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Retail business is one of the largest businesses in terms of revenue generated and certainly the largest business in terms of number of participants. We all are retail buyers and buy different merchandize to satiate our needs and aspirations. Though we all indulge in shopping, there is a special relationship between shopping and woman. Whenever we talk about shopping; the perception is that women shop more than men. There is a reason for this perception; this is because inside a typical departmental store or that matter inside any shop one finds women outnumber men. The most desirable demand of a wife is that she should be taken by her husband for shopping or and this is the most irritating for a husband!
There may be some element of truth in the perception that woman do more shopping than men. This is because a woman is a homemaker as well and therefore, she does shopping not only for herself but for her family members husband, son, daughter, in laws etc. as well and therefore, there should be no surprise that shopping becomes an integral part of her personality and she keeps talking about shopping more often than what a man would like. While for a woman shopping is something very important, because, she does a lot of it and the in search of value of money proposition she has to think and talk more about shopping; for a man shopping is something which is to be done and not to be talked as for them there are more important issues to think and talk about.
But here comes the difference, just because unlike woman, men do not like to spend more time on shopping and also not to talk much about it, can the shopping behavior of men can be disregarded. Certainly not because despite spending less time on shopping and discussing the same men are reported to be on higher side when it comes to the amount spent on shopping. Laura Sullivan (2009) reported that men spend an average amount of $701 on audio and visual equipments much while woman spend just $536.
It is very important for retailers to understand the behavior of males as compared to females while shopping, so that they can devise an appropriate sales strategy to increase their business revenue and profit. Precisely because of this reason, many researchers have conducted research on different aspects of behavior of different sexes about shopping.
A study by www.dirctional.com shows that men as well love to do shopping of fashion items. This study is focused on shopping behavior of men about fashion items. From the findings of this study it will be incorrect to assume that men do not indulge in shopping, they do indulge, but whether they indulge in the same manner or in a different manner is the subject of this study.
An study reported at knowledge@wharton entitled Men Buy, Woman Shop: The Sexes Have Different Priorities When Walking Down the Aisles have presented a report of the shopping behavior of the two sexes. However, this analysis is not in depth and is lacking the details.
Based on the review of the literature, it appears that there is not much work reported in literature on the differences in the shopping behavior of the two sexes and therefore, a detailed quantitative work has been carried out and the same is reported in this paper.
Hypothesis that I intend to test in this experimental research is
Women like to browse while men like to get what they need and leave the store .
Methods
In any quantitative research it is very important to first ask the question What I intend to measure? . This is important because the answer(s) of this question determines the variables for which data need to be collected, the instrument for the data collection whether it will be equipments and hardware as in case of scientific research, or it will be a questionnaire and then the method of data collection whether the data will be collected by doing some experiment or by conducting a survey or the data may be straight away taken from a census report. Another very important aspect is the sampling method used for the research.
Because data pertaining to entire population cannot be collected and analyzed it will be time consuming, resource consuming and defeating the very basic purpose of statistics it self, which is nothing but drawing useful inferences about a population by analyzing the data of a representative sample.
In this case the question to be answered is woman like to browse while men like to buy and get out of store. Therefore, important variables to be measured are
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Motive to go to a store
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Time spent inside a store
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Major activity inside a store (time spent on browsing)
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Feeling inside a store
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Perception about shopping (a work or an indulgence)
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Need of attention inside a store
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Response of the subject when the item s/he is looking for is missing in a store
To measure these variables the only option is to design a suitable questionnaire and get response of the subjects. The following questionnaire was designed after discussing the issue with my classmates.
0 No and 1 Yes
This questionnaire consists of twelve (12) categorical variable and two (2) continuous variables. This questionnaire was subjected to reliability analysis. Reliability is very important in quantitative analysis. This refers to how reliable is the instrument used for data collection and whether or not there is internal consistency in the data collection instrument (Cohen et al 2007). In this study, the questionnaire was the instrument of data collection.
Though, the questionnaire was designed with intense discussion with my classmates, it was essential to test the reliability of the data collecting instrument the questionnaire. Reliability of the questionnaire was measured by test retest method. This questionnaire was administered on 20 of my classmates (10 males and 10 females) twice at a gap of two weeks and the reliability was measured using kappa statistics K, which is coefficient of agreement for nominally scaled data (Siegel & Castellan, 1988). Thus reliability of the test instrument (the questionnaire) was confirmed before collecting the data and therefore, the study is therefore reliable.
Sampling and Data Collection
I decided to survey a sample of 50 males and females 10 each at five different departmental stores. I took help of my friends to conduct the survey at different stores. I decided to conduct the survey at the evening time when most of the shoppers come for shopping, so that a representative sample can be obtained. Though it was a convenient sample in the sense that I carried out the survey at five departmental stores of my choice, I took sufficient care to ensure that the sample is random to the extent possible by selecting the departmental stores in five distinct localities.
To collect actual time spent by the shoppers, the shoppers were identified randomly while they were entering the store and they were contacted for the survey while coming out of the store. Out of 35 50 shoppers identified and contacted for this survey at each of the five stores only about 10 were willing to participate in the survey. The data presented below belongs to that of the willing subjects in this study.
Results
Sample size was 50 for both males as well as females.
The findings of the survey are listed in the Table 1 and Table 2, below.
The findings are presented as bar diagram in Figure 1, below.
Time spent (actual) as well as that reported by the shoppers is shown in Fig. 2, below.
From Figure 1, it is clear that there is considerable difference in the response of the males from that of the females against the questions asked in the questionnaire. On the other hand Figure 2, shows there is considerable difference in the time spent by males than that be females inside a departmental store. Another interesting finding is that while there is hardly any difference between the actual time spent by males and that reported by them; this difference is considerable in case of females.
Whether or not these differences are statistically significant was determined using Hypothesis testing at 95% probability level or 5% significance level. The hypothesis testing is presented below.
Hypothesis Testing
Proportion of respondents with yes (1) for Q1 through Q12 for Males sample as well as Females sample was calculates and the same is listed in Table 1, above.
The hypothesis that is to be tested is whether or not there is statistically significant difference in the proportion of males and females responding Yes against these questions.
Therefore, Null Hypothesis is Ho: p1 = p2 ;
Alternate hypothesis is H1: p1 ` p2
Where 1 Males and 2 for Females
Significance Level chosen for this test is 0.05 (i.e. 95% probability)
Therefore, z-critical is 1.645
Decision rule is if z-test < z-critical then Null Hypothesis is accepted and Alternate Hypothesis is rejected else Null Hypothesis is rejected and Alternate Hypothesis is accepted.
z-test is computed using the following formula
Here p1 = Proportion of males with Yes
p1 = Proportion of females with Yes @^
= proportion of participants with Yes (p1 p2)
= 0 (Hypothesized equality of proportions)
The z-score for the test was calculated for each of the question and the same is listed in Table 2, below.
From this table is it amply clear that for all the twelve questions z-test > z-critical and therefore, the Null Hypothesis is rejected and Alternate Hypothesis is accepted.
What this means is that there is significant difference in the Response of Males and Females on these twelve Questions.
Let us discuss the repercussions of this hypothesis testing for each of these 12 questions.
Q1. Asks whether you go to store with clear idea of what to purchase? The answer for males is overwhelmingly Yes (p = 0.71) while for females this value is mildly yes (p = 0.46) and this difference is statistically significant. What it means is that while men go to the shop with clear idea of what to purchase, females go to just see what all is there and they may buy something if they feel like buying it, or they will return back just like that.
Q2. Do you go to store only for shopping. The answer for males is overwhelmingly Yes (p = 0.68) while for females this value is mildly yes (p = 0.42) and this difference is statistically significant. What it means is that while men go to the shop only when they have to buy something, women go for spending their time and meeting people and seeing what all is going on, if there is some discounts etc.
Similarly, analysis of remaining ten questions also points toward the same thing, that while males look at shopping as something they need to do to buy something they need. They look at it as a work, which is to be done and to be finished and not something to spend their time on. The quickly they can finish; the better it is for them. This is the reason, they do not feel very important while shopping, they do not mind if a sales associate comes to help them or not. It does not bother them if an item is not there; they will simply go out and may be to some other shop. They hardly get into what all discounts are there in the store. Instead they are interested in what they have to buy and that is all.
For woman, just reverse is true. They feel important while shopping, they like that a sales associate comes and helps them and explains them all the discounts and offers running in the store, so that they can buy the best and many times more that they have intended to buy when they came to the store.
For Q13 and 14 following three hypothesis were tested
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Difference in mean time (actual) spent by Males and Females inside a store is statistically significant.
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Difference in mean time spent (actual) by Males inside a store and that that reported by them is statistically insignificant.
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Difference in mean time spent (actual) by Females inside a store and that that reported by them is statistically significant.
For testing this hypothesis,
Therefore, Null Hypothesis is Ho: ¼1 = ¼2;
Alternate hypothesis is H1: ¼1 ` ¼2
Where 1 Males and 2 for Females
Significance Level chosen for this test is 0.05 (i.e. 95% probability)
Therefore, z-critical is 1.645
Decision rule is if z-test < z-critical then Null Hypothesis is accepted and Alternate Hypothesis is rejected else Null Hypothesis is rejected and Alternate Hypothesis is accepted.
z-test is computed using the following formula
Here
E1 = Average of Sample 1
E2 = Average of Sample 2
s1 = Standard Deviation of Sample 1
s2 = Standard Deviation of Sample 2
(E1 -E2 )0 = 0 (Hypothesized equality of averages)
z- score for the three hypothesis tested is listed below.
Difference in mean time (actual) spent by Males and Females inside a store is statistically significant.
z-test = 26.14 z-critical = 1.64
Therefore, Null Hypothesis is rejected and there is significant difference between the shopping time of males and females and obviously the average time spent by females inside a store is significantly higher than that spent by males.
Difference in mean time spent (actual) by Males inside a store and that that reported by them is statistically insignificant.
z-test = 0.99 z-critical = 1.64
Therefore, Null Hypothesis is accepted i.e. there is no significant difference between the actual shopping time of males and that reported by them. What it means is that males are candid and honest in reporting their shopping time, because do not take longer to shop what they shop and also they justify the same.
Difference in mean time spent (actual) by Females inside a store and that that reported by them is statistically significant.
z-test = 13.69 z-critical = 1.64
Therefore, Null Hypothesis is rejected and there is significant difference between the actual shopping time of females and that reported by them. What it means is that females know that they take longer in shopping what they shop and that they have a reputation of spending more time inside a store, so they do make a conscious effort to report less when surveyed. This means while females do indulge in browsing, they like to hide this.
From this quantitative research it can be concluded that while men are more focused on what they are buying, women indulge in browsing a lot more items and schemes in the store while shopping and this results in women taking lot more time in shopping as compared to men. This is something known not only to others but to them as well, because, they report less time than they actually spend inside a store.
References
Cohen L., Manion L., Morrison K., Research Methods in Education , 6th Ed., Routledge, 2007.
Siegel, S., & Castellan, J. N. (1988). Nonparametric statistics for the behavioral Sciences. New York: McGraw-Hill Book Co.
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