AMB201: MARKETING & AUDIENCE RESEARCH

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1 AMB201: MARKETING & AUDIENCE RESEARCH Assessment 3: Predictors of Online Retail Shopping Student name: Jenny Chan Student number: n Tutor name: Jay Kim Tutorial time: Friday 2pm-3pm Due Date: 3 June 2016 Word count: 1993

2 Table of Contents Participant Reflection... 2 Executive Summary Introduction and Background Importance of the research Scope of the report Research problem/question Aim and objectives Method Methodology considerations and assumptions Sample considerations Data collection and framework, and analytical considerations Ethical considerations Analysis Data cleaning and editing Descriptive Data Analysis for Objective Analysis for Objective Correlation Regression Discussion and Recommendations Objective Objective Limitations References Appendices Objective 2 definition for two variables Surveys

3 Participant Reflection The project I chose to participate was Handbags! Showy and Blingy, or Subtle and confident which it is an online study of quantitative survey based on the brand research on the handbags. Reason why I took this participant as a quantitative survey project because it is an good experience for me as a participant which I am interested in handbags fashion and I have the knowledge about the handbags design include luxury handbags. Before I take this project participant, I read the description on this project on the handbags research is to examining on the consumer perceptions of different types of luxury handbags. The participation project is based on the survey questions include the knowledge question about the luxury handbags brands and there is a two picture of the luxury handbags product brands are Coach and Louis Vuitton. While I did the survey, the Coach products with an equally price show the two similar products include handbags size design but different colour and pattern compare to Louis Vuitton. Louis Vuitton products has the equally price which it show the pictures of the same bags design but the Louis Vuitton logo is different on the bags. The first bag of Louis Vuitton logo is the middle of the bags and second bag is on the right hand corner. Overall with this survey are negative and positive questions for people are willing to buy the luxury bags design. Also there is a question in the survey is that if my friends were shopping for a handbag and I would recommend to my friend which bag design of Coach and Louis Vuitton between those two bags design. The use of this participate project experience would use my own survey question as different question. Using with my own questions in the survey would be easier because I can use my own questions by using the scale 1 to 7. 1 is disagree and 7 is agree which it can be relate how people see the brand of the handbags products for example: would you buy a handbags with a good quality products, I am motivated to buy luxury products, did some research on luxury handbags products and have you own any luxury handbags products. The researchers who are interested and have the knowledge in handbags can also take part in research as a participant because it shows that the researchers can see who take part of this project and they can have their own opinion because there is no right or wrong answer in the survey. 2

4 Executive Summary This descriptive research report is to investigate the determinants of Australian consumers attitude toward online retail shopping purchase behaviour and it is builds on previous qualitative research. The two objectives are based on the cognitive dimension of attitude will be analysed as the dependent variables includes: The segment is analysing on the relationship between age cohort and gender The t-test used the two group is different to their attitudes toward online shopping Measure the relationship between price consciousness and convenience seeking of individual characteristics The regression and correlation with the two variables characteristics of the result with positive or negative significant. The research report is the recommendation is that the two variables of attitudes toward online retail shopping is that the frequency of age is that the younger and older cohort. The future research is to improve in the market research by the respondent will conducted the survey without error. 3

5 1.0 Introduction and Background 1.1 Importance of the research The importance of the research is to be part as the market research is to systematic and objective process of generating the information by making in a marketing decision on the Australian adults with their attitudes toward online shopping (Zikmund, D Alessandro, Winzar, Lowe & Babin, 2014, p.6). The research is important to be part of the market research is to use the descriptive research with their behaviour on the Australian consumers attitudes towards online shopping by their behaviour, as well as any potential market segment. This research is related to the findings from the previous qualitative research with their experience online shopping. Quantitative research is important to allow the questioning of facts necessary determine a course of action which it building the insight from the qualitative research (Zikmund et al, 2014, p72). Unlike the exploratory research is conducted the initial stage of the research process and the descriptive research being undertaken based on a previous research to understanding of the research problem (Zikmund et al, 2014). 1.2 Scope of the report The scope of this research report is based on the Australian adults consumers behaviour concerns with their attitudes toward online shopping. The role of this research is stage 2 of 2 in the research report process. The participants must be over 18 to participate in surveys. The participants must have one respondent aged of which it is younger cohort and one respondent aged of 41+ which it is older cohort. This report will cover on segmentations variables and characteristics constructs based on the attitudes toward online retail shopping cognitive. 1.3 Research problem/question The research question is to show the behaviour on the determinants of Australian consumers attitudes toward online shopping. 1.4 Aim and objectives The aim and objectives of this report are to explore the quantitative research on the determinants of Australian consumers attitudes toward online retail shopping. The two specific objectives used in the survey include: 4

6 Objective 1: to examine if attitude toward online retail shopping differ across population segments is based on the younger verse older, men verse women and married verse single of the target population. Objective 2: to determine the impact of individual characteristics on attitudes toward online retail shopping is various each individual characteristics relate to the respondents attitude toward online shopping. 2.0 Method 2.1 Methodology considerations and assumptions The methodology in the report use the descriptive research is being is use quantitative research techniques is the objective to conducted the survey are designed of online shopping behaviour (Zikmund et al, 2014). The descriptive research is to describe the characteristics of the target population and conducted to help to segment the market and often to reveal the nature of shoppiung or other consumer behaviour (Zikmund et al, 2014, p.25). This research study is cross-sectional are surveys to divide the sample by age into subgroups and the respondents are only interviewed once (Zikmund, Ward, Lowe, Winza r & Babin, 2011, p134). Cross-sectional studies are time and cost efficient, measure the behaviour and attitudes at a point of time and the predictability of findings can be questionable (Zikmund et al, 2011, p135). The primary data is that the researcher specific purpose of addressing the problem (Malhotra, Hall, Shaw & Oppenheim, 2006, p138) to gather and assembled specifically for the research at hand (Zikmund et al, 2014, p.23-4). It is assumed that the participants have correct insight with their own behaviour and being honest with these as accuracy of paramount in descriptive research ((Zikmund et al, 2014, p.25). The number of male and female from each age have been selected as assumed the sample representative. However, the random sample error and systematic errors is related to the sampling process can be representative of the sample (Zikmund et al, 2011, p329-30). 2.2 Sample considerations The sample is the target population of the survey is Australian adults who regularly use the internet aged of 18 and above. The target population sample size is 748. The probability sampling techniques use the population known as non-zero probability in the research selection (Zikmund et al, 2014, p355). With these sampling is a quota sampling which the Australian consumers attitude toward shopping which it is various subgroups in the target 5

7 population to represent the sample with their characteristics result (Zikmund et al, 2011, p338). 2.3 Data collection and framework, and analytical considerations The research is generally involves with quantitative techniques in this report. Researchers were divided two equal groups according to the family surname. One group gathered two male respondents and other gathered two female respondents aged of and aged 41+. Each researcher interviewed one respondent from each age group using the same survey document attached the consent form and the survey should takes approximately 10 to 15 minutes to answer all survey questions. Researcher uploaded the data onto online database and leaving room for the systematic error. The survey use t-test, regression, correlation and coefficient. The t-test is to choose the two segmentation variables of age cohort, gender, relationship status and communication preference to statistically differ between with the two groups by the variability these means. The correlation and regression is to choose the two segmentation variables of risk aversion, price consciousness, variety seeking, convenience seeking, impulsiveness and materialism. The correlation is the relationship between two segment variables will be negative or positive correlation relationship (Zikmund et al, 2014, p479). The regression is analysis to identifies the nature of the relationship using the equation (Wilson, 2003, p215). 3.0 Ethical considerations The ethics is the important part in the marketing research as research is depends on the consumers willing be part of the research and willing to cooperate with their respondents (AMSRS, 2015). The consumers can trust and rely on the assumption of the research must be conducted honest, truthful and objectively with the respondents privacy (AMSRS, 2015). In line with Queensland University of Technology (QUT) is that the data material will be collected, maintained and retained in the ethics policy (QUT, 2016). The respondents are entirely voluntary at all the research stages and were not misleading (AMSRS, 2015). The Respondents are 18 and over, require to sign the consent form from the appendices section is under QUT policy which the form explain the participants confirms and agrees to do the surveys. The consent form describes the research, participant, expected benefits, risks and privacy and confidentially (AMSRS, 2015). 6

8 4.0 Analysis 4.1 Data cleaning and editing The data was cleaned, issues with respondent data were resolved which some of the data sets were removed and frequencies were checked to ensure that the data value were in range. Any negative phrased items were reversed and the construct values were determined for each respondent is to average the data across with their relevant items. 4.2 Descriptive Data Table 1: Descriptive Statistics * N Minimum Maximum Mean Std. Deviation ATTC RA PC IMP VS CS MAT Valid N (listwise) 741 Table 1 show that the mean has the highest is PC at and the lowest is IMP at However, the ATTC mean is higher at which the range is different to the other variable constructs. Figure 1: Age cohort * Frequency Percent Valid Percent Cumulative Percent Valid Younger Older Total

9 Figure 1 demonstrates there were similar numbers of respondents in each age cohort. Figure 2: What is your gender? * Frequency Percent Valid Percent Cumulative Percent Valid Male Female Total The figure 2 explains the male is slightly more than female in the sample. Figure 3: What is your relationship status? * Frequency Percent Valid Percent Cumulative Percent Valid Single Partnered Total Figure 3 shows that the number of partnered has more respondents than single who shop online. Figure 4: Which method of online communication do you use more frequently? * Frequency Percent Valid Percent Cumulative Percent Valid Instant messaging (online chat) Total Figure 4 explains that the two figures quite familiar, in figure 4 demonstrates respondents prefer to instant messaging (online chat) than . 8

10 Figure 5: What is your gender? Age Cohort Crosstabulation * Age Cohort Total Younger Older What is your gender Male Female Total The figure 5 explains relatively the age is split between genders. Figure 6: What is your relationship status? Age Cohort Crosstabulation * Age Cohort Total Younger Older What is your relationship Single status? Partnered Total Figure 6 shows that the younger group is more single and older group is more partnered. Figure 7: Which method of online communication do you more frequently use? Age Cohort Crosstabulation * Age Cohort Total Younger Older Which online communication do you more frequently use? Instant messaging (online chat) Total

11 Frequency Jenny Chan n Figure 7 is explain that the older group prefer and compare to younger group prefer instant messaging (online chat). 70 Figure 8: Frequency of Ages Ages In figure 8 the graph shows the highest frequency of ages from to 18 to 23 years and whilst the frequency of ages is relatively similar. 4.3 Analysis for Objective 1 Figure 9: Age Cohort group * Age Cohort N Mean Std. Deviation Std. Error Mean ATTC Younger Older In figure 9 is that the table for older cohort has the highest mean at attitudes toward online shopping than younger cohort at Figure 10: t-test on Age Cohort 10

12 ATTC Equal variances assumed Equal variances not assumed Levene s test t-test for equality of means for equality of variance f Sig. t df Sig. (2 tailed) Mean difference Std error difference 95% confidence interval of the difference Lower Upper In figure 10 is assuming equal variance, a t-test showed that the difference between younger and older cohort is that the t-test is significant at.000 which it is below This indicates that the means difference for younger and older cohort. Figure 11: Gender group * What is your gender? N Mean Std. Deviation Std. Error Mean ATTC Male Female Figure 11 is that the male has the highest mean at , while the mean attitude towards online shopping for female was Levene s test for equality of variance Figure 12: t-test on Gender t-test for equality of means 11

13 ATTC Equal variances assumed f Sig. t df Sig. (2 tailed) Mean difference Std error difference 95% confidence interval of the difference Lower Upper Equal variances not assumed The figure 12 assuming equal variance that the t-test showed that the difference the means for male and female was not significant at.309. This indicates that the.309 is higher than 0.05 meaning there is no significant difference between male and female. 4.4 Analysis for Objective Correlation Table 2: Individual Characteristics Price Consciousness Pearson Correlation Sig. (2-tailed) N Convenience Seeking Pearson Correlation Sig. (2-tailed) N.321** *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). Correlation is measure of the relationship between two variables showed the result that it is a moderate positive significant of price consciousness and convenience seeking which it is indicates as attitude toward online retail shopping. 12

14 4.4.2 Regression Figure 13: Price consciousness model summary Model* R R Square Adjusted R Square Std. Error of the Estimate 1.024ᵃ a. Predictors: (Constant), PC Figure 13 shows that the R indicates correlation between predicted values and observed data is.024². R square is the proportion of the variance in the dependent variable explained by the regression equation which it is.001 and the adjusted R Square is the value at which means it is 1% of the dependent variable by the model. Figure 14: Price Consciousness Coefficients Regression Unstandardized Coefficients Standardized Coefficients Model* B Std. Error Beta t Sig. 1 (Constant) PC a. Dependent Variables: ATTC Figure 14 display that the individual characteristic of price consciousness is significant of dependent variable of 0.24 and to predict the estimate of a person s attitude toward online shopping to give the good estimate for the ATTC. The predict estimate is 3 x = The predict estimate is Figure 15: Convenience Seeking Model Summary Model* R R Square Adjusted R Square Std. Error of the Estimate 1.321ᵃ a. Predictors: (Constant), CS 13

15 Figure 15 for R is indicates that the correlation of the values and observed data is.321. The proportion of R Square of the variance in the dependent variable regression equation is.103 and the adjusted R Square is the value at.102 which means it is 1.02%. Figure 16: Convenience Seeking Coefficients Regression Unstandardized Coefficients Standardized Coefficients Model* B Std. Error Beta t Sig. 1 (Constant) CS a. Dependent Variable: ATTC Figure 16 show that the individual characteristic of convenience seeking is significant of.321 which it is below 0.05 to predict the estimate of a person s attitude toward online shopping to give the estimate for ATTC. The predict equation is 2 x = The predict estimate is Discussion and Recommendations 5.1 Objective 1 The objective 1 is to examine on the different population of the age cohort and gender variables if attitudes toward online retail shopping differ across population segments on two segmentation variables are age cohort and gender. In figure 9 and 11 shows that the males and female have different behaviour attitudes toward online shopping, therefore that male in older cohort have the most population. Figure 10 and 12 have the equal variance for gender and age cohort. The recommendation is that the two segmentations variables is to have male and female similar result with their behaviour towards shopping online. 5.1 Objective 2 The objective 2 is to determine the impact of individual characteristics on attitudes toward online retail shopping based on two individual characteristics variables are price consciousness and convenience seeking (appendix 8.1). The behaviour of the two variables behaviour in table 2 for the correlation show that the attitude is moderate positive and the regression in figure 14 and 16 is the coefficient with their attitude of how it is convenience 14

16 and the price for online shopping. The recommendation for the two variables for correlation and the regression to make strong positive instead of moderate positive with their attitudes toward online shopping. 6.0 Limitations In figure 8 Frequency of Ages demonstrates is that the 18 to 23 years has the highest frequency and compare to 31 to 38 years old has the lowest frequency. Whilst the frequency of ages is that the sample is not representative which it is impacts on the accuracy and generalisability of the result. Random sampling error result may occur through statistical fluctuation due of chance variation (Zikmund, et al, 2011, p329). To improve the random sampling error by using the sample frame which relate to the target population to subset the list of infeasible is highly of how representative the subset (Zikumnd et al, 2014, p349). Interviewer cheating occurs when an interviewer falsifies the entire questionnaires or filled in the answers to intentionally skipped (Zikumnd, et al, 2014, p133). To improve for the future research by telling the interviewers with a small number of respondents will be called back to confirm whether the survey was conducted (Zikumd et al. 2011, p 133). 15

17 7.0 References AMSRS. (2015) Code of Professional Behaviour. Retrieved from Malhotra, N., Hall, J., Shaw, M., & Oppenheim, P. (2006). Marketing Research: An applied orientation (3 rd ed). French Forest, New South Wales: Pearson Australia. QUT. (2016). D/2.6 QUT Code of Conduct for Research. Retrieved from Queensland University of Technology: Wilson, A. (2003). Marketing Research. An Integrated Approach. Harlow, England, Pearson. Zikmund, W., D'Alessandro, S., Winzar, H., Lowe, B., & Babin, B. (2014). Marketing Research (3 rd ed). South Melbourne, Victoria: Cengage Learning Australia. Zikmund, W.G., Ward, S., Lowe, B., Winzar, H., & Babin, B. J. (2011). Marketing Research (2 nd ed.). South Melbourne, Victoria: Cengage Learning. 16

18 8.0 Appendices 8.1 Objective 2 definition for two variables Convenience Seeking refers to searching for ways of achieving tasks with minimal difficulty 1. I hate to spend time gathering information on products 2. I do not like complicated things 3. It is convenient to shop from home 4. It is important to me that I can shop anytime I choose 5. It is important to me that I can shop no matter where I am 6. The ability to quickly compare products is important to me 7. When shopping, I like to find what I want quickly Price consciousness refers to having a vigilance for difference in price among available options and avoiding those purchases that are too expensive. 1. I usually buy the cheapest product available 2. I usually purchase items on sale 3. I often find myself checking prices 4. A person can save a lot of money by shopping for bargains 8.2 Surveys 17

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