DISTRIBUCIÓN GEOGRÁFICA DEL PROGRAMA DE BAJA EXIGENCIA

Yin (2009) applied the concepts of construct validity, external and internal validity and reliability as criteria of accuracy of analysis in qualitative research. Lincoln and Guba (1985) denoted that the concepts of validity and reliability should not be applied to qualitative research, but credibility and transferability, dependability and confirmability

instead, which denotes the same concepts but emphasises the qualitative nature of the data. Construct validity evaluates consistency within the research process. This was achieved in this research through the complimentary lenses (see Figure 4.1). External validity evaluates how to apply the findings of the research to other cases. Farquhar (2012) calls it ‘generalizability’ and that it is not possible to show statistical evidence for it in case studies. The results seek to show patterns in CI, which firms with similar characteristics can benefit from. Internal validity evaluates evidence of relatedness between constructs. Reliability verifies that the findings can be replicated (Yin 2009).

The analysis process is shown and explained (see Chapter 5), and the data sources can be seen from Appendices I, II and X. Data gain reliability when generated with

precaution and the same meaning for everybody using them (Krippendorff 2013). Both validity and reliability are achieved by employing different instruments to generate the data with precaution to interview settings, wording, and the choice of interviewees.

Krippendorff (2013) recognised that case studies tend to rely on small samples of data and that it is common to apply content analysis methods, even though its full

methodological potential is not exploited, which is the case in this PhD study. He criticised a lack of theoretical background but this is carefully considered in this study.

Analytical constructs are used as basis for interpretation of data, which is seen by Krippendorff (2013) as a form of logical inference:

“An analytical construct accounts for what the content analyst knows, suspects, or assumes about the context of the text, and it operationalizes that presumption procedurally in order to produce inferences from that text.”

Farquhar (2012) noted that case studies should show relatedness between concepts (internal validity). In this PhD study the Integrative Framework of CI Activities represents an example of a solid analytical construct that enabled evidence data to be analysed in a valid way and to be interpreted for the first lens of analysis of the semi-structured interview data.

Teddlie and Tashakkori (2009) and Denscombe (2007) identified three characteristics of a mixed method approach, noting the value of triangulation of data:

“Use of qualitative and quantitative approaches within a single research project; explicit focus on the link between approaches (triangulation); emphasis on practical approaches to research problems (pragmatism).”

In a qualitative study some parts of research are emergent (Onwuegbuzie and Combs 2011). Emerging themes increase understanding (Onwuegbuzie, Dickinson, Leech and

Zoran 2009). In early stages of content analysis, emergent themes were collated and reduced though NVIVO categorisation. The data analysis strategy at the later stage was to analyse data by describing the interrelationship between individual and cross-case themes (Creswell 2007). This lends rigour to research (Sekaran 2002; Teddlie and Tashakkori 2009).

A deductive approach was taken towards the scenario analysis evaluating how firms adapted to change and in relation to the most probable scenario. Elo and Kyngäs (2007) claimed the selective use of data in the scenario approach as deductive, as those data that are selected for analysis, are only data that can correspond to the analysis scheme (Patton 2002). Table 4.9 gives an overview of the overall data analysis approach, and this identifies how the study switches between an inductive and a deductive approach (which is consistent with a pragmatist research philosophy).

Table 4.9: Data Analysis Approach

Analysis approach Analysis steps

Inductive:

Nature of CI activities

•! Thematic coding of semi-structured interviews transcripts and checklist data using established content analysis principles

•! Gathering objective documents in form of firm report to crosscheck the presence of themes with CI actions taken With actual Inductive:

Understanding of organisational support and structure for CI

•! Evidence for operational and strategic roles of analyst in interview data and in self-assessment

•! Noting of organisational characteristics shaping the CI process in interview data

Deductive:

Assessing CI process effectiveness

Identifying outcomes of predictive analysis

•! Identifying level of effectiveness and sophistication in CI activities based on ratings (self-reported) and on comparison with key criteria in past studies – logical inference

•! Establishing factual information on nature of CI Analyses in use and considering level of static/predictive scope of such analysis

•! Quantitative time series and scenario planning methods adopted leading to specific outcomes. Considering performance of one firm in light of outcomes

4.10! Summary of Chapter

In this chapter, the methodology has been set out. The research aims and objectives are outlined initially, followed by a justification of the research philosophy. Both an interpretivist approach using qualitative data analysis (Chen and Hirschheim 2006) and

a postpositivist approach using quantitative data analysis (Cresswell 2007) are drawn upon, thus leading to a pragmatist philosophy and a mixed methods approach in data collection (Tashakkori and Teddlie 1998). A case study method is outlined as the main research strategy and the data collection process involving semi-structured interviews, with additional checklist data from the Swiss telecom analysts used to support this. In addition, the approach taken to the market context analysis using scenario analysis is identified. The data analysis (Onwuegbuzie, Dickinson, Leech and Zoran 2009) will involve a content analysis of interview and other data.

The next two chapters (Chapters 5 and 6) report on the research findings.

Chapter 5: Research Findings from Case Analysis of CI