Sampling

There are five steps of sampling (Churchill and Iacobucci’s, 2009). Figure 5.3 illustrates the processes.

125 Figure 5-3 The Five Steps Research Sampling

Source: Churchill and Iacobucci, 2009, p. 282

5.5.1 Target population

The study focuses on United Kingdom residents aged 18 and over. The latest official recorded population in 2016 of the United Kingdom was 65,600,000 (Office for National Statistics, 2017).

5.5.2 Sampling frame

According to Saunders (2011), a list of all cases in the population from which the sample can be drawn is defined as the sampling frame. Based on the study, the defined population is determined as UK adults. In reaching the sampling frame of the study, the Qualtrics panel respondents were used, which a sample of adult United Kingdom residents has been obtained. The adult United Kingdom respondents were randomly invited by the Qualtrics.com whom have registered as a panel in the system. During the process of data collection in 2015, population estimates based on the 2014 census calculate United

Kingdom’s usually resident population at 64, 679, 700 people. Of these 46,828,200 people are aged 18 years or older, according to UK local government elections (Office for National Statistics, 2015).

5.5.3 Sampling method

Generally, there are two major sampling methods: probability and non-probability approaches. Probability sampling refers to the case where each element (person or case etc.) in a population has a known, a non-zero chance of being included in the sample (Churchill and Iacobucci, 2002). Meanwhile, a non-probability sample refers to a sample which relies on personal judgment somewhere in the element selection process and, therefore, prohibits an

Step 2

Identify the Sampling Frame

Step 5

Collect Data from the Sample

Step 1

Define the Target Population Step 3 Select a Sampling Method Step 4 Determine the Sample Size

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estimation of the probability that any population element will be included in the sample (Churchill and Iacobucci, 2002).

In relation to the first approach, Levy and Lemeshow (2008) described there are four main different categories of probability samples. Generally, the classification includes, firstly, the Simple Random Sampling, which is the most well-known procedure. Secondly, the Stratified Sampling, which provides a significant improvement to simple random sampling. Thirdly is known as the Systematic Sampling which recognised as the easiest to apply, followed by the fourth one which is suitable for a large survey, i.e. national surveys, which sampling method is namely a Cluster Sampling.

Meanwhile, the non-probability samples are chosen based on the subjective

judgement and suitable for exploratory studies, for example to test new extended items for a construct in the framework (Kinnear, 1991). The non-probability sampling comprises several numbers of categories. First, the Convenience Sampling focuses on selected identified population. Second, the Consecutive Sampling which single person or groups is used for numbers of research subjects. Third, the Quota Sampling involves certain numbers of individuals being identified to be used to represent the population. The fourth one is

recognised as Judgment or Purposive Sampling, which only identified credible respondent is selected to participate. Fifth, known as Snowball Sampling, which roles like a referral programme when the respondent forward the questionnaire to their friends or relatives.

In relation to this study, Quota Sampling is considered appropriate. It is useful when a specific individuals or groups are identified to be the respondents. This method can produce a sample which is similar to the population and it provides a good control over the sampling procedure as certain attributes of importance to the study are proportionately represented in the sample (Kinnear, 1991).For instance, elements such as the required number of

respondents, and demographics, are predetermined. Quota sampling is often applied in consumer food research. For instance, in a study by Tarkiainen and Sundqvist (2005) that focuses on the consumer intentions to the purchase of organic food in Finland, Hieke et al., (2018) for European consumers' interest in nutrition information, and Scalvedi and Saba (2018) studying organic food consumption.

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The quota sampling method in this study utilises a private research software company of Qualtrics.com to reach the registered panel respondents via online. The selection of

respondents is made by the system on qualified registered panels based on predetermined criteria set by the researcher. In relation to Qualtrics software, Scott, (2012) described the platform is very reliable, especially in the context of various choices of online platform available for data collection in the consumer research. The quota sampling method was utilised as the number of respondents was limited to a maximum of 350 individuals for each functional food product type questionnaire, which should not exceed 700 respondents

altogether. Besides that, potential respondent must fulfil predetermined criteria, i.e. must be a UK resident aged 18 years and above.

5.5.4 Sample size

To produce greater stability, an appropriate sample size should be considered. Gerbing and Anderson (1985) conducted a Monte Carlo study using samples ranging in size from 50 to 300, found that a sample size of between 100-200 respondents is adequate and acceptable. Nevertheless, a sample size of below 100 is not recommended. Bearden et al., (1982) indicated that, a good sample size required for modelling should be at least 200. In another view, Hair et al., (2010) suggested a good sample size for Structural Equation

Modelling (SEM), with minimum of 100 but not over 400 should be utilised. The justification is based upon the fact that a larger sample size (>400) is problematic as slight changes can affect the result and the model becomes more unstable, thus the goodness of fit measures suggests a poor fit (Hair et al., 2010).

For this study, the total sample utilised was 345 for each functional food studied. The collected number of responses in this study is thus appropriate to conduct analysis relating to reliability, validity and statistical power (Preston and Colman, 2000).

5.5.5 The process of data collection of the sample and research ethics

Data collection occurred in June 2015. All respondents were UK consumers aged above 18 years. A paid survey platform (Qualtrics.com) was used to collect the data by distributing the online questionnaires. Despite the cost of data collection being rather expensive, this reliable platform method provided a sample of over 700 hundred responses, divided into two groups of 350 respondents each, according to the two different types of functional foods in this study. Data collection took approximately three weeks to complete.

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At the beginning of the process, every potential respondent has been explained the purpose of the survey. They, also, were informed that participation was voluntary. To increase response rates, each respondent was paid based on the rates set by Qualtrics.com. The condition set to receive the payment was the full completion of the questionnaire. To increase the reliability of the data Qualtrics software employs quality checks. The three main ‘quality checks’ used are validation, attention filters, and survey duration checks. Details on these are further discussed in Section 5.6.1.

Respondents did not provide their name or any personal details as part of completing the survey. The full anonymity of the results is maintained. The research fully complied with Newcastle University’s policy on research ethics, including the ESRC Framework for

Research Ethics (ESRC, 2010) and the Market Research Society’s Code of Conduct Guidelines (2014).