TIPOS DE RIESGO

Data collection encompasses the sources and collection methods used to obtain primary data and secondary data.

3.4.1. SECONDARY DATA COLLECTION

Secondary data is data that has already been collected (Pellissier, 2007). Collis and Hussey (2003) highlighted that secondary information can be sourced from books, journals, newspaper articles, government publications, theses, conference proceedings, dictionaries, Google scholar, company annual reports, market reports and surveys.

For the purposes of this study, a national and international data search was done through the library of Nelson Mandela University. This includes a search on EBSCO: Master File premier, Business Source premier and Academic Source premier; Sabinet databases;

48 ISAP (National Library of South Africa). Academic journals, textbooks and dissertations will be used as the main reliable sources for secondary data.

3.4.2. PRIMARY DATA COLLECTION

Primary data is gathered at source (Collis & Hussey, 2003). Creswell (2009) mentioned that in selecting a sample, the population should be identified. Decisions then have to be made about sample frame and eventually, the sample (Pellissier, 2007).

Population is any complete group of body that shares some generic set of characteristics (Zikmund et.al., 2010). According to May (2002) the population is the universe to be sampled. Collis and Hussey (2003) expressed that population is described as all people or group of entities that may be part of the research because of a number of similar characteristics. Population is the body of people or collection of item that is under consideration for research purpose (Collis & Hussey, 2003). With regards to the population of this study, all small businesses in the Nelson Mandela Metropole will form part of the population.

A sample frame is the complete list of the population (May, 2002). Collis and Hussey (2003) refer to a sample frame as a list or record of the population from which a sample can be selected. A sample is a fraction of the target population and it must be carefully selected to represent the target population (Cooper & Schindler, 2008). May (2002) defines a sample as a portion of a larger group called a population. In other words a sample is a subset consisting of only a few people or group of entities selected from the population.

Zikmund et.al. (2010) state that a sample is drawn from a list or a record of a population. The sample will be small businesses within the construction sector. Sampling may be achieved through a probability or non-probability sample. It is essential to differentiate between the two. In probability sampling, it is possible to express the mathematical probability of sample characteristics being reproduced in the population (May, 2002). According to Pellissier (2007) probability sampling occurs when the sample has an equal

49 chance of being chosen from the population. Probability sampling techniques are simple random sampling, stratified random sampling, cluster sampling, and systematic sampling (Pellisier, 2007). Simple random sampling used to ensure that each member in the population has an equal probability of being selected as a sample (Zikmund et.al., 2010).

Pellisier (2007) argued that a stratified random sampling is used to divide a population in subgroups according to some common characteristic and then subgroups are randomly selected as a sample. Saunders, Lewis and Thornhill (2000) state that stratified random sampling refers to the process of dividing the population into two or more subgroups based on one or more common characteristics and then randomly selecting the subgroup to make up the sample. Cluster sampling is when the population is divided into subgroups prior to sampling (Saunders et.al., 2000). Cluster sampling requires that groups with similar characteristics are to be identified and randomly selected (Cavana et.al. 2001:226).

Systematic sampling is a process of selecting the sample on a regular interval (Saunders

et.al., 2000). According to May (2002) the researcher selects a random number as a start and then systematically samples every nth person. The sample fraction is used to select members from the sample frame. Systematic sampling has a number of pitfalls, but is sometimes the only procedure practically available (May, 2002).

Non-probability sampling occurs when items for the sample are selected by the researcher and the researcher makes little attempt to obtain a representative sample and the participants will not have an equal opportunity to be included in the sample (Pellissier, 2007; Zikmund et.al., 2010). Non-probability sampling refers to the possibility of members being selected who are not known (Saunders et.al., 2000).

Non-probability sampling may take three forms, namely, convenient sampling, purposive sampling and snowball sampling. Convenient sampling involves selecting members in the sample frame that are easiest to select as a sample (Pellisier, 2007). Convenient sampling is used to find those members of the sample frame that are easy and conveniently available to the researcher (Zikmund et.al., 2010).

50 There are two types of purposive sampling, namely, judgment and quota sampling (Cooper & Schindler, 2003). Judgment sampling is used when the members of the sample frame are selected based in relevant experience which they possess (Collis & Hussey, 2003). According to Cavana et.al. (2000) judgment sampling is used when the sample is restricted to certain members in the sample frame because the researcher can obtain the desired information from them.

Zikmund et.al. (2010) discussed that quota sampling is used to ensure that all members in the sample frame are represented by the chosen sample on related characteristic as identified by the researcher. Quota sampling is often employed in market research (May, 2002). The author further states that this method is often used for street interviewing and while arguably representative if properly selected, often suffers from sample bias in so far as those that more obviously display the desired characteristics (May, 2002).

According to Zikmund et.al. (2010), snowball sampling is used when the initial selection of the members in the sample frame is based on some other type of sampling technique and the number of the sample is extended by using information obtained from the selected members. Snowball sampling is used when participants are selected based on referral made by other participants being interviewed that fall in the same profile (Pellissier, 2007).

For the purposes of this research, the non-probability sampling technique was used, in the form of convenience sampling whereby the researcher will select readily available small businesses in the Nelson Mandela Metropole as participants.

The number of possible participants was unknown, largely due to the lack of availability of recorded information on existing and registered small businesses in the chosen geographic area. Some small businesses are informal and thus not required to be registered, thereby making it difficult for the researcher to obtain accurate statistics.

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