THE PRELIMINARY STUDY FOR ANALYSIS OF DECISION SUPPORT APPLICATIONS

An analysis of decision support applications was undertaken as the first stage of this study to have a better understanding of the decision support components relating to the use of BIDSA in Australia. However, it was expected that preliminary information gathering (by interviews) could help in designing a full survey questionnaire and perhaps assist to develop the

theoretical framework. Short semi-structured interviews were selected and this preliminary study provided a useful data (Sekaran 2003). This method is useful in that the interviewer can adapt the questions as necessary, clarify doubts, and ensured that the responses are

appropriately understood by repeating the question, and could establish relationships and motivate respondents. Moreover, rich data could be obtained. Key variables from the

literature review were elaborately combined with information from interviewing with the aim of developing an effective questionnaire used in this survey.

Therefore, in order to perform the initial exploratory study, during the month of August 2007 in the conference of the SAP Australian User Group (SAUG) summit 2007, short semi- structured interviews were conducted by approaching twenty ERP (SAP) managers. Each interview took approximately ten to fifteen minutes to complete. The researcher had two instruments and a list of pre-determined open-ended questions but could ask other relevant questions. This section has four parts: 1) instruments for the analysis of decision support technologies; 2) sampling of organisations using decision support technologies; 3) data collection; and 4) data analysis.

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4.5.1 Instruments for Analysis of Decision Support Applications

For this study, the researcher worked on the sample decision support technology instruments and determined open-ended questions based on the literature review to evaluate the features of decision support applications and decision maker’s procedure needs by using short semi- structured interviews in Australia.

 The first instrument is lists of decision support technologies used for this study. This was based upon the works of Gibson & Arnott (2003), McDonald (2004), Foster, Hawking & Stein (2005), and Hawking, Foster & Stein (2008). The modified decision support technology samplings grouped fourteen attributes into 5 main categories: 1) Basic BIDSA; 2) BIDSA infrastructure; 3) BIDSA analytic applications; 4) BIDSA extended business applications; and 5) BIDSA real-time applications. The first instrument is provided in Appendix (A4).

 The second instrument is lists of factors aimed to investigate the extent to which ERP users are concerned with factors affecting the adoption of BIDSA. Fifty eight

attributes relating to factors affecting BIDSA adoption are based on (e.g. Rogers (1983, 1995), Tornatzky & Fleischer (1990), Premkumar & Ramamurthy (1995), Grover (1993), Chau & Tam (1997), Damanpour (1991), Thong (1999), and Hwang et al. (2004)) categorised into four contexts: 1) decision maker characteristics; 2) system (technology) characteristics; 3) organisational characteristics; and 4) environmental characteristics were used to be as a checklist option and guidelines while doing an interview. The second instrument of potential factors is provided in Appendix (A5).

 Predetermined open-ended questions aimed to investigate the environment (e.g. idea, reason, experience) relating to technology, user, and organisation associated with the

126 use of BIDSA from IT executives. These will be used to identify why the participants answered each question as they did.

4.5.2 Sampling

For standardisation, the criteria applied for the selection of the population and the sample is presented below.

4.5.2.1 Population size

The population for this study was chosen by applying these criteria.

 Criterion 1: ERP users for this research had already adopted BIDSA.

 Criterion 2: Identified using the definition of ERP users which can be defined as

members of SAP user groups. Most of them in this stage are from the SAP Australian Group (SAUG) in Australia.

ERP falls into the category of packaged software applications with the added feature of integration and these applications are available from vendors (e.g. SAP, Oracle), which are recognised currently as the top ERP vendors (Reilly 2005). As a member of this group, SAP is a suitably high-dynamic system that can integrate decision support applications (e.g. SAP R/3) for enterprises. The SAP users have the market leading ERP system and in order to increase understanding of how BI systems may affect the adoption of business organisations. This group is appropriate to investigate because ERP adoption and implementation continues to grow globally (Markus, Tanis & Fenema 2000). It was shown that SAP has approximately 56 % of the ERP market worldwide and 75 % of the Australian market (Foster, Hawking & Stein 2005). The lists of the SAP Australian user group were chosen because they included a

127 large number of ERP user members that were among the largest organisations for providing a list of ERP user sectors in Australia.

4.5.2.2 Sample Selection

The procedure of selecting ERP managers to be face-to-face interviewed was based on simple convenience sampling as follows. For convenience, twenty SAP managers were selected from different industries (e.g. manufacturing, servicing, and public sectors) from over hundreds of attendants of the SAP Australian Group Summit 2007 in Sydney. In this case, there was no bias limitation because all SAP attendants were from different parts of Australia and from various industries, and the respondents were informed that the information they provided would be kept strictly confidential.

4.5.3 Data Collection

Each ERP user participant, based on simple convenience sampling, was assessed by two instruments as mentioned above for the presence or otherwise of the aforementioned

seventeen attributes of decision support features and twenty nine attributes of potential factors affecting the adoption of BIDSA provided by ERP users. The researcher coded “X” with specific features in the sheet that participants answered. Insight details relating to the BIDSA environment provided by ERP managers were investigated and categorised.

4.5.4 Data Analysis

Data analyses were conducted and described by putting them into a specific table (see Appendix A2). Results of the exploratory study were described and are showed in the tables

128 in Appendix A2, Table A2-1 and Table A2-2. Descriptive statistics test was used with

appropriate consideration relating to the nature of the data (Pallant 2005). Descriptive

statistics including frequency and percentages were used to quantify the presence or otherwise of the attributes as mentioned by the two instruments and open-ended question option.