SAMPLE SELECTION 1. Target population

With respect to research design and statistical analysis, a population is the entire collection of entities one seeks to understand or, more formally, about which one seeks to draw interference. Consequently, defining clearly the population of interest is a fundamental component of research design because the way in which the population is defined dictates the scope of the inferences resulting from the research effort (Salkind 2010:1052). Furthermore according to Kolb (2008:180) the population of a study needs to be clearly defined so no unsuitable individuals are included in the sample frame from which the final respondents will be chosen.

The population or population of interest is according to McDaniel and Gates (2008:328) the complete group of people about whom the researcher needs to gather information that is the first step in the sampling process to be defined. Also McBurney (2001:412) affirms that a population is the entire collection of individuals being considered for the research.

For the purpose of this study the target population was small businesses located in the Nelson Mandela Bay area including the city of Port Elizabeth, Uitenhage and Despatch. However, a proper database of registered small businesses was unattainable. It was, however, possible to start the sampling process by using the

existing databases of registered businesses in this area through the website of the Nelson Mandela Bay Chamber of Commerce.

4.6.2. Sampling Method

As reported by McDaniel and Gates (2008:328) sampling in a research study refers to the process of collecting information from a subset (a sample) of a larger group (population).The researcher makes use of the research results obtained from the sample to characterise the larger group. It is demonstrated that sampling a small population can result in very precise estimates (presidential election). Ideally, the sample from or about which information is obtained is a representative cross section of the total population.

The choice of a sampling method will depend on the objectives of the study, the financial resources available, time limitations, and the nature of the problem under investigation. The major alternative sampling methods can be grouped under two headings: probability sampling method and non-probability sampling methods (Mc Daniel & Gates 2008: 334).

4.6.2.1. Non-probability sampling method

Non-probability methods include judgement, quota and convenience, where each potential subject does not have the same probability of being included (Kolb 2010:

192).

Salkind (2010: 922) reports that non-probability sampling is carried out without the knowledge about whether those chosen in the sample are representative of the total population of interest. In some instances, the researcher does have sufficient information about the population to undertake probability sampling. The researcher might not even know who or how many people or events make up the population.

McDaniel and Gates (2008:345) state the four different types of non-probability samples frequently used: convenience, judgement, quota and snowball sampling.

According to Zikmund (2003:380) convenience method sampling is traditionally used when the researcher wants to rapidly and in a cost-effective way analyse a large number of completed questionnaires as easily as possible. Snowball sampling refers to several processes through which initial respondents are selected using probability

methods (Zikmund 2003:384) and additional respondents are obtained from information provided by the initial respondents (McDaniel & Gates 2008: 347).

McDaniel and Gates (2008: 345) state that a major disadvantage of non-probability samples is the inability to calculate the sampling error for them.

4.6.2.2. Probability sampling method

According to McDaniel and Gates (2008:334) probability samples are chosen in such a way that every element of the population has a known, nonzero likelihood of selection. Simple random sampling is the best known and most widely used probability sampling method.

The methods of probability sampling from which researchers can choose include simple, stratified, systemic and cluster. These vary in the randomness of the resulting sample. They also vary in their complexity and the time and effort it will take to construct a sample. Sometimes researchers may decide to use the services of a commercial provider (Kolb 2008: 183).

4.6.2.3. Internet sampling

Mc Daniel (2008:347) reports that the advantages of internet sampling are compelling:

 Target respondents can complete the survey at their convenience

 Data collection is inexpensive

 The survey can be completed quickly

For the purpose of the study a non-probability method was adopted with the snowball sampling techniques and the researcher also benefitted from the advantages by offering Internet sampling. The sampling process started by creating a mailing list of small businesses from the existing main database of registered businesses in the Nelson Mandela Bay area which was accessible through the website of the ―Nelson Mandela Bay Chamber of Commerce‖

(www.nmbbusinesschamber.co.za). Since the Nelson Mandela Bay Chamber of Commerce regrouped different types of businesses, the mailing list of small businesses was obtained by deducting from the databases all larger firms not

considered as small businesses such as corporate, international companies, multinational, franchising, banks, publics companies etc. At the end of the process the remaining companies were considered as small businesses and their contact emails were recorded in a mailing list which represented our population frame of small businesses in the Nelson Mandela Bay Area. After potential small businesses were identified, mails were sent to their different email addresses with a cover letter explaining the purpose of the study and including an internet link directing them to the online questionnaire. The cover letter was also a means for the researcher to address small businesses owners and/or managers to spread the questionnaire by forwarding the email to other small businesses in their networks.

4.6.3. Sampling size and response rate

According to Aaker et al (2007:408) the size of the sample can be identify by the use of technique statistics or through other ad hoc informal approaches. Ad hoc approaches are applied when a person knows from experience what sample size to adopt. Han and Liu (2009: 105) citing Sekaran acknowledge that sample sizes larger than 30 and smaller than 500 are suitable for most research. In this research the proposed sample size was to attain a minimum of 50 small business respondents to a maximum of 105. For this study 67 respondents were obtained from a population of 244 small businesses from the Nelson Mandela Bay Chamber of Commerce.