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Fashion Clothing Purchase Behaviours AMB201 Assessment 3 – Descriptive Research Report

Colleen Dunne

Colleen Dunne n8614725

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Table of Contents III. EXECUTIVE SUMMARY ..................................................................................................................... 2 1.0 INTRODUCTION AND BACKGROUND .......................................................................................... 3

1.1 IMPORTANCE OF THE RESEARCH .......................................................................................................................... 3 1.2 SCOPE OF THE RESEARCH ....................................................................................................................................... 3 1.3 RESEARCH PROBLEM/QUESTION .......................................................................................................................... 4 1.4 AIMS AND OBJECTIVES ........................................................................................................................................... 4

2.0 METHOD .................................................................................................................................................... 4 2.1 METHODOLOGICAL CONSIDERATIONS AND ASSUMPTIONS ......................................................................... 4 2.2 SAMPLE CONSIDERATIONS .................................................................................................................................... 5 2.3 DATA COLLECTION AND FRAMEWORK, AND ANALYTICAL CONSIDERATIONS ..................................... 5

3.0 ETHICAL CONSIDERATIONS ........................................................................................................... 5 4.0 ANALYSIS .................................................................................................................................................. 6

4.1 DATA CLEANING AND CODING ............................................................................................................................ 6 4.2 DESCRIPTIVE DATA .................................................................................................................................................. 6 4.3 T-TESTS ..................................................................................................................................................................... 10 4.4 CORRELATION ......................................................................................................................................................... 11 4.5 MULTIPLE REGRESSION ....................................................................................................................................... 12

4.5.1 Gender ................................................................................................................................................................... 13 4.5.2 Age .......................................................................................................................................................................... 15 4.5.3 Relationship Status ........................................................................................................................................... 17 4.5.4 Social Desirability ............................................................................................................................................ 19

5.0 FINDINGS AND RECOMMENDATIONS ....................................................................................... 22 5.1 IDENTIFYING THE IMPACT OF INDIVIDUAL CHARACTERISTICS ON FASHION CLOTHING PURCHASE BEHAVIOUR. .................................................................................................................................................................... 22 5.2 IDENTIFYING THE IMPACT OF INTRINSIC MOTIVES ON FASHION CLOTHING PURCHASE BEHAVIOUR. .................................................................................................................................................................... 23 5.3 IDENTIFYING THE IMPACT OF EXTRINSIC MOTIVES ON FASHION CLOTHING PURCHASE BEHAVIOUR. .................................................................................................................................................................... 23 5.4 IDENTIFYING ANY MEANINGFUL MARKET SEGMENTS IN THE FASHION CLOTHING MARKET. ...... 23 5.5 UNDERSTANDING HOW SOCIAL DESIRABILITY BIAS MAY INFLUENCE THE RESULTS OF THE RESEARCH. ....................................................................................................................................................................... 25

6.0 LIMITATIONS ........................................................................................................................................ 25 7.0 REFERENCES ........................................................................................................................................ 27 8.0 APPENDICES .......................................................................................................................................... 29

8.1 APPENDIX A – CONSTRUCT DEFINITIONS ...................................................................................................... 29 8.2 APPENDIX B – HOW CONSTRUCTS RELATE TO OBJECTIVES ................................................................... 30 8.3 APPENDIX C – SURVEYS ...................................................................................................................................... 31


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iii. Executive Summary This descriptive research report investigates the drivers of Australian fashion clothing

purchase behaviours, and builds on previous qualitative research. Findings indicate the need

to segment across age and relationship status when marketing fashion clothing.

Findings include:

• Respondents identified they seek to own trends before the mass market does, and like

to be confident in what they are wearing.

• Respondents who were more delicate and excitable were more likely to engage in

fashion purchasing behaviours.

• Intrinsic motives were found to impact on fashion purchasing behaviours: respondents

indicated they sought to project a ‘good’ image and are motivated to engage in fashion

purchasing as a pastime.

• Extrinsic motives were found to impact fashion purchasing behaviours: respondents

identified they were motivated to gain social approval and attention when choosing

clothing.

• No meaningful market segment exists for gender.

• A meaningful market segment exists for generational cohorts and relationship status

• Social desirability impacted the results of this report.

Drivers of fashion clothing differ across age and relationship status, reinforcing them as

meaningful market segments. Gender is not a meaningful market segment and can be

approached using mass marketing.


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1.0 Introduction and Background

1.1 Importance of the research

This research will give insight into the impact of certain variables on fashion clothing

purchase behaviours, as well as any potential market segments. This is important for

marketers as it will allow for the systematic and objective generation of information to aid in

marketing decisions (Zikmund, Ward, Lowe, Winzar, & Babin, 2011, p. 4).

This research is important from a theoretical view as it will may add to current theoretical

models, or reinforce current marketing theories. Piamphongsant (2006) stipulates research has

shown conformity and individuality are important foundations in fashion clothing purchase

behaviour. Hourigan and Bougoure (2012) state materialism and gender are other drivers of

fashion clothing involvement. One potentially relevant theory is the theory of planned

behaviour: behaviours are governed by, and can be predicted, based on personal attitudes,

social pressures and a sense of control (Cooke & Sheeran, 2004). Another theory that may

apply is the theory of conspicuous consumption: people spend money on expensive items to

demonstrate their wealth and power (Trigg, 2001).

These theoretical and practical applications relate to findings in previous qualitative research.

It was found age, timeliness, self-perception, cost, media and context were all drivers of

fashion purchasing behaviours. Quantitative research is important as it allows the questioning

of facts to determine a course of action, building on the insight qualitative research provided

initially (Zikmund et al. 2011, p.68). Unlike the exploratory research conducted initially, the

descriptive research being undertaken is based on a previous understanding of the nature of

the research problem (Zikmund et al. 2011, p.23).

1.2 Scope of the research This research is based on reported behaviours (Smyth et al. 2013) concerning the drivers of

fashion purchasing behaviours of consumers aged between eighteen and sixty-five years in

Australia. The report will cover impact variables, intrinsic and extrinsic motives, potential

segments and social desirability bias.


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1.3 Research problem/question The research question is whether segmentation or mass marketing is most suited when

marketing fashion clothing to Australian consumers.

1.4 Aims and Objectives The aim of this report is to quantitatively examine the drivers of fashion purchase behaviours.

The table below outlines the objectives of this report.

Objective i. To identify the impact of individual characteristics on fashion

clothing purchase behaviour.

Objective ii. To identify the impact of intrinsic motives on fashion clothing

purchase behaviour.

Objective iii. To identify the impact of extrinsic motives on fashion clothing

purchase behaviour.

Objective iv. To identify any meaningful market segments in the fashion

clothing market.

Objective v. Understand how social desirability bias may influence the results

of the research.

2.0 Method

2.1 Methodological considerations and assumptions Descriptive research is being conducted as surveys are designed to describe the characteristics

of fashion purchase behaviours (see 1.4 Aims and Objectives) (Zikmund et al. 2011, p.23),

and not to identify a cause and effect relationship (i.e. causal research) (Zikmund et al. 2011,

p.25). Descriptive research is being conducted as it helps to segment and target markets and is

often used to reveal the nature of shopping or other consumer behaviours (Zikmund et al.

2011, p.23). The study is cross-sectional as the survey has been divided by age into sub-

groups and respondents are only interviewed once (Zikmund et al. 2011, p.134). Whilst cross-

sectional studies are time and cost efficient, measurements are made at a point of time and so

the predictability of findings can be questionable (Zikmund et al. 2011, p.135.).

Primary data is being collected as it has been gathered for the project at hand (Zikmund et al.

2011, p.22). It is assumed participants have correct insight into their own behaviours, and are


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being honest about these, as accuracy is imperative in descriptive research (Zikmund et al.

2011, p.23). An equal number of males and females from each age bracket have been

selected, and so it is assumed the sample is representative. However, random sampling errors

and systematic errors associated with the sampling process can affect the representativeness

of the sample (Zikmund et al. 2011, p.330).

2.2 Sample Considerations The target population of this survey is Australian purchasers of fashion clothing aged eighteen

and above. The sample consisted of males and females across three age brackets: 18-31 years,

32-48 years, and 49-65 years. Time and cost constraints dictated a sampling frame was not

feasible, so the selection of respondents was based on researcher judgement (Zikmund et al.

2011, p.326). Whilst this convenient sampling was more practical, it affects the

generalisability of results (Zikmund et al. 2011, p.328). The sample size was 1 174, with 571

males and 603 females.

2.3 Data collection and framework, and analytical considerations Researchers were divided into two equal groups according to surname. One group gathered

results from females, the other, males. Each researcher interviewed one respondent from each

age bracket using the same survey document with an attached consent form. Researchers

uploaded data onto an online database, leaving room for systematic error (see 6.0

Limitations).

The surveys consisted of interval and nominal scales, including likert scales, semantic

differential scales and dichotomous scales. These interval scales allow for averaging and

adding of data to make comparisons between respondents and segments. Demographical

information was collected at the end of the survey to identify any relevant market segments.

3.0 Ethical Considerations Ethics are important in marketing research as research depends on the continuous willing

cooperation of respondents (AMSRS, 2013). In addition, consumers trust and rely on the

assumption that research is being conducted honestly, objectively and with regard to

respondent’s privacy (AMSRS, 2013). In line with the Queensland University of


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Technology’s (QUT) ethics policy, data was properly collected, maintained and retained

(QUT, 2013).

Respondent’s cooperation was entirely voluntary at all stages and respondents were not

mislead (AMSRS, 2013). Technical details of the research carried out were given to

respondents (AMSRO, 2013). Respondents were aged 18 and over and were required to sign

a consent form which described the research, participation, expected benefits, risks and

confidentiality (AMSRS, 2013).

4.0 Analysis

4.1 Data Cleaning and Coding

The data was cleaned, issues with respondent data were resolved, some data sets removed and

frequencies checked to ensure values were in range. Each discrepancy was assessed

individually. Any negatively phrased items were reversed. Construct values were determined

for each respondent for each respondent by averaging across their relevant items. Social

desirability was determined by summing values together to provide an index.

4.2 Descriptive Data

Figure 1.0 Descriptive Statistics

N Minimum Maximum Mean Std.

Deviation

PurchBehaviour 1174 1.00 7.00 2.8985 1.16744

SocApproval 1174 1.00 6.86 3.4848 1.03994

Recognition 1174 1.00 7.00 3.7076 1.22290

ImageExpression 1174 1.00 7.00 4.0094 1.25162

Recreation 1174 1.00 7.00 4.2216 1.46690

Confidence 1174 1.00 7.00 4.4504 1.10037

FashInnovativeness 1174 1.00 7.00 3.4219 1.05335

Success 1174 1.00 7.00 3.5327 1.08547

Centrality 1174 1.14 7.00 3.9401 0.94630

Happiness 1174 1.00 7.00 3.8327 1.20055


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SocDesire 1174 10.00 20.00 15.0281 2.32083

Valid N (listwise) 1174

Figure 1.0 demonstrates the highest mean in the data is Confidence at 4.4504, whilst the

lowest is purchasing behaviour at 2.8985. Though social desirability’s mean is higher at

15.0281, its range is different to the other constructs.

Figure 1 What is your gender?

Frequency Percentage Valid Percent Cumulative

Percent

Val

id Male 571 48.6 48.6 48.6

Female 603 51.4 51.4 100.0

Total 1174 100.0 100.0

Figure 1 demonstrates there were slightly more females than males in the sample.

Figure 2 Generational Cohort? (Group)


Percent

Val

id

GenY 390 33.2 33.2 33.2

GenX 398 33.9 33.9 67.1

BBoomer 386 32.9 32.9 100

Total 1174 100.0 100.0

Figure 2 demonstrates there were similar numbers of respondents in each generational cohort.

Figure 3 When buying clothing, do you prefer to shop alone or with others?


Percent

Val

id

Alone 649 55.3 55.3 55.3

With

others

525 44.7 44.7 100.0

Total 1174 100.0 100.0


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While the two figures are quite similar, Figure 3 demonstrates more respondents prefer to

shop alone than with others.

This graph demonstrates there is a large grouping of respondents aged eighteen to twenty-two

years, whilst the frequency of the rest of the ages is relatively similar.

Figure 5 What is your gender? Crosstabulation

What is your gender? Total

Male Female

Group

GenY 190 200 390

GenX 195 203 398

BBoomer 186 200 386

Total 571 603 1174

Figure 5 demonstrates there is a relatively even split between genders.

Figure 6 When buying clothing, do you prefer to shop alone or with others?

Crosstabulation

When buying clothing, do you prefer to

shop alone or with others?

Total

Alone With others

0 10 20 30 40 50 60 70 80

18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64

Frequency

Age

Figure 4. Frequency of Ages


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Group

GenY 184 206 390

GenX 231 167 398

BBoomer 234 152 386

Total 649 525 1174

Figure 6 demonstrates most respondents from generation X and the baby boomers prefer

shopping alone, whilst generation Y prefers shopping with others.

Figure 7 Do you regularly use public transport? Crosstabulation

Do you regularly use public transport? Total

Yes No

Group

GenY 239 151 390

GenX 123 275 398

BBoomer 89 297 386

Total 451 723 1174

Figure 7 demonstrates the majority of respondents from generation Y rely on public transport,

whilst the majority of respondents from the two older age brackets do not.

Figure 8 What is your relationship status? Crosstabulation

What is your relationship status? Total

Single Partnered

Group

GenY 217 173 390

GenX 100 298 398

BBoomer 64 322 386

Total 381 793 1174

Figure 8 demonstrates most generation Yer’s are single and most people in generation X and

baby boomers are partnered.

Figure 9 What is your employment status? Crosstabulation

What is your employment status? Total

FT Work PT Work No Work


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Group

GenY 95 219 76 390

GenX 284 79 35 398

BBoomer 212 93 81 386

Total 591 391 192 1174

Figure 9 demonstrates most generation Y respondents are part time workers, whilst most

generation X respondents and baby boomers are in full time employment.

4.3 t-Tests

Does self-reported fashion purchasing differ between males and females?

Figure 10. Group Statistics

What is your

gender?

N Mean Std.

deviation

Std. Error

Mean

PurchBehaviour Male 571 2.9222 1.18564 0.4962

Female 603 2.8760 1.15047 0.04685

This table displays that the mean self-reported fashion purchasing behaviour for males

(2.9222) was higher than females (2.8760).

Assuming equal variances, a t-Test shows sig. is 0.497, which is higher than 0.005, meaning

there is no significant difference between the means for males and females.

Figure 11. Independent Samples Test Levene’s Test

for Equality of Variances

t-Test for Equality of means

f Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper

PurchBehaviour

Equal Variances assumed

.361 .548 .679 1172 .497 .04629 .06819 -.08749 .18007

Equal Variances not assumed

.678 1163.663 .498 .04629 .06824 -.08760 .18018


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Does self-reported fashion purchasing differ based on relationship status?

Figure 12. Group Statistics

What is your

relationship status?

N Mean Std.

deviation

Std. Error

Mean

PurchBehaviour Single 381 3.1207 1.14750 0.05879

Partnered 793 2.7917 1.16258 0.04128

Figure 12 shows the mean for singles (3.1207) is higher than partnered people (2.7917).

Figure 13 demonstrates the difference in means for singles and partnered people is significant.

4.4 Correlation Correlation was used to measure self concept.

Figure 14. Correlations Self Concept with Purchase Behaviour

PurchBehaviour

Rugged/Delicate Pearson Correlation

Sig. (2 tailed)

N

.157**

0.000

1174

Excitable/Calm Pearson Correlation

Sig. (2 tailed)

-.149

0.000

Figure 13. Independent Samples Test Levene’s Test

for Equality of Variances

t-Test for Equality of means

f Sig. t df Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference Lower Upper

PurchBehaviour

Equal Variances assumed

.052 .820 4.560 1172 .000 .32906 .07217 .18747 .47065

Equal Variances not assumed

4.581 758.694 .000 .32906 .07184 .18804 .47008


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N 1174

Tense/Relaxed Pearson Correlation

Sig. (2 tailed)

N

-.005

.872

1174

Results showed a significant positive correlation between rugged and delicate: fashion

purchasing behaviour is higher in people who consider themselves to be delicate. A

significant negative correlation between excitable and calm qualities is present: fashion

purchasing behaviour is higher in people who consider themselves to be excitable. A non-

significant correlation is present between tense and relaxed qualities: there is no impact.

4.5 Multiple Regression Other constructs in the model can be tested using multiple regression, allowing the impact of

independent variables on the dependent variable to be measured.

Figure 15. Model Summary

Model R R Square Adjusted R

Square

Std. Error of

the Estimate

1 .707a .500 .496 .82846

a. Predictors (constant): Recreation, Happiness, Confidence, Recognition,

SocApproval, Centrality, FashInnovativenss, Success, ImageExpression

R indicates the strength of the correlation between the predicted values and observed data and

is .7072. R square is the proportion of variance in the dependant variable explained by the

regression equation and is 0.50. The adjusted R Square value was 0.496 which means that

49.6% of variation in the dependent variable is accounted for by the model.

Figure 16. ANOVAa

Model Sum of

Squares

df Mean

Square

F Sig.

1

Regression 799.793 9 88.866 129.477 0.000b

Residual 798.904 1164 .686

Total 1598.697 1173


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a. Dependent variable: PurchBehaviour

b. Predictors (constant): Recreation, Happiness, Confidence, Recognition,


Figure 16 displays the F statistic is less than 0.05 (0.00), meaning predictors do a good job

explaining the variation in the dependent variable.

Figure 17. Coefficients

Model Unstandardised

Coefficients

Standardised

Coefficients

t Sig.

B Std. Error Beta

(Constant) -.116 .129 -.900 .368

Confidence -.142 .027 -.134 -5.272 .000

FashInnovativenes .516 .034 .465 14.965 .000

Success .050 .035 .047 1.423 .155

Centrality .226 .037 .183 6.149 .000

Happiness -.080 .027 -.083 -2.970 .003

SocApproval .253 .033 .226 7.744 .000

Recognition .055 .026 .058 2.097 .036

ImageExpression .110 .031 .118 3.523 .000

Recreation -.096 .027 -.120 -3.590 .000

Figure 17 displays all individual predictors are significant except Success, which has a

significance level above 0.05 and is therefore not a useful predictor. Fashion Innovativeness

(.465), Social Approval (.226) and Centrality (.183) have the strongest impact on fashion

purchasing behaviours.

4.5.1 Gender

Figure 18. Model Summarya


Square

Std. Error of

the Estimate

Male 1 .727b .528 .520 .82107


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Female 1 .710b .504 .497 .81633

a. What is your gender?



Figure 18 displays that the strength of correlation (R) and proportion of variance (R Square) is

higher in males (.727; .528) then females (.710; .504). 52% of variation for males, and 49.7%

for females is accounted for by the model.

Figures 19 and 20 demonstrate Success, Recognition and Recreation are insignificant

constructs for both male and female fashion purchasing behaviours. Fashion Innovativeness,

Centrality and Social Approval have strongest correlation to fashion purchasing behaviours..


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4.5.2 Age



Square

Std. Error of

the Estimate

GenY 1 .651b .423 .410 .85662

GenX 1 .755b .570 .560 .79522

BBoomer 1 .726b .527 .515 .78987

a. What is your age?



Figure 21 shows the correlation between the predicted values and purchasing behaviour and

proportion of variance (R Square) is strongest for generation X (.755; .570), followed by baby

boomers (.726; .527) and generation Y is the lowest (.651; .570). 41% for of variance is

accounted for by the model in generation X, 56% for generation Y and 51.5% for baby

boomers.


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Figures 22, 23 and 24 demonstrate that drivers of fashion purchasing behaviour differ greatly

across age groups. Success and recognition were insignificant for all age groups. Fashion

innovativeness and social approval showed strong correlations across all age groups.

Centrality and showed strong correlations for generation X and baby boomers, but was an

insignificant factor for generation Y.


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4.5.3 Relationship Status



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Square

Std. Error of

the Estimate

Single 1 .668b .446 .432 .86460

Partnered 1 .723b .523 .518 .80745

a. What is your relationship status?

b. Predictors (constant): Recreation, Happiness, Confidence, Recognition, SocApproval,

Centrality, FashInnovativenss, Success, ImageExpression

Figure 25 shows the correlation between the predicted values and purchasing behaviour is

stronger for partnered people (.723) than singles (.668). R Square was also higher in partnered

people (.523) than singles (.446). 43.2% of variance is accounted for by the model for single

people and 51.8% for partnered people.


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Figures 26 and 27 demonstrate a difference in purchasing behaviours based on relationship

status. Fashion innovativeness is similar for both groups and shows the strongest correlation.

Success is insignificant for both, whilst confidence, recognition and image expression are also

insignificant for singles and happiness is insignificant for partnered people.

4.5.4 Social Desirability

Social Desirability results were scored from 10-20 and were split into two groups (high and

low) using a median of 15, as is shown in Figure 28. Those with scores over 15 had low social

desirability, whilst 15 and under had high social desirability.


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Square

Std. Error of

the Estimate

High 1 .667b .445 .437 .82646

Low 1 .743b .552 .544 .82836

a. Social desirability



Figure 29 shows the correlation between the predicted values and purchasing behaviour and R

Square is significantly stronger for those with low social desirability (.743; .552) than those

with high levels of social desirability (.667; .445). 54.4% of variance is accounted for by the

model for people with low social desirability and 43.7% for high social desirability.

Figures 30 and 31 demonstrate a difference in reported purchasing behaviours based on social

desirability. Success was insignificant for both high and low groups, but happiness,

recognition and recreation were additionally insignificant for those with high social

desirability levels. Fashion innovativeness showed the strongest correlation for both groups.

0

50

100

150

200

10 11 12 13 14 15 16 17 18 19 20

Frequency

Social Desireability

Figure 28 Social Desirability


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5.0 Findings and Recommendations

See 8.1 Appendix A and 8.2 Appendix B for the definitions of constructs and their relationship

with objectives.

5.1 Identifying the impact of individual characteristics on fashion clothing

purchase behaviour.

All constructs of individual characteristics are relevant to fashion purchasing behaviour,

except success. This is surprising as Hourigan and Bougoure (2012) stipulated materialism is

a strong driver of fashion purchasing behaviours. However, centrality had the second

strongest correlation with fashion purchasing behaviour, and happiness the fourth (both

elements of materialism), which supports Hourigan and Bougoure’s (2012) stipulation. The

significance of these two constructs also reinforces the theory of conspicuous consumption:

people may make purchases because they believe possessions to be central t the individual

and are essential to satisfaction. Because the results conflict with secondary research, more

research may need to be conducted to determine the extent materialism actually does impact

fashion purchasing behaviour.

Fashion Innovativeness had the strongest impact of fashion clothing purchase behaviour, and

confidence had the second. This indicates fashion purchasers seek to own trends before the

mass market does, and that they like to be confident in what they are wearing. This reinforces

Piamphongsant’s (2006) stipulation that individuality is an important factor of fashion

purchasing behaviour. It also reinforces the theory of planned behaviour (Cooke & Sheeran

2004), as fashion purchasing behaviour are governed by and can be predicted based on

personal attitudes (such as innovativeness and confidence) and social pressures surrounding

fashion innovativeness.

Results from Figure 14. Correlations Self Concept with Purchase Behaviour demonstrates the

more delicate someone perceives himself or herself to be, the higher their fashion purchasing

behaviour is, and the more rugged, the lower it is. In addition, fashion purchasing behaviour is


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higher in people who consider themselves to be excitable rather than calm. Whether a person

is tense or relaxed was found to have no impact on fashion purchasing behaviour.

These findings are important as they can impact how a marketer selects a target audience: a

target audience that considers themselves to be delicate or excitable would be more likely to

purchase fashion clothing than someone who perceived themselves to be rugged or calm., and

a campaign would be more successful if it focussed around its clothing being fashion

innovative.

5.2 identifying the impact of intrinsic motives on fashion clothing purchase

behaviour.

Figure 17. Coefficients found image expression and recreation impact similarly on fashion

purchasing behaviour. This means respondent’s seek to project a ‘good’ image and are

motivated to engage in fashion purchasing as a past time. It is interesting to note these two

constructs are not consistently significant when data is broken into s gender, relationship

status and age segments (see 5.4 Identifying any meaningful segments in the fashion clothing

market). For marketers, these findings could impact how they market fashion clothing

campaigns.

5.3 Identifying the impact of extrinsic motives on fashion clothing purchase behaviour. Figure 17 Coefficients demonstrates social approval and recognition both impact on fashion

purchasing behaviours. The findings that people are motivated to gain social approval through

clothing and attention from being fashionable indicates the theory of planned behaviour

(Cooke & Sheeran 2004), as it demonstrates fashion purchasing behaviours are governed by

and can be predicted based on social pressures. This is important for marketers of fashion

clothing as extrinsic motives are important to be identified when creating a campaign.

5.4 Identifying any meaningful market segments in the fashion clothing market.

T-tests and multiple regression found no meaningful market segment present in gender, which

conflicts with Hourigan and Bougoure’s (2012) stipulation gender is a driver of fashion


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clothing involvement. Whilst different clothing is marketed to males and females, campaigns

do not need to be segmented due to gender: a mass marketing approach applies.

A meaningful market segment was found to be present between generational cohorts. Fashion

innovativeness, confidence and social approval impacted all age groups, reinforcing that

people like to be confident in what they wear, ahead of trends, and gain social approval

through clothing (once again reinforcing the theory of planed behaviour (Cooke and Sheeran

2004)).

Based on the surveyed generation Y’s answers, recreation was the only additional value

showing a relationship for fashion purchasing behaviour. This implies generation Y is likely

to engage in fashion purchasing as a pastime. More research is needed, potentially

observational, to study what influences generation Y, as few factors were found to have

significance for this group.

The most values impacted on generation X: centrality, happiness, social approval, image

expression and recreation. These findings imply generation X seek to gain social approval

through clothing, be seen as projecting a ‘good’ image and engage in fashion purchasing as a

pastime, which indicates the theory of planned behaviour is relevant (Cooke & Sheeran

2004). Respondents in generation X also believed possessions and acquisitions are central to

the individual and are essential to satisfaction and wellbeing. This highlights that generation

X may be more materialistic than other age cohorts, implying the theory of conspicuous

consumption applies to this generation (Trigg 2001).

Multiple regression test indicated respondents from the baby boomers consider acquisitions to

be central to their self, seek to gain social approval through their clothing and want to be seen

as projecting a ‘good’ image.

T-tests and multiple regressions also found relationship status to be a meaningful market

segment. Once again, fashion innovativeness was a strong driver for both groups. Levels of

centrality were also similar, indicates both groups like to be ahead of the fashion pack and

acquisitions are important to them. Social approval and recreation had more impact on fashion

purchasing behaviour for singles than partnered people. This implies single respondents seek

to gain more social approval through clothing and engage in fashion purchasing as a pastime


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more than partnered people. In addition, single respondents indicated they based satisfaction

on their acquisitions, whereas this was an insignificant factor for partnered people. In

contrast, partnered respondents indicated their confidence in appearance, attention from being

fashionable and projection of a ‘good’ image impacted on their fashion purchasing

behaviours. This means that marketers could segment audiences based on relationship status.

5.5 Understanding how social desirability bias may influence the results of the research.

In order to gain an accurate understanding of results, it is important to gauge the extent social

desirability affects respondent’s answers, as well as the drivers (Zikmund et al. 2011, p.132).

Social desirability was found to affect the results of the research. Happiness, recognition and

recreation were insignificant for those with high social desirability levels, but not those with

low social desirability levels. This indicates findings surrounding these three values have been

impacted by social desirability and may not be accurate. Fashion innovativeness and

confidence weren’t affected by social desirability as they showed similar levels across both

groups, indicating findings around these values are accurate. Centrality and social approval

may also have been affected by social desirability bias as they were significantly stronger for

those with high levels of social desirability. Image expression had a far lower impact for

those with high levels of social desirability, meaning the impact of this value may have been

misrepresented to be perceived in a certain manner. Thus, it is recommended further

observational study be conducted into the drivers of fashion purchasing behaviours to

determine how respondents actually behave.

6.0 Limitations

Figure 4. Frequency of Ages demonstrates there was a large representation of respondents

aged eighteen to twenty-two years, and a small number of those aged twenty-seven to thirty-

one years. Whilst the frequency of the rest of the ages are relatively proportionate, this infers

the sample is not representative, which impacts on the accuracy and generalizability of results

(Zikmund et al. 2011, p.127). In addition to this, random sampling error may have occurred

through a statistical fluctuation due to chance variation (Zikmund et al. 2011. P.329). Issues


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with this could be improved by using a sampling frame, or by using probability sampling such

as simple random sampling (Zikmund et al. 2011, p.331-34).

Reliability of the data is also questionable because of the multiple researchers (Guest, 2012).

Data-processing error in the form of a mistake in the entering of data into the database may

have occurred (Zikmund et al. 2011, p.132). Interviewer cheating may also have occurred

where interviewers falsified questionnaires or filled in answers where they had been skipped

(Zikmund et al. 2011, p.133). Issues with this could be improved for future research by telling

interviewers a small number of respondents will be called back to check whether the survey

was conducted (Zikmund et al. 2011, p.133).


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7.0 References

AMSRO. (2013). The Market and Social Research Privacy Code. Retrieved April 6, 2013

from Association of Market and Social Research Organisation:

http://www.amsro.com.au/privacy/the-market-and-social-research-privacy-code

AMSRS. (2013). AMSRS Code of Professional Behaviour. Retrieved April 6, 2013 from

Australian Market and Social Research Society:

http://www.amsrs.com.au/documents/item/194

Cooke, R., & Sheeran, P. (2004). Moderation of Cognition Intention and Cognition-

Behaviour relations: A meta-analysis of properties of variables from the theory of

planned behaviour. British Journal of Social Psychology (43), 159-186.

Guest, G. (2012). Applied Thematic Analysis. Thousand Oaks, California: Sage

Publications.

Hourigan, Sally & Bougoure, Ursula-Sigrid (2012). Towards a Better Understanding of

Fashion Clothing Involvement. Australasian Marketing Journal. 20(2):127-135.

Retrieved from

http://gateway.library.qut.edu.au/login?url=http://search.proquest.com.ezp01.library.q

ut.edu.au/docview/1027770401?accountid=13380

Piamphonsant, T. (2006, July). A Cross-Cultural Study of Fashion Clothing Behaviours:

Specific Situations and In-Group Differences Among Career Women in Cosmopolitan

City Contexts. Retrieved April 6, 2013 from ABI/Inform Global:

http://search.proquest.com.ezp01.library.qut.edu.au/abiglobal/docview/304914326/13

D43299E7056CB8B74/3?accountid=13380

QUT. (2013). D/2.6 QUT Code of Conduct for Research. Retrieved April 5, 2013 from

Queensland University of Technology:

http://www.mopp.qut.edu.au/D/D_02_06.jsp#D_02_06.01.mdoc


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Smyth , J., Webb, M., & Oikawa, M. (2013). Self-report of cancer related behaviours .

Retrieved June 1, 2013 from National Cancer Institute :

http://dccps.cancer.gov/brp/constructs/self-report/

Trigg, A. (2001). Veblen, Bourdieu, and conspicuous consumption. Journal of Economic

Issues , 35 (1), 99-115.

Zikmund, W. G., Ward, S., Lowe, B., Winzar, H., & Babin, B. J. (2011). Marketing Reserach

(2nd ed.). Sydney: Cengage Learning.


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8.0 Appendices

8.1 Appendix A – Construct Definitions

Construct Definition

Social Approval This is how motivated the respondent is to gain social

approval through their clothing.

Recognition This is how much the person believes that they will gain

attention from being fashionable.

Image Expression This is how important it is to the respondent to be seen as

projecting a ‘good’ image.

Recreation This is how motivated the person is to engage in fashion

purchasing as a pastime.

Confidence in

Appearance

This is how confident an individual is in their general

appearance. It is possible that people with low confidence will

compensate by being more fashionable.

Fashion

Innovativeness

Innovativeness is the extent to which a person is more in tune

with fashion and more likely to adopt trends before the mass

market.

Materialism

(success, centrality,

happiness)

Success: the extent to which people tend to judge themselves

and others by the number and quality of possessions

accumulated.

Centrality: the extent to which possessions and acquisitions

are central to the individual.

Happiness: the belief that possessions and acquisitions are

essential to ones satisfaction and well-being in life.

Self Concept These are descriptions of a person’s image. It is possible that

some people have a self image that leads them to be more

fashion consuming than other images.

Social Desirability A potential bias in data.


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8.2 Appendix B – How Constructs Relate to Objectives

Objective Constructs

Objective (i) individual characteristics • Confidence in appearance

• Innovativeness

• Materialism

• Self-concept

Objective (ii) intrinsic motives • Image expression

• Recreation

Objective (iii) extrinsic motives • Social approval

• Recognition

Objective (iv) segmentation • Gender

• Generational cohort

• Relationship status

• Employment status

• Residential location

• Nationality

• Education

• Shopping preference

• Living situation

• Transport usage

Objective (v) social desirability • Social desirability


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8.3 Appendix C – Surveys

fashion(clothing(purchase(behaviours(( - … · fashion(clothing(purchase(behaviours((amb201 ......

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