- Trang Chủ
- Kế hoạch kinh doanh
- Influence of merchandising and pricing strategies on consumer buying behaviour – a cross -sectional study of hypermarkets in Bangalore city
Xem mẫu
- International Journal of Management (IJM)
Volume 8, Issue 3, May– June 2017, pp. 180–189, Article ID: IJM_08_03_020
Available online at
http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=8&IType=3
Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com
ISSN Print: 0976-6502 and ISSN Online: 0976-6510
© IAEME Publication
INFLUENCE OF MERCHANDISING AND
PRICING STRATEGIES ON CONSUMER BUYING
BEHAVIOUR – A CROSS -SECTIONAL STUDY OF
HYPERMARKETS IN BANGALORE CITY
Shilpa Sarvani Ravi and Shikha Bhagat
Assistant Professors, Faculty of Management Studies,
PES University, Banashankari, Bangalore, India
ABSTRACT
India has occupied a third position among emerging and developed nations after China
and Brazil in global retail rankings. India has moderate political risk, low economic risk
and market potential. Country’s has quite significant net retail sales are among developed
and emerging nations. The global retail business is evolving on a faster phase, it is essential
for the retailers to opt the appropriate merchandising and pricing strategies in the Indian
marketing scenario to avail the sustainable advantage in their market. This paper, attempts
to study empirically the extent to which merchandising and pricing strategies formulated,
affect the consumer purchase decisions. A Survey of 366 valid data was examined using
PLS-SEM (Partial Least Squares Structural Equating Modelling). Results emphasised that
the (1) Stock Availability (2) Promotional Signage (3) Standardized Discounts (4) Festival
Sale factors have significant relationship with consumer buying behaviour. This paper has
implications for both the retailers and the manufactures to take a note of these above
variables, to formulate their strategies and tactics for delivering value to the consumers in
Retail Outlets.
Key words: PLS-SEM, Buying behaviour, Merchandising Strategies, Pricing Strategies.
Cite this Article: Shilpa Sarvani Ravi and Shikha Bhagat, Influence of Merchandising and
Pricing Strategies on Consumer Buying Behaviour – A Cross -Sectional study of
Hypermarkets in Bangalore City. International Journal of Management, 8(3), 2017, pp.
180–189.
http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=8&IType=3
http://www.iaeme.com/IJM/index.as 180 editor@iaeme.com
- Shilpa Sarvani Ravi and Shikha Bhagat
1. INTRODUCTION
The idea of 21st century consumer buying behavior is that consumers prefer products mostly for
what they remain rather that for what they do. This concept drives that a functional purpose of the
product is majorly considered than their actual utility. Belch and Belch (2007) characterized
shopper behavior, to satisfy needs and desires consumers engage in activities like searching for,
selecting, purchasing, using, evaluating, and disposing of products and services. Buyers have a
tendency to build up an association with the products they like (Kumar.M, 2014)
A hypermarket is a superstore joining a supermarket and a departmental store, carrying an
extensive variety of items under one rooftop, including groceries and general merchandise.
Hypermarkets enable consumers to fulfill all their regular shopping needs in one trip. In General,
hypermarkets have more than 200,000 distinctive SKUs (Stock Keeping Units) of merchandise
accessible at any given time (Vashishta&B.Balaji, 2016).
2. SIGNIFICANCE IN CONTEXT TO INDIAN MARKET
Retail market in India has matured with retailers focusing on profitability rather than unconstrained
growth. Progressive usage of Store-level promotions will help getting attention of consumers and
furthermore to offer direct inducements. However, low penetration of modern retail in the overall
market indicates significant room for growth and is expected to see strong double digit growth in
the next 5-10 years. Even as India’s tier-2 cities are becoming saturated, there is immense scope
for modern retailers to expand into tier-3 and semi urban towns and become first movers in
untapped growth markets (Shukla&Banerjee, 2014).
(Chandon et al. 2012) stated that the significance of consumer consideration. He also
recommended that consumer price consciousness play as critical determinant of consumer
consideration at the store level. (Shukla&Banerjee, 2014) identified that low price positioning for
most of the brands are highlighted by store-level promotions.
3. HYPER MARKETS GROWTH IN INDIA
Hypermarkets, in India, contributed to almost 2.5% of the total organized retail sales and 21% of
total retail space in 2016. In India, hypermarkets bring together the concept of modern retail format
and reasonable price offering. Thus the retail format has a high appeal with the Indian middle and
upper middle class which seek a higher level of experience from their shopping, along with the
convenience of shopping for all their needs in one place (Vashishta&B.Balaji, 2016).
India as a country compared itself favorably with its peers among foreign investors. The first
half of 2016 showed the highest annual private equity (PE) with investments around US$ 511.76
billion in the retail sector (IBEF, 2017). Retail formats in India have evolved significantly in the
last decade. With the retail industry finally coming of age, newer formats that mirror those found
in western developed markets are taking precedence over older forms. Consumer’s lifestyles are
continuously evolving and they are becoming more demanding and selective in terms of products
as well as services. Retailers are likewise understanding this move and have been proactively
redesigning furthermore, adjusting their current formats to serve them better, while dealing with
their costs and profitability.
http://www.iaeme.com/IJM/index.as 181 editor@iaeme.com
- Influence of Merchandising and Pricing Strategies on Consumer Buying Behaviour – A Cross -
Sectional study of Hypermarkets in Bangalore City
4. LITERATURE REVIEW
Merchandising Strategies
The essential purpose of retailing is to sell merchandise. Merchandising is the process of several
activities executed by the retailer such as planning, buying, and selling of products to the consumers
for their utility. It is also an inherent part of managing store operations. Merchandising control
includes outlining the strategies and procedures to accomplish the predefined objectives. The
objectives range from micro level to the corporate strategies with respect to merchandise
assortment, stocking, and re-arrangement (Mann&Jha, 2013).
Pricing Strategies
As today's consumers are looking for good value, the significance of pricing decisions is growing
in the purchase of goods and services. As price is the the simple and quick variable to alter because
of its immediate association with a company's objective and its cooperation with other retailing
elements (Mann&Jha, 2013).
Retail outlets are loaded with in-store sensory stimuli, appealing promotion offers, including
engaging displays, innovative advertising and flawless packaging. Unrecognized needs and goals
are triggered by in-store stimuli and allure customers to buy more merchandise (Shankar et al.,
2011).
(Newman and Peter, 2008) explained that the printed dictions that communicate the in-store
message to the consumers are the promotional signages. They are embodied in different structures
and shapes, simple and elegant.
Most of the store-level promotions appear beneficial, the outcomes identifying with their effect
on sale are decidedly blended. In the previous research study emphasizing on US customers' food
buying behavior, (Wu et al., 2011) discovered positive however non-significant relationship
between store level promotions and store-level consumer purchases. In the prior research survey
of 15 markets in South Africa, (Mihic et al., 2010) discovered consistent rates of in-store stimuli
related with purchase. However, (Kalyanam et al., 2010) noted that consumer’s perspective of
store-level and customers integrate stimuli like a store-level promotion into their buying behavior
promotions had been less considered. Analyzing store-level promotions effect on consumer buying
behavior had been also called for further research (Grewal et al., 2011). Conventional in-store
promotions to out-of-store media advertisements, understanding their effect will help retailers and
manufacturers in influencing consumers buying behavior (Chandon et al., 2012).
(Suk et al., 2012), commented price consciousness as a buyer's unwillingness to pay a more or
a concentrate on paying low price. Prior research related to price consciousness of consumers are
conscious in the majority of their purchases and use diverse price reference focuses to take the final
decision, including the last exchange cost or highest and lowest price(konuk, 2015). For price
conscious shoppers, to get low cost for the selected item is more critical than other non-price
conscious shopper. They also have tendency to participate in many price comparisons.
(Palazon&Delgad, 2011) contended shoppers who are price-conscious, invest more energy
thinking in purchase choices. The ratio of price paid to the quality of any product, the price
conscious consumers have the strong desire. (Khare A,2014) observed, in contrast with other
shoppers that tendency to be less impulsive and more discipline in buying behavior are the traits of
price conscious shoppers. He also claimed that when additional efforts put in for price conscious
shoppers in their process of purchase, their intention of purchase will diminish.
http://www.iaeme.com/IJM/index.as 182 editor@iaeme.com
- Shilpa Sarvani Ravi and Shikha Bhagat
Decision sciences and marketing research in current trend proposes that while breaking down
complex purchase information, shoppers attempt to streamline their general choice by
concentrating on cues that can offer quick help (Durbach and Stewart,2012). Shoppers to simplify
their final purchase decisions, store-level promotions are the strong cues. They also offer an extra
chance to affirm the belief to get a good deal. Price conscious shoppers always focus on price
factors and the effect of store-level promotion may be marked for such price conscious purchasers
(Manzur et al., 2011).
PLS-SEM
Structural Equation Modeling (SEM) is a multivariate data analysis technique of second generation
that is frequently utilized as a part of business research to test linear and addictive causal model
(Statsoft, 2013). It can be utilized as a part of handling exploration issue to treat undetectable,
difficult to-quantify latent variable (Wong, 2013). The basic approach is the majorly used
covariance based SEM (CB-SEM) which has been vastly used in the field of social sciences since
former decades, and is as yet the high rated data analysis technique today to confirm or dismissing
hypothesis through testing of theory, especially when the sample size is huge, the data distribution
is normal, and in particular, the model is accurately determined. That is, the right dependent and
independent variables are picked and connected together to make a structural model from the theory
available. (Hair et. al.., 2011).
Research Gap
Relevant research has not been done in exploring the concept of buying behavior of consumers of
retail hyper markets especially in merchandising and pricing strategies.
Problem Statement
There is ambiguity in buying behavior of retail consumers majorly with retail hyper markets with
respect to merchandising and pricing strategies.
Objectives
1. To determine the influence of merchandising factors on buying behavior in hypermarkets.
2. To determine the influence of pricing strategies on buying behavior in hyper markets.
Significance of the research
This study alleviates the research gap by validating the proposed merchandising and pricing
strategies of retail hyper markets in India by testing the buying behavior of consumers by the
proposed model. This research attempts to benefit all the retail hyper markets to formulate the
merchandising and pricing strategies by understanding the relationship of consumer buying
behavior with each strategy proposed. This will strengthen the retailer’s competitive edge by
formulating the best merchandising and pricing strategies.
Research Model
The Merchandising Strategies (Independent Variables) considered are Stock availability,
Promo Talkers, Floor Stacking Units. The Pricing Strategies (Independent Variables) considered
are the Standardized Discounts, Festival Sale, and Bench Marking Price. The Buying Behavior is
the dependent Variable.
http://www.iaeme.com/IJM/index.as 183 editor@iaeme.com
- Influence of Merchandising and Pricing Strategies on Consumer Buying Behaviour – A Cross -
Sectional study of Hypermarkets in Bangalore City
Null Hypothesis
1. Ho1: There is no significant difference of stock availability on buying behavior.
2. Ho2: There is no significant difference of Promo-talkers on buying behavior.
3. Ho3: There is no significant difference of Floor stacking unit displays on buying behavior.
4. Ho4: There is no significant difference of standardized discounts on buying behavior.
5. Ho5: There is no significant difference of festival sale on buying behavior.
6. Ho6: There is no significant difference of competitive benchmark pricing on buying behavior.
5. METHODOLOGY
This study conducted was descriptive in nature. The area chosen for the study is Bangalore city,
South India, and is done during Dec 2016 and Jan 2017. The sampling frame comprises the
customers shopping at the retail hyper markets (Big Bazaar, Reliance, Dmart and Spar).The
sampling technique used is quota sampling. The data is collected through questionnaire survey
(adopted). The sample size is 366 after excluding the rejections. The data was analyzed interpreted
using smart PLS as data analysis tool.
Explanation of target endogenous variable variance:
R2, the coefficient of determination for the Consumer Behavior endogenous latent variable is 0.920.
It means, the six latent variables (Festive Sales, Influence of Promotional Signage, Stock
availability and Standardized discounts, Floor Stacking Units and Competitive Benchmarking)
moderately explain 92% of the variance on consumer Buying Behavior (Shown in Fig 2).
Indicator Reliability and Validity
To complete the examination of the structural model, the reliability and validity of the latent
variables is extracted. This below table shows various reliability and validity items which can be
checked and analyzed while conducting a PLS-SEM (see Table 1).
Table 1 Findings Summary for Reflective Outer Model
Latent Variables Indicators Loadings Composite Reliability AVE
SA1 0.786
Stock Availability 0.802 0.670
SA2 0.850
IPS1 0.788
Influence of Promotional Signage IPS2 0.728 0.736 0.510
IPS3 0.763
FSU1 0.757
Floor Stacking Units FSU2 0.797 0.702 0.508
FSU3 0.731
FS1 0.783
Festive Sales FS2 0.803 0.763 0.523
FS3 0.759
SD1 0.742
Standardized Discounts 0.764 0.619
SD2 0.829
BM1 0.889
Benchmarking BM2 0.808 0.741 0.518
BM3 0.723
CB1 0.833
Consumer Behavior 0.798 0.664
CB2 0.796
http://www.iaeme.com/IJM/index.as 184 editor@iaeme.com
- Shilpa Sarvani Ravi and Shikha Bhagat
The initial check was “Composite Reliability”. It is observed seen that all the values of
indicators were showed more than 0.7, Thus internal consistency reliability have been observed
very high when verified among latent variables. Convergent validity was checked and all latent
variable’s AVE (Average Variance Extracted) was examined. It was identified that values of AVE
are higher than the minimum acceptable level of 0.5, so the confirmation of convergent validity is
done. Fornell and Laker (1981) model was followed to confirm the discriminant validity. This
model suggested that if the AVE values are larger than other correlation values among the latent
variables, the square root of AVE in each latent variable should be utilized to show the discriminant
validity. The correlations between the latent variables were copied from the “Latent Variable
Correlation” section of the default report which were placed in the lower left triangle of the table
(see Table 2)
Table 2 Fornell-Larcker Criterion Analysis for Discriminant Validity
BM CB FS FSU IPS SA SD
Benchmarking 0.720
Consumer Behaviour 0.544 0.815
Festive Sales 0.570 0.948 0.723
Floor Stacking Units 0.452 0.597 0.620 0.665
Influence of Promotional Signage 0.547 0.471 0.591 0.505 0.695
Stock Availability 0.523 0.823 0.821 0.598 0.458 0.819
Standardized Discounts 0.529 0.665 0.665 0.395 0.413 0.760 0.665
The latent variables AVE ware found smaller than the correlation values in that column. Same
was also observed in the matrix for the latent variables. The findings emphasized that partial
discriminant validity was established well.
Structural Equation Modeling Findings
T-statistics was generated by PLS for significance testing of both the outer and inner models,
through bootstrapping. The Bootstrap process was used to analyse the result which approximates
the normality of data. After the bootstrapping, Results were as the follows as in Table 3.
Table 3 Result of PLS-SEM
Standard
Original Sample T Statistics
Paths Sample (O) Mean (M)
Deviation
(|O/STDEV|)
P Values
(STDEV)
Benchmarking->consumer Behavior 0.030 0.030 0.022 1.403 0.161
Festive Sales->consumer Behavior 0.904 0.902 0.035 26.032 0.000
Floor Stacking Units->consumer
0.026 0.025 0.022 1.178 0.239
Behavior
Influence of Promotional Signage-
0.151 0.150 0.036 4.240 0.000
>consumer Behavior
Stock Availability->consumer
0.107 0.109 0.034 3.119 0.002
Behavior
Standardized Discounts->consumer
0.135 0.035 0.016 2.170 0.030
Behavior
After inner model path coefficients were reviewed, The outer model was explored by checking
the T-statistic in the “Outer Loadings (Means, STDEV, T-Values)” window. As represented in
http://www.iaeme.com/IJM/index.as 185 editor@iaeme.com
- Influence of Merchandising and Pricing Strategies on Consumer Buying Behaviour – A Cross -
Sectional study of Hypermarkets in Bangalore City
table 3, four of the T-Statistics are greater than 1.96 which emphasized that the outer model
loadings of Festive Sales, Influence of Promotional Signage, Stock availability and Standardized
discounts are highly significant. So H01, H02, H04 and H05 null hypothesis are rejected. These
results complete a the analysis of PLS-SEM in the study. It also showed that benchmarking and
floor stacking units had no significant relationship on Buying Behaviour.
Figure 2 Path Model and PLS-SEM Estimate
6. LIMITATIONS OF THE STUDY
There were few limitations of this research. This data is collected from only four major hyper
market chains in Bangalore city and the other hyper markets are excluded from the sample size.
The customers at the busy hyper retails in Bangalore were always in a hurry and were reluctant to
spend some time to answer the questionnaire. Out of 400 responses 34 were considered invalid and
resulting 366 responses were analyzed. There was a time constraint on completing the study with
a large sample size within the given time frame.
http://www.iaeme.com/IJM/index.as 186 editor@iaeme.com
- Shilpa Sarvani Ravi and Shikha Bhagat
7. CONCLUSIONS
• The study concluded that merchandising and pricing strategies plays substantial role in buying
behavior of consumers. The merchandising strategies such as Stock availability and Influence of
promotional signage have a high impact on the consumer buying behavior. The pricing strategies
which have significant relationship with consumer buying behavior are Standardized discounts and
festive sales.
• The research findings demonstrated that Floor staking units had a less impact on consumer buying
behavior. It also implied that floor stacking units may not be highly lucrative for retailers to grab
attention and retain the customers and also non profitable for the manufacturers to improve sale.
• The research illustrates that bench marking as a pricing strategy has also less direct impact on
consumer buying behavior. As there is very minimum price difference between the hyper markets
in retail industry, this factor of pricing strategy is not showing significant relationship with the
buying behavior of consumers.
• Merchandising and pricing strategies require modern, creative and presentation expertise, and also
requires good planning. It gives a competitive advantage and facilitates in creating an overall image
of the store.
8. SUGGESTIONS
• The Study suggested that much consideration and emphasis should be given to stock availability in
the store which also means the retail hyper store should have all the SKUs (Sock keeping Units)
available on the shelf for the customer to choose and pick the products. The retail outlets should
focus on placing regular purchase orders to the vendors and keep a track on the fill rates of the
vendors for a right assortment.
• Promotional signage should be given special importance. Promo talkers (rate cards) for all the
products should be displayed on the shelf for the customer to easily compare the prices between the
competitor’s SKUs. Responsibility should be given to the promoters inside the store for their
respective departments.
• The results also suggested that Standardized store level discounts should be given to make
consumers think that they are getting a better bargain which attracts them to buy the products. This
states that the consumers are more attracted to the stores like Dmart where 365 days minimum
discount of 6% is run.
• Attractive and detailed flyers/ pamphlets with special festive sale offers may be prepared and should
distribute to the consumers which in turn helps them to take effective and efficient decisions. These
flyers can have more impact if they are distributed just outside the store for the potential consumers
to get an idea about the offers inside the store.
9. SCOPE FOR FUTURE STUDY
Three factors of merchandising and three factors of pricing are tested with the consumer buying
behavior of hyper markets. The other variables of emerging merchandising strategies like frontal
presentation, tonnage merchandising, Cleanliness, Stock arrangements (planogram), unit planning,
store layout, store design, share of shelf, atmospherics etc. can be variables for future study on
consumer behavior. Few other strategies like advertising, fill rates of vendors, vendor relationships,
credit system, retailers own label products, location of store, can be also studies to understand the
consumers behavior towards buying the products in the retail outlets.
http://www.iaeme.com/IJM/index.as 187 editor@iaeme.com
- Influence of Merchandising and Pricing Strategies on Consumer Buying Behaviour – A Cross -
Sectional study of Hypermarkets in Bangalore City
REFERENCES
[1] C. Fornell., & D. F. Larcker.(1981). Evaluating structural equation models with unobservable
variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
[2] Chandon, P., &Wansink, B. (2012). Does food marketing need to make us fat? A review and
solutions. Nutrition reviews, 70(10), 571-593.
[3] Durbach, I. N., & Stewart, T. J. (2012). Modeling uncertainty in multi-criteria decision
analysis. European Journal of Operational Research, 223(1), 1-14.
[4] Grewal, D., Ailawadi, K. L., Gauri, D., Hall, K., Kopalle, P., & Robertson, J. R. (2011).
Innovations in retail pricing and promotions. Journal of Retailing, 87, S43-S52.
[5] Hair Jr, J. F., Hult, G. T. M., Ringle, C., &Sarstedt, M. (2016). A primer on partial least squares
structural equation modeling (PLS-SEM). Sage Publications
[6] Hair, J. F., Ringle, C. M., &Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of
Marketing theory and Practice, 19(2), 139-152.
[7] Kalyanam, K., Lal, R., & Wolfram, G. (2010). Future store technologies and their impact on
grocery retailing. In Retailing in the 21st Century (pp. 141-158). Springer Berlin Heidelberg.
[8] Khare, A., Achtani, D., &Khattar, M. (2014). Influence of price perception and shopping
motives on Indian consumers' attitude towards retailer promotions in malls. Asia Pacific Journal
of Marketing and Logistics, 26(2), 272-295.
[9] Konuk, F. A. (2015). The effects of price consciousness and sale proneness on purchase
intention towards expiration date-based priced perishable foods. British Food Journal, 117(2),
793-804.
[10] Krishnakumar, M. (2014). The role of visual merchandising in apparel purchase decision. IUP
Journal of Management Research, 13(1), 37.
[11] Mann, P. W., &Jha, M. (2013). Impact of Various Situational Factors on" Store Environment,
Merchandising and Consumer Behavior"--A Study on Furniture Bazaar. Journal of Marketing
& Communication, 9(2).
[12] Manzur, E., Olavarrieta, S., Hidalgo, P., Farías, P., & Uribe, R. (2011). Store brand and national
brand promotion attitudes antecedents. Journal of Business Research, 64(3), 286-291.
[13] Mihić, M., &Kursan, I. (2010). Assessing the situational factors and impulsive buying behavior:
Market segmentation approach. Management: Journal of Contemporary Management
Issues, 15(2), 47-66.
[14] Mohan, G., Sivakumaran, B., & Sharma, P. (2013). Impact of store environment on impulse
buying behavior. European Journal of Marketing, 47(10), 1711-1732.
[15] Palazon, M., & Delgado-Ballester, E. (2011). The expected benefit as determinant of deal-prone
consumers' response to sales promotions. Journal of Retailing and Consumer Services, 18(6),
542-547.
[16] Shankar, V., Inman, J. J., Mantrala, M., Kelley, E., &Rizley, R. (2011). Innovations in shopper
marketing: current insights and future research issues. Journal of Retailing, 87, S29-S42.
[17] Shukla, P., & Banerjee, M. (2014). The direct and interactive effects of store‐level promotions
on impulse purchase: Moderating impact of category familiarity and normative
influences. Journal of Consumer Behaviour, 13(4), 242-250.
http://www.iaeme.com/IJM/index.as 188 editor@iaeme.com
- Shilpa Sarvani Ravi and Shikha Bhagat
[18] Suk, K., Lee, J., & Lichtenstein, D. R. (2012). The influence of price presentation order on
consumer choice. Journal of Marketing Research, 49(5), 708-717.
[19] Vashishta, D. S., &Balaji, B. (2016). Retail Service Convenience In Hypermarkets of India and
Indonesia. ”I J A B E R, 14(8), 5581-5593.
[20] Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM)
techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
[21] Wu, P. C., Yeh, G. Y. Y., & Hsiao, C. R. (2011). The effect of store image and service quality
on brand image and purchase intention for private label brands. Australasian Marketing Journal
(AMJ), 19(1), 30-39.
[22] Dr. Mehal Pandya, Consumer Buying Behaviour For Children Apparel: A Critical Review.
International Journal of Management, 7(5), 2016, pp. 188–199.
[23] Hanna Joseph and Dr. David T Easow, Study on Impact of Akshaya Tritiya on Consumer
Buying Behaviour of Gold. International Journal of Management, 7(7), 2016, pp. 128–133.
[24] Vijay.R.Kulkarni, A Factorial Study Of Consumer Buying Behavior Of Laptops Of Post
Graduate Students In Pune, Volume 4, Issue 2, March- April (2013), pp. 09-21, International
Journal of Management.
[25] StatSoft, I. (2013). Electronic Statistics Textbook. StatSoft, Tulsa, USA.
[26] Newman A J and Peter C (2008), Signage: Retail Marketing Operations, Retailing Environment
& Operations, 3rd Indian Report, Cengage Learning, Australia, pp. 264
[27] https://www.ibef.org/industry/indian-retail-industry-analysis-presentation
http://www.iaeme.com/IJM/index.as 189 editor@iaeme.com
nguon tai.lieu . vn
