Whether Shoppers of Tier I City are aware about Multi-Brand Outlets?

 

Dr. M. Rupesh Kumar¹, Dr. A.G.V. Narayanan²

¹Assistant Professor, Institute of Management, Christ University, Bangalore – 560025 Karnataka, India

²Dean, Faculty of Management, Studies Ebet Group of Institutions, Kangayam - 638108 Tirupur (Dist) Tamilnadu, India.

*Corresponding Author E-mail: rupmba@yahoo.co.in, agvnarayan@yahoo.co.in

 

 

1. INTRODUCTION ABOUT THE RETAILING INDUSTRY:

The Indian retail industry has a long historical background starting from haats and melas to traditional unorganized retail formats. The Indian retail industry changed a lot in the past few decades; recently the retail industry is undergoing a transformation called as organized retail formats. The emerging organized retail formats include MBOs - Multi-Brand Outlets, EBOs - Exclusive Brand Outlets, shopping malls, department stores, and hypermarket. The organized retail format has become popular now-a-days due to changes in shopping habit.            

 

1.2 Introduction about the study:

The customers are interested in knowing about various stores available in their city to meet out their shopping expectations with ease and convenience. The number of stores available in the same format and their branches available at various destinations within the city plays a vital role in determining the awareness of customers towards a new store format called as Multi-Brand Outlets. In this study, the awareness about apparel MBOs was analyzed under four categories namely number of MBOs the respondents are aware of in Coimbatore city, source of awareness, selection of MBOs for making their purchases, number of branches available for the selected MBOs.

 

2. PURPOSE OF RESEARCH:

The various authors have studied the consumer awareness about the ‘brand’ but less research on ‘store’. In this study, efforts have been taken to analyze the various personal factors (age, gender, marital status, monthly family income, education, employment, family size, family category and number of years of living in a particular city) which influence the consumer awareness about the Multi-Brand Outlets.     

 

3. LITERATURE REVIEW:

The dimensions of consumer behaviour to be measured are limited to 'awareness' and 'acceptance'. The “Familiarity” about a store or format was also seen as an important factor (Seiders and Tigert, 1997). The brand awareness plays a vital factor always to manipulate the buying decisions and purchase intentions (Macdonald and Sharp, 2000). The growing awareness of the systems and techniques of modern retail management introduced by foreign retailers signified the proliferation of more effective merchandising, promotion and personnel management techniques among Greek retailers (Bourlakis and Bourlakis, 2001; Bennison, 2002).

 

The lack of education affected the level of awareness among people about fashionable products, but now-a-days due to increase in the literacy rate and advent of mass media, consumers have got awareness about each product group and its associated brand. Many consumers in India are aware of foreign brands but they are unable to distinguish the feature or value of the products and fear to buy the new ones has forced them to prefer only the familiar brands (Karthikeyan Sundarraj, 2011).

 

A study was conducted to identify the consumer awareness about different apparel brands available in the Indian market in gender perspective. This study considered the personal factors like age, income, education, occupation, lifestyle, personality and self concept, influencing the buying decision of consumers with respect to gender discrimination. The study concluded that awareness about the branded apparels is an independent attribute which has no impact on gender discrimination (Namita Rajput et al., 2012).

 

A study was performed to find out the awareness level of various organized retail sector at Krishnagiri District in India. The source of awareness was through media, family, and friends. The study concluded that 60% of the respondents are aware about the organized retail sector in Krishnagiri District. 50% of the respondents say that media played a vital role in promoting the awareness about organized retail stores (Ravi et al., 2013).

 

This study shows that some of the specific elements like product information, customer involvement, atmosphere, customer attributions and choices play important roles in shopping decision. So customers are now showing preference for shopping malls, enable them to shop variety of products under one roof with shopping experience in term of ambience and entertainment (Bikrant Kesari 2014).

 

 

4. OBJECTIVES OF THE STUDY:

1    To identify the awareness level about apparel Multi-Brand Outlets.

2    To recognize the various sources influencing the shoppers in knowing about the apparel Multi-Brand Outlets.

3    To verify whether the significant association exists between respondents’ awareness about MBOs and demographic variables.

 

5. RESEARCH METHODOLOGY:

The study was conducted for about 400 respondents in Coimbatore city, India. The research is a descriptive one. The study was conducted using non-probability sampling method. In this study the convenience sampling method was adopted because the population size was unknown. The sampling unit covers the shoppers of apparel MBOs at Coimbatore city. The data was collected using a schedule. The data was analyzed by chi-square test.

 

6. HYPOTHESIS:

H1: Significant association between number of MBOs the respondents are aware and age of the respondents

H2: Significant association between number of MBOs the respondents are aware and gender of the respondents

H3: Significant association between number of MBOs the respondents are aware and marital status of the respondents

H4: Significant association between number of MBOs the respondents are aware and education of the respondents

H5: Significant association between number of MBOs the respondents are aware and employment category of the respondents

H6: Significant association between number of MBOs the respondents are aware and monthly family income of the respondents

H7: Significant association between number of MBOs the respondents are aware and family size of the respondents

H8: Significant association between number of MBOs the respondents are aware and family category of the respondents

H9: Significant association between number of MBOs the respondents are aware and number of years living in Coimbatore city by the respondents

              

7. DATA ANALYSIS:

For the purpose of the study, the shoppers of apparel Multi-Brand Outlets are chosen as samples, for to find out the awareness level about the apparel Multi-Brand Outlets.

 

7.1 DISCUSSION:

Following are the summarized result from analysis of data.

 

Table 1: DEMOGRAPHIC CHARACTERISTICS

 

Table 2:Number of MBOs the respondents aware of in Coimbatore city

 

Table 3: Source of awareness about MBOs

 

 

Figure 1: Number of MBOs the respondents aware of in Coimbatore city

 

It is inferred that 41.75% of the respondents are aware of 5 to 10 Multi-Brand Outlets in Coimbatore city. Only 6.25% of the respondents are aware of more than 20 MBOs in the city. So, it could be inferred that majority of the people are aware of 5 to 10 Multi-Brand Outlets in Coimbatore city.

 

Figure 2: Source of awareness about MBOs

 

It is inferred that out of 400 respondents, 35% of the respondents are aware of MBOs through walk by and 31.5% of the respondents are aware of MBOs through friends and relatives. Therefore, walk by stands as a strong source to make the respondents aware of the Multi-Brand Outlets.

 

Table 4: Distribution of number of MBOs the respondents are aware of based on the age profile

 

 

The table shows that majority of the respondents are aware of a number of MBOs irrespective of age. In the age group between 26 and 30 years, 52.1% of the respondents are aware of 5 - 10 outlets whereas only 4.2% of the respondents falling under the age group of 26 and 30 years are aware of more than 20 outlets. The association of age of the respondents with number of MBOs they are aware of is tested by framing the following hypotheses.

 

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and age of the respondents.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and age of the respondents.

Chi-square Test

Test	Value	df	Sig.
Chi-square	20.379	9	*

* - Significant at 5% level

 

The chi-square test was applied to find whether the age of the respondents is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (20.379) is higher than the table value (16.919) at 5% level of significance. Therefore, it is inferred that there is a significant relationship between the number of MBOs the respondents are aware of and age of the respondents. Hence, the null hypothesis is rejected and alternative hypothesis is accepted.

 

 

 

Table 5: Distribution of number of MBOs the respondents are aware of based on gender

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Gender	Male	94	33.9	123	44.4	44	15.9	16	5.8	277	100.0
	Female	57	46.3	45	36.6	12	9.8	9	7.3	123	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

                      

The table shows that majority of the respondents are aware of a number of MBOs based on the gender. 46.3% of the female respondents are aware of less than 5 outlets whereas only 7.3% of the female respondents are aware of more than 20 outlets. Similarly, 44.4% of the male respondents are aware of 5 – 10 outlets whereas only 5.8% of the male respondents are aware of more than 20 outlets. The association of the respondents’ gender with a number of MBOs they are aware of is tested by framing the following hypotheses.

                   

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and gender.

 

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and gender.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	7.321	3	Ns

                    

The chi-square test was applied to find whether gender of the respondents is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (7.321) is lower than the table value (7.815) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between the number of MBOs the respondents are aware of and the gender. Hence, the null hypothesis is accepted.

 

 

Table 6: Distribution of number of MBOs the respondents are aware of based on marital status

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Marital status	Married	16	23.9	31	46.3	16	23.9	4	6.0	67	100.0
	Unmarried	135	40.5	137	41.1	40	12.0	21	6.3	333	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

                             

The table shows that majority of the respondents are aware of a number of MBOs based on the marital status. 46.3% of the married respondents are aware of 5 – 10 outlets whereas only 6% of the married respondents are aware of more than 20 outlets. Similarly, 41.1% of the unmarried respondents are aware of 5 – 10 outlets whereas only 6.3% of the unmarried respondents are aware of more than 20 outlets. The association of marital status of the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

 

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and marital status.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and marital status.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	10.072	3	*

* Significant at 5% level

 

 

The chi-square test was applied to find whether marital status of the respondents is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (10.072) is higher than the table value (7.815) at 5% level of significance. Therefore, it is inferred that there is a significant relationship between the number of MBOs the respondents are aware of and the marital status. Hence, the null hypothesis is rejected and alternative hypothesis is accepted.

 

Table 7: Distribution of number of MBOs the respondents are aware of based on educational qualification

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Educational qualification	≤ Plus two	5	21.7	12	52.2	5	21.7	1	4.3	23	100.0
	Diploma	14	43.8	11	34.4	4	12.5	3	9.4	32	100.0
	Graduate	93	38.4	97	40.1	37	15.3	15	6.2	242	100.0
	PG	39	37.9	48	46.6	10	9.7	6	5.8	103	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

                      

The table shows that majority of the respondents are aware of a number of MBOs based on the educational qualification. In the education group less than or equal to plus two, 52.2% of the respondents are aware of 5 – 10 outlets whereas only 4.3% of the respondents in the education group less than or equal to plus two are aware of more than 20 outlets. The association of educational qualification of the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

                             

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and educational qualification.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and educational qualification.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	6.979	9	Ns

 

The chi-square test was applied to find whether educational qualification of the respondents is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (6.979) is lower than the table value (16.919) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between the number of MBOs the

 

respondents are aware of and the educational qualification. Hence, the null hypothesis is accepted.

 

 

Table 8 Distribution of number of MBOs the respondents are aware of based on employment classification

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Employment classification	Student	97	42.9	91	40.3	23	10.2	15	6.6	226	100.0
	Govt. employee	2	22.2	6	66.7	1	11.1	-	-	9	100.0
	Private employee	38	30.4	54	43.2	23	18.4	10	8.0	125	100.0
	Homemaker	6	50.0	4	33.3	2	16.7	-	-	12	100.0
	Business	4	20.0	11	55.0	5	25.0	-	-	20	100.0
	Others	4	50.0	2	25.0	2	25.0	-	-	8	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

 

The table shows that majority of the respondents are aware of a number of MBOs based on the employment classification. In the employment group, 66.7% of the government employees are aware of 5 – 10 outlets whereas only 6.6% of the student respondents are aware of more than 20 outlets. The association of employment classification among the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

                             

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and employment classification.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and employment classification.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	19.858	15	Ns

 

The chi-square test was applied to find whether employment classification is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (19.858) is lower than the table value (24.996) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between the number of MBOs the respondents are aware of and the employment classification. Hence, the null hypothesis is accepted.

 

Table 9 Distribution of number of MBOs the respondents are aware of based on the monthly family income

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Monthly family income	Below Rs.10,000	20	43.5	14	30.4	10	21.7	2	4.3	46	100.0
	Rs.10,001-20,000	38	37.3	41	40.2	15	14.7	8	7.8	102	100.0
	Rs. 20,001-30,000	34	30.9	52	47.3	18	16.4	6	5.5	110	100.0
	Rs. 30,001-50,000	33	44.0	33	44.0	5	6.7	4	5.3	75	100.0
	Above Rs.50000	26	38.8	28	41.8	8	11.9	5	7.5	67	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

                   

The table shows that majority of the respondents are aware of a number of MBOs based on the monthly family income. 44% of the respondents whose monthly family income is ranging between Rs.30001 and Rs.50000 are aware of less than 5 outlets or 5 to 10 outlets respectively. Whereas only 6.6% of the respondents whose monthly family income is less than Rs.10,000 are aware of more than 20 outlets. The association of monthly family income of the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

                             

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and the monthly family income.

 

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and the monthly family income.

Chi-square Test

Test	Value	df	Sig.
Chi-square	11.488	12	Ns

                    

The chi-square test was applied to find whether monthly family income is significantly associated with awareness about the number of MBOs. It is observed that the calculated chi-square value (11.488) is lower than the table value (21.026) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between the number of MBOs the respondents are aware of and the monthly family income. Hence, the null hypothesis is accepted.

 

 

Table 10 Distribution of number of MBOs the respondents are aware of based on family size

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	%of Resp.
		No.	%	No.	%	No.	%	No.	%
Family size	Couple	4	40.0	4	40.0	2	20.0	-	-	10	100.0
	3-5 members	131	37.4	150	42.9	47	13.4	22	6.3	350	100.0
	6-10 members	16	40.0	14	35.0	7	17.5	3	7.5	40	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

                   

The table shows that majority of the respondents are aware of number of MBOs based on the family size. 42.9% of the respondents whose family size is 3 – 5 members are aware of 5 – 10 outlets whereas only 6.3% of the respondents whose family size is 3 – 5 members are aware of more than 20 outlets. The association of family size of the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

                    

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and family size.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and family size.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	2.029	6	Ns

 

The chi-square test was applied to find whether the family size is significantly associated with awareness about the number of MBOs. It is observed that the calculated chi-square value (2.029) is lower than the table value (12.592) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between the number of MBOs the respondents are aware of and the family size. Hence, the null hypothesis is accepted.

 

 

Table 11 Distribution of number of MBOs the respondents are aware of based on the family category

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
Family category	Single Income	108	40.9	104	39.4	35	13.3	17	6.4	264	100
	Double Income	43	31.6	64	47.1	21	15.4	8	5.9	136	100
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100

                             

The table shows that majority of the respondents are aware of a number of MBOs based on the family category. 47.1% of the respondents belong to double income family category and are aware of 5 – 10 outlets whereas 39.4% of the respondents comprising single income family category are aware of 5 – 10 outlets. The association of family category of the respondents with the number of MBOs they are aware of is tested by framing the following hypotheses.

                             

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and family category.

                    

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and family category.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	3.659	3	Ns

                           

The chi-square test was applied to find whether the family category is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (3.659) is lower than the table value (7.815) at 5% level of significance. Therefore, it is inferred that there is no significant relationship between number of MBOs the respondents are aware of and the family category. Hence, the null hypothesis is accepted.

 

 

Table 12 Distribution of number of MBOs the respondents are aware of based on number of years living at Coimbatore city

		No. of MBOs the respondents are aware of								Total
		Less than 5 outlets		5-10 outlets		11-20 outlets		More than 20 outlets		No. of Resp.	% of Resp.
		No.	%	No.	%	No.	%	No.	%
No. of years living at Coimbatore city	Below 5 yrs	100	51.8	65	33.7	19	9.8	9	4.7	193	100.0
	5-10 yrs	15	30.6	26	53.1	7	14.3	1	2.0	49	100.0
	11-20 yrs	19	26.4	35	48.6	12	16.7	6	8.3	72	100.0
	21-50 yrs	11	15.9	33	47.8	17	24.6	8	11.6	69	100.0
	Above 50 yrs	6	35.3	9	52.9	1	5.9	1	5.9	17	100.0
Total		151	37.8	168	42.0	56	14.0	25	6.3	400	100.0

 

 

The table shows that majority of the respondents are aware of MBOs based on the number of years living at Coimbatore city. 53.1% of the respondents living in Coimbatore city from 5 – 10 years are aware of 5 – 10 outlets whereas only 2% of the respondents living in Coimbatore city from 5 – 10 years are aware of more than 20 outlets. The association about number of years living at Coimbatore city with the number of MBOs the respondents are aware of is tested by framing the following hypotheses.

                             

 

Null Hypothesis: There is no significant association between number of MBOs the respondents are aware of and the number of years living at Coimbatore city.

 

Alternative Hypothesis: There is a significant association between number of MBOs the respondents are aware of and the number of years living at Coimbatore city.

 

Chi-square Test

Test	Value	df	Sig.
Chi-square	43.305	12	**

**Significant at 1% level

 

The chi-square test was applied to find whether the number of years living at Coimbatore city is significantly associated with number of MBOs the respondents are aware of. It is observed that the calculated chi-square value (43.305) is higher than the table value of (26.217) at 1% level of significance. Therefore, it is inferred that there is a significant relationship between the number of MBOs the respondents are aware of and the number of years living at Coimbatore city. Hence, the null hypothesis is rejected and the alternative hypothesis is accepted.

 

8. FINDINGS:

8.1. The analysis indicates that 42 percent of the respondents are aware of 5 to 10 MBOs. Therefore, it is inferred that majority of the customers knew a reasonable number of MBOs in tier I city like Coimbatore for fulfilling their shopping needs.

 

8.2. The study identified that Out of 400 respondents, 35 percent of the respondents are aware about the MBOs through a source called ‘walk by’ and 31.5 percent of the respondents are aware of MBOs through friends and relatives.

 

8.3. It was found that significant relationship exists between number of MBOs the respondents are aware of and the age profile, marital status, and number of years living at Coimbatore city.

 

8.3.1. 52 percent of the respondents falling under the age group of 26 and 30 years are aware of 5 - 10 MBOs in Coimbatore city. This depicts that the youngsters have good exposure about the MBOs than the other age group.

 

8.3.2. 46 percent of the married respondents and 41 percent of the unmarried respondents are aware of 5 – 10 MBOs in Coimbatore city. So, it declares that both the marital groups have an identical exposure regarding the Multi-Brand Outlets.

 

8.3.3. 53 percent of the respondents living at Coimbatore city from 5 – 10 years are aware of 5 – 10 MBOs in Coimbatore city whereas only 2% of the respondents living in Coimbatore city from 5 – 10 years are aware of more than 20 outlets. The people with lesser years of livelihood in the city have good knowledge about the count of MBOs than the other years of living.

9. MANAGERIAL IMPLICATIONS:

9.1. As this is the emerging organized retail format people need time to gain exposure and knowledge.

 

9.2. The retailers need to concentrate on improving the awareness level of the customers about apparel Multi-Brand Outlets through various other sources of direct marketing like E-mail, Short Message Service, Multimedia Messaging Service, Social Medias, Blogs, etc.

 

9.3. The retailers should focus more on the people of age group above 30 years to create a good familiarity about apparel MBOs.

 

9.4. A separate consideration is desired for the married and unmarried respondents to create an exposure about the apparel MBOs.

 

9.5. Though people live in Coimbatore city for 5 – 10 years, only 2 percent are aware of more than 20 outlets. This depicts that still efforts have to be taken by the Multi-Brand Retailers to create good publicity about the presence of apparel MBOs in the city.

 

10. CONCLUSION:

The overall retail market in India is likely to reach Rs 47 trillion (US$ 792.84 billion) by 2017. India is the 5^th most favourable destination for international retailers. The apparels are being sold by the thousands of Multi-Brand Retailers in India. The customers’ awareness about the apparel Multi-Brand Outlets are 319 respondents out of 400 respondents are aware of 10 MBOs in Coimbatore city. It declares that the awareness about apparel Multi-Brand Outlets in Tier I city like Coimbatore is good, which could further be improved in the years to come through the various modern media.

              

11.REFERENCES:

1      Bennison, D., Retailing in Europe: Structures, Competition and Performance, Routledge, London, 2002.

2      Bikrant Kesari. A Review of Customer Preference towards Organized Retail Stores, International Journal Research in Social and Management Studies, 2 (3); 2014: 24-28.

3      Bourlakis, M. A., and Bourlakis, C. A. Deliberate and emergent logistics strategies in food retailing: a case study of the Greek multiple food retail sector. Supply Chain Management: An International Journal, 6(4); 2001: 189-200.

4      Karthikeyan, S. An investigation on consumer behavior and preferences towards apparel purchase by Indian consumers age - A project Report submitted at Swedish School of Textiles - Boras, 2011: 15–25.

5      Macdonald, E. K., and Sharp, B. M.. Brand Awareness Effects on Consumer Decision Making for a Common, Repeat Purchase Product: A Replication. Journal of business research, 48(1); 2000: 5-15.

6      Rajput, N., Kesharwani, S., and Khanna, A. Consumers’ Attitude towards Branded Apparels: Gender Perspective. International Journal of Marketing Studies, 4(2), 2012: 111.

7      Ravi, A and Abinaya, S,  A study on the awareness level of rural consumers with reference to organized retail shops in Krishnagiri district, Indian Journal of Applied Research, 3(11); 2013:1-4.

8      Seiders, K., and Tigert, D. J. Impact of market entry and competitive structure on store switching/store loyalty. The International Review of Retail, Distribution and Consumer Research, 7(3); 1997: 227-247.

 

 

 

 

 

Accepted on 18.08.2016                © A&V Publication all right reserved