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Editorial Board A Refereed Monthly International Journal of Management
Prof. B. P. Sharma
(Editor in Chief)
Prof. Mahima Birla
(Group Editor)
Dr. Khushbu Agarwal
(Editor)
Ms. Asha Galundia
(Circulation Manager)

 Editorial Team

Dr. Devendra Shrimali
Dr. Dharmesh Motwani
 

                      E-tailing   - A niche Market in Retail Sector

 

Dr. Ankita Nanda                                                                                                                                                                      Asst. Prof

School of Management MIET

ankitadewan44@gmail.com

Mob No.9419100770

Postal Address:

Flat no.1 Dewan Modern Breweries Ltd.

Talab Tillo, Bohri

Jammu, Jammu & Kashmir

India

                 

Abstract

 

The Retail Sector of Indian Economy is going through the phase of tremendous transformation. The impact of the alterations in the format of the retail sector has changed the lifestyle of the Indian consumers drastically. Nowadays the Indian consumers are well versed with the concepts about quality of products and services. These demands are clearly visible in the retail sector.

With rapid growth of the Internet and globalization of market, the retail sector has become an increasingly competitive and dynamic business environment. The developed countries have already started to take the benefits by transforming their businesses from old form of retail to E-Retailing. As the backbone of the businesses, E-Retailing explores the thinking of infrastructure, social values, economical variances and cultural thinking. It has helped the companies to think about the new business strategies based on up growing new technologies.

The current web-based models for etailing are part of an embryonic phase preceding an era of rapid transformation, challenge, and opportunity in Indian retail market. It is not just the metros that are fueling the online scene in India the demand supply gap in tier 2-3 cities where there is brand awareness but no availability of products and services is also adding to growth.

A study shows that Europe is the market for E-Retailing sales, Asia and rest of the world has only 47.51% E-Retailing sales which just includes developing countries like India [IMRG World, 2012]. This implies that the E-Retailing sales of these developing countries is still very less as these countries have 80% of world population. Thus, there is a need to find out the reasons of E-Retailing sales in developing countries especially India.

Therefore, the present study tries to find the growth drivers of online retail. In addition, it has tried to analyze the online shopping habits of college going students which includes their preference for various online shopping websites as well as importance of factors responsible for online shopping.

Keywords: Technology, Internet, Changing Lifestyle, Online Retail , Niche Marketing.

INTRODUCTION

The Retail Sector of Indian Economy is going through the phase of tremendous transformation. The impact of the alterations in the format of the retail sector has changed the lifestyle of the Indian consumers drastically. Nowadays the Indian consumers are well versed with the concepts about quality of products and services. These demands are the visible impacts of the Retail Sector of Indian Economy.

With rapid growth of the Internet and globalization of market, the retail sector has become an increasingly competitive and dynamic business environment. The developed countries have already started to take the benefits by transforming their businesses from old form of retail to E-Retailing. As the backbone of the businesses, E-Retailing explores the thinking of infrastructure, social values, economical variances and cultural thinking. It has helped the companies to think about the new business strategies based on up growing new technologies. The technology professionals also have got a big challenge to provide the technology requirements of the increased population. As the internet users around the world are increasing, the governments from the developing countries like India have also started to taking special interest and investment on telecommunication and E-Retailing infrastructure.

The study shows that through Europe is the market for E-Retailing sales, Asia and rest of the world shown in the figure has 47.51% E-Retailing sales which just includes developing countries [IMRG World,2012] and  India is one of them. But the E-Retailing sales of these developing countries is still very less because these countries have 80% of world population. Thus, the need arise to find the reasons of E-Retailing sales in developing countries especially India.

The present study tries to study the various growth drivers of on-line retail. In addition it also tries to analyse online shopping habits of the college going students and also their preference of the various online websites.

Global E-Tailing % Sales 2013

 Business and marketing activities are affected by the invent of Internet technologies and the Internet is revolutionizing commerce, marketing, retailing, shopping and advertising activities of products and services. The Indian retail market is witnessing a revolution. As one of the market trends, e-Retailing has been widely used in retail industry and growth is increasing day by day in today‘s scenario. The Internet has changed the way many consumers shop, not just in the digital domain, but also in the physical world. It is a potent medium that can serve as a unique platform for the growth of retail brands in India. The current web-based models for etailing are part of an embryonic phase preceding an era of rapid transformation, challenge, and opportunity in Indian retail market. It is not just the metros that are fueling the online scene in India the demand supply gap in tier 2-3 cities where there is brand awareness but no availability of products and services is also adding to growth.

According to Turban (2006), e-Retailing is defined as retailing conducted online, over the internet. E-tailing or e-retailing refers to the selling of retail goods electronically over the Internet. The concept surfaced in the 1990s including prominent examples like Dell, Amazon. com and e-Bay. In the year 2009, clothing and apparel segment clocked online revenues to the tune of $ 19.5 billion. E-tailing currently accounts for 12% of the retail purchases in the U.S. Amazon is clearly the leading e-tailer in terms of its reach, projected buyers and the unique users around the world. Online retailing can be categorized into:

  1. Click – The businesses that operate only through the online channel fall into this category. Prominent examples in this category include: Dell, Amazon.com and e-Bay.
  2. Click and Brick – The businesses that use both the online as well as the offline channel fall into this category.

Common example includes: Barnes and Noble’s.E-tailing / multichannel retailing offers unique advantages to the consumer that no other form of retailing can match like allowing easier comparisons across broad product categories with the evolution of shopping bots and similar mechanisms, flexible/dynamic pricing mechanisms, doorstep delivery of bulky durables and other products to the consumer. These evolutions reduce any friction in the online market place and stimulated the growth of e-tailers benefitting both marketers and consumers in the long-run. As per CRISIL e-retailing definition includes standalone online retailers and marketplaces, but excludes segments such as online ticketing and online deals, which do not compete directly with traditional brick and-mortar retailers.

                                                 

    Fig. 1 Online retail market size and growth

Source: CRISIL Research

India’s online retail industry has grown at a swift pace in the last 5 years from around Rs 15 billion revenues in 2007-08 to Rs 139 billion in 2012-13, translating into a compounded annual growth rate (CAGR) of over 56 per cent. The 9-fold growth came on the back of increasing internet penetration and changing lifestyles, and was primarily driven by books, electronics and apparel.

CRISIL Research expects the buoyant trend to sustain in the medium term, and estimates the market will grow at a healthy 50-55 per cent CAGR to Rs 504 billion by 2015-16. The entry of new players in niche segments such as grocery, jewellery and furniture, along with large investments by existing players in the apparel and electronics verticals, will be the drivers.

In terms of size, India’s online retail industry is very small compared with both organised and overall (organised + unorganised) retail in the country. This speaks volumes of its potential. We expect the industry’s revenues to more than double to around 18 per cent of organised retail by 2016 from around 8 per cent in 2013. Yet, its share of the overall retail (organised + unorganised) pie will be just over 1 per cent. That compares with 9-10% in the US and UK, and around 4-5% in China.

THE COMPARATIVE PICTURE (2012-13)

Source: CRISIL Research

 

 

 

 

 

LITERATURE REVIEW

According to Turban (2006), e-tailing is defined as retailing conducted online, over the internet. Wang (2002) has provided a broad definition of etailing by defining it as the selling of goods and services to the consumer market via the internet. Zeithaml (2002) has defined that the success of e-tailing depends on the efficient web site design, effective shopping and prompt delivery. The other e-store services are delivery on real time, return and replacement process, period of filling out online orders form, speed of response time to e-customers queries. Ratchford (2001) has said that through Internet, consumers can gather information about merchandise and they compare a product across suppliers at a low cost.

Rao (1999), E-commerce offers increased market activity for retailers in the form of growing market access and information and decreased operating and procurement costs. Myerson (1998) expressed that consumers are getting smarter in using e-tailers (and online search engines and Rao (1999), E-commerce offers increased market activity for retailers in the form of growing market access and information and decreased operating and procurement costs. Myerson (1998) expressed that consumers are getting smarter in using e-tailers (and online search engines and agents) for convenience and comparison- shopping. Guttman (1998) describes several unique elements make online shopping different from the traditional instore retail model. Besides offering convenience and expanded product variety, the online model also makes it easy for consumers to access and compare data from multiple sources. Meeker (1997), retailers might cry foul, but the new shopping paradigm they have to face is that as premium customers begin to accept the e-tail alternative in larger numbers.

 

OBJECTIVES OF THE STUDY:

 

  1. To draw out, the driving factors for growth of the e-tailing.
  2. To analyse the online shopping habits of college students in the retail sector.
  3. To study the effect of demography on online shopping behavior.

 

 

 

Hypotheses:

H1: Convenience, Time Saving, Website Design/Features, Easy Return policy, Easy Payment option and Security have a positive influence on intention to purchase online.

H2: Demographics have an impact on intention to purchase online.

 

GROWTH DRIVERS OF E-TAILING:

The key global e-tailing drivers includes, increasing broadband penetration Expansion in e-tailing services is closely correlated with an increase in broadband penetration. Continuing growth in broadband uptake, as well as   

faster connection speeds, provides support for growth at internet companies. Continuing increased broadband penetration will remain a key factor in the ability of e-tailers to acquire market share at the expense of general retailers.

Better Technology= Better Services:

Increased internet connectivity and lower costs of computer processing power are making the mechanics of conducting an e-tailing business easier. The advent of sophisticated software and supporting hardware has allowed e-tailers to study consumer behavior more efficiently, facilitating targeted sales and increased product cross-selling. This gives e-tailers a major and increasing competitive advantage compared to their B&M competitors. Extensive product search, instant product comparison, wide scope of brand selection, easy transacting, and free shipment and flexible sale return policies (within 1-3 weeks time) are more petals of this service flower.

Increased Product Diversity:

With e-tailers better understanding customer requirements, online shopping has responded by providing a greater diversity of products and services, include more specific, niche offerings. In the case of a number of very small specialist markets, regarded as either too small or specific for traditional retail outlet viability, the development of online retailing has improved their commercial feasibility, increasing the range of products available online.

 

 

More Confidence In Payment Options:

Another crucial driver has been improvements in processing payments for transactions. For example, Amazon allows payment using either credit cards or electronic funds transfer. eBay has implemented PayPal, through which shoppers run a personal online account, enabling them to shop online without disclosing their financial details to retailers. Credit card providers have made advances in security, and increasing consumer familiarity has also improved confidence.

 

Reducing Incremental Mark Up:

Majority of Intermediaries are feeling the pinch from manufacturers as the Internet threatens, disintermediation in channel networks allowing the manufacturers to sell direct to the consumers. It is possible to enjoy the cost advantages of direct selling while still maintaining an effective and economic customer service without passing the expense for either on to the consumer. Such a business model sounds too good to be true yet its configuration is simple. The manufacturer initiates a web strategy allowing it to sell direct to the customer reducing the incremental mark-up at intermediate levels.

Recession:

The protracted weakness in consumer spending has continued to threaten B&M retailers with significant numbers having filed for bankruptcy. Recent B&M bankruptcies are expected to drive more consumers towards e-tailers. According to the Centre for Retail Research, UK consumers spent £38bn online in 2009, a record high 10% of total retail sales. We expect his share to continue to increase, both in the UK and globally. The mobile revolution Smart phones are fast emerging as an alternative computing platform. According to Morgan Stanley,global mobile data users will increase at a CAGR of 29%, reaching 1.1 bn by 2013. This trend could change the dynamics of the e-tailing sector, while there is no consensus on the exact impact.

Increase in the Number of Buyers and Sellers:

 Over the years there has been a sharp increase in the number of buyers and sellers in this segment. In addition to online buyers, many offline stores have begun to sell their products in the online marketplace.

 Change In Consumer Attitude:

 There has been a significant change in the attitude of an average Internet user. He is ready to experiment to suit his convenience. Truly, an average user is buying a variety of products online.

 Shop 24x7:

People nowadays find it easier shopping online, as the products get home-delivered coupled with the facility to shop 24x7. Convenience appears to be a big attraction as most online shoppers find the crowded high streets too stressful. Thus, an online buyer saves time, effort and money when buying online as compared to buying from physical stores.

Better Bargains:

 e-Tailing eliminates the need to maintain expensive and fancy

showrooms. Instead, what attracts customer attention to online stores is the ‘great deals’ ‘best prices’ and ‘better bargains’. For an industry player, Online retailers can manage to offer attractive offers as they operate out of websites and thus save on inventory handling and maintenance costs.

 

Economical:

Unlike the brick–and–mortar environment, in e–commerce there is no physical store space, insurance, or infrastructure investment. All you need is an idea, a unique product, and a well–designed web storefront to reach your customers, plus a partner to do fulfillment. This makes e–commerce a lot more economical.

 

RESEARCH METHODOLOGY

Method of data collection; A Questionnaire was used to collect data from the respondents. Random Sampling was used to collect data from 122 respondents. The data was analysed using SPSS 19. Multiple Regression analysis along with t-test and ANOVA were used to analyse the impact of age, gender and income on the intention to purchase online.

Questionnaire design: The questionnaire was carefully designed to meet the requirements of the research. The questions are taken from previous literature on Consumer’s attitudes towards online shopping with a view to validate the research more and some of the questions were self structured to cover the diversity of research problems. The questionnaire consists of two main parts and one sub part, first part is mainly focused on questions pertaining to factors that influence consumers to shop online. First part of the questionnaire covers the questions relating to factors influencing consumers to shop online, these factors are Convenience, Time Saving, Website Design/Features and Security. All questions are constructed with 5 point Likert scale ranging from 1 (strongly disagree), 3 (Uncertain or not applicable) to 5 (strongly agree). The advantage of using likert scale can be to create interest among respondents as according to Robson (1993) as likert scale can be interesting for users and they often enjoy completing a scale like this. Another advantage can be simplicity as Neuman (2000) suggests the real strength of Likert scale is the simplicity and ease of use.

 

The sample profile of the respondents is shown in the tables below. 

Table 1: Gender Profile of Respondents

Gender

No. of Respondents

Percent

Male

54

44.26

Female

68

55.73

Total

122

100

 

From the gender profile it is clear that among the 122 respondents, 44.26% were males and 55.73% were females.

Table 2:  Age wise representation of respondents

Age Group

No. of Respondents

Percent

15-19

64

52.45

20-24

41

33.60

25-29

17

13.93

Total

122

100

 

Most of the respondents 52.45 were in the age group of 15-19 followed by 33.6 percent in the age group of 20-24 and 13 percent in the age group of 25-29.

 

Table 3: Income group of respondents

Income Group

No. of Respondents

Percent

Upto 5 lac

51

41.80

5-10 lac

39

31.96

Above 10 lac

32

26.22

Total

122

100

 

While analyzing the demographics, another important variable which has been studied is the income group. The customers belonging to various groups have responded to the instrument of the study, which is presented in the table 3 above. This indicates that most of the online purchases are made by the people having annual income upto 5 lacs followed by people having income between 5-10 lacs

 

DATA ANALYSIS:

 In this section below, a discussion on how the objectives set forth were achieved has been deliberated. The objective was to examine and analyze online shopping habits of college students in the retail sector. In order to achieve this objective, regression analysis was undertaken with purchase intention as dependent variable and factors influencing consumers to shop online viz. Convenience, Time Saving, Website Design/Features, Easy Return policy, Easy Payment option and Security as independent variables. The results clearly point out that in 87.3%variation in online shopping is explained by the factors listed above.

 

 Further, the regression coefficients have indicated that out of all six factors namely. Convenience, Time Saving, Website Design/Features, Easy Return policy, Easy Payment option and Security  β value for website design  (β=0.452, p=0.000) has been recorded to be the highest followed by easy payment option(β=0.379,p=0.000) easy return policy (β=0.317,p=0.000), Security(β=0.315,p=0.000), Time Saving(β=0.284,p=0.000) and Convenience(β=0.246,p=0.000).

The Regression equation can therefore be given as:

PI= 5.461+.452wd+.270epo+.379erp+0.315sec+0.284ts+.246 conv

Where PI= Purchase Intention

          wd= Website design

           epo= Easy Payment Option.

           erp= Easy Return Policy

           sec= Security

           ts=Time Saving

           conv=Convenience

 

To analyse the impact of demographics on impulse buying, multiple linear regression  was run with purchase intention as dependent variable and age, gender and income as independent variables. The coefficients on predictor variables show that intention to purchase is positively and significantly related to age β=0.36, t(695) = 10.27,p<.001 whereas gender  β=0.06, t(695) = 1.33,p>.001, income β=0.04, t(695) = 1.22,p>.001 do not exert a significant influence on impulse buying. Therefore, out of the various personal factors only age exerts a significant impact on intention to purchase online.

CONCLUSION

Online shopping is becoming more popular day by day with the increase in the usage of World Wide Web. It has become very important for online retailers to understand the needs of the customers and is one of the biggest challenge for marketers as well. By making improvements in the factors that affect consumers purchase intention to shop online will help marketers to gain the competitive edge over others.

From the results we have concluded that the most influencing and attractive factor among six factors is website design/features followed by easy payment option, easy return policy, Security, Time Saving and Convenience.

 

 

 

 

 

 

 

References:

Guttman, Robert H., Moukas, Alexandros G. and Maes, Pattie (1998), "Agents asMediators in Electronic Commerce". International Journal of Electronic Markets 8(2):pg.no:22-7.

 

Meeker, M.(1997).Morgan Stanley: Internet Advertising Report,New York,NY:Harper Collins.

 

Ratchford , B.T. , Talukdar ,D.&  Lee , M.S. (2001): “ A model of consumer choice of  the Internet as an information source”, International Journal of Electronic commerce , vol. 5, no. 3, pp. 7-21

 

Rao, B.(1999): “Developing an effective e-tailing strategy”, Electronic markets, vol. 9, no1, pp 89-92

 

Turban E. (2006)., King D., Lee J., Warkentin M. & Chung H.M., Electronic Commerce: A Managerial Perspective. Prentice Hall.

 

Wang, F. and Head, M. (2002): “E-tailing: An analysis of web impacts on the retail market”, Journal of Business Strategies, vol 19, no 1, ABI/INFORM Global, p. 73

 

 
 

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