Tools for Analysis

It should be highlighted that IS solutions in this context refers to a complete solution of technology and business process knowledge, gained from the best standard practice prevailing in the airline industry. This standard might not be the best in all cases; however, taking most of the airlines and their practice in the industry over time. Initially, the author was coding the data carefully to generate most the suitable data. The first long round of open coding generated around 66 categories, but some of these categories have subsumed others and some were weakly referenced, so they did not have substantial reason to exist.

The author had another coder for the first stage, in order to increase the reliability of the coding and the outcomes as follows in the table 4.2 below:

Theme Theme

Clear Requirement Competing Challenges

Organisation Change MES Business Process Challenges

122

Technology Leakage High Risk

Low Employment Retention Commitment Multi-vendor Advantage IT Capability

Homogeneous Agent Achieving Strategic Business Faster

Knowledge Transfer Training Needs

Margin for Non-Conformances Integrations

Trust Adoption

Disclosing Information High Interdependency

BPM IT Capability Internal

CEO Support SF in Adoption of MES

Concurrent Challenge Budget Competitive Advantage

Few Vendors Credibility

Vendor Management Training Best Business Process Practice (BBPP) vs. Re-engineering

Champions of Change Best of Breed Vs. Fewer Vendors

Adopt BBPP as is Cons Objective

Leadership as Enabler Executive Support

Need for Change Concurrent Needs

Training with Contract IT Leading Project

Change Business Process Big Bang Vs. Sequential

Politics Project Management

Change Resistance Change Business Process MES

Capability ASP vs Each Other

Uniqueness Slack Resources

Post-Implementation Support Strategic Partners Traits

Concurrent Challenge Time Concurrent Challenge IT and Business Alignment Culture

Sign of Success Adopt BBPP as is

Change Management Governance

Concurrent Challenge Resources Flexibility Factor Influencing Selection of

Strategic Partner

People Change Management

Technology Influence BP Communication Challenges

Table ‎4.2 Open Codes First Cycle

Coding is a salient tool in the grounded theory research process. Initial coding or open coding is characterised by being open to all possibilities of interpretations and exploring any theoretical possibility that could be detected in the data (Charmaz, 2006); in a sense, the grounded theories search for concepts with an open mind. Researchers at the beginning tend to give a simple and descriptive code, while later coding tends to be more substantive and abstract (Strauss, 2008). Furthermore, researchers should be aware not to consider the frequency as the ultimate factor on which judgement is based upon. The emergent core theme should be substantiated based on quality too (Saldana, 1997, 2003). Inductively new themes are to be recognised and coded to compose a so-called codebook. NVivo software is helpful in this open coding phase, as it organises the researcher’s thoughts and helps to build the basis of coding in the comparative analysis. . After building the foundations of the coding scheme, the next task was to group the coded themes into categories and

sub-124 synthesise, and organise enormous amounts of data and to rearrange them in a better representation that can easily be identified and categorised. In this phase, the focus of the strategy is on how the main categories and sub-categories are to be established to give a systematic approach as much as possible. Occasionally there will be one theme that necessitates more attention from the researcher than others; nonetheless, the selection of these themes has to be based on certain logic that supports the selection, otherwise, it would be difficult to draw a conclusion and perform solid conceptualisation if the selection is biased. Evidently, the conceptualisation of the theory and understanding of the context of the phenomenon under study are materialised in this phase.

Selective coding is the final stage of coding where categories and sub-categories from previous coding stages are interrelated to compose the emerging theory or model (Creswell, 2007). Strauss and Corbin (1998) expounded that the process of selective coding deploys a code’s selection method involving those codes that have a high correlation with the main theme and are related to the research question; then these are conceived as being highly related codes. Such codes are characterised by high frequency occurrences and thus form the basis of the core themes.

Participants’ interviews were transcribed and coded using the grounded theory scheme. Transcribed interviews were inter-coded between two researchers to increase the reliability. The amount of data to be analysed were immense, so it was justified to use an electronic package to help in detailing all aspects relating to the phenomenon. NVivo was an enormous help to manage the coding phase.

All the transcribed interviews had to be reorganised to cope with the auto coding feature in NVivo, which was a massive help to the researcher. The first question had to be in a standard form, and all of the following questions had to

be in a heading style so that NVivo could recognise them as questions. The questions had to be the same in the entire transcribed interview. For this, the researcher had reformatted all transcribed files, so that the questions appeared the same. As the interviews were of a dynamic nature, some questions emerged later after the first or second interview or were not answered by some participants (left blank). Though this process consumed an immense amount of time, it saved considerable time regarding the analysis. After that process NVivo was able to give all of the answers to certain questions from all the participants in one window, enabling the coder to focus on a certain question and be able to code it separately.

Manipulating large volumes of data is a gargantuan task. Without the software package it would have been a difficult task; however, the author’s competency at using this software provided a competitive advantage in the analysis stage.

The capabilities of NVivo facilitated and helped in managing the tedious manipulation of themes during the comparative phase. The figure 4.1 below illustrates the first categories that sustain the exhausted continuous comparative analysis and the proposed open categories that were created after rigorous iterations of constant comparative process.

126 By and large, avoiding failure in such a complex context would require certain aspects to be studied and investigated in-depth. The ultimate target for such adoption is to capitalise on MES and to improve business processes; therefore, the author would like to explore factors involved in facilitating such a change in business processes. Here are some related factors that help the integration of simultaneous multi-collaboration of ASPs with each other and the organisation to absorb such a change in business processes:

Figure 4.1 Open Coding Categories