FACTORS IDENTIFICATION FOR MERCHANDISING OF COSMETICS PRODUCTS USING CLUSTER ANALYSIS- AN EMPIRICAL STUDY IN
DEHRADUN
SUCHITA GERA1 AND DR. RAJAT PRAVEEN DIMRI2
1Research scholar, Uttarakhand Technical University, Dehradun, Uttarakhand, India.
2Associate Professor, Department of Management, Swami Rama Himalayan University, Dehradun, Uttarkhand, India.
ABSTRACT
The present study explores the major driving force for the Indian Consumers to buy Cosmetics. Another objective was to study the visual merchandising and its role in stimulating customers in favor of purchase of cosmetics. In a survey of 193 respondents, the study indicates that television is the most reliable source of information as perceived by the respondents. Factor Analysis was carried out and following five factors has emerged. This include; Creative Assortment, Attractiveness, Interesting, Desirability and Merchandising stimulant. Among the favor factors, merchandising attractiveness has emerged as one of the main important criteria influencing customers in favor of particular brand of cosmetics/skin care products. It is suggested that with the help of various permutation and combination, retailers must enhance product visibility to enhance product preferences and boost consumption.
Key words: Merchandising, Product visibility, merchandising stimulant, etc.
I. INTRODUCTION
In an age of globalizations, average consumers today are very demanding when it comes to the layout and aesthetics of any establishment they visit. They want to be attracted and motivated to enter a shop or stall and in that moment of decision-making rests the difference between a prospect and a sale for retailers. Successful retailing businesses always wish to create a distinct and consistent image in the customers mind.
Visual merchandising has emerged as one of the powerful tool to lure customer. According to the AMA (American Marketing Association), merchandising is a wide term that encompasses promotional activities run by the manufacturer in the form of special presentations that take place within
establishments, as well as initiatives run by the retailer to make the product stand out. In any case, merchandising refers to commercial actions at the point of sale aimed to stimulate customer purchases as soon as they enter the establishment. Segmenting the Consumer Markets: strategy of market segmentation started in the later part of 1950s. It is based on the assumption that all potential customers are not identical and that a firm should develop the different marketing programmes for different groups of people. The purpose of segmentation is the concentration of marketing force on the subdivision to gain a competitive advantage within the segment. Markets can be segmented in many ways.
Segmentation variables are the
criteria that are used for dividing a market into segments. The chosen criteria should be good predictors of the differences in buyer behaviour. There are three broad categories of consumer segmentation criteria.
• Behavioural variables such as benefits sought from the product and buying patterns such as frequency and the volume of purchase may be considered as the fundamental basis.
• Psychographic variables
are used when
purchasing behaviour is correlated with the personality or life style of
the consumers.
Consumers with different personalities or life styles have varying product preferences and may respond differently to the marketing mix offerings.
• Profile variables are valuable in describing the customers of the identified group. The objective of profiling is to identify and locate the customers age wise, socio-economic group wise etc. so that they can be approached by the marketers easily.
The increasing interest in merchandising can be credited to current studies that show that unplanned purchases make up between 46 and 70% of total purchases (Bezawada et al., 2009, Inman et al., 2009 and Bell et al., 2011). That is, there are purchases that are decided at the store and
thus, are very influenced by commercial incentives that arise in it. Thus, from the manufacturer‟
point of view, the effective segmentation on the basis of their opinion about merchandising will be very useful actions to increase the visibility and attraction of their brands at the point of sale.
Beauty and personal care value sales recorded healthy growth despite high inflation and increased retail prices. Beauty may be glamorous, but its allure goes more than skin deep. It's also a growing multi-billion dollar industry packed with ample opportunity to flex creative muscles and hone business and marketing skills. Beauty industry insiders design and promote the skin, hair, body, fragrance, and colour products that help everyone look and feel his or her best.
Visual merchandising is a retail strategy that maximizes the aesthetics of a product with the intent to increase sales. Visual merchandising can also play a role in the look, feel and culture of a brand. Done well, it can create awareness while simultaneously increasing brand loyalty. Most importantly, it can draw customers in and close the sale – all based on the aesthetic quality of your retail display. In the broadest sense, merchandising is any practice which contributes to the sale of products to a retail consumer. At a retail in-store level, merchandising refers to the variety of products available for sale and the display of those products in such a way that it stimulates interest and entices customers to make a purchase.
Today‟s customers have many shopping choices, as the merchandise is available easily.
Some make purchases on the internet they don‟t have to worry about the long hours of operation, parking or getting large purchases home. So as compared to the past with development in technology retailers job have become more difficult. In retail commerce, visual display merchandising means merchandise sales using product design, selection, packaging, pricing, and display that stimulates consumers to spend more. This includes disciplines and discounting, physical presentation of products and displays, and the decisions about which products should be presented to which customers at what time. Retailers need to create an exciting store design with innovative merchandising techniques to make people come and visit the stores.
Here comes the role of visual merchandiser which creates the store design.
Indian Cosmetic Market cosmetic market has witnessed phenomenal growth over the last few years. As the Indian economy is improving, the youth are becoming more inspirational and demand for are increasing substantially.
Traditionally the Indian cosmetic market was dominated by female consumers, but with the passage of time the demand for men‟s grooming products is also increasing and the male are also becoming more beauty conscious.
Over the last few decade, the Indian cosmetic market has witnessed a significant growth of various cosmetic segments such as hair Care, skin care, fragrance, make-up, others etc.
Table-1: Global Cosmetic Market Segments
Cosmetic Products Market
Segments Share
Hair care Shampoos, conditioners, styling
products, 23%
hair color, etc.
Skin care kin moisturizers, cleansers, facial 35%
products, anti-aging products etc.
Fragrance Perfume, Essence, deodorants,
etc. 13%
Make up Lipstick, nail polish, blush, eye
shadow, 17%
foundation, etc.
Others Toothpaste, sunscreens and other
personal 12
care products etc.
Source: http://www.consultancy.uk/news/2810 The increasing beauty concerns
among both genders are propelling the Indian cosmetics industry, which has witnessed a strong growth in the last few years. The country‟s cosmetic sector has emerged as one of the markets
holding and strong growth potential. The market segmentation and choice analysis of customer will help the marketer to position its product effectively.
with rising purchasing power and growing fashion consciousness, the
industry is estimated to expand and call for an effective positioning of products.
Review of Related Literature
In the case of market segmentation, most of the researcher and thinker
immediately think of
psychographics, lifestyles, values, behaviors, and multivariate cluster analysis routines. Market segmentation is a much broader concept. Taehyun Kim, Hon.
Young Lee, (2011) in their study on
"External validity of market segmentation methods: A study of buyers of prestige cosmetic brands", compare and validate the results of two clustering methods for the segmentation of the market for prestige cosmetics in Korea found that Segmentation by traditional K‐means clustering was not judged useful, whereas segments generated by the innovative alternative of mixture regression modelling had clear marketing strategy potential.
T.P. Beane, D.M. Ennis, (1987) in their study
on"Market Segmentation:
A Review", suggested to remain creative when conducting segmentation research. Author suggests many different ways to segment a market like geographic, demographic, psychographic, behaviouristic and image. Apart from this author suggests the some important techniques like automatic interaction detector,
conjoint analysis,
multidimensional scaling and canonical to establish and verify segments.
Orsay Kucukemiroglu, (1999) in his study on "Market segmentation
by using consumer lifestyle dimensions and ethnocentrism identifies consumer market segments existing among Turkish consumers by using lifestyle patterns and ethnocentrism. By using the lifestyle dimensions author extracted, three distinct market segments. The study indicates that consumers in the Liberals/trend setters customer market segment showed similar behavioural tendencies and purchasing patterns to consumers in western countries. The study gives some insight implication to marketers who currently operate in or are planning to enter into Turkish markets in the near future.
Arminda do Paço, Mário Raposo, (2009) in their study on "“Green”
segmentation: an application to the Portuguese consumer market", identify distinct market segments based on several environmental variables. In a survey of 887 respondents, it was found that consumers who buy green products can be differentiated on various issues. The study suggests that there are consumers who are prepared to base their buying decisions on purchasing products that do not harm the environment.
In fact, it was seen that there is a segment of “greener” consumers in the sample that differs significantly in some aspects from the other market segments.
Cathy Bakewell, Vincent Wayne Mitchell, (2003) "Generation Y female consumer decision making styles", examines the decision making of Adult Female Generation Y consumers using Sproles and Kendall‟s (1986) Consumer Styles Inventory (CSI).
The study uses the CSI as a basis for segmenting Generation Y consumers in to five meaningful and distinct decision making groups, namely: “recreational quality seekers”, “recreational discount seekers”, “trend setting loyals”, “shopping and fashion uninterested” and “confused time/money conserving”. The study gives some insight implications for retailers and marketing practitioners targeting Generation Y consumers.
Starting from the positive synergistic effect between the merchandising (commonly understood as „display‟ and promotions, we expect this effect remains positive if the merchandising techniques are implemented properly. The synergistic effect between end of aisle and price promotion is bigger than synergistic effect between the island and price promotion.
II. OBJECTIVE OF THE
STUDY AND
METHODOLOGY
Present study has been taken up with the objectives to segment the Indian cosmetic consumer market into the groups of similar characteristics known as Cluster in respect to their opinion about various merchandising strategies.
Thus the customers included in different clusters can be served separately as per their choice and requirement.
Assumption of Hypothesis
It was hypothesised that the mean of different merchandising factors influencing customers in favour of cosmetic products does not differ significantly across the
professional categories and level of education of the Respondents.
Present study is based on descriptive study. Study is based on primary as well as secondary data. Secondary data was collected from various news paper, research journals, magazines, internet etc.
primary data was collected from respondents using questionnaire.
A structure questionnaire were designed covering different aspect on merchandising like product display, promotional techniques, product lay out, product assortment, product visibility in the store and consumer buying behaviour. The data used in this study has been compiled from the customers visiting in organised retail store belong to some of the important retail outlet in Dehradun. These data offer information on, merchandising techniques and consumer buying behaviour of cosmetics during a time period of ten weeks.
Questionnaire was used personally visiting different organised retail department. A total 193 responses were received and taken for the study. The collected information was systematically arranged, tabulated and appropriate analysis was carried out. An SPSS statistical package, K-means clustering has been used, for clustering 193 randomly selected respondents on the basis of their similarities in their preferences for the product merchandising.
Particularly hierarchical clustering method is used to find out the number of clusters first and then K-means clustering method is used to give the output. The method of clustering is based on commonly used Euclidian distance measure program. The sample consists of
men and women of the different age groups of the city Dehradun.
The selected sample is explored to fifteen attributes (as tabulated below) on five point scale. Where 1
indicates the most unfavourable and 5 indicates the most favourable attitude. Table 1 indicates the demographic characteristics of respondents Table 2: Demographic Characteristic of Respondents
Characteristics
Group Category Of Respondents Total Number
Of Respondents
No. of
Respondents
193 %
100
Upto 20 Years 14 7.3
21-30 Years 75 38.9
Age 31-40 Years 62 32.1
41 to 50 Years 36 18.7
Above 50 Years 6 3.1
Gender Male 109 56.5
Female 84 43.5
Marital Married 123 63.7
Status Unmarried 70 36.3
Upto 2 Members 57 29.5
Family size 3-5 Members 129 66.8
More than 5 members 7 3.6
Upto Matriculation 6 3.1
Education Upto Intermediate 8 4.1
Graduate 56 29.0
Qualification
Post Graduate 93 48.2
Others 30 15.5
Level of Income
Upto Rs15000 PM Rs.15001 to Rs25000PM Rs25001 to Rs35000 PM Rs45001 to Rs55000PM
31 37 70 19
16.1 19.2 36.3 9.8
Student 30 15.5
Business 16 8.3
Profession Services 97 50.3
Professional 8 4.1
Housewife 35 18.1
Others 7 3.6
Source: Data from primary sources
Cosmetic products play an essential role in everyone‟s life.
Today most of the people use soap, shampoo, conditioner, deodorant,
toothpaste, shaving cream, aftershave, cleanser, perfume, make-up and lots of other products. The purpose of cosmetic products is to enhance well-being and as a result, self-esteem.
Through innovation, cosmetic manufacturers provide better and better products while ensuring that consumer safety remains their highest priority.
Factor Analysis
Understanding consumer perception and attitude towards merchandising and its role in cosmetics/skin care product has been of a major interest for marketer at different levels. The perceptions of customer are affected by exogenous factors such as merchandising and market interaction among the major players like consumer, manufacturer and society as whole. The empirical study indicates that consumers perception are based on their own personal attributes such as age and education, as well as exogenous factors merchandising of product and its positioning in the prospect‟s mind. Exogenous factors such as merchandising strategies may also impact both consumer purchase decisions and manufacturer decisions. These components are viewed together since they are highly interdependent and together represent forces that influence how the consumer will react to the object. Taking these into consideration, an attempt was made to identify the influencing merchandising factors and their role in their purchase decisions.
For this respondents were asked to rate their views on the statement
related to the merchandising variable. The response to these statements was recorded on a scale of 1 to 5 in order of their preference. The exploratory factor analysis is used in order to identify the motivational factors influencing customer in favor of green environment and use of green products. Principal Component analysis was employed for extracting factors and orthogonal rotation with Varimax is applied. As latent root criterion is used for extraction of factors, only the factors having latent roots or Eigen values greater than one are considered significant; all other factors with latent roots less than one are considered insignificant and disregarded. The extracted factors along with their Eigen values are shown in table 6. The factors have been given appropriate names on the basis of the group representation of the variables. The statements that are asked for rating, the labels and factor loading and the names of the factors have been summarized in Tables 6. The KMO measure of sampling adequacy for the items is 0.803 (that is, > 0.5), indicating sufficient inter-correlations of the Bartlett's Test of Sphericity, which is found to be significant (Chi- square = 1140.184< 0.005). Thus, the sample size of 193 was adequate and satisfactory in this study. The cronbach alpha for each factor is 0.933. Cronbach alpha for all the factors are greater than 0.6 which means that the scale scores for each of the dimensions are reasonably reliable (Hair et al., 1998). There are five factors each having Eigen value exceeding one for merchandising factors. Eigen values for five
factors are 5.147, 1.758, 1.454, 1.102 and 1.073 respectively. The index for the present solution accounts for 70.225% of the total variations for the motivational factors. It is a pretty good extraction because we are able to economize on the number of choice factors (from 15 to 5 underlying factors), we lost 29.774% of information content for choice of variables. The percentages of variance explained by factors one to seven are 34.31%, 11.717%, 9.696%, 7.347% and 7.154%
respectively. Large communalities indicate that a large number of variance has been accounted for by
the factor solutions. Varimax rotated factor analysis results for motivational factors are shown in table which indicates that, after 5 factors are extracted and retained the communality is 0.598 for variable1, 0..677 for variable 2, 0..561 for variable 3 and so on. It means that approximately 59.82%
of the variance of variable1 is being captured by extracted factors together. The proportion of the variance in any one of the original variable which is being captured by the extracted factors is known as communality (Nargundkar, 2002).
Table 3: Principal Component analysis with Rotated Component and Associate Variable
Component Co
CreativeAssortmen Attractiveness Interesting Desirable Merchandising
mm una lity
When I see a good deal, I tend to buy more .74 .598
then I intended to buy 5
I tends to enter the store when I am
.72 .677
attracted by an eye catching window
Display 0
I get idea about what to buy when looking .69 .561
through in store display 2
When I see cosmetic in new form on .69 .34 .650
display, I tend to buy it 1 9
I tend to rely on store display when I make .52 .438 - .647
a decision to purchase cosmetics 4 .335
When I see Cosmetic that catches my eye, I
.871 .773
tend to buy it
When I see cosmetics that I like on in store
.842
.787
display , I tend to buy it
After I make an impulsive purchase I feel
.707
.47 .742
Happy 1
I feel compelled to enter the store when I
.53 .761
see an interesting window display of .692
cosmetic products 0
I tend to try an product that catches my eye .32 .419 .666 .703
when I pass by 4
I go for shopping of cosmetics product to
.606
.52 .704
change my mood 8
I feel a sense of excitement when I make .82 .739
an impulsive purchase of cosmetics 6
I have difficulty in controlling my urge to
.71 .596
buy when I see good offer on cosmetic
9 Product
When I see an special promotion sign/ offer .756
, I go to look at that cosmetics and tend to .829
buy it
When I walk along the isle I tend to look .32 .488 .554 .703
through close to it 7
Eigen Values
5.14 1.10
7 1.758 1.454 2 1.073
% of Variation
34.3 11.71 7.34
1 7 9.696 7 7.154 Cumulative % of Variation
34.3 46.02 55.72 63.0 70.22
1 7 3 71 5
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 13 iterations.
Principal components & associated Variables indicate that the first factor “creative assortment” shows the role of media which is the combination of the variables, i.e.
“When I see a good deal, I tend to buy more then I intended to buy I tends to enter the store when I am attracted by an eye catching window display I get idea about what to buy when looking through in store display When I see cosmetic in new form on display, I tend to buy it I tend to rely on
store display when I make a decision to purchase cosmetics and accounts 34.31% variance of the total variances. The second factor is “Attractiveness; is the combination of variable like, When I see Cosmetic that catches my eye, I tend to buy it When I see cosmetics that I like on in store display , I tend to buy it and accounts 11.717% variance of the total variances. The third factor is the Interesting factor which is the combination of variables; After I
make an impulsive purchase I feel happy I feel compelled to enter the store when I see an interesting window display of cosmetic products I tend to try an product that catches my eye when I pass by I go for shopping of cosmetics product to change my mood and this factor accounts for 9.696% of total variance. Fourth factor is the desirability factor which is the combination of variables; “I feel a sense of excitement when I make an impulsive purchase of cosmetics I have difficulty in controlling my urge to buy when I see good offer on cosmetic product and is accounted for 7.347% of total variance. The fifth factor is the Merchandising stimulant and is the association of variables i.e When I see an special promotion sign/ offer , I go to look at that cosmetics and tend to buy it When I walk along the isle I tend to look through close to it and is accounted for 7.154% of total variances.
Cluster analysis
Cluster analysis is a collection of statistical methods, which identifies groups of samples that behave similarly or show similar characteristics (Nethra Sambamoorthi, 2003). In common parlance it is also called look-a-like groups. The simplest mechanism is to partition the samples using
measurements that capture similarity or distance between samples. In other words, Clustering refers to the process of grouping samples so that the samples are similar within each group. For the present study hierarchical clustering was carried out to classify the group on the basis of factors identified by the factor analysis. Factor scores derived from Factor analysis is the starting point for cluster analysis.
Factor scores represented a shopper‟s response to all attributes captured in a factor. So the clustering done on factor scores will create clusters on the basis of five identified factor (from factor analysis) rather than on 23 attributes. The biggest dilemma was to whether to use hierarchical clustering technique or non hierarchical clustering technique.
Hierarchical clustering creates a dendogram or a tree like structure on the basis of the relationship between entities or individuals. In non hierarchical clustering, the researcher has to define the number of clusters before the analysis. In this research, hierarchical clustering was used to identify the number of clusters.
Table-IV Final Cluster Centers Cluster
1 2 3 4 5
Creative
Assortment 4.44 3.81 2.40 3.33 2.75 Attractiveness 4.59 2.58 2.44 4.08 2.52 Interesting 4.25 3.75 1.92 3.41 2.99 Desirable 4.31 3.66 1.83 3.66 3.43 Merchandising
4.31 3.70 2.22 3.28 2.57 Stimulant
Number of Cases in each Cluster
Cluster 1 61.000
Cluster 2 32.000
Cluster 3 9.000
Cluster 4 69.000
Cluster5 22.000
Valid 193.000
Missing .000
First cluster is composed of responses 85 respondents whose have given importance to Social media and Desirability for the product as it has scored highest mean of 3.96 followed by Value Addition through social media and Reliability and dependability on social media with mean 3.49.
Second cluster is the respondents of 24 member who have given higher importance to Social media and Desirability (3.29) and Reliability and dependability on social media 2.73. Third cluster is of 9 respondents who have given more importance to Socialization Information sharing through social media as it scored highest mean of 3.42. Fourth cluster is of 25 respondents who have given importance to Reliability and dependability on social media with mean 4.68 followed by Social media and Desirability with mean 4.65.
III. CONCLUSIONS AND SUGGESTIONS:
In the present fast changing economic environment, the enterprises are in a continuous effort to stay successful and be profitable. For this reason, the enterprises use several merchandising techniques to enhance the visibility of the product the study reveals that almost half of the respondents (48.2%) were of the opinion that advertisement creates the need for the cosmetic/skin care product to some extent. It was also observed that the internet has also made its pace the media as substantial amount of consumer are viewing the advertisement and taking information from internet. The study indicates that television is the most reliable source of information as perceived by the respondents. Through innovation, cosmetic manufacturers provide better and better products while ensuring that consumer safety
remains their highest priority.
Factor Analysis was carried out and following five factors has emerged. This include; Creative Assortment, Attractiveness,
Interesting, Desirability and Merchandising stimulant. Among the favour factors, merchandising attractiveness has emerged as one of the main important criteria influencing customers in favour of particular brand of cosmetics/skin care products. It is suggested that with the lhelp of various permutation and combination , retailers must enhance product visibility to enhance product preferences and boost consumption .
REFERENCES:
1.AC Nielsen, 2013 AC Nielsen Anuario Nielsen (2013) http://es.nielsen.com/news/2013 0213
2.Arminda do Paço, Mário Raposo, (2009) "“Green” segmentation: an application to the Portuguese consumer market", Marketing Intelligence & Planning, Vol. 27 Iss: 3, pp.364 – 379 DOI http://
dx.doi.org/10.1108/02634500910 955245
3.Arminda do Paço, Mário Raposo, (2009) "“Green” segmentation: an application to the Portuguese consumer market", Marketing Intelligence & Planning, Vol. 27 Iss: 3, pp.364 – 379 DOI http://
dx.doi.org/10.1108/02634500910 955245
4.Bezawada et al., 2009 R.
Bezawada, S. Balachander, P.K.
Kannan, V. Shankar Cross- category effects of aisle and display placements: a spatial modeling
approach and insights J.
Marketing, 73 (2009), pp. 99–117 5.Bhalla Swati, Anurag S., Visual Merchandising,(2009),Understandi ng Retail and Visual Merchandising,2-30,Tata McGraw Hill .
6.Burton, D.R. Lichtenstein, R.G.
Netemeyer Exposure to sales flyers and increased J. Advert. Res., 39 (1999), pp. 7–14
7.Chandon et al., 2009 P.
Chandon, J.W. Hutchinson, E.T.
Bradlow, S.H. Young Does in- store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase J. Marketing, 73 (2009), pp. 1–17 8.Chaudhuri, 2000 A. Chaudhuri A macro analysis of the relationship of product involvement and information search: the role of risk J.
Marketing Theory Pract. (winter) (2000), pp. 1–15
9..Chevalier, 1975 M. Chevalier Increase in sales due to in-store display J.Marketing Res., 12 (1975), pp. 426–431
10.Cooper et al., 1996 L.G. Cooper, D. Klapper, A. Inoue Competitive- component analysis: a new approach to calibrating asymmetric market-share models J. Marketing Res., 33 (2) (1996), pp. 224–238
11.Inman, R.S. Winer, R. Ferraro The interplay among category characteristics, customer characteristics, and customer activities on in-store decision
making J. Marketing, 73 (2009), pp. 19–29
12.Jarboe G R and McDaniel C D (1987), “ A profile of browsers in regional shopping malls”, Journal of the Academy of Marketing Science, Vol. 15 (Spring), pp. 46- 53
13.K.L. Ailawadi, K. Gedenk, C.
Lutzky, S. Neslin,Decomposition of the sales impact of promotion- induced stockpiling, J. Marketing Res., 44 (2007), pp. 450–467
14.K.L. Ailawadi, J.P. Beauchamp, N. Donthu, D.K. Gauri, V.
Shankar,Communication and promotion decisions in retailing: a review and directions for future research, J. Retailing, 85 (1) (2009), pp. 42–55
15.Kunwar, Pooja, “Visual Merchandising: A Silent Salesman of Retailers,” Marketing Mastermind, vol-X, no.2 pp.29-33, February 2010
16.Madrid (1975) Díez-De Castro et al., 2006 E.C. Díez-De Castro, F.J. Landa-Bercebal, A. Navarro- García Merchandising Pirámide, Madrid, España (2006)
17.Orsay Kucukemiroglu, (1999) in his study on "Market segmentation by using consumer lifestyle dimensions and ethnocentrism”, European Journal of Marketing, Vol. 33 Iss:5/6, pp.470 – 487
18.Mela et al., 1998 C.F. Mela, K.
Jedidi, D. Bowman The long-term impact of promotions on consumer stockpiling behavior J. Marketing Res., 35 (1998), pp. 250–262
19.Neslin and Stone, 1996 S.A.
Neslin, L.G.S. Stone Consumer inventory sensitivity and the postpromotion dip Marketing Lett., 7 (1) (1996), pp. 77–94
20. Rook D W (1987), “The buying impulse”, Journal of Consumer Research, Vol. 14, pp. 189-99.
21.Sheth, 1983 J.N. Sheth An integrative theory of patronage preference and behaviour W.R.
Darden, R.F. Lusch (Eds.), Patronage Behaviour and Retail Management, Elsevier-North, Holland (1983), pp. 7–28
22.Smith and Burns, 1996 P.
Smith, D.J. Burns Atmospherics and retail environments: the case of the power aisle Int. J. Retail Distrib. Manage., 24 (1) (1996), pp.
7–14
23.T.P. Beane, D.M. Ennis, (1987) in their study on "Market
Segmentation: A
Review",European Journal of Marketing, Vol. 21 Iss: 5, pp.20 – 42, DOI,http://dx.doi. org/10.11 08/E UM0000000004695
24.V. Shankar, L. Krishnamurthi Relating price sensitivity to retailer promotional variables and pricing policy: an empirical analysis J.
Retailing, 72 (3) (1996), pp. 249–
272
25.Taehyun Kim, Hoon-Young Lee, (2011) in their study on "External validity of market segmentation methods: A study of buyers of
prestige cosmetic
brands"European Journal of Marketing, Vol. 45 Iss: 1/2, pp.153
– 169. DOI http://dx.do i.org/10 .1108/03090561111095630
26.V. Shankar, J.J. Inman, M.
Mantrala, E. Kelley, R. Rizley Innovations in shopper marketing:
current insights and future research issues J. Retailing, 87 (2011), pp. 529–542
