I am trying to find if there is a link between perceived service quality (mainly urban services) and tourist satisfaction. I will be asking tourists through a questionnaire (five point likert scale, strong disagree to strong agree) some questions to capture their satisfaction with various urban services and their overall satisfaction with the visit.
The literature I read uses mainly three methods: i) Chi square test for independence ii) Log-linear regression iii) Fisher exact test (for small sample size). Chi-square test might indicate if there is correlation between dependent variable (tourist satisfaction) and independent variable (perceived urban service quality). Log-linear shows how much variability in dependent variable is due to independent variable.
All methods are related and used to find correlation/association/dependence. However, I cannot find a clear way to calculate sample size. Many articles seem to use a sample size anywhere between 100 and 500 without specifying how they arrived at that number or why they chose that number. I can do that same, but how would I justify that number?
I am looking for a formula to figure out how many questionnaires I should target. The annual tourist population is around 300K. I will be doing survey for about 2-3weeks. All variables are categorical.
To conduct exploratory factor analysis needed for your validity a basic formula is number of factors x 5 rating scale x 5 items per factor.
Example : The total sample must be at least 300 (12 factors x 5 rating scale x 5 items per factor) respondents to conduct an exploratory factor analysis.
Hope it helps
Danie
For your literature review, you may be interested in the attached qualitative study, which I co-authored.
Article Service Quality and Customer Satisfaction: Qualitative Resea...
Dear Sourabh,
Many criteria are used to ascertain sample size such as types of scales used in measurement, availability of population size, use of pilot study results, or the possible scope of errors, and also the use of various analytical techniques. The sample size can be based on;
1) Sample size table
Even tables are developed that help in easily finding out the sample size. Krejcie & Morgan (1970) have developed a table that helps the researcher determine (with 95 percent certainty) the sample size, and as per his table, a sample size of 384 is sufficient for a population size of more than 1000000.
2) Based on types of scales used in the instrument designing:
Based on the type of scale used for measuring variables, sample size can be ascertained. If study primarily uses 7-point likert scale, as per Cochran’s sample size formula for a seven point scale likert, sample size of 118 is deemed sufficient.
3) Based on number of factors to be analyzed:
Literature (MacCallum, Widaman, Zhang, & Hong, 1999) reveals that for factor analysis, adequate sample size is partly determined by the strength of data, i.e. if the data strength is good, even for the smaller sample, results can be accurate and reliable. However, strength of data cannot be ascertained in advance, and thus it is important to have criteria for ascertaining the sample size.
In this regard, Comrey and Lee (1992) offered a rough rating scale for factor analysis and gave rough rating scale for sample size in factor analysis as: 100=poor; 200=fair; 300=good; 500=Very Good; and 1000 or more excellent. They urged the researchers to obtain samples of 500 or more observations whenever factor analysis was being used.
The best method of determining the sample size for Factor Analysis is subject to item ratio, and in this regard, the very common method approved by a number of leading names (David Garson, 2008; Everitt, 1975; Everitt, 1975, Nunnally, 1978, Arrindell & van der Ende, 1985) is called the rule of 10, wherein, it is suggested that there should be at least 10 cases for each item in the instrument being used.
Thus, if we go by this assessment, an overall sample size of around 450 would be deemed sufficient as in totality we deal with around 45 items.
Hope it helps.
(Z* S/ e)2
where Z is the confidencelevel
S is sample standard deviation , approximated as range/6
e is the tolerable error.
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