Chapter 4 Research Methodology
4.4 Sampling Method and Data Collection Procedures
A Sample is “a subset, or some part, of a larger population” (Zikmund et al., 2012, p. 387) as it is impossible to collect data from the entire population. Therefore a sampling method is employed to estimate the sample size required to represent a study’s population (Ruane, 2005; Sekaran & Bougie, 2010; Zikmund et al., 2012). The following sections examine the process of the sampling method and data collection used in this study in detail.
4.4.1
Sample Derivation
Phuket Province Thailand was selected as the research field. Primary data was collected from resort hotels’ guests who stayed at one of any four star resort hotel located in Phuket. The nationality, length of stay and interaction with the resort, along with standard of service of the resort, were criteria for classifying and selecting participants. All of the resort hotels offered a similar service level and service space (based on the information obtained from the Tourism Authority of Thailand). This study focused on resort hotel guests from the United Kingdom, Australia and United States as they represent
Thailand’s main tourist markets in terms of budget spending and numbers lodging in resort hotels in Thailand (Tourism Authority of Thailand, 2014a). In addition, only customers lodging for at least 5 days, and demonstrating a high interaction with the resort (joining activities and often dining at the resort) were invited to participate in this research as these two criteria were used to qualify long duration and high involvement customers and service provider interaction.
4.4.2
Sample Size
Sample size is the number of subjects chosen to represent a population in a research study (Sekaran & Bougie, 2010). The sample size is one critical factor for precise generalization; therefore, it requires a reliable estimation with a minimal error, as well as closely reflecting important population parameters (Ruane, 2005; Sekaran & Bougie, 2010). Moreover, sample size has an impact on the reliability of factors that emerge from a factor analysis (Hair et al., 2010). While there is no consensus on
an acceptable sample size (Hair et al., 2010; Leisa Reinecke & Pearcy, 2001), several authors agree that the number of participants in the sample should be at least greater than the number of variables analysed (Bryman & Cramer, 2004). Krejcie and Morgan (1970) suggest that a sample size of at least 384 is likely to be sufficient, no matter how large the population is represents.
The main objectives of this study were to develop a measurement model for a resort hotel stay, and to determine the interrelationship among the five marketing constructs. Exploratory Factor Analysis (EFA), the Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were employed to satisfy these objectives. Therefore, the sample size estimation should also consider the requirement of all the employed techniques.
Hinkin (1995) suggests a ratio of items to responses from 1:4 to 1:10 is suitable for EFA and CFA, while at least 200 respondents are required for conducting the SEM (Boomsma, 1983; Kelloway, 1998). However, the SEM method tends to be more sensitive, with almost any difference that is detected making the goodness-of-fit measures indicate a poor fit with a sample size greater than 400 (Tanaka, 1993).
Schumacker and Lomax (2004, p. 108) propose some advice for measurement model analysis namely that, “a researcher could begin model generation by using exploratory factor analysis (EFA)
on a sample of data to find the number and type of latent variables in a plausible model.
Once a plausible model is identified, another sample of data could be used to confirm or test the model, that is, confirmatory factor analysis (CFA).” Kline (2011) also confirms that the sample used for the EFA and the CFA should be separated as the results of the EFA are subject to capitalization on chance variation, so this problem will be compounded when analysing the CFA to specify the model based on the results of the EFA. In addition, the factor structures identified through the EFA may result in having a poor fit to the same data when evaluated using the CFA.
In line with all the aforementioned advice from scholars, at least five occurrences for an item was the minimum sample size required in this study (Hair et al., 2010; Kline, 2011; Pallant, 2010).
Therefore, a sample of at least 480 needed to be obtained as there were 48 items subjected to the EFA and CFA, and the other 26 items were used for SEM. Therefore, at least a sample of 240 was required for the EFA, and another 240 for CFA and SEM.
4.4.3
Sampling Method
There are two main categories of sampling techniques: probability and non-probability. The probability technique is “a sampling technique in which every member of the population has a known, non-zero probability of selection”, while the non-probability technique is “a sampling technique in which units of the sample are selected on the basis of personal judgment or convenience, and the probability of any particular member of the population being chosen is unknown” (Zikmund et al., 2012, p. 394). The probability technique is accepted as a more preferred technique in terms of the generalization of the research findings (Leary, 2004; Yu & Cooper, 1983). However, convenient sampling, which is non-probability sampling, was selected to use for the data collection in this study for several reasons. Firstly, the fundamental requirement of probability sampling is that all samples must have an equal probability of being selected was not feasible in this study as a target population in the hotel industry was unable to be identified (Back, 2005; Zikmund et al., 2012).
Secondly, non-probability sampling is considered as an acceptable sampling technique if the objectives of the research are to: test the theoretical premises, test the hypotheses regarding how variables are related to behaviour, and provide evidence in supporting or rejecting the theory test, regardless of the nature of the sample (Leary, 2004; Reynolds, Simintiras, & Diamantopoulos, 2003; Suhartanto et al., 2013).
Thirdly, for ethical reason, the questionnaires were distributed only to resort hotel guests who consented to participation in the study. In order to minimize the drawbacks of using convenience sampling, data was gathered from several resort hotels in Phuket Province, and a non-response bias test was conducted.
4.4.4
The Data Collection Procedure
Invitation letters to participate in this study were sent to 15 resort hotels in Phuket. The letters described the aim of the study, the study’s significance to the resort hotel industry, the intended use of data, the issues related to confidentiality, and a request for voluntary participation of the
organisation. As a result of this process, 10 resort hotels agreed to participate. Following their consent, the data collection process took place from April 1st to August 20th 2012. After receiving acceptance from the resort hotels, the researcher visited all of the participating resort hotels to discuss the data collection process and explain the details of the questionnaire with the managers. The questionnaires were then sent to all participating resorts hotels for distribution to voluntary participants.
Several scholars suggest that a personal approach is a useful method to improve the response rate, as it enables the researcher to reduce surprise and uncertainty of attracting a respondent, it also creates a more cooperative atmosphere among respondents (Cooper & Shcindler, 2006; Malhotra, 2010). Thus, the resort hotel guests were personally approached and invited to participate in the research by the resort hotel front-desk personnel when they checked in. Only the guests who were willing to participate were given the questionnaires with a personalised cover letter, and asked to fill out the questionnaires and return to the reception on their check-out date. The cover letter illustrated the purpose of the study, the approximate length of time to complete a questionnaire, an assurance about the confidentiality of the response, age eligibility (18 years of older), and the channel to contact the researcher or his supervisors. The guests were encouraged to participate by suggesting that their response to the survey would provide valuable information for resort hotel management to understand their customers’ perceptions of service quality with the intention, in turn, to improve and provide a superior service. A prepaid non-monetary incentive has been found to be an effective way to increase response rates (Willimack, Schuman, Pennell, & Lepkowski, 1995). In this research, Thai style key-rings were given to the participants as an appreciation for completing the questionnaire.