2.2 Data collection methods
The data came from a survey of 250 students at University of Queensland. The students were in either studying undergraduate or postgraduate courses. Personally administered questionnaires was adopted on this survey. The reason for using personally administered questionnaires is that ‘the researcher can collect all the completed responses within a short period of time. Also the researcher has the opportunity to introduce the research topic and motivate the respondents to give frank answers’ (Cavana, Delahaye & Sekaran 2002:307).
2.3 Data collection procedures
The researcher went to the cafeterias in University of Queensland between 12 pm and 1:30 pm while most students were eating lunch at there. The students were selected randomly by the researcher to answer the questionnaire. Firstly, the researcher introduced the research topic and purpose clearly to the students with polite attitude. Also the researcher should mention this survey would not take too long to answer the questionnaire to the students, because majority people were unwilling to spend long period of time for doing survey during the lunch time. Then the student was given the questionnaire (see Appendix). When the respondents had any doubts with the questions, then the researcher should clarify those problems for them. In addition, the researcher should maintain patient during the participants doing the questionnaires. The researcher should not give any pressure to expose participants to physical or mental stress, it may effect participants gave untruly answers for the question or refused to complete the questionnaires.
2.4 Sample characteristics
A simple random sample of 250 students was selected from the University of Queensland. Their ages ranged from 18 to 40 years. Most of the participants were under 25 years (190 students, 76 per cent), and others over 25 years (60 student, 24 per cent). There were 116 (46.4 per cent) men and 134 (53.6%) women in the sample.
2.5 Responses
A total of 250 questionnaires were collected but 195 (78 per cent) were regarded as invalid due to 30 (12 per cent) of the participants did not access the Internet, and the others 165 (66per cent) of the participants who did access the Internet but did not ever make any purchase online. Those 195 students did not answer the major research question of the factor influencing Internet purchases of goods. Hence, the analysis was based on 55 valid (22 per cent) participants who did have the experience of purchasing goods on the Internet.
3. Data Analysis
3.1 The process of data analysis
After data have been obtained through questionnaires, they need to be edited firstly. Then the blank answers were handled by researchers, because not all respondents answered every item in the questionnaire. For this online purchasing research, the answers have been left blank over half questions done by 195 (78 per cent) respondents. The reason was the respondent was simply indifferent to answer the entire questionnaire, those students did not ever purchase goods on the Internet. The next step was to code the data, and set up a categorization scheme for categorizing the variables. Finally, the data were keyed into a software program to analyses the data (Cavana, Delahaye & Sekaran 2002:315-318).
3.2 Using software program of SPSS
In this project interpreted the results using SPSS, a menu-driven software program to do the statistical analysis. Firstly, the SPSS data file presented on the table, and ‘each row showed the reposes to each question by each respondent; and each column showed the responses to each question by all respondents’ (Cavana, Delahaye & Sekaran 2002:403). There were 55 responses to this questionnaire, which had nine questions. Because this project main aim is to analyse the factors influencing Internet purchasing namely, security, price, convenience, brand loyalty and control. And finding the question of do heavy Internet users (using more than 25 hours per week) influence by different factor comparing with light Internet users (using less than 5 hours per week)? Due to the reasons above, we just chose two questions becoming two variables, then the labels and vales were given to each variable, which shows on the table below
Next, the SPSS Data Editor provided the views of this input data and each variable was specified. Finally, the SPSS package has a program called frequencies to perform descriptive statistics, and then examined the hypothesis (Cavana, Delahaye & Sekaran 2002:403-405).
3.3 Results
The overall results indicated that of the 55 valid responses, 20 per cent (11) of the respondents influence mostly by security while they purchasing online, 30.9 per cent (17) by price, 32.7 per cent (18) by convenience, 5.5 per cent (3) by brand loyalty and 10.9 per cent (6) by control. The respondents citing the convenience formed the largest factor, which examined the hypothesis of if consumers purchase online, they will influence mostly by the factor of convenience. There was a significant positive correlation, then the hypothesis was substantiated.
Frequency Percent
Price 17 30.9
Convenience 18 32.7
Brand loyalty 3 5.5
Control 6 10.9
For the second research question of do heavy Internet users (using more than 25 hours per week) influence by different factor comparing with light Internet users (using less than 5 hours per week)? The results indicated who using the Internet less than 5 hours per week influenced by the factor of price with 3. On the other hand, who using the Internet more than 25 hours per week influenced by the factor of price with 5. The hypothesis stated If consumers are the heavy Internet users, they will consider price much than the light Internet users. There was a significant positive correlation, then the hypothesis was substantiated.
Less than 5 (hours) 5-15 15 -25 More than 25 Total
4. Strengths
There were several strengths in this redesigned study. Firstly, the personally administered questionnaire was adopted to gather the data. This method offered the researchers to collect all the completed responses within a short period of time and collected the questionnaires immediately after they are completed. Also the researcher had the opportunity to introduce the research topic and was given frank answers by the respondents. Moreover, there was a almost 100 per cent response rate.
In contrast with original study, the author used the research method of electronic questionnaires. An e-mail was sent to each individual in the sampling frame. The respondents could either send the completed questionnaire that was attached to the e-mail or they could visit the Web page containing the questionnaire. In this circumstance, not all respondents were willing to complete the survey and sent it back to the researchers (Cavana, Delahaye & Sekaran 2002:243-245).
Secondly, the redesigned study added one more independent variable as security into the survey. Because the studies have identified that many Internet users concerns security when making online purchases (Brendon 2002). However, in the original study, the author did not add this factor into his research. In addition, the redesigned study compared the influencing factors between heavy internet users and light internet users, and provided extra information to understand the people’s consideration by different time level of using Internet.
5. Limitations
There were several limitations in this redesigned study. Firstly, the samples were selected randomly from the students in the university. There still had a small number of participants did not access to the Internet, and a large number of participants who did access to the Internet, but without making any purchasing online. Due to those reason above, the number of valid responses became less. On the other hand, in the original study, the author selected anticipants from a consumer panel of 10,000 Internet users owned by a research firm. There was a higher proportion obtaining the valid responses from this specific group.
Moreover, the redesigned study used personally administered questionnaires to obtain the valid responses in the small boundary. However, for the original study, the author used electronic questionnaires could reach out broad geographic area.
References
Brendon, D. F. 2002, ‘Customer trust is no longer an option’, The requirement for success Quality Congress, Retrieved 2 October 2003 from ProQuest database.
Cavana, R. Y., Delahaye, B. L. & Sekaran, U. 2002, Applied business research: Qualitative and Quantitative Methods, John Wiley & Sons Australia, Ltd, Milton.
Goldsmith, R. E. 2002, ‘Buying apparel over the Internet’, Product and Brand Management, vol. 11. Retrieved 2 October 2003 from ProQuest database.
Quick, R. 1999 ‘Shopping Lists: The ABCs of buying online’, Finding a retailer to getting the goods, Retrieved 4October 2003 from ProQuest database.
Appendix
1. Which age group do you belong? (years)
◻ Under 25 ◻ 25-35 ◻ over35
2. What is your gender?
◻ Male ◻ Female
3. Do you have access to the Internet?
◻ Yes ◻ No (If you tick ‘Yes’, continue answer question below)
4. Have you ever purchased any goods online?
◻ Yes ◻ No (If you tick ‘Yes”, continue answer questions below)
5. How often do you purchase online?
◻ Very often ◻ Often ◻ Sometimes ◻ Rarely
6. How many hours a week do you spend using the Internet?
◻ Less than 5 ◻ 5-15 ◻ 15-25 ◻ More than 25
7. Which factor do you consider mostly while you purchase online?
◻ Security ◻ Price ◻ Convenience ◻ Brand loyalty ◻ Control
8. What type of goods do you purchase on the Internet?
◻ Ticket ◻ Book ◻ Electronic Equipment ◻ Other
9. How much do you spend to buy products or services online per month?
◻ Less AU$50 ◻ AU$50-AU$150 ◻ Over AU$150
