Triangulation does not only enhance validity to data analysis but also adds

Triangulation does not only enhance validity to data

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operators, tax practitioners and business experts) in data collection. Triangulation does not only enhance validity to data analysis but also adds depth and richness to analysis (Snape & Spencer, 2003). The evidence provided by the business experts and tax practitioners helped to clarify meanings, and verified the repeatability of accounts given by the ethnic SME operators (Silverman, 1993). In doing so, triangulation assisted with the trustworthiness of the inquiry (Patton, 2002) and validity of the qualitative research (Denzin, 1970). 5.7 Data analysis Qualitative findings illuminate the people behind the accounts given by providing understanding and interpretation for their actions (Punch, 2005). The knowledge gained from this research and the underlying reasons which underpin this knowledge may subsequently inform policymakers and tax authorities to address any issues that ethnic SME operators may have in regards to tax compliance. The analysis of the transcripts follows a three stage process as suggested by O’Dwyer (2004), which is an adaptation
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83 of the analytical process developed by Miles and Huberman (1984), involving data reduction, data display, and data interpretation and conclusion drawing. The full analytical procedure adopted for this research is shown in Figure 5.1 on the next page. 5.7.1 Data reduction According to Miles and Huberman (1984), data reduction “refers to the process of selecting, focusing, simplifying, abstracting, and transforming raw data” (p. 21). It offers a general overview of the data collected and loosely classifies any emerging themes (O' Dwyer, 2004). It requires the researcher to reflect on the data after some time, to identify any commonalities in the participants’ accounts. Three phases were applied to reduce the data into manageable amounts. First, it involved listening to the tapes and reviewing the field notes to get a general overview of the data. Second, the researcher made a comparison of each participant’s notes, which resulted in 15 loosely classified themes to be refined further at a later stage. While working with the data, the researcher continuously had to make decisions about the coding and themes, and to review some of the codes. Some codes were confirming existing theories while others were not. Third, the researcher had to reflect on the data to identify any commonality or deviant cases, by constantly comparing one account to another to build some themes and patterns. For example, the researcher found that most ethnic operators did not dispute their obligations to pay taxes but they questioned the extent, frequency and types of taxes paid. This was not very evident initially, until the researcher took a more “detached” view of the data. 5.7.2 Data display Data display is “an organised assembly of information that permits conclusion drawing and action taking. It involves assembling the data into displays such as matrices, graphs, networks, and charts, which clarify the main direction (and missing links) of the analysis” (Miles & Huberman, 1984, pp. 21-22).
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84 General overview Recording initial themes Reflection Phase Mind maps Coding Matrices Big Picture Analysis within context Stages Phases
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  • Fall '16
  • tax compliance, SME Operators

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