Mark-Down Pricing: The Study of an Indian Fashion Retailer

Mark-Down Pricing: The Study of an Indian Fashion Retailer

Saji K. Mathew, Pratap Chandra Biswal
DOI: 10.4018/jisss.2012070105
(Individual Articles)
No Current Special Offers


Discount sales have been increasing in Indian retailing due to the growing competition in the sector. In this research the authors analyze the data of a fashion retail store to study the effect of mark-down pricing on the sales. Their store level analysis shows that mark-downs have a positive impact on sales in an aggregate level. At a style level, however, some items showed a negative and significant effect on sales. This negative influence is explained by the predominant focus of the Store to attract high end customers characterized by conspicuous consumption.
Article Preview


Driven by favorable demographics, rising disposable income, increasing final consumption expenditure, and growing urbanization, the retail sector in India has grown at a compound annual growth rate of 10-14% during 2006-08 (CRISIL, 2009). During this period, organized retail, with a huge unexplored market, grew at a much faster pace of 28% due to large expansions by existing retailers and entry of many new players. Following the economic rebound post 2009, CRISIL Research expects the Indian organised retail sector to grow at a CAGR of 22% to reach INR 2570 by 2013-141. Moreover, the 2009 Global Retail Development Index (A. T. Kearney, 2010) ranked India as the #1 destination for international players.

Fashion retailing involving apparel and footwear is a steadily growing business in the Indian retail industry (Joseph, Soundararajan, Gupta, & Sahu, 2008). The apparel market in India was estimated at around US$16-17bn in 2006 and is dominated by unorganized players having a share of about 80-85% (Cygnus Business Consulting & Research, 2007). This market has been growing at 10-12% per annum. Apparel retailing is the country’s second largest opportunity for organized retailers (Footwear retail being the number one). Some of the factors driving the demand for fashion items include changing lifestyle, entry of leading international brands like Tommy Hilfiger®, greater awareness, exposure to international trends, increased foreign travel, and fast-evolving retail industry (Ernst & Young, 2006). The competitive advantage of firms in this market is related to their ability to produce designs that capture the imagination and preferences of consumers, in addition to cost effectiveness (Cygnus Business Consulting & Research, 2007). Further, the economic liberalization in India post 1990 and the subsequent Government policies led to the entry of International fashion brands in India. The entry of global players in the Indian market has seriously challenged the home grown retailers. One distinct advantage of the new entrants (e.g., Wal-Mart through cash and carry format) is their access to advanced analytics for informed decision making (Davenport & Harris, 2007). Although several studies have been reported on analytics to support decision making (e.g., Davenport & Harris, 2007; Hui & Wan, 2008; García-Crespo, Colomo-Palacios, Gómez-Berbís, & Martín, 2010; Walczak, 2010), data mining applications in the Indian consumer context has been much less.

Growing competition in retailing has forced several Indian retailers to resort to discounts of various types such as flat discounts, mark-downs, and clearance sales. In recent times mark-down practice has been an important pricing policy for fashion retailers in India ( A decade ago a 50% discount for a branded footwear or apparel gave rise to doubts in the minds of consumers. Such sales often comprised store rejects and used items. Today the concept of discount sales has taken a complete turn with the terminology also being changed to value retailing. Discount sales also appears to be a way to combat recession hit fashion retail in India (Jaggi, 2009).

Complete Article List

Search this Journal:
Volume 15: 1 Issue (2024)
Volume 14: 4 Issues (2022): 3 Released, 1 Forthcoming
Volume 13: 4 Issues (2021)
Volume 12: 4 Issues (2020)
Volume 11: 4 Issues (2019)
Volume 10: 4 Issues (2018)
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing