3-1. BADM 633 - Wk 2 International Business Culture Terry Ryan.
BADM Project Report Group-10
Transcript of BADM Project Report Group-10
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On
Business Analytics for Decision Making
Submitted in partial fulfilment of the requirements of
Post Graduate Programme
IILM Institute for Higher Education
Gurgaon
Submitted To: Submitted By:
Mr. Piyush Singhal Rotash Chandra Sahu
Mr. Dinesh kumar Raju Sharma
Abhishek Dudani
Sharvan Pandey
Pradeep Saini
Vineet Singh
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Contents
Serial No. Particulars
1 Cover page
2 Acknowledgement
3 Executive summary
4 Problem definition
5 Research design
6 Sampling plan
7 Instrument (questionnaire)
8 Data collection
9 Data analysis
10 Hypothesis testing
11 Methodology
12 Cross tabulation
13 Correlation
14 Manova
15 Chi-square test
16 Limitations
17 Conclusions
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Executive Summary and Background
Citi & Urban (Realtors & Consultants) is a property dealer firm that
offers a variety of real estate services. A few of the service include both buyer
and seller representation in the sell, purchase and rent of real property. This
dealer is currently located in Sushant lok, Sector-57, Gurgaon.
Citi & Urban is interested in knowing Gurgaon sector 55-56-57 can
support a possible branch office, as this area has the growing potential having
the population approximately 80,000. The only main limitation for this firm is
that the people intend to buy or rent home according to the availability of the
market for shopping nearby home & also trying to purchase or rent through
some other mode or sources.
The existing property dealers in this location are approximately 40 .The
analysis of the market through this market study plan is for the purpose of
modifying branch office in big budget and to advertise the firm (broking)
publicly, so that the people get aware of this service. If this study determines
that there is no potential for a market to sustain a branch office, no expenditure
should be made.
Problem Definition
Management Decision Problems
Should the Citi & Urban realtors and consultants enlarge their
business on the basis of place?
Is there a market in sector 56-57 (Gurgaon) area to sustain a real estate
(property dealer)?
Marketing Research Problems
Do people like real estate service?
Can the realtors market be segmented on the basis of consumer’s income
or age?
Does the consumer preference of different income groups for the sell, buy
or rent of home varies according to the place, brand loyalty or news paperadvertisement?
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Approach to the Problem
The purpose of the study is to conduct a descriptive probe to determine if
the result of the market study required further research. The study surveyed a
proportions of the residents in the above area and the results of the research will
determine if Citi & Urban able to modify a real estate office.
The main focus during questionnaire would be; “Are there enough people
willing to take advantage of real estate service in sector 56-57 area”.
Research Design
The study conducted using a personal door to door survey method of theresidents in sector 56-57. The survey identified following questions;
1. Do residents of sector-57 take advantage of real estate service?
2. Is there a trend in the above area leading to use of real estate service?
3. Do people rent or own?
4. How long have they switch?
5. Do they rent, lease, buy or sell their property on their own?
Sampling Plan
The survey was to gain data from the sample of the total sector 56-57 area
population. The sample would be the representation of the 67 persons .This
sample can then be used to make assumptions regarding the total population in
this area of sector 56-57.
Research Instrument
The research instrument used by us is questionnaire method because it is
the easiest way to interact with people and get the relevant data for our market
research. Mostly all questions are in structured form as the questions are
multiple choice questions. The questionnaire was invented by Sir Francis
Galton. Questionnaire have advantages over some other types of surveys in that
they are cheap, don’t require as much effort from the questioner as verbal or
telephone surveys and often have standardised answers that makes it simple tocompile data.
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Scaling techniques used by us in the questionnaire include:
Dichotomous questions
Which has only two response alternatives: own or rent.
Multiple choice questions
In which respondents have to choose one answer from many options.
These questions give a wide choice to the respondents so that they can give the
most accurate and reliable answer e.g. strongly agree, agree, neither agree nor
disagree, disagree, strongly disagree.
The Questionnaires are:
1. Sector 56 - 57 is the best place to live.
a) Strongly disagree b) disagree c) agree d) strongly agree
2. How long have you lived in your present home?
a) less than 1 years b) 1-5 years c) 6-10 years d) 10 + years
3. How many homes have you lived in since moving to this area?
a) 1-2 b) 3-4 c) 5-6 d) more than 6
4. Did you locate your home on your own, or you use a real estate service
firm?
a) Own b) real estate service firm c) Friends d) Relatives
5. Do you rent or own the house you are living in ?
a) Rent b) own
6. Would you consider using a real estate service firm in the search for
another home?
a) yes b) no c) may be
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7. If yes, in which area would you prefer real estate service firm in
Gurgaon?
-----------------------
8. Would you consider using a real estate firm in the sale of your home ?
a) yes b) no c) may be
9. Are you planning on moving in the next?
a) 0 – 6 months b) 7-12 months c) 13-24 months d) unknown
10) How would you describe the local real estate service firm?
a) Convenient b) service oriented c) efficient d) not consulted yet
11) Newspaper advertisement enough to choose right property dealers?
a) Strongly disagree b) disagree c) agree d) strongly agree
12) The property dealer with Brand Name provides better service than local?
a) Strongly disagree b) disagree c) agree d) strongly agree
13) The commission charge by local property dealer is affordable
a) Strongly disagree b) disagree c) agree d) strongly agree e) neither agree
nor disagree
14) Which of the following groups include your age?
a) 21-30 b) 31-40 c) 41-50 d) 51-60 e) 61+
15) What is the size of your family?
a) 1 b) 2 – 3 c) 4 – 5 d) 6+
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Data Collection
The data obtained directly from the people of sector 55-56-57, Gurgaon.
Data Analysis
Responses to each item on the survey were tabulated. Design the statistics
calculation to show the relationship between instrument questions and the data
itself.
Quantitative analysis
In quantitative research the information obtained from the participants is
expressed in numerical form. Quantitative analysis is often more influenced
than qualitative analysis by the biases and theoretical assumptions of the
investigator.
Hypothesis Testing
Null Hypothesis (H0): The small realtors and consulters should enlarge their
business in sector 55-56-57, Gurgaon.
Alternate Hypothesis (H1): The small realtors and consulters should not
enlarge their business in sector 55-56-57, Gurgaon.
Methodology
Independent variables:
Preference of real-estate service Advertisement
Income
Place
Dependent variables:
Brand
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Cross Tabulation
Cross tabulation is the merging of the frequency distribution of two or more
variables in a single table.
Case Processing Summary
Cases
Valid Missing Total
N Percent N Percent N Percent
place_likability * brand 67 100.0% 0 .0% 67 100.0%
consideration_of_realestate *
brand
67 100.0% 0 .0% 67 100.0%
news_advertisement * brand 67 100.0% 0 .0% 67 100.0%
income * brand 67 100.0% 0 .0% 67 100.0%
Place_likability Vs Brand
Crosstab
Count
Brand
Totaldisagree
nither agree nor
disagree agree strongely agree
place_likability not toomuch 7 5 3 2 17
don't no 1 5 2 1 9
a little 2 3 4 0 9
a lot 7 10 12 3 32
Total 17 23 21 6 67
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Consideration_of_Realestate Vs Brand
Crosstab
Count
brand
Totaldisagree
nither agree nor
disagree agree strongely agree
consideration_of_realestate No 1 2 0 0 3
may be 9 8 9 4 30
Yes 3 9 7 0 19
absolutely 4 4 5 2 15
Total 17 23 21 6 67
News_advertisement Vs Brand
Crosstab
Count
brand
Totaldisagree
nither agree nor
disagree agree
strongely
agree
news_advertisement strongly disagree 11 6 8 1 26
nither agree nor disagree 2 15 6 2 25
Agree 4 2 7 0 13
strongely agree 0 0 0 3 3
Total 17 23 21 6 67
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Income Vs brand
Crosstab
Count
Brand
TotalDisagree
nither agree nor
disagree Agree strongely agree
income < 1 Lack 1 5 0 1 7
1lack to 3 lack 3 4 5 1 13
3 lacks to 5 lack 5 7 7 4 23
5 lack to 7 lack 8 7 9 0 24
Total 17 23 21 6 67
Inferences from Cross tabulation
There is a strong significance between Brand and Consideration of real
estate i.e. 0.551 which is greater than 0.05.
Also there is a strong significance between Brand and Income i.e 0.575.
Correlation
A statistical technique that is used to analyze the strength and direction of the
relationship between two quantitative variables is called correlation analysis.
Significance level Remarks
< 0.05 Reject null hypothesis
>0.05 Accept null hypothesis
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Place_likability Vs brand
Symmetric Measures
Value
Asymp. Std.
Errora
Approx. Tb
Approx. Sig.
Interval by Interval Pearson's R .135 .129 1.095 .278c
Ordinal by Ordinal Spearman Correlation .146 .127 1.187 .240c
N of Valid Cases 67
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
Consideration_of_realestate Vs Brand
Symmetric Measures
Value
Asymp. Std.
Errora
Approx. Tb
Approx. Sig.
Interval by Interval Pearson's R .074 .126 .599 .551c
Ordinal by Ordinal Spearman Correlation .073 .125 .589 .558c
N of Valid Cases 67
News_advertisement Vs Brand
Symmetric Measures
Value
Asymp. Std.
Errora
Approx. Tb
Approx. Sig.
Interval by Interval Pearson's R .327 .133 2.788 .007c
Ordinal by Ordinal Spearman Correlation .275 .130 2.303 .025c
N of Valid Cases 67
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Income Vs Brand
Symmetric Measures
Value
Asymp. Std.
Errora
Approx. Tb
Approx. Sig.
Interval by Interval Pearson's R -.070 .112 -.564 .575c
Ordinal by Ordinal Spearman Correlation -.077 .116 -.622 .536c
N of Valid Cases 67
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.
Inferences from Correlation
There are strong relations between
Income and Brand (0.575)
Consideration of real estate and Brand (0.551)
Place likability and Brand (0.278)
There is no relation between News paper advertisement and Brand.
Manova
MANOVA is a generalized form of univariate ANOVA. It is used when there
are two or more dependent variables. It helps to answer : 1. do changes in theindependent variable(s) have significant effects on the dependent variables; 2.
what are the interactions among the dependent variables and 3. among the
independent variables.
Elements:
One or more between subject factors
Two or more metric dependent variables
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General Linear Model
Between-Subjects Factors
Value Label N
consideration_of_realestate 1.00 no 3
2.00 may be 30
3.00 yes 19
4.00 absolutely 15
Income 1.00 < 1 Lack 7
2.00 1lack to 3 lack 13
3.00 3 lacks to 5 lack 23
4.00 5 lack to 7 lack 24
news_advertisement 1.00 strongly disagree 26
2.00 nither agree nor disagree 25
3.00 agree 13
4.00 strongely agree 3
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Multivariate Testsc
Effect Value F Hypothesis df Error df Sig.
Intercept Pillai's Trace .920 194.649a
2.000 34.000 .000
Wilks' Lambda .080 194.649a
2.000 34.000 .000
Hotelling's Trace 11.450 194.649a
2.000 34.000 .000
Roy's Largest Root 11.450 194.649a
2.000 34.000 .000
consideration_of_realestate Pillai's Trace .355 2.516 6.000 70.000 .029
Wilks' Lambda .663 2.584a
6.000 68.000 .026
Hotelling's Trace .481 2.645 6.000 66.000 .023
Roy's Largest Root .416 4.853b
3.000 35.000 .006
Income Pillai's Trace .071 .428 6.000 70.000 .858
Wilks' Lambda .930 .420a
6.000 68.000 .863
Hotelling's Trace .075 .412 6.000 66.000 .869
Roy's Largest Root .066 .765b
3.000 35.000 .521
news_advertisement Pillai's Trace .452 3.406 6.000 70.000 .005
Wilks' Lambda .588 3.450a
6.000 68.000 .005
Hotelling's Trace .634 3.488 6.000 66.000 .005
Roy's Largest Root .499 5.824b
3.000 35.000 .002
consideration_of_realestate *
income
Pillai's Trace .489 1.620 14.000 70.000 .095
Wilks' Lambda .569 1.581a
14.000 68.000 .107
Hotelling's Trace .654 1.542 14.000 66.000 .121
Roy's Largest Root .390 1.952b
7.000 35.000 .091
consideration_of_realestate *
news_advertisement
Pillai's Trace .391 1.416 12.000 70.000 .180
Wilks' Lambda .639 1.424a
12.000 68.000 .177
Hotelling's Trace .520 1.430 12.000 66.000 .175
Roy's Largest Root .408 2.378b
6.000 35.000 .049
income *
news_advertisement
Pillai's Trace .307 1.270 10.000 70.000 .264
Wilks' Lambda .716 1.236a
10.000 68.000 .285
Hotelling's Trace .364 1.201 10.000 66.000 .307
Roy's Largest Root .210 1.467b
5.000 35.000 .226
consideration_of_realestate *
income *
news_advertisement
Pillai's Trace .276 1.404 8.000 70.000 .210
Wilks' Lambda .731 1.444a
8.000 68.000 .194
Hotelling's Trace .359 1.481 8.000 66.000 .181
Roy's Largest Root .330 2.883b
4.000 35.000 .037
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a. Exact statistic
b. The statistic is an upper bound on F that yields a lower bound on the significance level.
c. Design: Intercept + consideration_of_realestate + income + news_advertisement + consideration_of_realestate *
income + consideration_of_realestate * news_advertisement + income * news_advertisement +
consideration_of_realestate * income * news_advertisement
Tests of Between-Subjects Effects
Source
Dependent
Variable
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model brand 38.346a
31 1.237 2.183 .013
place_likability 50.711b
31 1.636 1.014 .482
Intercept brand 162.158 1 162.158 286.162 .000
place_likability 241.196 1 241.196 149.458 .000
consideration_of_realestate brand 4.572 3 1.524 2.689 .061
place_likability 15.961 3 5.320 3.297 .032
Income brand 1.291 3 .430 .759 .525
place_likability .526 3 .175 .109 .954
news_advertisement brand 9.751 3 3.250 5.736 .003
place_likability 8.756 3 2.919 1.809 .164
consideration_of_realestate *
income
brand 6.912 7 .987 1.743 .131
place_likability 17.894 7 2.556 1.584 .173
consideration_of_realestate *
news_advertisement
brand 8.086 6 1.348 2.378 .049
place_likability 6.465 6 1.078 .668 .676
income * news_advertisement brand 4.137 5 .827 1.460 .228
place_likability 8.730 5 1.746 1.082 .387
consideration_of_realestate *
income * news_advertisement
brand 6.530 4 1.632 2.881 .037
place_likability 1.926 4 .482 .298 .877
Error brand 19.833 35 .567
place_likability 56.483 35 1.614
Total brand 394.000 67
place_likability 646.000 67
Corrected Total brand 58.179 66
place_likability 107.194 66
a. R Squared = .659 (Adjusted R Squared = .357)
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Tests of Between-Subjects Effects
Source
Dependent
Variable
Type III Sum of
Squares df Mean Square F Sig.
Corrected Model brand 38.346a
31 1.237 2.183 .013
place_likability 50.711b
31 1.636 1.014 .482
Intercept brand 162.158 1 162.158 286.162 .000
place_likability 241.196 1 241.196 149.458 .000
consideration_of_realestate brand 4.572 3 1.524 2.689 .061
place_likability 15.961 3 5.320 3.297 .032
Income brand 1.291 3 .430 .759 .525
place_likability .526 3 .175 .109 .954
news_advertisement brand 9.751 3 3.250 5.736 .003
place_likability 8.756 3 2.919 1.809 .164
consideration_of_realestate *
income
brand 6.912 7 .987 1.743 .131
place_likability 17.894 7 2.556 1.584 .173
consideration_of_realestate *
news_advertisement
brand 8.086 6 1.348 2.378 .049
place_likability 6.465 6 1.078 .668 .676
income * news_advertisement brand 4.137 5 .827 1.460 .228
place_likability 8.730 5 1.746 1.082 .387
consideration_of_realestate *
income * news_advertisement
brand 6.530 4 1.632 2.881 .037
place_likability 1.926 4 .482 .298 .877
Error brand 19.833 35 .567
place_likability 56.483 35 1.614
Total brand 394.000 67
place_likability 646.000 67
Corrected Total brand 58.179 66
place_likability 107.194 66
a. R Squared = .659 (Adjusted R Squared = .357)
b. R Squared = .473 (Adjusted R Squared = .006)
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Bar chats
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Chi-square Test
Chi-Square tests enable us to test more than two population proportions.
If we classify a population into several categories with respect to two attributeswe can then use a chi-square test to determine whether the two attributes are
independent of each other.
Chi-square test is used to test the significance of the observed association in a
cross-tabulation.
where O= an observed frequency in a particular category
E= an expected frequency for a particular category
Place_likability Vs Brand
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 7.121a
9 .624
Likelihood Ratio 7.806 9 .554
Linear-by-Linear Association 1.195 1 .274
N of Valid Cases 67
a. 11 cells (68.8%) have expected count less than 5. The minimum
expected count is .81.
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Consideration_of_realestate Vs Brand
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 7.743a
9 .560
Likelihood Ratio 10.368 9 .322
Linear-by-Linear Association .363 1 .547
N of Valid Cases 67
a. 10 cells (62.5%) have expected count less than 5. The minimum
expected count is .27.
News_advertisement Vs Brand
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 48.160a
9 .000
Likelihood Ratio 33.362 9 .000
Linear-by-Linear Association 7.047 1 .008
N of Valid Cases 67
a. 10 cells (62.5%) have expected count less than 5. The minimum
expected count is .27.
Income Vs Brand
Chi-Square Tests
Value df
Asymp. Sig. (2-
sided)
Pearson Chi-Square 11.151a
9 .266
Likelihood Ratio 14.390 9 .109
Linear-by-Linear Association .321 1 .571
N of Valid Cases 67
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Inferences from Chi-square Test
1ST Attribute 2nd Attribute Asymptoticsignificance
Chi-square
Remarks
Place likability Brand 0.624 Observed
value is don’t
differ from
expected value
Consideration
of real estate
Brand 0.560 Observed
value is don’t
differ from
expected value
News
advertisement
Brand 0.000 Observed
value is differfrom expected
value
Income Brand 0.266 Observed
value is don’t
differ from
expected value
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Study Limitations
This includes Respondent Errors
There are two types of respondent errors. They are, Non-Response Error
and Response Error. Non- Response errors include non-respondents error,
where people could refuse to cooperate. Here people could refuse to answer
some questions like information relating to the amount of income they receive
per month or their age.
Customers could also answer questions with a certain incline that does
not represent the truth completely. This is called a response bias. Here theanswers are misinterpreted or falsified.
The interviewer could sometimes influence the way the respondent
answers the question. The presence of the interviewer could make the
respondent modify their answer so that the interviewer does not see them as un-
usual.
Social desirability bias is also a form of response bias. This is when
people try to create a good impression in the interviewer’s presence. A good
example can be when respondents are answering a question about the amount of
income they earn per month. The respondents may give an answer of a higher
income than what they truly receive, especially if they are planning on going to
a better paying job in a few months or years to come.
Administrative Errors:
This refers to errors caused by “the improper administration or executionof the research task” by the researchers.
Data Processing Error:
This is when the researcher codes the data received from the interview or
questioner wrongly on the computer. E.g., a researcher can code the age of a
respondent wrongly on the computer, and this might affect the end result of the
survey conducted.
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Interviewer Error:
This can occur when the interviewer incorrectly records the responses
from the survey.
Interviewer Cheating: This is when the interviewer fills in questions that were left out by the
respondent.
Conclusion
Null hypothesis is accepted because:
There are strong relations between:
Income and Brand (0.575)
Consideration of real estate and Brand (0.551)
Place likability and Brand (0.278)
Also from the chi-square test it is clear that the p value is greater in maximum
cases it means that observed values do not differ significantly from expectedvalue.
The realtors and consultants should enlarge their businesses in sector 55-56-57
(Gurgaon), by spending more money. So that it will be beneficial for them.