PRIMARY STUDY

The primary study of this research will consist of an empirical investigation among pre- retired black individuals. The next section elaborates on the research paradigm, sampling, and data analysis applicable to the empirical investigation.

1.6.2.1 Research paradigm

Gravetter and Forzano (2012:158) identify two main research paradigms: the positivistic paradigm and the phenomenological paradigm. A positivistic research paradigm refers to social research that adopts a scientific method and meticulously tests hypotheses by means of data in the form of quantitative measurements (Teddlie & Tashakkori 2009:342). The positivistic research paradigm can also be referred to as a quantitative, objectivist, scientific, experimentalist, and traditionalist research paradigm (Collis & Hussey 2003:47). A phenomenological research paradigm means that research is orientated to subjective experiences, perceptions, and events of individuals (Teddlie & Tashakkori 2009:341). The positivistic research paradigm will be implemented, as this study will make use of quantitative techniques to analyse data.

Burns (2000) asserts that the methods of data collection are rigid and strict when making use of the positivistic research paradigm. Collis and Hussey (2003:52) explain that the positivistic approach seeks facts and has little regard for the state of the individual. Logic and reasoning are applied in the positivistic research paradigm to ensure objectivity, precision and thoroughness. The positivistic paradigm not only produces quantitative data, but also uses large samples. However, with the positivistic approach, the validity is low and the reliability is high. (Gravetter & Forzano 2012:158; Collis & Hussey 2003:55).

The hypothesised model and hypothesised relationships will be tested through an empirical investigation as part of this study. The empirical research will be conducted among pre-retired black individuals in the Eastern Cape, South Africa. As the study will use a large sample to gather perceptions by means of a questionnaire, and the data will be analysed statistically, the positivistic research paradigm is the most suitable one to use.

1.6.2.2 Sampling and data collection

According to Saunders, Lewis and Thornhill (1997), sampling techniques are used to allow for the collection of data from a subgroup from which generalisations can be made. A “population” is defined by Wiid and Diggines (2013:186) as the distinct set of

individuals who are under consideration. The population of this study will comprise pre-retired black individuals in the Eastern Cape, South Africa.

For the purposes of this study, a mixed sampling method will be used. Blumberg, Cooper and Schindler (2005:208) describe probability sampling as a procedure that gives every element in the population a known and a non-zero probability of being selected. Beins (2013:126) explains that, in probability sampling, stratified sampling is employed when the researcher intends to identify the proportion of the total sample that has the characteristics the researcher is interested in. Beins (2013:126) adds that a researcher can stratify according to “age, gender, socioeconomic status, education level, political affiliation geographical location, height, weight, etc.” Furthermore, proportionate stratified sampling ensures that a sample is obtained such that the proportions in the sample exactly match the proportions in the overall population (Gravetter & Forzano 2012:149). This study will make use of proportionate stratified sampling, and the following strata will be used:

• Geographical location: As there are nine provinces in South Africa, the study will focus specifically on the Eastern Cape.

• Race: The respondents should be “black individuals of African descent”. • Age: The respondents should fall between the ages of 18 and 65 years. • Retirement status: The respondents should not be retired, or have never

formally retired.

Gravetter and Forzano (2012:143) state that, in non-probability sampling, the researcher cannot list the members of the population. Zikmund (2003b:380) explains that units of a sample are selected on the basis of convenience. “Convenience sampling” refers to sampling that makes use of units or people that are most convenient to collect data from (Daniel 2012:66; Zikmund 2003b:380).

Due to the nature of the research that will be undertaken, proportionate stratified sampling and convenience sampling will be the best way to select respondents to gather data on the perspectives of individuals about retirement planning and the retirement funding adequacy of black pre-retired South Africans residing in the Eastern Cape. Proportionate stratified sampling will be used to ensure that the respondents

meet the strata applicable to the study. Once the respondents are eligible to be potential respondents, the researcher will collect data on the basis of convenience.

Bartlett, Kotrlik and Higgins (2001:48) state that, where the researcher aims to test relationships between variables in a study, the ratio of an observation-to-independent variable ratio should be at least 5:1. If this minimum variable ratio is not met, then there is a risk of causing the results to be too specific to the sample, thus resulting in a lack of generalisability (Hair, Anderson, Tatham & Black 1995:105). However, Bartlett et al. (2001:48) elaborate that a more conservative ratio for an observation-to-independent variable would be 10:1. Nevertheless, an appropriate sample size is dependent on the goals of the researcher (Alasuutari, Bickman & Brannen 2008:167). For the purpose of this study, following the sample size recommendations above, the following was considered: This study has six variables. A minimum of 10 respondents per variable is prescribed by Bartlett et al. (2001:48) for a conservative observation. In addition, a minimum of five statements is advised by Costello and Osborne (2005:5). Therefore, multiplying the six variables by 10 respondents and five statements produces a minimum sample size of 300.

Mitchell and Jolley (2012:310) caution, however, that in a study that makes use of probability sampling, random sampling error can cause the sample to be less representative of the population. To ensure that the sample size used in this study is representative of the population, Mitchell and Jolley (2012:310) prescribe that a study with a population of between 100 000 and 100 000 000 should have 384 respondents if the researcher wants to be 95% confident that the results of the study will be within 5% of the true percentage in the population. Based on the prescriptions of previous research, the size of the sample for the study will not be less than 384 pre-retired black respondents in the Eastern Cape Province.

As discussed, this study will make use of the quantitative method of research, and therefore a measuring instrument in the form of a questionnaire will be constructed and distributed to gather the necessary data from individuals as respondents. The questionnaire will be compiled to identify the relationships among the independent, mediating, and dependent variables (Zikmund 2003b:312). A self-developed and self- administered measuring instrument in the form of a structured questionnaire will be distributed to a sample of a minimum of 384 pre-retired black individuals.

The language of communication will be English, and the questionnaire will consist of three sections. Section A will gather the biographical and demographic data of the respondents, including their gender, age, and employment status. Section B will gather data about the retirement plans of individuals – their planned retirement age, their sources of financial advice, and the length of time they have already spent contributing to their retirement scheme. Section C will be in the form of a five-point Likert-type scale with responses ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5), and consist of statements based on the literature review regarding the factors (Financial literacy, The role of the financial planner, Family support structure, and Health status) possibly influencing the retirement planning of individuals. Section C will also be in the format of a five-point Likert-type scale, with responses ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5), and will gather data on the aspects of retirement planning and the retirement funding adequacy of black individuals.

The data that will be collected will be statistically analysed using the software programs Amos 24, Microsoft Excel 10, Statistica 13, and SPSS 24 for Windows. A comprehensive analysis of the data will also be undertaken to ensure the validity and reliability of the questionnaire.

1.6.2.3 Data analysis

The data collected from the respondents will be subjected to various data analysis procedures. The content validity of the measuring instrument will be ensured, as experts in the field of financial planning and retirement planning will assist and comment on the questionnaire design. In addition, to ensure validity, a pilot study among individuals will be conducted to pre-test the questionnaire. If necessary, based on the pilot study results, changes to the questionnaire will be made to ensure that the respondents interpret the questionnaire items or statements as intended by the researcher. Furthermore, a pro forma ethics clearance form will be completed and submitted to the Nelson Mandela University’s Business and Economic Sciences’ Faculty Research, Technology and Innovation committee.

The data analysis procedures that will be undertaken in this study include descriptive statistics, which can be referred to as the statistics that are used to describe or summarise information about a population or sample (Gravetter & Forzano 2012:396;

Zikmund 2003b:402). Collis and Hussey (2003:198) explain that descriptive statistics can be used to determine patterns that are not apparent in the raw data.

The study will also make use of an exploratory factor analysis (EFA) to ensure the measuring instrument’s construct validity. The EFA will be performed on all of the items in the measuring instrument relating to the variables used in the study (Struwig & Stead 2013:149). This test will be done in order to ensure that the researcher’s understanding of the constructs is consistent with the nature or true meaning of the constructs. Wiid and Diggines (2013:242) explain that the purpose of a factor analysis is to determine the composition of factors and to summarise the information contained in a large number of variables into a smaller number of factors.

To test the reliability and internal consistency of the measurement instrument, Cronbach’s alpha coefficients will be calculated. Cronbach’s alpha coefficient is a reliability test technique that requires only a single administration to provide a distinct estimate of the reliability of a given test. (Mitchell & Jolley 2010:153; Gliem & Gliem 2003:84).

In order to establish the relationships between the different variables under investigation, a Pearson’s product moment correlation will be undertaken. Pearson’s product moment correlation coefficient is a measure of association between different variables, and the correlation coefficient (r) varies over a range from +1 through 0 to - 1. (Mitchell & Jolley 2010:623; Cohen, Manion & Morrison 2007:530).

Multiple regression analyses will be used to predict a dependent variable based on several independent variables (Mitchell & Jolley 2010:626; Cooper & Schindler 2007; Hair, Anderson, Tatham & Black 1998); it allows for the simultaneous investigation of the influence of two or more independent variables on a single dependent variable. Multiple regression analyses will be performed to see whether the independent variables (Financial literacy, The role of the financial planner, Family support structure, and Health status) influence the mediating variable (Aspects of retirement planning) and consequently the dependent variable (Retirement funding adequacy).

Another statistical technique that will be used for this study’s empirical investigation is structural equation modelling (SEM), a multivariate statistical technique that is used

by researchers when constructing and testing statistical models (Bordens & Abbott 2011:495; Hair, Black, Babin, Anderson & Tatham 2006:724). SEM combines aspects of multiple regression and factor analysis to estimate a series of interrelated dependence relationships simultaneously; it is particularly useful when a dependent variable becomes an independent variable in subsequent dependence relationships (Kline 2011:7; Cooper & Schindler 2007:583; Hair et al. 2006:711).

A t-test is used to determine whether two means are significantly different between two groups of respondents (Collis & Hussey 2009:262; Cohen et al. 2007:546). While a t-test is used to compare only two means at a time, analysis of variance (ANOVA) tests are used to simultaneously compare or assess the differences in the means of more than two groups (Springer 2010:319; Zikmund 2003b:529). To conclude the data analysis of this study, t-tests and ANOVA tests will be performed to assess the influence of demographic variables on respondents’ perceptions of the independent, mediating, and dependent variables used in the study. In addition, ANOVA tests will be conducted to assess differences in means between the different groups of pre- retired black individuals. Post-hoc tests will be used to assess statistical significance where differences in means are evident, and Cohen’s d values will be used to assess practical significance.