Reliability and Validity

The goal of scientific research is usually the quest for objective knowledge, which implies that it is free from bias and prejudice. It is also claimed that objectivity is made up of two characteristics: validity and reliability (Minichiello, Aroni & Hays 2008). Reliability refers to the degree measurement procedures yield the same result when repeated. Validity refers to whether the procedures give the correct answer or are interpreted correctly. In any event establishing validity and reliability of the research is about believability or credibility of the research (Bazeley 2013; Minichiello, Aroni & Hays 2008; Pouliot 2007; Zhang 2009).

Qualitative and quantitative researchers have different notions of validity and reliability, and different procedures in their determination.

Reliability

Quantitative researchers’ primary measure of reliability is for the results to be able to be repeated or replicated across time and place. However, qualitative researchers believe phenomena are ever changing, and therefore unique to time and place. Therefore, different researchers are likely to yield different results because of the differing dynamics involved at each subsequent encounter. Consequently qualitative researchers do not ascribe to the idea that replication is relevant; instead they rely on the idea of consistency as being the equivalent of the positivists’ reliability (Neuman 2003). Therefore, it is important for consistency to be evident across the various data sources.

Consistency may be categorised as internal consistency or external consistency (Neuman 2003). Internal consistency concerns the credibility research informant and their account of the phenomena. Consistency should be evident over time to mitigate fraud, deception, and misrepresentations. External consistency refers to corroboration of data from other sources, such as crosschecking of the data collected with observations, documentations, public record, and corroboration, as described earlier, is a form of establishing external consistency.

While reliability is about credibility, validity is about authenticity (Neuman 2003).

Validity

Validity refers to the authenticity of the data, in that it represents what it is purported to represent and the researcher is truthful in their representations of the data (Patton 2002).

Again, corroboration can help establish validity by comparing the data collected from other sources and corroborating that the data is a fair representation of the phenomena. It can also involve research participant validation, by providing transcripts of the interviews to the participants, so that they may affirm that what is recorded is what they meant to convey (Bazeley 2013).

Validity of data analysis for qualitative research may be established through:

• Plausibility - through thick description by the researcher and persuasive representation of the data presented (Rubin & Rubin 2005)

• Weight of evidence contained within the data. Claims should be evident through numerous sources (informants). A researcher should not make claims on a single source (Neuman 2003).

• Transparency - involves fully describing methodological approaches and basis of analysis, so that others have a clear understanding of the research methodology (Bazeley 2013).

• Consistency and accuracy of interpretation by calling things by their right names, checking meaning of language usage, and meaning intent (Minichiello, Aroni &

Hays 2008).

• Peer consensus validation - checking interpretations and analysis with peers to test for gaps and biases (Bazeley 2013). In particular, interpretations of meanings and emergent patterns were validated with the case subjects in follow-up interviews, and a presentation of the research findings at the completion of the research analysis and theory building. This latter validation was conducted individually with three of the four case subjects (including the Thai case subject) with the fourth case subject unable to make it to their scheduled meeting. In each instance no errors or omissions were noted and the case subjects were supportive of the findings according to their knowledge and experience.

As described at various pints throughout this Methodology Chapter, the design and practices employed, such as corroboration and member checking together with detailed description of the analysis in the following chapter, reliability and validity of this research has been established through practical qualitative-interpretivist techniques.

4.4.11 Summary

In this chapter a detailed description of the research design was provided. The chapter included an overview of methodological options for this research, and provided justification for the choices of social constructivist epistemological orientation and qualitative methodology. Descriptions and justification of data collection methods, incorporating the corroboration of general participants, case subject participants and secondary data sources were also provided. This chapter also included an overview of ethical, reliability and validity issues.

In this chapter a detailed description of the research design was provided. The chapter included an overview of methodological options for this research, and provided justification for the choices of social constructivist epistemological orientation and qualitative methodology. Descriptions and justification of data collection methods, incorporating the corroboration of general participants, case subject participants and secondary data sources were also provided. This chapter also included an overview of ethical, reliability and validity issues.

This concludes Part 1 of this thesis. Part 2 of this thesis encompasses the analysis chapters 5 & 6, which are followed by theory building in 7. The conclusion to the Thesis is encompassed in Chapter 8. Two principal themes emerged from the analysis of the data for this research; namely the Driver Domain for cross-cultural PM, and the Constraint Domain for cross-cultural PM. Chapter 5 provides an account of the inductive analysis approach applied in this research, together with the analytical outcomes with respect to the Constraint Domain.