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Transcript of AP-18
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Project
On
Consumer Preferences for Features in High-
rise Flats in different Income groups in
Bhubaneswar
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Objectives
The major objectives of the study are as follows:
1. To examine the differences in customer preferences across gender.
2. To examine the differences in customer preferences across age.
3. To examine the differences in customer preferences across monthly income (Household)
category
Hypotheses
The following hypotheses were formulated.
H1. Perception of consumers regarding their preferences for features in high-rise flats would not
differ across gender.
H2. Perception of consumers regarding their preferences for features in high-rise flats would not
differ across age.
H3. Perception of consumers regarding their preferences for features in high-rise flats would not
differ across monthly (Household) category.
Method
1. Sample
The data were collected from 70 respondents, out of which 54 (77 per cent) were male and
female 16 (23 per cent). The data were collected from respondents who were only flat-owners
and living in the study area for more than two years was chosen. The study area was small
enough so that two year of residence was considered an adequate amount of time to become
familiar with the geographic area. Obviously, the familiarization time is dependent upon the area.
In a large urban area the time of residence may have to be lengthened and a more direct measure
of the respondent’s exposure to the area may have to be developed. This could be a measure of
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the residential linkage pattern. In the end, two years of residence was considered was considered
adequate for the Bhubaneswar flat (housing) market.
Due to time and cost constraints as well as non-availability of the respondents for participation in
the survey. Purposive sampling method was used to collect data. Time and expense precluded the
use of procedures to correctly handle non-response (a significant problem given the length of the
interview for this study). A large number of students were utilized during the data-gathering
process.
Each was assigned a specific area of Bhubaneswar and given a quota of interview to complete. It
was left to each student to find flat-owners who met the study criteria and were willing to
complete the interview process.
A total of 70 interviews were completed in usable form. A brief summary of sample
characteristics is given (Table 1). As can be seen, the sample contains an over representation of
males, has slightly more people per household than average, and is noticeably above the general
population income level, this pattern is not inconsistent with the study limitation of selecting
only flat-owners having lived in the area for at least two years.
The data for a perceptual model may take the form of similarly (or dissimilarly) judgments
concerning the flats and/or preference rankings of the flats. This study gathered data using both
of these approaches. In the data-gathering process for the similarity judgments, the respondents
is presented information on a sample of flats and asked to make judgments about them. Each
respondent is asked to rank order every possible non-ordered pair of flats in the sample from the
pair that in his mind is the most similar to the pair that is the least similar. This requires that the
data provided to the respondents must be manageable, consistent, and non-abstract.
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A manageable database was generated by a priori limitation of the sample to six houses from
which fifteen pairs of house were established. This information set was small enough to the
manageable during the interview process and not overburden the respondent whole keeping
measurement error within reasonable limits.
Table 1: Summary of Sample Characteristics
The sample of flats, although restricted to the middle of the market, was large enough to give a
simplified, but realistic view of the market being analyzed. Other data-gathering methods which
allow the use of a larger number of flats are possible and could be experimented with in future
research efforts.
The sample of flats was selected with the assistance of several real estate agents who were very
familiar with and had been active in the housing market during the preceding year. A sample of
flats was obtained from those that recently sold and which represented the housing choices
No. Percentage
Sex
Male 54 77
Female 16 23
Total 70 100
Age
Below 30 10 14
31-40 16 23
41-50 16 2351-60 25 36
61 and above 3 4
Total 70 100
Marital Status
Single 8 11
Married 62 89
Total 70 100
Household Income (Rs)
Below 30,000 6 9
30,001-40,000 22 31
40,001-50,000 16 23
50,001-60,000 17 2460,001 and above 9 13
Total 70 100
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generally available throughout the city. All major residential areas at Bhubaneswar were
represented in the sample.
The consistency and non-abstractness of the data was assured by providing each respondent the
sample package of information about the flats. The following information was presented to each
respondent:
a. A map of the market area. The map identified the location of each flat in the study as well as
the location of schools or collages, shopping areas, and recreation areas. While the respondents
were residents and thus familiar with most of the identified facilities, inclusion of these locations
helped to reduce informational bias and allowed the respondent to form a clear mental picture of
the location of each residence.
b. For each residence in the sample a fact sheet was prepared. This fact sheet included
photographs of the flat and the immediate surrounding area from all appropriate views; a floor
plan of the flat including room dimensions; a list of features of the flat (e.g. construction type
and materials, type and number appliances, type of heating/cooling, etc.) and a site plan of the of
the lot showing the size of the lot, the placement of the house on the lot, additional structures,
fences, and trees.
The use of trend student also helped to insure consistency. The students were told the nature of
the study and the precise manner in which the data was to be gathered. They were trained not to
influence the decision making process of the respondent. The entire interview process was
simulated with the student to clarify the steps necessary to minimize interviewer bias, and to
allow them to check each interview packet for completeness. Post interview discussions with the
students indicated that the respondents took the interview process seriously and spent a amount
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of time completing the process. The interviews ranged from 25 to 50 minutes with most
respondents requiring approximately 40 minutes to complete the requested tasks.
Measures
The data were collected through a structured interview schedule (questionnaire) consisting of
two parts-Section I, Section II. In Section I, the variables included in this study were measured
using the five-point Likert scale. The five point scale was used for the sake of uniformity. The
18-item questionnaire administered to the set of respondents was complied using items from
different standardized scales measuring a single variable of the study (See Section I). The
selection of the items for inclusion in the questionnaire was finalized on the basis of a pilot
survey and consultation with experts.
Consumer Preferences
In order to measure preferences for features in high-rise flats, a 18-item scale was used. Item
numbers CP1 to CP18 (in Section I) of the questionnaire measured the consumer preferences of
flat purchasing process. The reliability coefficient for Factor 1 was .66, Factor 2 was .70, Factor
3 was .70, Factor 4 was .66, and Factor 5 was .74. Since Factor 6 have a single item, it was
dropped from the study.
Table 2: A Summary of Tool Characteristics
Serial
No.
Factor No. of Items Mean SD Alpha
Coefficient
1. Factor 1 3 13.06 1.91 .662. Factor 2 4 16.87 2.59 .70
3. Factor 3 5 20.71 2.99 .70
4. Factor 4 3 10.58 2.45 .66
5. Factor 5 2 8.91 1.41 .74
6. Factor 6 1 3.60 .92 -
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Data was obtained by establishing a list of attributes that closely resembled the lists of attributes
established by other researchers. Each respondent was asked to evaluate each flat on each
attribute on a 5-point scale of “very undesirable” to “very desirable”. These rankings, which
were gathered after the similarity and preference ranking process so as not to influence the
process by providing appropriate evaluative criteria, were used in the analysis to help define the
actual criteria used by the respondents.
Specifically, each respondent was asked
How would you rate this flat in terms of its;
CP1. Room layout (overall floor plan)
CP2. Size of room
CP3. Ease of access to shopping
CP4. Ease of access to airport
CP5. Ease of access to railway station
CP6. Ease of access to hospital
CP7. Ease of access to ATM
CP8. Ease of access to recreation
CP9. Shopping complex within the campus
CP10. Gymnasium within the campus
CP11. Parking facilities within the campus
CP12. Earthquake resistance
CP13. DG (generator) back up
CP14. Quality of PHD & electrical fittings
CP15. Ease of access to schools/colleges
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CP16. Ease of access to job place/office
CP17. Overall neighborhood quality
Finally, demographic information was also requested. Because the tasks requested during the
interview were time consuming, the demographic profile was kept very brief. A total of five
questions were asked on the demographic profile questionnaire
These were:
1. How long have you been a resident of Bhubaneswar?
Less than 2 yrs
More than 2 yrs
2. Gender: Male/Female
3. Age (years): Below 30
31-40
41-50
51-60
61 and above
4. Marital Status : Single
Marred
4. Monthly Income (Rs)
Below 30000
30001-40000
40001-50000
50001-60000
60001 and above
Procedure
After developing a conceptual framework for the study, identifying the variable, and finalizing
the questionnaire based on the high reliability obtained, it was decided that the survey would be
concluded at Bhubaneswar. Due to time and cost constraints as well as non-availability of the
respondents for participation in the survey, purposive sampling method was used to collect data.
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Moreover, the survey had to be administered using single approach, i.e. conducting personal
interviews. A total of one hundred thirty six responses were collected.
Survey questionnaires were pre-tested using a small number of respondents (about twelve; the
pre test participants did not participate in the final data collection). As the consequences of the
pre testing, relatively minor modifications were made in the written instructions and
questionnaire items. The respondents were selected from their residential area of flats, and they
were requested to fill the questionnaire either on the bank premises itself or at their residence,
after getting their consent. Written instructions, along with brief oral presentations, were given to
assure the respondents of anonymity protection, and the purpose of the project was also
explained. The participants were given the opportunity to ask questions and were encouraged to
answer the surveys honestly. Anonymity was guaranteed and no names or identifying
information was asked for.
Results and discussion
The study was conducted in a exploratory framework using survey project. The data were
collected from one hundred thirty six respondents. The data were subjected to statistical analysis
for drawing inferences. Analysis of variance (ANOVA) was used to differences with regard to
different factors.
Factor Analysis Result
The data were subjected to factor analysis to identify the factors and establish construct validity.
The factor analysis was done using principle component with varimax rotation, as they appeared
to be interrelated with each other. The highest loading against any factor was taken into account
as a representative of that scale showing the construct validity. The actors obtained from this
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analysis for all the scales were subjected to further statistical analysis. A summary of the factor
analyses result is presented below.
Consumer Preferences
This is a standardize scale and has extensively used by researchers. However, factor analysis was
performed to confirm the dimensionality of the original scale for this study, which was
conducted in Indian socio cultural context, where the respondents’ characteristics and values are
different.
Factor analysis results showed 6 factors identified as Factor 1, Factor2, Factor 3, Factor 4, Factor
5 and Factor 6 had an Eigen value of 4.62, 2.15, 1.63, 1.43, 1.35 and 1.10 respectively and all
together accounted for 68 percent of variance. Factor 6 was dropped from the study which
consists of a single item. A summary of the factor analysis results along with their loadings
presented in Table 3.
Table 3: Summary of Factor Analysis results for Consumer Preferences
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6
Item Loading Item Loading Item Loading Item Loading Item Loading Item Loading
5 .65 3 .69 1 .50 9 .61 7 .83 8 .86
6 .80 13 .46 2 .62 10 .79 14 .86
18 .68 16 .80 4 .56 11 .72
17 .66 12 .59
15 .77Eigen
Value4.62 2.15 1.63 1.43 1.35 1.10
Percentage
of Variance
26 12 9 8 7 6
Total variance explained = 68 per cent
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In order to examine whether factor analysis is an appropriate analysis to indentify factor, the
Kaiser -Meyer-Olkin (KMO) measure of sample adequacy and bartlett’s test of sphericity was
conducted.
The Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy (KMO=0.57) value is
acceptable if KMO value is greater than 0.50. Bartlett’s test result shows that the values are
significant and thus acceptable (Table 4).
Table 4: KMO and Bartlett's Test Results for Consumer Preferences
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .57
Bartlett's Test of Sphericity
Approx. Chi-Square 460.37df 153
Sig. .01
After examining the construct validity and identifying the factors, and the inter-correlation
among the variables, proposed hypothesis were tested. The results related to different hypothesis
are presented and discussed below.
H1. Perception of consumers regarding their preferences for features in high-rise flats would not
differ across gender.
In order to examine the differences in consumer perception across gender, ANOVA was
conducted. Consumers were divided into two different categories, male and female. The results
(Table 5) showed that there were significant differences with regard to Factor 1 (F=3.86, p<.01),
Factor 2 (F=5.10, p<.01) and Factor 5 (F=5.89, p<.01). However, no significant differences
were found with regard to Factor 3 (F=. 50, p>.05) and Factor 4 (F=.02, p>.05).
The results reveal that males were given more preference to easy access to ATM, job place, and
neighborhood quality while selecting residential flats compare to females. The results also
suggest that males were given priority to easy access to schools and colleges from their campus.
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Table 5: Summary of Analysis of Variance (ANOVA) examining differences in Consumer
Preferences across gender
**Significant at 0.01 level * Significant at 0.05 level.
H2. Perception of consumers regarding their preferences for features in high-rise flats would not
differ across age.
In order to examine the differences in consumers perception regarding their preferences for
features in high-rise flats would not differ across age, ANOVA was conducted. Customers were
divided into five different age groups starting from below 30 to 61 and above. The results (Table
6) showed that there were significant differences with regard to Factor 1 (F=4.11, p<.01), Factor
2 (F=3.77, p<.01) and Factor 3 (F=2.49, p<.01). However, no significant differences were found
with regard to Factor 4 (F=. 08, p>.05) and Factor 5 (F=.36, p>.05).
Sum of
Squares df
Mean
Square
F
Factor 1
Between Groups 13.51 1 13.51
3.86*Within Groups 238.26 68 3.50
Total 251.77 69
Factor 2
Between Groups 32.22 1 32.22
5.10*Within Groups 429.62 68 6.32
Total 461.84 69
Factor 3
Between Groups 4.47 1 4.47
.50Within Groups 611.82 68 9.00
Total 616.29 69
Factor 4
Between Groups .14 1 .14
.02Within Groups 415.23 68 6.11
Total 415.37 69
Factor 5
Between Groups 10.96 1 10.96
5.89**Within Groups 126.53 68 1.86
Total 137.49 69
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The results suggest that aged consumers (50-60) were given more preference to quality electrical
equipment and earthquake resistant in their flats, easy access to railway station, hospitals,
shopping, job place and parking facilities within the campus, compare to younger consumers
(30-40).
Table 6: Summary of Analysis of Variance (ANOVA) examining differences in Consumer
Preferences across age
**Significant at 0.01 level * Significant at 0.05 level.
H3. Perception of consumers regarding their preferences for features in high rise flats would
not differ across monthly income household category.
In order to examine the differences in perception of consumers regarding their preferences for
features in high rise flats across monthly income household category. ANOVA was conducted
.customers were divided into five different income categories starting from rupees below 30
thousand to rupees more than sixty thousand. The results (Table 7) showed that there were
significant differences with regard to Factor 1 (F=2.91, p<.01) and Factor 2 (F=3.55, p<.01).
Sum of
Squares df
Mean
Square
F
Factor 1
Between Groups 50.86 4 12.71
4.11**Within Groups 200.92 65 3.09
Total 251.77 69
Factor 2
Between Groups 86.93 4 21.73
3.77**Within Groups 374.91 65 5.77
Total 461.84 69
Factor 3
Between Groups 81.74 4 20.44
2.49*Within Groups 534.54 65 8.22
Total 616.28 69
Factor 4
Between Groups 1.91 4 .48
.08Within Groups 413.46 65 6.36
Total 415.37 69
Factor 5Between Groups 2.98 4 .75
.36Within Groups 134.50 65 2.07
Total 137.48 69
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However, no significant differences were found with regard to Factor 3 (F=1.74, p>.05), Factor 4
(F=2.13, p>.05) and Factor 5 (F=1.49, p>.05).
Table 7: Summary of Analysis of Variance (ANOVA) examining differences in Consumer
Preferences across monthly income household category
**Significant at 0.01 level * Significant at 0.05 level.
The results reveal that consumers whose income were comparatively low, given more emphasis
towards neighborhood quality, earthquake resistant and also easy access to railway station
compare to higher income group.
Conclusion
The results reveal that males were given more preference to easy access to ATM, job place, and
neighborhood quality while selecting residential flats compare to females. The results also
suggest that males were given priority to easy access to schools and colleges from their campus.
Sum of
Squares df
Mean
Square
F
Factor 1
Between Groups 38.23 4 9.56
2.91*Within Groups 213.54 65 3.29
Total 251.77 69
Factor 2
Between Groups 82.76 4 20.69
3.55**Within Groups 379.08 65 5.83
Total 461.84 69
Factor 3Between Groups 59.49 4 14.87
1.74Within Groups 556.80 65 8.57
Total 616.29 69
Factor 4
Between Groups 48.07 4 12.02
2.13Within Groups 367.30 65 5.65
Total 415.37 69
Factor 5
Between Groups 11.53 4 2.88
1.49Within Groups 125.96 65 1.93
Total 137.49 69
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The results also suggest that aged consumers were given more preference to quality electrical
equipment and earthquake resistant in their flats, easy access to railway station, hospitals,
shopping, job place and parking facilities within the campus, compare to younger consumers.
The results reveal that consumers whose income were comparatively low, given more emphasis
towards neighborhood quality, earthquake resistant and also easy access to railway station
compare to higher income group.