Consumer switching behavior among online retailers in India

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A STUDY ON CONSUMER SWITCHING BEHAVIOR AMONG ONLINE
RETAILERS IN INDIA
BY
NISHANT CHAND
2014
A Dissertation presented in part consideration for the degree of
“Master of Business Administration Degree”

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ABSTRACT:
66% of consumers switched companies in at least one of ten industries due to poor service in the past year. 82% of
consumers felt their service provider could have done something to prevent switching. 55% say they’d have stayed
if the company had proactively contacted them, and 51% would have stayed had the company simply recognized
them and rewarded them for their business (Accenture Global Consumer Pulse Research, 2013).
In the booming of age of organizations expanding their operations globally and companies diversifying their services
and products, the only constant and critical aspect is - customer. One such booming nation is India where with
improvement and penetration of internet, E-commerce is emerging as one of the biggest industry. However as it is
still a new player, there is doubt of what Indian consumers seek in these online retailers to be loyal. The objective of
this research is to study the consumer switching behavior among Indian online retailers. It not only focuses on the
various factors which influence customers to skip from one e-retailer to another, but also why they choose to remain
loyal. It also gives a perception of Indian online consumers on how they see customer value and E-service quality.
Data for this research was collected via online survey questionnaire from 163 consumers in India. The results show
that Indian consumers perceive high standards towards E-service quality and privacy is incredibly important to them.
Most of the respondents were happy with their current “favorite” online retail but emphasized that they would make
a switch on few reasons. The one reason which is most crucial is ethical issues. The findings of the research also show
that price and promotion is least influential in order to choose another retailer.

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ACKNOWLEDGEMENTS:
The completion of MBA and this research study is one of best enlightening and enriching experience of my life. It
would have not been possible because of few people and I would l like to take this opportunity to thank them
from bottom of my heart.
Firstly my supervisor, Ms Anita Chakrabarty for her never ending support, thoughts and assistance for this
dissertation. Your guidance and was critical and is much appreciated.
To all my MBA batchmates, with whom I worked during this course. Memories of knowing and spending time with
you all would be cherished lifelong.
My ex-bosses, who helped and guided me in my professional career. I could use and relate to many work
experience moments during my MBA.
My dad, to whom I look up to everyday of my life. Thank you for instilling importance of education in our family.
Lastly my mom, for all that you have done for me. I could have never been here without your love, care, support
and encouragement.

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List of figures:
Figures: Page:
Figure 1.1 Global online sales from 2007-2012 ..............................................................................................................................12
Figure 1.2 2013 Global retail e-commerce index ............................................................................................................................13
Figure 1.3 E-commerce evolution in India - The Two Waves .........................................................................................................19
Figure 1.4 Annual internet sales growth in 5 years .........................................................................................................................20
Figure 1.5 Top 10 online shopping websites in India.......................................................................................................................23
Figure 1.6 Evolution of E-commerce logistics ................................................................................................................................26
Figure 2.1 Comparison of physical and online stores ....................................................................................................................36
Figure 2.2 Framework for Online consumer satisfaction ................................................................................................................39
Figure 2.3 Conceptual framework of E consequences of E-servqual .............................................................................................44
Figure 2.4 Framework of Consumer value for an E-commerce model ...........................................................................................47
Figure 2.5 Framework for Online trust for E-commerce model .......................................................................................................52
Figure 2.6 Types of switching costs ................................................................................................................................................60

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List of TABLEs:
Tables: Page:
Table 2.0 Factors leading to customer switching for Online platform ........................................................................................56
Table 3.1 Research plan ...........................................................................................................................................................66
Table 3.2 E-service quality variables with questions .................................................................................................................68
Table 3.3 Consumer value variables with questions ..................................................................................................................69
Table 3.4 Online consumer trust and Online loyalty variables with questions ...........................................................................69
Table 3.5 Consumer switching behavior variables with questions .............................................................................................70
Table 4.1 Demographic profile of the respondents ....................................................................................................................75
Table 4.2 Descriptive statistics of statements in construct ........................................................................................................77
Table 4.3 Reliability analysis of E-service quality variables .......................................................................................................79
Table 4.4 Reliability analysis of Consumer Value variables .......................................................................................................80
Table 4.5 Reliability analysis of Online trust variables................................................................................................................80
Table 4.6 Reliability analysis of Online loyalty variables.............................................................................................................80
Table 4.7 Reliability analysis of Consumer switching variables .................................................................................................81
Table 4.8 Total variance explained for top 4 constructs ............................................................................................................82
Table 4.9 Rotated Component Matrix with Communalities and Respective Eigenvalues and Variance ....................................84
Table 4.10 Reliability statistics .....................................................................................................................................................85
Table 4.11 Regression analysis on E-service quality and Online loyalty......................................................................................86
Table 4.12 R and R Square scores for the model .......................................................................................................................86
Table 4.13 Regression analysis on Consumer value and Online loyalty......................................................................................87
Table 4.14 R and R Square scores for the model ........................................................................................................................88
Table 4.15 Regression analysis on Online trust and Online loyalty..............................................................................................88
Table 4.16 R and R Square scores for the model ........................................................................................................................89
Table 4.17 Consumer switching behavior component ranking.....................................................................................................90

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TABLE OF CONTENTS:
Abstract…............................................................................................................................................................................... 2
Acknowledgements ................................................................................................................................................................ 3
List of Figures ........................................................................................................................................................................ 4
List of Tables .......................................................................................................................................................................... 5
Table of Contents ................................................................................................................................................................... 6
CHAPTER 1 INTRODUCTION ........................................................................................................................... 9
1.0 Introduction.................................................................................................................................... 10
1.1 Evolution of internet and Online Shopping .................................................................................... 11
1.2 Changing attributes of Online Retailing ........................................................................................ 13
1.3 Consumer behavior towards Online Shopping ............................................................................. 15
1.4 Consumer switching behavior ...................................................................................................... 17
1.5 Online retailing in India ................................................................................................................. 18
1.6 Scope of business and major Indian players................................................................................. 22
1.7 Future trends in Indian e-commerce landscape ........................................................................... 24
1.8 Challenges ahead ........................................................................................................................ 25
1.9 Research objective ....................................................................................................................... 28
1.10 Research question ....................................................................................................................... 29
1.11 Chapter’s outline ........................................................................................................................... 30
1.12 Conclusion…………..……………………………………………………..............................................31
CHAPTER 2 LITERATURE REVIEW ............................................................................................................... 32
2.0 Introduction………………………………….…………………………………………………………….33
2.1 Online retailing ........................................................................................................................... 34
2.2 Online retail - Having attributes of a physical store .................................................................... 36
2.3 Online shopping behavior ........................................................................................................... 37
2.4 Influencers of Online shopping behavior .................................................................................... 42
2.5 Customer switching behavior ..................................................................................................... 53

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2.6 Switching costs and switching behavior ..................................................................................... 58
2.7 Types of switching costs ............................................................................................................ 59
2.8 Summary of Literature Review ................................................................................................... 60
CHAPTER 3 RESEARCH METHODOLOGY ............................................................................................... 62
3.0 Introduction……….... ….……………………………………………………………………………… 63
3.1 Research method ..................................................................................................................... 64
3.2 Determining the research design .............................................................................................. 65
3.3 Identification of information and source .................................................................................... 65
3.4 Designing the survey instrument .............................................................................................. 65
3.5 Survey questionnaire design .................................................................................................... 66
3.6 Sampling size and Data collection ............................................................................................ 67
3.7 Research parameters and measures………………….……………………………………………..68
3.8 Conclusion…………………………………………………………………………………..…………..71
CHAPTER 4 ANALYSIS AND FINDINGS .................................................................................................... 72
4.0 Introduction…………….……………….……………………………………………………………….73
4.1 Demographic profile of respondents ......................................................................................... 74
4.2 Descriptive statistics of construct variables .............................................................................. 76
4.3 Reliability .................................................................................................................................. 79
4.4 Factor analysis ......................................................................................................................... 82
4.5 Regression analysis ................................................................................................................. 85
4.2 Descriptive statistics of construct variables .............................................................................. 76
4.3 Reliability .................................................................................................................................. 79
4.4 Factor analysis ......................................................................................................................... 82
4.5 Regression analysis ................................................................................................................. 85
4.6 Consumer switching behavior ranking model ........................................................................... 90
4.7 Conclusion ............................................................................................................................... 92

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CHAPTER 5 DISCUSSION AND CONCLUSION......................................................................................... 93
5.1 Introduction …............................................................................................................................ 94
5.2 Indian online shopping behavior ............................................................................................... 95
5.3 Consumer demographic profile ................................................................................................ 95
5.4 Consumer perception towards E-service quality ...................................................................... 97
5.5 Consumer perception towards Consumer value........................................................................ 98
5.6 Consumer perception towards Online loyalty............................................................................ 99
5.7 Consumer perception towards Consumer switching behavior................................................ .100
5.8 Key findings of the research .................................................................................................... 101
5.9 Managerial recommendations to e-retailers ............................................................................ 104
5.10 Closure .................................................................................................................................... 106
5.11 Limitations of the research ...................................................................................................... 107
5.12 Future research recommendations…………………………………………………………………..108
References …..................................................................................................................................................................... 109
Appendices ........................................................................................................................................................................ 123
Appendix 1 Questionnaire Survey ......................................................................................................................... 123
Appendix 2 Demographic data analysis ................................................................................................................ 136
WORD COUNT: 21897 [Excluding Table of contents, References, Appendices, Abstract and Acknowledgments]

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CHAPTERI:INTRODUCTION

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CHAPTER 1 : INTRODUCTION:
 1.0. Introduction:
The online retail industry was in its immaturity stage for most time in the previous decade. However, the last
few years have surprised everyone, with industry witnessing incredible growth of 150 percent, increasing from
USD 3.8 billion in 2009 to USD 12.6 billion in 2013 (PwC,2013). Out of the numerous business models which are
prevalent, consumer e-commerce is seen to have a stronger and wider impact on retail and has engaged
governments, entrepreneurs and investors.
India has also not been untouched. As India advances to become a consumption driven economy, a
transformative and enormous opportunity is presented by this consumer centric model. Over the past three
years, the e-commerce allied companies have turbo charged the online shopping growth engine by introduction
of innovative business models to capture wallet share and online time. Marketing concepts such as ‘by invite
only’, ‘Cyber Monday’, ‘Great online shopping festival’, ‘Flash sales’ have proved to be smashing hits in order to
promote online shopping (KPMG, 2013)
This chapter introduces the evolution of internet shopping over the years and how the attributes have changed
in time. It then discusses consumer shopping and switching behavior when shopping online. It then discusses
the scope of e-commerce in India, the future trends and challenges which lie ahead.

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 1.1. Evolution of internet and Online Shopping:
The magnitude at which internet has expanded itself, many aspects of the business practices have been
transformed throughout the globe (Zwass, 1996). It has lead to the creation of a novel blue ocean business
platform facilitating consumers buying and making transactions online, and after a while an era of E-commerce.
Terms like E-commerce or internet commerce have been refined over the years to explain the process in which
electronic transactions simplify exchange and payment for goods and services among consumers, private and
public organizations, businesses and consumers. OECD (Organization for Economic Co-operation and
Development) defines E-commerce as a process of ordering goods and services by the use of internet platform,
but the payment as well as final product or service delivery is conducted online or offline.
E-commerce had created an offline marketplace which made global businesses easier, accessible, cost efficient
and simple as all transactions were regulated and communicated over the internet (Haque and Khatibi, 2005).
Despite the global economic crisis in 2008, research conducted suggests that Business-to-consumer (B2C) online
retail has achieved massive growth and scope. Figure 1.1 illustrates on how the online retail sales have rocketed
to a $500 plus industry in just five years, and growing. The growth rate of 17% can be seen as spiking faster than
most of the other industries.

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Figure 1.1 : Global online sales from 2007-2012 ( Source from AT Kearney, 2013)
In the meantime, as online retail is termed as a key revenue generating unit in developed nations, a global
research from (MasterCard, 2009) shows a significant growth in developing nations of Asia and Africa.
Figure 1.2 shows on how research from Euromonitor sees immense potential growth in online retail market of
“Established and growing” and “Next Generation” in the next few years. Even though some of developing
countries like India, China, Thailand etc have low internet penetration and significant infrastructure constraints,
results show that consumption of online shopping has increased over the years and still thriving.

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Figure 1.2 : 2013 Global retail e-commerce index ( Source from AT Kearney, 2013)
1.2. Changing attributes of Online Retailing:
As discussed in above sections, online retailing has become more prevalent and consumers have
accepted it faster and in greater number than expected in past the past decade. However, within this
context, the characteristics of e-retailers and customers have evolved rapidly in recent years. The
following paragraphs key changes in customers as well as online retailers in recent past.

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 Consumer transformation: Customers in both developing and developed and countries are found to do a
detailed research before buying anything online and looking for things like product description, shipping
options, return policy etc. Therefore they are seen to become more cynical. They tend to gather more
information from physical stores and through peers & friends by social media. For example, research shows that
half the French customers research products in physical store before going online and three fourth of Brazilian
customers have product discussions on social network (Vazquez, 2009). More consumers are using comparison
shopping engines (CSE’s) to collect product information from a list of retailers on a single page in order to
compare the best overall product (Chylinski, 2010).
 Retailer’s transition: Online retailers are becoming more creative and skillful and they understand that in order
to attract and retain intelligent consumers, they must create industry lead value proposition, variety and
competitive price. Online websites have evolved into product encyclopedias presenting impeccable
information, user reviews and details about the products in every category to the consumers (Yannopoulos,
2011). Customers also have the option to contact the manufacturers, fashion advisors, publishers etc. Retailers
encourage customers to write post purchase feedback but with different intentions. For example many Chinese
e-retailers ask customers to leave a positive feedback for a promo coupon whereas online giant Amazon,
investigates reviews for product flaws (Mckinsey, 2013).
 Dominant product categories of online retail: Though consumers have different taste and preference for clothes
and electronics, yet these two categories dominate over other product categories globally. They sell well
because they have clear product specifications which can communicated easily. Customers can also read user
reviews and compare with other online retailers. Some of the websites offer trying out the apparels on virtual
models in order to facility buying (Parvinen, 2014).

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 Level of competition: The online retail platform has grown to be quite competitive over the years. The
competition can be easily seen in market fragmentation as in every top 30 markets, 50 retailers account for
about 80 per cent sales (Morganosky, 1997). Amazon, world’s biggest online retailer is a leader in 9 markets,
showcasing an aggressive global expansion strategy and it’s USP of gathering consumer followings. Many
retailers with global dominance are now partnering with e-commerce channels and logistics companies in order
to sell their products to international consumers (Colla, 2012).
The above changing trends significantly indicate on how consumer perception towards e-commerce has
evolved. We can certainly claim that this change offers them a larger and wider platform of choices, and thus
more options to choose and switch. The successive section would discuss consumer purchasing and switching
behavior.
1.3. Consumer behavior towards Online Shopping:
Existing research suggests that growth of online retailing looks optimistic, and there is a rapid increase in
numbers of customers worldwide (Ernst and Young, 2001). Product categories of apparel, electronics and
grocery are among the top selling on most online platforms. As per (UCLA Centre Communication Policy, 2001),
online retailing has become third most favorite internet activity after emailing and web browsing. As the internet
penetration and scope increases worldwide, it hints towards the massive sales and opportunity ahead. The
interactive nature of web browsing and internet has improved over the past to offer many opportunities to
upsurge the efficiency of online shopping behavior of customers. Some of them are detailed product
information and prices which enable direct comparisons reducing customers search costs and time (Alba et al,
1997)..

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Online shopping behavior or online buying behavior can be defined as the process of buying products and
services via internet. Liang and Lai (2000) state that there are five steps involved in this process compared to
traditional shopping. In a standard online shopping process, when individual recognizes a need for an item, they
search for need related information on the internet. However most of the times, they are attracted by
information presented about the product linked to their need. They then compare and evaluate the options,
and choose the one which best fits their need. In the end, a transaction is made and a post sales service
conducted. Online shopping attitude can be termed as psychological state of customer in making a purchase
decision on the internet (Davis et al, 1992). Consumer purchase decisions are influenced by cyberspace
appearance such as product info, images, videos, reviews etc and not on actual experience
A framework developed by Laudon and Traver (2009), comparing offline decision making and online customer
decision suggested that when customer want to purchase a product, they would evaluate the brand and the
features of the product or services. While some products can be easily bought and shipped over the internet
e.g. books, software, some were hard to decide through online channel e.g. jewellery.
Customer skills, website features, marketing communication stimuli, click-stream behavior and company’s
capabilities were main constituents in their framework. Customer skills or customer experience with online
shopping which means consumer knowledge about products, technology and competition affect the buying
decision of customer (Broekhuizen and Huizingh, 2009). A lot of retailers invest to improve their website
features and quality in order to influence customer perceptions of web environment and hence affecting their
decision making (Prasad and Aryasri, 2009). Click-stream behavior is another critical element in online purchase
decision making. It refers to online behavior of customers as they search for information through numerous
websites (many websites at the same time), then to a single website, to a single page, and finally to a decision
to buy (Laudon and Traver, 2009).

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All of the above factors lead to certain behavior of online purchasing as well as a sense to control their shopping
environment on online platform.
At last the key influencers of online buying decision are availability of products and services, convenience,
efficiency of cost and time and authenticity of information (Prasad and Aryasri, 2009).
1.4. Consumer switching behavior:
With internet users increasing to a quarter billion worldwide and estimated about 30 billion by 2016, growth in
online retail has been exponential. With this perceived growth, a concern for customer “churn” has developed.
It is a concern which parallels problems of customer switching behavior in online retail industry. Some of this
churn is discontinuance of online service, where consumers try a service but subsequently stop using service
category on the whole. For example, 10 million tried and started using internet by 2006 but stopped by 2008
(Kingsley, 2008). Some of this churn is “consumer switching behavior” where individuals continue to use the
service, but switch to another service provider.
A survey by consultants found that consumers are more likely to revisit and repurchase items from their favorite
“e-retail stores” than traditional physical retail stores and also that e-retail stores are “sticky” as they enjoy
more consumer loyalty (Reichheld and Schefter, 2000). On the whole, with e-shopping developments becoming
more prevalent, online retailers have the benefit of more consumer loyalty than their brick and mortar
competitors.
But the bigger question which has started reflecting on their business is how much customer loyalty persists
within the online retail community. The cost involved in locking up new customers means that loyalty has
become economic necessity and business differentiation among e-commerce retailers.

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While financially driven companies aim for efficient system resulting a drop in customer acquisition cost, “for
most, average consumer acquisition cost is greater than average lifetime value of consumer” ( Novak and
Hoffman, 2000). In addition to costs related to customer acquisition, retaining and winning back lost consumers,
a lot of other expensive activities develop like marketing expenditure to build value equity, brand equity and
relationship equity. This is the reason that a lot of focus has developed in order to study and investigate the
buying patterns and switching behavior of customers.
With this pattern, two key strategies have developed to increase behavioral form of loyalty. The first being
increasing customer satisfaction so that consumers see fewer gaps to switch to a competitor; the second being
to make it difficult for consumers to switch i.e. increasing switching barriers. Customer satisfaction and
switching barriers are seen as antecedents of customer loyalty (Dick, 1994).
Therefore in order to stay profitable, retailers have to ensure that their customers stay with them on online
channel of shopping. E-commerce vendors need to showcase integrated multi channel operations and value
packages which generate interest and offer product differentiation (Sinioukov, 2000). Also, to retain customers
and minimize switching to other retailers, some companies need to provide same shopping experience on both
online and offline platforms. By carefully synchronizing its channels, activities and operations, a retailer can offer
a superior service output which gives consumers fewer reasons and opportunities to switch. This would entail
comparison of multiple retail channel benefits and costs viewed by customers more holistically.
.1.5. Online retailing in India:
As per World Internet Stats, India finds itself as third largest among internet users in the world after China and
USA. It is surprising because it has a very low internet penetration of 8.5 %. The count for Indian internet users
has been rising at a CAGR of 35 per cent since 2007. As per Boston Consulting Group 2010 report, the figure of
100 million Indian internet users in 2010, the number would rise to 237 million by 2015 (Brown, 2001).

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Figure 1.4 : E-commerce evolution in India - The Two Waves ( Source Ernst & Young, 2013)
With the debut of internet in India in 1995, the first wave of e-commerce had also touched the country (Figure
1.4). Moreover, with liberalization of economy in 1991, many MNC’s were setting up their base in India brining
IT growth in the country (Ganguly, 1999). Although online businesses were beginning to develop by late 1990’s,
the infrastructure required to support the activity was not in place. Therefore the first wave of e-commerce was
met only by small online shopping consumers due to low internet penetration, slow broadband speed, low level
of acceptance of online retail and poor logistics.
With the introduction of Low Cost Carriers (LCC’s) in 2005, a second wave of e-commerce in India was predicted.
Travel started emerging as one of largest segment in online retail segments. Consumers were now depending
on internet websites and portals to search of travel information, bookings, payments etc. With a ripple effect,
the acceptance of online travel made Indian consumers comfortable towards the concept on shopping online,
thus leading to growth of online retail industry.

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India ranks as 16th in annual internet sales growth depicting its future growth and capacity in internet business
(Figure 1.5). This rapidly increasing internet penetration and scope is believed to directly impact Indian Online
shopping business and trends or e-tailing.
Figure 1.5 : Annual internet sales growth in 5 years (Source Cushman & Wakefield, 2013)
Some of the reasons which have resulted in high internet growth are:
 Smaller urban areas are growing: Out of 120 million users in India, the bigger growth is seen from small towns
with a population of half a million. They have a combined usage of 60 per cent which is greater than eight metro
cities added together (Ling, 2010).
 Increasing internet diffusion in lower SEC’s: India is classified into a number of Socio Economic Classification
(SEC) bases on per capita income. But the growth of internet has been seen more in SEC C at 25 per cent and 11
per cent in SEC D and E status. With the rise in literacy rate, these figures are projected to rise further.

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 Increased usage of internet on mobile: India is believed to have more than 1.1 billion active mobile users as of
December 2013. Out of this, about 67 million access web via their mobile devices. This behavioral change has
been nourished by high cost of ownership by broadband companies.
 Youth driving the change: About 75 per cent of active internet users are Indians within the age group of 21-35.
The major usage is towards social networking, emails, browsing, and downloading digital content
(Economist, 2012).
When India’s first online retail website, Fabmart.com (now Indiaplaza) had started operating in 1999, only a
small number of three million users shopped online and the market size was only 11 million USD (Economist,
2012). The same Indian market is seen as 8.8 billion USD online retail industry by 2016 and its growth rate is
projected to be fastest in Asia Pacific at 57 per cent. The online platform in India is burgeoning by offering
various options of movies, books, travel, hotel reservations, matrimonial services, gadgets, groceries etc. India
is a nerve center to 2217 import hubs, 3311 e-commerce hubs, 391 export hubs and 1267 rural hubs
(Ebay, 2011).

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1.6. Scope of business and major Indian players:
With introduction, implementation and revolution in the technology and internet, a new market has been
created for service providers as well as manufacturers. It has also handed over a new arena which involves
constant improving strategies and innovative marketing (Yulihasri, 2011). There have been numerous reasons
as to major shift of consumer buying patterns towards e-commerce. The ease of comparing products with
competitive items on basis of color, size, price, quality and shipping speed has been one of the biggest benefits
perceived. With evolution of online shopping in India, new terms became popular like web stores, virtual store,
online storefront, web-shop, e-shop, internet mall etc (Na Wang, 2008). With increasing sale of smartphones,
mobile commerce or m-commerce is also becoming popular by which consumers can simply place orders via
mobile application of websites. Also, the various coupons, discounts, deals like Black Friday & Big Billion Day
sale are fascinating Indian consumers to shop online.
Even the rising inflation in past few years has not affected the performance of leading online shopping portals
of India. In 2013, the capacity of online retail in India was $16 billion which was only $8.5 billion in 2012
(Ernst & Young, 2013). Earlier the Indian online shopping market was only limited to sale of mobile phones,
books and electronic gadgets, but in past two years products reflecting lifestyle, viz. apparels, health & beauty,
watches etc. have gained high popularity. Now the e-retailers are aiming to make categories like e-books,
jewellery, kitchen appliances more acceptable to consumers.
If we were to consider the update from (Ernst & Young, 2013), the number of online shopping websites have
reached 600 in 2013, which was mere 100 in 2012. This rising popularity of e-commerce websites is also
significant in addition to global online retail leaders like Amazon and Ebay. The following Table 1.1 gives a
glimpse to current top ten e-commerce websites in India.

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RANKING WEBSITES SERVICES OFFERED
1 Flipkart It is a mega online store which offers wide range of products including
clothes, books and electronics.
2 Ebay India It has unique business concept where a seller can sell the product
directly to buyer.
3 Snapdeal It is online marketing and shopping company which has
existence in more than 400 cities in India.
4 Jabong It has been a front runner in online shopping websites in India and
offer attractive discounts, promotional and deals for Indian
customers on many fashion, home décor and lifestyle variants.
5 Myntra It retails many famous national and international brands like Puma,
Adidas, John miller, Lotto and many more.
6 Tradus It offers wide range of wholesale and retail products online. Tradus.
com is an Auction and shopping company operate in many European
countries.
7 Junglee Junglee is an online website which provides electronics, lifestyle,
men & women apparel, accessories, movie CD/DVD, home décor
products etc.
8 Homeshop18 It is an online shopping website and retail distribution network
company.
9 Shopclues An online mega store recorded highest growth in year 2012 and
Alexa ranked 1000 in mid of August -13.
10 Yebhi It deals in many top national & international brands and products
such as footwear, fashion, accessories and jewellery.
Table 1.1 : Top 10 online shopping websites in India

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1.7. Future trends in Indian e-commerce landscape:
 First few movers and focused will proper: With second wave of e-commerce hitting the Indian consumer market,
many young entrepreneurs have ventured into e-commerce. Across wide number of categories, there are
numerous retailers spending money on marketing to grab some portion of market share. The scenario is quite
similar to dot com bubble in US, where several companies tried to sell the same common concept to consumers,
with little or no differentiation (Chen, 2002). With past studies and examples, the e-commerce industry shows
that only a few early starters and companies offering differentiated services, products, marketing and customer
relationship management will emerge as long run winners. Flipkart and recently launched Amazon are seen as
big players in Indian market.
 Acquisition cost and Customer lifetime contribution are key factors: Online retailers archive promotions,
discounts and free shipping under marketing budget which increases Customer Acquisition Cost (CAC). CAC in
India is currently about an average of USD 25 (Businessline, 2013). It is surprisingly higher than international
brand like Amazon which has CAC of USD 12. Ebay has even lower CAC of USD 4. Customer Lifetime Contribution
(CLTC) on the other hand is the Net present value of profit from consumer’s total purchases and ideally it should
be more than CAC for a profitable consumer. If CLTC is twice the cost of acquiring a new customer, with 1X
coming in first 12 months after it acquires, the company is doing very well (Bauer, 2003). A successful retailer
needs to invest in business analytics and study parameters like website performance, conversion, returning
traffic, customer service etc to create better customer acquisition strategies.

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 Physical retailers will have an advantage: In the west, where brick-and–mortar retailers are seeing fierce
competition from digital retailers, the market scenario in India is likely to be different. With low internet
penetration, limited payment options and slow growing infrastructure, pure click retailers might face slow
growth and revenue. Digital platform can thus be an additional benefit to big physical stores who wish to take
their business online. These physical stores can leverage on their size, brand name, operations efficiency and
marketing strategies to penetrate the online platform better (Crisil, 2014).
 Tier II and III cities should on business hit list: Towns with population of about 0.5 million have internet usage of
more than 60 per cent, more than eight metros put together. With growing economy, the disposable income is
also rising. A successful e-retailer needs to create a delivery and business network of about 3000-4000 pin codes
out of total 150,000 pin codes in India (Crisil, 2014)..
1.8. Challenges ahead:
 Logistics: Logistics is a major key driver towards successful service fulfillment. It has been a key focus area for
digital retailers in an attempt to make Indian consumer comfortable to shop online. For quite few years, almost
all online retailers were dependent on third party logistics companies for delivery to customers. Now many have
started delivering the orders themselves. The number of courier companies has also been rising, with about
4500 covering all the pincodes of the country. The cost of logistics is high due to lack of good quality
infrastructure. With creation of its own logistics, the retailer can benefit by higher profits; competitive
advantage over local and new global entrants; lastly, it can open its delivery options to other retailers and charge
them e.g. Amazon encouraging small companies to use it marketplace platform and cloud services.

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Figure 1.7 : Evolution of E-commerce logistics (Source Jones Lang LaSelle, 2013)
Figure 1.7 shows how the e-commerce logistics has evolved from their initial introduction in 1970’s to 20h
century in India. Suppliers have changed their supply chain from delivering to shops to creating a full strategic
operational supply chain cycle.
 Payment options: With Cash On Delivery (COD) being provided as a payment options by most Indian online
retailers, perception of shopping online has certainly increased. Earlier, many consumers felt uncomfortable
sharing their debit/credit card details over the internet which was a major hindrance for shopping online. Also
a major population in India did not have a debit or a credit card. COD allowed customers to make payment when
the items were delivered to them. Furthermore, even those who did possess a card, preferred to shop via COD.
About 60 per cent of Indian buyers who had a credit card, still preferred COD for most of their purchases (BCG
Report, 2013). More than 50 per cent of payment transactions were via COD (IBEF Report, 2013). But unlike
electronic payments, collecting cash manually is expensive, laborious and risky. The current need is to make
credit or debit card more popular as payment option.

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 Short attention span by consumers: One of the major challenge and difference on shopping online is that
consumer’s attention span and patience is quite less. Customers can easily navigate to various websites in case
they do not find the product. The problem becomes worse in places where broadband speed is very slow. About
40 per cent would not wait for more than 3 seconds for a webpage to respond (Roland, 2013).

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1.9. Research objective:
As online shopping is gaining rapid interest in India, an investigation on the consumer switching behavior, online
trust, E-service quality and consumer value has therefore become a timely topic for research.
The main objectives of the research would be:
i. To identify key factors which influence Indian consumer switching behavior when shopping online.
ii. To determine crucial elements which influence online loyalty, consumer value and E-service quality perceptions
of Indian customers towards e-commerce companies.

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1.10. Research question:
The first and foremost reason which provoked an interest for this study was with growing economy, Foreign
direct investment by raising billions, more use of tablets & smart phones, the Indian E-commerce is growing at
an astounding rate. Though attracting new customers is a key strategy for major players, retaining many of them
by studying a switching behavior might give them larger loyalty and thus bigger profits. Hence, in order to retain
and attract consumers in a thriving competitive market, e-commerce store owners need to recognize on how
web-consumers perceive value and loyalty (Goldsmith, 2002). At the same time, understanding reasons and
patterns of customer exit can help them offer prolong and enriching shopping experience.
Therefore to meet the objectives of the research, I have developed three research questions. They are:
i. What are the factors which influence customer exiting behavior amongst Indian consumers?
ii. Which are the key variables which determine online loyalty for E-commerce companies by Indian online
shoppers?
iii. What are the factors which help Indian customers determine value and E-service quality of online retailers?

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1.11. Chapter’s outline:
Now that the groundwork for the research has been introduced, the remaining part of the research aims to
answer the objectives in the following structure:
Chapter 2 : “Literature Review” would cover the relevant literature, findings and previous studies associated
with online retailing, E-service quality, Consumer value, online loyalty & trust and switching behavior. It would
focus on various previous research frameworks. Lastly, a conceptual research model is discussed in this chapter.
Chapter 3: “Research Methodology” would bring out on how the research objective is planned to be responded.
It would illustrate research plan, design and action plan of data collection.
Chapter 4: “Data Analysis and Findings” would present an analysis of the result from the surveys and compare
them with earlier discussion of Literature Review. Also, it would highlight new and major findings linked to
research objective.
Chapter 5: “Discussion” would try and elaborate the major finding of the research and create a debate around
it.
Chapter 6: “Conclusion” would be the last chapter which would bring out key findings and conclude the research
with future research recommendations.

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1.12. Conclusion:
In this chapter we were able to have an overview of evolution of internet retailing in the world and how it has
grown in India in past few years. Not only has it evolved in number of shopping websites being offered, it has
seen sales in new product categories. A research which brought this out was conducted by Great Online
Shopping Festival (GOSF), which is supported by Google. As per the sales analysis of GOSF (2013), the partner
online websites saw 350 per cent growth in daily sales and 50 per cent of buyers were shopping for the first
time (Chaudhary, 2013). Also surprisingly was seen that highly valued items like five houses worth Rs 25 crore,
34 Nissan cars and over 200 Tata motor vehicles being bought in four days of online shopping festival (Sushma,
2013).
Overall, electronic commerce in India still accounts for only small fraction of total sales, but looks to grow to a
considerable amount due to the factors of rapid urbanization, support of demographics, increasing adoption,
ease of payment modes, penetration of internet and technology, invitation to foreign direct investments and
customer centric innovative policies. While the online retailers view future opportunities as being first movers
and acquiring and retaining customers by various marketing strategies, they must understand the challenges
which stand in terms of logistics, difficult payment options, acquiring new customer or exit of existing customer.
The introductory chapter thus provides background and future of online retail in relation to growing Indian
market. It also presents various opportunities and challenges which can be a crucial service differentiator. In
the successive section we would lay the research objectives and questions followed by a breakdown of research
outline by chapters.

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CHAPTERII:
LITERATUREREVIEW

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Chapter 2: Literature review:
2.0. Introduction:
The main objective of this chapter is to bring forward relevant literature focusing on dimensions of consumer
switching behavior, online shopping behavior, online consumer trust & loyalty, E-service quality and customer
value. The chapter showcases an overview on consumer exiting behavior and provides previous studies and
researches conducted in relation to above mentioned parameters.
The chapter starts with an introduction to online retailing and how it shares common attributes of offline stores
followed by literature on online purchasing behavior. Then the chapter brings about various influencers of
online purchasing behavior. Next, the chapter sets forth the consumer switching behavior model and discusses
various switching costs. The chapter then ends with a summary of the complete Literature Review.

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2.1. Online retailing:
The rapid rise in growing number of online shopping customers has brought forward numerous opportunities
and challenges for organizations (Bai et al, 2008).These growing numbers lead interest of many researchers to
investigate consumer’s perception and behavior, and their influence for the emerging new e-commerce
business models (Hackman et al, 2006; Janda et al, 2002; Liu et al, 2008). Srinivasan and Anderson (2003)
suggested using a service marketing framework which was initially created for offline businesses. They felt it
could also investigate the consumer purchasing behavior patterns of e-commerce business models.
In contrast, few researchers emphasize on the fact that few of the crucial fundamentals of online retailing
environment and behavior, were distinct to conventional offline or physical store context (Janda et al, 2002; Liu
et al, 2008). Regardless to these different approaches to various frameworks, most researchers admitted that
by offering anticipated quality and satisfaction, retailers can control the consumer behavior and limit their
switching habits (Janda et al, 2002; Bai et al, 2008). This also helps to create a long lasting loyalty and trust
platform offering them a distinctive competitive advantage.
It can now be universally accepted that internet’s scope, interactivity and power provides retailers potential and
opportunity to transform customer shopping experience (Wolﬁnbargers and Gilly, 2003; Evanschitzky et al.,
2004), and in doing so, also bolster their competitive position (Levenburg, 2005; Doherty and Ellis-Chadwick,
2009).
The magnitude of the internet to facilitate communication with consumers, provide information, collection of
market data, promotion of products and services and supporting online shopping experience, provides retailers
innovative, flexible and rich channel (Muylle and Basu, 2003).

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By doing so, internet has provided a mechanism to broaden target markets, extend product categories, reduce
costs, improve efficiency, enhance consumer relationship and deliver promotions and offers. But it was not until
last decade that internet touched shopping world. In few years it redefined the conventional world of retailing.
Retailing is defined as a list of business activities which add useful value to services and products sold to
customers for their use (Levy, 2006). On the other hand, Internet retailing, Electronic retailing, E-tailing or E-
commerce can termed as retail-ing business over the internet (Rosenbloom, 1999). Electronic retailing, which
involves online transaction and interaction between a retailer and a consumer, from the moment the consumer
browses retailer’s website to the point consumer’s order is fulfilled by the retailer, has swiftly emerged to
become an efficient and effective class of service operations (Field et al., 2004; Smith et al., 2007). It can also be
explained as, on one side, sellers sell products or provide services over their online platform i.e. website;
whereas on the other side customers purchase these products and services by accessing or browsing these
platforms by the use of internet. Non-digital products get delivered by linking supply chain and logistics whereas
digital products are delivered over the internet.
Ellis-Chadwick and Doherty (2006) divided the research on online retail in three categories. The first category
examines customer perception, psychology and focuses on online purchasing behavior of consumer. The second
studies company’s or retailer’s approach to retail management, business model and online inventory. The third
category researches technology perspective on how innovation in emerging IT sector can influence future
trends e.g. use of flash player to display products to be visually compelling.
But many researchers believe that much of the business model and strategies of online retail have been
developed from traditional stores. Many concepts which online retailers use have been developed by traditional
brick-and-mortar shopping methods. The same is presented in next section which focuses on how similar and
how different is online platform from conventional retail stores.

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2.2 Online retail - Having attributes of a physical store:
Electronic or online shopping incorporates some of the same features as “real” shopping which has lead to its
wide acceptance. Many of the attributes which consumers favor while shopping in department stores, are seen
while shopping online (Berry, 1969). Some of the researches have categorized physical store into areas of
function like store polices, merchandise selection, price and layout of a store. These areas are also considered
when designing a business model for an online platform. (Lindquist, 1974) further explains these attributes by
categorizing into four groups of service, promotion, merchandise and navigation. The variable of service
showcases general service process in a store and sales service for product returns. The variable of promotion
records marketing, advertising and features to attract customers e.g. “What’s new” section on a webpage. The
variable of merchandise measures product selection, quality, variety, pricing, guarantee and warranty. The
variable of navigation defines layout of the store and checking out process.
Figure 2.1 : Comparison of physical and online stores (Source Lohse and Spiller, 1999)

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Figure 2.1 shows comparison among online and offline stores. We can see how sales desk customer service in
physical store is replaced by aspects such as product page, search function and customer service on phone or
email in an online platform. The physical window shopping is showcased in the form of website homepage to
customers whereas checkout cashier’s role is played by online shopping cart and electronic payment page.
The above literature gives a perception on how online retailing is identical in some aspects of conventional
retailing and how some forms are modified for consumers, all of which serves as a variable for online shopping
behavior which is discussed elaborately in upcoming section.
2.3. Online shopping behavior:
Electronic commerce has emerged as one of the most distinctive characteristics of internet era. As per (UCLA,
2001), it is third most popular activity on the internet after email and web browsing. It even beats trends like
looking for entertainment and news on the internet, two most common activities people think what internet
users do. Online shopping behavior/Online buying behavior/Internet shopping behavior is referred to as process
of purchasing services or goods on the internet. The shopping process involves five steps similar to traditional
shopping process (Liang and Lai, 2000).
Online shopping is viewed complex in nature and can be subdivided into various processes such as customer
interaction, navigation, search for information, online transaction etc. It is highly unlikely that consumers
evaluate each sub-process individually and in detail during single transaction. Rather they would evaluate and
rate the overall shopping experience (Van Riel et al., 2001).
The Online shopping process starts when consumers feel the need for a product or service, go on the internet
and search for related product. However, most of the times potential consumers are engaged by product or
service information which they feel fits their need. They then compare various options, make an evaluation and

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choose the best which fits their budget. Finally, a payment is made for the product and after-sales service is
provided.
Donthu and Garcia (1999) said that online shoppers were innovative, variety seekers, less risk adverse and more
impulsive when compared to non-online shoppers. As they exhibited higher level of self-confidence, they were
found to have better knowledge and information about shopping online. In order to ensure that internet spreads
and propagates as retail channel, it is critical to realize customer shopping intentions and conduct in relation to
online buying practice. Johnson,Lohse and Bellman (2009) examined relationship between personal
characteristics, demographics and attitude in relation to internet shopping. They found that consumers who
have more wired lifestyle and have more time constraints, tend to shop more frequently i.e. people who used
internet as routine tool and/or deprived of personal time, preferred shopping via online retailers. Another study
on young Malaysian shoppers showed that young consumers were searching and browsing more for online
products and services & found internet shopping more convenient compared to traditional shopping (Sorce et
al., 2005).
Dholakia (1999) claimed that items which sold the most through online platform were usually of low risk and
had low cost convenience e.g. books, music etc. However with higher internet penetration, over the years
consumers have started shopping largely on other product categories. However products with low investment
are purchased frequently, have intangible value and high on differentiation are likely to be purchased more
through online retail than conventional shopping method.
Consumers also use both offline and online platforms in combination to make a purchase decision.
Francis (2004) found that online research also drove offline sales. Many consumers navigate through websites,
find product information, compare prices and in the end make the final purchase from a physical store. Morris
(2013) conducted a study on ‘More Consumers Prefer Online Shopping’ Shoppers increasingly want what’s
called a “seamless omnichannel experience,” meaning one in which retailers allow them to combine online and
brick and mortar browsing, shopping, ordering and returning in whatever combo they would like.

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Schiffman, and Long (2003) asserted in their research that “individual attitude does not influence one’s intention
or behavior by itself, instead that intention or behavior is a result of variety of attitudes which the customer has
about range of points relevant to situation at hand, in this case it would be internet shopping”. A study on
consumer attitude towards online shopping in New Zealand included several variables towards four main
categories; shopping experience, value of product or service, quality of service offered by e-retailer and risk
perceptions of e-commerce. It was found that regular and loyal shoppers were more satisfied by all four
variables compared to rare or trial buyers (Shergill and Chen, 2005).
The above two studies suggest that regular shoppers tend to be relatively more comfortable shopping online
and perceive risks as non-existing. Also, e-commerce is widely accepted by young age customer base with loyalty
and trust being developed by long term service and ethics.
Figure 2.2: Framework for online consumer satisfaction (Source Bigné and Ruiz, 2008)
Figure 2.2 shows a framework created by Bigne and Ruiz (2008) showing positive relationship between customer
satisfaction, trust and commitment towards retailer. They also presented that positive effect of effective
communication, privacy and user friendly features of the website developed trust and consumer satisfaction.
On the other hand, Chowdhury and Ahmad (2011) found in their study of Malaysian online shopping behavior
that four key variables which were trust, ability, benevolence and integrity, were directly positively influenced

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by each other. Though trust and ability emerged as major influencers of online shopping behavior, integrity
instigated customer exit. The study however does not take into account other major variables like consumer
switching, competition etc.
The source and nature of information and knowledge has been seen to influence online buying behavior (Bigné-
Alcañiz et al., 2008). The most critical feature of internet is that it regulates pre-buying stage as it facilitates
consumer to compare various options of the same item (Dickson, 2000). In the purchasing stage, assortment of
products, sale service and quality of information are the most important purchase decision factors for the
consumer (Koo et al., 2008). They decide the end product and the online retailer. The major influencers of online
shopping are - efficiency, availability of products, information, convenience and cost efficiency.
Post-purchase behavior comes into picture after the sale is made. Customers might have concerns or problems
relating to product or service and might need to return or exchange. Thus, two major dimensions of post-
purchase behavior are return and exchange services (Liang and Lai, 2002).
Few of the conclusions from above literature is that need for a product or service initiates the online purchasing
behavior where information plays the role of the catalyst. Online buyers seek diversity of options, comfort and
cost capacity.
Internet has also emerged as a tool for comparison of shopping as consumers often browse through various
websites, compare products, and maybe make a purchase online or offline. Also online consumers do more
research for products and prices compared to offline shoppers. Therefore, online shopping allows customers
freedom to visit “virtual shops” and make a purchase, or even perform “window-shopping” with confidence.
With the increasing size, more demand by youth and change in the behavior of youth towards shopping has
clearly indicated a huge market is available to the incumbents and existing performers. And at this stage it is
important to understand the buying behavior of Indian customers towards online shopping which is mandatory
for a great marketing strategy by the players in this industry.

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The size and growth rate of this industry was never like this before. And considering all this, the present study
has made an attempt to understand the online shopping behavior of Indian customers.
Content privacy, vendor profile, security of transactions, logistics timeframe and discounts are crucial factors
which influence electronic exchange (Rao, 1999). Donthu and Garcia (1999) presented convenience, risk
aversion, income, impulsiveness, age, attitude towards direct marketing and advertising and variety seeking
propensity as key elements to influence online buying behavior. Lukas and Maignan (1997) and Rowley (2000)
presented a research which conveyed that financial risks were cited as primary reason to stop shopping over
the internet and personal security had become dominant concern in both online relationship as well
transactions. Customer’s preference and willingness in order to adopt internet as his/her shopping medium is
positively associated with household size, income and innovativeness (Sultan and Henrichs, 2000). Perceived
risk is also seen to negatively affect the online purchasing behavior. Internet shopping experience is also affected
with privacy and security concerns. Therefore the above literature suggests that with online shopping still not
be in comfort zone of most shoppers in developing countries, it should be a prime strategy of online vendors to
assure customers of transaction security, managing website traffic, minimizing return hassle for better online
shopping experience. Apart from the above mentioned influencers of online shopping, few distinct have been
consistently mentioned.
The past literature and research have suggested that there are three main influencers which govern online
shopping behavior and are discussed in upcoming section.

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2.4. Influencers of Online shopping behavior:
(a) E-Service Quality:
The main goal for functioning of any business is to earn high and long term profits. While the production in
scope of conventional offline service quality is measured by comparison of consumer expectations with
company’s substantive service performance (Sasser, Olsen, and Wyckoff, 2001), components evaluating
electronic service quality were modified to adapt to electronic domain (Parasuraman et al., 2005). E-Service
quality is one of the crucial aspects to determine failure or success of an e-commerce has been developed from
traditional internet marketing. The concept of electronic service quality or E-SERVQUAL, also termed as E-service
quality in online retail, can be defined as customer’s evaluation of excellence and quality e-service offered on
virtual platform. A perceived service quality framework incorporates guaranteed tailored web services,
optimum performance of logistics (Doney and Cannon, 1997), and warranties provided by the online retailer
(Kim et al., 2004). In order to deliver superlative quality service over the internet, e-commerce organizations
need to understand consumer perceptions regarding how they evaluate the quality of their services.
Santos (2003) studied E-SERVQUAL and found that electronic service quality is assessment of extensive
consumer intuition and measurement of delivery of internet retailers on virtual marketplace. The importance
of e-service delivery is highly recognized in business world and also as to why consumers seek an increase of
these services is due to its ease of making comparison among various service providers in contrast to traditional
offline ways (Santos, 2003). Because comparing product prices, information and features becomes much easier
than traditional methods of shopping, E-service quality becomes a crucial factor for consumers (Santos, 2003).
Therefore it would be correct to mention that online consumers expect equal or higher level of E-service quality
compared to traditional shopping method.

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The literature of the above two studies shows that as for online retail stores, a well accessible and designed
website creates an expectation for consumer for the service they expect E-service quality (E-SERVQUAL) not
only provides a competitive edge over the competition but also boosts relationship between e-retailers and
customers.
Online consumers believe that when internet and technology potential is realized by e-retailers, ideal E-service
quality can be achieved (Yang, 2001). In the past many researchers have laid importance on detailed analysis of
links between E-SERVQUAL and its outcomes (Oliver and Rust, 2001), because the links are not direct and simple
(Brady et al., 2005). Few of the studies have probed in comparison of conventional service quality and outcomes
of trust (Sharma and Patterson, 1999), loyalty and consumer satisfaction (Cronin et al., 2000) but only in context
to physical retailing.
With improvement in technology, most internet based companies have modified their interaction with
consumers. Ample studies have been conducted which focus on evaluating and measuring online e-service
quality. Researchers have developed distinctive scales to evaluate E-SERVQUAL. E-service is also an interactive
information tool which provides firms a mechanism to differentiate their key strategies and gain competitive
advantage (Santos, 2003). Key notes from E-service quality literature, various dimensions of web experience
were used in relation to factors such as trust, satisfaction, convenience and loyalty (Rowley, 2006). A research
by Hitt and Chen (2002) concluded that Electronic service quality was negatively correlated to consumer
switching behavior and costs. The findings also showed that high levels of electronic service quality can increase
customer intentions like repurchase of products and services from website, site revisit and reduced switching
behavior.

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Figure 2.3 : Conceptual framework of E consequences of E-servqual Source (Keyoor ,2008)
Figure 2.3 further illustrates the consequences of E-servqual linkage between dimensions of E-SERVQUAL and
aspects of customer satisfaction and trust. All of the core variables of E-service quality when put together in
strategic business framework of online retail leads trust and customer satisfaction which in turn leads to long
term customer loyalty. Zeithaml et al. (2002) developed an assessment tool for measuring E-service quality
which consisted of following seven dimensions: contact, efficiency, privacy, compensation, reliability,
responsiveness, fulfillment and contact. They are divided into core service and recovery scale depending on
when the consumers contact to experience the e-service. While the core-service variables control the pre-
purchasing online shopping behavior, recovery scale variables come into effect after the sale, usually in cases of
service failure.
They are as follows:
 Core Service Scale of E-SERVQUAL: (a) Fulfillment: Efficiency in service requirements, items in stock and
delivering orders on time. (b) Efficiency: Accessibility of website to consumers, finding the desired product and
information regarding minimum effort from consumers. (c) Privacy: Assurance that payment details are secure.
(d) Reliability: Technical functionality and availability of website.

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 Recovery Service Scale of E-SERVQUAL: (a) Contact: The need of consumers to speak and interact with “living”
agent and not a “robot”, whenever they contact customer service. (b) Responsiveness: It involves assurance by
e-retailers to consumers to handle warranties, returns and data as promised before purchase decision is made.
(c) Compensation: It involves refunds made back to consumers and how return shipping is handled by the
retailer.
Therefore it can be concluded that efficient and exceptional E-service quality is a critical factor for online
vendors as it is one the factors that would not only enable them to attract more online consumers but also
prevent customer switching. The variables of Core-service scale of E-SERVQUAL would further be discussed in
Research Methodology chapter.
(b) Consumer value:
From a strategic perspective, this change has provided opportunities for retailers to improve business efficiency
and increase market reach by using internet platform and offer better service value to their customers.
(Zeithaml, 1988) defined perceived customer value as consumer’s appraisal of the benefits received for a
product or service in comparison to the cost incurred for those benefits. These benefits include objective,
subjective, quantitative and qualitative attributes.
From the viewpoint of marketing, creating consumer value means ensuring consumer needs are met and
increasing consumer satisfaction (Porter, 1985). The concept of consumer value management is extensively
used by market oriented companies to differentiate their selling points from competition (Heiman, 1996).
Adding to it Woodruff (1997), states that consumer value is “perceived preference for evaluation of product
traits, performance of those traits and consequences resulting from usage which help achieving consumer goal
and purpose”.

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With the help of above literature, we can define consumer value as net benefits a consumer obtains from a
store or a product. And in terms of e-commerce, if the company has presence on internet by selling products or
providing information, then consumer expects different value and service compared to offline retail. Consumer
value has received extensive research in marketing segments in the past two decades e.g. Parasuraman et
al.1985, Zeithaml 1988, Dodds et al. 1991, Holbrook 1999, Chen & Dubinsky, 2003). Not only it plays a key role
in consumer choice prediction, but also influences long term loyalty. If retailers offer optimum value to their
customers, they create enormous competitive advantage (Chen and Dubinsky, 2003). Despite its critical
importance in offline environment, consumer value has been less studied in online retail context. Online
consumer value is different from offline counterpart in many aspects. In e-commerce settings, not only the
product but even the e-store and internet channel affect value quotient for consumers (Keeney, 1999).
There have been two key streams of the research; product value and shopping value. Product value is referred
as to what a customer gets on paying for a product or price/quality tradeoff whereas shopping value is defined
as store‘s shopping experience evaluations (Babin et al.,1994).
While we can derive some similarities, there are key differences between two. Firstly shopping value of retail
mentions on how items are provided to consumer via store’s operations e.g. efficient service, lower pricing.
Therefore two retail stores selling the same item could be offering different value to consumers. Secondly,
certain share of product value, e.g. price is determined by operations of the store, which gives the perception
of overlapping of shopping and product value (Chen and Dubinsky, 2003).
We can therefore derive that product value is critical to consumer’s decision for product choice whereas
shopping value is critical to patronage online shopping behavior. Also consumer value is used as underlying
concept which encompasses both product and shopping value.

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Figure 2.4: Framework of Consumer value for an E-commerce model Source (Lohse,2000)
The framework shown in Figure 2.4 presets major factors which influence perceived consumer value in B-to-C
E-commerce scenario. It focuses on perceived core value as core variable and other antecedents and mediating
factors. The framework also justifies two scenarios. Firstly, consumers spend too much effort and time on pre-
purchase evaluation and internet is an ideal medium for this activity. Secondly, perceived consumer value also
influences purchase intentions of individuals. Also a number of literatures reveal four major aspects which are
involved in pre-purchase shopping phase which have powerful influence on customer’s value perception as well
as buying intentions. They are price, emotional experience, perceived risk and perceived quality. Each of these
factors can either negatively or positively provoke perceived consumer value. For e.g. highly perceived product
quality can benefit company sales whereas, low or bad quality can act as a cost and reduce customer’s value
perception.

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Customers use price as an indicator of quality as it shows a belief that demand and supply forces lead to a
universal ordering of items on price scale. It means that there is positive relationship between product quality
and price. Emotional experience is defined as customer’s attitude or emotional state which is aroused by pre-
purchase online shopping. Consumer behavior is a function of both, the environment and the person (Wilkie,
1994). Customer perception is a process of sensing, selection, interpretation of stimuli from physical world to
mental world of a person.
Perceived product quality in terms of online shopping can be explained as a situation when customers have no
intrinsic attributes for products to develop opinion about product quality in pre-purchase shopping stage (i.e.
customers not having previous experience with the product). Online retail only provides visual showcasing of
product categories. This lack of demonstration, further promotes lower level of tangibility perception among
the customers.
Perceived risk is seen as customer’s perception of uncertainty, fear and consequence of using a product or
service. The three risks associated with online shopping are privacy, financial and performance. Broydrick (1998)
claims that eliminating risk is one of the ways to enhance perceived consume value. For e.g. in online retail,
word of mouth is crucial source to reduce risk perception as its independent nature shows true features of a
product (Bansal & Voyer, 2000). Fornell (2001) found that perceived risk, perceived quality and price not only
effect perceived consumer value but also influence consumer switching behavior by controlling satisfaction
levels. He claimed that consumer value is positively related to customer satisfaction. High consumer value
heightens customer loyalty, reduces consumer service failure sensitivity, enhances brand name and prevents
customer churn or exit. A few key observations can be drawn from the above mentioned literature. Firstly, if
consumers are to give up traditional retail stores, they must be offered value added features and benefits which
are not available in conventional marketplace. It would offer them additional customer value. Secondly, as both
shopping and product value make consumer value, both online store operation effects as well as product effects
affect online shopping behavior. Thirdly optimum consumer value not only provokes online shopping behavior
but also reduces customer exit.

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(c) Online consumer trust and loyalty:
Creating loyalty among online customers or retention of existing consumers has become a necessity for e-
retailers. In order to attract new customers, online retailers incur at least 20-40% more than it costs serving
them in traditional market space (Reichheld and Schefter, 2000). To reduce these costs and earn profit, online
retailers must push customer loyalty which would mean convincing consumers to return to their websites to
purchase again and again. For e.g. in the e-book selling platform, it takes about a year of repeated purchases to
cover the initial cost of attracting the customer. For grocery and apparel categories, the figure is also a year. But
it electronics the average is about four years to break even. Given these timeframes, pushing for more customer
loyalty becomes an economic necessity (Zhu. Z., 2004).
As a behavioral notion, consumer loyalty is defined as consumer intentions to do more business with seller and
recommend him to other consumers (Zeithaml et al., 1996). (Heskett et al, 1994) suggested that one of the ways
to increase consumer loyalty is by offering superior e-service quality. As quality is something consumers typically
demand and value, by offering high quality service they would be willing to return and do more business with
the e-retailer. On the other hand, consumers experiencing low service value are more inclined to defect, switch
or exit to other retailers (Reichheld and Schefter 2000).
Customer loyalty increases revenue and growth in many ways. Firstly by increasing customer loyalty by 5 per
cent, revenues can increase from 30 to 85 per cent (Chow and Reed, 1997; Heskett et al. 1994). Considering the
type of industry, the revenue is even higher for online retailing industry (Reichheld and Schefter, 2000). Secondly
consumers are willing to pay a higher price and also stand a better chance for “service recovery”. They are also
easier to satisfy as retailer knows their expectations (Heskett et al. 1994; Reichheld and Sasser 1990; Zeithaml
et al. 1996). The success stories of many online retailers can be linked to their high inclination to customer
loyalty. For example, Amazon.com’s success is highly linked to customer loyalty as 66 per cent of their purchases
are made by returning consumers (The Economist, 2000). Loyal customers also reduce advertising and

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marketing expenses, as they speak about their experiences to other consumers which acts as word of mouth.
For example, EBay highly capitalized on this aspect by attracting consumers through a similar referral system.
Another key antecedent of consumer loyalty is degree of trust which consumers have in the retailer (Reichheld
and Schefter, 2000). Trust can be defined as willingness to make oneself susceptible towards actions taken by
trusted party upon feelings of assurance and confidence (Gefen, 2000). Trust is of imperative importance when
it is nearly impossible to fully regulate business agreement or when it is necessary to depend on third party on
not to take unfair advantage or engage in opportunistic behavior (Young, 2001).
Consumer trust on online retailer is significant because there is minimum guarantee on online platform that the
retailer with refrain from opportunistic, undesirable, unethical behaviors, such as distribution of personal data,
unfair pricing, purchase activity without permission, inaccurate information presentation and unauthorized use
of payment methods (Kollock, 2002). Given these risks, consumers who do not trust the retailer would be least
inclined to do business or return for repeated purchases (Jarvenpaa and Tractinsky, 1999). Therefore trust can
be considered as compelling and imperative constituent of a long term business interaction. One of ways to
build trust is through process of transference, by which consumers start trusting “unknown others” only because
“unknown others” are trusted by individuals they trust (Doney and Cannon, 1997).
Trust is also a major precedent for consumers who are willing to do business with e-commerce marketplace
vendor (Jarvenpaa and Tractinsky, 1999). Consumer trust becomes important on online retailing platforms
because of the reason that the “invisible” seller provides little guarantee that on online environment he/she
would refrain from opportunistic, undesirable and unethical behaviors. There is always scope for presentation
of wrong information, unfair prices, distribution of personal data, unauthorized use of debit and credit cards
and monitor purchase activities (Naquin, 2003).
Given these perceived risks, a segment of population who do not accept and trust online platforms would be
less inclined to shop online or even return back for re-shopping.

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Trust plays a central role in major repeated buying decision because of two possible reasons. The first being that
it is a method to reduce social complexity (Gefen, 2000), and secondly reduction in risk of doing business with
the seller (Jarvenpaa and Tractinsky, 1999). As a mechanism for social complexity reduction, trust ensures
overpowering social complexities are reduced on interaction with other people. (Luhmann, 1979) tells us that
trust is important because individuals are motivated to understand the social environment they live in and how
their behavior is perceived by others and actions they take.
Based upon above literature we can conclude that trust plays a central role in increasing long term loyalty. Not
only it serves as a social complexity reduction tool, but also reduces perceived risk of doing business with the
online retailer.
As previously mentioned, internet also links up offline and online retail space. Many consumers like to compare
products over the internet and then make the purchase on physical retail stores. This in a way also invokes
customer exit behavior. Nearly all the product categories have also been used in study of consumer switching
behavior. It is due to low level of trust and loyalty, that consumers merely “use” online retailer’s platform to
make better purchase decision (Mayer, 2003).
“High touch” product categories like health & grooming, clothing, consumer electronics were bought more in
traditional physical stores whereas “low touch” categories like software, books, and airline tickets were favored
by online services as they required quick delivery (Levin & Heath, 2003).
There also have been studies investigating consumer switching behavior in relation to online loyalty using
combination of three channels (internet, brick and mortar and catalogs) for both shopping and information. It
was found that compared to customers who buy through single platform, multi-channel shoppers have greater
trust, lower perception for risk and deeper relationship with retailer which further motivates them to spend
more with retailer (Kumar & Venkatesan’s, 2005).

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Figure 2.5: Framework of Online trust for e-commerce platform Source (Gefen,2000)
Figure 2.5 shows a framework developed by Gefen (2000) for online trust for e-commerce platform. It revolves
around three key variables of reputation, habit and satisfaction which build online trust. The reputation
variables includes parameters of membership, recommendation and repurchase intention. The habit variable
incorporates consistency of website and product and delivery speed. The satisfaction comprises of quality and
price.
With presentation of above literature we can conclude that consumer satisfaction significantly contributes to
online loyalty. It also adds up to retailer’s revenue as loyal consumers recommend the retailer to other
customers by word of mouth which also reduces marketing expenses. Habit, satisfaction and reputation are key
determinants of online trust and loyalty.
Online
trust
Reputation
Satisfaction
Habit
Consistency of website
Product delivery &
speed
Price
Membership
Recommendation to
others
Repurchase intention
Quality

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2.5. Customer switching behavior:
Business organizations globally, in dynamic changing marketplace are becoming increasingly consumer-
oriented, realizing gravity of keeping consumers in long term relation and seeking their loyalty. Online retailing
has not been much different. And though consumer retention is critical, it is equally necessary to examine and
explore factors which can cause consumers to switch or exit from their services. It is simply because in order to
“preserve” consumers, it is crucial for companies to understand why they switch (Colgate, 2001).
The era of offline and online retailing is marked with a number of events which have restructured the industry
over the years. Among these are arrival of new concepts such as superstore, discount store and new technology
like Point-of-Sale (POS terminals) (Rauh & Shafton, 2001). Therefore today both online and offline retailing is
predominantly about choices; a “needy” consumer has a choice of shopping channels of catalogs, traditional
stores and the internet. And even in their individual categories, there is large number of choices due to fierce
competition.
By attracting customers via marketing methods like promotions and discounts across numerous channels, online
retailers generate more sales and gain more revenue per customer than they would from different channels
different customer approach (Hoover, 2001). Various online retailing platforms created on multi-dimensions,
influence buying decisions and channel preference by a variety of factors (Hyde, 2003). The past research
suggests that customers have been choosing those channels which they perceive as most effective, efficient and
satisfactory (Kim & Kang, 1997).
Customer switching behavior is described as customer exit or defection (Hirschman, 1970; Stewart, 1994).
According to Bolton and Bronkhurst (2001) consumer switching behavior shows the decision which a consumer
makes to stop using a particular product or service or patronizing the firm’s services completely. Reichheld
(1996) and Keaveney & Parthasarathy (2001) researched and found that consumer switching behavior reduces
company’s profits and earnings.

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Added dividends are also lost because start up investment on customer (e.g. advertising, promotion costs) are
wasted and additional costs add up to obtain a new customer (Colgate, Steward & Kinsella, 1996; Fornell &
Wernerfelt, 1987). As per Reichheld & Sasser’s (1990) study, consumer exit is seen having a larger influence to
impact unit costs, revenue, market share and factors affecting competitive advantage. Consumer switching
brings negative word of mouth marketing which can downslide online retailer’s brand and reputation (Diane,
2003).
The value which consumers seek the most is usually composed of four resources; space, money, effort and time
(Seth & Sisodia, 1997). The time has evolved in business context where a single marketing strategy was effective
for all target segments as consumers expect tailor-made strategies as per their needs (Pitta, 1995). In the
current scenario, it is critical for e-retailers to know who their consumers are and why they are choosing one
channel or one e-retailer over another. (Crawford, 2005) says that ambiguity is that it is relatively easy for online
retailers to know their customers compared to brick and mortar outlets.
We can therefore conclude from above literature that customers now drive the entire marketing process and
demand more customized or tailor made services from the retailer. We can also claim that customer would be
willing to switch retailers as well as channels upon their attitude and belief towards each retailers, as well as
social norms and perceived behavioral control.
A model was created by (Keaveney, 1995) which mentioned eight incidents which lead to consumer switching
behavior. These are attraction by competitors, inconvenience, failure of core-services, pricing, ethical issues,
failure of service encounters, involuntary switching and employee reaction towards service failure.

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These incidents can further be defined as:
 Attraction by competitors: This category mentions customers who switch due to “negative” experience from an
online retailer to a “positive” e-retailer. Negative experiences can be defined as situations which drive a
consumer away from one retailer to another e.g. if a customer shops from a retailer who promises One Day
Delivery and if the package is delayed, the experience becomes negative (Diane, 2003).
 Inconvenience: It means aspects of location, operating hours and waiting time involved in transaction or delivery
which causes customer to feel inconvenience. Customers may feel that they have to spend considerable effort
and time.
 Failure of core-services: This section discusses service mistakes such as wrong order, billing errors etc.
 Pricing: This category mentions increase in price, high prices, unfair and deceptive pricing.
 Ethical Issues: This category mentions unsafe warehouses, dishonest behavior and conflict of interest.
 Failure of service encounters: This category has the attributes of impolite, uncaring and unknowledge staff.
 Involuntary switching: This category discusses the reason of switching as change of location for consumer or
retailer or maybe merger or alliance of the retailer.
 Employee reaction to service failure: This category describes level of employee reaction to service failure or
negative response.
Dahui and Glenn (2007) further developed on Keaveney’s switching model and produced factors leading to
customer switching behavior on online platform (Table 2.0). In their research they were able to specifically
converge the exit behavior for online platform. Thus their study is optimum for this research analysis.

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CUSTOMER
SWITCHING
BEHAVIOR
FACTORS EXAMPLE OF FACTORS
 Pricing
 High prices
 Rapid increasing prices
 Unfair pricing
 Deceptive pricing
 Inconvenience
 Location/Time
 Wait time for complaints
 Wait time for service
 Core service failure
 Service errors
 Billing errors
 Service catastrophe
 Service encounter
failure
 Uncaring
 Impolite
 Unresponsive
 Unknowledgeable
 Response to service
failure
 Negative response
 No response
 Reluctant response
 Competition
 Found better service
 Ethical issues
 Cheat
 Hard sell
 Unsafe
 Conflict of interest
 Involuntary
switching
 Customer migration
 Service provider closes
Table 2.0 : Factors leading to customer switching for online platform (Dahui and Glenn, 2007)
Consumer switching or channel switching can further lead to conflict among channels as customers can get
service or information from another channel (e.g. physical store) and conduct business with another e-retailer
(e.g. online store). It is an opportunity cost faced by today’s retailers (Moore, 1996).

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Internet provides services for products with prevalent search characteristics, low buying frequency and rapidly
changing technology; whereas cross channel customer retention is more vivid for items which are bought
infrequently (Baal & Dach’s, 2005). Their research showcases that product features did influence consumers
who would seek information and knowledge online but conducted their business offline.
It therefore confirms that at any stage of shopping process, customers will choose the retailer or the channel as
per its relevance to reach the satisfaction or goal they pursue while shopping. And if two retailers or channels
are similar and provide same utility or service, consumers tend to switch easily.
Adding to this, (Bala & Mahajan, 2005) said that customer’s usage of a channel or channels in the shopping
experience should be examined either as final outcome (i.e. purchasing product or information browsing) or the
process of using the channel, as various channels provide different opportunities to the customers. Most of the
times the final outcome was attaining the economic goals the consumers desired. (Bendoly & Venkataramanan,
2005) too investigated consumer switching behavior and found out that more anticipation of integration among
company’s various channels eventually lead to customer loyalty. However if customers find that certain
products would take longer to deliver (out of stock or delayed shipping), alternate competitors or channels
appear appealing to them in present as well as long run. Online shoppers tend to have different value for
different product category, with customers being less interested in using multiple retailers when buying
frequently purchases items, e.g. grocery items. Most customers appreciate the option of buying products online,
getting it delivered and being able to return the items back to the retailer via mail (Burke’s, 2002). The consumer
switching behavior can also be explained with various shopping orientations like credibility of product
information and demographics (age, gender, location) which are also different for both offline and online
platforms. Interestingly multi-channel offline shoppers consider use of internet and family/ friends reference as
critical purchasing decision compared to online shoppers (Choi & Park, 2006). Demographics such as gender,
age, income, family composition etc have major impact on customer perception of online and physical shopping
benefits.

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(Gupta & Walter, 2004) linked the theory of utility maximization with consumer switching behavior stating that
utility derived from e-commerce needs to be greater than utility provided from traditional physical stores in
order to influence consumer to switch to online platforms. The study also showed that risks (payment option,
invisible seller) had negative influence on switching behavior, wide variety (products, prices and information)
had positive influence and effort (evaluation, comparison) did not seem to have major influence on customer’s
intentions to switch to online retailers.
We can therefore summarize that “having consumers, not merely acquiring consumers” determine long run
productivity, profits and image of a firm. In terms of consumers, relationship management, service quality and
overall satisfaction can improve consumer intentions to stay with the retailer. Though a new and growing
concept, E-commerce has to yet to achieve delightful and stimulating benefits related to shopping experience.
2.6. Switching costs and switching behavior:
A consumer’s loyalty is determined not only by costs arising from dealing with the retailer, but also those costs
from switching to other retailer (Lee and Cunningham, 2001). Fornell (1992) added that consumer loyalty is
created by both consumer satisfaction as well as switching costs.
Dick and Basu (1994) however described switching costs in terms of monetary, time and psychological costs.
They could also include perceived risk which can be explained as consumer’s perceptions of adverse
consequences and uncertainty in buying a service or a product. On the other hand, Fornell (1992) summarized
switching costs into learning costs, emotional costs, search costs, loyal consumer discounts and transaction
costs.
Porter (1980) implied that switching costs are only incurred “onetime” in comparison to ongoing costs which
grow once the products and services are purchased repeatedly due to long term relationship. It can also be
defined as onetime cost which consumers associate to switch from one retailer to another. Though switching
costs are associated with switching process, it does not need to be incurred immediately on switching.

Consumer switching behavior among online retailers in India

Consumer switching behavior among online retailers in India

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