Title of the research paper: Factors affecting impulse buying behavior in FMCG sector with special reference to big Bazzar and Vishal Megamart in Delhi/NCR region. There are many factors which affect Consumers Impulse Buying Behaviour in FMCG market but we are only analysing marketer’s driven factors which are: Price and discount Advertising and sales promotion Visual merchandising Emotional attachment Company Income Festival season
Key words:Impulse buying, Retail industries in India, FMCG sector
Abstract This paper is an attempt to find the variables/factors that effects customer impulse buying behaviour behaviour in FMCG sector considering considering retail retail market in India. The impact of various impulse buyin buying g factor factorss like like sales sales and promot promotion ions, s, placeme placement nt of product products, s, window window merchan merchandis dising ing,, effective price strategy etc on customer impulse buying behaviour has been analyzed. A hypothetical model has created in this paper which has been taken into consideration for our research work on impulse buying beahviour of the consumers. The study is based on the primary data collected from Vishal Megamart and Big Bazzar from the area of DELHI and NCR regions with the help of structured questionnaire on ricter scale. Data analysis has been done using SPSS software. The statistical analysis method employed in this study is Factor Analysis. After the through analysis of the available data it has been found out that since income of indivi individual dual is increa increasin sing g and more more and more more people people are moving moving towards towards wester western n cultur culturee in dressing dressing sense, in eating etc so the purchasing purchasing power of the people has really gone up and thus the impulse buying of the commodities is on a great increment mainly due to pricing strategies of retail players and full of festivals throughout the year.
Introduction Impuls Impulsive ive purchas purchasing, ing, genera generally lly define defined d as a consume consumer’s r’s unplan unplanned ned purchas purchasee which which is an important part of buyer behavior. It accounts for as much as 62% of supermarket sales and 80% of all sales in certain product categories. Though impulsive purchasing has attracted attention in consumer research. Unfortunately, there is a dearth of research on group-level determinants. This research suggests that the presence of other persons in a purchasing situation is likely to have a normative influence on the decision to make a purchase. The nature of this influence, however, depends on both perceptions of the normative expectations of the individuals who exert the influence and the motivation to comply with these expectations. Peers and family members, are the two primary sources of social influence, often have different normative expectations. Thus, it has been evaluated two factors that are likely to affect the motivation to conform to social norms: a) The inherent inherent susceptibi susceptibility lity to social social influence influence and and b) The struct structure ure of the group group Group cohesiveness refers to the extent to which a group is attractive to its members. The theory proposed by Fishbein and Ajzen helps conceptualize these effects. This theory assumes that behavior is a multiplicative function of expectations for what others consider to be socially desirable and the motivation to comply with these expectations.
Company profile In the present research paper, the study has been focused on Big Bazzar and Vishal Megamart to know the impulse buying behaviour of the consumers. The brief profiles of two companies are as follows: Big Bazzar
Big bazaar is owned and operated by Future Bazaar India Ltd., a subsidiary of Pantaloon Retail (India) Limited. As part of India’s largest retail chain, it enjoys the benefits of buying in bulk for the entire group and keeps the margins low, so that customers get a great range of products at great prices. Pantaloon Retail (India) Limited led by Kishore Biyani is the country's largest retailer. It owns and operates multiple retail formats including Pantaloons, Big Bazaar, Food Bazaar, Central, E-Zone, Fashion Station, Depot and many others.
Pantaloon Retail was selected as the Best of Best Retailers in Asia by Retail Asia-Pacific Top 500 magazine in 2006.Big Bazaar was awarded the CNBC-Awaaz Consumer Awards in 2006 and the Readers' Digest Platinum Brand Award 2006. Further details on Pantaloon Retail are available on www.pantaloon.com Vishal Megamart
Vishal Vishal Megamart is India’s India’s first hyper market which is having 126 showrooms in 83 cities cities / 20 states. Vishal is one of fastest growing retailing groups in India. Its outlets cater to almost all price ranges. The showrooms have over 70,000 products range which fulfills all your household needs, and can be catered catered to under one roof. It is covering about 2059292 lac sq. ft. in 18 states across India. Each store gives you international quality goods and prices hard to match. The group had a turnov turnover er of Rs. 1463.12 1463.12 millio million n for fiscal fiscal 2005, 2005, under under the dynamic dynamic leader leadershi ship p of Mr. Ram Chandr Chandraa Aggarwa Aggarwal. l. The group had of turnove turnoverr Rs 2884.43 2884.43 million million for fiscal fiscal 2006 and Rs. 6026.53 million for fiscal 2007. The Vishal stores offer affordable family fashion at prices to suit every pocket.
Research methodology The resear research ch methodo methodolog logy y was divided divided into into two stages stages which which involv involvee two source sourcess for collecting the data in order to achieve the objective of project. 1. Colle Collect ctin ing g data data regar regardi ding ng the the pote potent ntia iall cust custom omer erss from from the the exis existi ting ng outle outlets ts of Big Big Bazzar & Vishal Megamart 2. Col Collecti ecting ng the prim primar ary y data data dir direct ectly wit with the cust custom omer er wit with the hel help of the the questionnaire (Refer Annexure-1).
The research methodology was divided into two stages which involve two sources for collecting the data in order to achieve the objective of project. hypothetical consumer impulse buying behaviour model We have taken into consideration consideration a hypothetical (Refer Fig 4) which has been mentioned in conclusion and findings part.
Research design
In this project multi stage sampling sampling is used because the total population was too large and due to time constraint it was not practically possible to make a list of entire population .At first stage I have divided sample area wise and then further divided it into income status so that I can get correct and related information.
Sample design •
Sampling Unit: Vishal Megamart And Big Bazzar Customers
•
Sampling Size: 100 potential customers
•
Sampling technique: multistage sampling
•
Sampling area: Delhi and NCR regions
•
Contact Method: Personal Contacts.
Literature review There was a study conducted by “Sales & Customer Service Department” of “Texas Agricultural Extension Service Texas A&M University System College Station, Texas”. According to this study the researchers find the tips to increase the impulsive sales of the flowers. The findings of the study were: Tips for Boosting Impulse Sales:
Creating variety in the department with frequent changes of display and movement of regularly sold merchandise also entices customers. Recognizing items that typically make a minimal contribution to sales and replacing them with items that create "sales appeal" increases the likelihood of impulse sales. Displays that tie in with a national slogan or storewide theme generate interest, as do displays that highlight special products and services. •
Tip 1: use color to create original, eye-catching displays.
•
Tip 2: use themes to create interest in unusual products and renew interest in everyday items.
•
Tip 3: keep keep undecor undecorate ated d plants plants availa available ble to attrac attractt consume consumers rs who are buying buying for themselves.
•
Tip 4: create displays that emphasize special products o r services.
•
Tip 5: change stock and displays often so consumers are drawn into the department each week.
•
Tip 6: be flexible enough to change an item or arrangement that isn¹t selling.
•
Tip 7: have a person on hand to provide information and assistance at all times.
•
Tip 8: create a friendly, comfortable atmosphere with accessible displays that encourage browsing.
•
Tip 9: offer only quality plants and floral arrangements.
•
Tip 10: situate the department so that customers know where it is and can see it from most areas of the store.
Data analysis Demographic profile of respondents Descriptive profile of respondents (n=100)
Gender Fig 1 Demographic data for genders
The above graph inferences that most of the time male genders are the one who goes for impulse buying decision.i.e. 88% are male respondents in our research while female comprises of only 12% of the toatal respondents. Age
Fig .2. Demographic data considering different age groups
From the graph its easily visible that the age group 18-25 are the one who go maximum times for impulse buying since this is the age group when they are most active having some power of purchasing too.
Occupation Fig. 3. Demographic data considering their occupations
From the graph its clear that most of the impulse buying is being done by students which compromises of 51% of total 100 respondents 2 3% is for the services providing people and 20 % to the business oriented person and at last only 6% comprises of house wife’s.
Factor Analysis for factors affecting impulse buying decision of consumers To continue towards the main analysis, factor analysis has been performed to identify the key dimensions affecting purchase of FMCG products provided at these retail stores. The respondent rating ratingss were were subjec subjectt to princi principal pal axis axis factor factoring ing with with varima varimax x rotati rotation on to reduce reduce potent potential ial multicollinearity among the items and to improve reliability on the data (Refer Table 6: Rotated Factor Factor Matrix Matrix). ). Varima Varimax x rotati rotation on (with (with Kaiser Kaiser Normal Normaliza izatio tion n was converg converged ed in twenty twenty six itera iteratio tions. ns. Twenty Twenty Six items items were were reduced reduced to seven seven orthogo orthogonal nal factor factor dimens dimension ionss which which explained 72.357% of the overall variance (Refer Table 4) indicating that the variance of original values was well captured by these seven factors. The seven factors and their components is given in table 7. (Refer Table 7) Reliability of Data ( KMO and Bartlett's Test) Analysis done with the help of statistical software SPSS Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Sphericity
Approx. Chi-Square
.605 1318.916
Df
325
Sig.
.000
Kaiser-Meyer-Olkin
[Index for comparing the magnitudes of the observed co-relation coefficient to the magnitude of the partial correlation coefficients] From the above table, we can interpret that there is no error in 60.5% of the sample and in the remaining 39.5%, there may occur o ccur some sort of error. Bartlett’s Test of Sphericity
Strength of relationship among variables is strong. It presents good idea to proceed to factor analysis for the data. Ho: There is significant indifference of all the factors affecting impulse buying decision H1: There is significant difference of all the factors affecting impulse buying decision
The observe significance significance level is 0.0000 which is less than .05, which is small enough to reject the hypothesis. It means there is a significant difference between the factors affecting impulse buying decisions. Communality”- Common Factor Variance
Commun Communali ality ty of each statement statement refers refers to the varian variance ce being being shared shared or common common by other other statements. With reference to the first statement, the extraction is .639 which indicates that 63.9% of the variance is being shared or common to other statements. (Refer Table 2.) “Eigen Value” : Indicates the amount of variance in the original variables accounted or by each
component. The total initial variance in the new components will be 26. Table 2: Communalities Common Factor variance
Attractive price of product affects my impulse buying behavior Discount offers regarding product attracts me Various schemes like (buy 1 get 1 free) affects my buying behavior positively. Availability of discounted products motivates me to buy. Advertisement of product in print and visual media attracts me to buy Various promotional activities regarding product motivates to buy the products Hording and pamphlets of product help me in impulse buying. Any event organized by organization affects my buying behavior. Display of product in store attracts my attention. Packaging of product attracts me to by the products. Placing of product in store gains my attention towards it. Compatibility Compatibility of another product with the product you are buying Emotional attachment attachment with product is a motivational factor to buy product Behavior of sales person affects my buying behavior. Popularity of product increases recall value and helps in impulse buying. Changing trend in society is a major factor in impulse buying The person with whom you are going for shopping influences buying behavior. Comments of reference group influence my buying behavior. Kind of product which i am buying Your income status affects my impulse buying behavior. Standard of living has a role to play in buying products.
Init nitial ial 1.000
Extra xtract ctio ion n .639
1.000
.803
1.000
.647
1.000
.808
1.000
.752
1.000
.616
1.000
.823
1.000
.843
1.000
.647
1.000
.705
1.000
.841
1.000
.596
1.000
.748
1.000
.793
1.000
.709
1.000
.594
1.000
.788
1.000
.683
1.000
.760
1.000
.652
1.000
.724
Your perception about saving and investment Special occasion motivate me to buy. Requirement of product in festival season prompts me to buy. Traditions and customs triggers my purchase decision Various festival discounts on product induces purchase of product.
1.000
.763
1.000
.574
1.000
.754
1.000
.780
1.000
.770
Table 3: Total Variance Explained Comp onent
Initial Eigenvalues
Total
% of Variance
Cumulati ve %
Extraction Sums of Squared Loadings % of Varianc Cumulativ Total e e%
Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative %
1
7.971
30.658
30.658
7.971
30 30.658
30.658
4.735
18.213
18.213
2
3.324
12.786
43.445
3.324
12 12.786
43.445
3.308
12.724
30.937
3
1.961
7.541
50.986
1.961
7.541
50.986
3.108
11.955
42.892
4
1.710
6.575
57.561
1.710
6.575
57.561
2.620
10.079
52.971
5
1.442
5.547
63.108
1.442
5.547
63.108
1.734
6.670
59.641
6
1.276
4.908
68.016
1.276
4.908
68.016
1.654
6.363
66.004
7
1.129
4.341
72.357
1.129
4.341
72.357
1.652
6.353
72.357
8
.914
3.514
75.871
9
.853
3.282
79.154
10
.807
3.103
82.257
11
.743
2.857
85.115
12
.606
2.332
87.447
.519
1.998
89.445
14
.465
1.787
91.231
15
.384
1.476
92.707
16
.349
1.342
94.049
17
.286
1.101
95.149
18
.267
1.028
96.177
19
.222
.855
97.032
20
.191
.734
97.766
21
.172
.660
98.426
22
.139
.533
98.959
23
.105
.404
99.364
24
.077
.294
99.658
25
.061
.233
99.891
26
.028
.109
100.000
13
Table 4: Distribution in different components
Comp Compon onen entt 1
Expl Explai ain n a vari varian ance ce of of 4.73 4.735, 5, whi which ch is 18.213 % of the total variance of
Cumulative Frequency 18.213%
26 Comp Compon onen entt 2
Expl Explai ain n a vari varian ance ce of of 3.30 3.308, 8, whi which ch is 12.724 % of the total variance of 26 Expl Explai ain n a vari varian ance ce of of 3.10 3.108, 8, whi which ch is 11.955% of the total variance variance of 26 Expl Explai ain n a vari varian ance ce of of 2.62 2.620, 0, whi which ch is 10.079 % of the total variance of 26 Expl Explai ain n a vari varian ance ce of of 1.73 1.734, 4, whi which ch is 6.670 % of the total variance of 26 Expl Explai ain n a vari varian ance ce of of 1.65 1.654, 4, whi which ch is 6.363 % of the total variance of 26 Expl Explai ain n a vari varian ance ce of of 1.65 1.652, 2, whi which ch is 6.353 % of the total variance of 26
Comp Compon onen entt 3
Comp Compon onen entt 4
Comp Compon onen entt 5
Comp Compon onen entt 6
Comp Compon onen entt 7
30.937%
42.892%
52.971%
59.641%
66.004%
72.357%
Fig 4. Screen plot for the Factor Analysis S creeP lo t
8
e6 u l a v n e4 g i E 2
0
1
2
3
4
5
6
7
8
9
1 0
1 1
1 2
1 3
1 4
1 5
1 6
1 7
1 8
1 9
2 0
2 1
2 2
2 3
2 4
2 5
2 6
C o m p o n en tN u m b e r
With the help of Table 3 and 4, we can interpret that 26 statements are now reduced to 7 components components contributing contributing 72.357% of the total variance. With the help of Fig4. Screen plot, we can just visualize that 7 factors are reduced with Eigen value greater than 1.0000 Table 5. Component Matrix:
This table reports the factor loadings for each variable on the unrotated components or factors. Component v1
1 .689
2 .214
3 -.064
v2
-.027
.046
v3
-.045
v4
4
5 -.062
-.220
6 -.091
7 .231
.744
.373
.116
.061
.301
.487
.167
.179
.422
-.010
-.412
.119
.600
-.048
-.474
.174
.420
.026
v5
.788
-.096
.074
.164
-.195
.225
-.017
v6
.756
-.120
.091
-.048
.002
-.013
-.139
v7
.765
-.035
-.008
.264
.197
.357
-.023
v8
.676
-.196
-.113
-.476
.103
.113
-.292
v9
.654
-.099
.160
-.283
-.281
.129
-.091
v10
.807
-.106
.075
.084
-.143
-.072
-.067
v11
.816
.045
-.189
-.002
.271
-.008
-.253
v12
.629
-.212
-.038
-.141
.221
.165
.240
v13
.443
.314
-.237
.536
.222
-.126
-.210
v14
.647
.287
.168
.410
-.030
-.159
.265
v15
.739
.087
-.035
.291
-.041
.145
-.217
v16
.346
.259
.093
.093
-.606
.143
-.048
v17
.331
-.720
-.150
.326
-.041
.171
.021
v18
.328
-.744
.055
-.085
.071
.074
-.028
v19
.420
-.664
-.167
-.111
.104
-.115
.282
v20
.340
.400
-.547
-.094
-.036
.045
.256
v21
.496
.428
-.368
.041
.054
-.022
.393
v22
.606
.183
.307
-.252
.235
-.386
-.015
v23
-.067
.533
.169
-.050
-.278
.421
-.020
v24
.405
.152
.474
-.249
.429
.089
.298
v25
.492
.011
.540
-.229
-.297
-.291
-.143
v26
.538
.313
-.239
-.109
-.134
-.544
-.023
Extraction Method: Principal Component Analysis.
Each Each number number repres represent entss the correl correlati ation on betwee between n the item item and the unrota unrotated ted factor factor.. This
correlation helps to formulate an interpretation of the factors fa ctors or components. This is done by looking for a common thread among the variables that have large loadings for a particular factor or component. It is possible to see items with with larg large e load loadin ings gs on seve severa rall of the the unro unrota tate ted d fact factor ors, s, whic which h makes akes interpretation difficult. In these cases, it can be helpful to examine a rotated solution. Table 6: Rotated Component Matrix Component 1
2
3
4
5
6
7
v1 v2
.301
.152
.390
.527
.080
.047
.295
.025
-.078
.055
-.217
.014
.862
.049
v3
.291
-.674
.041
-.128
.097
.071
-.273
v4
.011
-.380
.005
.251
.748
-.147
.136
v5
.653
.310
.231
.134
.071
.094
.381
v6
.557
.264
.454
.071
.111
-.033
.107
v7
.818
.216
.032
.153
.232
.149
.085
v8
.433
.323
.441
-.013
.408
-.437
.012
v9
.325
.295
.466
.013
.240
-.107
.411
v10
.579
.292
.454
.166
-.042
.033
.217
v11
.750
.101
.346
.240
.171
-.208
-.134
v12
.388
.473
.180
.226
.359
.075
-.063
v13
.680
-.286
.003
.330
-.259
.028
-.164
v14
.485
-.024
.293
.461
-.134
.470
.143
v15
.775
.038
.185
.158
-.015
.003
.217
v16
.198
-.088
.167
.153
-.090
.011
.698
v17
.428
.701
-.189
-.158
-.230
.003
.008
v18
.238
.712
.123
-.301
.029
-.055
-.098
v19
.145
.813
.151
.105
-.010
-.038
-.206
v20
.145
-.043
-.064
.730
.163
-.242
.087
v21
.255
-.019
.044
.794
.153
.034
.042
v22
.245
-.030
.760
.186
.195
.142
-.180
v23
-.028
-.436
-.128
.042
.296
.086
.520
v24
.144
.047
.374
.087
.585
.463
-.163
v25
.109
.054
.795
-.131
-.003
.142
.310
.560
-.197
-.223
-.001
v26
.181 -.085 .573 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.
With the help of table 6, we can categorize each statements depending upon the factor loadings and shown in table7. Table 7: Factors Factor 1: S5 : Advertisement of product in print and visual media S6 : Various promotional activities regarding product • S7 : Hording and pamphlets pamphlets of product • S10 : Packaging of product • S11 : Placing of product in store • S13 : Emotional attachment with product • S14 : Behaviour of sales person • S15 : Popularity of product • S17: The person with whom you are going for shopping • Factor 2: •
• • •
S3 : Various schemes like (buy 1 get 1 free) S12: Compatibility of another product with the product you are buying S18: Influenced by other people
S19: Kind of product which you are buying Factor 3: •
S8 : Any event organized by organization S9 : Display of product in store • S22 : Your perception about saving and investment • S25 : Traditions and customs • S26 : Various festival discounts on product • Factor 4: S1 : Price of product • S20 : Your income status • S21 : Standard of living • Factor 5: •
S4 : Availability of product S24 : Requirement of product in festival season • Factor 6: S2 : Discount offers regarding product • Factor 7: •
• •
S16 : Changing trends in society S23 : special occasions
Table 8: Component Score Coefficient Matrix Component S1 S2
1 .019
2 -.096
3 .179
4 -.106
5 -.051
6 .347
7 -.042
8 -.094
9 .209
.062
.064
.164
-.069
-.018
-.386
-.001
.100
.174
S3
.051
-.113
.193
.009
-.025
-.058
.034
.119
-.033
S4
.026
-.010
.082
.079
-.386
-.084
.132
-.020
-.120
S5
.022
-.144
.202
-.001
-.010
.062
-.054
-.017
.226
S6
-.031
.226
-.105
.060
-.035
.102
-.080
.101
.149
S7
.010
.031
.009
-.035
.016
-.053
.008
.035
.627
S8
.011
.064
.400
-.185
-.120
-.091
-.054
.111
.065
S9
.119
-.112
.105
.005
.244
-.177
-.097
-.193
.122
S10
-.055
.261
.081
-.028
.029
-.074
-.163
-.101
.035
S11
.040
.282
.025
-.007
.003
-.087
.116
.059
-.023
S12
.030
-.011
-.075
.212
-.240
-.050
-.187
.164
.124
S13
.099
.022
.000
.047
.097
.282
-.100
-.043
-.010
S14
-.022
.010
-.099
.169
-.035
-.110
.175
.103
.078
S15
.007
.080
.084
-.017
-.037
.084
.068
.150
.041
S16
-.048
-.037
.092
.240
-.129
.031
.099
-.311
.084
S17
-.013
.149
.148
-.012
-.305
.020
.046
-.028
-.147
S18
.048
.087
.145
.057
.150
-.049
.019
-.200
-.191
S19
-.111
-.007
-.011
-.033
.164
-.004
.054
-.026
-.087
S20
-.080
.034
.081
.039
.056
-.001
-.563
.075
-.067
S21
-.040
.001
.028
.042
-.054
-.130
.289
.050
-.139
S22
.037
-.002
.006
.158
.071
-.077
-.219
.358
-.196
S23
.021
.001
.076
-.179
-.028
-.022
.021
.444
.171
S24
.073
.026
-.146
.470
-.076
.010
-.068
.035
-.079
S25
.329
-.023
-.029
-.008
.116
-.040
.076
.130
-.021
S26
-.027
.055
.148
.147
-.006
.085
-.248
.079
-.225
S27
.291
.047
.067
.001
.027
-.041
.061
.013
.003
S28
-.071
-.018
-.032
.289
.000
.079
-.004
-.250
.039
S29
.295
-.042
.018
.112
-.102
.018
.125
.001
-.044
S30
.150
.153
-.061
.078
.170
-.117
.109
.201
-.132
From the table 8 of component score coefficient matrix, we can obtain the quantifiable data of each factor. The coefficients between the statements and the factors are taken according to the statement affecting the factor (on the basis of Table 7)
CONCLUSIONS AND FINDINGS Since Indian retail market is continuousl continuously y increasing, increasing, people are purchasing purchasing goods as there is increase of income of common people as well as change in tastes and preferences of consumers. It is important for the retail players to be able to understand the different factors affecting the extent in impulse buying behaviour. The factor analysis results indicate that factor 1 (Table 7) which consists of Information provided by custom customers ers - Adverti Advertisem sement ent of product product in print print and visual visual media, media, Variou Variouss promot promotion ional al activities regarding product, Hording and pamphlets of product, Packaging of product, Placing of product in store, Emotional attachment with product, Behaviour of sales person, Popularity of product, The person with whom you are going for shopping are the main factors for impulse buying behaviour which broadly defines about the Emotional appeal of advertisements. Factor 2 includes various schemes like (buy 1 get 1 free), Compatibility of another product with the product you are buying, Influenced by other people, Kind of product which you are buying Customer’s impulse buying decision causing a variance of 3.308.This shows that importance of influence of other peoples on buying behaviour of customers. Factor Factor 3, includes includes from Table-7 Table-7 ,Any event organized organized by organization organization, Display of product in store, Your perception about saving and investment, Traditions and customs, various festival discounts on product, which in totally shows the direct impact product placement in the stores in a retail outlet like Vishal Megamart & Big Bazzar. Factor 4 includes Price of product, your income status, and Standard of living, which clearly defi define ness the the indi indivi vidu dual al purc purcha hasi sing ng powe power. r. Cont Contin inui uing ng with with the the next next fact factor or-- Fact Factor orss 5
includes.Availability of product, Requirement of product in festival season which shows that discount offers during festival seasons attract customers for their impulse buying behaviour. While While Factor Factor 6 includes includes Discount offers regarding product, focusing on effective price and discount strategies which is in brought by the retail players in order to attract there potential customers. At last Factor 7 includes Changing trends in society, special occasions which signifies that how much today also people give preferences to the traditions and rituals during festival season that it has created a emotional bond which results in impulse buying behaviour. Overal Overall, l, variou variouss intern internal al and extern external al factor factorss affect affectss the impul impulse se buying buying behavio behaviour ur of the consumer which is explained by the above findings
Fig.5 Impulse buying behavior model
Emotional appeal of advertisements
Emotional bonding and Usage of product In festivals
Brand image of Product
IMPULSE BUYING BE HAVIOUR HAVIOUR
Product placement in the store
Income of the Customer
Effective Pricing and discount strategy
Various festival Seasonal discounts
Although the study was conducted on a small population to find Impulse Buying Behaviour of the consumer IN Vishal Megamart and Big Bazzar, the finding of the studies can be generalized
to the whole population. population. It can be very comfortably comfortably inferred inferred that, based on the Impulse Buying Behaviour model that has been formed shows 1. Emotio Emotional nal appea appeall of advert advertise isement mentss 2. Bran Brand d imag imagee of the the produ product ct 3. Product Product placem placement ent in the store store 4. Inco Income me of the the cus custo tome mer r 5. Variou Variouss festi festival val seas seasonal onal discoun discounts ts 6. Effect Effective ive prici pricing ng and disc discount ount str strate ategy gy 7. Emotional Emotional Bonding Bonding and usage usage of of the the product product in in festival festivalss affects impulse buying behaviour of the consumer very strictly. The Indian marketers’ has to go a long way to understand the impulse buying behaviour as it is a very subjective and its depends on multiple factors, but marketers can take advantage for this behaviour and in almost every product category impulse buying witness.
References •
Alice Hanley and Mari S.Wilhelm (1992).Compulsive buying: An exploration into selfesteem and money attitudes. Journal attitudes. Journal of economic Psychology 135-18.
•
Anja Schaefer & Andrew Crane (June 2005).Addressing Sustainability and Consumption. Journal of macro marketing .Vol .Vol 25, No.1, 76-92.
•
Ann Elizabeth Ericson, (2001) University of Iowa “Antecedents of older adolescent’s credit card enhanced spending attitude and self reported financing behaviour”.
•
Aviv Shoham and Maja Makovec Brencic (2003).Compulsive buying behaviour. Journal behaviour. Journal of consumer marketing , Vol 20, No.2.
•
Celia ray Hayhoe, Lauren Leach, & Pamela R.Turner (1999). Discriminating the number of credit cards held by college students using credit and money attitudes. Journal of Economic Psychology 20,643-656.
•
Gordon C.Winston (1987).A new approach to economic behaviour. Journal of Economic behaviour and organization, organization, 8,567-585.
•
Hans Baumgar Baumgartne tner, r, Jan Benedi Benedict ct & E.M. E.M. Steenk Steenkamp amp(19 (1996) 96).. Explor Explorato atory ry consume consumer r buying behaviour: conceptualization and measurement. International measurement. International journal of Research in marketing , 13,121-137.
•
http://www.chinadaily.com.cn/en/doc/2003-09/25/content_267490.htm
•
http://www.indiainfoline.com/pefi/feat/cred.html
•
www.pantaloon.com
•
www.vishalmegamart.com
•
www.futuregroup.com
•
www.marketresarch.com
ANNEXURE-1 Questionnaire
Name …………………………… ………………………………………………………… …………………………………….. ……….. Age …………………………… ……………………………………………………… ………………………………………. ……………. Gender -
MALE
FEMALE
Occupation …………………………………………………… ……………………………………………………………. ………. According to you which of these factors affect your impulse buying behavior for fmcg products.
1
2
3
4
1. PRICE AND DISCOUNT i. Attrac Attractiv tivee price price of produ product ct affec affects ts my impu impulse lse buyi buying ng behavior ii. Discount Discount offer offerss regardi regarding ng product product attracts attracts me iii. Various Various schemes schemes like (buy 1 get 1 free) free) affects affects my buying buying behavior positively. iv. Availabili Availability ty of discounted discounted products products motivate motivatess me to buy.
1. ADVERTISEMENT AND SALES PROMOTION
i.
Advert Advertise isemen mentt of product product in in print print and visua visuall media media attract attractss me to buy ii. Various Various promotion promotional al activitie activitiess regarding regarding product product motiva motivates tes to buy the products iii. Hording Hording and pamphlets pamphlets of product product help me in impulse impulse buying. iv. Any event organize organized d by organization organization affects affects my buying buying behavior. 1. VISUAL MERCHANDISING i.
Displa Display y of produ product ct in stor storee attrac attracts ts my atte attenti ntion. on.
SA
A
DA
SDA
ii. Packaging Packaging of product product attracts attracts me to by the the products. products. iii. Placing Placing of product in store store gains my attention attention towards towards it. iv. Compatibili Compatibility ty of another another product with with the product product you are buying 1. EMOTIONAL ATTACHMENT . i. Emotio Emotional nal attach attachment ment with with produc productt is a motivat motivation ional al factor factor to buy product ii. Behavior Behavior of sales sales person person affects affects my my buying buying behavior. behavior.
iii. Popularit Popularity y of product increases increases recall recall value and helps in impulse buying. iv. Changing Changing trend in in society society is a major major factor factor in impulse impulse Buying 1. COMPANY
i.
The pers person on with with whom whom you are going going for for shop shoppin ping g influences my buying behavior. ii. Comments Comments of reference reference group group influence influence my buying buying behavior. iii. Kind of product product which i am buying buying 1. INCOME
i.
Your income income stat status us affec affects ts my impu impulse lse buyi buying ng behavi behavior. or.
ii. Standard Standard of living living has has a role role to play play in buying buying products products.. iii. Your percepti perception on about saving saving and investm investment ent 1. FESTIVAL SEASON
i.
Spec Specia iall occas occasio ion n motiv motivat atee me to to buy. buy.
ii. Requirement Requirement of of product product in festival festival season season prompts prompts me to buy. iii. Traditions Traditions and customs customs triggers triggers my purchase purchase decision decision iv. Various Various festival festival discounts discounts on product product induces induces purchase purchase of product.
