The Customer Attitude Towards Buying Fashion Online Marketing Essay

Published Date: 23 Mar 2015

Framing an appropriate research methodology in order to conduct a conclusive research is the most important ingredient of any research paper. Various research papers have been reviewed to gather information about the research designs, data collection methods, data analysis methods, sampling techniques etc. Therefore, this section of the chapter on research methodology talks about the existing researches which have been conducted in the field on customer attitude towards online fashion retailing.

A study on consumer choice towards Online Shopping in Malaysia conducted has been done to identify factors influencing consumers towards online shopping. The researcher has used convenience sampling for 100 respondents through a structured likert scale type questionnaire .Reliability was also tested using Cronbach's alpha coefficient. The hypothesis revolved around the independent factors affecting online shopping attitude. Following this, correlation analysis and regression analysis was conducted for hypothesis testing. Ultimately this research concludes that internet knowledge and website quality are the highest factors that contribute towards online shopping attitude. (Hassan and Abdullah, 2010) A different research conducted in Malaysia by Jusoh and Ling (2013) also investigates the impact of socio-demographic variables and factors affecting customer online shopping attitude. A similar questionnaire survey through convenience sampling of 100 respondents was used here wherein One-way ANOVA test and Pearson Correlation test was used to test the relation between dependent variable(customer attitude) and independent variables like age ,income, education, and factors influencing customer attitude.

Another research conducted in Bangkok, Thailand revolves around similar project objectives. A Descriptive research design with Questionnaire survey to gather primary data from 385 respondents has been applied to this research. Various statistical tools for hypothesis testing were applied like factors influencing customer attitude were tested using multiple linear regression analysis, gender influences on consumer attitude used independent t-test and difference in attitude towards online shopping when segmented by age and education used ANOVA method. (Mengli, 2010) 

Consequently a study on Modeling Consumer Trust in Internet Shopping based on the Standard Learning Hierarchy: A Structural Approach by (FJ Martínez-López, 2004) in Spain was also conducted over a non-probability sampling procedure for sample unit of 529 Spanish students who were frequent internet users. In this study firstly, SPSS software was used in the reliability assessment.

Research paper titled "Consumer Attitudes towards Online Shopping in Jordan: Opportunities and Challenges" by Alsmadi, 2002 uses convenience sampling of 500 self-administered likert scale based questionnaires. Cronbach Alpha test of reliability correlation along with other analytical tests such as descriptive and frequency analysis and One-Way ANOVA were used to test the hypothesis statements. The findings reveal that customers weigh security as a crucial factor in making purchases over the web. Also, the Income and positive customer attitude towards online shopping varies directly. (Alsmadi, 2002) 

The views of 900 respondents through a likert scale based questionnaire were used in another research paper titled "Attitudes, Preferences and Profile of Online Buyers in India: Changing Trends" in which the 3 hypothesis revolved around gender ,age and website attributes being an influencing factor towards customers online shopping attitude. In this study statistical approach through Chi-square, standard deviation, mean and factor analysis have been applied to identify the Internet usage trends and factors affecting E-shopping in India.

Another paper by Lodorfos,.et al. (2013) talks about consumer behaviour in the online commodities market. This study implemented a quantitative methodological approach by surveying 211 consumers with prior online shopping experience .A pilot survey on a few professionals and students (approx. 17) was done before finalising the questionnaire. Firstly, Cronbach's alpha test for reliability was used to judge the reliability of the survey. This value was found out to be greater than 0.70 which is a proof of internal consistency. Various analytical tools were used on SPSS software to draw conclusive results ranging from exploratory factor analysis, correlation matrix, factor analysis, independent t-test, and regression analysis in order to test the hypothesis.

Researcher Ha and Stoel, (2008) in his research paper titled "Consumer e-shopping acceptance: Antecedents in a technology acceptance model" also uses a survey construct measures to judge consumers acceptance towards online shopping. The study used a sample size of 298 college students through convenience sampling. The study laid emphasis on apparel e-shopping identifying 4 important variables such as website dynamics or layout, security, atmospheric and customer experience. The questionnaire consisted of demographic questions, shopping experience, TAM Variables and quality of online shopping. Ultimately, data analysis tests like reliability analysis, exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were used in this study. A separate study by Kim et,al. (2009) on attitude formation in TAM model had also been carried out through survey research. A sample of 101 respondents consisting of MIS,database management course students were used for this research. Following the pattern, similar data analysis tests like reliability test and Confirmatory factor analysis (CFA) was used in this as well.

Another study by Sultan (2011) has been done to identify factors affecting consumers' online shopping attitude in Sweden, where online shopping has acquired a very prominent position in almost every persons' lifestyle. In order to narrow the scope of this study, 100 students from Gotland University were identified as valid respondents through convenience sampling. Finally, about 3 factors responsible for affecting consumers' attitude towards online shopping were identified through reliability tests, factor analysis and correlation analysis.

PART 2

Section 2 of the Research Methodology chapter focuses on the research design, sampling technique and data collection methods formulated in order to complete this research. Therefore, on the basis of the inputs gathered through various researches conducted worldwide on the relationship between customer attitude and online fashion retailing the following hypothesis have been drawn:-

RESEARCH OBJECTIVES

1.To study customer attitude and acceptance of online shopping medium for apparel towards buying fashion online in Delhi /NCR. On the basis of secondary data through research papers, customer's belonging to the age group of 18-45 have been identified as the valid prospects for this study.

2.To analyze the factors influencing Indian customers attitude to shop for apparel Online.

3.To investigate how socio-demographic (age, sex, income and education) affect consumers' attitude towards online shopping

4. To investigate and identify best practices of online fashion retailers models followed by successful domestic and International retailers.

RESEARCH HYPOTHESIS

H.1 There is a relationship between age and the customer attitude towards buying fashion online.

H.2 There are differences between male and female consumer attitudes towards online shopping.

H.3 There are difference in attitude towards buying fashion online, when segmented by income and education.

H.4 There is a positive relation between web design aspects and consumer attitude towards buying fashion online.

H.5. Online security has a significant positive impact on the consumers' attitude to adopt online purchase.

H.6 The greater the usefulness offered by in-home shopping (Convenience & Customer Service), the better the consumer's attitude towards buying fashion merchandise online.

H.7 Better product assortment available through online shopping positively influences customers' attitude.

H.8 The is a significant relation between the perceived price or deal offered by an e-retailer, and the customers' attitude to buy online.

RESEARCH DESIGN AND DATA COLLECTION METHOD

Research design is a plan for conducting a research. It specifies the research method, data collection methods, measurement tools, the end analysis and findings generated from a research paper.(Gray, 2004)In simple language, how the research has been carried about? What questions have been addressed? Who has been asked? What inference has been gathered from the research?

RESEARCH METHOD

This research paper tries to explore or unveil the customers' attitude towards buying fashion online in Delhi/NCR. It fundamentally revolves around the impact of socio-demographic factors and the other independent variables affecting a customers' attitude to eventually shop online or not. According to Amin (2012) the purpose of a descriptive research is to derive the answers to who, where, what, when, how or depicting the current state of affairs. Therefore, this study follows a descriptive research design. Narrowing it down further, both quantitative and qualitative research approaches can be adopted for developing a research paper. Woodhouse, mentions that quantitative research helps to obtain statistically reliable and conclusive data findings. Also, Saunders (2009) cited in Sultan (2011) explains that in comparison qualitative research techniques are difficult and require experienced and experimental researchers and psychological to interpret the results whereas quantitative methods are much faster to obtain accurate results. This paper has been done for academic purpose to acquire the Degree of Masters in Fashion Marketing. So, keeping the pros and cons in mind and adhering to the time provided quantitative approach has been adopted.

DATA COLLECTION

Data can be collected through Primary research method or Secondary Research method. Primary research method refers to collecting first hand information in the form of questionnaire surveys, interviews, case studies, focus groups etc. It can be termed as raw data which has been collected primarily for a specific research work .

On the other hand Secondary research method refers to reading about literature available from different resources or research works conducted by different researchers worldwide. In the book titled "Doing Research in the Real World" by Gray,(2004) the author mentions that a particular checklist has to be followed for the use of secondary research method. Example: Who wrote the document? Why was it made? What objectives does it fulfil? Was the research work genuine or not?

Consequently, this study about customer attitude on buying fashion online would be carried forward through primary research method by distribution of survey questionnaires to analyze the situation in Delhi/NCR. The questionnaire would help to identify the factors responsible for influencing the Indian customers' to shop for apparel online.

SAMPLING TECHNIQUE

Fundamentally sampling refers to deciding a part of a population or a few representative persons which can be said to represent the whole population. The idea behind this is to choose objects which can closely be identified, to match the characteristics of the entire population. The principle benefit of deciding a sample is to ensure speedy data collection, greater response, lesser cost incurred and less time requirement. In real world it also becomes next to impossible to attain hundred percent enumerations. This type of sampling technique yields great accuracy but it requires great amount of time, money and energy. (Fao.org, A Statistical Manual For Forestry Research ; n.d.)

In general two types of sampling techniques have been formulated namely probability sampling technique and non-probability sampling technique. In the former technique, the actual chances of selecting or choosing a subject (consumer, part of the population) is known. When sampling is done to ensure that each and every unit of the population gets selected through conducting a strict selection procedure, it is known as probability sampling On the other hand, in Non-probability sampling technique, the researcher is unable to determine the probability or likelihood of choosing a subject.(Gray, 2004)

Probability sampling techniques (Random Sampling) are based on various methods namely simple random sampling, stratified random sampling, cluster sampling and stage sampling. Similarly non probability or non-random sampling techniques can be classified as purposive sampling, quota sampling, convenience or volunteer sampling and snowball sampling. (Fao.org, A Statistical Manual For Forestry Research ; n.d.)

According to Bell & Bryman (2007), The most popular sampling technique used by past researcher to conduct a similar type of a research in the online shopping category has been observed as convenience sampling. Convenience Sampling is mostly used by researchers since it provides decent ease of use and understanding. The only problem in this type of sampling technique is practically generalizing or classifying the results on the basis of a particular sample selected. With the perspective of time limitation and availability of resources many researchers still prefer to adopt convenience sampling technique. (Sultan, 2011) Furthermore, Lin and Lu,2000 (cited in FJ Martínez-López, 2004) elaborate that the data acquired through convenience or purposive sampling can only be called reliable if the sample population selected is ideal to draw findings for the entire population.

Therefore, Non probability sampling technique has been considered as appropriate to draw samples from the sampling frame and convenience sampling method has been utilized.

SAMPLE DESIGN

Sample design refers to the method for selecting a sample unit. Mixed methods have been used to conduct this research. A self -administered questionnaire was distributed through both online and offline methods (in person or distribution by hand). A survey on "Customer Attitude towards buying fashion Online" was designed on www.surveymonkey.com to gather responses from consumers in Delhi/NCR.

With the help of Surveymonkey a web link was generated which was used ultimately to collect data through e-mails and social networking sites, most importantly Facebook. About 9 questionnaires, was also hand-collected from students cafeteria at Pearl Academy of Fashion. Also, enough time was provided to each person for filling the questionnaire to avoid any missing vales.

SAMPLE SIZE

A sample size of 150 respondents has been used in order to complete this research. Specifically keeping the research objectives and hypothesis in mind, the consumers situated in Delhi/NCR , belonging to the age group of 18-45 having prior online shopping experience have been chosen. Prior internet experience becomes a prerequisite for the respondents, as those consumers can exactly identify and help to determine the most influential factors affecting customer attitude towards buying fashion online.

QUESTIONNAIRE DESIGN

A self-administered questionnaire was designed to meet the requirements of the research objectives. Previous researcher's findings and literature on customer attitude towards online shopping had been studied to validate the questions to be asked in the survey. Drawing inference from the work of past researchers a structured questionnaire comprising of 25 questions was prepared to conduct the research in Delhi/NCR. The questionnaire has been divided into two main parts .The first part has questions about the demographic profile of the respondents. The second part revolves around questions pertaining to the factors that influence consumers to shop for fashion online.

PART A:

This part includes questions pertaining to age,gender,education,average income ,online shopping a[pattern and amount usually spent while purchasing fashion online.These 6 questions have been designed to gather personal information about the respondents.This would help to determine the demographics of the consumers situated in Delhi/NCR who shop for fashion, over the web.

PART B:

The second part contains questions relating to factors that influence consumers' attitude to buy fashion online. There are 18 questions in total containing 3 questions for each factor. Six factors which have been considered are Convenience value, Website Design or Quality, price and deals, product assortment or categories, level of security and customer service. These questions were framed as statements, on which the respondents had to provide their ratings. The five-point rating scale was used with options ranging from 1= Strongly agree, 2= Agree, 3= Uncertain, 4= Disagree and 5= Strongly Disagree.

VALADITY & RELIABILITY

According to Fischer, 2007 cited in Sultan, M. (2011) "Validity of the questionnaire" refers to designing the statements or the questions in a manner that they help to reveal or discover the answers to the previously framed research objectives. The questionnaire designed on Customer Attitude towards buying Fashion Online draws inspiration from previous literature and researches conducted in this area. The questionnaire has been constructed with 5 point Likert scale ranging from 1 (Strongly Agree), 3 (Uncertain) to 5 (Strongly Disagree).The statements used for testing consumers' attitude are valid statements ,which have been used in some of the previously done research work as well. Also, to maintain uniformity and avoidance of the risk that a respondent terminates the questionnaire survey, it has only been distributed to persons with previous online shopping experience.

PRE-TEST

Firstly a pre-test was done to know the reliability of the questionnaire with 113 responses. The Cronbach's alpha scores was calculated for testing the reliability .Its value came out to 0.764 which is greater than 0.7 ,therefore the questionnaire is highly reliable.

ACTUAL RELIABILITY TESTING

On the basis of the pre-test, further data collection was done to get responses from at least 150 respondents. Finally the data was collected through www.surveymonkey.com by sending web links on e-mail ids and social networking websites like facebook. Also, professional practice forms an integral part of this thesis; therefore it has also been integrated into this project. The professional practice has been done with Jabong.com an online fashion e-tailer. About 30 respondents (out of 150) are the ones which have prior shopping experience with www.Jabong.com. This has been only made possible because all the respondents were asked personally about their prior shopping experience and the websites they have previously shopped from, for buying fashion products specifically. Consequently, the research findings would be presented to their company so that they can be utilised for knowing the customers attitude towards buying fashion online in Delhi/NCR and follow the thumb rule practice to attract every online shoppers attention.

The questionnaire consisted of close-ended questions in English. A total of 150 usable responses for collected for analysing. The data has been analysed using "Statistical Package for the Social Sciences" (SPSS for Windows - Version 20). The Cronbach's alpha score for all variables is calculated to know about the reliability of the data collection tool i.e. the questionnaire. Alpha Coefficient ranges from 0 to 1 ,which can be used to depict the reliability of the statements and the data collected through the questionnaire. Higher score denotes higher reliability. For the purpose of clear judgement, Nunnaly (1978) cited in Santos, J.R.A. (1999) indicates that any value greater than 0.5 or less than 1 (>0.5=<1) is "acceptable" and any value greater than 0.7 or less than 1 (>0.7=<1) denoted that the questionnaire is "highly reliable & acceptable".

Subsequently, Cronbach's Alpha coefficient for the questionnaire was calculated. The value came out to 0.771 which shows that the questionnaire is highly reliable.

N

%

Cases

Valid

150

100.0

Excluded

0

.0

Total

150

100.0

Reliability Statistics

Cronbach's Alpha

N of Items

.771

25

The statements used to test each factor influencing consumers' attitude to buy fashion online have also been tested individually for reliability. The table below depicts the reliability of the study.

RELIABILITY OF THE STUDY

DIMENSION:INDEPENDENT VARIABLE

NUMBER OF STATEMENTS

CRONBACH'S ALPHA

Convenience

3

.588

Website Quality & Design

3

.614

Price/Deals

3

.641

Product Assortment/Category

3

.670

Security/Privacy

3

.538

Customer Service

3

.626

CHAPTER 4.DATA ANALYSIS

DEMOGRAPHIC PROFILE OF THE RESPONDENTS

The demographic profile of the respondents was initially studied and percentages were calculated. The female respondents slightly outnumbered the male respondents. There were 54% female respondents compared to 47% male respondents. Majority of the respondents belonged to the age group of 18-24 years(84% of the total).10% are in the range of 25-31 years old,3% are 32-38 years old and 35% are 39-45 years old. Most of the respondents (57%) are graduates.23% of the total respondents hold a Matser's degree and very few (3%) of the total respondents are Phd. Also, about 16% of them are just high school graduates. More than half of the respondents (57%) have an average annual income below Rs. 5,00,000 , 26% have an Income between Rs. 5,00,000 -Rs. 15,00,000, 9% have an Income between Rs. 15,00,000 -Rs. 25,00,000 and 8% have an income above Rs. 25,00,000.The maximum frequency of shopping was observed to be the once a month by about 46% of the respondents and most of the respondents felt that the amount spent for making a fashion purchase over the web was between Rs. 1000 - Rs. 2000 (31%) or between Rs. 2000-Rs. 3000 (28%).

Age

Frequency

%

Gender

Frequency

%

Education

Frequency

%

18-24

126

84

Female

80

53

High School or Below

16%

24

25-31

14

10

Male

40

47

Bachelor Degree

57%

85

32-38

5

3

Masters Degree

23%

35

39-45

5

3

Doctoral Degree

4%

6

TOTAL

150

100

TOTAL

150

100

TOTAL

150

100

Income

Frequency

%

Frequency of shopping

Frequency

%

Amount Spent

Frequency

%

Below 5 Lacs

85

57

Once a week

9

6

Less than 1,000

28

19

5 Lacs-15 Lacs

39

26

Once a Month

69

46

1,000-2,000

47

31

15 Lacs- 25 Lacs

14

9

Once in 6 Months

49

33

2,000-3,000

42

28

25 Lacs & Above

12

8

Once in a Month

23

15

3,000-4,000

33

22

TOTAL

150

100

TOTAL

150

100

TOTAL

150

100

HYPOTHESIS TESTING

H.1 There is a relationship between age and the customer attitude towards buying fashion online.

Researchers in different countries have tested this relationship through the use of questionnaire surveys and observed that a relation does exist. With rise in the age, the interest in trying new technology or new formats also starts dying. On the other hand people belonging to the youth segment are friendlier to new technology. Subsequently, most of the online shoppers tend to belong to the younger strata compared to older generations.

In order to test the relation between age and customers' attitude towards buying fashion online, Pearson's Correlation Coefficient would be calculated. The questionnaire included three Customer Attitude Statements like frequency of buying online, amount spent while buying fashion online and Preference of buying Online over Offline.

The data analysis shows that the Pearson correlation coefficient between age and frequency of online shopping is r=-0.40 (p=0.624>0.05).The questionnaire had depicted the options for age in a rising manner and frequency of shopping in a reducing manner, therefore a negative value in this instance shows a moderately positive correlation between age and frequency of online shopping. Therefore, as the age increases ,the frequency of online shopping also increases.

The Pearson's Correlation Coefficient between Age and amount spent while buying fashion online is r= 0.002 (p= .981>0.05) (moderately positive correlation). Therefore, we conclude that as age increases the amount spent while buying fashion online also increases. However, this finding is not statistically significant.

The correlation value between age and preference of online shopping over offline shopping is r=-0.099 where p=0.227>0.05. This shows that the preference for Online shopping over offline shopping rises proportionately, as age increases.(Moderately Positive Correlation) However, even this finding is not statistically significant.

Hence, H.1. has been accepted. This shows that there is a relationship between age and the customer attitude towards buying fashion online.

Correlations

Statements

What is your age?

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

I spend _______ while buying fashion apparel online.(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

What is your age?

(1= 18-24;4=39-49)

Pearson Correlation

1

-.040

.002

-.099

Sig. (2-tailed)

.624

.981

.227

N

150

150

150

150

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

H.2 There are differences between male and female consumer attitudes towards online shopping.

One-way ANOVA was utilized to examine the differences in consumers' attitude towards buying fashion online amongst the male and female buyers. The result of this analysis has been summarized in table below. From the table given below, the research finding showed that there was no significant difference in attitude towards online shopping amongst both the genders.

On an average women prefer online shopping once in six months (Mean= 2.68) compared to men who prefer once a month (2.46). However, there is no significant difference between male and female consumers' attitude towards online shopping and their frequency of shopping, as F(3,146)= 2.651012 and p=0.106 (p>0.05).

On a comparison, men spend between Rs. 2000- Rs. 3000 (2.64) while making an online purchase and women spend slightly lesser between Rs. 1000-Rs. 2000 (2.44).But this difference is not statistically significant. There is no significant difference between male and female consumer attitudes towards online shopping and the amount they spend, as F(3,146)= 1.477012 and p=0.226 (p>0.05).

On an average both men and women are uncertain about their preference for Online shopping over Offline shopping. Preference of online shopping amongst men and women also does not bear any significant differences as, F(3,146)= =3.683891 and p=0.057 (p>0.05).

Hence, H.2.has been rejected. This showed that the gender of the respondents do not have effect on consumers‟ attitude to make e-commerce purchases through online shopping.

Statements

N

Mean

F

Significance

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

Female

80

2.68

2.651012

0.106

Male

70

2.46

Total

150

2.57

I spend _______ while buying fashion apparel online.

(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

Female

80

2.44

1.477012

0.226

Male

70

2.64

Total

150

2.53

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

Female

80

3.03

3.683891

.057

Male

70

2.73

Total

150

2.89

H.3 There are differences in attitude towards buying fashion online, when segmented by income and education.

Past researchers have conducted studies worldwide to identify the relation between the socio-demographics like income and education of a customer and its likely impact on his/her customer attitude. One-way ANOVA was utilized to examine the differences in attitude towards online shopping among different income groups. The result of this analysis was summarized in the table given below. From the table given below, the research finding showed that:-

The mean value of frequency of buying fashion over the web lies between 2 and 3,(Total mean = 2.57) i.e., online shopping is done mostly once in 6 months across consumers belonging to different income groups. The frequency of online shopping doesn't vary typically with the income of the consumer as the as F(3,146)= 2.070720 and p=0.106 (p>0.05).

A significant difference in attitude towards online fashion shopping among different income groups has been observed as, F(3,146)= 5.834003 and p=0.000860 (p<0.05).A person earning an average monthly income below Rs. 5,00,000 prefers spending Rs. 1000 - Rs. 2000 while a person earning 25,00,000 and above is most likely to spend Rs.3000 -Rs. 4000 while making an online purchase. Therefore, higher the consumers' income, higher is his/her spending power.

No difference in the consumer's preference for online shopping over offline shopping has been observed as, F(3,146)= 1.709397 and p=0.167 (p>0.05).

Statements

N

Mean

F

Significance

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

Below 5,00,000

85

2.68

2.070720

0.106643

5,00,000-10,00,000

39

2.51

15,00,000-25,00,000

14

2.50

25,00,000 and above

12

2.08

Total

150

2.57

I spend _______ while buying fashion apparel online.

(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

Below 5,00,000

85

2.28

5.834003

0.000860

5,00,000-10,00,000

39

2.77

15,00,000-25,00,000

14

2.64

25,00,000 and above

12

3.42

Total

150

2.53

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

Below 5,00,000

85

3.00

1.709397

0.167646

5,00,000-10,00,000

39

2.87

15,00,000-25,00,000

14

2.64

25,00,000 and above

12

2.42

Total

150

2.89

One-way ANOVA was utilized to examine the differences in attitude towards online shopping among consumers with different levels of education. The result of this analysis has been summarised in the table given below.

The mean value of frequency of buying fashion online lies between 2 and 3 (Total mean 2.57) which means that online shopping is mostly done once a month or once in 6 months. The frequency of online shopping also doesn't vary with the education level of the consumers as the F(3,146)= 0.409421 where p= 0.746464. Both, a high school graduate or a person holding a doctoral degree have the same shopping frequency.

The F(3,146) value between amount spent and education level acquired is given by 1.526000 where, p= 0.210244>0.05. Therefore, it can be said that the amount spent on buying fashion online across consumers having acquired different educational qualifications doesn't vary. In other words, the educational qualification does not influence the consumers attitude towards the amount spent.

The consumers' preference for online shopping over offline shopping lies between 2.5 and 3 (Total average 2.89).The F(3,146) value is given by 0.113861 where, p=0.951877>0.05)Therefore, it can be said that most of the consumers are uncertain about this statement, irrespective of their educational qualification.

The research findings show that there the attitude of consumers who buy fashion online is not influenced by their level of education. In other words, there is no significant difference in attitude of consumers on the basis of their education. But the level of income does play an important role in influencing the consumers' attitude towards buying fashion online. A significant difference in the spending power on the basis of income level has been observed as per the ANNOA test. Therefore, the hypothesis has been split into two parts to arrive at a conclusion:-

H.1. (a)There are differences in attitude towards buying fashion online, when segmented by income : Accepted

H.3.(b)There are differences in attitude towards buying fashion online, when segmented by education : Rejected

Statements

N

Mean

F

Significance

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

High School degree or below

24

2.71

0.409421

0.746464

Bachelor degree

85

2.52

Masters Degree

35

2.63

Doctoral Degree

6

2.50

Total

150

2.57

I spend _______ while buying fashion apparel online.

(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

High School degree or below

24

2.79

1.526000

0.210244

Bachelor degree

85

2.45

Masters Degree

35

2.46

Doctoral Degree

6

3.17

Total

150

2.53

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

High School degree or below

24

2.79

0.113861

0.951877

Bachelor degree

85

2.92

Masters Degree

35

2.89

Doctoral Degree

6

2.83

Total

150

2.89

H.4 There is a positive relation between web design aspects and consumer attitude towards buying fashion online.

Correlation analysis was utilized to understand the relation between web design aspects and the consumer attitude towards buying fashion online. Three statements pertaining to the website design aspects and three statements pertaining to customer attitude were put into the questionnaire. . The result of this analysis was summarized in the table given below. From the table given below, the research finding showed that:-

The consumers who shop once a year or once in six months feel that the website design helps them to search easily for the products, but those who shop weekly or once a month don't agree much on the statement that website design promotes easy search. The relation between the two variables that "web site design is responsible for easy search" and "how many times do consumers shop online -frequency" can be seen from the Pearson's correlation coefficient i.e. ,r= -0.098 (p=0.234). The conclusion of this relationship is that as frequency of online shopping increases, the belief that website design helps in searching products easily, decreases. So there is a moderately negative correlation between these two variables, however not statistically significant.

Pearson's correlation coefficient, r=0.015 (p=.854>0.05) signifies moderately positive correlation depicting that those consumers who shop online more frequently feel that an attractive website encourages them to shop online.

Pearson's correlation coefficient, r=-0.065 (p=.431>0.05) signifies moderately negative correlation depicting that those who shop online occasionally like once in 6 months or once in a year prefer to shop from a website showing good pictures and structured information, compared to those who are frequent online shoppers.

The consumers who spend more amount for buying fashion online strongly feel that website design promotes easy search while online shopping .The correlation value here is r=-0.047 (p=0.567>0.05), which signifies a moderately positive correlation.

The Pearson's correlation value of r=-0.063 also signifies moderately positive correlation. The questionnaire coding presented the amount spent on shopping in an increasing manner and the likert scale for website attribute was presented in a decreasing manner i.e, from strongly agree to strongly disagree. Therefore a negative r value in this case would mean a positive correlation. It has been corrected and made positive for easy reading. In other words, the consumers who splurge more on online fashion shopping feel that an attractive website layout encourages them to shop.

On the contrary, some consumers who spend more on buying fashion online felt that better picture and structured information was not the criteria they look for while shopping online. This has been depicted by the r value = 0.028 where, p=0.737 > 0.05.(moderately negative correlation).

Consumers who prefer online shopping compared to offline shopping agreed that website design helps in easy search. The Pearson's coefficient highlights this moderately positive correlation as r=0.183.Also this value is statistically significant because the significance value is p=0.025 (p<0.05).Similarly, consumers who prefer online shopping compared to offline shopping also agreed that attractive website layout encourages them to shop online. Here, r=0.140 and p=0.089>0.05 which represents a moderately positive correlation.

The consumers who prefer online shopping compared to offline also strongly felt that they preferred buying from a website which has better pictures and ease of navigation as the correlation value shows a moderately positive correlation where r= 0.109 (p=0.184>0.05).

It was hypothesized that there is a positive correlation between the web design aspects and the consumer attitude towards buying fashion online. But, based on the correlation between the two most relevant statements "I prefer Online shopping to Offline Shopping" and "While shopping online, I prefer to purchase from a website that has shows good pictures, structured information and easy navigation" the hypothesis has been rejected. Although the r value=0.109 depicts a positive correlation but it is not statistically significant as p=0.184>0.05 .Hence, the hypothesis is rejected.

Statements

The Website Design helps me in searching the products easily

(1= SA ; 5= S D)

I feel that an attractive website encourages me to shop online

(1= SA ; 5= S D)

While shopping online, I prefer to purchase from a website that has shows good pictures, structured information and easy navigation.

(1= SA ; 5= S D)

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

Pearson Correlation

-.098

.015

-.065

Sig. (2-tailed)

.234

.854

.431

N

150

150

150

I spend _______ while buying fashion apparel online.

(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

Pearson Correlation

-.047

-.063

.028

Sig. (2-tailed)

.567

.443

.737

N

150

150

150

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

Pearson Correlation

.183*

.140

.109

Sig. (2-tailed)

.025

.089

.184

N

150

150

150

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

H.5. Online security has a significant positive impact on the consumers' attitude to adopt online purchase.

Correlation analysis was utilized to understand the relationship between security concerns and the consumer attitude towards buying fashion online. Three statements pertaining to the security concerns and three statements pertaining to customer attitude were put into the questionnaire. The result of this analysis was summarized in the table given below.

The consumers who shop online more frequently like weekly or once a month agree to the statement that they feel secure and safe while shopping online, as Pearson's correlation value is r=0.198 showing a moderately positive correlation between the two variables. Also this correlation in statistically significant as p=0.015 <0.05.

There is a moderately negative correlation between the frequency of online shopping and concern for giving away credit card details. So, the consumers who shop online frequently are less concerned about giving away their credit card details while online shopping. Likewise, the consumers who shop online occasionally fear giving away their credit cards details and personal information. This correlation is denoted by r= -0.067 where p=0.419>0.05.

The consumers who shop online frequently prefer to shop online from a trustworthy and a popular seller as r= 0.183 where p=0.025<0.05.Therefor this Pearson's correlation coefficient is also statistically significant.

There is a moderately positive correlation between the spending power and the consumer's attitude that they feel safe and secure while online shopping. In other words, the consumers who feel safe while online shopping have a tendency to spend more. This is depicted by the r value = -0.137 (p= 0.095>0.05).

The correlation value of 0.011(where, p=0.893>0.05) signifies a moderately negative correlation. The consumers who spend more on online shopping are less concerned about giving their private information to online companies. On the other hand, the consumers who spend money in lesser denominations while online shopping tend to be more concerned about giving away their private information.

The correlation between the spending power and preference to shop from a trustworthy seller is given by r=-0.117 (p= .155>0.05; moderately positive correlation).Therefore, the consumers who spend more amount while online shopping prefer to shop only from a trustworthy and popular seller.

A significant positive correlation was observed between security of online shopping and consumers' preference for online shopping over offline shopping. This is given by r= 0.284 where p= 0.000<0.005.Therefore this correlation is statistically significant. The consumer's who feel that online shopping is safe and secure; prefer online shopping over offline shopping.

Interestingly, the consumers who prefer online shopping to offline shopping also stated that they are actually concerned about giving their private information and credit card details to online companies. In other words, there is a positive correlation between the preference for buying fashion online and concern about giving credit card details. This has been given by r value= 0.083 where p=0.310>0.05.However, this is not statistically significant.

Another significant positive relation was observed between the consumers' preference for online shopping and their choice to shop online only from a trustworthy and popular seller as the Pearson's correlation coefficient is given by 0.174 and p=0.033<0.05.Therefore, this value is value statistically significant.

It was hypothesized that there is a positive correlation between the online security and the consumer attitude towards buying fashion online. Therefore, based on the correlation between the two most relevant statements "I prefer online shopping to Offline Shopping" and "I feel safe and secure while shopping online" the hypothesis has been accepted. The Pearson's correlation value, r= 0.284 depicts a moderately positive correlation. Also, the significance value is p=0.025<0.05 i.e, the value is statistically significant.

 Statements

I feel safe and secure while shopping online

(1= SA ; 5= S D)

I am concerned about giving private information and credit card details to online companies

(1= SA ; 5= S D)

I like to shop online only from a trustworthy and popular seller

(1= SA ; 5= S D)

I Shop Online ________.

(1=Weekly ; 2= Once a Month ; 3=Once in 6 Months ; 4= Once in a Year)

Pearson Correlation

.198*

-.067

.183*

Sig. (2-tailed)

.015

.419

.025

N

150

150

150

I spend _______ while buying fashion apparel online.

(1= Upto Rs. 1000 ; 2= Rs.1000-Rs.2000 ; 3= Rs.2000-Rs.3000 ; 4=Rs. 3000-Rs.4000)

Pearson Correlation

-.137

.011

-.117

Sig. (2-tailed)

.095

.893

.155

N

150

150

150

I prefer Online shopping to Offline Shopping

(1= SA ; 5= S D)

Pearson Correlation

.284**

.083

.174*

Sig. (2-tailed)

.000

.310

.033

N

150

150

150

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).