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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
Volume 3, Issue 3, September- December (2012)

ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 3, Issue 3, September- December (2012), pp. 72-91                        IJM
© IAEME: www.iaeme.com/ijm.asp
Journal Impact Factor (2012): 3.5420 (Calculated by GISI)
                                                                          ©IAEME
www.jifactor.com




       AN EMPIRICAL ANALYSIS TO STUDY THE INFLUENCE OF
        BEHAVIOURAL PATTERN OF MEN ON FORMAL SHOES

                                        Mrs. Uma V.R
                                       Assistant Professor
                                   Department of Commerce
                                        Christ University
                                  Bangalore, India - 560 029
                                Email: uma.vr@christuniversity.in

                                      Dr. M. I. Saifil Ali
                                     Professor & Director
                               School of Management (DASM)
                            Dhaanish Ahmed College of Engineering
                                       Chennai - 601301
                               Email: saifil_ali_33@yahoo.co.in


ABSTRACT

The present study attempts to present a model in which the footwear attributes are associated
with the behavioural patterns of the consumers. The behavioural pattern of the consumers was
studied through the AIO statements. The consumers were profiled into eleven clusters using
factor analysis namely stylistic, confident, cautious shoppers, traditional, relaxed, optimistic,
strivers, systematic, dominant, spiritual and stay trim. Regression scores were used to assign the
respondents into the respective components that were extracted through factor analysis.
Reliability Test and KMO Test were conducted to check the reliability and adequacy of the
sample size. Further only those variables that qualified the collinearity test were alone subject to
regression analysis. Through ANOVA test it was observed that significant differences existed
among the consumers within the clusters. Therefore the AIO statements were considered as
independent variables that were regressed against ten selected footwear attributes. The study
finds that consumers’ footwear preferences varied according to their behavioural patterns. This
model can help the retailers and manufacturers to revisit their existing strategies of targeting the
consumers based on demography or material construction.

Key Words: Footwear, Behavioral pattern, Regression, Lifestyle, Consumer, Clusters

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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

1.1 INTRODUCTION

With low production cost, abundant supply of raw material, evolving retail system, buying
patterns and huge consumption market, this sector is posed to grow to great heights. India being
a country of artisans is known for its traditional craft of footwear making. Some of the traditional
footwear created by village craftsmen include leather chappals in Kohlapur' embroidered Juttis in
Jodhpur, Indo-Tibetan felt boots in Sikkim and vegetable fibre shoes in Ladakh. The industrial
policy 1967 reserved the leather industry including footwear only for small scale sectors. It was
only during the mid 1970s, 100% export oriented footwear units in large scale sector were
promoted. From June 2001 onwards the Government of India de-reserved the leather sector.
During the past four decades starting from the year 1981 – 1982, the export of footwear from
India had increased tremendously. Though India has a negligible proportion of exports in world
trade, it is the second largest producer of footwear next to China. India accounts for 14% of the
global annual footwear production of 14.52 billion pairs. India manufactures around 2065million
pairs of footwear every year of which 909 million pairs are made of leather, 1056 million pairs of
non leather footwear and 100 million pairs of shoe uppers. Nearly 70 percent of the labour
constituting around 15 lakh people are employed in the unorganised sector majority of them are
rural artisans, cottage and household units, while the organised sector accounts for remaining 30
percent and employs over 5 lakh people.
The Indian consumer markets are growing and changing rapidly in terms of its nature and
composition. With the revolution taking place in the distribution system through entry of super
markets, shopping malls, chain stores etc in the metros, small cities and towns the potential for
lifestyle products have increased drastically (S L Rao, 2000). With the change in the lifestyle
patterns among the people especially the youth, this product has also undergone a tremendous
transition in terms of its character. Though Indians have not been the ones to spend on items like
footwear, for the past two decades due to liberalization, there has been a tremendous change in
the buying habits of the consumers. More than sixty international brands are sourced from India.
Most of these brands are manufactured in Agra, Kanpur or Chennai footwear clusters.

1.2 REVIEW OF LITERATURE

India is a country of artisans comprising of footwear clusters spread in many parts of the country.
These clusters predominantly consist of small-scale manufacturers with skilled craftsmen, out
dated technologies having less access to automation. In a developing country like India, there
exist tremendous opportunity for combining the artisanal touch with high technology (knorringar
1998). Unlike India after Liberalization the textile and footwear industries collapsed in
Zimbabwe due to improper restructuring and low labour productivity (Carmody 1998) where as
countries like India, Korea and Taiwan enjoy high labour productivity. The author finds the
African market to be generally uncompetitive due to shrinking markets, low labour productivity,
and poor infrastructure with poor political instability due to which foreign investment is scarce
when compared to the Asian countries. Heather (1998) draws attention to the existence of
fashion consciousness of the people towards footwear even before 8000 years ago. The author
throws light on the evolution of the bear-fur shoes that the Japanese Samurai used to wear to the
platform sandals that is worn by people today are all due to the fashion desire. The article was
the result of excavation of shoes dated more than 8000 years from the Missouri cave. The
complex weaving and design of the excavated shoes reveal that the people were fashion


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

conscious as we are today and specialized artisans and craftsmen existed even at that time. The
study by Troy (2000) stipulates the need for appropriate footwear as they are more than just
shoes. According to the author shoes give identity and image and is also a symbol of status.
Despite the benefits, diabetes patients refrain from purchase of therapeutic footwear as they are
not attractive with limited colours and designs (Carolyn et al 2002, Gautham et al, 2004).
Miranda (2009) explores the rise of Bata as a major player in the footwear sector. Post World
War I, the international trade in footwear took a different turn. The large footwear exporting
countries like United States and UK gradually became world’s leading importers.

1.3 STATEMENT OF THE PROBLEM

Though the Indian consumers have become discerning and brand conscious, but in this sector the
proliferation of the unorganized sector seem to be higher. The unorganized sector dominates the
industry posing a threat to the organised players. In the organised sector, men’s footwear
accounts for only half of the total market. Therefore it is clear that only 50% - 55% of the sales
take place in the organized sector even in the men’s sector. Though footwear is considered as
lifestyle enhancement product, the manufacturers and retailers have failed to understand this.
Still the traditional segmentation patterns are followed in this industry, which include materials
used for construction of the footwear, usage patterns and demographics. Also there are
innumerable literatures that focus on trade policies followed in the footwear market in
international countries, treatment of workers in the footwear industry, therapeutic use of
footwear, supply chain patterns etc but there are hardly any study that explores the consumer
behaviour and their association towards the footwear preferences. Behavioral segmentation
though has been used in many other products like apparels, insurance, real estate etc., but not in
the footwear sector. The present study is an attempt to fill the gap. This sector is a highly
promising one with less knowledge about its customers.

1.4 OBJECTIVES

From the problems stated above the objectives have been derived as under:
   • To profile men into different clusters based on their activities, interest and opinions
   • To examine the differences that exists in the preferences towards the formal footwear
       attributes according to the consumers’ behavioural patterns

1.5 STUDY AREA

The study was conducted in Bangalore being the capital of Karnataka and a fast emerging
metropolitan city. Further it is the third most populous city and stands fifth in the urban
population. As on 2011 the total population of the city stood at 8,425,970. Geographically the
city is divided into 5 regions namely East, West, North, South and Central Bangalore. Bangalore
has only 41% of local population and the rest of them belong to other states and countries
especially from Europe. Hence, it is vivid that Bangalore has a population with diverse profiles.
Therefore the city of Bangalore has been selected for the study purposively.




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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

1.6 SAMPLE RESPONDENTS

The respondents for the study include men between the age group of 20 – 55 yrs and between the
income classes of Rs 12000 to Rs 200000 per month. The respondents were drawn randomly
from the various strata of East, West, North, South and Central Bangalore. 500 men were
selected from each stratum totaling to 2500 men. Out of the total respondents only 2074 men
qualified for the study as the responses furnished by the rest of them was incomplete hence were
eliminated.
1.7 SURVEY INSTRUMENT

Primary data was collected through distribution of questionnaires. The questionnaire comprised
of three sections. Section I includes 50 statements (Mitchell, A. 1983, Anderson, W.T. and
Golden, L. 1984; Hanspal et al, 1999; Hanspal et al, 2000 ) that would help in profiling the
customers into behavioural clusters based on the activities they normally engage in their day to
day life, interests and opinions on certain common issues. These statements were to be rated in a
7 point likert scale. Section II comprised of their demographic details and the attributes they
expect their formal and casual footwear to possess. These attributes were arrived after an
exploratory study. The exploratory study was conducted to a group of 20 members. The group
members comprised of consumers who belonged to different age groups. They were asked to list
the attributes they generally preferred their footwear to possess. Eighteen attributes were listed.
Though all the eighteen attributes were included in the instrument only ten attributes were
selected for analysis. These ten attributes were selected based on the ranking given by majority
of the group members. These attributes were also to be rated in a 7 point likert scale. The
instrument so constructed was pre-tested on thirty respondents to find out if the questions framed
had sufficient clarity. Then based on their suggestions the final instrument was constructed and
administered.

1.8 STATISTICAL TOOLS USED

The statistical tools used for the study include Reliability Test, KMO test, Factor analysis,
ANOVA, and Multiple Regression Analysis. Statiscal packages such as SPSS 16 and EXCEL
were employed in the study.

1.9 SCOPE

The study will be helpful for the retailers to restructure their product offerings. The report will
also be useful for new retailers for designing their market strategies. It also offers a scope for
further research as there is not much study done in this area. Many international brands are
looking out for a place of business in India, this study will help them in understanding the
consumer characteristics and the factors that influence their purchase decision. The study can be
extended to global markets as similar purchase patterns may exist in multiple countries.




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Volume 3, Issue 3, September- December (2012)

1.10 ANALYSIS:

1.10.1 CONSUMER PROFILING
For profiling the respondents on the basis of their behaviour, factor analysis was employed on
the 50 AIO statements (See Appendix1). Initially inorder to test the reliability of these AIO
statements, Cronbach’s alpha score was computed. The Cronbach’s alpha on 50 AIO statements
revealed a score of 0.803 showing that the statements were reliable enough for further analysis.
Also Kaiser-Mayo-Olkin (KMO) Test was conducted to measure the adequacy of sample size.
The test generated a score of 0.694. Thus KMO test also proved that the samples were adequate
enough to conduct factor analysis. On employing factor analysis 11 factors that constitutes 52%
of the variance was considered for the study. Further for authentication Scree plot was also read.
Only those factors that constituted Eigen value above 1 were considered as principal component
analysis was employed. Varimax rotation was used to extract the factors with factor loadings
greater than +/- 0.30.


Table 1.1 Components with total and cumulative variance

                                  Initial Eigen values

Components       Total      % of Variance           Cumulative %
1                5.81           11.63                  11.63
2                3.20            6.40                  18.03
3                3.07            6.13                  24.16
4                2.46            4.92                  29.09
5                1.98            3.96                  33.04
6                1.87            3.74                  36.78
7                1.68            3.36                  40.14
8                1.56            3.11                  43.25
9                1.40            2.80                  46.06
10               1.39            2.79                  48.85
11               1.34            2.69                  51.54


As Varimax rotation was utilized, those statements which had a factor loading of 0.3 and above
was assigned to the respective component. Further case wise regression scores were considered
to classify each individual to the respective components. The 11 components that were extracted
include Stylistic, Independents, Economicals, Traditional, Socialising, Globe trotters, Strivers,
Systematic and Dominant (See Table 4.5). It should be noted that the components have been
named according to the variable (Statement) with higher rotated factor loadings.




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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.2 Statements with Rotated Factor Loadings and assignment to respective
components

                           Components                                  Rotated Factor
                                                                       Loadings
Component 1: Stylistic
I like to spend a year in a foreign country                            0.72
I have one or more outfits that are of very latest style               0.72
I pay cash for everything I buy                                        0.68
I enjoy stylistic dresses                                              0.65
The most important of life is to dress smartly                         0.58
I am fashionable in the eyes of others                                 0.58
Component 2: Confident
I have more self confidence than most people                           0.77
As far as possible after marriage nuclear family is better             0.74
I am more independent than most people                                 0.71
I have a lot of personal ability                                       0.64
Component 3: Cautious Shoppers
I visit many shops before I finalise my sales                          0.81
I am active in all social functions                                    0.64
I check the prices even for small items                                0.61
I watch advertisements for announcements of sales                      0.56
One should bargain before a purchase                                   0.40
I prefer my friends to spend when I am out on a party                  0.37
Component 4: Traditional
Women are dependents and need men’s protection                         0.73
A women should not work if her husband does not like her to work       0.72
Looking after the house is primarily a woman’s responsibility          0.59
In the evenings, it is better to stay at home                          0.53
Component 5: Relaxed
I drink soft drinks several times in a week                            0.76
I spend a lot of time with friends talking about brands and products   0.70
I participate in sports activities                                     -0.53
One should have own credit/debit cards                                 0.43
Component 6: Optimistic
Think I will have more money to spend next year                        0.83
I want to take a trip around the world                                 0.77
Component 7: Strivers
Doing nothing makes me feel uncomfortable                              0.77
I will take some courses to brighten my future                         0.45
Component 8: Systematic
One should always keep the house neat and clean                        0.66
One must save for the rainy day                                        0.63
A distinctive living attracts me                                       0.52


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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Component 9: Dominant
Friends often come to me for advice                                        0.66
Giving dowry in marriage is a tradition and cannot be done away            0.54
I would go for a walk than sit idle                                        0.52
I can be considered a leader                                               0.39
Component 10: Spiritual, Diet conscious and Socialising
I eat only home food                                                       0.59
Spiritual values are important than material things                        0.58
I can mingle with strangers easily                                         0.50
Component 11: Stay Trim (6%)
I skip breakfast regularly                                                 0.77
I like to watch games than any other entertainment channels                0.71

For the purpose of the study the AIO statements were considered as predictor variables and the
footwear attributes were considered the criterion variables. Further only those statements that
satisfied the collinearity test was selected. ANOVA test revealed the existence of significant
differences among the consumers in the same component. Therefore multiple regressions were
employed to study the association between the behavioural pattern of consumers and the
preferences towards formal footwear attributes.

COMPONENT 1 – STYLISTIC CONSUMERS
Table 1.3: COLLINARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES
PREDICTOR VARIABLES                                                   TOLERANCE VIF*
I pay cash for everything I buy (Budgeted spenders)                               .726 1.377
I enjoy stylistic dresses (Stylistic)                                             .900 1.112
The important part of life is to dress smartly (Smartly dressed)                  .943 1.060
I like to spend a year in a foreign country (Foreign land)                        .675 1.482
I am fashionable in the eyes of others (Fashionable)                              .703 1.422


Table 1.4 Multiple Regression Analysis for Stylistic Consumers (Component 1) and Formal
Footwear Attributes

                                               FORMAL FOOTWEAR PREFERENCES
Variables             B       SE        Beta    t-       Variables       B     SE      Beta    t-value
                                                value
Criterion Variable                                       Criterion
Coordinated Colours   5.23    1.99              2.62  ** Family          -1.20 1.62            -.74
Predictor Variables                                      Predictor
Budgeted spenders     -1.02   .25       -.31    -4.1** Budgeted spenders -.439 .203    -.163   -2.17*
Stylistic              -.09   .23       -.03      -.43   Stylistic       .142  .186    .052    .76
Smart Dressers          .54   .13        .28    4.29  ** Smart Dressers  .288  .102    .186    2.82**
Foreign land           -.35   .22       -.13     -1.62   Foreign land    .902  .176    .400    5.13**
Fashionable             .89   .22        .31             Fashionable     .131  .176    .056    .74


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Volume 3, Issue 3, September- December (2012)

                                             4.11**
Criterion Variable                                    Criterion
Elegance              1.19    .60            1.98*    Posture              -1.10    1.07           -1.03
Predictor Variables                                   Predictor
Budgeted spenders     .26     .08      .18   3.43**   Budgeted spenders    -.015    .133   -.007   -.12
Stylistic             .01     .07      .00   .07      Stylistic            -.540    .122   -.228   -4.41**
Smart Dressers        .03     .04      .04   .84      Smart Dressers       -.149    .067   -.112   -2.22*
Foreign land          -.51    .07     -.42   -7.8**   Foreign land         1.28     .116   .660    11.08**
Fashionable           1.01    .07      .81   15.4**   Fashionable          .422     .116   .213    3.64**
Criterion Variable                                    Criterion
Comfort               6.34    .417           15.2**   Ambience             .244     1.35           .18
Predictor Variables                                   Predictor
Budgeted spenders     .027    .052   .042    .521     Budgeted spenders    .302     .169   .127    1.79
Stylistic             -.065   .048   -.09    -1.35    Stylistic            .747     .155   .307    4.81**
Smart Dressers        -.061   .026   -.16    -2.31*   Smart Dressers       .182     .085   .133    2.14*
Foreign land          .046    .045   .084    1.01     Foreign land         -1.09    .147   -.550   -7.48**
Fashionable           .115    .045   .208    2.54*    Fashionable          .718     .147   .352    4.88**
Criterion Variable                                    Criterion Variable
Branded               3.98    .994           4.01**   Salesmen             .263     1.35           .194
Predictor Variables                                   Predictor
Budgeted spenders     .465    .124   .268    3.74**   Budgeted spenders    .364     .169   .153    2.15*
Stylistic             -.226   .114    -.13   -1.98*   Stylistic            .618     .156   .253    3.97**
Smart Dressers        -.067   .063    -.07   -1.07    Smart Dressers       .150     .085   .109    1.75
Foreign land          -.483   .108    -.33   -4.5**   Foreign land         -1.09    .147   -.549   -7.45**
Fashionable           .629    .108   .423    5.81**   Fashionable          .787     .148   .385    5.33**
Criterion Variable                                    Criterion Variable
Friends               -1.54   1.73           -.89     Amenities            11.3     1.88           6.01**
Predictor Variables                                   Predictor
Budgeted spenders     -.382   .217   -.13    -1.76    Budgeted spenders    -.991    .236   -.305   -4.2**
Stylistic             -.051   .199   -.02    -.26     Stylistic            .696     .217   .210    3.21**
Smart Dressers        -.353   .109   -.20    -3.2**   Smart Dressers       .207     .119   .111    1.74
Foreign land          .913    .188   .356    4.85**   Foreign land         -.785    .204   -.289   -3.84**
Fashionable           .907    .189   .346    4.80**   Fashionable          -.128    .205   -.046   -.62
** Significant at 1% level, * Significant at 5% level

COMPONENT 2- CONFIDENT CONSUMERS

Table 1.5 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                          TOLERANCE VIF*
As far as possible nuclear family is better (Nuclear Family)        .847 1.181
I have more self confidence than most people (Confident)            .789 1.267
I am more independent (Independent)                                                .821 1.218
I have a lot of personal ability (Skilled)                                         .900 1.111
*Variance Inflation Factor




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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.6 Multiple Regression Analysis of Confident Men (Component 2) and Formal
Footwear Attributes

                                                   FORMAL FOOTWEAR
Variables             B       SE     Beta    t-value Variables       B       SE     Beta    t-value
Criterion Variable                                    Criterion
Coordinated Colours   .995    1.09           .911     Family         8.16    1.46           5.59**
Predictor Variables                                   Predictor
Nuclear Family        .014    .092   .010    .155     Nuclear Family -.42    .123   -.220   -3.4**
Confident             -.033   .122   -.018   -.274    Confident      .360    .163   .148    2.22*
Independent           .708    .141   .328    5.019** Independent     .191    .188   .066    1.01
Skilled               -.023   .122   -.012   -.186    Skilled        -.67    .163   -.257   -4.1**
Criterion Variable                                    Criterion
Elegance              4.57    .804           5.682** Posture         6.99    1.41           4.94**
Predictor Variables                                   Predictor
Nuclear Family        -.208   .068   -.202   -3.07** Nuclear Family -.21     .119   -.117   -1.75
Confident             -.016   .090   -.012   -.180    Confident      .292    .157   .128    1.853
Independent           .217    .104   .140    2.094* Independent      -.35    .183   -.129   -1.89
Skilled               .234    .090   .166    2.606** Skilled         -.04    .158   -.016   -.243
Criterion Variable                                    Criterion
Comfort               5.82    .594           9.803** Ambience        9.19    1.49           6.157**
Predictor Variables                                   Predictor
Nuclear Family        -.058   .050   -.075   -1.160 Nuclear Family -.374     .126   -.194   -2.976**
Confident             -.273   .066   -.276   -4.14** Confident       .447    .166   .181    2.689**
Independent           .284    .077   .242    3.700** Independent     -.425   .193   -.146   -2.206*
Skilled               .171    .066   .161    2.575** Skilled         -.339   .167   -.128   -2.034*
Criterion Variable                                    Criterion
Branded               -.319   1.00           -.318    Salesmen       4.85    1.33           3.662**
Predictor Variables                                   Predictor
Nuclear Family        -.299   .085   -.213   -3.54** Nuclear Family -.037    .112   -.022   -.330
Confident             .559    .112   .312    5.001** Confident       .380    .148   .178    2.575**
Independent           .647    .130   .306    4.996** Independent     -.345   .171   -.137   -2.02*
Skilled               -.014   .112   -.007   -.126    Skilled        .043    .148   .019    .289
Criterion Variable                                    Criterion
Friends               11.5    1.57           7.331** Amenities       6.69    1.11           6.018**
Predictor Variables                                   Predictor
Nuclear Family        -.493   .132   -.238   -3.72** Nuclear Family -.397    .094   -.272   -4.23**
Confident             .196    .175   .074    1.121    Confident      -.236   .124   -.127   -1.91
Independent           -.556   .203   -.178   -2.74** Independent     .005    .144   .002    .036
Skilled               -.280   .175   -.099   -1.595 Skilled          .152    .124   .077    1.225
** Significant at 1% level, * Significant at 5% level

COMPONENT 3 – CAUTIOUS SHOPPERS
Table 1.7 COLLINARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES
PREDICTOR VARIABLES                           TOLERANCE VIF*
I am active in all social functions (Social)         .810 1.235
I visit many shops before I finalise my sales (Cautious buyers)                .800 1.250
I check the prices even for small items (Price Conscious)                      .911 1.098
*Variance Inflation Factor



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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.8 Multiple Regression Analysis of Cautious Shoppers (Component 3) and Formal
Footwear Attributes

                                                   FORMAL FOOTWEAR
Variables             B       SE     Beta    t-value Variables        B       SE     Beta    t-value
Criterion Variable                                    Criterion
Coordinated Colours   4.59    1.32           3.485** Family           4.99    1.29           3.848**
Predictor Variables                                   Predictor
Social                .171    .159   .075    1.071    Social          .839    .157   .366    5.345**
Cautious buyers       -.552   .189   -.207   -2.92** Cautious buyers -.703    .186   -.261   -3.782**
Price Conscious       .435    .102   .285    4.289** Price Conscious -.066    .100   -.042   -.657
Criterion Variable                                    Criterion
Elegance              2.23    .736           3.030** Posture          5.95    .961           6.196**
Predictor Variables                                   Predictor
Social                .230    .089   .173    2.587** Social           -.165   .116   -.100   -1.421
Cautious buyers       .005    .105   .003    .051     Cautious buyers -.169   .138   -.087   -1.230
Price Conscious       .373    .057   .415    6.577** Price Conscious .298     .074   .268    4.036**
Criterion Variable                                    Criterion
Comfort               4.21    .609           6.908** Ambience         1.34    .981           1.370
Predictor Variables                                   Predictor
Social                -.216   .074   -.199   -2.93** Social           .350    .119   .209    2.955**
Cautious buyers       .463    .087   .362    5.302** Cautious buyers -.133    .140   -.067   -.947
Price Conscious       .096    .047   .131    2.042* Price Conscious .294      .076   .260    3.891**
Criterion Variable                                    Criterion
Branded               2.15    .932           2.303* Salesmen          .367    1.05           .347
Predictor Variables                                   Predictor
Social                .425    .113   .253    3.773** Social           .523    .128   .289    4.091**
Cautious buyers       -.452   .133   -.228   -3.38** Cautious buyers .027     .152   .013    .177
Price Conscious       .470    .072   .414    6.544** Price Conscious .135     .081   .110    1.651
Criterion Variable                                    Criterion
Friends               1.17    1.08           1.084    Amenities       -2.33   1.06           -2.190*
Predictor Variables                                   Predictor
Social                .628    .131   .329    4.81**   Social          .753    .129   .391    5.851**
Cautious buyers       -.427   .155   -.190   -2.76** Cautious buyers .134     .152   .059    .877
Price Conscious       .406    .083   .315    4.879** Price Conscious .200     .082   .154    2.441*
** Significant at 1% level, * Significant at 5% level

COMPONENT 4 – TRADITIONAL

Table 1.9 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                                           TOLERANCE VIF*
A woman should not work if her husband does not like her to work
                                                                                         .859 1.164
outside the house (dominating)
Women are dependants and need men’s protection (protectionist)                           .829 1.207
Looking after the house is primarily a woman’s responsibility
                                                                                         .892 1.121
irrespective of whether she is working or not (egotistic)
In the evenings, it is better to stay at home rather than going out
(conservative)                                                                           .900 1.111
*Variance Inflation Factor


                                                  81
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Volume 3, Issue 3, September- December (2012)

Table 1.10 Multiple Regression Analysis of Traditional (Component 4) and Formal
Footwear Attributes
                                                   FORMAL FOOTWEAR
Variables             B       SE     Beta    t-value Variables      B       SE     Beta    t-value
Criterion Variable                                    Criterion
Coordinated Colours   1.34    .782           1.718    Family        1.69    .563           3.010**
Predictor Variables                                   Predictor
Dominating            .249    .085   .189    2.917** Dominating     .268    .062   .253    4.351**
Protectionist         .114    .093   .081    1.236    Protectionist -.047   .067   -.042   -.709
Egotistic             -.060   .101   -.038   -.592    Egotistic     -.049   .072   -.038   -.674
Conservative          .392    .071   .338    5.550** Conservative   .507    .051   .544    9.963**
Criterion Variable                                    Criterion
Elegance              1.43    .457           3.128** Posture        1.34    .387           3.464**
Predictor Variables                                   Predictor
Dominating            .118    .050   .141    2.358* Dominating      .321    .042   .399    7.588**
Protectionist         .288    .054   .323    5.317** Protectionist  .276    .046   .321    6.006**
Egotistic             .216    .059   .215    3.669** Egotistic      .171    .050   .177    3.434**
Conservative          .102    .041   .139    2.468* Conservative    .018    .035   .025    .501
Criterion Variable                                    Criterion
Comfort               4.00    .425           9.422** Ambience       1.83    .618           2.968**
Predictor Variables                                   Predictor
Dominating            -.044   .046   -.060   -.951    Dominating    .217    .068   .207    3.206**
Protectionist         .206    .050   .265    4.096** Protectionist  -.025   .073   -.023   -.346
Egotistic             .251    .055   .287    4.592** Egotistic      .200    .080   .160    2.518*
Conservative          .002    .038   .003    .055     Conservative  .270    .056   .295    4.842**
Criterion Variable                                    Criterion
Branded               -.45    .394           -1.128 Salesmen        2.47    .596           4.136**
Predictor Variables                                   Predictor
Dominating            .358    .043   .397    8.306** Dominating     .080    .065   .080    1.226
Protectionist         .388    .047   .405    8.318** Protectionist  .327    .071   .305    4.626**
Egotistic             .050    .051   .046    .984     Egotistic     .127    .077   .106    1.658
Conservative          .238    .036   .301    6.690** Conservative   .016    .054   .018    .296
Criterion Variable                                    Criterion
Friends               1.48    .614           2.413* Amenities       2.68    .617           4.351**
Predictor Variables                                   Predictor
Dominating            -.028   .067   -.027   -.418    Dominating    .059    .067   .060    .881
Protectionist         .252    .073   .224    3.469** Protectionist  .151    .073   .143    2.068*
Egotistic             .376    .079   .296    4.752** Egotistic      .157    .079   .132    1.978*
Conservative          .097    .056   .105    1.754    Conservative  .068    .056   .078    1.214
** Significant at 1% level, * Significant at 5% level

COMPONENT 5 - RELAXED
Table 1.11 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES
PREDICTOR VARIABLES                                                  TOLERANCE VIF*
One should have his/her own credit/debit cards (Practical)                  .952 1.051
I spend a lot of time with friends talking about brands and products
(Brand Analyst)                                                             .965 1.036
I drink soft drinks several times a week (unhealthy)                        .839 1.192
I do not participate in sports activities (non playful)                     .873 1.146
*Variance Inflation Factor



                                                  82
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Volume 3, Issue 3, September- December (2012)

Table 1.12 Multiple Regression Analysis of Relaxed (Component 5) and Formal Footwear
Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables      B       SE     Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours 4.83         1.38               3.510** Family         2.22    1.69           1.313
Predictor Variables                                          Predictor
Practical               -.015    .071 -.015         -.216    Practical     -.184   .087   -.145   -2.112*
Brand Analyst           .054     .112 .033          .477     Brand Analyst .512    .138   .251    3.700**
Unhealthy               .008     .157 .004          .049     Unhealthy     -.050   .193   -.019   -.261
Nonplayful              -.302    .131 -.169         -2.303* Nonplayful     .314    .161   .139    1.946
Criterion Variable                                           Criterion
Elegance                3.92     1.14               3.451** Posture        -.622   1.32           -.470
Predictor Variables                                          Predictor
Practical               -.143    .058 -.165         -2.443* Practical      -.123   .068   -.118   -1.804
Brand Analyst           .005     .093 .003          .050     Brand Analyst .574    .108   .344    5.301**
Unhealthy               .183     .129 .102          1.417    Unhealthy     .327    .151   .151    2.166*
Nonplayful              .468     .108 .305          4.327** Nonplayful     .330    .126   .179    2.614**
Criterion Variable                                           Criterion
Comfort                 7.39     .731               10.10** Ambience       -3.25   1.26           -2.577*
Predictor Variables                                          Predictor
Practical               -.082    .038 -.151         -2.181* Practical      .182    .065   .168    2.811**
Brand Analyst           .003     .060 .004          .057     Brand Analyst .522    .103   .301    5.067**
Unhealthy               -.010    .083 -.009         -.124    Unhealthy     .710    .143   .315    4.945**
Nonplayful              -.201    .070 -.209         -2.89** Nonplayful     -.314   .120   -.164   -2.617**
Criterion Variable                                           Criterion
Branded                 7.59     1.04               7.288** Salesmen       -3.25   1.25           -2.601**
Predictor Variables                                          Predictor
Practical               -.134    .054 -.154         -2.500* Practical      .197    .064   .186    3.074**
Brand Analyst           -.390    .085 -.281         -4.58** Brand Analyst  .757    .102   .445    7.421**
Unhealthy               .307     .119 .170          2.588** Unhealthy      .389    .142   .176    2.736**
Nonplayful              -.476    .099 -.309         -4.79** Nonplayful     -.014   .119   -.007   -.117
Criterion Variable                                           Criterion
Friends                 5.78     1.30               4.448** Amenities      3.37    1.60           2.100*
Predictor Variables                                          Predictor
Practical               -.309    .067 -.313         -4.62** Practical      -.470   .083   -.366   -5.691**
Brand Analyst           .137     .106 .087          1.288    Brand Analyst .008    .131   .004    .065
Unhealthy               -.026    .148 -.013         -.179    Unhealthy     .552    .183   .207    3.021**
Nonplayful              .185     .124 .106          1.491    Nonplayful    .221    .153   .097    1.449
** Significant at 1% level, * Significant at 5% level




                                                     83
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Volume 3, Issue 3, September- December (2012)

COMPONENT 6 – OPTIMISITIC

Due to multi collinearity only one variable was considered for regression analysis

Table 1.13 Regression Analysis of Optimistic (Component 6) and Formal Footwear
Attributes

                                                          FORMAL FOOTWEAR
Variables             B        SE     Beta          t-value Variables       B       SE     Beta     t-value
Criterion Variable                                           Criterion
Coordinated Colours     6.46     .868               7.447** Family          4.88    1.23            3.970**
Predictor Variables                                          Predictor
Globe Trippers          -.184    .130 -.129         -1.418 Variables        -.134   .184   -.067    -.728
                                                             Globe Trippers
Criterion Variable                                           Criterion
Elegance                7.93     .941               8.423** Posture         6.87    1.31            5.247**
Predictor Variables                                          Predictor
Globe Trippers          -.369    .141 -.234         -2.62** Globe Trippers  -.296   .196   -.138    -1.511
Criterion Variable                                           Criterion
Comfort                 6.96     .343               20.31** Ambience        .749    .844            .886
Predictor Variables                                          Predictor
Globe Trippers          -.045    .051 -.080         -.871    Globe Trippers .570    .126   .383     4.505**
Criterion Variable                                           Criterion
Branded                 7.59     .918               8.261** Salesmen        7.29    .708            10.296**
Predictor Variables                                          Predictor
Globe Trippers          -.330    .138 -.215         -2.397* Globe Trippers  -.246   .106   -.209    -2.320*
Criterion Variable                                           Criterion
Friends                 6.97     .929               7.496** Amenities       -1.92   1.14            -1.684
Predictor Variables                                          Predictor
Globe Trippers          -.324    .139 -.210         -2.328* Globe Trippers  .810    .170   .401     4.753**
** Significant at 1% level, * Significant at 5% level

COMPONENT 7 – STRIVERS

Table 1.14 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                                       TOLERANCE VIF*
Doing nothing makes me feel uncomfortable (Active)                        .974      1.027
I will take some courses to brighten my future (Hard Working) .974                          1.027
*Variance Inflation Factor




                                                      84
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Volume 3, Issue 3, September- December (2012)

 Table 1.15 Multiple Regression Analysis of Strivers (Component 7) and Formal Footwear
                                                Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables     B       SE     Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours -4.58        2.36               -1.945 Family         5.06    1.66           3.054**
Predictor Variables                                          Predictor
Active                  1.68     .242 .539          6.949** Active        .740    .170   .345    4.352**
Hard Working            -.260    .214 -.094         -1.213 Hard Working   -.680   .151   -.357   -4.512**
Criterion Variable                                           Criterion
Elegance                5.14     1.71               3.005** Posture       11.2    2.77           4.035**
Predictor Variables                                          Predictor
Active                  .060     .176 .032          .342     Active       -.360   .284   -.117   -1.268
Hard Working            .080     .156 .048          .514     Hard Working -.480   .252   -.175   -1.907
Criterion Variable                                           Criterion
Comfort                 3.48     .607               5.736** Ambience      6.74    2.22           3.030**
Predictor Variables                                          Predictor
Active                  .420     .062 .536          6.745** Active        -.040   .228   -.016   -.175
Hard Working            .060     .055 .086          1.087    Hard Working -.220   .202   -.101   -1.087
Criterion Variable                                           Criterion
Branded                 13.8     1.93               7.128** Salesmen      9.38    2.56           3.666**
Predictor Variables                                          Predictor
Active                  -.300    .199 -.128         -1.510 Active         -.480   .263   -.169   -1.828
Hard Working            -.900    .176 -.432         -5.11** Hard Working  -.140   .233   -.056   -.601
Criterion Variable                                           Criterion
Friends                 20.7     2.64               7.828    Amenities    8.38    2.87           2.917**
Predictor Variables                                          Predictor
Active                  -1.28    .271 -.388         -4.72** Active        1.02    .295   .264    3.460**
Hard Working            -1.04    .240 -.355         -4.33** Hard Working  -1.64   .261   -.478   -6.276**
** Significant at 1% level, * Significant at 5% level

COMPONENT 8 – SYSTEMATIC

Table 1.16 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                        TOLERANCE VIF*
One should always keep the house neat and clean (Neatness)        .821 1.219
A fancy and distinctive living attracts me (Distinctive)         .946 1.057
One must save for the rainy day (Cautious)                                        .821 1.217
*Variance Inflation Factor




                                                    85
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.17 Multiple Regression Analysis of Systematic (Component 8) and Formal
Footwear Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables    B       SE     Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours -5.19        3.85               -1.349 Family        -12.4   3.59           -3.44**
Predictor Variables                                          Predictor
Neatness                2.07     .600 .289          3.445** Neatness     2.48    .561   .363    4.42**
Distinctive             -.425    .157 -.212         -2.71** Distinctive  .028    .146   .015    .193
Cautious                -.278    .313 -.074         -.886    Cautious    .056    .293   .016    .193
Criterion Variable                                           Criterion
Elegance                -24.8    1.79               -13.9** Posture      -21.4   3.06           -6.99**
Predictor Variables                                          Predictor
Neatness                3.85     .278 .692          13.82** Neatness     3.79    .477   .567    7.95**
Distinctive             -.127    .073 -.08          -1.75    Distinctive .274    .125   .146    2.19*
Cautious                .746     .145 .257          5.19**   Cautious    -.167   .249   -.048   -.67
Criterion Variable                                           Criterion
Comfort                 .676     .927               .729     Ambience    -20.7   3.0            -6.89**
Predictor Variables                                          Predictor
Neatness                .419     .144 .219          2.89**   Neatness    2.36    .469   .357    5.03**
Distinctive             .109     .038 .202          2.83**   Distinctive .525    .122   .284    4.29**
Cautious                .360     .075 .360          4.78**   Cautious    .907    .245   .263    3.71**
Criterion Variable                                           Criterion
Branded                 -23.3    2.67               -8.74** Salesmen     3.39    2.36           1.44
Predictor Variables                                          Predictor
Neatness                1.93     .415 .254          4.65**   Neatness    .006    .367   .001    .016
Distinctive             -.239    .108 -.113         -2.21*   Distinctive -.008   .096   -.007   -.084
Cautious                2.52     .216 .636          11.65** Cautious     .270    .192   .123    1.41
Criterion Variable                                           Criterion
Friends                 -16.1    3.74               -4.30** Amenities    -14.2   4.31           -3.30**
Predictor Variables                                          Predictor
Neatness                3.09     .583 .424          5.30**   Neatness    2.38    .671   .293    3.55**
Distinctive             -.121    .152 -.059         -.794    Distinctive -.179   .175   -.079   -1.02
Cautious                .044     .304 .012          .146     Cautious    .499    .350   .117    1.43
** Significant at 1% level, * Significant at 5% level

COMPONENT 9 - DOMINANT

Table 1.18 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                                              TOLERANCE VIF*
Giving dowry in marriage is a tradition and cannot be done away with
(Conventional)                                                                              .962 1.039

Friends often come to me for advice (Opinion Leaders)                                       .975 1.025
I would go for a walk or do some exercise than sit idle (Stay Fit)                          .982 1.018
*Variance Inflation Factor




                                                    86
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.19 Multiple Regression Analysis of Dominant (Component 9) and Formal Footwear
                                                 Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables       B       SE      Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours -1.88        .738               -2.549* Family          3.86    .858            4.493**
Predictor Variables                                          Predictor
Conventional            .369     .057 .369          6.440** Conventional    -.112   .067    -.114   -1.676
Opinion leaders         .630     .076 .469          8.241** Opinion leaders .186    .089    .142    2.091*
Stay Fit                .292     .091 .182          3.213** Stay Fit        .144    .106    .092    1.364
Criterion Variable                                           Criterion
Elegance                2.17     .538               4.042** Posture         1.59    .688            2.315*
Predictor Variables                                          Predictor
Conventional            .305     .042 .435          7.304** Conventional    .227    .053    .272    4.240**
Opinion leaders         .349     .056 .370          6.264** Opinion leaders .350    .071    .313    4.914**
Stay Fit                .071     .066 .063          1.067    Stay Fit       .171    .085    .128    2.015*
Criterion Variable                                           Criterion
Comfort                 3.22     .360               8.926** Ambience        2.47    .625            3.953**
Predictor Variables                                          Predictor
Conventional            .213     .028 .444          7.620** Conventional    .319    .049    .413    6.567**
Opinion leaders         .196     .037 .305          5.264** Opinion leaders .215    .065    .208    3.330**
Stay Fit                .221     .044 .287          4.979** Stay Fit        -.034   .077    -.027   -.438
Criterion Variable                                           Criterion
Branded                 -2.50    .666               -3.76** Salesmen        2.68    .836            3.207**
Predictor Variables                                          Predictor
Conventional            .243     .052 .246          4.702** Conventional    .128    .065    .134    1.965
Opinion leaders         .705     .069 .531          10.22** Opinion leaders .275    .087    .215    3.180**
Stay Fit                .594     .082 .375          7.244** Stay Fit        .071    .103    .046    .688
Criterion Variable                                           Criterion
Friends                 -.077    .875               -.088    Amenities      3.38    1.02            3.317**
Predictor Variables                                          Predictor
Conventional            -.007    .068 -.006         -.106    Conventional   .110    .079    .096    1.396
Opinion leaders         .801     .091 .520          8.839** Opinion leaders -.175   .106    -.113   -1.654
Stay Fit                .166     .108 .090          1.537    Stay Fit       .236    .126    .128    1.878
** Significant at 1% level, * Significant at 5% level

         COMPONENT 10 - SPIRITUAL, DIET CONSCIOUS AND SOCIALISING

Table 1.20 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                                  TOLERANCE VIF*
Spiritual values are more important that material things (Spiritual)       .910 1.099
I eat only home food and do not like to eat out (Diet Conscious)           .897 1.114
I can mingle with strangers easily (Socialising)                                           .849 1.178
*Variance Inflation Factor




                                                      87
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.21 Multiple Regression Analysis of Spiritual, Diet conscious and Socialising
(Component 10) and Formal Footwear Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables       B       SE     Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours 2.30         .982               2.341* Family           3.28    1.19           2.753**
Predictor Variables                                          Predictor
Spiritual               -.208    .137 -.109         -1.512 Spiritual        .552    .166   .246    3.318**
Diet Conscious          .448     .114 .283          3.911** Diet Conscious  -.397   .139   -.214   -2.865**
Socialising             .207     .076 .201          2.704** Socialising     .083    .093   .069    .896
Criterion Variable                                           Criterion
Elegance                2.24     .734               3.056** Posture         .196    .866           .227
Predictor Variables                                          Predictor
Spiritual               -.090    .103 -.047         -.873    Spiritual      .208    .121   .110    1.720
Diet Conscious          -.003    .086 -.002         -.034    Diet Conscious .240    .101   .154    2.383*
Socialising             .749     .057 .732          13.11** Socialising     .463    .067   .456    6.87**
Criterion Variable                                           Criterion
Comfort                 7.52     .698 -.158         10.77** Ambience        .551    .910           .605
Predictor Variables                                          Predictor
Spiritual               -.206    .098 -.113         -2.108* Spiritual       .568    .127   .320    4.465**
Diet Conscious          -.122    .081 .257          -1.501 Diet Conscious   .319    .106   .217    3.008**
Socialising             .180     .054               3.312** Socialising     -.185   .071   -.194   -2.611**
Criterion Variable                                           Criterion
Branded                 1.98     1.01               1.971* Salesmen         -.949   .906           -1.048
Predictor Variables                                          Predictor
Spiritual               -.293    .141 -.144         -2.081* Spiritual       .920    .127   .485    7.267**
Diet Conscious          .658     .117 .391          5.613** Diet Conscious  .291    .106   .185    2.759**
Socialising             .183     .078 .168          2.343** Socialising     -.240   .070   -.235   -3.401**
Criterion Variable                                           Criterion
Friends                 .589     1.14               .518     Amenities      2.69    1.21           2.223*
Predictor Variables                                          Predictor
Spiritual               .538     .159 .252          3.387** Spiritual       .307    .170   .139    1.806
Diet Conscious          -.025    .132 -.014         -.190    Diet Conscious .018    .141   .010    .126
Socialising             .100     .088 .087          1.132    Socialising    -.086   .094   -.072   -.909
** Significant at 1% level, * Significant at 5% level

COMPONENT 11 – STAY TRIM

Table 1.22 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES

PREDICTOR VARIABLES                                                                 TOLERANCE VIF*
I skip breakfast regularly (Stay Trim)                                                    .985 1.015
I like to watch games than any other entertainment channels (Sports
Viewers)                                                                                       .985 1.015

*Variance Inflation Factor




                                                      88
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

Table 1.23 Multiple Regression Analysis of Stay Trim (Component 11) and Formal
Footwear Attributes

                                                          FORMAL FOOTWEAR
Variables               B        SE       Beta      t-value Variables       B       SE     Beta    t-value
Criterion Variable                                           Criterion
Coordinated Colours -.65         3.52               -.184    Family         -4.38   3.28           -1.337
Predictor Variables                                          Predictor
Stay Trim               -.270    .447 -.052         -.605    Stay Trim      1.68    .416   .336    4.028**
Sports Viewers          1.04     .313 .283          3.323** Sports Viewers  -.351   .292   -.101   -1.205
Criterion Variable                                           Criterion
Elegance                -7.24    2.45               -2.96** Posture         -5.59   3.01           -1.857
Predictor Variables                                          Predictor
Stay Trim               1.65     .311 .422          5.297** Stay Trim       1.67    .383   .361    4.362**
Sports Viewers          .203     .218 .074          .929     Sports Viewers -.213   .268   -.066   -.794
Criterion Variable                                           Criterion
Comfort                 3.49     1.37               2.548** Ambience        -8.99   3.73           -2.390*
Predictor Variables                                          Predictor
Stay Trim               -.047    .174 -.023         -.272    Stay Trim      2.28    .474   .393    4.819**
Sports Viewers          .470     .122 .324          3.855** Sports Viewers  -.318   .332   -.078   -.956
Criterion Variable                                           Criterion
Branded                 -9.03    2.22               -4.058 Salesmen         -21.1   3.08           -6.830**
Predictor Variables                                          Predictor
Stay Trim               1.41     .283 .384          4.975** Stay Trim       3.06    .392   .551    7.818**
Sports Viewers          .689     .198 .268          3.480** Sports Viewers  .753    .274   .194    2.745**
Criterion Variable                                           Criterion
Friends                 -5.97    2.24               -2.67** Amenities       -11.8   3.61           -3.270**
Predictor Variables                                          Predictor
Stay Trim               1.85     .285 .499          6.48**   Stay Trim      1.16    .459   .208    2.534**
Sports Viewers          -.314    .199 -.12          -1.58    Sports Viewers 1.18    .322   .299    3.657**
** Significant at 1% level, * Significant at 5% level

1.11 RESULT AND DISCUSSION

A brief discussion on the highest preferences of the consumers for formal shoes (based on the
highest Beta value and significant t-value) in each of the factors extracted is given below.
Component 1 comprised of stylistic consumers. Six variables (AIO statements) were loaded in
this component. Out of which five variables qualified for study due to multicollinearity.
Therefore the five types of consumers in this component include Budgeted spenders, stylistic,
smart dressers, foreign settlers and fashionables. From Table 1.4 it can be observed that the
Budgeted spenders preferred more of branded shoes for formal wear. The stylistic consumers
were more store conscious. They preferred to purchase formal wear from the store that had good
ambiences. The smart dressers preferred their formal shoes to coordinate with the colour of their
attire. The consumers who preferred to settle abroad preferred to wear formal shoes that
enhanced their postures. The fashionables preferred elegant formal shoes. Component 2
comprised of confident consumers. Four variables (AIO statements) were loaded in this
component. The four types of consumers in this category include Nuclear Family oriented,
Confident, Independent and Skilled. From Table 1.6 it can be observed that the consumers who
preferred to live in nuclear family were bound to purchase shoes from the store that exclusively
sold footwear and no other amenities. The confident consumers purchased formal shoes based on


                                                      89
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

brands. The independent consumers preferred to wear formal shoes with coordinated colours.
The skilled consumers who perceived that they had lot of personal ability preferred elegant and
comfortable shoes and they never consult their family in the purchase of formal shoes.
Component 3 was named as cautious shoppers. This component comprised of three types of
consumers namely social, cautious shoppers and price conscious. From Table 1.8 it can be
inferred that the social consumers who are very active in all the social functions preferred to
purchase formal shoes from the outlets that sold other amenities as well. The cautious shoppers
who visit many shops before they finalised their sales preferred to wear formal shoes that were
comfortable. The price conscious consumers preferred to wear formal shoes that were elegant
and branded. Component 4 named as traditional comprised of four types of consumers namely
dominating, protectionist, egotistic and conservative. From Table 1.10 it can be read that the
dominating types preferred to purchase formal shoes on the basis of brand and those that enhance
their postures. The protectionist also purchased formal shoes on the basis of brand. The Egotistic
consumers purchased formal shoes primarily after consultation with their friends. The
conservative consumers were very family oriented. Component 5 comprised of relaxed
consumers. The four types of consumers in this category include Practical, Brand Analyst,
Unhealthy lifestyle and Nonplayful. From Table 1.12 it can be observed that the practical
consumers preferred to purchase shoes from specialized store. The brand analysts were highly
influenced by the behaviour of the salesmen. The consumers who lead unhealthy lifestyle
preferred to purchase formal shoes from the outlets that had better ambiences. The consumers
who generally do not participate in sports activities preferred to purchase unbranded shoes.
Component 6 were named as optimistic consumers. Due to multicollinearity only one variable
qualified for the study. Therefore there was only one type of consumers i.e., the globe trippers
who were passionate about touring around the world. From Table 1.13 it can be observed that the
consumers in this category preferred to purchase formal shoes from the store that sold other
amenities also. Component 7 was named as strivers. The two types of consumers in this
category were active and hard working. The active consumers were colour conscious. The hard
working consumers preferred to purchase formal shoes from specialized store (Refer Table 1.15).
Component 8 was named as systematic. The three types of consumers in this category include,
men who preferred to keep their house neat and clean, men who were attracted towards a
distinctive lifestyle and men who were very cautious about saving money. The first category
preferred formal shoes that were elegant. The second category preferred to purchase formal
shoes from the outlets that had better ambiences. The cautious men who were very particular
about saving money preferred branded footwear (Table 1.17). Component 9 was named as
dominant. Under this category, there were the conventional consumers who primarily preferred
formal shoes that were comfortable. The opinion leaders and the Stay fit type of consumers in
this category were very brand conscious (Table 1.19). Component 10 comprised of spiritual and
diet conscious consumers. There were three types of consumers in this category, the spiritual,
diet conscious and socialising. The spiritual consumers took their purchase decision based on the
behaviour of the salesmen. The diet conscious consumers were highly brand conscious and the
socialising ones preferred formal shoes that were elegant (Table 1.21). Component 11 was
named as stay trim. The two types of consumers in this component include stay trim, the men
who often skipped their breakfast and the Sports Viewers, the men who preferred to watch sports
than any other channels. The stay trim preferred to purchase formal shoes from the outlets, where
the salesmen treated them well. The sports viewers preferred to wear footwear that was primarily
comfortable.


                                               90
International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online),
Volume 3, Issue 3, September- December (2012)

CONCLUSION

The footwear industry is susceptible to certain vital issues namely, market volatility due to
frequent changes in fashion, diverse market, competition from innumerable manufacturers both
from the organised and unorganized sector and the dissimilar buying habits of the customers.
The conclusion reached through the present study is that mapping the behavioural pattern of the
consumers and then associating with the footwear attributes can help the manufacturers and
retailers to understand their target market better. Further similar behavioural patterns can also
exist in other countries, therefore it becomes easier to tap the global markets. The Indian
Footwear is a sector with tremendous opportunity but still untapped.


REFERENCES

  1. Peter Knorringar, Mar 1998, “Economics of Collaboration in Producer-Trader Relations:
     Transaction Regimes between markets and hierarchy in the Agra Footwear cluster” Small
     Business Economics, 10 (2), 193 – 195, Springer
  2. Carmody, Padraig, Oct 1998, “Neoclassical practice and the collapse of industry in
     Zimbabwe: The cases of Textiles, Clothing and Footwear”, 74(4): ProQuest Research
     Library 319-343
  3. Pringle Heather, Jul 3, 1998, “Eight Millennia of footwear fashion” Science, 281, 5373,
     ProQuest, 23 - 25
  4. Segal Troy, Aug (2000), “Footwear Fervor”, ABA Journal, 86, 82 – 84
  5. Gayle E Reiber, Douglas G Smith, Carolyn M Wallace, Christy A, Vath B S, Katrina
     Sullivan, Shane Hayes, Onchee Yu, Don Martin, Mathew Maciejewski Sep/Oct 2002,
     “Footwear used by individuals with diabetes and a history of foot ulcer” Journal of
     Rehabilitation Research and Development, 39(5) , ProQuest Research Library, PP 615 –
     622
  6. Vijay Viswanathan, Sivagami Madahavan, saraswathy Gnansundaram, Gauthan
     Rajasekar, Ambady Ramachandran, Feb 2004, “Effectiveness of different types of
     footwear insoles for the diabetic neuropathic foot”, Diabetes Care, 27 (2), ProQuest
     Research Library Pg 474 – 477
  7. Jose Antonio Miranda, 2009, “Competing in Fashion Goods: Firms and Industrial
     Districts in the development of the Spanish Shoe Industry “, 7, 1 - 34
  8. Zakim, Michael, 2007, “A foot in the past: Consumers, Producers and Footwear in the
     long Eighteenth Century”, Business History Review, 81(1), ProQuest Research Library,
     194 - 196
  9. S L Rao (September 30, 2000) “India’s Rapidly Changing Consumer Markets”,
     Economic and Political Weekly, 3570 – 3572
Web References

   1.   http://www.leatherindia.org/products/footwear.asp,
   2.   http://en.wikipedia.org/wiki/Bangalore
   3.   http://www.aplfindia.com/seminars.asp
   4.   http://www.indianexpress.com/news/footwear-industry-seen-at-rs-38-500-cr/912014/



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An empirical analysis to study the influence of behavioural pattern of men on formal shoes

  • 1. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), INTERNATIONAL JOURNAL OF MANAGEMENT (IJM) Volume 3, Issue 3, September- December (2012) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 3, Issue 3, September- December (2012), pp. 72-91 IJM © IAEME: www.iaeme.com/ijm.asp Journal Impact Factor (2012): 3.5420 (Calculated by GISI) ©IAEME www.jifactor.com AN EMPIRICAL ANALYSIS TO STUDY THE INFLUENCE OF BEHAVIOURAL PATTERN OF MEN ON FORMAL SHOES Mrs. Uma V.R Assistant Professor Department of Commerce Christ University Bangalore, India - 560 029 Email: uma.vr@christuniversity.in Dr. M. I. Saifil Ali Professor & Director School of Management (DASM) Dhaanish Ahmed College of Engineering Chennai - 601301 Email: saifil_ali_33@yahoo.co.in ABSTRACT The present study attempts to present a model in which the footwear attributes are associated with the behavioural patterns of the consumers. The behavioural pattern of the consumers was studied through the AIO statements. The consumers were profiled into eleven clusters using factor analysis namely stylistic, confident, cautious shoppers, traditional, relaxed, optimistic, strivers, systematic, dominant, spiritual and stay trim. Regression scores were used to assign the respondents into the respective components that were extracted through factor analysis. Reliability Test and KMO Test were conducted to check the reliability and adequacy of the sample size. Further only those variables that qualified the collinearity test were alone subject to regression analysis. Through ANOVA test it was observed that significant differences existed among the consumers within the clusters. Therefore the AIO statements were considered as independent variables that were regressed against ten selected footwear attributes. The study finds that consumers’ footwear preferences varied according to their behavioural patterns. This model can help the retailers and manufacturers to revisit their existing strategies of targeting the consumers based on demography or material construction. Key Words: Footwear, Behavioral pattern, Regression, Lifestyle, Consumer, Clusters 72
  • 2. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) 1.1 INTRODUCTION With low production cost, abundant supply of raw material, evolving retail system, buying patterns and huge consumption market, this sector is posed to grow to great heights. India being a country of artisans is known for its traditional craft of footwear making. Some of the traditional footwear created by village craftsmen include leather chappals in Kohlapur' embroidered Juttis in Jodhpur, Indo-Tibetan felt boots in Sikkim and vegetable fibre shoes in Ladakh. The industrial policy 1967 reserved the leather industry including footwear only for small scale sectors. It was only during the mid 1970s, 100% export oriented footwear units in large scale sector were promoted. From June 2001 onwards the Government of India de-reserved the leather sector. During the past four decades starting from the year 1981 – 1982, the export of footwear from India had increased tremendously. Though India has a negligible proportion of exports in world trade, it is the second largest producer of footwear next to China. India accounts for 14% of the global annual footwear production of 14.52 billion pairs. India manufactures around 2065million pairs of footwear every year of which 909 million pairs are made of leather, 1056 million pairs of non leather footwear and 100 million pairs of shoe uppers. Nearly 70 percent of the labour constituting around 15 lakh people are employed in the unorganised sector majority of them are rural artisans, cottage and household units, while the organised sector accounts for remaining 30 percent and employs over 5 lakh people. The Indian consumer markets are growing and changing rapidly in terms of its nature and composition. With the revolution taking place in the distribution system through entry of super markets, shopping malls, chain stores etc in the metros, small cities and towns the potential for lifestyle products have increased drastically (S L Rao, 2000). With the change in the lifestyle patterns among the people especially the youth, this product has also undergone a tremendous transition in terms of its character. Though Indians have not been the ones to spend on items like footwear, for the past two decades due to liberalization, there has been a tremendous change in the buying habits of the consumers. More than sixty international brands are sourced from India. Most of these brands are manufactured in Agra, Kanpur or Chennai footwear clusters. 1.2 REVIEW OF LITERATURE India is a country of artisans comprising of footwear clusters spread in many parts of the country. These clusters predominantly consist of small-scale manufacturers with skilled craftsmen, out dated technologies having less access to automation. In a developing country like India, there exist tremendous opportunity for combining the artisanal touch with high technology (knorringar 1998). Unlike India after Liberalization the textile and footwear industries collapsed in Zimbabwe due to improper restructuring and low labour productivity (Carmody 1998) where as countries like India, Korea and Taiwan enjoy high labour productivity. The author finds the African market to be generally uncompetitive due to shrinking markets, low labour productivity, and poor infrastructure with poor political instability due to which foreign investment is scarce when compared to the Asian countries. Heather (1998) draws attention to the existence of fashion consciousness of the people towards footwear even before 8000 years ago. The author throws light on the evolution of the bear-fur shoes that the Japanese Samurai used to wear to the platform sandals that is worn by people today are all due to the fashion desire. The article was the result of excavation of shoes dated more than 8000 years from the Missouri cave. The complex weaving and design of the excavated shoes reveal that the people were fashion 73
  • 3. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) conscious as we are today and specialized artisans and craftsmen existed even at that time. The study by Troy (2000) stipulates the need for appropriate footwear as they are more than just shoes. According to the author shoes give identity and image and is also a symbol of status. Despite the benefits, diabetes patients refrain from purchase of therapeutic footwear as they are not attractive with limited colours and designs (Carolyn et al 2002, Gautham et al, 2004). Miranda (2009) explores the rise of Bata as a major player in the footwear sector. Post World War I, the international trade in footwear took a different turn. The large footwear exporting countries like United States and UK gradually became world’s leading importers. 1.3 STATEMENT OF THE PROBLEM Though the Indian consumers have become discerning and brand conscious, but in this sector the proliferation of the unorganized sector seem to be higher. The unorganized sector dominates the industry posing a threat to the organised players. In the organised sector, men’s footwear accounts for only half of the total market. Therefore it is clear that only 50% - 55% of the sales take place in the organized sector even in the men’s sector. Though footwear is considered as lifestyle enhancement product, the manufacturers and retailers have failed to understand this. Still the traditional segmentation patterns are followed in this industry, which include materials used for construction of the footwear, usage patterns and demographics. Also there are innumerable literatures that focus on trade policies followed in the footwear market in international countries, treatment of workers in the footwear industry, therapeutic use of footwear, supply chain patterns etc but there are hardly any study that explores the consumer behaviour and their association towards the footwear preferences. Behavioral segmentation though has been used in many other products like apparels, insurance, real estate etc., but not in the footwear sector. The present study is an attempt to fill the gap. This sector is a highly promising one with less knowledge about its customers. 1.4 OBJECTIVES From the problems stated above the objectives have been derived as under: • To profile men into different clusters based on their activities, interest and opinions • To examine the differences that exists in the preferences towards the formal footwear attributes according to the consumers’ behavioural patterns 1.5 STUDY AREA The study was conducted in Bangalore being the capital of Karnataka and a fast emerging metropolitan city. Further it is the third most populous city and stands fifth in the urban population. As on 2011 the total population of the city stood at 8,425,970. Geographically the city is divided into 5 regions namely East, West, North, South and Central Bangalore. Bangalore has only 41% of local population and the rest of them belong to other states and countries especially from Europe. Hence, it is vivid that Bangalore has a population with diverse profiles. Therefore the city of Bangalore has been selected for the study purposively. 74
  • 4. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) 1.6 SAMPLE RESPONDENTS The respondents for the study include men between the age group of 20 – 55 yrs and between the income classes of Rs 12000 to Rs 200000 per month. The respondents were drawn randomly from the various strata of East, West, North, South and Central Bangalore. 500 men were selected from each stratum totaling to 2500 men. Out of the total respondents only 2074 men qualified for the study as the responses furnished by the rest of them was incomplete hence were eliminated. 1.7 SURVEY INSTRUMENT Primary data was collected through distribution of questionnaires. The questionnaire comprised of three sections. Section I includes 50 statements (Mitchell, A. 1983, Anderson, W.T. and Golden, L. 1984; Hanspal et al, 1999; Hanspal et al, 2000 ) that would help in profiling the customers into behavioural clusters based on the activities they normally engage in their day to day life, interests and opinions on certain common issues. These statements were to be rated in a 7 point likert scale. Section II comprised of their demographic details and the attributes they expect their formal and casual footwear to possess. These attributes were arrived after an exploratory study. The exploratory study was conducted to a group of 20 members. The group members comprised of consumers who belonged to different age groups. They were asked to list the attributes they generally preferred their footwear to possess. Eighteen attributes were listed. Though all the eighteen attributes were included in the instrument only ten attributes were selected for analysis. These ten attributes were selected based on the ranking given by majority of the group members. These attributes were also to be rated in a 7 point likert scale. The instrument so constructed was pre-tested on thirty respondents to find out if the questions framed had sufficient clarity. Then based on their suggestions the final instrument was constructed and administered. 1.8 STATISTICAL TOOLS USED The statistical tools used for the study include Reliability Test, KMO test, Factor analysis, ANOVA, and Multiple Regression Analysis. Statiscal packages such as SPSS 16 and EXCEL were employed in the study. 1.9 SCOPE The study will be helpful for the retailers to restructure their product offerings. The report will also be useful for new retailers for designing their market strategies. It also offers a scope for further research as there is not much study done in this area. Many international brands are looking out for a place of business in India, this study will help them in understanding the consumer characteristics and the factors that influence their purchase decision. The study can be extended to global markets as similar purchase patterns may exist in multiple countries. 75
  • 5. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) 1.10 ANALYSIS: 1.10.1 CONSUMER PROFILING For profiling the respondents on the basis of their behaviour, factor analysis was employed on the 50 AIO statements (See Appendix1). Initially inorder to test the reliability of these AIO statements, Cronbach’s alpha score was computed. The Cronbach’s alpha on 50 AIO statements revealed a score of 0.803 showing that the statements were reliable enough for further analysis. Also Kaiser-Mayo-Olkin (KMO) Test was conducted to measure the adequacy of sample size. The test generated a score of 0.694. Thus KMO test also proved that the samples were adequate enough to conduct factor analysis. On employing factor analysis 11 factors that constitutes 52% of the variance was considered for the study. Further for authentication Scree plot was also read. Only those factors that constituted Eigen value above 1 were considered as principal component analysis was employed. Varimax rotation was used to extract the factors with factor loadings greater than +/- 0.30. Table 1.1 Components with total and cumulative variance Initial Eigen values Components Total % of Variance Cumulative % 1 5.81 11.63 11.63 2 3.20 6.40 18.03 3 3.07 6.13 24.16 4 2.46 4.92 29.09 5 1.98 3.96 33.04 6 1.87 3.74 36.78 7 1.68 3.36 40.14 8 1.56 3.11 43.25 9 1.40 2.80 46.06 10 1.39 2.79 48.85 11 1.34 2.69 51.54 As Varimax rotation was utilized, those statements which had a factor loading of 0.3 and above was assigned to the respective component. Further case wise regression scores were considered to classify each individual to the respective components. The 11 components that were extracted include Stylistic, Independents, Economicals, Traditional, Socialising, Globe trotters, Strivers, Systematic and Dominant (See Table 4.5). It should be noted that the components have been named according to the variable (Statement) with higher rotated factor loadings. 76
  • 6. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.2 Statements with Rotated Factor Loadings and assignment to respective components Components Rotated Factor Loadings Component 1: Stylistic I like to spend a year in a foreign country 0.72 I have one or more outfits that are of very latest style 0.72 I pay cash for everything I buy 0.68 I enjoy stylistic dresses 0.65 The most important of life is to dress smartly 0.58 I am fashionable in the eyes of others 0.58 Component 2: Confident I have more self confidence than most people 0.77 As far as possible after marriage nuclear family is better 0.74 I am more independent than most people 0.71 I have a lot of personal ability 0.64 Component 3: Cautious Shoppers I visit many shops before I finalise my sales 0.81 I am active in all social functions 0.64 I check the prices even for small items 0.61 I watch advertisements for announcements of sales 0.56 One should bargain before a purchase 0.40 I prefer my friends to spend when I am out on a party 0.37 Component 4: Traditional Women are dependents and need men’s protection 0.73 A women should not work if her husband does not like her to work 0.72 Looking after the house is primarily a woman’s responsibility 0.59 In the evenings, it is better to stay at home 0.53 Component 5: Relaxed I drink soft drinks several times in a week 0.76 I spend a lot of time with friends talking about brands and products 0.70 I participate in sports activities -0.53 One should have own credit/debit cards 0.43 Component 6: Optimistic Think I will have more money to spend next year 0.83 I want to take a trip around the world 0.77 Component 7: Strivers Doing nothing makes me feel uncomfortable 0.77 I will take some courses to brighten my future 0.45 Component 8: Systematic One should always keep the house neat and clean 0.66 One must save for the rainy day 0.63 A distinctive living attracts me 0.52 77
  • 7. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Component 9: Dominant Friends often come to me for advice 0.66 Giving dowry in marriage is a tradition and cannot be done away 0.54 I would go for a walk than sit idle 0.52 I can be considered a leader 0.39 Component 10: Spiritual, Diet conscious and Socialising I eat only home food 0.59 Spiritual values are important than material things 0.58 I can mingle with strangers easily 0.50 Component 11: Stay Trim (6%) I skip breakfast regularly 0.77 I like to watch games than any other entertainment channels 0.71 For the purpose of the study the AIO statements were considered as predictor variables and the footwear attributes were considered the criterion variables. Further only those statements that satisfied the collinearity test was selected. ANOVA test revealed the existence of significant differences among the consumers in the same component. Therefore multiple regressions were employed to study the association between the behavioural pattern of consumers and the preferences towards formal footwear attributes. COMPONENT 1 – STYLISTIC CONSUMERS Table 1.3: COLLINARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* I pay cash for everything I buy (Budgeted spenders) .726 1.377 I enjoy stylistic dresses (Stylistic) .900 1.112 The important part of life is to dress smartly (Smartly dressed) .943 1.060 I like to spend a year in a foreign country (Foreign land) .675 1.482 I am fashionable in the eyes of others (Fashionable) .703 1.422 Table 1.4 Multiple Regression Analysis for Stylistic Consumers (Component 1) and Formal Footwear Attributes FORMAL FOOTWEAR PREFERENCES Variables B SE Beta t- Variables B SE Beta t-value value Criterion Variable Criterion Coordinated Colours 5.23 1.99 2.62 ** Family -1.20 1.62 -.74 Predictor Variables Predictor Budgeted spenders -1.02 .25 -.31 -4.1** Budgeted spenders -.439 .203 -.163 -2.17* Stylistic -.09 .23 -.03 -.43 Stylistic .142 .186 .052 .76 Smart Dressers .54 .13 .28 4.29 ** Smart Dressers .288 .102 .186 2.82** Foreign land -.35 .22 -.13 -1.62 Foreign land .902 .176 .400 5.13** Fashionable .89 .22 .31 Fashionable .131 .176 .056 .74 78
  • 8. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) 4.11** Criterion Variable Criterion Elegance 1.19 .60 1.98* Posture -1.10 1.07 -1.03 Predictor Variables Predictor Budgeted spenders .26 .08 .18 3.43** Budgeted spenders -.015 .133 -.007 -.12 Stylistic .01 .07 .00 .07 Stylistic -.540 .122 -.228 -4.41** Smart Dressers .03 .04 .04 .84 Smart Dressers -.149 .067 -.112 -2.22* Foreign land -.51 .07 -.42 -7.8** Foreign land 1.28 .116 .660 11.08** Fashionable 1.01 .07 .81 15.4** Fashionable .422 .116 .213 3.64** Criterion Variable Criterion Comfort 6.34 .417 15.2** Ambience .244 1.35 .18 Predictor Variables Predictor Budgeted spenders .027 .052 .042 .521 Budgeted spenders .302 .169 .127 1.79 Stylistic -.065 .048 -.09 -1.35 Stylistic .747 .155 .307 4.81** Smart Dressers -.061 .026 -.16 -2.31* Smart Dressers .182 .085 .133 2.14* Foreign land .046 .045 .084 1.01 Foreign land -1.09 .147 -.550 -7.48** Fashionable .115 .045 .208 2.54* Fashionable .718 .147 .352 4.88** Criterion Variable Criterion Variable Branded 3.98 .994 4.01** Salesmen .263 1.35 .194 Predictor Variables Predictor Budgeted spenders .465 .124 .268 3.74** Budgeted spenders .364 .169 .153 2.15* Stylistic -.226 .114 -.13 -1.98* Stylistic .618 .156 .253 3.97** Smart Dressers -.067 .063 -.07 -1.07 Smart Dressers .150 .085 .109 1.75 Foreign land -.483 .108 -.33 -4.5** Foreign land -1.09 .147 -.549 -7.45** Fashionable .629 .108 .423 5.81** Fashionable .787 .148 .385 5.33** Criterion Variable Criterion Variable Friends -1.54 1.73 -.89 Amenities 11.3 1.88 6.01** Predictor Variables Predictor Budgeted spenders -.382 .217 -.13 -1.76 Budgeted spenders -.991 .236 -.305 -4.2** Stylistic -.051 .199 -.02 -.26 Stylistic .696 .217 .210 3.21** Smart Dressers -.353 .109 -.20 -3.2** Smart Dressers .207 .119 .111 1.74 Foreign land .913 .188 .356 4.85** Foreign land -.785 .204 -.289 -3.84** Fashionable .907 .189 .346 4.80** Fashionable -.128 .205 -.046 -.62 ** Significant at 1% level, * Significant at 5% level COMPONENT 2- CONFIDENT CONSUMERS Table 1.5 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* As far as possible nuclear family is better (Nuclear Family) .847 1.181 I have more self confidence than most people (Confident) .789 1.267 I am more independent (Independent) .821 1.218 I have a lot of personal ability (Skilled) .900 1.111 *Variance Inflation Factor 79
  • 9. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.6 Multiple Regression Analysis of Confident Men (Component 2) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours .995 1.09 .911 Family 8.16 1.46 5.59** Predictor Variables Predictor Nuclear Family .014 .092 .010 .155 Nuclear Family -.42 .123 -.220 -3.4** Confident -.033 .122 -.018 -.274 Confident .360 .163 .148 2.22* Independent .708 .141 .328 5.019** Independent .191 .188 .066 1.01 Skilled -.023 .122 -.012 -.186 Skilled -.67 .163 -.257 -4.1** Criterion Variable Criterion Elegance 4.57 .804 5.682** Posture 6.99 1.41 4.94** Predictor Variables Predictor Nuclear Family -.208 .068 -.202 -3.07** Nuclear Family -.21 .119 -.117 -1.75 Confident -.016 .090 -.012 -.180 Confident .292 .157 .128 1.853 Independent .217 .104 .140 2.094* Independent -.35 .183 -.129 -1.89 Skilled .234 .090 .166 2.606** Skilled -.04 .158 -.016 -.243 Criterion Variable Criterion Comfort 5.82 .594 9.803** Ambience 9.19 1.49 6.157** Predictor Variables Predictor Nuclear Family -.058 .050 -.075 -1.160 Nuclear Family -.374 .126 -.194 -2.976** Confident -.273 .066 -.276 -4.14** Confident .447 .166 .181 2.689** Independent .284 .077 .242 3.700** Independent -.425 .193 -.146 -2.206* Skilled .171 .066 .161 2.575** Skilled -.339 .167 -.128 -2.034* Criterion Variable Criterion Branded -.319 1.00 -.318 Salesmen 4.85 1.33 3.662** Predictor Variables Predictor Nuclear Family -.299 .085 -.213 -3.54** Nuclear Family -.037 .112 -.022 -.330 Confident .559 .112 .312 5.001** Confident .380 .148 .178 2.575** Independent .647 .130 .306 4.996** Independent -.345 .171 -.137 -2.02* Skilled -.014 .112 -.007 -.126 Skilled .043 .148 .019 .289 Criterion Variable Criterion Friends 11.5 1.57 7.331** Amenities 6.69 1.11 6.018** Predictor Variables Predictor Nuclear Family -.493 .132 -.238 -3.72** Nuclear Family -.397 .094 -.272 -4.23** Confident .196 .175 .074 1.121 Confident -.236 .124 -.127 -1.91 Independent -.556 .203 -.178 -2.74** Independent .005 .144 .002 .036 Skilled -.280 .175 -.099 -1.595 Skilled .152 .124 .077 1.225 ** Significant at 1% level, * Significant at 5% level COMPONENT 3 – CAUTIOUS SHOPPERS Table 1.7 COLLINARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* I am active in all social functions (Social) .810 1.235 I visit many shops before I finalise my sales (Cautious buyers) .800 1.250 I check the prices even for small items (Price Conscious) .911 1.098 *Variance Inflation Factor 80
  • 10. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.8 Multiple Regression Analysis of Cautious Shoppers (Component 3) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours 4.59 1.32 3.485** Family 4.99 1.29 3.848** Predictor Variables Predictor Social .171 .159 .075 1.071 Social .839 .157 .366 5.345** Cautious buyers -.552 .189 -.207 -2.92** Cautious buyers -.703 .186 -.261 -3.782** Price Conscious .435 .102 .285 4.289** Price Conscious -.066 .100 -.042 -.657 Criterion Variable Criterion Elegance 2.23 .736 3.030** Posture 5.95 .961 6.196** Predictor Variables Predictor Social .230 .089 .173 2.587** Social -.165 .116 -.100 -1.421 Cautious buyers .005 .105 .003 .051 Cautious buyers -.169 .138 -.087 -1.230 Price Conscious .373 .057 .415 6.577** Price Conscious .298 .074 .268 4.036** Criterion Variable Criterion Comfort 4.21 .609 6.908** Ambience 1.34 .981 1.370 Predictor Variables Predictor Social -.216 .074 -.199 -2.93** Social .350 .119 .209 2.955** Cautious buyers .463 .087 .362 5.302** Cautious buyers -.133 .140 -.067 -.947 Price Conscious .096 .047 .131 2.042* Price Conscious .294 .076 .260 3.891** Criterion Variable Criterion Branded 2.15 .932 2.303* Salesmen .367 1.05 .347 Predictor Variables Predictor Social .425 .113 .253 3.773** Social .523 .128 .289 4.091** Cautious buyers -.452 .133 -.228 -3.38** Cautious buyers .027 .152 .013 .177 Price Conscious .470 .072 .414 6.544** Price Conscious .135 .081 .110 1.651 Criterion Variable Criterion Friends 1.17 1.08 1.084 Amenities -2.33 1.06 -2.190* Predictor Variables Predictor Social .628 .131 .329 4.81** Social .753 .129 .391 5.851** Cautious buyers -.427 .155 -.190 -2.76** Cautious buyers .134 .152 .059 .877 Price Conscious .406 .083 .315 4.879** Price Conscious .200 .082 .154 2.441* ** Significant at 1% level, * Significant at 5% level COMPONENT 4 – TRADITIONAL Table 1.9 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* A woman should not work if her husband does not like her to work .859 1.164 outside the house (dominating) Women are dependants and need men’s protection (protectionist) .829 1.207 Looking after the house is primarily a woman’s responsibility .892 1.121 irrespective of whether she is working or not (egotistic) In the evenings, it is better to stay at home rather than going out (conservative) .900 1.111 *Variance Inflation Factor 81
  • 11. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.10 Multiple Regression Analysis of Traditional (Component 4) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours 1.34 .782 1.718 Family 1.69 .563 3.010** Predictor Variables Predictor Dominating .249 .085 .189 2.917** Dominating .268 .062 .253 4.351** Protectionist .114 .093 .081 1.236 Protectionist -.047 .067 -.042 -.709 Egotistic -.060 .101 -.038 -.592 Egotistic -.049 .072 -.038 -.674 Conservative .392 .071 .338 5.550** Conservative .507 .051 .544 9.963** Criterion Variable Criterion Elegance 1.43 .457 3.128** Posture 1.34 .387 3.464** Predictor Variables Predictor Dominating .118 .050 .141 2.358* Dominating .321 .042 .399 7.588** Protectionist .288 .054 .323 5.317** Protectionist .276 .046 .321 6.006** Egotistic .216 .059 .215 3.669** Egotistic .171 .050 .177 3.434** Conservative .102 .041 .139 2.468* Conservative .018 .035 .025 .501 Criterion Variable Criterion Comfort 4.00 .425 9.422** Ambience 1.83 .618 2.968** Predictor Variables Predictor Dominating -.044 .046 -.060 -.951 Dominating .217 .068 .207 3.206** Protectionist .206 .050 .265 4.096** Protectionist -.025 .073 -.023 -.346 Egotistic .251 .055 .287 4.592** Egotistic .200 .080 .160 2.518* Conservative .002 .038 .003 .055 Conservative .270 .056 .295 4.842** Criterion Variable Criterion Branded -.45 .394 -1.128 Salesmen 2.47 .596 4.136** Predictor Variables Predictor Dominating .358 .043 .397 8.306** Dominating .080 .065 .080 1.226 Protectionist .388 .047 .405 8.318** Protectionist .327 .071 .305 4.626** Egotistic .050 .051 .046 .984 Egotistic .127 .077 .106 1.658 Conservative .238 .036 .301 6.690** Conservative .016 .054 .018 .296 Criterion Variable Criterion Friends 1.48 .614 2.413* Amenities 2.68 .617 4.351** Predictor Variables Predictor Dominating -.028 .067 -.027 -.418 Dominating .059 .067 .060 .881 Protectionist .252 .073 .224 3.469** Protectionist .151 .073 .143 2.068* Egotistic .376 .079 .296 4.752** Egotistic .157 .079 .132 1.978* Conservative .097 .056 .105 1.754 Conservative .068 .056 .078 1.214 ** Significant at 1% level, * Significant at 5% level COMPONENT 5 - RELAXED Table 1.11 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* One should have his/her own credit/debit cards (Practical) .952 1.051 I spend a lot of time with friends talking about brands and products (Brand Analyst) .965 1.036 I drink soft drinks several times a week (unhealthy) .839 1.192 I do not participate in sports activities (non playful) .873 1.146 *Variance Inflation Factor 82
  • 12. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.12 Multiple Regression Analysis of Relaxed (Component 5) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours 4.83 1.38 3.510** Family 2.22 1.69 1.313 Predictor Variables Predictor Practical -.015 .071 -.015 -.216 Practical -.184 .087 -.145 -2.112* Brand Analyst .054 .112 .033 .477 Brand Analyst .512 .138 .251 3.700** Unhealthy .008 .157 .004 .049 Unhealthy -.050 .193 -.019 -.261 Nonplayful -.302 .131 -.169 -2.303* Nonplayful .314 .161 .139 1.946 Criterion Variable Criterion Elegance 3.92 1.14 3.451** Posture -.622 1.32 -.470 Predictor Variables Predictor Practical -.143 .058 -.165 -2.443* Practical -.123 .068 -.118 -1.804 Brand Analyst .005 .093 .003 .050 Brand Analyst .574 .108 .344 5.301** Unhealthy .183 .129 .102 1.417 Unhealthy .327 .151 .151 2.166* Nonplayful .468 .108 .305 4.327** Nonplayful .330 .126 .179 2.614** Criterion Variable Criterion Comfort 7.39 .731 10.10** Ambience -3.25 1.26 -2.577* Predictor Variables Predictor Practical -.082 .038 -.151 -2.181* Practical .182 .065 .168 2.811** Brand Analyst .003 .060 .004 .057 Brand Analyst .522 .103 .301 5.067** Unhealthy -.010 .083 -.009 -.124 Unhealthy .710 .143 .315 4.945** Nonplayful -.201 .070 -.209 -2.89** Nonplayful -.314 .120 -.164 -2.617** Criterion Variable Criterion Branded 7.59 1.04 7.288** Salesmen -3.25 1.25 -2.601** Predictor Variables Predictor Practical -.134 .054 -.154 -2.500* Practical .197 .064 .186 3.074** Brand Analyst -.390 .085 -.281 -4.58** Brand Analyst .757 .102 .445 7.421** Unhealthy .307 .119 .170 2.588** Unhealthy .389 .142 .176 2.736** Nonplayful -.476 .099 -.309 -4.79** Nonplayful -.014 .119 -.007 -.117 Criterion Variable Criterion Friends 5.78 1.30 4.448** Amenities 3.37 1.60 2.100* Predictor Variables Predictor Practical -.309 .067 -.313 -4.62** Practical -.470 .083 -.366 -5.691** Brand Analyst .137 .106 .087 1.288 Brand Analyst .008 .131 .004 .065 Unhealthy -.026 .148 -.013 -.179 Unhealthy .552 .183 .207 3.021** Nonplayful .185 .124 .106 1.491 Nonplayful .221 .153 .097 1.449 ** Significant at 1% level, * Significant at 5% level 83
  • 13. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) COMPONENT 6 – OPTIMISITIC Due to multi collinearity only one variable was considered for regression analysis Table 1.13 Regression Analysis of Optimistic (Component 6) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours 6.46 .868 7.447** Family 4.88 1.23 3.970** Predictor Variables Predictor Globe Trippers -.184 .130 -.129 -1.418 Variables -.134 .184 -.067 -.728 Globe Trippers Criterion Variable Criterion Elegance 7.93 .941 8.423** Posture 6.87 1.31 5.247** Predictor Variables Predictor Globe Trippers -.369 .141 -.234 -2.62** Globe Trippers -.296 .196 -.138 -1.511 Criterion Variable Criterion Comfort 6.96 .343 20.31** Ambience .749 .844 .886 Predictor Variables Predictor Globe Trippers -.045 .051 -.080 -.871 Globe Trippers .570 .126 .383 4.505** Criterion Variable Criterion Branded 7.59 .918 8.261** Salesmen 7.29 .708 10.296** Predictor Variables Predictor Globe Trippers -.330 .138 -.215 -2.397* Globe Trippers -.246 .106 -.209 -2.320* Criterion Variable Criterion Friends 6.97 .929 7.496** Amenities -1.92 1.14 -1.684 Predictor Variables Predictor Globe Trippers -.324 .139 -.210 -2.328* Globe Trippers .810 .170 .401 4.753** ** Significant at 1% level, * Significant at 5% level COMPONENT 7 – STRIVERS Table 1.14 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* Doing nothing makes me feel uncomfortable (Active) .974 1.027 I will take some courses to brighten my future (Hard Working) .974 1.027 *Variance Inflation Factor 84
  • 14. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.15 Multiple Regression Analysis of Strivers (Component 7) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours -4.58 2.36 -1.945 Family 5.06 1.66 3.054** Predictor Variables Predictor Active 1.68 .242 .539 6.949** Active .740 .170 .345 4.352** Hard Working -.260 .214 -.094 -1.213 Hard Working -.680 .151 -.357 -4.512** Criterion Variable Criterion Elegance 5.14 1.71 3.005** Posture 11.2 2.77 4.035** Predictor Variables Predictor Active .060 .176 .032 .342 Active -.360 .284 -.117 -1.268 Hard Working .080 .156 .048 .514 Hard Working -.480 .252 -.175 -1.907 Criterion Variable Criterion Comfort 3.48 .607 5.736** Ambience 6.74 2.22 3.030** Predictor Variables Predictor Active .420 .062 .536 6.745** Active -.040 .228 -.016 -.175 Hard Working .060 .055 .086 1.087 Hard Working -.220 .202 -.101 -1.087 Criterion Variable Criterion Branded 13.8 1.93 7.128** Salesmen 9.38 2.56 3.666** Predictor Variables Predictor Active -.300 .199 -.128 -1.510 Active -.480 .263 -.169 -1.828 Hard Working -.900 .176 -.432 -5.11** Hard Working -.140 .233 -.056 -.601 Criterion Variable Criterion Friends 20.7 2.64 7.828 Amenities 8.38 2.87 2.917** Predictor Variables Predictor Active -1.28 .271 -.388 -4.72** Active 1.02 .295 .264 3.460** Hard Working -1.04 .240 -.355 -4.33** Hard Working -1.64 .261 -.478 -6.276** ** Significant at 1% level, * Significant at 5% level COMPONENT 8 – SYSTEMATIC Table 1.16 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* One should always keep the house neat and clean (Neatness) .821 1.219 A fancy and distinctive living attracts me (Distinctive) .946 1.057 One must save for the rainy day (Cautious) .821 1.217 *Variance Inflation Factor 85
  • 15. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.17 Multiple Regression Analysis of Systematic (Component 8) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours -5.19 3.85 -1.349 Family -12.4 3.59 -3.44** Predictor Variables Predictor Neatness 2.07 .600 .289 3.445** Neatness 2.48 .561 .363 4.42** Distinctive -.425 .157 -.212 -2.71** Distinctive .028 .146 .015 .193 Cautious -.278 .313 -.074 -.886 Cautious .056 .293 .016 .193 Criterion Variable Criterion Elegance -24.8 1.79 -13.9** Posture -21.4 3.06 -6.99** Predictor Variables Predictor Neatness 3.85 .278 .692 13.82** Neatness 3.79 .477 .567 7.95** Distinctive -.127 .073 -.08 -1.75 Distinctive .274 .125 .146 2.19* Cautious .746 .145 .257 5.19** Cautious -.167 .249 -.048 -.67 Criterion Variable Criterion Comfort .676 .927 .729 Ambience -20.7 3.0 -6.89** Predictor Variables Predictor Neatness .419 .144 .219 2.89** Neatness 2.36 .469 .357 5.03** Distinctive .109 .038 .202 2.83** Distinctive .525 .122 .284 4.29** Cautious .360 .075 .360 4.78** Cautious .907 .245 .263 3.71** Criterion Variable Criterion Branded -23.3 2.67 -8.74** Salesmen 3.39 2.36 1.44 Predictor Variables Predictor Neatness 1.93 .415 .254 4.65** Neatness .006 .367 .001 .016 Distinctive -.239 .108 -.113 -2.21* Distinctive -.008 .096 -.007 -.084 Cautious 2.52 .216 .636 11.65** Cautious .270 .192 .123 1.41 Criterion Variable Criterion Friends -16.1 3.74 -4.30** Amenities -14.2 4.31 -3.30** Predictor Variables Predictor Neatness 3.09 .583 .424 5.30** Neatness 2.38 .671 .293 3.55** Distinctive -.121 .152 -.059 -.794 Distinctive -.179 .175 -.079 -1.02 Cautious .044 .304 .012 .146 Cautious .499 .350 .117 1.43 ** Significant at 1% level, * Significant at 5% level COMPONENT 9 - DOMINANT Table 1.18 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* Giving dowry in marriage is a tradition and cannot be done away with (Conventional) .962 1.039 Friends often come to me for advice (Opinion Leaders) .975 1.025 I would go for a walk or do some exercise than sit idle (Stay Fit) .982 1.018 *Variance Inflation Factor 86
  • 16. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.19 Multiple Regression Analysis of Dominant (Component 9) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours -1.88 .738 -2.549* Family 3.86 .858 4.493** Predictor Variables Predictor Conventional .369 .057 .369 6.440** Conventional -.112 .067 -.114 -1.676 Opinion leaders .630 .076 .469 8.241** Opinion leaders .186 .089 .142 2.091* Stay Fit .292 .091 .182 3.213** Stay Fit .144 .106 .092 1.364 Criterion Variable Criterion Elegance 2.17 .538 4.042** Posture 1.59 .688 2.315* Predictor Variables Predictor Conventional .305 .042 .435 7.304** Conventional .227 .053 .272 4.240** Opinion leaders .349 .056 .370 6.264** Opinion leaders .350 .071 .313 4.914** Stay Fit .071 .066 .063 1.067 Stay Fit .171 .085 .128 2.015* Criterion Variable Criterion Comfort 3.22 .360 8.926** Ambience 2.47 .625 3.953** Predictor Variables Predictor Conventional .213 .028 .444 7.620** Conventional .319 .049 .413 6.567** Opinion leaders .196 .037 .305 5.264** Opinion leaders .215 .065 .208 3.330** Stay Fit .221 .044 .287 4.979** Stay Fit -.034 .077 -.027 -.438 Criterion Variable Criterion Branded -2.50 .666 -3.76** Salesmen 2.68 .836 3.207** Predictor Variables Predictor Conventional .243 .052 .246 4.702** Conventional .128 .065 .134 1.965 Opinion leaders .705 .069 .531 10.22** Opinion leaders .275 .087 .215 3.180** Stay Fit .594 .082 .375 7.244** Stay Fit .071 .103 .046 .688 Criterion Variable Criterion Friends -.077 .875 -.088 Amenities 3.38 1.02 3.317** Predictor Variables Predictor Conventional -.007 .068 -.006 -.106 Conventional .110 .079 .096 1.396 Opinion leaders .801 .091 .520 8.839** Opinion leaders -.175 .106 -.113 -1.654 Stay Fit .166 .108 .090 1.537 Stay Fit .236 .126 .128 1.878 ** Significant at 1% level, * Significant at 5% level COMPONENT 10 - SPIRITUAL, DIET CONSCIOUS AND SOCIALISING Table 1.20 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* Spiritual values are more important that material things (Spiritual) .910 1.099 I eat only home food and do not like to eat out (Diet Conscious) .897 1.114 I can mingle with strangers easily (Socialising) .849 1.178 *Variance Inflation Factor 87
  • 17. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.21 Multiple Regression Analysis of Spiritual, Diet conscious and Socialising (Component 10) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours 2.30 .982 2.341* Family 3.28 1.19 2.753** Predictor Variables Predictor Spiritual -.208 .137 -.109 -1.512 Spiritual .552 .166 .246 3.318** Diet Conscious .448 .114 .283 3.911** Diet Conscious -.397 .139 -.214 -2.865** Socialising .207 .076 .201 2.704** Socialising .083 .093 .069 .896 Criterion Variable Criterion Elegance 2.24 .734 3.056** Posture .196 .866 .227 Predictor Variables Predictor Spiritual -.090 .103 -.047 -.873 Spiritual .208 .121 .110 1.720 Diet Conscious -.003 .086 -.002 -.034 Diet Conscious .240 .101 .154 2.383* Socialising .749 .057 .732 13.11** Socialising .463 .067 .456 6.87** Criterion Variable Criterion Comfort 7.52 .698 -.158 10.77** Ambience .551 .910 .605 Predictor Variables Predictor Spiritual -.206 .098 -.113 -2.108* Spiritual .568 .127 .320 4.465** Diet Conscious -.122 .081 .257 -1.501 Diet Conscious .319 .106 .217 3.008** Socialising .180 .054 3.312** Socialising -.185 .071 -.194 -2.611** Criterion Variable Criterion Branded 1.98 1.01 1.971* Salesmen -.949 .906 -1.048 Predictor Variables Predictor Spiritual -.293 .141 -.144 -2.081* Spiritual .920 .127 .485 7.267** Diet Conscious .658 .117 .391 5.613** Diet Conscious .291 .106 .185 2.759** Socialising .183 .078 .168 2.343** Socialising -.240 .070 -.235 -3.401** Criterion Variable Criterion Friends .589 1.14 .518 Amenities 2.69 1.21 2.223* Predictor Variables Predictor Spiritual .538 .159 .252 3.387** Spiritual .307 .170 .139 1.806 Diet Conscious -.025 .132 -.014 -.190 Diet Conscious .018 .141 .010 .126 Socialising .100 .088 .087 1.132 Socialising -.086 .094 -.072 -.909 ** Significant at 1% level, * Significant at 5% level COMPONENT 11 – STAY TRIM Table 1.22 COLLINEARITY STATISTICS BETWEEN THE PREDICTOR VARIABLES PREDICTOR VARIABLES TOLERANCE VIF* I skip breakfast regularly (Stay Trim) .985 1.015 I like to watch games than any other entertainment channels (Sports Viewers) .985 1.015 *Variance Inflation Factor 88
  • 18. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) Table 1.23 Multiple Regression Analysis of Stay Trim (Component 11) and Formal Footwear Attributes FORMAL FOOTWEAR Variables B SE Beta t-value Variables B SE Beta t-value Criterion Variable Criterion Coordinated Colours -.65 3.52 -.184 Family -4.38 3.28 -1.337 Predictor Variables Predictor Stay Trim -.270 .447 -.052 -.605 Stay Trim 1.68 .416 .336 4.028** Sports Viewers 1.04 .313 .283 3.323** Sports Viewers -.351 .292 -.101 -1.205 Criterion Variable Criterion Elegance -7.24 2.45 -2.96** Posture -5.59 3.01 -1.857 Predictor Variables Predictor Stay Trim 1.65 .311 .422 5.297** Stay Trim 1.67 .383 .361 4.362** Sports Viewers .203 .218 .074 .929 Sports Viewers -.213 .268 -.066 -.794 Criterion Variable Criterion Comfort 3.49 1.37 2.548** Ambience -8.99 3.73 -2.390* Predictor Variables Predictor Stay Trim -.047 .174 -.023 -.272 Stay Trim 2.28 .474 .393 4.819** Sports Viewers .470 .122 .324 3.855** Sports Viewers -.318 .332 -.078 -.956 Criterion Variable Criterion Branded -9.03 2.22 -4.058 Salesmen -21.1 3.08 -6.830** Predictor Variables Predictor Stay Trim 1.41 .283 .384 4.975** Stay Trim 3.06 .392 .551 7.818** Sports Viewers .689 .198 .268 3.480** Sports Viewers .753 .274 .194 2.745** Criterion Variable Criterion Friends -5.97 2.24 -2.67** Amenities -11.8 3.61 -3.270** Predictor Variables Predictor Stay Trim 1.85 .285 .499 6.48** Stay Trim 1.16 .459 .208 2.534** Sports Viewers -.314 .199 -.12 -1.58 Sports Viewers 1.18 .322 .299 3.657** ** Significant at 1% level, * Significant at 5% level 1.11 RESULT AND DISCUSSION A brief discussion on the highest preferences of the consumers for formal shoes (based on the highest Beta value and significant t-value) in each of the factors extracted is given below. Component 1 comprised of stylistic consumers. Six variables (AIO statements) were loaded in this component. Out of which five variables qualified for study due to multicollinearity. Therefore the five types of consumers in this component include Budgeted spenders, stylistic, smart dressers, foreign settlers and fashionables. From Table 1.4 it can be observed that the Budgeted spenders preferred more of branded shoes for formal wear. The stylistic consumers were more store conscious. They preferred to purchase formal wear from the store that had good ambiences. The smart dressers preferred their formal shoes to coordinate with the colour of their attire. The consumers who preferred to settle abroad preferred to wear formal shoes that enhanced their postures. The fashionables preferred elegant formal shoes. Component 2 comprised of confident consumers. Four variables (AIO statements) were loaded in this component. The four types of consumers in this category include Nuclear Family oriented, Confident, Independent and Skilled. From Table 1.6 it can be observed that the consumers who preferred to live in nuclear family were bound to purchase shoes from the store that exclusively sold footwear and no other amenities. The confident consumers purchased formal shoes based on 89
  • 19. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) brands. The independent consumers preferred to wear formal shoes with coordinated colours. The skilled consumers who perceived that they had lot of personal ability preferred elegant and comfortable shoes and they never consult their family in the purchase of formal shoes. Component 3 was named as cautious shoppers. This component comprised of three types of consumers namely social, cautious shoppers and price conscious. From Table 1.8 it can be inferred that the social consumers who are very active in all the social functions preferred to purchase formal shoes from the outlets that sold other amenities as well. The cautious shoppers who visit many shops before they finalised their sales preferred to wear formal shoes that were comfortable. The price conscious consumers preferred to wear formal shoes that were elegant and branded. Component 4 named as traditional comprised of four types of consumers namely dominating, protectionist, egotistic and conservative. From Table 1.10 it can be read that the dominating types preferred to purchase formal shoes on the basis of brand and those that enhance their postures. The protectionist also purchased formal shoes on the basis of brand. The Egotistic consumers purchased formal shoes primarily after consultation with their friends. The conservative consumers were very family oriented. Component 5 comprised of relaxed consumers. The four types of consumers in this category include Practical, Brand Analyst, Unhealthy lifestyle and Nonplayful. From Table 1.12 it can be observed that the practical consumers preferred to purchase shoes from specialized store. The brand analysts were highly influenced by the behaviour of the salesmen. The consumers who lead unhealthy lifestyle preferred to purchase formal shoes from the outlets that had better ambiences. The consumers who generally do not participate in sports activities preferred to purchase unbranded shoes. Component 6 were named as optimistic consumers. Due to multicollinearity only one variable qualified for the study. Therefore there was only one type of consumers i.e., the globe trippers who were passionate about touring around the world. From Table 1.13 it can be observed that the consumers in this category preferred to purchase formal shoes from the store that sold other amenities also. Component 7 was named as strivers. The two types of consumers in this category were active and hard working. The active consumers were colour conscious. The hard working consumers preferred to purchase formal shoes from specialized store (Refer Table 1.15). Component 8 was named as systematic. The three types of consumers in this category include, men who preferred to keep their house neat and clean, men who were attracted towards a distinctive lifestyle and men who were very cautious about saving money. The first category preferred formal shoes that were elegant. The second category preferred to purchase formal shoes from the outlets that had better ambiences. The cautious men who were very particular about saving money preferred branded footwear (Table 1.17). Component 9 was named as dominant. Under this category, there were the conventional consumers who primarily preferred formal shoes that were comfortable. The opinion leaders and the Stay fit type of consumers in this category were very brand conscious (Table 1.19). Component 10 comprised of spiritual and diet conscious consumers. There were three types of consumers in this category, the spiritual, diet conscious and socialising. The spiritual consumers took their purchase decision based on the behaviour of the salesmen. The diet conscious consumers were highly brand conscious and the socialising ones preferred formal shoes that were elegant (Table 1.21). Component 11 was named as stay trim. The two types of consumers in this component include stay trim, the men who often skipped their breakfast and the Sports Viewers, the men who preferred to watch sports than any other channels. The stay trim preferred to purchase formal shoes from the outlets, where the salesmen treated them well. The sports viewers preferred to wear footwear that was primarily comfortable. 90
  • 20. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 – 6510(Online), Volume 3, Issue 3, September- December (2012) CONCLUSION The footwear industry is susceptible to certain vital issues namely, market volatility due to frequent changes in fashion, diverse market, competition from innumerable manufacturers both from the organised and unorganized sector and the dissimilar buying habits of the customers. The conclusion reached through the present study is that mapping the behavioural pattern of the consumers and then associating with the footwear attributes can help the manufacturers and retailers to understand their target market better. Further similar behavioural patterns can also exist in other countries, therefore it becomes easier to tap the global markets. The Indian Footwear is a sector with tremendous opportunity but still untapped. REFERENCES 1. Peter Knorringar, Mar 1998, “Economics of Collaboration in Producer-Trader Relations: Transaction Regimes between markets and hierarchy in the Agra Footwear cluster” Small Business Economics, 10 (2), 193 – 195, Springer 2. Carmody, Padraig, Oct 1998, “Neoclassical practice and the collapse of industry in Zimbabwe: The cases of Textiles, Clothing and Footwear”, 74(4): ProQuest Research Library 319-343 3. Pringle Heather, Jul 3, 1998, “Eight Millennia of footwear fashion” Science, 281, 5373, ProQuest, 23 - 25 4. Segal Troy, Aug (2000), “Footwear Fervor”, ABA Journal, 86, 82 – 84 5. Gayle E Reiber, Douglas G Smith, Carolyn M Wallace, Christy A, Vath B S, Katrina Sullivan, Shane Hayes, Onchee Yu, Don Martin, Mathew Maciejewski Sep/Oct 2002, “Footwear used by individuals with diabetes and a history of foot ulcer” Journal of Rehabilitation Research and Development, 39(5) , ProQuest Research Library, PP 615 – 622 6. Vijay Viswanathan, Sivagami Madahavan, saraswathy Gnansundaram, Gauthan Rajasekar, Ambady Ramachandran, Feb 2004, “Effectiveness of different types of footwear insoles for the diabetic neuropathic foot”, Diabetes Care, 27 (2), ProQuest Research Library Pg 474 – 477 7. Jose Antonio Miranda, 2009, “Competing in Fashion Goods: Firms and Industrial Districts in the development of the Spanish Shoe Industry “, 7, 1 - 34 8. Zakim, Michael, 2007, “A foot in the past: Consumers, Producers and Footwear in the long Eighteenth Century”, Business History Review, 81(1), ProQuest Research Library, 194 - 196 9. S L Rao (September 30, 2000) “India’s Rapidly Changing Consumer Markets”, Economic and Political Weekly, 3570 – 3572 Web References 1. http://www.leatherindia.org/products/footwear.asp, 2. http://en.wikipedia.org/wiki/Bangalore 3. http://www.aplfindia.com/seminars.asp 4. http://www.indianexpress.com/news/footwear-industry-seen-at-rs-38-500-cr/912014/ 91