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ISSN: 2289-4519

International Journal of Accounting & Business Management

www.ftms.edu.my/journals/index.php/journals/ijabm

Vol. 8(No.1), April, 2020

ISSN: 2289-4519 DOI: 10. 24924/ijabm/2020.04/v8.iss1/01.29

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Creative Commons Attribution 4.0 International License.

Research Paper

IMPACT OF CRITICAL SUCCESS FACTORS OF ERP IMPLEMENTATION

ON EFFICIENCY OF BUSINESS ORGANIZATION – A CASE OF WWF

MALAYSIA

Richard Wan

FTMS MBA Alumni,

FTMS Global Cyberjaya

[email protected]

Ismail Nizam

Head/Deputy Dean – School of Accounting and Business Management,

FTMS Global Malaysia

[email protected]

ABSTRACT The need for increased business prosperity and growth, organizations recognized that their internal processes must be geared towards efficiency, cost savings and higher level of productivity to achieve sustainability; many have adopted Enterprise Resource Planning (ERP), a business management system to operate more efficiently. However, there is little information on the awareness of organizations on the impact of key success factors of ERP implementation on efficiency of business organization. The adoption of ERP in Malaysia was widely spread across from small medium enterprise to multinationals but specifically, the existing research has less shed light on the factors that facilitate the success of ERP implementation by non-governmental organizations (NGOs) in Malaysia. Therefore, it is important to study the various factors that would contribute to the success of ERP implementation by NGOs efforts in Malaysia. The independent variables comprised of top management, organizational culture, business process re-engineering, training, user involvement, external pressure, project management, vendor support and implemented modules. To test the relationship between the theories and to establish the measurement model validity, the descriptive and normality analysis was used and multiple regression to test the hypotheses. The research design adopted for this research was explanatory and the target population were employees of WWF Malaysia in Klang Valley, Malaysia. The data collected from the employees via on-line self-administered questionnaires between March and April 2018. A sample of 108 employee’s responses was collected using a pre-designed survey questionnaire based on the 5-point Likert Scale. The data gathered from the questionnaires were recorded and coded into SPSS for analysis. The findings revealed that top management, organizational culture, external pressure, user involvement, training, business process re-engineering and training have a positive significant impact on the ERP implementation success. The regression analysis disclosed the implemented modules; project management and implementation success had an impact on the organizational performance. The outcome of the research would provide useful information to Malaysian non-governmental and business organizations to engage a more

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prudent and careful approach to implementing ERP in their IT project with consideration to all these key success factors.

Keywords: Enterprise Resource Planning (ERP), Critical Success Factors (CSF), ERP Implementation Framework Theory, Multiple Regression, Non-Governmental Organizations, Malaysia.

1. Introduction

ERP is an integrated functional business management software which serves its purpose of providing companies with competitive advantage through automation, business process alignment, communication and mobility covering areas such finance, distribution and manufacturing and some including warehouse management, the ERP applications market is expected to reach USD 84.7 billion by 2021 at a compound annual growth rate of 0.6%.

Worldwide ERP Software Market 2016-2021 Forecast, $M

Year 2016 2021 2016-2021 CAGR, %

Total 82267 84742 0.60%

Source: Apps Run The World, December 2017

According to analyst firm Gartner (Cloud, 2017), approximately 75 percent of all ERP projects was unsuccessful, although the industry’s focus was to deliver better customer service and better IT systems. But why? Given ERP is one of the biggest IT investments businesses make, particularly for mid-size organisations, it’s vital that the journey from supplier sourcing to end-users going live is a smooth one. A company’s ability to see a return on an ERP project tends to depend on how quickly it can deploy a new system, and whether it’s in line with what was promised at the outset. Any delay or overspend can have a massive impact. These research results suggest that the industry still has a long way to go in delivering the transparency businesses need to ensure implementation success, and in turn, their business goals. The rationale behind this research is to investigate how these key critical factors can determine the ERP implementation success and to avoid a delay paid back on the returns of investment.

There were several researches most recently conducted on the critical success factors in ERP implementation both in Malaysia and foreign countries on its significance

Author Purpose of Research Target Population

Adam (2009) The critical success factors of

ERP Implementation:

Malaysian and American experiences

Malaysian and USA companies

Ganesh & Mehta (2010)

Critical Success Factors for Successful Enterprise Resource Planning Implementation at Indian SMEs

Indian SMEs

Dezdar Ainin (2011)

Critical Success Factors for ERP Implementation: Insights from a Middle-Eastern Country

Iranian companies

Nikitovic, Strahonja (2012)

Critical Success Factors Aspects of the ERP Implementation

Croatian companies

Amini & Sadat Review Paper: Critical Success Factors for ERP Malaysian companies

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Safavi (2013) Implementation

Al-Sabaawi (2015)

Critical success factors for enterprise resource planning implementation success

Cihan University project in Iraq

Chaushi et. al (2016)

Critical success factors in ERP implementation Macedonia

Li, Chang & Yen (2017)

Investigating CSFs for the life cycle of ERP system from the perspective of

IT governance

Taiwan

Table 1. Researches conducted in Malaysia and foreign countries

Research Aim and Objectives The aim of this research is;

Examine the impact of critical success factors that would decide the success of ERP implementation in an organization in Malaysia.

Specific Objectives:

1. To examine the impact of people-factor on the ERP implementation success. 2. To examine the impact of process-factor on the ERP implementation success. 3. To examine the impact of technology-factor on the ERP implementation success. 4. To develop a framework within people, process and technology as a guideline to

help organization achieve ERP implementation success.

The structure of this research comprises of five chapters. Chapter One, the present chapter includes the introduction which provides the background to study, rationale for research, research objectives and questions, and the significance of research. Chapter Two, literature review defining the key concepts including critical reviews of related key theories and current research, establishing the research gap and designing the implementation framework with hypothesis synthesis of the critical key success factors ensuring implementation success. Chapter Three entails the methodology outlining the research approach, strategy and methods. Chapter Four shall present the findings, analysis and discussions from the survey results compared with the reviewed literature. Finally, Chapter Five, includes summary, limitations, conclusions and recommendations for future studies.

2. Literature Review

Below in Table 2 are the research topics concerning the key success factors in ERP implementation in various countries and businesses, evaluated and studied to understand what are the common key findings to determine a ERP pre-implementation process.

Table 2

Researcher (s), Year Critical Success Factors (CSFs) Research Outcome

(Al-Fawaz, Al-Salti & Eldabi, 2008) titled “ Critical success factors in ERP implementation: A review”

Top Management Support Business Plan and Vision Re-engineering business

process Effective project

management and project champion

The study reviewed the ERP literature and identify the benefits, drawbacks and the critical success factor in ERP implementation

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Teamwork and composition ERP System selection User Involvement Education and training

(Adam, 2009) titled “ The critical success factors of enterprise resource planning (ERP) implementation: A Malaysian and American Experience”

Top management Support Project missions and

strategies Project schedule and

planning Appropriate operational

technology Appropriate personnel, skills

and expertise Strong control system,

monitoring and feedback User acceptance

The study confirmed the positive impact of ERP on overall performance in both

countries with USA performing better than Malaysia. The findings demonstrated length of ERP implementation and quality performance are the two most important variables in

explaining firm’s overall performance

(Doom et al., 2010) titled “Critical success factors for ERP implementations in Belgian SMEs”

Vision, scope, and goals Culture, communication, and

support User involvement Effective change

management Internal communication Supplier management. Infrastructure Approach Focus on user requirements User training Alignment with business

processes Project management

The study demonstrates that

critical success factors for the implementation of ERP systems in SMEs may differ

substantially on some specific factors in Belgium as compared to other countries.

(Dezdar & Ainin, 2011) titled “Critical Success Factors for ERP Implementation: Insights from a Middle-Eastern Country”

Top Management Support Enterprise-Wide

Communication Business Plan and Vision Organizational Culture Appropriate Business and IT

Legacy Systems Project Management Business Process

Reengineering ERP Team Composition and

Competence Change Management

Program Project Champion User Training and Education User Involvement Careful Selection of ERP

Software

The report findings showed that some of critical factors may not be equally important to different countries and that ‘Top management support, Project management, Project champion, Business process reengineering and ERP team composition and competence’ are the top five critical factors for successful ERP systems implementation in Iranian firms.

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System Quality Software Analysis, Testing

and Troubleshooting Vendor Support Use of Consultant

(Chauhan, Dwivedi & Sherry, 2012) titled “Offshoring ERP Implementations: Critical Success Factors in Swiss Perspective”

Customer Interaction Skills Business Process Skills ERP Package Skills Scalability Language Project Management Choice of Work to be

Offshored Personnel Split Between

Onsite/Offshore

The study of critical success factors emphasized a broad spectrum of hard skills to soft skills. Soft skill factors are Customer Interaction Skills, Cultural Compatibility and Language. Hard skills are Business Process Skills, ERP Package Skills and Project Management.

(Mengistie, Heaton & Rainforth, 2013) titled “Analysis of the Critical Success Factors for ERP Systems Implementation in U.S. Federal Offices”

1. Strategic Factors Project management. Top Management

Support. Project champion. Clear goals and

objectives. Business plan and

Vision. 2. Tactical

Team Composition. User involvement and

motivation. Decision Making

Processes. Business Process

Reengineering (BPR). Inter-agency

communication and cooperation.

Change Management. Vendor Support. Effective Communication

3. Operational Factors

User Training and Education.

Dedicated Resources. Technological

infrastructure

The study was to empirically test the relationship between perceived effectiveness of managing IFs (independent variables) in ERP projects and project success results (dependent variables). The secondary purpose of this study is to analyse the implementation factors that contributed to the success of ERP implementations in U.S. Federal offices

(Beheshti et al., 2014) titled “ Selection and critical success factors in successful ERP implementation”

Top Management Support Project Management Interdepartmental

communication User training and education

The purpose of this study is to examine factors that contributed to:

• the motivations for acquiring

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Clear goals and objectives Change management plan Business process re-

engineering (BPR) Vendor support Use of consultants Minimal ERP customization User involvement in

evaluation, modification and implementation

Organizational culture

ERP systems;

• the strategies of successful implementation; and

• the cultural adjustments following implementation

(Al-Sabaawi, 2015) titled “Critical Success Factors for ERP Implementation Success”

Commitment and support of top management

Project management User training and education Business Plan and Vision Technological infrastructure Departments (Stakeholder)

participation Change Management Communication

The study was to explore the factors that influence the success and failure of ERP systems in Cihan university. the study tried to answer two main questions:

1. “What are the critical factors for ERP implementation success in a Cihan university?”

2. What are the KCSFs (Key Critical Success Factors, most preferred CSFs) that should be taken into high priority for the successful ERP implementation in a Cihan university and how they are ranked by sample?

(Chaushi, Chaushi & Dika, 2016) titled “Critical success factors in ERP implementation”

Organization and legacy systems

Clear and concise strategy Top management

sponsorship Project management

practices Change management

practices Team composition Clear procedures for data

entry and accuracy Training and streamlining

the communication Performance measurement Implementation approach

This study conducts state of the art literature review of critical success factors for enterprise

resource planning systems implementation success. It provides a more comprehensive list of ten factors that companies that have adopted and struggle with the implementation, as well as companies who are in the process of considering implementation of ERP system can easily adopt and follow

(Li, Chang & Yen, 2017) titled “Investigating CSFs for the life cycle of ERP system from the perspective of

Strategic alignment Risk management Resource management

This study investigates possible CSFs for the life cycle of an ERP system. This study also analyses the effects of CSFs from the perspective of

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IT governance” Information Technology Governance (ITG).

Reitsma and Hilletofth (2017) titled “Critical success factors for ERP system implementation: A user perspective”

Project Team Top Management

Involvement Strategic decision-making Communication Project Management Project Support Minimum customization Organizational change

management Business process alignment Software testing Performance measurement Education and training Technical possibilities

The study was to evaluate critical success factors (CSFs) for the implementation of an ERP system from a user perspective. The findings reveal that users regard eleven of the thirteen CSFs found in the literature as important for ERP system implementation.

Based on the current research results from the past ten years, for successful implementation these key factors have significant role to play. They are categorized under technology, people and process. Technology aspect includes the key elements of the ERP package selection, IT infrastructure, vendor tool/support, data conversion and integrity, system testing and troubleshooting, package and architectural choice. The people element includes top management support, user involvement, education and training, project champion, team composition, business plan and vision, effective communication and organizational change management. And finally, the process element takes into consideration of the organization business process re-engineering, decision making, communication, legacy systems, project management and implementation approach. These current researches will aid and provide sound understanding on how these key success factors in ERP implementation contribute to the relevance of this thesis.

Conceptual Framework and Hypotheses As stated earlier, the present study aims to (I) build a coherent conceptual framework consisting the most significant antecedents of ERP implementation success and (II) test that framework gathering quantitative data. The conceptual framework of this study incorporates nine (independent) factors, resulting from the qualitative and quantitative research and one dependent factor, namely ERP implementation success. Additionally, ‘organisational impact’ is added in the proposed conceptual framework to ascertain the effect of ERP implementation on various measures of company performance. The nine independent factors are external pressure, top management support, business process reengineering, organizational culture, user involvement, project management, training, implemented modules, vendor support.

A. External pressure can be defined as a continuous cooperation with a partner, supplier and/or customer by implementing ERP system for extrinsic motives. Sometimes companies are forced to implement such system as a prerequisite by their supply chain partners or by their competitors, while in the second case the decision is based on the need to adopt such system to avoid any possible downturn compared to what the competitors are doing so (Liang et al., 2007; Waarts et al., 2002). It is hypothesized that when a company find themselves

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vulnerable to the pressure from external environment, then tend to work harder to achieve towards their desired goals, therefore the higher the external pressure, the more successful will be the ERP implementation.

H1: External pressure has a direct positive effect on ERP implementation success.

B. Top management support can be easily defined as business executive’s involvement in areas related to ERP implementation (Sharma & Yetton, 2003). Several authors have highlighted this as a critical success factor for ERP implementation success (Zhang et al., 2005; Al-Mashari, 2003; Umble et al., 2003). Senior management plays two significant roles in ensuring the ERP implementation success as these projects are usually demanding in financial support and time consuming and the roles are leadership and supplying funds (Somers & Nelson, 2004). Senior management support should be offered during the whole implementation period without disruption and the tasks include communicating to all the employees, setting reasonable goals, proving engagement and setting limitations (Dezdar & Ainin, 2011). Support, participation and senior-level sponsorship are significant dimensions found to affect the ERP implementation success (Koh et al., 2006). ERP implementation includes extensive restructuring of business process and does not evolve around software engineering. Consequently, senior management should publicly, clearly indicate their support economic or not by highlighting the implementation priority (Koh et al., 2006), therefore:

H2: Top management support has a direct positive effect on ERP implementation success.

C. Business process re-engineering (BPR) is the reorganized thoughts and radical redesign of business process to achieve improvements in critical measures such as quality, cost, speed and delivery (Ettlie et al., 2005). ERP system does underlines the essential for BPR and compels the company to redefine, redesign workflows to fit the new system (Yusuf, Gunasekaran & Abthorpe, 2004). In a way business process re-engineering ensure compatibility with the implemented system and appears as important antecedent of ERP implementation success (Ettlie et al., 2005). Therefore:

H3: Business Process Re-engineering (BPR) has a direct positive effect on ERP implementation success.

D. Organizational culture represents a common sharing of convictions, ideologies, standards that have an impact on organizational activities and attitudes (Koh et al., 2006). A common culture shared among various members of the organization have an impact on the willingness for change, e.g. to adopt a new decision support system. Past research has indicated that organizational culture is significant to the success of most organizational changes (Jones, Celine & Ryan, 2006; Jarvenpaa & Staples, 2001). According to Jones, Celine and Ryan (2006) employee behavior towards knowledge sharing can be affected by organizational culture and it is crucial for the successful implementation of ERP systems. An organizational culture affects the implemenation of intranet and other IS systems used in an organization (Ruppel & Harrington, 2001).Hence it can be hypothesized that:

H4: Organizational culture has a direct postive effect on ERP implementation success.

E. User involvement increases user satisfaction and experience by forming realistic expectations regarding the system capabilities and increases the perceived level

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of control through participation in the whole project (Garg & Chauhan, 2015). It is one of the most influential factor in ERP implementation process as this will ensure the system will fit appropriately with the business processes since the development will be based on real needs. Additionally, according to several authors (Garg & Chauhan, 2015) resistance to change will reduce significantly when the users have participated in its development. Once all of the above criterias are met, the implementation of the ERP system will be successful and efficient.

H5: User involvement has a direct positive effect on ERP implementation success.

F. Project management refers to an ERP project time-tables, hardware equipment requirements, various milestones, workforce availability which is very crucial and should be carefully monitored and managed to ensure that will ensure the ERP implementation success (Al-Mashari, 2003). The project is risky and complex and requires excellent management as many parties are deeply involved (different business units, vendors/consultant, customers, suppliers), effective management will determine how this plethora of tasks are handled and managed (Hong & Kim, 2002). Management has high expectations on the implementation period to be completed on budget and time (Lee, Lee, & Kang 2008). Therefore, all the project collaborators are provided with reports and expected to attend meetings (Umble et. al, 2003).

H6: Project Management has a direct positive effect on ERP implementation success.

G. Training is part of a basic coverage in every ERP implementation project (Al-Mashari, 2003; Umble et al., 2003). Training should be organized before, during and after implementation and same time the technical and procedural parameters should be neatly addressed (Hong & Kim, 2002). The most efficient choice among all available methods is in-house training (on-the-job-training) (Zhang et al., 2005). Sufficient training provides employees with efficient use of the implemented ERP software and create a positive inclination towards the system, hence increases its utilization and acceptance while lack of training undermines the entire process (Dezdar & Ainin, 2011; Nah, Zuckweiler &Lee-Shang Lau, 2003; Bradley, 2008), moreover training enhances ease of use and increases the system success probablity.

H7: Training has a direct positive effect on ERP implementation success.

H. Implemented modules are the various functional components of an ERP system which can be implemented on a need to basis and special requirements therefore company do not need to perform a full-scale implementation (Madapusi & D’Souza, 2012). However according to (Yeh, Yang, & Lin, 2007) to benefit fully from ERP system it is unwise to avoid implementing the rest of the modules as past empirical studies have shown the effectiveness of the system have demonstrated all these modules relationship, so the more modules has been implemented the greater the company will reap the benefits from cross-functional cooperation (Mabert, Soni & Venkataramanan, 2001).

H8: The number of implemented software modules has a direct positive effect on ERP implementation success.

I. Vendor support is often provided by software solution providers or consulting firms. In most cases the solution software provider is also the consultant during or after the implementation (Tsai et al., 2011). Vendor support provides

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extended technical help, user training during and after implementation, maintenance support, software patches and updates, etc. They provide consultative, analytical advice regarding selection of the appropriate ERP system (El Sawah, Tharwat, & Rasmy, 2008). According to Wang, Lin, Jiang, & Klein (2007), vendors via experience sharing and knowledge transfer can significantly enhance the effectiveness of the implemented ERP software. It is through continuos collaboration, knowledge dissemination and formal training, software consultants can assist their customers to receive the full benefits of the implemented ERP system (Wang et al., 2007). The vendor trust worthiness is very important in ensuring the success or failure of the entire effort hence the close relationship with vendor is a critical success factor for the ERP implementation (Koh et al., 2006).

H9: Vendor support has a direct positive effect on ERP implementation success.

J. Organizational performance as presented in this study includes measures of several dimensions, such as cycle time, productivity, information flow, cost reduction and customer include both qualitative and quantitative measure of an organizational performance and this similar approach was followed by (Law & Ngai, 2007). Law & Ngai (2007) argued that many past studies investigated the impact of ERP implementation on performance has received fewer empirical examination therefore, it is hypothesized:

H10: ERP implementation success has a direct positive effect on organizational performance.

The synthesis of the hypothesis presented above formulates the proposed conceptual framework of the present study, it is underlined according to the best of researcher’s knowledge such a conceptual framework which has been examined before in literature and application to study in-depth in finding out further the level and impact it has on ERP implementation.

The proposed synthesis of the hypothesis is represented in figure 1 below to support the above study of critical success factors in ERP implementation

Figure 1. Proposed conceptual framework.

Organizational

Impact

H10

ERP Implementation

Success

H1

Top Management

H2

Organizational Culture

H3

External Pressure

H4

Business Process Re-engineering

H5

User Involvement

H6

Project Management

H7

Training

H8

Vendor Support

H9

Implemented Modules

ERP

Implementation CSF

Organizational

Performance

Organizational

Impact

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3. Research Design and Methodology

Positivistic Paradigm Crowther & Lancaster (2008) cited that positivist studies usually adopt deductive approach and relates to the viewpoint that researcher needs to concentrate on facts. In this research study the use of positivist paradigm as a basic notion and the research will be based on facts, with hypothesis formulation which can be tested. Therefore, the research findings in using positivism paradigm will be descriptive and it may also have some shortcomings as it will lack insight into in-depth issues given the fact there may be challenges and comfort level for the company’s management willingness to share their confidential information.

Research Design A research design is a method used for collecting and analysing the variables specified in the research study. The study can be descriptive, correlational, semi-experimental, experimental, review, meta-analytic (Creswell & Creswell, 2011). This research was based on explanatory research listing out all the descriptive issues affecting the implementation of ERP and how does each of these critical factors affects the outcome of its success.

Explanatory Research In this research findings on the Impact of key success factors of ERP implementation on Efficiency of Business Organization – A Case of WWF Malaysia, explanatory research was used to provide statistical data presented by others in the past rather exploratory research will be conducted. Also, because this research was perceived as critical problem which simply exists in business organization regardless of the industry.

Quantitative Method The objective of quantitative research is to develop and employ mathematical models, hypotheses pertaining to phenomena (Given, 2008). The qualitative method will include focus group, in-depth interviews, more subjective to describe a problem or condition from the point of view of those experiencing it. This is primary inductive process used to formulate theory or hypothesis whereas the quantitative method used which is number based. This research employed quantitative method to investigate the impact of critical success factors of ERP implementation on efficiency of business organizational performance based on the survey data collected.

Data Collection Method Primary data are collected with the objective of identifying some specific factors needed by the researcher. These data should not have been collected by another investigator previously to be primary data.

Population, sample Size and Sampling Method Selective sampling methods was used for this research analysis and for valid results, so that many people and company can be determined, the intent will be based on purposive reason such as studying a group. The investigation was based on the judgments of this research to learn more about non-probability sampling.

Data Analysis plan

Correlation Correlation refers to the strength of a relationship between two variables. Statistical software like SPSS can determine if relationships between two variables are present and how strong it is. The more popular type of correlation coefficient is the Pearson r. (Crossman, 2016)

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Regression Regression analysis is a related technique to assess the relationship between an outcome variable and one or more risk factors or confounding variables.

This research analysis plan, the correlation analysis was used to quantify the relationship based on the coefficient which is the Value of P to measure the positive and negative strength of the relationship between the critical success factors of ERP implementation success and its impact on the organizational performance.

4. Results and Discussion

Analysis of the Demographic Profile of Respondents Table 3 below shows the demographic profile of respondents with 47.7% being male and 52.3% female with majority aged between 35 to 49 years old, coupled with the level of maturity in understanding the critical success factors in ERP implementation on the efficiency of business organization. It is evident the position and number of years these employees have stayed with their organization to have the visibility of the company’s roadmap (Wairimu & Theuri, 2014). Out of the 22 respondents removed earlier due to outliers, some of them are respondents are junior position the fact they may lack the knowledge of the organization’s financial and strategic moves on ERP implementation (Wairimu & Theuri, 2014).

Table 3. Demographic Profile of respondents

Variable Frequency Percent Cumulative Percent

Gender Female 45 52.3 52.3

Male 41 47.7 100.0

Age >50 6 7.0 7.0

18-24 2 2.3 9.3

25-34 21 24.4 33.7

35-49 57 66.3 100.0

Marital Status Married 58 67.4 67.4

Not married 28 32.6 100.0

Education Bachelor Degree 41 47.7 47.7

Master Degree 26 30.2 77.9

Others 13 15.1 93.0

Secondary School 6 7.0 100.

Experience < 5 years 6 7.0 7.0

> 20 years 20 23.3 30.2

10 - 20 years 46 53.5 83.7

5-10 years 14 16.3 100.0

Job Position Associate 3 3.5 3.5

Director 12 14.0 17.4

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Manager 27 31.4 48.8

Professional 9 10.5 59.3

Self-employed 8 9.3 68.6

Senior Manager 12 14.0 82.6

Specialist/Team Lead 15 17.4 100.0

Business Type Financial Services 13 15.1 15.1

Government, NGO & GLC 8 9.3 24.4

Healthcare 5 5.8 30.2

ICT, Telecommunication & Share Services

15 17.4 47.7

Manufacturing, Trading & Distribution

24 27.9 75.6

Oil & Gas 4 4.7 80.2

Others 17 19.8 100.0

Descriptive and Normality Analysis Table 4 below depicts the data are highly skewed for business process re-engineering, training, implemented modules with skewness greater than 1 and rest of the skewness are mostly showing skewness between -1 and -0.9 where the data are symmetrical. For the kurtosis all the constructs are having a value of +/- 1 which is acceptable.

Table 4. Descriptive Statistics for Each of the Construct

N Minimu

m Maximu

m Mean

Std. Deviati

on Skewness Kurtosis

Statistic Statistic Statistic Statistic

Statistic

Statistic

Std. Erro

r Statist

ic Std.

Error

TM1 86 3.0 5.0 4.616 .5566 -1.105 .260 .255 .514

TM2 86 3.0 5.0 4.663 .4997 -.988 .260 -.353 .514

TM3 86 3.0 5.0 4.628 .5541 -1.164 .260 .402 .514

TM4 86 3.0 5.0 4.640 .5294 -1.072 .260 .094 .514

TM5 86 3.0 5.0 4.605 .5375 -.896 .260 -.297 .514

OC1 86 3.0 5.0 4.547 .5669 -.782 .260 -.392 .514

OC2 86 3.0 5.0 4.593 .6015 -1.198 .260 .443 .514

OC3 86 3.0 5.0 4.616 .5351 -.953 .260 -.179 .514

OC4 86 3.0 5.0 4.593 .5610 -.991 .260 -.001 .514

OC5 86 3.0 5.0 4.570 .5849 -1.000 .260 .036 .514

EP1 86 2.0 5.0 4.500 .7154 -1.283 .260 .959 .514

EP2 86 3.0 5.0 4.581 .6224 -1.216 .260 .423 .514

EP3 86 2.0 5.0 4.535 .7467 -1.771 .260 3.005 .514

EP4 86 3.0 5.0 4.570 .6047 -1.091 .260 .201 .514

EP5 86 3.0 5.0 4.628 .6145 -1.440 .260 1.000 .514

BPR1 86 3.0 5.0 4.581 .6224 -1.216 .260 .423 .514

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BPR2 86 2.0 5.0 4.547 .6626 -1.417 .260 1.821 .514

BPR3 86 2.0 5.0 4.581 .6591 -1.569 .260 2.245 .514

BPR4 86 3.0 5.0 4.605 .5796 -1.164 .260 .399 .514

BPR5 86 3.0 5.0 4.616 .5774 -1.221 .260 .542 .514

UI1 86 3.0 5.0 4.628 .5541 -1.164 .260 .402 .514

UI2 86 3.0 5.0 4.616 .5566 -1.105 .260 .255 .514

UI3 86 3.0 5.0 4.709 .5284 -1.648 .260 1.892 .514

UI4 86 3.0 5.0 4.663 .4997 -.988 .260 -.353 .514

UI5 86 3.0 5.0 4.686 .4914 -1.118 .260 -.033 .514

TT1 86 3.0 5.0 4.674 .5624 -1.542 .260 1.470 .514

TT2 86 3.0 5.0 4.698 .4868 -1.186 .260 .153 .514

TT3 85 3.0 5.0 4.694 .5123 -1.390 .261 .995 .517

TT4 86 3.0 5.0 4.605 .5796 -1.164 .260 .399 .514

TT5 86 3.0 5.0 4.663 .5227 -1.199 .260 .423 .514

PM1 86 3.0 5.0 4.640 .5512 -1.226 .260 .562 .514

PM2 86 3.0 5.0 4.663 .4997 -.988 .260 -.353 .514

PM3 86 3.0 5.0 4.698 .5104 -1.408 .260 1.049 .514

PM4 86 3.0 5.0 4.535 .6077 -.941 .260 -.093 .514

PM5 86 3.0 5.0 4.640 .5294 -1.072 .260 .094 .514

IM1 86 3.0 5.0 4.593 .6208 -1.269 .260 .551 .514

IM2 86 3.0 5.0 4.663 .5227 -1.199 .260 .423 .514

IM3 85 3.0 5.0 4.706 .5306 -1.630 .261 1.826 .517

IM4 86 3.0 5.0 4.651 .5481 -1.289 .260 .737 .514

IM5 86 3.0 5.0 4.698 .4868 -1.186 .260 .153 .514

VS1 86 3.0 5.0 4.640 .5512 -1.226 .260 .562 .514

VS2 86 3.0 5.0 4.674 .5411 -1.424 .260 1.137 .514

VS3 86 3.0 5.0 4.651 .5481 -1.289 .260 .737 .514

VS4 86 3.0 5.0 4.605 .5996 -1.254 .260 .579 .514

VS5 86 3.0 5.0 4.535 .6268 -1.015 .260 .001 .514

IS1 86 3.0 5.0 4.628 .5950 -1.371 .260 .887 .514

IS2 86 3.0 5.0 4.651 .5262 -1.134 .260 .251 .514

IS3 86 3.0 5.0 4.663 .5227 -1.199 .260 .423 .514

IS4 86 3.0 5.0 4.581 .6032 -1.144 .260 .317 .514

IS5 86 3.0 5.0 4.616 .5774 -1.221 .260 .542 .514

OP1 86 3.0 5.0 4.698 .5104 -1.408 .260 1.049 .514

OP2 86 3.0 5.0 4.651 .5262 -1.134 .260 .251 .514

OP3 86 3.0 5.0 4.640 .5722 -1.343 .260 .867 .514

OP4 86 4.0 5.0 4.686 .4668 -.816 .260 -1.366 .514

OP5 86 3.0 5.0 4.674 .5189 -1.266 .260 .612 .514

Top Management

86 3.00 5.00 4.6302 .48168 -1.015 .260 .115 .514


86 3.00 5.00 4.5837 .49488 -.925 .260 .068 .514

External Pressure

86 2.80 5.00 4.5628 .57600 -1.122 .260 .359 .514


86 3.00 5.00 4.5860 .54947 -1.299 .260 .906 .514

User Involvement

86 3.20 5.00 4.6605 .46025 -1.199 .260 .390 .514

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Training 86 3.00 5.00 4.6669 .45449 -1.276 .260 1.000 .514

Project Management

86 3.40 5.00 4.6349 .46748 -.979 .260 -.321 .514

Implemented Modules

86 3.00 5.00 4.6593 .49071 -1.286 .260 .680 .514

Vendor Support

86 3.00 5.00 4.6209 .52605 -1.232 .260 .708 .514

Implementation Success

86 3.00 5.00 4.6279 .50612 -1.128 .260 .260 .514

Organizational Performance 86 3.20 5.00 4.6698 .45994 -1.177 .260 .212 .514

Valid N (list wise)

84

Reliability Analysis In this research study, the most commonly used reliability measure of Cronbach’s Alpha was applied (Hair et al., 2010). The table 5 below showed the “Cronbach’s Alpha coefficients” for all the variables and its individual constructs. From the table, the overall data reliability for internal consistency is excellent (0.95) together with the individual construct reliability achieving mostly excellent and good results. As the overall values are in a more than adequate level, there were no significant changes made to the survey questionnaires. All the variables scored more than 0.9 and above, given the questionnaire good strength of association prepared for reliability and can be replicated by other researchers for future study.

Table 5. Reliability Analysis Measurement

Reliability of Measurement RESEARCH CASES Strength of Association

No of Items

Cronbach’s Alpha

All variables 55 0.989 Excellent

Construct 1: Top Management 5 0.941 Excellent

Construct 2: Organizational Culture 5 0.981 Excellent

Construct 3: External Pressure 5 0.918 Good

Construct 4: Business Process Re-engineering

5 0.93 Excellent

Construct 5: User Involvement 5 0.923 Excellent

Construct 6: Training 5 0.908 Good

Construct 7: Project Management 5 0.915 Good

Construct 8: Implemented Modules 5 0.939 Excellent

Construct 9: Vendor Support 5 0.952 Excellent

Construct 10: Implementation Success 5 0.937 Excellent

Construct 11: Organizational Performance

5 0.93 Excellent

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Analysis of the Assumptions for Multiple Regression

Analysis of the Autocorrelation The Table 6 below model summary shows Durbin-Watson as 1.6 which is closer to 2 indicating no auto-correlation and Durbin-Watson less than 2 indicates it’s a positive autocorrelation.

Table 6: Analysis of Autocorrelation

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of the

Estimate Durbin-Watson

1 .822a .676 .672 .26322 1.684

a. Predictors: (Constant), Implementation Success b. Dependent Variable: Organizational Performance

Analysis of Multicollinearity

In the coefficients table 7 below, the VIF is less than 2 indicating no multicollinearity. The alternative in validating the existence of multicollinearity is via the Tolerance level. According to Byrne (2010), the Tolerance co-efficient should be less than 0.90 for no multicollinearity. In the results below, it is visible that the tolerance is between 0.3 to 0.6 which indicates no multicollinearity.

Table 7: Analysis of Multicollinearity

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Toleranc

e VIF

1 (Constant) 1.211 .263 4.612

.000


.747 .056 .822 13.24

9 .00

0 1.000 1.000

a. Dependent Variable: Organizational Performance

Analysis of Normality of the Dependent Variable

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The dependent variable is the Organizational Performance (OP) and Implementation Success (IS) indicating the distribution disturbance is approximately normal. There is no violation of the normality assumption in which the regression analysis indicates a normal probability plot.

Graph 1: Histogram of Normality of the Dependent Variable

Analysis of Normality of the Residuals From the normal p-p plot below, there is an almost straight line where the points are coming from normal distribution showing there is a strong correlation among its actual result and its model predictions.

Analysis of Homoscedasticity In the present study these independent variables like top management, organizational culture, external pressure, business process re-engineering, training, vendor support, implemented modules, project management and user involvement were positively associated with all the dependent variables. These independent variables were proven to be key importance in ERP implementation success by researchers like (Adam, 2009;

Madapusi, 2012; M. Beheshti et al., 2014;

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Chaushi, Chaushi & Dika, 2016). Though there is a great variation in the size of the scatterplots, the variability of the size of error differs from the independent variable. The dependent variable graph below shows that the normality is met with the standardized residual and equally distributed points (Kline, 2011). The implementation success dependent variable was most affected by key variables such as organizational culture, top management, external pressure, user involvement, vendor support, training and business process re-engineering whereas the organizational performance dependent variable key variables were all of those mentioned for implementation success dependent variable and in addition to that there are also implemented modules, project management and implementation success itself.

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Graph 3: Scatterplot for Homoscedasticity Analysis

Regression Analysis

Regression Model One The R Square value for this study is 0.867 which is close to the substantial range for the endogenous latent variables, which indicates the data is 86.7% closer to the fitted regression line, also known as coefficient of determination. Further to that, the adjusted R Square value is 0.867 which indicates the significant model fitness for this study.

Table 8: Model Summary

Model Summaryb

Model R R Square Adjusted

R Std.

Error of Durbin-Watson

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Square the Estimate

1 .931a .867 .855 .19276 2.124

a. Predictors: (Constant), Vendor Support, Top Management, External Pressure, Training, Business Process Re-engineering, User Involvement, Organizational Culture b. Dependent Variable: Implementation Success

The ANOVA table below shows Sig value as 0.00 which proves the model is extremely significant for this study. The F- Statistic is 72.570 indicating that there is 72.57% of chances to obtain similar result if this study is done elsewhere. Therefore, this indicates a regression model fit as indicated in the table 9 below.

Table 9: Model Significance – Anova

ANOVAa

Model Sum of Squares df Mean

Square F Sig.

1 Regression 18.875 7 2.696 72.570 .000b

Residual 2.898 78 .037

Total 21.773 85

a. Dependent Variable: Implementation Success b. Predictors: (Constant), Vendor Support, Top Management, External Pressure, Training, Business Process Re-engineering, User Involvement, Organizational Culture

Hair, et. al., (2010), the hypotheses makes assumption of the contribution of the constructs to the measurement theory. The covariance matrix can be used in the examination to test the hypotheses. The sig value of each independent variable should be less than 0.05, if so the hypothesis is accepted otherwise the hypothesis is rejected. The other measurement of Standardized Beta Coefficient value assists to measure how significantly the dependent variable is influenced by the independent variables (Hair et al., 2010). Strong correlation or significant impact will be realized when the value goes higher. Given the results indicated in the coefficients table 10 below, the measurement theory hypotheses of Top Management, Organizational Culture, External Pressure, Business Process Re-engineering, User Involvement, Training and Vendor Support are accepted because of an existing type 1 error rate of 0.05 as presented.

Table 10: Hypothesis- Coefficients Table

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Toleran

ce VIF

1 (Constant) -.101 .230 -.437 .664

Top Management .244 .073 .233 3.325 .001 .349 2.866


-.033 .119 -.032 -.274 .785 .126 7.933

External Pressure .362 .077 .412 4.697 .000 .221 4.518


-.145 .101 -.158 -

1.434 .156 .141 7.089

User Involvement .077 .126 .070 .608 .545 .129 7.726

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Training .147 .118 .132 1.248 .216 .153 6.548

Vendor Support .371 .094 .386 3.960 .000 .180 5.567

a. Dependent Variable: Implementation Success

Model Fitness The model fitness informs the good fit index in which the R, R square and the Adjusted R square are assessed. These provide an estimate of the strength of the correlation between the response variable and the model while not providing a formal hypothesis test for the relationship (Hair et al., 2010). The higher the value goes; it increases the coefficient between the observed value and the predicted value. R Square is considered as substantial when it ranges above 0.75, moderate when it is 0.50 and weak for 0.25 values (Henseler & Chin, 2010).

Regression Model Two The R Square value for this study is 0.676 which is close to the substantial range for the endogenous latent variables, which indicates the data is 67.6% closer to the fitted regression line, also known as coefficient of determination. Further to that, the adjusted R Square value is 0.672 which indicates the significant model fitness for this study.

Table 11: Model Summary

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Durbin-Watson

1 .822a .676 .672 .26322 1.684

a. Predictors: (Constant), Implementation Success b. Dependent Variable: Organizational Performance

Model Significance Following the validity and reliability analysis, there is a need to identify the results of the test based on the measurement theory which offers a comparison for the theoretical measurement model against the reality presented by the sample of current research considering the estimates of the parameters and the key fit statistics. The rule of thumb is p value should be less than 0.05 for a statistically significant model (Hair et al., 2010) and the ANOVA table below shows Sig value as 0.00 which proves the model is extremely significant for this study. The F- Statistic is 175.537 indicating that there is 175% of chances to obtain similar result if this study is done elsewhere. Therefore, this indicates a regression model fit as indicated in the table 12 below.

Table 12: Model Significance – Anova

ANOVAa

Model Sum of Squares df Mean

Square F Sig.

1 Regression 12.162 1 12.162 175.537 .000b

Residual 5.820 84 .069

Total 17.981 85

a. Dependent Variable: Organizational Performance b. Predictors: (Constant), Implementation Success

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Hypothesis testing The measurement presumes many theories considering the hypotheses of the research. As cited by Hair et al. (2010), the hypotheses take assumption of the contribution of the constructs to the measurement theory. The covariance matrix can be used in the examination to test the hypotheses. The sig value of each independent variable should be less than 0.05, if so the hypothesis is accepted otherwise the hypothesis is rejected. The other measurement of Standardized Beta Coefficient value assists to measure how significantly the dependent variable is influenced by the independent variables (Hair et al., 2010). Strong correlation or significant impact will be realized when the value goes higher. Given the results indicated in the coefficients table below, the measurement theory hypotheses of Implementation Success are accepted because of an existing type 1 error rate of 0.05 as presented.

Table 13: Hypotheses – Coefficients Table

Model

Unstandardized Coefficients Standardized Coefficients

t Sig. B Std.

Error Beta

1 (Constant) 1.211 .263 4.612 .000


.747 .056 .822 13.249 .000

a. Dependent Variable: Organizational Performance

Discussion

The regression analysis was done to accomplish two goals. First, it was aimed at presenting the hypothesized interrelations existent between the dependent and independent variables of Implementation Success, Organizational Performance, Top Management, Organizational Culture, External Pressure, Training, Business Process Re-engineering, User Involvement and Vendor Support. According to the theory as advanced by (Al-Mashari, 2003) and operationalized by (M. Beheshti et al., 2014) and (Chaushi, Chaushi & Dika, 2016), there is an inter-relationship among these factors. The defence of any of the variables requires the preservation of all the others.

Secondly, the multiple regression analysis has proven that some of the measurement variable advanced by (Madapusi & D’Souza, 2012; Adam, 2009; Al-Sabaawi, 2015; Bradley, 2008; Hakim & Hakim, 2010) and (Madapusi & D’Souza, 2012) and (Yeh & Xu, 2013) under the seven variables are appropriate to measure the key success factors of ERP implementation. The factor loading of the measurement variables of each factor has aided in the identification of significant variables, which include the measurement of the dependent variables, implementation success and organizational performance.

ERP Implementation Success

The coefficient of determination (R2) of the endogenous variables provides high explanatory power. The proposed model provides guidance for the implementers and organizations aimed at enforcing appropriate policy and implementation steps to invest in ERP through adoption of a process oriented and systematic method. In accordance to the model, the Key Success Factors of ERP Implementation is designed to encourage the use of ERP solutions while increasing pervasive use of technology for higher productivity, lower cost and efficiency. For instance, using ERP will positively influence the productivity level of employees giving higher output of quality work. This would result in the reduction of time and decrease the organisations overhead. The overall results indicated a suitable guidance to the top management within an organisational

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setting there is existing statistical evidence that focus on various facets of the people, technology and process dimensions. The research has proved the theory of Key Success Factors of ERP Implementation to a significant extent from a standard range of actions or norm to positive actions with good disciplines observed through the evidence of the hypothesized associations.

Direct Positive Impact on ERP Implementation Success

The hypothesis in table 17 shows some of the key variables which has the most significant positive impact on ERP implementation are top management (significant value 0.001), external pressure (significant value 0.000 and vendor support (significant value 0.000) which are less than 0.05 in the regression analysis. Some of these key success factors were also highlighted from previous researchers (Yeh & Xu, 2013), (M. Beheshti et al., 2014) and (Chaushi, Chaushi & Dika, 2016).

Indirect Impact on ERP Implementation Success

The hypothesis in table 17 also indicated other variables which has an indirect impact on ERP implementation success but are less significant which are organizational culture (significant value 0.785), business process re-engineering (significant value 0.156), user involvement (significant value 0.545) and training (significant value 0.216) exceeding 0.05 which makes them less significant however previous researchers like (Adam, 2009; Madapusi & D’Souza, 2012; FitzGerald & Arnott, 1996) have stated otherwise from their analysis based on the outcome of their study.

The perception of ERP critical success factors may vary in accordance to the research conducted which depends on the outcome of several factors such as the country in which the research was based on, the size of the industry whether they are large corporations, government or small medium enterprise (SMEs) and demographic profile of the respondents.

5. Conclusion

At the core of this research, information seeking to determine the impact of technology, process and people impact on the implementation of ERP by organization was performed conscientiously considering all the key variables surrounding the framework of technology, process and people (TPP). It can be concluded that technology, people and process has significant impact on the ERP implementation success. The TPP in an organization does affect the ERP implementation success since an organisation that is committed to implement ERP could decide to overhaul their existing ICT infrastructure in favour of ERP system. The findings of this research have uncovered that there is a direct positive relationship between top management, business process re-engineering, organizational culture and ERP implementation success. The multiple regression revealed a significant positive correlation of these three variables. In addition, the competition in an industry can affect ERP implementation success by an organization in that industry. For instance, if some multinational organizations in a country are adopting ERP systems, then the other multinational organization may be obliged to keep up with the trend to be at par with other international companies. Internal environment of an organization such as organizational culture, human talent, business processes affects the ERP implementation success by an organization. When leaders at the helm of an organization are dedicated towards talent development, organizational performance and business process improvement, they are likely to support ERP implementation with confidence and ease. This conclusion acknowledged well by previous studies by (Chaushi, Chaushi, & Dika, 2016) and (Buckhout et al., 1999) who

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concluded that ERP implementation success has a positive significant impact on organizational performance.

Secondly, it is positive to conclude that organizational culture has a positive impact on the ERP implementation success. The data analysis disclosed a significant positive correlation between organizational culture and ERP implementation success; therefore it is proper to deduce that organizational culture significantly affects the ERP implementation success.

When the employees have a positive orientation towards ERP system implementation for the good of the organization performance, it is likely to increase the chances of success. Previous research by Al-Sabaawi (2015) and Madapusi & D’Souza, (2012) arrived at similar conclusion helps to reinforce the conception that organizational culture matters in the success of ERP implementation.

Lastly, the discoveries of this research disclosed a significant positive correlation between business process re-engineering and ERP implementation success, concluding that business process management has a positive impact on ERP implementation. Therefore, when the organisation is fully aware of the potential advantages of implementing ERP system, they are positive in supporting the implementation efforts. The advantages must include specifically of how the stakeholders will benefit from the system. For example, the top management would like to know whether ERP system will improve the cost of production, improve the level of productivity, and be more efficient to increase capital gain. The employees would like to know how ERP system will ease their workload by learning new processes. Similar research conducted by (Garg & Chauhan, 2014; Ahmad & Cuenca, 2013; Nour & Mouakket, 2013) arrived at similar conclusions that business process re-engineering has a significant positive impact on ERP implementation success.

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