MATRIZ DOCUMENTAL

The levels of BI and decision support application (BIDSA) adoption have been described in a number of studies illustrating the transition from the use of personal decision support systems to real-time, interactive access to data, allowing manipulation and analysis of critical

information. For example, Gibson and Arnott (2003) defined the level of BI framework using five levels of capabilities ranking from personal or group decision support, executive

information systems, data warehousing, intelligent systems (e.g. artificial intelligence, neural networks), and knowledge management.

Characteristics of Organisations - Scale - Type/ Structure - Management Characteristics of IT - Benefits - Complexity - Barriers Characteristics of Environment - Competitors - Partners/vendors

The adoption and use of IT and BIDSA in Organisations

Characteristics of Individual - Perception - Knowledge - Education

93 In contrast, McDonald (2004) further attempts to classify the BI adoption in terms of

solutions. The effectiveness of BI solutions is reliant on the underlying data structure. His classification includes:1) BI infrastructure which represents operational systems, transforms, consolidates, and aggregates data in readiness for reporting for decision-making; 2) Business Performance Management (BPM) which refers to the use of data in the previous stage to provide feedback for management on key performance indicators (KPI); 3) Decision Enablement which refers to the automation of decisions using data from a knowledge

repository; and 4) Business Activity Monitoring (BAM) which refers to processes to monitor for changes or trends indicating opportunities or problems, and helping managers to take corrective action.

Foster, Hawking & Stein (2005) and Hawking, Foster & Stein (2008) categorised the degree of BI system adoption of Australian ERP firms into four levels: 1) business information warehouse (refers to data warehouse used); 2) advanced planner and optimiser (refer to SCM used); 3) customer relationship analytics (refer to CRM analytics used); and 4) strategic enterprise management (refer to real-time monitoring applications used).

According to the discussion above, it is implied that the level of BIDSA adoption and implementation can be explained using levels of capabilities rankings from “basic capability of decision support characteristics” to “being able to monitor problems and provide multi- business solutions in real-time. Level 1 is an organisation with basic decision support and infrastructure characteristics of a relational database, but no advanced capabilities. Level 2 represents an organisation with data warehouse for data integration while BI with analytics applications represents level 3. Level 4 refers to an organisation that is able to extend the

94 capabilities of business functions (e.g. SCM, CRM). The last level represents an organization that comes with all level with near real-time monitoring.

In this study, two stages of adoption of BI and decision support based applications by business organisations who are implementing ERP are: 1) an early adopter group; and a non- early adopter group. These have been identified based on the literature utilising the work of Rogers (1995) and also prior studies on decision support applications and BI systems (Foster, Hawking & Stein 2005; Hawking, Foster & Stein 2008; Negash, Solomon 2004).

For the purpose of this study, “early adopters” are defined as ERP user organisations that have data integration level: data warehouse, ETL, data mart etc for data acquisition and storing, analytic applications (e.g. OLAP, data mining) for versatile analyses of data and other extended application systems (e.g. CRM, SCM, BI real-time) for various decision-making. The definition of “non-early adopters” is ERP user firms that have only a basic decision support approach (e.g. DSS, KMS, EIS); the firms that have a basic decision support approach and relational database for helping in making decisions; and the organisations that have BI infrastructure and business analytics for creating strategies for business purpose.

2.11 SUMMARY

In summary, this chapter has described the importance and the success of the use of BIDSA in business organisations in Australia particularly for ERP user organisations. The purpose of this chapter was to describe the theoretical underpinnings of this research study. Studies related to the adoption of technological innovation in an organisation and ERP user

businesses were reviewed. The finding of a comprehensive analysis of all factors affecting the use of BIDSA derived from extensive analysis of secondary data sources, mainly existing

95 adoption and diffusion literature and the literature on the diffusion of ICTs and decision support applications.

In particular, several aspects of the literature have been chosen as the basis for the conceptual model described in the next chapter. There are based on Tornatzky & Fleischer’s (1990) model: 1) technological innovation (Rogers 1995; Thong 1999); 2) organizations (Kamal 2006; Ramamurthy, Sen & Sinha 2008; Thong 1999); and 3) environment (Hwang et al. 2004; Kamal 2006). These perspectives have developed analytical and empirical models which describe and/or predict the adoption decision and extent of diffusion of IT within an organization.

Consistent with the relevant literature, the BIDSA adoption construct is incorporated into the proposed theoretical model, as this construct is increasingly being recognised as playing an important role in the adoption of organisational innovation (Gatignon & Roberston 1989; Kwon 1990; Rogers 1995; Tornatzky & Fleischer 1990). This is presented to fill the gap of BIDSA adoption. In summary, this chapter has described the importance and the success of the use of BIDSA in business organizations in Australia particularly for ERP user

organizations.

The next chapter will present a conceptual model for the adoption of BIDSA by Australian firms along with complement reviews of exploratory study integrated into the proposed model. This is done to establish the factors affecting BIDSA adoption by organizations in Australia with an ERP perspective.

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