Ala’a Hawari, 2010; Kim, 2009). The consequences of
ERP implementation depend on how the employees use the system. Employees and workers face
radical changes in business process reengineering and should be familiar with new procedures
and processes. End-user resistance are as one of the main contributing factors towards the failure
(Edith Galy, 2014). Human risks are different, some of them come from system feature (Amin
Amid et al., 2012) and some of them are individually (Singh et al., 2010; Upadhyay et al., 2010).
4. RESEARCH METHODOLOGY
This study conducted a hybrid approach using both interviews and literature review to develop the
measurement items. There are also some risk factors that might have not been well documented
in available research works. The research method to extract the risks was “content analysis”
through the reviewing literature.
4.1. The Sample of Survey
ERP implementation among developing countries (DC) is less likely to succeed. This is because
of some factors such as lack of skills and technology, absence of good quality data, user resis-
tance, and cultural issues (El Sayed, 2013; Salih, 2011; Singh et al., 2010). Our target is Iranian
industries as part of developing countries for data collection. As the current failure rate of ERP
is mainly evidence among DC countries (Ala’a Hawari, 2010; Hakim et al., 2010; Kim, 2009;
Lin, 2009). Therefore, this study conducted semi-structured interview within the ERP managers
and consultants to identify the failure issues and risk factors in Iranian industries. The target of
this study was ERP projects team members that face to challenges directly. They know about
the problems occurred after implementation. ERP managers and IT managers indicated some
critical failure factors (CRFs) such as lack of strong support from ERP vendors.

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74 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
4.2. Instruments Development
Risk factors as measurement items are defined by reviewing the literature in the domain of each
construct. The risk factors were revised and adapted within risk dimensions domain in develop-
ing countries. Moreover, the chosen risks were adapted with the risks in Iranian ERP industries
through the interviews. To verify the instruments, the content validity method was applied to
ensure that the instrument items are well established (sekaran, 2000). The structure and context of
proposed conceptual model reflects the relevant of previous author’s knowledge (Ala’a Hawari,
2010; Nunes, 2009; Yan Zhua, 2010). To identify any measurement problem, the questionnaire
was investigated carefully in order to find any anomalies. Therefore, the questionnaire was
distributed among ERP researchers and potential respondents (Lawley, 2000). We got some
minor comments to improve the structure and content of the questionnaire from the respondent’s
feedback. Table 1 shows the risk dimensions and their resources.
4.3. Face-Validation Approach
The next step to validate the questionnaire is using Face-validation approach to validate the
questionnaire effectively (Grant, 1996). Face-validation is applied to assure applicability the
questionnaire. Questionnaire is sent to ERP managers and IT managers by email. In addition,
Table1.ERPfailuredimensionsandtheirsources
ERP Failure Dimension Name No. of
Items
Sources
Operational risks OP 4 (D’Ambrosio, 2011; Nunes, 2009; Peng et
al., 2010)
Technical risks TCHN 6 (Amin Amid et al., 2012; Chen, 2009; El
Sayed, 2013; Häkkinen & Hilmola, 2008;
Mei Ling Keong, 2012; Nunes, 2009; Yu,
2005)
Top management TOPMGN 3 (Ala’a Hawari, 2010; David Gwillim, 2005;
Edith Galy, 2014; Gwillim et al., 2005;
Häkkinen & Hilmola, 2008; Hoch, 2013;
Jiwat Ram, 2013; Jose L. Salmeron &
Lopez, 2010; Singh et al., 2010)
Managerial MANGR 8 (Ala’a Hawari, 2010; Andreas I. Nicolaou,
2006; Basu et al., 2012; Kwak, 2009; Lin,
2009; Peng & Nunes, 2009; Yu, 2005; Zafar
U. Ahmed, 2006)
Lack of external supports ENR 6 (Azadeh Pishdad, 2012; Edith Galy, 2014;
El Sayed, 2013; Haider, 2013; Hassan
Elnaby, 2012; Woosang Hwang, 2013;
Young & Ahn, 2013)
ERP post-implementation Failure ERP FAIL 4 (Amin Amid et al., 2012; Azadeh Pishdad,
2012; El Sayed, 2013; Haider, 2013; Hoch,
2013; Woosang Hwang, 2013; Young &
Ahn, 2013)
User’s inefficiency USER 6 (Chou, 2014; Edith Galy, 2014; Hassan
Elnaby, 2012; Jiwat Ram, 2013; Singh et
al., 2010)

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 75
interview was conducted to understand the failure issues and risk factors descriptions and their
classification. Comments are applied; some measurements were removed and changed. Totally,
37 risk factors were selected into questionnaire. Instruments items of this questionnaire are
available in appendix B (Table 4).
4.4. Questionnaire Structure
The next step to develop the questionnaire is to define the control variables. Control variables are
very important to specify the valuable data as well. Therefore, three questions were defined. The
first question is the working experiences in the large organization and second one is the working
experiences in the ERP projects. Third question is related to respondent’s positions. Nine posi-
tions were defined to show the data sample’s demographics, Respondents include the employees
who serve the management level and key users. These groups of respondents were selected since
they deal with risky issues daily. 37 questions were put in questionnaire. The questionnaire was
structured through this basis question: “to what extend the chosen risk factors influence on ERP
failure in post-implementation”. The answers were assessed by a seven-point likert scale. The
respondents were required to give their rating for each item, 7 representing “strongly agree” and
1 representing “strongly disagree”.
4.5. Data Collection
A survey was used to collect empirical data from Iranian industries among manufacturing sec-
tors. Some criteria were determined to identify appropriate respondents before gathering data
including: First, the organizations should have basic modules from an ERP package. Second,
the ERP system should also be implemented at least two years before to ensure that it has passed
the shakedown phase and has stepped into post-implementation stage (Yan Zhua, 2010). Third,
the organizations in our sample must be sufficient large, more than 500 employees. Four large
organizations as manufacturing sectors were selected. 100 questionnaires distributed among
respondents. Totally, 60 data were collected.
4.6. Data Analysis Method
The structural equation modelling (SEM) technique using Smart PLS 2.0 was used to analysis
the data (Henseler, 2009). It does not depend on sample size and data. The Smart PLS allows
estimation of models when sample size is small (Barclay, 1995). Two type of assessments are
supported by PLS (Barclay, 1995), the measurement model assessment and structural model
assessment. The measurement model offers psychometric properties, such item reliability,
convergent and discriminant validities of the measurement scales. In this study, we used the
measurement model assessment.
5. RESULTS
The quality of constructs and items in measurement model were validated by examining each
factor’s reliability. For this purpose, the internal consistency reliability, convergent validity and
discriminant validity for constructs were assessed. The construct presentations of proposed model
include ENR: Environmental, ERP FAIL: ERP failure, TECHNOLO: inadequate implementa-
tion, OP: Operational system risks, TCHN: technical risks, TOPMGN: top management risks,
MANGR: managerial risks, ORG: Organizational risks. Table 2 shows the results. The results

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76 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
demonstrate that all constructs report adequate validity. Composite reliability should be higher
than 0.7 (in exploratory research, 0.6 to 0.7 is considered acceptable (Fornell, 1981). Coronbach’s
alpha (CA) considers as a conservative measure of internal consistency. Table 2 shows that the
CA for all constructs are above the 0.7. The CR values of all the constructs were found to exceed
the recommended threshold of 0.7, majority of construct are around 0.8.
Indicator reliability shows that indicator’s outer loadings should be higher than 0.7. Indica-
tors with outer loading between 0.4 to 0.7 should be removed if deletion leads to an increase in
composite reliability and AVE above the suggested threshold value. Some questions were removed
in this stage. Convergent validity (AVE) should be higher than 0.5 (Fornell, 1981). Table 2 shows
the AVE of all construct are acceptable. Discriminant validity state the square root of the AVE of
each construct should be higher than its highest correlation with any of other construct (Henseler,
2009). Each construct checked, as table 2 shows refer to Ifinedo study (Princely Ifinedo, 2010),
square root of AVEs considered to prove discriminant validity.
In addition, item loading table shows that the measurement item’s weights are high. More-
over, the chosen constructs also were selected correctly. The results are available in appendix
A (Table 3). Therefore, the measurements items and constructs accurately identified for ERP
post-implementation failure model.
6. IMPLICATION FOR RESEARCH AND PRACTICE
This study has implications for further research to understand what risks are critical and how
those leads to ERP failure by structural model assessment. Few studies are available in related
work in post-implementation assessment to investigate quantitatively (Jiwat Ram, 2013). Pre-
vious research applied to assess the success of ERP post-implementation. Hence, according
to success model consideration to achieve the ERP benefits, the failure model is required to
establish. According to high failure rate, the proposing ERP failure can increase the knowledge
of ERP team members and researchers toward for preventing the ERP Failure. This study filled
this gap appropriately. The findings have implications for further research to understand failure
issues for practitioners as well. In addition, our study served the IS theory evaluation to propose
research model.
Table2.Resultsofthetestsofreliability,convergentvalidity,discriminantvalidity,andcronbach
Alpha
Constructs AVE CR CA ENR FAIL MANGR OP ORG TCHN TOP
Mangmt
TECH USER
ENR 0.54 0.872 0.836 0.734 0 0 0 0 0 0 0 0
ERP FAIL 0.638 0.876 0.809 0.633 0.798 0 0 0 0 0 0 0
MANGR 0.545 0.915 0.894 0.775 0.817 0.738 0 0 0 0 0 0
OP 0.767 0.908 0.848 0.663 0.531 0.652 0.887 0 0 0 0 0
ORG 0.506 0.918 0.901 0.761 0.843 0.979 0.659 0.711 0 0 0 0
TCHNOL 0.548 0.916 0.895 0.666 0.643 0.716 0.904 0.732 0.740 0 0 0
TOPMGN 0.647 0.846 0.729 0.48 0.660 0.615 0.478 0.761 0.56 0.804 0 0
TECH 0.551 0.88 0.835 0.601 0.633 0.679 0.756 0.699 0.963 0.549 0.742 0
USER 0.604 0.92 0.868 0.764 0.733 0.820 0.633 0.830 0.743 0.604 0.74 0.777
CR: Composite Reliability CA: Cronbachs Alpha

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 77
The study presents the taxonomy of risks which it provides the potential foundation to apply
risk assessment as main procedure of risk management. Moreover the research model presents
the hierarchy risk level and future work can use this multi-criteria approach such as Salmeron
study (Jose L. Salmeron & Lopez, 2010) to assess the level of risks for example by using AHP
methodology (Huang et al., 2004).
7. CONCLUSION
This study proposed ERP post-implementation failure measurement model based on TOE theory.
Therefore, the paper examined the instruments items for ERP post-implementation failure model.
A pre-analysis test was conducted through the survey among Iranian industries. This examination
showed that the instruments items are valid and reliable. This study used the smart PLS software
to assure the measurement assessment. Totally, 37 items were examined in this questionnaire.
ACKNOWLEDGMENT
The authors would like to thank the anonymous reviewers and the editor for their insightful
comments and suggestions.
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MaliheMotieiisaPhDcandidateattheDepartmentofInformationSysteminFacultyofCom-
putingatUniversitiTeknologiMalaysia(UTM).SheholdsaBScdegreeinComputerSoftware
EngineeringfromIslamicAzadUniversityinIranandanMScdegreeinInformationTechnol-
ogyManagementfromUniversitiTeknologiMalaysia.HerresearchinterestsincludeEnterprise
ResourcePlanningSystems,InformationSecurity,andRiskManagement.HerMaster’sThesis
focusedontheareaofInformationSecurityAwarenessMeasuring.Currently,sheisdoingresearch
onEnterpriseResourcePlanningEffectivenessandERPpost-implementationRiskassessment.
ShehaspublishedpapersinCITA07,WorldAcademyofScienceEngineeringandTechnology,
JournalofInformationassuranceandSecurity,andICSIPA2011.
NorHidayatiZakariaisanacademicmemberoftheFacultyofComputingatUniversitiTeknologi
Malaysia(UTM),Skudai,Johor.SheholdsaPhDfromtheUniversityofQueenslandofTechnology
SystemsandaMaster’sdegreeinComputerSciencefromtheUniversitiTeknologiMalaysia.She
holdsaBachelor’sdegreeinInformationTechnologyfromtheUniversitiKebangsaanMalaysia
(UKM).Hermainresearchinterestsincludeinnovativesolutionsfor“knowledge-based”infor-
mationsystemsandKnowledgeIntegrationforEnterpriseSuccess.Shehaspublishedpapersin
JournalofEnterpriseInformationManagement,InternationalJournalofEnterpriseInformation
Systems,JournalofTheoreticalandAppliedInformationTechnology.
DavideAloini is Associate ProfessorofBusinessProcessManagement at the Department of
Energy,Systems,LandandConstructionsEngineeringattheUniversityofPisa,Italy.Heholds
aPhDinManagementEngineeringfromtheUniversityofRome.In2008,hewasrewardedwith
aCitationofExcellenceAwardbyEmeraldforhisresearchontheorganizationalimpactofIS
projects.HisresearchinterestsincludeSupplyChainandInformationSystemmanagement,Risk
Managementand Innovation Management. Mostofhisresearchactivityhas been concerned
withtheapplicationofRiskmanagementtechniquestoERPprojects.Hehaspublishedpapers
ininternationaljournalssuchasInformation&Management,EuropeanJournalofOperation
Management,ProductionPlanning andControl,ExpertSystems withApplicationsandInter-
nationalJournalofInnovationManagement.
MohammadAkbarpourSekehisanassociateprofessorandanacademicmemberofIslamicAzad
UniversityinIran.HeholdsaBScdegreeinComputerSoftwareEngineeringfromIslamicAzad
UniversityinIran,anMScdegreeinComputerSoftwareEngineeringfromFerdowsiUniversity
inIranandaPhdDegreeinComputerSciencefromUniversitiTeknologiMalaysia.Hisresearch
interestsincludeBusinessModelGeneration,IntrusionDetection,PatternClassification,Image
ForgeryDetectionandDesignPatternSelectioninSoftwareEngineering.Currently,heisdoing
researchonInformationSecurityandE-BusinessDevelopment.MohammadAkbarpourSekeh
haspublishedpapersinDigitalInvestigation,CITA07,WorldAcademyofScienceEngineering
andTechnology,JournalofInformationAssuranceandSecurity,andICSIPA2011.

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82 International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015
APPENDIX A
Item Loading Weight
Table3.ItemLoadingWeight
Items ENR FAIL MANGR OP ORG TCHN TOPMGN TECH USER
TCH1 0.5674 0.3428 0.5193 0.6081 0.5037 0.739 0.2997 0.764 0.5463
TCH2 0.3832 0.4235 0.4289 0.5552 0.4643 0.7275 0.4376 0.7694 0.4816
TCH3 0.4648 0.5458 0.628 0.5233 0.6097 0.6135 0.3701 0.5974 0.5096
TCH4 0.3289 0.5532 0.4771 0.4979 0.5201 0.7236 0.4914 0.7906 0.5425
TCH5 0.4147 0.2911 0.4478 0.5906 0.4493 0.7191 0.3147 0.7453 0.6162
TCH6 0.52 0.6726 0.5447 0.5898 0.5837 0.7548 0.5275 0.7704 0.5938
OP1 0.5372 0.5846 0.6311 0.8988 0.6295 0.8665 0.431 0.7571 0.5545
OP2 0.5762 0.3431 0.5166 0.9027 0.5385 0.8132 0.446 0.6864 0.549
OP3 0.6464 0.4636 0.5658 0.8231 0.5622 0.6783 0.3752 0.5185 0.5664
TOP1 0.3793 0.4631 0.422 0.3434 0.5428 0.4678 0.7712 0.4934 0.4779
TOP2 0.4069 0.5116 0.4751 0.3959 0.5988 0.4618 0.8139 0.456 0.485
TOP3 0.3765 0.6056 0.5727 0.4103 0.6832 0.4294 0.8276 0.3914 0.496
TOP4 0.3765 0.6056 0.5727 0.4103 0.6832 0.4294 0.8276 0.3914 0.496
FAIL1 0.5837 0.8842 0.7333 0.4956 0.7570 0.5495 0.6005 0.5114 0.5344
FAIL2 0.6592 0.7547 0.6545 0.5198 0.6582 0.5912 0.4609 0.57 0.6534
FAIL3 0.4174 0.7626 0.5711 0.3037 0.6193 0.4698 0.5774 0.5157 0.5824
FAIL4 0.354 0.7876 0.6456 0.3671 0.6525 0.4435 0.4684 0.4295 0.5847
MAGR1 0.5389 0.5712 0.6329 0.435 0.6138 0.4044 0.3495 0.3406 0.629
MAGR2 0.6873 0.7562 0.8392 0.5984 0.8068 0.6589 0.4491 0.6245 0.7038
MAGR3 0.6158 0.6142 0.737 0.5005 0.7142 0.57 0.4205 0.5541 0.6329
MAGR4 0.5632 0.5265 0.7337 0.4639 0.7246 0.5252 0.4854 0.508 0.5265
MAGR5 0.5816 0.5634 0.7733 0.524 0.761 0.49 0.5013 0.4142 0.5697
MAGR6 0.5454 0.7212 0.8105 0.532 0.8366 0.5605 0.6644 0.5117 0.6029
MAGR7 0.5234 0.5754 0.6527 0.4118 0.6654 0.5476 0.4971 0.5781 0.6264
MAGR8 0.504 0.5256 0.6787 0.3052 0.6373 0.4094 0.3089 0.4341 0.5778
MAGR9 0.5878 0.554 0.7613 0.5249 0.7161 0.5652 0.3617 0.5297 0.5999
ENR1 0.8642 0.5619 0.6817 0.6024 0.6517 0.5413 0.3538 0.4475 0.6471
ENR2 0.8187 0.5242 0.6136 0.526 0.6047 0.4989 0.3913 0.4304 0.5729
ENR3 0.7117 0.5113 0.5761 0.4787 0.581 0.5907 0.4138 0.6046 0.6605
ENR4 0.6592 0.7547 0.6545 0.5198 0.6582 0.5912 0.4609 0.57 0.6534
ENR5 0.8419 0.5652 0.6865 0.5568 0.6635 0.5787 0.3852 0.5332 0.6553
ENR6 0.5995 0.2086 0.4028 0.4322 0.4031 0.3764 0.2875 0.3065 0.3508
USER1 0.6199 0.5535 0.6444 0.5611 0.622 0.6672 0.3535 0.6736 0.8341
USER2 0.6162 0.5347 0.614 0.4179 0.6162 0.5053 0.4304 0.5093 0.7886
USER3 0.6558 0.6967 0.7484 0.6055 0.7698 0.7062 0.6003 0.6989 0.8723
USER4 0.6414 0.7066 0.699 0.507 0.7028 0.6669 0.4949 0.6987 0.8166
USER5 0.636 0.3874 0.6043 0.4656 0.5964 0.4544 0.3895 0.4079 0.6791
USER6 0.3827 0.4366 0.4793 0.3653 0.5321 0.3736 0.5349 0.3372 0.6451

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International Journal of Enterprise Information Systems, 11(3), 68-83, July-September 2015 83
APPENDIX B
Instrument Items
Table4.InstrumentItems
TCH1: Poor establishment of the standards to measure the quality of system
TCH2: Different modules of the ERP system are not seamlessly integrated
TCH3: System is not properly modified to meet new business requirements
TCH4: Poor data quality and documentation
TCH5: Invalid data is not automatically detected when getting new information
TCH6: using poor accounting systems and financial software
OP1: System contain inaccurate records (supplier/inventory record)
OP2: System contain inaccurate or incomplete bill of material and production schedule plan
OP3: System fail to use the ERP system to generate accurate sales and forecast
TOP1: Top management make decision to find solutions without external experts/consultant
TOP2: Changing top management position
TOP3: Internal conflicts between departments
TOP4. Changing team members position (key users’ replacement) after training
MAGR1: Managers do not get relevant and needed information from users
MAGR2: Inadequate measurement/tools for testing the system
MAGR3: Maintenance costs surpass the budget
MAGR4: Wrong estimating resources business needs and requirements
MAGR5: Loss qualified IT/ERP experts
MAGR6: Direction for further ERP development and improvement is unclear
MAGR7: ERP post-implementation development plan is misfit with business strategy
MAGR8: Data access right is authorised to inappropriate users
ENR1: Poor timeline delivery and sales services
ENR2: Lack of transfer significant knowledge and information by the vendors to company
ENR3: Lack of information Sharing between suppliers and buyers to coordinate transactions and processes
ENR4: Market and competitive pressures
ENR5: Political and Governmental pressures
ENR6: Pressures from high rate of customization
USER1: Users input incorrect data and stored into the system
USER2: ERP related problem are not reported to managers
USER3: Lack of ownership and release responsibilities
USER4: Users are not able to obtain needed data and information
USER5: Unwilling to take up additional responsibilities
USER6: Unrealistic expectations of users about the system features.
FAIL1: Front-line managers refuse to use the system
FAIL2: lack of strong support from vendor
FAIL3: Insufficient support for ERP post-implementation maintenance
FAIL4: Lack of sufficient training program regularly