TECHNIQUES AND PROCEDURES

3.10.1 Data collection method

The method of data collection can either be a communication study or by monitoring (Cooper & Schindler, 2006:139). Communication studies use personal and impersonal means to question and obtain information from the subjects of the study (Cooper &

Schindler, 2006:140). This may occur through “… (1) interviews or telephone conversations, (2) self-administered or self-reported instruments … or (3) instruments presented before and/or after a treatment or stimulus condition in an experiment” (Cooper

& Schindler, 2006:140-141). This study used a focus group, personal interviews and a survey to collect data from South African emigrants in Australia and New Zealand. The review of literature and theory that was discussed in Chapter 2, guided the formulation of a list of specific questions to be used as the research instrument in the qualitative part of the study. The interviews and focus group were recorded by means of a voice recorder. All participants were informed that the interviews and focus group would be recorded and gave consent for the recordings. The recordings were transcribed by an external source. The researcher read through the transcriptions while listening to the recordings to ensure accuracy and trustworthiness of the data. The information gathered from the qualitative study was then used to formulate a questionnaire which served as the research instrument in the quantitative part of the study. The questionnaire was formulated in collaboration with

the study leader. The questionnaire was informally pre-tested by means of convenience sampling. The pre-test was administered to participants that are known to the researcher and took part in the qualitative phase of the study. The final quantitative collection instrument was formulated and administered with an online questionnaire. A professional at the University of South Africa created the format and uploaded the questionnaire to the internet. A message about the questionnaire and a link to the questionnaire was posted on the 17 private Facebook pages' walls that were formed for South Africans that live in either Australia or New Zealand, for the entire population on those pages (termed by Facebook as "members") to view. The detail of the self-administered questionnaire, such as the items, scales and tests for internal consistency are discussed in detail in Chapter 6, tables 6.1 to 6.8.

For first part of the study, qualitative research methodology was deemed appropriate for this part of the study was exploratory and descriptive. The purpose was to explore and describe the reasons why South Africans emigrate to Australia and New Zealand. For the second part of the study the quantitative methodology was deemed appropriate because a wider audience (complying with inclusion criteria) could be reached and included in the study, due to the social organisation of the South African emigrants in Australia and New Zealand and the social media platforms that they use to communicate. This enabled the researcher to determine whether the reasons remained the same over a five-year period for South African emigrants in general (causal, quantitative).

3.10.2 Errors in data collection

3.10.2.1 Focus group and interviews

The specific forms of data collection errors that are believed to be the most likely to have influenced the results of the study in the first phase of the focus group and interviews, follow.

 Response-based error

Respondents may have failed to answer questions correctly or in full, which would have caused response errors.

 Intentional distortion of data

A deliberate distortion occurs when data are misrepresented to suite a specific purpose (Saunders, et al., 2012:329). The intention of such a study may be to reach a predetermined conclusion (Smith in Saunders, et al., 2012:3). An effort to void this error was made by involving an external source to transcribe the focus group and interviews. Once the transcriptions were received, the researcher listened to the recordings while reading the transcriptions. Errors were corrected which is known as data cleaning (Saunders, et al., 2012:550). The data were used to formulate the questionnaire in the second phase of the study and the results allowed for triangulation, which validated the data and results.

 Participant error by embellishment

If a participant did not fully remember the experience of emigration or was not able to fully convey the memory of the experience, the participant may have included creative additions to his/her memory to fully participate in the research. This would have negatively influenced the results, as it would not be a true representation of the interviewees’ and focus group members’ descriptions of the reasons why South Africans emigrate to Australia and New Zealand.

 Participant error by misrepresentation of information

A participant may cause error by, consciously or unconsciously, misinterpreting his/her actual behaviour, attitudes, motivations or intensions; this results in response bias. A participant may create response bias when he/she wants to be socially acceptable or boost a reputation with the interviewer (Cooper & Schindler, 2006:252). This will be a definite challenge in this study, as it will measure the participant’s own personality. The participant may want to create a better image of his/her personality with the interviewer.

 Interview error by inappropriate influencing behaviour

The interviewer of this study can interfere with the results of the study, either intentionally or unintentionally, by making inappropriate suggestions or directions to the respondents of the questionnaire that may influence the answers respondents give. Verbal probes, such as word emphasis and rephrasing questions or the tone of voice that the interviewer uses while asking questions from the questionnaire may influence responses. Non-verbal probes (by

body language or facial reactions to answers) can either encourage or discourage participants to give true and accurate answers (Cooper & Schindler, 2006:249).

3.10.3 Data analysis

The data of the first phase were analysed with content analysis, by means of thematic analysis. The qualitative data were analysed with an inductive approach where codes were identified and derived from the data. An inductive approach allows conceptual categories and descriptive themes to emerge from the data, whereas a deductive approach enforces a specific theory in order to test hypothesis (Suter, 2012:346; Greener, 2008:16). The codes were further defined and grouped into themes. Data were then analysed within these themes. King (as cited in Saunders, et al, 2012:572-574) describes this type of data analysis as template analysis. The findings of the analysed qualitative data are presented as evidence throughout the following chapters to validate selected factors.

The data contained in the questionnaires of the second phase were coded in consultation with the study leader and statistician and imported into Statistical Program for the Social Statistics (SPSS) version 17.0, cleaned and new variables were computed for computer analysis. A descriptive analysis was conducted, and trends and distributions were detected.

Appropriate statistical tests were identified, and the data was analysed to answer the research questions.

3.10.4 Establishing trustworthiness

There are various verification procedures that can be followed to increase the trustworthiness of a study, including validity strategies, reliability procedures and triangulation (Creswell, 2009:190). Similarly, a study’s trustworthiness can be increased by overcoming quality criteria such as credibility and transferability, (Sinkovics, Penz & Ghauri, 2008:691). Validity means that the accuracy of the finding are checked through certain procedures (Creswell, 2009:190). Reliability means that the approach to the research is consistent across different researchers or projects (Creswell, 2009:190). Validity and reliability do not mean the same for qualitative and quantitative research. Each of the concepts will now be discussed separately for qualitative and quantitative research.

Qualitative validity can be separated into internal (credibility) and external (transferability) validity. Credibility refers to the correctness of the data (Quilan, Babin, Carr, Griffen &

Zikmund, 2015). It was addressed by triangulating the data collection, as well as, results between the data sources (interviews and focus group) to justify themes that were formed.

Moreover, participants’ responses during the interviews and focus group were consistently repeated back to them to ensure that the interpretation of the information was accurate and well understood. The interviews were audio recorded and the transcriptions outsourced to a professional transcriber. Transcriptions were read through while listening to the audio recordings to ensure that there were no obvious mistakes. Codes that were developed during the process of coding were cross-checked by the study leader to ensure the level of consistency. Furthermore, direct verbatim quotes from the participants support the discussion of the data analysis. Transferability refers to the degree to which findings may be generalised (Saunders, et al., 2012:194; Yin, 2014:48). The research methods and data collection were fully described to allow the transferability to other research studies.

Qualitative reliability entails making it possible for other researchers to conduct the same research in other fields (in this case, countries). Also, the qualitative data collection instrument is included in appendix D. Furthermore, as mentioned, the audio recordings and transcriptions are kept for auditing purposes.

The type of validity in the study can be classified as predictive criterion-related validity.

Criterion-related validity refers to the use of one measure to predict either an influence on another or the future of that occurrence (Churchill in University of Pretoria, 2007:103). There are two types of criterion validity, (1) concurrent validity and (2) predictive validity.

Concurrent validity simultaneously collects data from respondents “… on the new scale to be validated (i.e., the predictor) and on the predictor to be predicted” (University of Pretoria, 2007:104). This means that the researcher should collect the data from a sample of respondents by asking them all relevant questions in the same questionnaire at the same point in time. With predictive validity, data for the predictor is collected “before the data for the criterion is collected” (University of Pretoria, 2007:105). The researcher first gathered data for the new scale to be validated (i.e., the predictor) by gathering data from participants in the qualitative phase in 2009. Based on the outcome of the data, respondents answered a questionnaire in 2015. The quantitative data collection instrument is included in appendix F. This data were then compared to the initial data and the researcher tried to draw

correlations between the results. Data was not gathered on the same questionnaire for the predictor and the criterion at the same point in time and can subsequently not be a concurrent criterion-related validity. It can therefore be concluded that the type of validity used in the study is a predictive criterion-related validity.

The form of quantitative reliability assessed in the study is internal consistency achieved through split-half, KR20 or Cronbach’s Alpha. This form of reliability occurs when a test produces the same results when the test is conducted more than once (Van Zyl, 2014:115;

Babbie, 2016:146; Yin, 2014:148). The formula that was used for all multiple item rating scales in this study are Cronbach’s coefficient alpha, with the decision rule (i.e., cut-off value) of 0,70 or greater to be reliable. This represents a 70 percent true score variance, whereas 30 percent represents error variance.