Convenience sampling Simple random sampling
Quota sampling Stratified random sampling
Purposive sampling Systematic random sampling
47 2.4.3 Determination of the sampling frame
A sampling frame is a representation of the elements of the target population and consists of a list of directions for identifying the target population (Malhotra, 2006: 337; Parasuraman et al, 2007: 333). Examples of a sampling frame may be in the form of a physical or electronic medium. This includes a telephone book, a “Yellow Pages directory” or a “Braby‟s directory”
which list the businesses of the industry or a database from a commercial organisation, a city directory, or a map.
The sampling frame for the current study was supplied by the Eastern Cape Parks and Tourism Agency (ECPTA), the government agency tasked with the oversight of biodiversity, conservation and tourism in the Eastern Cape Province. The ECPTA was formed in July 2009 from the merger of the former Eastern Cape Tourism Board and Eastern Cape Parks Agency. As a tourism authority, it is mandated to manage the database of tourism products in the province. This database contained approximately 2,300 registered tourism businesses, which included tour operators, accommodation establishments, conference centres, travel agencies, and restaurants.
2.4.4 Determination of the sample size
The sample size refers to the number of elements to be included in the study (Malhotra, 2006: 338). It is the absolute size of the sample that is important, regardless of the size of the population. The larger the sample, the more
48 representative it is likely to be (Bryman & Bell, 2011: 188; Veal, 2006: 288). Bryman and Bell (2011: 188) caution that it is important to conduct the survey in such a way as to maximise the number of interviews possible or the number of questionnaires to be sent out, given the amount of time and resources available.
Various approaches are used to determine the sample size. These include using a census for small populations, imitating a sample size of similar studies, using published tables and applying formulas to calculate a sample size (Israel, 1992: 1). However, an important consideration with sample size relates to the number needed for the data analysis. If descriptive statistics are to be used, then almost any sample size will suffice. According to Israel (1992: 4) a good sample size, if inferential statistics are to be used, would range from 200 to 500. This size would be appropriate for multiple regression, analysis of covariance or structural equations which may be performed for more rigorous evaluations. To this end, the sample size should be appropriate for the analysis which is planned. In the current study a sample of 332 SMTEs were used out of a population of approximately 2,300. The number of usable questionnaires amounted to 310. The method of selection of respondent businesses from the database follows in the next section.
49 2.4.5 Execution of the sampling process
The final step of the sampling process concerns the execution of the sampling process. This requires a detailed specification of sampling decisions concerning the population, sampling frame, sampling unit, sampling technique and sample size to be implemented (Malhotra, 2006: 339). McDaniel and Gates (2008: 338) caution that this step requires thorough checking to ensure that all necessary procedures are followed. Systematic random sampling was used whereby every seventh respondent was chosen from the database which consisted of approximately 2,300 respondents in total.
2.5 TYPES OF DATA, DATA COLLECTION METHODS AND
TECHNIQUES
As research provides data to help solve specific problems, researchers should be able to identify the types and sources of data they wish to use. Bless and Higson-Smith (2000: 97) observe that data can be classified according to the manner it was collected. They contend that when researchers collect their own original data for the purpose of a particular study, the data is called primary data. Data collected in this way is most appropriate to the aims of the research, since the data gathering is directed towards answering precisely the questions raised by the researcher. However, and on the contrary, researchers often have to use data collected
50 by other investigators in connection with other research problems, or as part of the gathering of social data. Such data is referred to as secondary data.
The next section briefly explains secondary data, followed by a discussion of primary data.
2.5.1 Secondary data
Secondary data is data that is collected for purposes other than for solving the problem at hand. Collecting secondary data is one of the cheapest and easiest means of accessing information. Hence, firstly, a researcher should solicit all secondary data available on the topic. If the amount of secondary data available is overwhelming, researchers must locate and utilise the data that is most relevant to their research (Kumar, Aaker & Day, 2002: 106-107). Secondary data, according to Kumar et al (2002: 106-107):
may provide enough information to resolve the problem being investigated;
can be a valuable source of new ideas that can be explored later through primary research;
is a prerequisite to collecting primary data;
helps to define the problem and formulate hypotheses concerning its solution;
51 helps to define the population, select the sample in primary information collection and define the parameters of primary research; and
is of use in the collection of primary data.
2.5.2 Primary data and methods of collection
Malhotra (2006: 106) explains that “primary data are originated by a researcher for the specific purpose of addressing the problem at hand”. The
collection of primary data involves all the steps of the marketing research process. Primary data can be expensive to obtain, as well as time consuming (Malhotra, 2006: 106). A variety of methods of data collection can be used to collect primary data.
A survey research method is often the mainstay of marketing research in general and is associated with both descriptive and causal research situations. One of the distinguishing factors of survey research methods is the dominant need to collect raw data from groups of people of approximately two hundred or more (Hair et al, 2000: 253).
The continual advances in communication, telecommunication, and personal computer technologies have created an almost limitless number of survey methods. Hair et al (2000: 253) contend that all survey methods can be classified as person-administered, self-administered, or telephone- administered. Emerging technologies have had a significant effect on what
52 are known as automatic or computer-assisted survey techniques. By far the majority of marketing or information research is conducted through one or more of the various survey methods.
In the current research, primary data were collected using face-to-face interviews, telephone interviews and electronic questionnaires as will be explained in section 2.5.3. Table 2.4 provides a summary of the advantages and disadvantages of the data collection methods used in the current study.
TABLE 2.4