Data analysis

5.5.6.1 Data analysis process

Borrowing some ideas from the data analysis procedure proposed by Zhang and Wildemuth (2009) for qualitative interview analysis, this study took the following steps to data analysis:

Firstly, all audio records of interviews were transcribed into written text.

Secondly, the unit of analysis was defined. This study mainly used individual themes,

namely the six marketing characteristics, as the unit for analysis. In this way, the author was primarily looking for the expressions of an idea.

Thirdly, a categories scheme was developed, namely identifying each respondent’s general opinions toward six marketing characteristic dimensions that were distilled from

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the literature review and analysis of links between Chinese and Western cultural values and SME marketing characteristies, as well as the variables construeting the six marketing characteristies. During this process, constant comparisons of each text were made between data collected from two groups of firm.

Fourthly, all the text was categorised. This study categorised the texts and statements

manually.

Fifthly, categorizing consistency was assessed. The categories of each text or statement

were rechecked and their consistency across the whole corpus reviewed.

Finally, conclusions were drawn from the categorized data.

5.5.6.2 Transcribing

Although it is arguable, some researchers claim that the transcription is a pivotal aspect of qualitative inquiry because this representation can affect how data are conceptualised (i.e. Oliver et al., 2005). Oliver et al. (2005) argue that the transcription process should be incorporated more intimately into qualitative research designs and methodologies. They also suggest that conversation analysts focus on the empirical description and analysis of speech. This current research belongs to such a case. Therefore, in this step, all audio records taken from the in-depth interviews were transcribed into written text naturally, where utterances are transcribed in as much detail as possible (Oliver et a l, 2005), including the voice records of interviewer and interviewees.

5.5.6.3 Data analysis method

Study 1 is a qualitative research with a semi-structured question list aimed at hearing stories through interviews. Easterby-Smith et al. (1995: .105) suggested that there were “two basic ways of analysis of qualitative data. In one, often known as content analysis, the researcher ‘goes by numbers’ and ‘fi-equeney’; in the second, label "grounded theory’, the researcher goes by feel and intuition, aiming to produce common or contradictory themes and patterns from the data which can be used as a basis for interpretation.” The differences between ‘content analysis’ and ‘grounded theory’ are shown in Table 5.4.

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Curran and Blackburn (2001: p 104) put content analysis process in this way: “the result is (such) an analysis often illustrated with quotations from respondents expressing their views

Content analysis Grounded theory

Bitty Holistic

Goes by frequency Goes by feel

Objective Closer to the data, open much longer

Deductive Inductive

Testing hypotheses Testing out themes, developing patterns Source: Easterby-Smith et al. (1991: p. 105)

in their own words, which attempts to let the reader enter the world of the respondents and see it from their point of view. It is valuable in adding to the understanding of a particular variety of small enterprise and offers a strong basis for comparisons with other research on other small businesses, including indigenous kinds.” Content analysis offers a useful tool to allow researchers to obtain an objective and systematic description of the manifest content of communication (Berealon, 1952, cited in Marino et a l, 1989). Easterby-Smith et al. (1995: p. 105) stated that ""content analysis has been used very successfully in the examination of historical artefacts. It involved certain key phrases or words being counted, and the frequencies were then analysed. The selection of these would depend on the hypothesis the researcher wished to prove or disprove.”

Zhang and Wildemuth (2009) suggest that qualitative content analysis uses inductive reasoning, by which themes and categories emerge from the data through the researcher’s careful examination and constant comparison. But qualitative content analysis does not need to exclude deductive reasoning. Patton (2002: p.453) suggests that content analysis refers “any qualitative data reduction and sense-making effort that takes a volume of qualitative material and attempts to identify core consistencies and meanings”. Generating concepts or variables from theory or previous studies is also very useful for qualitative research, especially at the inception of data analysis (Berg, cited in Zhang and Wildemuth 2009). The current study moves between the two ways, namely inductive and deductive content analysis.

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Furthermore, to make the data reveal more meaningful implieations behind them, more analysis methods were used for the study. Contextual analysis was used in this research.

Contextual analysis is suggested to have a nature that helps construct internal relations

between statements and the context in which they are embedded, and was used to guide the identification of the meaning of a particular statement in relation to its context of the surrounding statement and the whole transcript (Zhang and Wildemuth, 2009) compared with content analysis which focuses more on the particular statements themselves.

5.5.6.4 Verifying: validity and reliability

Validity and reliability in qualitative research can be achieved through forms of cross-checking (Rao and Perry, 2007). Yin (2009: p.40) suggests that four tests have been commonly used to establish the quality of any empirical social research and they can be summarised as follows:

• Construct validity: identifying correct operational measures for the concept being studied.

• Internal validity (for explanatory or causal studies only and not for descriptive or exploratory studies): seeking to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships.

• External validity: defining the domain to which a study’s findings can be generalized.

• Reliability: demonstrating that the operations of a study, such as the data collection procedures, can be repeated, with the same results.

Learning from the research by Yin (2009) and Rao and Perry (2007), the current qualitative in-depth interviewing achieved construct validity through two tactics. First, using of multiple sources of evidence (12 participants) that provide multiple measures on the same phenomenon. Second, flexibility of the proposed conceptual framework and models that allows re-evaluation and re-design of the content of the interviews, thus establishing content validity. The reliability of Study 1 was also secured through two tactics. First, all the participants were provided with the same introduction and principal question list in

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order to ensure that every interview had the same concentrations (suggested by Knox and Burkard, 2009), even though the responses and conversations could be different from one ease to another ease during the interviews. Second, through the structured process for administration and interpretation of in-depth interviews that enhances the reliability of the study. Table 5.5 shows tactics for the validity and reliability of this research.