AP-18

8/4/2019 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.


differ across age.


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.


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.


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


5.10*Within Groups 429.62 68 6.32

Total 461.84 69

Factor 3


.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


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).


Preferences across age


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


4.11**Within Groups 200.92 65 3.09

Total 251.77 69

Factor 2


3.77**Within Groups 374.91 65 5.77

Total 461.84 69

Factor 3


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).


Preferences across monthly income household category


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


2.91*Within Groups 213.54 65 3.29

Total 251.77 69

Factor 2


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


2.13Within Groups 367.30 65 5.65

Total 415.37 69

Factor 5


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.

AP-18

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