A CONCEPTUAL MODEL OF ADOPTION OF BIDSA BY ERP USER ORGANIZATIONS

Based on assessment of these prior studies, it is clear that the factors affecting the adoption and implementation of BIDSA by ERP user organisations in Australia have not yet been fully investigated (Grover 1998; Hawking, Foster & Stein 2008; 2004; Ramamurthy, Sen & Sinha 2008; Xu & Quaddus 2005). As Tornatzky & Klien (1982) pointed out, studies of

organisational adoption should examine multiple explanations of adoption behaviour to assess the influence of different forces. Specifically, Newell, Swan & Galliers (2000) suggested that diffusion of innovation theory can be used positively to examine information communication technology and complex information technology adoption in business organisations.

97 Mistillis, Agnes & Presbury (2004) provide another example for suggesting use of this theory in order to determine ICT adoption. Thus, a conceptual model for the adoption of BIDSA will incorporate those factors affecting the use of IT in an organisation; a concept derived from the organisational innovation and specific ERP user organization literature.

3.2.1 Pilot Study to Help Build the Conceptual Framework

As there was no previous research on the adoption of BIDSA with the ERP perspective in Australia (see Table 2-4), an exploratory study was employed to supplement the literature review. Therefore, during the month of August 2007 at a conference of the SAP Australian User Group (SAUG) summit 2007, short semi-structured interviews were conducted with representatives from twenty ERP user organisations in Australia. Each interview took

approximately ten to fifteen minutes to complete. Participants were at IT executive level (e.g. CIO, IT executives, IT project managers, IT managers). The short interview questions (see Appendix A1) were designed to determine:

 General information about firm demographics,

 Main reasons for, and problems influencing the adoption of BIDSA by ERP users in

Australia,

 Benefits and cost of the adoption of BIDSA by the ERP sector in Australia, and  Factors expected in Australia that support the use of BIDSA

The results of these interviews (e.g. opinions, recommendations, and experiences) (see Appendix A2) provided direction as to what factors were important for firms in Australia and how these factors were assessed by occupants of these senior management positions.

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3.2.2 Proposed Research Variables

The proposed conceptual model for this study was developed incorporating key variables derived from a review of the research literature on innovation adoption in organisations and from the results of the exploratory in-depth interviews in Australia. In table 3-1, the research variables used in this study are summarised.

Table 3-1: Research variables in the study

In this study, the proposed conceptual model incorporates three key groups of factors: organisational factors, technological innovation factors, and environmental factors based on Tornatzky & Fleischer (1990).

The organisational factors consist of the inherent characteristics of the ERP user firm- top management support, organisation size, absorptive capacity, and internal need. The

technological innovation factors consist of three aspects: 1) perceived benefits; 2) complexity; 3) compatibility. The environmental factors for the organisational environment consist of two

Research Variables Categorised for the Study

Groups of Factors Theoretical Contexts Variables

Organisational Factors Organisational Structure and Process

Top Management Support Organisational Size/ Resources Absorptive Capacity Internal Need Technological Factors Technological Contexts Perceived Benefits

Task Complexity System Compatibility Environmental Factors Organisational

Environment

Selection of Vendors Competitive Pressure Sources: Group of factors (adapted from Tonatzky & Fleischer 1990; Thong 1999; Kamal 2006) : Research variables (adapted from organisational innovation adoption,

decision support and ERP system literature and the results of preliminary study (short interviews))

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The Adoption of BI and Decision Support Applications (BIDSA)

Organisational Factors

• Top management supports

• Organisational Size • Absorptive Capacity • Internal Need Environment Factors • Selection of vendors • Competitive pressure

aspects: 1) competitive pressure; and 2) selection of vendors, which represents organisational environment theory.

This model proposes that there is a direct relationship between these factors and the adoption of BIDSA by business firms. The degree of adoption of BIDSA will be measured in two levels: 1) early adopter; and 2) non-early adopter ERP users. Figure 3-1 below shows a conceptual model of adoption of BIDSA by ERP perspectives.

Figure 3-1: A conceptual model of adoption of BI and decision support

applications (BIDSA) by ERP user organizations

Remark: For an explanation of the abbreviation used in this model (e.g. BI, BIDSA, ERP, DW, ETL, OLAP, DM, DSS, KMS, EIS) (see the glossary section)

Technology Characteristics

• Perceived benefits

• Task Complexity

• System Compatibility

Early Adopters:

ERP organisations that have BI basic infrastructure (DW, ETL, data mart) for data integration, analytic applications (OLAP, DM) for versatile analyses of data, extended

application systems for various decision making, and real-time applications for monitoring problems and making a decision in real-time

Non-Early Adopters:

ERP organisations that have only basic decision support characteristics (DSS, KMS, EIS); organisations that have basic DSS and BI basic infrastructure (DW, ETL, data mart ) for improving data integration; and organisations that have both data warehouse and basic IS providing better data integration and helping making a decision

100 Consequently, the proposed conceptual model provides the foundation for empirical

investigation of the effect of three main categories of determinants consisting of;

technological innovation, organizational, and environmental factors on adoption of BIDSA in Australian firms. Each of these factors below is discussed in the next section.

1. Technological innovation factors: 1) perceived benefit; 2) task complexity; and 3) system compatibility.

2. Organizational factors: 1) top management support; 2) organizational size (resources); 3) absorptive capacity; and 4) internal need.

3. Environmental factors: 1) competitive pressure; and 2) vendor selection