Chapter 3

Methodology



3.1 Conceptual Framework


Figure 3.1 Conceptual Framework

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3.2 Population and Sample Size

The population of interest for the research is the iOS and Android users in Bangkok, Thailand. Because of indefinite population, the size of sample group in this study was calculated by using equation (Zubair K.O., 2012) as follows:

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𝑛 = Desired sample size

Z = Standard normal deviate; usually set at 1.96, which correspond to 95% confidence level.

P = Proportion in target population estimated to have a particular characteristics. If there is no reasonable estimate, use 50% (i.e. 0.5)

D = Degree of accuracy required, usually set at 0.05 level

From equation the sample size can be calculated as follows;

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3.3 Data collection

This study collected data from 404 samples from people in Bangkok who use iOS or Android operating system. The research applied the convenience sampling since the cost of a census for surveying the entire population is too high. Convenience sampling is a type of non-probability sampling. It involves the sample being drawn from that part of the population, which is close to hand. A population is selected because it is available and convenient.

The questionnaire was distributed via two channels. The first channel is the Internet. To distribute the questionnaire massively and to collect them efficiently, the questionnaire was distributed on a smartphone forum (pantip.com) and facebook.com on the Internet and was filled in by people who were qualified. The second channel is document through friends who met the requirements. The contents of the questionnaire of two channels have no difference.

The research proceeded to have the pre-test questionnaire. This process was conducted by interviewing friends and asking the qualifiers completing the questionnaire to gather respondents’ opinions and to understand whether there are inadequacies in the questionnaire. At this stage, 30 questionnaires were collected and found that Cronbach’s Alpha Coefficient was 0.702. After the modifying based on the collected data of the first stage, formal questionnaires were distributed to the two channels via Internet and document.

3.4 Hypotheses of Study

1. 𝐻0 There is no significant relationship between gender and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between gender and user’s decisions to use iOS and Android.

2. 𝐻0 There is no significant relationship between age and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between age and user’s decisions to use iOS and Android.
3. 𝐻0 There is no significant relationship between education level and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between education level and user’s decisions to use iOS and Android.

4. 𝐻0 There is no significant relationship between income level and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between income level and user’s decisions to use iOS and Android.

5. 𝐻0 There is no significant relationship between current operating system and decisions to change operating system.

𝐻1 There is a significant relationship between current operating system and decisions to change operating system.

6. 𝐻0 There is no significant relationship between price and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between price and user’s decisions to use iOS and Android.

7. 𝐻0 There is no significant relationship between appearance and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between appearance and user’s decisions to use iOS and Android.

8. 𝐻0 There is no significant relationship between specification and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between specification and user’s decisions to use iOS and Android.

9. 𝐻0 There is no significant relationship between application and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between application and user’s decisions to use iOS and Android.

10. 𝐻0 There is no significant relationship between stability and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between stability and user’s decisions to use iOS and Android.

11. 𝐻0 There is no significant relationship between compatibility and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between compatibility and user’s decisions to use iOS and Android.

12. 𝐻0 There is no significant relationship between after sale service and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between after sale service and user’s decisions to use iOS and Android.

13. 𝐻0 There is no significant relationship between social acceptance and user’s decisions to use iOS and Android.

𝐻1 There is no significant relationship between social acceptance and user’s decisions to use iOS and Android.

14. 𝐻0 There is no significant relationship between word of mouth effect and user’s decisions to use iOS and Android.

𝐻1 There is a significant relationship between word of mouth effect and user’s decisions to use iOS and Android.

3.5 Research Design and Instrument

The questionnaire will be distributed to respondents randomly during October to November 2013. The questionnaire will be composed of 3 parts 16 questions as follows;

Part 1 Consist of close-ended questions including demographic data of respondents in total of 5 questions namely gender, age, education background, income, current operating system; questions number 1-5.

Part 2 Consist of questions including factors that influencing people to use iOS or Android; questions number 6-15.

Part 3 Consist of questions about decision to change operating system; questions number 16-17.

The researcher defines the criteria to measure level of variable according to the separate of five levels following Likert’s scale. The class interval is calculated by creating a frequency distribution from grouped data to find the range of the scores (highest minus lowest score); make a preliminary choice of the desired number of class intervals; determine the interval width by dividing the range by the number of class intervals; determine the lower real limit of the lowest interval; prepare a list of the limits of each class interval, starting at the bottom; and count the number of observations that occur in each interval (Kendall, 1969).

Table 3.1 Width of Class Interval

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3.6 Personal Depth Interview

Interview 2 companies which use mobile application for marketing channel to gain information about factors that influencing their decisions to use iOS and Android. Interview 4 developers to gain information about factors that influencing their decisions to develop iOS and Android. The researcher uses structured survey questionnaire for interviews by phone.

3.7 Quantitative Data Analysis

The researcher analyzes data variables using SPSS program to compute for the results. The outputs of the program have been presented in chapter four (Results) and the result of respondents will be analyzed as follows:

1) Descriptive statistics to describe the demographic variables as gender, age, education level, income, current operating system, changing operating system and reasons that affecting users change operating system by mean, frequency distribution and percentage.

2) Descriptive statistics including mean, frequency, percentage and standard deviation are employed to test hypothesis and answer research questions.

3) Chi square (𝑥2) Test and T-Test are used to analyst data variables at significant level 0.05.

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