This article was downloaded by: [University of Liverpool]On: 06 October 2014, At: 01:42Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Internet CommercePublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/wico20

Innovativeness/Novelty-Seeking Behavioras Determinants of Online ShoppingBehavior Among Indian YouthArpita Khare a , Shveta Singh b & Anshuman Khare ca LDC Institute of Technical Studies , Allahabad, Indiab Indian Institute of Technology Delhi , Delhi, Indiac Faculty of Business , Athabasca University , St. Albert, Alberta,CanadaPublished online: 20 Nov 2010.

To cite this article: Arpita Khare , Shveta Singh & Anshuman Khare (2010) Innovativeness/Novelty-Seeking Behavior as Determinants of Online Shopping Behavior Among Indian Youth, Journal ofInternet Commerce, 9:3-4, 164-185, DOI: 10.1080/15332861.2010.529054

To link to this article: http://dx.doi.org/10.1080/15332861.2010.529054

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Innovativeness/Novelty-Seeking Behavioras Determinants of Online Shopping

Behavior Among Indian Youth

ARPITA KHARELDC Institute of Technical Studies, Allahabad, India

SHVETA SINGHIndian Institute of Technology Delhi, Delhi, India

ANSHUMAN KHAREFaculty of Business, Athabasca University, St. Albert, Alberta, Canada

The purpose of this research is to examine the relationship betweeninnovativeness=novelty-seeking behavior of Indian youth and theironline shopping behavior. Three hundred students studying inuniversities in the northern region of India between the ages of18 and 24 years participated in the survey. The research findingsshow a positive relationship between innovativeness=novelty-seeking behavior and online shopping behavior. The article con-cludes that Indian youth are interested in online shopping Websites because these Web sites provide the latest information aboutproducts and services. Their online shopping is influenced byWeb site attributes such as convenience and flexibility. The sur-veyed population felt comfortable purchasing with cash becauseonline transactions are considered insecure. The article concludeswith some suggestions that companies can incorporate to success-fully attract Indian youth to their Web sites for shopping.

KEYWORDS convenience, Indian youth, information avail-ability, novelty-seeking behavior, online shopping behavior

Address correspondence to Dr. Arpita Khare, Associate Professor, LDCITS, Allahabad,India. E-mail: khare.arpita@gmail.com

Journal of Internet Commerce, 9:164–185, 2010Copyright # Taylor & Francis Group, LLCISSN: 1533-2861 print=1553-287X onlineDOI: 10.1080/15332861.2010.529054

164

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

INTRODUCTION

The information and communication technology era has spurred increaseduse of technology in business. Information communication technology(ICT) has grown from being a ‘‘concentrated’’ technology to a ‘‘mass’’ or‘‘social’’ technology used for marketing (Adams and Ghose 2003). Moreand more people around the world browse the Internet to get informationabout products and services. However, recent research indicates thatthere is limited use of the Internet for shopping (Moe and Fader 2004;Soopramanien and Robertson 2007).

According to a survey conducted by Nielsen, Indian netizens are thethird largest credit card users for online shopping next to only Turkey andIreland (Achille 2008; Express India 2008). Among online shoppers, thehighest percentage comes from South Korea (99%), followed by the UnitedKingdom (97%), Germany (97%), Japan (97%), and the United States (94%).Internet use in Asia between 2000 and 2009 has increased more than 5 timesand accounts for 42.2 percent of users. India stands fourth globally, with 4.9percent being Internet users as compared to China, which has 20.8 percent.The United States has 13.1 percent users, followed by Japan at 5.5 percent(Internet World Statistics 2009).

Growth in Internet accessibility has increased its adoption for brows-ing and shopping among Indians. However, with a population of over abillion, the number of Internet users is still quite small. It is to be notedthat among 71 million users, only 52 million are active users. Indian youthcontinue to drive the surge of Internet usage and comprise a large sectionof total users. Among youths, the Internet is primarily used for searchinggeneral information and browsing entertainment Web sites (Ganguly2009). Internet World Statistics (2008) stated that India had a 7 percentpersonal computer penetration rate in 2008. The increase in the numberof a net-savvy population of around 81 million has spurred the growthof online retail in India (Chahal and Kohli 2009). Indian retail is projectedto touch $607 billion in 2010, and the growth in middle-class incomelevels will keep the sector growing at the rate of 10 percent over next5 years (Mishra 2009).

Mahmood, Bagchi, and Ford (2004), in their research on onlineshopping in different countries, suggested that trust and economic con-ditions have positive and significant impact on consumers’ online shop-ping behavior. The researchers tried to understand the influence ofnovelty-seeking behavior in determining online purchase tendenciesamong Indian youth. Since consumer shopping behavior is governedby personality traits, its impact on choosing the online medium as a retailoption cannot be ignored. India, one of the fastest growing, emergingeconomies with a large youth population, presents a promising marketfor online retail.

Online Shopping Behavior Among Indian Youth 165

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

LITERATURE REVIEW

Online Shopping Behavior

Turley and Milliman (2000) stated that shopping environments affect con-sumer shopping behavior, as they derive utility from searching for productsin different store environments (Bloch, Sherrell, and Ridgway 1986). Haubland Trifts (2000, 5) defined online shopping behavior ‘‘as a shopping activityperformed by a consumer via computer-based interface, where the consu-mer’s computer is connected to, and can interact with, a retailer’s digitalstorefront.’’ Online shopping behavior is based upon appearance of Websites, quality of images and pictures, and video clippings, not on actualproduct experiences (Lohse and Spiller 1998; Park and Kim 2003). Researchhas examined the role of different factors on individuals’ e-commerce adop-tion, such as geography and store accessibility (Farag et al. 2006), perceivedrisk and online shopping benefits (Pires, Stanton, Eckford 2004), typology ofonline stores (Moe 2003), enjoyment and trust in Web sites (Grewal,Lindsey-Mullikin, and Munger 2004; Gefen 2004; Lee, Cheung, and Chen2005; Ha and Stoel 2009), gender differences in online shopping (Dittmar,Long, and Meek 2004; Sanchez-Franco 2006; Hasan 2010), attitudes towardonline shopping (Dittmar et al.; Ahn, Ryu, and Han 2007; Lin 2007; Hasan),and impact of consumers’ socio-economic conditions (Sorce, Perotti, andWidrick 2005; Farag et al.).

Increased Internet penetration has affected consumers’ preferences forusing it for browsing and surfing (Soopramanien and Robertson 2007) andsearching for new product information (Moe and Fader 2004). Alba andcolleagues (1997) suggested that consumer shopping behavior in onlineinterfaces differs from the traditional retail environment. The online shop-ping environments motivate consumers to look for products that enhancethe utilitarian and hedonic aspects of shopping (Menon and Kahn 2002;Dabholkar and Bagozzi 2002; Monsuwe, Dellaert, and de Ruyter 2004; Bauer,Falk, and Hammerschmidt 2006; Ha and Stoel 2009).

Hirschman and Holbrook (1982) described shopping motives as enter-tainment seeking or utilitarian in nature. The utilitarian shopping behaviorhas been defined as task related and rational (Batra and Ahtola 1991) andfocuses on the accomplishment of a particular consumption need (Babin,Darden, and Griffen 1994). Much shopping behavior is focused toward get-ting emotional stimulation while exploring for products (Sherry, McGrath,and Levy 1993; Babin et al.). To encourage consumers to shop online entailsretail Web sites combining utilitarian and hedonic values. Online retailingpresents shoppers with an interactive environment that combines bothhedonic and utilitarian shopping motives (Childers et al. 2001; Shang,Chen, and Shen 2005; Bauer et al. 2006). Childers and colleagues posited thatconvenience, navigability, and interactivity of Web sites are predictors to

166 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

consumer online shopping attitudes. The sensual and emotional aspect ofshopping should not be ignored (Batra and Ahtola). Liu and colleagues(2008), in their research on Chinese consumers’ online shopping behavior,suggested factors like information quality, Web site design, merchandiseattributes, transaction capability, security=privacy, payment, delivery, andcustomer service as predictors to online shopping.

The reasons for using the Internet for shopping are triggered by diverseattitudes and motivations. Consumers seek value, temporal benefits,flexibility, and possibility of exploring products in online environments (Sorceet al. 2005). Korgaonkar and Wolin (1999), in their research on onlineshopping motivation, stated that consumers look for transaction securityand privacy, information availability, interactivity, escapism, socialization,non-transactional privacy, and economic motivation. Consumers search forconvenience in online transactions (Bhatnagar, Misra, and Rao 2000) as it givesthem flexibility to browse Web sites at their leisure (Alreck and Settle 2002).

The technology adoption model (TAM) suggests that technology usedepends on factors like enjoyment, ease of use, usefulness, and navigability(Davis, Bagozzi, and Warshaw 1989). For enhancing the perceived useful-ness of online media, the instrumental and entertainment aspects of shop-ping should be combined (Chiders et al. 2001; Wang, Pallister, and Foxall2006). Hedonic motivations have become increasingly important in attractingconsumers to visit the stores or retail Web sites (To, Liao, and Lin 2007).Consumers seek sensual stimulation while shopping in both online andoffline environments (Falk 1997; Shang et al. 2005; Bauer et al. 2006; Toet al.; Ha and Stoel 2009). Overby and Lee (2006), in their research on con-sumer preferences for online retailers, suggested that consumers give morepreference to the utilitarian components of retail Web sites. The utilitarianaspects in online shopping enable consumers to examine different productsand their prices and service components (Jarvenpaa and Todd 1997;Vijaysarathy and Jones 2000; Mathwick, Malhotra, and Rigdon 2001; Teo2001). Fiore, Kee, and Kunz (2003) posited that online shopping formatsappeal to consumers because of the fun, enjoyment, and engaging attributesthat which make shopping pleasurable.

Consumer Innovativeness and Novelty-Seeking Behavior

Consumer predisposition to try new products, services, and ideas is depen-dent upon their variety-seeking behavioral trait. Venkatraman and Price(1990) stated that consumer innovativeness or novelty-seeking behavior isa predisposition to look for new products and services. It relates to the desirefor new experiences (Venkatraman 1991) and trying new products. This isaffected by consumer demographic and psychographic profiles (Kim et al.2010) as it helps them express themselves. Midgley and Dowling (1978)postulated that there are three types of consumer innovativeness: specific

Online Shopping Behavior Among Indian Youth 167

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

innovativeness for a single product, specific innovativeness for a single cate-gory of products, and innate innovativeness that stretches across multipleproduct categories. Most researchers are of the view that consumer innova-tiveness or novelty-seeking behavior is a personality trait and differs acrossindividuals (Midgley and Dowling; Rogers 1983; Agarwal et al. 1998; Citrinet al. 2000; Crespo and del Bosque 2008). Hirschman (1980) links the innova-tiveness to consumer creativity and novelty-seeking experiences. There is adirect relationship between consumer innovativeness and new productadoption (Foxhall and Haskins 1986; Mudd 1990; Venkatraman and Price;Chau and Hui 1998; Bearden, Hardesty, and Rose 2001), and a similar trendcan be hypothesized regarding consumers’ adoption of new technologies.Hirunyawipada and Paswan (2006), in their research on role of consumerinnovativeness and adoption of high-technology products, found that cogni-tive and domain-specific innovativeness affects product adoption. Theyclassified innovativeness into three levels—global innovativeness, domain-specific innovativeness, and innovative behavior. Global innovativeness is apersonality trait (Leavitt and Walton 1975; Midgley and Dowling; Goldsmith,Freiden, and Eastman 1995) and is defined by traits like openness andnovelty- and variety-seeking behavior (Leavitt and Walton; Midgleyand Dowling; Hirschman; Manning, Bearden, and Madden 1995; Menonand Kahn 1995; Goldsmith et al.). Domain-specific innovativeness is a con-sumer tendency to try out new products and services (Goldsmithand Hofacker 1991; Goldsmith et al.) and varies across product categories(Roehrich 2004). Consumers differ in the adoption rate of new productsand technologies; some are early adopters, whereas others are laggards(Midgley and Dowling; Rogers). Manning and colleagues stated that consu-mers first must be aware of the product and then only can adopt it. Theyclassified novelty-seeking behavior as a trait to adopt new products and ser-vices. Hirschman suggested that an individuals’ novelty-seeking behavioraffects his or her behavior of seeking new information about products andplays a role in initial product adoption. Novelty-seeking consumers searchfor information about new product launches through various media andretail outlets (Manning et al.). Consumer innovativeness or novelty-seekingbehavior is linked with the enjoyment that a consumer gets from tryingnew products and services (Engelland, Hopkins, and Larson 2001).

Wang and colleagues (2006) conducted research to understand howinvolvement=innovativeness and cognitive styles affects consumers’ brandloyalty and Web site behavior. They discovered that consumer involvementand cognitive styles interact to influence decision making. Consumer innova-tiveness is an important determinant of online purchasing behavior (Foxhall1995; Alba et al. 1997; Citrin et al. 2000; Limayem, Khalifa, and Frini 2000;Goldsmith 2002; Alpert et al. 2003; Lassar, Manolis, and Lassar 2005). Con-sumer innovativeness and cognitive styles affect adoption of online shopping(Foxhall). Bigne-Alcaniz and colleagues (2008) examined the role of

168 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

information dependency and innovativeness on online shopping. Theysuggested that online shopping information has a positive and direct impacton consumer intentions. They concluded that consumer innovativenessaffects Internet exposure, while ease of use influences shopping decisions.The involved consumers were more willing to purchase online.

The research objectives of this research were as follows:

R1: To identify whether consumer novelty-seeking behavior has a posi-tive relationship with the online shopping behavior of Indian youth.

R2: To identify whether consumers’ novelty-seeking behavior influencesonline purchasing.

R3: To identify whether willingness of Indian youth to shop online isdependent upon online shopping behavior.

Significance of this Research

The general research objective was to study the relationship betweennovelty-seeking=innovativeness and online shopping behavior among Indianyouth. Vij (2007) stated that the younger generation constitutes an attractivesegment for online retail, as they spend more time browsing the Internet(Reimer 2006; Vij). Research published by Gupta, Handa, and Gupta (2008)regarding online shopping by Indian youth found that consumers do not trustWeb sites for shopping. Indian consumers are reluctant to purchase expens-ive products online, and their online behavior is restricted to browsing.

Research suggests that Internet usage is increasing in developing coun-tries and that the younger population is addicted to the Internet. As statedearlier, India stands fourth after China, Japan, and the United States in Inter-net use. Therefore, understanding Indian youth’s online shopping behaviorcan be of considerable importance to companies trying to sell their productsand services through online retail models. Consumer innovativeness=novelty-seeking behavior is a personality trait (Manning et al. 1995) and playsa significant role in encouraging consumers to use new technologies forreceiving service and buying products. In India, the younger generation ismore enamored by new mobile gadgets, Web-enabled mobile phones, Inter-net, and high-tech products (Internet and Mobile Association of India [IAMAI]2006). They present an interesting segment for online sellers, as they areaccustomed to using Internet for accessing information.

RESEARCH METHODOLOGY

The research instrument for assessing Indian youth’s novelty-seeking beha-vior and its implication on online shopping was comprised of 20 constructs.The first section of the questionnaire was comprised of eight constructsadapted from Manning and colleagues’s (1995) consumer innovativeness=

Online Shopping Behavior Among Indian Youth 169

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

novelty-seeking behavior scale. The second section of the instrument con-tained 12 constructs adapted from the online shopping scale developed bySorce et al. (2005). Over 300 graduate and postgraduate students from Indianuniversities participated in the survey. The students were from different partsof the country and were studying in the universities after gained admissionthrough a national entrance examination. This provided a diverse sampleof Indian youth belonging to different regions and states. The age of thestudents ranged between 18 and 24 years.

The students were asked to fill out a structured questionnaire by indicat-ing their agreement on a 5-point Likert-type scale (1¼ strongly agree,5¼ strongly disagree). As most Indians are conversant in English, the ques-tionnaire was administered in English. Out of 300 filled questionnaires, 259completed questionnaires were able to be used.

The reliability test was run on the scale items to understand whetherthe scale could be used for further research purposes. Cronbach’s (1951)coefficient alpha measures the extent to which the scale items cohere witheach other. The reliability of the items were ascertained by computingthe Cronbach alpha, and the score for 20 constructs was 0.874. Cronbach’salpha value for the 8 novelty-seeking constructs was 0.825; for the 12 onlineshopping constructs, it was 0.866.

FINDINGS AND DISCUSSION

The total sample size of 259 included 210 male and 49 female respondents.The low number of female respondents is because fewer female students arestudying in post-graduate and graduate courses in India.

A correlation test was conducted to understand the impact ofnovelty-seeking behavioral attributes on online shopping attitude. Theresults (table 1) show that there exists a positive correlation between theonline shopping attitude constructs with the novelty-seeking behavior ofIndian youth.

The first dimension for novelty-seeking behavior, ‘‘I often seek outinformation about new products and services,’’ shows a low correlation withthe online shopping behavior dimensions of ‘‘I can shop online for productsthat are not available or are hard to find offline’’ (r¼ 0.106, p¼ .087; insignifi-cant at the .05 level), ‘‘it is easier to compare shop online’’ (r¼ 0.121,p¼ .052; insignificant at the .05 level), and ‘‘I like to shop online because Ican do it any time of the day and night’’ (r¼ 0.121, p¼ .052). The resultsshow that novelty-seeking individuals like to examine the products. Hirsch-man (1980) posited that a novelty-seeking behavior trait affects the indivi-dual’s motive to look for new information. Consumers possessingnovelty-seeking traits may not prefer the convenience attribute of browsingthe Internet for information. They prefer to acquire information about new

170 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

TABLE1

Correlationbetw

eenNovelty-SeekingBehavioran

dOnlineSh

oppingBehaviorAttributes

Ioftenseek

outinfor-

mation

aboutnew

products

and

services

Iliketo

goto

placeswhereI

willbe

exposedto

inform

ation

aboutnew

productsan

dservices

Ilikemaga-

zinesan

dWeb

sitesthat

intro-

duce

new

products

Ifrequently

lookfornew

productsan

dservices

Iseekout

situationsin

whichIwillbe

exposedto

new

anddif-

ferentsources

ofinform

ation

Iam

continu-

ally

seeking

new

product

experiences

When

Igo

shopping,I

findmyself

spendingvery

little

time

checkingout

new

products

andservices

Itakead

van

tage

ofthefirstavail-

able

opportunity

tofindoutab

out

new

anddiffer-

entproducts

Ifindco

mmercial

Websites(e.g.,

man

ufactureror

retail)more

helpfulthan

inform

alch

atrooms

Pearson

correlation

.242��

.278��

.308

��.190

��.152�

.204��

.170��

.340��

Sig.(two-tailed)

.000

.000

.000

.002

.014

.001

.006

.000

Ipreferto

learn

aboutproductson

theWeban

dthen

buythem

using

thephoneorat

the

retailstore

Pearson

correlation

.186��

.180��

.231

��.320

��.201��

.098

–.009

.191��

Sig.(two-tailed)

.003

.004

.000

.000

.001

.115

.891

.002

When

Ishoponline,

Ilookforprice

inform

ation

Pearson

correlation

.158�

.234��

.216

��.204

��.177��

.013

–.045

.220��

Sig.(two-tailed)

.011

.000

.000

.001

.004

.831

.469

.000

When

Ishoponline,

Ilookforbrand

inform

ation

Pearson

correlation

.155�

.228��

.209

��.245

��.253��

.059

.052

.122�

Sig.(two-tailed)

.012

.000

.001

.000

.000

.347

.407

.050

When

Ishoponline,

Ilookfor

inform

ationab

out

dealers

that

carry

theproduct

Pearson

correlation

.164��

.219��

.232

��.220

��.237��

.154�

.033

.146�

Sig.(two-tailed)

.008

.000

.000

.000

.000

.013

.600

.019

Itiseasyto

shopfor

thingsonline

Pearson

correlation

.178��

.141�

.194

��.233

��.195��

.130�

.025

.116

Sig.(two-tailed)

.004

.023

.002

.000

.002

.037

.693

.061

(Continued

)

171

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

TABLE1

Continued

Ioftenseek

outinfor-

mation

aboutnew

products

and

services

Iliketo

goto

placeswhereI

willbe

exposedto

inform

ation

aboutnew

productsan

dservices

Ilikemaga-

zinesan

dWeb

sitesthat

intro-

duce

new

products

Ifrequently

lookfornew

productsan

dservices

Iseek

out

situationsin

whichIwillbe

exposedto

new

anddif-

ferentsources

ofinform

ation

Iam

continu-

ally

seek

ing

new

product

experiences

WhenIgo

shopping,I

findmyself

spendingvery

little

time

checkingout

new

products

andservices

Itakead

van

tage

ofthefirstavail-

able

opportunity

tofindoutab

out

new

anddiffer-

entproducts

Icanshopfor

productsonline

that

arenot

available

orare

hardto

findoffline

Pearson

correlation

.106

.149

�.170��

.218��

.169��

.063

.026

.175

��

Sig.(two-tailed)

.087

.017

.006

.000

.006

.315

.678

.005

Shoppingonline

savestime

Pearson

correlation

.130�

.084

.133�

.155�

.231��

.118

.013

.127

�

Sig.(two-tailed)

.037

.179

.032

.013

.000

.058

.834

.041

Itiseasierto

compareshop

online

Pearson

correlation

.121

.037

.087

.179��

.188��

.050

.061

.163

��

Sig.(two-tailed)

.052

.552

.161

.004

.002

.427

.332

.008

Shoppingonline

avoidsthehassle

ofgoingto

astore

Pearson

correlation

.155�

.115

.168��

.205��

.214��

.033

.002

.109

Sig.(two-tailed)

.012

.064

.007

.001

.001

.602

.972

.080

Iliketo

shoponline

because

Icandoit

anytimeoftheday

ornight

Pearson

correlation

.121

.171

��.200��

.264��

.288��

.181��

.138�

.280

��

Sig.(two-tailed)

.052

.006

.001

.000

.000

.003

.027

.000

Iwould

liketo

shop

online

Pearson

correlation

.132�

.161

��.232��

.269��

.273��

.165��

.118

.275

��

Sig.(two-tailed)

.034

.010

.000

.000

.000

.008

.058

.000

� Correlationissignifican

tat

the.05level(two-tailed);

��co

rrelationissignifican

tat

the.01level(two-tailed).

172

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

products and services by examining them at their leisure and making com-parisons offline. Consumer innovativeness as a trait enables consumers toembrace change and try new products more often and quickly than others(Venkatraman 1991; Engelland et al. 2001; Hirunyawipada and Paswan2006; Aldas-Manzano et al. 2009).

The second dimension of novelty-seeking behavior, ‘‘I like to go toplaces where I will be exposed to new products and services,’’ has a low cor-relation with the three dimensions of online shopping behavior ‘‘shoppingonline saves time’’ (r¼ 0.084, p¼ .179), ‘‘it is easier to compare shop online’’(r¼ 0.037, p¼ .552), and ‘‘shopping online avoids the hassle of going to thestore’’ (r¼ 0.115, p¼ .064). Consumers prefer to visit new stores and placesto seek new information. Online shopping does not give the consumersopportunities to visit new places or stores in pursuit of their interest to lookfor information. They consider exploring for products a pleasurable activityrather than a hassle. The results for the novelty-seeking behavior traits ofthe third, fourth, and fifth constructs show a positive correlation with all 12dimensions of online shopping behavior. The shopping Web sites are con-sidered important for acquiring new information. Indian youth use Web sitesfor browsing, looking for new information, and chatting (Sudhakar and Rao2003; Gupta et al. 2008). Innovativeness or novelty-seeking behavior is astimulation need and a desire to look different (Steenkamp, Hofstede, andWedel 1999).

For the novelty-seeking behavior dimension of ‘‘I am continually seek-ing new product experiences,’’ there was no correlation with the onlineshopping behavior dimensions of ‘‘I prefer to learn about products onthe Web and then buy them using the phone or at the retail store’’(r¼ 0.098), ‘‘when I shop online I look for price information’’ (r¼ 0.013),‘‘when I shop online I look for brand information’’ (r¼ 0.059), ‘‘I can shopfor products online that are not available or are hard to find offline’’(r¼ 0.063), ‘‘shopping online saves time’’ (r¼ 0.118), ‘‘it is easier to com-pare shop online’’ (r¼ 0.050), and ‘‘shopping online saves the hassle ofgoing to a store’’ (r¼ 0.033). For each of these dimensions, p> .05. Thisshows that online product information does not encourage novelty-seekingconsumers to visit Web sites for saving time and comparing prices andbrands. Since the pleasure of shopping lies in examining new products,the hedonic experience is lacking in online retail Web sites. This supportsearlier research that stated that consumers seek pleasure in shoppingexperiences (Menon and Kahn 2002; Dabholkar and Bagozzi 2002;Monsuwe et al. 2004; To et al. 2007) and shopping formats should appealto their intrinsic needs (Fiore et al. 2003). If the shopping Web sites lack theentertainment element, the consumer is not encouraged to visit and shoponline.

The seventh dimension of novelty-seeking behavior, ‘‘when I go shop-ping, I find myself spending very little time checking out new products and

Online Shopping Behavior Among Indian Youth 173

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

services’’ showed low correlation with ‘‘I prefer to learn about products onthe Web and then buy them using the phone or the retail store’’ (r¼ 0.009,p¼ .891; insignificant at the .05 level), ‘‘when I shop online I look for priceinformation’’ (r¼ 0.045, p¼ .469), ‘‘when I shop online I look for brandinformation’’(r¼ 0.052, p¼ .407; insignificant at the .05 level), ‘‘when I shoponline, I look for information about dealers that carry the product’’(r¼ 0.033, p¼ .600; insignificant at the .05 level), ‘‘it is easy to shop forthings online’’ (r¼ 0.025, p¼ .693; insignificant at the .05 level), ‘‘I can shopfor products online that are not available or are hard to find offline’’(r¼ 0.026, p¼ .678), ‘‘shopping online saves time’’ (r¼ 0.013, p¼ .834;insignificant at the .05 level), ‘‘it is easy to compare shop online’’(r¼ 0.061, p¼ .332), ‘‘shopping online saves the hassle of going to a store’’(r¼ 0.002, p¼ .972; p is insignificant at the .05 level), and ‘‘I would like toshop online’’ (r¼ .118, p¼ .058; insignificant at the .05 level). The resultsshow that Indian youth did not consider online retail Web sites as sourcesof new information about products, brands, and their prices. Indian youthprefer to go to the stores and spend time looking for products. This may beunderstood with respect to the hedonic aspects of shopping behavior(Hirschman and Holbrook 1982; Babin et al. 1994; Menon and Kahn2002; Dabholkar and Bagozzi 2002).

The last dimension of novelty-seeking behavior, ‘‘I take advantage ofthe first available opportunity to find out about new and different products,’’showed low correlation with ‘‘it is easy to shop for things online’’ (r¼ 0.116,p¼ .061; insignificant at the .05 level) and ‘‘shopping online avoids the hassleof going to a store’’ (r¼ 0.109, p¼ .080; insignificant at the .05 level). They donot like the convenience offered by online retail. The dimensions that act asstimuli for exploring new aspects of online retailing, like flexibility and find-ing new information, showed a positive correlation with novelty-seekingbehavior. The new innovations attract the youth, as it enables them toexpress themselves as technology savvy. Most Indian youth feel confidentabout the Internet for accessing information and interacting with their friends(Berkowitz et al. 2000; Comegys and Brennan 2003; Gupta et al. 2008). This isin line with earlier research that states that Internet users perceive its utility insearching for information about a purchase (Hoffman and Novak 1996;Maignan and Lukas 1997; Moe and Fader 2004; Soopramanien and Robertson2007).

To understand the predictors of the online shopping behavior of Indianyouth, multiple regression tests were conducted with online shopping beha-vior dimensions (the 12 online shopping behavior variables were taken as 1construct) as a dependent variable for novelty-seeking behavior. Thenovelty-seeking traits are inherent characteristics of consumers and affecttheir motives to shop online.

The regression analysis results show that the novelty-seeking behaviordimensions motivated consumers to seek new information (table 2). The

174 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

findings support earlier research that states that Indian youth prefer tobrowse the Internet for information (Sudhakar and Rao 2003; IAMAI2006; Gupta et al. 2008), but very few preferred to shop online. Thenovelty-seeking dimensions of ‘‘I seek out situations in which I will beexposed to new and different sources of information’’ was significant at.01 levels and the p value was .001. The consumer innovativeness trait isanchored in personality inventory that determines behavior, specificallythe adoption of new products (Leavitt and Walton 1975) and Web sites thathelp consumers’ to acquire information. The adoption of new technologiesis driven by its utility in the consumers’ lifestyles. With reference to theadoption of the new innovations theory proposed by Rogers (1983), onlineshopping may be considered as enhancing the variety-seeking trait amongIndian youth. The construct related to searching for new information of thenovelty-seeking behavior was an important determinant of online shoppingbehavior. The novelty attribute of online shopping motivates consumers toexplore Web sites as source of new information. Indian youth does notconsider retail Web sites as convenient and easy for comparing informationabout products. In comparison to brick-and-mortar stores, retail Web sites

TABLE 2 Multiple Regression Analysis—Predictors to Online Shopping Behavior

Unstandardizedcoefficients

Standardizedcoefficients

t Sig.B SE Beta

Constant 18.028 1.691 10.659 .000I often seek out information about new

products and services0.051 0.565 0.007 0.090 .928

I like to go to places where I will beexposed to information about newproducts and services

0.046 0.625 0.006 0.074 .941

I like magazines and Web sites thatintroduce new products

0.440 0.658 0.055 0.668 .505

I frequently look for new products andservices

1.542 0.658 0.195 2.342 .020�

I seek out situations in which I will beexposed to new and differentsources of information

1.737 0.512 0.237 3.391 .001��

I am continually seeking new productexperiences

–0.782 0.519 –0.106 –1.508 .133

When I go shopping, I find myselfspending very little time checkingout new products and services

–0.351 0.408 –0.052 –0.860 .391

I take advantage of the first availableopportunity to find out about newand different products

0.949 0.516 0.124 1.839 .067

Note. Dependent variable is online shopping behavior.�Significant at the .05 level (two-tailed); ��significant at the .01 level (two-tailed).

Online Shopping Behavior Among Indian Youth 175

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

are not perceived as an alternative option. For most consumers, retail Websites are difficult to understand and navigate.

The other novelty-seeking behavior dimension that was a significantpredictor to online shopping was ‘‘I frequently look for new products andservices,’’ which had a p-value of .02 and is significant at .05 levels. Indianyouth consider Web sites to be important sources of information but not apotential medium for conducting transactions. This is in line with earlierresearch that showed young Indians use the Web for browsing rather thanfor actual transactions (Reimer 2006; Vij 2007; Gupta et al. 2008). The generalinnovativeness trait is related to openness and a search for new experiencesand is a significant predictor of shopping intention (Craig and Ginter 1975;Midgley and Dowling 1978; Joseph and Vyas 1984; Venkatraman 1991;Manning et al. 1995).

A second regression analysis was run to understand the predictors toshopping online. One dimension of the online shopping behavior was takenas a dependent variable to ascertain the role of online shopping behaviordimensions in predicting Indian youth’s reasons to shop online. The objec-tive was to understand the factors affecting choice of online shopping Websites and motives behind Indian youth’s reasons to shop online. These couldbe used by online retailers to improve their Web sites to attract youth to shoponline.

The results indicate that Indian youth’s preference to shop online wasgoverned by the flexibility, convenience, reducing wastage of time, and itsutility in helping them browse for information about stores (table 3). Thedimension ‘‘shopping online saves time’’ has a p-value of .019 (significantat the .01 level), ‘‘it is easier to compare shop online’’ has a p-value of is.016 (significant at the .01 level), ‘‘shopping online avoids the hassle of goingto the store’’ has a p-value of .040 (significant at the .05 level), and ‘‘I like toshop online because I can do it any time of the day or night’’ has a p-value of.000 (significant at the .01 level). Interactivity, information availability, flexi-bility, and convenience are major determinants of online shopping behavior.This is in tandem with research that states that online shopping behavioris based upon the appearance of the Web sites, quality of the images andpictures, and video clippings and not on actual product experiences (Daviset al. 1989; Jarvenpaa and Todd 1997; Lohse and Spiller 1998; Ho and Wu1999; Park and Kim 2003; Fiore and Jin 2003; Sorce et al. 2005; McKechnie,Winklhofer, and Ennew 2006; Bigne-Alcaniz et al. 2008). The research find-ings of this study are similar to the research of Bigne-Alcaniz and colleagues,which concluded that online shopping behavior is governed by consumers’perceptions about the usefulness of the information available on the shoppingWeb sites. If the Web sites cater to their needs, the consumers would bewilling to use it for shopping. The research shows a direct relationshipbetween consumer desire to get new information and Web site use. Theonline shopping Web sites are convenient if the consumer wants to save time.

176 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

MANAGERIAL IMPLICATIONS

Some of the conclusions that can be drawn from the analysis presented in theearlier sections are discussed here. Indian youth is more Internet savvy anduse the Internet in their social and professional interactions. The Internet isused in India mainly for browsing, chatting, and sending e-mails. Indianyouth perceive the Internet as a medium that gives them access to the latestinformation and enables them to satisfy their desire for ‘‘new’’ information.

The increased penetration of the Internet into major cities of India hasincreased its acceptability, and consumers are willing to use it as an alterna-tive purchasing channel. However, the Internet as a medium for online shop-ping has still to gain acceptance among the masses.

Indian youth consider online shopping Web sites to be sources of infor-mation for specific attributes, such as product features, pricing, retailer infor-mation, and store comparisons. The reason to use online shopping Web sitesis largely governed by convenience, flexibility, and temporal factors.

TABLE 3 Multiple Regression Analysis—Predictors to Indian Youth’s Preference to ShopOnline

Unstandardizedcoefficients

Standardizedcoefficients

t Sig.B SE Beta

Constant –0.282 0.197 –1.430 .154I find commercial Web sites (e.g.,

manufacturer or retail) more helpfulthan informal chat rooms

0.088 0.047 0.087 1.856 .065

I prefer to learn about products on theWeb and then buy them using thephone or at the retail store

0.099 0.054 0.097 1.840 .067

When I shop online, I look for priceinformation

0.079 0.066 0.071 1.187 .236

When I shop online, I look for brandinformation

–0.009 0.066 –0.009 –0.143 .887

When I shop online, I look forinformation about dealers that carrythe product

–0.031 0.059 –0.030 –0.524 .600

It is easy to shop for things online 0.111 0.069 0.099 1.625 .105I can shop for products online that are

not available or are hard to findoffline

–0.026 0.062 –0.023 –0.412 .681

Shopping online saves time 0.156 0.066 0.145 2.365 .019��

It is easier to comparison shop online 0.150 0.062 0.136 2.414 .016��

Shopping online avoids the hassle ofgoing to a store

0.135 0.065 0.120 2.068 .040�

I like to shop online because I can do itany time of the day or night

0.350 0.057 0.340 6.117 .000��

Note. Dependent variable is would like to shop online.�Significant at the .05 level (two-tailed); ��significant at the .01 level (two-tailed).

Online Shopping Behavior Among Indian Youth 177

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Use of the Internet for shopping is primarily done for inexpensive pro-ducts due to the perceived lower degree of risk associated with online trans-actions (Gupta et al. 2008). Indians feel more comfortable doing thetransaction through cash, because online transactions are considered to beinsecure. A majority of financial transactions in India are done with cash,and credit card use is still restricted to a small section of the society.

To encourage consumers to shop online, the interactivity aspects of theWeb site should be appealing. Some people are not comfortable with Inter-net use and are turned off by retail Web sites that appear complex and diffi-cult to navigate. The interactive nature of Web sites affects consumers’browsing and purchase behavior (Hartnett 2000; Fiore and Jin 2003; Joines,Scherer, and Scheufele 2003; Swinyard and Smith 2003; Fiore, Jin, and Kim2005). Interactive aspects of Web sites can be improved through toll-freenumbers (where consumers can call and get their queries resolved) or havinga FAQ section. Attractive images, easy to understand instructions, answers tofrequently asked questions, and a help menu on the Web sites can act aspositive inducement to consumers.

Credit card use would also increase if consumers felt confident that theWeb sites were secure for financial transactions. Security, network reliability,and perceived risk factors are vital in online transactions (Cockburn andWilson 1996; Liang and Huang 1998; Miyazaki and Fernandez 2001), andreducing these fears can improve consumers’ attitudes toward online shop-ping. Online Web sites should be designed to instill confidence in the mindsof consumers. There should be service support available through telephoneand e-mail to assure them.

To encourage online shopping, promotional programs can be under-taken by companies to convince consumers that an online medium issecure, and consumers can save money or get special deals by using it.Most people lack information about online shopping Web sites. The com-panies can adopt promotional strategies to inform consumers about theadvantages of using online shopping Web sites. Promotional offers in theform of discounts can be given to consumers who use Web sites for shop-ping. In India, most consumers prefer to order products through phones(as they are familiar with the retailers), and the Internet may prove to bea convenient new medium. The first stage for the adoption of online retail-ing would imply knowing the retailers and having confidence in purchas-ing through them.

FUTURE RESEARCH DIRECTIONS

This research was administered only on Indian youth, since it was felt thatthis section presents a promising segment of consumers for online retailers.These consumers are Internet savvy and willing to try new ideas. Being

178 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

brought up with technology and computers, they are likely to adopt them, asit reflects their lifestyle.

Research may also be conducted on young working Indians between 25and 40 years of age to understand their attitude toward online shopping. Thesample selected in the research was comprised of youth who studying and,consequently, are dependent upon their parents for financial assistance.Research can be conducted on working-class consumers; as they are finan-cially independent, their behavior may differ from the students.

Research could be also conducted to understand the kind of productsthat consumers are most willing to purchase online. This can be of immenseuse to marketers in designing their online strategies. Further research couldbe done to make a comparison between the attitudes of Indians residing inmetropolitan and non-metropolitan areas. This may prove interesting, asmetropolitan consumers in have access to a better technology infrastructureand network connectivity. This factor is an important external variable inmotivating consumers to use online retail stores.

REFERENCES

Achille, S. J. 2008. India ranks third biggest e-shopping nation online today. http://www.multilingual-search.com/india-ranks-third-biggest-e-shopping-nation-online-today/29/01/2008/ (accessed June 15, 2010).

Adams, P. C., and R. Ghose. 2003. India.com—the construction of a space between.Progress in Human Geography 27 (4): 414–437.

Agarwal, R., M. Ahuja, P. E. Carter, and M. Gans. 1998. Early and late adopters of ITinnovations: Extensions to innovation diffusion theory. Paper presented atthe Diffusion Interest Group in Information Technology (DIGIT) Conference,Helsinki.

Ahn, T., S. Ryu, and I. Han. 2007. The impact of Web quality and playfulness on useracceptance of online retailing. Information and Management 44:263–275.

Alba, J., J. Lynch, B. Weitz, C. Janiszewski, R. Lutz, A. Sawyer, and S. Wood. 1997.Interactive home shopping: Consumer, retailer, and manufacturer incentivesto participate in electronic marketplaces. Journal of Marketing 61 (July): 38–53.

Aldas-Manzano, J., C. Lassala-Navarre, C. Ruiz-Mafe, and S. Sanz-Blas. 2009. The roleof consumer innovativeness and perceived risk in online banking usage. Inter-national Journal of Bank Marketing 27 (1): 53–75.

Alpert, S. R., J. Karat, C.-M. Karat, C. Brodie, and J. G. Vergo. 2003. User attitudesregarding a user-adaptive e-commerce Web site. User Modeling andUser-Adapted Interaction 13 (4): 373–e96.

Alreck, P., and R. Settle. 2002. The hurried consumer: Time-saving perceptions ofInternet and catalogue shopping. Journal of Database Marketing 10 (1): 25–35.

Babin, B. J., W. R. Darden, and M. Griffen. 1994. Work and=or fun: Measuring hedonicand utilitarian shopping value. Journal of Consumer Research 20 (4): 644–656.

Batra, R., and O. T. Ahtola. 1991. Measuring the hedonic and utilitarian sources ofcustomer attitudes. Marketing Letters 12 (2): 159–170.

Online Shopping Behavior Among Indian Youth 179

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Bauer, H. H., T. Falk, and M. Hammerschmidt. 2006. e-TransQual: A transactionprocess-based approach for capturing service quality in online shopping. Jour-nal of Business Research 59 (7): 866–875.

Bearden, W. O., D. M. Hardesty, and R. L. Rose. 2001. Consumer self-confidence:Refinements in conceptualizations and measurements. Journal of ConsumerResearch 28:121–134.

Berkowitz, E. N., R. A. Kerin, S. W. Hartley, and W. Rudelius. 2000. Interactivemarketing and electronic commerce marketing, 205–209. Boston: Irwin,McGraw-Hill.

Bhatnagar, A., S. Misra, and H. R. Rao. 2000. On risk, convenience and Internet shop-ping behaviour. Communications of the ACM 43 (11): 98–105.

Bigne-Alcaniz, E., C. Ruiz-Mafe, J. Aldas-Manzano, and S. Sanz-Blas. 2008. Influenceof online shopping information dependency and innovativeness on Internetshopping adoption. Online Information Review 32 (5): 648–667.

Bloch, P. H., D. L. Sherrell, and N. M. Ridgway. 1986. Consumer search: An extendedframework. Journal of Consumer Research 13:119–126.

Chahal, H., and R. Kohli. 2009. Managerial opinion towards IT intensive firms ofJammu and Ludhiana regions of north India. International Journal of IndianCulture and Business Management 2 (1): 71–94.

Chau, P. Y. K., and K. L. Hui. 1998. Identifying early adopters of new IT products: Acase of Windows 95. Information and Management 33 (5): 225–230.

Chiders, T. L., C. L. Carr, J. Peck, and S. Carson. 2001. Hedonic and utilitarian motiva-tions for online retail shopping behaviour. Journal of Retailing 77:511–535.

Citrin, A. V., D. E. Sprott, S. N. Silverman, E. Donald, and J. Stem. 2000. Adoption ofInternet shopping: The role of consumer innovativeness. Industrial Manage-ment and Data Systems 100 (7): 294–300.

Cockburn, C., and T. D. Wilson. 1996. Business use of the world wide Web.International Journal of Information Management 16 (2): 83–102.

Comegys, C., and M. Brennan. 2003. Students’ online shopping behaviour: Adual-country perspective. Journal of Internet Commerce 2 (2): 69–87.

Craig, S. C., and J. L. Ginter. 1975. An empirical test of a scale for innovativeness. InAdvances in consumer research. Vol. 2, ed. M. J. Achlinger, 555–562. Chicago,IL: Chicago Association for Consumer Research.

Crespo, A. H., and I. R. del Bosque. 2008. The effect of innovativeness on the adop-tion of B2C e-commerce: A model based on the theory of planned behaviour.Computers in Human Behaviour 24:2830–2847.

Cronbach, L. J. 1951. Coefficient alpha and the internal structure of tests. Psychome-trika 16 (3): 297–334.

Dabholkar, P. A., and R. P. Bagozzi. 2002. An attitudinal model of technology-basedself-service: Moderating effects of consumer traits and situational factors. Jour-nal of the Academy of Marketing Science 30 (3): 184–201.

Davis, F. D., R. P. Bagozzi, and P. R. Warshaw. 1989. User acceptance of computertechnology: A comparison of two theoretical models. Management Science 5(8): 982–1003.

Dittmar, H., K. Long, and R. Meek. 2004. Buying on the Internet: Genderdifferences in on-line and conventional buying motivation. Sex Roles 50 (5=6):423–444.

180 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Engelland, B. T., C. D. Hopkins, and D. A. Larson. 2001. Market mavenship asan influencer of service quality evaluations. Journal of Marketing Theory andPractice 9 (4): 15–26.

Express India. 2008. Indian netizens world’s third biggest online shoppers. http://www.expressindia.com/latest-news/Indian-netizens-worlds-third-biggest-online-shoppers/266267/ (accessed June 15, 2010).

Falk, P. 1997. The scopic regimes of shopping. In The shopping experience, ed.P. Falk and C. Campbell, 177–185. London: Sage.

Farag, S., J. Weltevrenden, T. Van Rietbergen, M. Dijst, and F. Van Oort. 2006.E-shopping in the Netherlands: Does geography matter? Environment andPlanning Business: Planning and Design 33:59–74.

Fiore, A. M., and H.-J. Jin. 2003. Influence of image interactivity on approachresponses towards an online retailer. Internet Research 13 (1): 38–48.

Fiore, A. M., H.-J. Jin, and J. Kim. 2005. For fun and profit: Hedonic value from imageinteractivity and responses toward an online store. Psychology and Marketing22 (8): 669–694.

Fiore, A. M., S.-E. Lee, and G. Kunz. 2003. Psychographic variables affecting willing-ness to use body-scanning. Journal of Business Management 9 (3): 271–287.

Foxall, G. R. 1995. Cognitive styles of consumer initiators. Technovation 15 (5):269–288.

Foxall, G. R., and C. G. Haskins. 1986. Cognitive style and consumer innovativeness:An empirical test of Kirton’s adoption-innovation theory in food purchasing.European Journal of Marketing 20 (3): 63–80.

Ganguly, M. 2009. State of Internet in India. http://www.slideshare.net/Manas.Ganguly/cdocuments-and-settingsm100029my-documentsstate-of-internet-in-india(accessed June 15, 2010).

Gefen, D. 2004. What makes an ERP implementation relationship worthwhile:Linking trust mechanisms and ERP usefulness. Journal of Management Infor-mation System 21 (1): 263–288.

Goldsmith, R. E. 2002. Explaining and predicting consumer intention to purchaseover the Internet: An exploratory study. Journal of Marketing Theory andPractice 10 (2): 22–28.

Goldsmith, R. E., J. B. Freiden, and J. K. Eastman. 1995. The generality=specificity issue in consumer innovativeness research. Technovation 15 (10):601–612.

Goldsmith, R. E., and C. F. Hofacker. 1991. Measuring consumer innovativeness.Journal of Academy of Marketing Science 19 (3): 209–221.

Grewal, D., J. Lindsey-Mullikin, and J. Munger. 2004. Loyalty in e-tailing: A concep-tual framework. Journal of Relationship Marketing 2 (3=4): 31–49.

Gupta, N., M. Handa, and B. Gupta. 2008. Young adults of India—online surfers oronline shoppers. Journal of Internet Commerce 7 (4): 425–444.

Ha, S., and L. Stoel. 2009. Consumer e-shopping acceptance: Antecedents in a tech-nology acceptance model. Journal of Business Research 62:565–571.

Hartnett, M. 2000. New features take do-it-best Website to higher level. Stores,February, 50–54.

Hasan, B. 2010. Exploring gender differences in online shopping attitude. Computersin Human Behaviour 26:597–601.

Online Shopping Behavior Among Indian Youth 181

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Haubl, G., and V. Trifts. 2000. Consumer decision making in online shopping envir-onments: The effects of interactive decision aids. Special issue, MarketingScience 19 (1): 4–21.

Hirschman, E. C., and M. B. Holbrook. 1982. Hedonic consumption: Emergingconcepts, methods and propositions. Journal of Marketing 46 (3): 92–101.

Hirschman, E. L. 1980. Innovativeness, novelty-seeking, and consumer creativity.Journal of Consumer Research 7:283–295.

Hirunyawipada, T., and A. K. Paswan. 2006. Consumer innovativeness andperceived risk: Implications for high technology product adoption. Journal ofConsumer Marketing 23 (4): 182–198.

Ho, C. F., and W. H. Wu. 1999. Antecedents of customer satisfaction on the Internet:An empirical study of online shopping. Proceedings of the 32nd Hawaii Inter-national Conference on Systems Sciences, Maui.

Hoffman, D., and T. Novak. 1996. Marketing in hypermedia computer-mediatedenvironments: Conceptual foundations. Journal of Marketing 60 (3): 50–68.

Internet and Mobile Association of India (IAMAI). 2006. Youth to drive e-commercegrowth in India. Internet and Mobile Association of India Summit, Mumbai.http://www.domain-b.com/ebusiness/general/20060119_commerce.html(accessed May 30, 2010).

Internet World Statistics. 2008. http://www.internetworldstats.com/asia.htm#in(accessed June 14, 2008).

Internet World Statistics. 2009. Top 20 countries with the highest number of Internetusers. http://www.internetworldstats.com/top20.htm (accessed June 10, 2010).

Jarvenpaa, S. L., and P. A. Todd. 1997. Consumer reactions to electronic shoppingon the world wide Web. International Journal Electronic Commerce 1 (2):59–88.

Joines, J. L., C. W. Scherer, and D. A. Scheufele. 2003. Exploring motivations of con-sumer Web use and their implications for e-commerce. Journal of ConsumerMarketing 20 (2): 90–108.

Joseph, B., and S. J. Vyas. 1984. Concurrent validity of a measure of innovativecognitive style. Journal of the Academy of Marketing Science 12 (2): 159–175.

Kim, H., A. M. Fiore, N. S. Niehm, and M. Jeong. 2010. Psychographic characteristicsaffecting behavioural intentions towards pop-up retail. International Journal ofRetail and Distribution Management 38 (2): 133–154.

Korgaonkar, P., and L. Wolin. 1999. A multivariate analysis of Web usage. Journal ofAdvertising Research 38 (1): 7–21.

Lassar, W. M., C. v, and S. S. Lassar. 2005. The relationship between consumer inno-vativeness, personal characteristics, and online banking adoption. InternationalJournal of Bank Marketing 23 (2): 176–199.

Leavitt, C., and J. Walton. 1975. Development of a scale for innovativeness. Advancesin Consumer Research 2 (1): 545–555.

Lee, M. K. O., C. M. K. Cheung, and Z. Chen. 2005. Acceptance of Internet-basedlearning medium: The role of extrinsic and intrinsic motivation. InformationManagement 42 (8): 1095–1104.

Liang, T. P., and J. S. Huang. 1998. An empirical study on consumer acceptance ofproducts in electronic markets: A transaction cost model. Decision SupportSystems 24 (1): 29–43.

182 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Limayem, M., M. Khalifa, and A. Frini. 2000. What makes consumers buy from Inter-net? A longitudinal study of online shopping. IEEE Transactions on Systems,Man, and Cybernetics Part A: Systems and Humans 30 (4): 421–432.

Lin, H. F. 2007. Predicting consumer intentions to shop online: An empirical testof competing theories. Electronic Commerce Research and Applications 6 (4):433–442.

Liu, X., M. He, F. Gao, and P. Xie. 2008. An empirical study of online shoppingcustomer satisfaction in China: A holistic perspective. International Journalof Retail and Distribution Management 36 (11): 919–940.

Lohse, G. L., and P. Spiller. 1998. Electronic shopping. Communications for ACM 41(7): 81–89.

Lunn, R. J., and M. W. Suman. 2002. Experience and trust in online shopping. In TheInternet in everyday life. The information age series, ed. B. Wellman andC. Haythornthwaite, 549–554. Malden, MA: Blackwell.

Mahmood, M. A., K. Bagchi, and T. C. Ford. 2004. On-line shopping behaviour:Cross country empirical research. International Journal of Electronic Commerce9 (1): 9–30.

Maignan, I., and B. Lukas. 1997. The nature and social uses of the Internet: Aqualitative investigation. The Journal of Consumer Affairs 31 (2): 346–371.

Manning, K. C., W. O. Bearden, and T. J. Madden. 1995. Consumer innovativenessand the adoption process. Journal of Consumer Psychology 4 (4): 329–345.

Mathwick, C., N. Malhotra, and E. Rigdon. 2001. Experiential value: Conceptualiza-tion, measurement, and application in the catalog and Internet shoppingenvironment. Journal of Retailing 77:39–56.

McKechnie, S., H. Winklhofer, and C. Ennew. 2006. Applying the technology accept-ance model to the online retailing of financial services. International Journal ofRetail and Distribution Management 34 (4=5): 388–410.

Menon, S., and B. Kahn. 2002. Cross-category effects of induced arousal and plea-sure on the Internet shopping experience. Journal of Retailing 78 (1): 31–40.

Menon, S., and B. E. Kahn. 1995. The impact of context on variety seeking in productchoices. Journal of Consumer Research 22 (3): 285–295.

Midgley, D. F., and G. R. Dowling. 1978. Innovativeness: The concept and itsmeasurement. Journal of Consumer Research 4:229–242.

Mishra, R. K. 2009. Benchmarking schemes for retails stores efficiency. InternationalJournal of Marketing Studies 1 (2): 131–150. www.ccsenet.org/journal.html(accessed May 3, 2010).

Miyazaki, A. D., and A. Fernandez. 2001. Consumer perceptions of privacy andsecurity risks for online shopping. The Journal of Consumer Affairs 35 (1):27–44.

Moe, W. 2003. Buying, searching, or browsing: Differentiating between online shop-pers using in-store navigational clickstream. Journal of Consumer Psychology 13(1=2): 29–39.

Moe, W., and P. S. Fader. 2004. Dynamic conversion behaviour at e-commerce sites.Management Science 50 (3): 326–335.

Monsuwe, T. P., B. G. C. Dellaert, and K. de Ruyter. 2004. What drives consumersto shop online? A literature review. International Journal of Service IndustryManagement 15 (1): 102–121.

Online Shopping Behavior Among Indian Youth 183

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Mudd, S. 1990. The place of innovativeness in models of the adoption process: Anintegrative review. Technovation 10 (2): 119–136.

Overby, J. W., and E.-J. Lee. 2006. The effects of utilitarian and hedonic online shop-ping value on consumer preference and intentions. Journal of BusinessResearch 59:1160–1166.

Park, C.-H., and Y.-G. Kim. 2003. Identifying key factors affecting consumer pur-chase behaviour in online shopping context. International Journal of Retailand Distribution Management 31 (1): 16–29.

Pires, G., J. Stanton, and A. Eckford. 2004. Influences on the perceived risk ofpurchasing online. Journal of Consumer Behaviour 4 (2): 118–131.

Reimer, J. (2006). Study shows youth embracing technology even more than before.http://arstechnica.com/news.ars/post/2006 0801–7401.html (accessed May 6,2010).

Roehrich, G. 2004. Consumer innovativeness: Concepts and measurements. Journalof Business Research 57 (6): 671–677.

Rogers, E. M. 1983. Diffusion of innovations. New York: The Free Press.Sanchez-Franco, M. J. 2006. Exploring the influence of gender on the Web usage via

partial least squares. Behaviour and Information Technology 25 (1): 19–36.Shang, R.-A., Y.-C. Chen, and L. Shen. 2005. Extrinsic versus intrinsic motivations for

consumers to shop online. Information Management 42 (3): 401–413.Sherry, J. F., M. A. McGrath, and S. L. Levy. 1993. The dark side of the gift. Journal of

Business Research 28 (4): D8.Soopramanien, D. G. R., and A. Robertson. 2007. Adoption and usage of online

shopping: An empirical analysis of the characteristics of ‘‘buyers’’ ‘‘browsers’’and ‘‘non-Internet shoppers.’’ Journal of Retailing and Consumer Services14:73–82.

Sorce, P., V. Perotti, and S. Widrick. 2005. Attitude and age differences in onlinebuying. International Journal of Retail and Distribution Management 33 (2):122–132.

Steenkamp, J. B. E. M., F. T. Hofstede, and M. Wedel. 1999. A cross-national com-parison into the national and national cultural antecedents of consumer innova-tiveness. Journal of Marketing 63 (2): 55– 69.

Sudhakar, A., and S. V. R. Rao. 2003. How to convert browsers into buyers. Strategy 7(October): 16.

Swinyard, W. R., and S. M. Smith. 2003. Why people (don’t) shop online: A lifestylestudy of the Internet consumer. Psychology and Marketing 20 (7): 567–597.

Teo, T. 2001. Demographic and motivation variables associated with Internet usageactivities. Internet Research 11 (2): 125–137.

To, P.-L., C. Liao, and T.-H. Lin. 2007. Shopping motivations on Internet: A studybased on utilitarian and hedonic value. Technovation 27:774–787.

Turley, L. W., and R. E. Milliman. 2000. Atmospheric effects on shopping behaviour: Areviewof the experimental evidence. Journal of Business Research 49 (2): 193–211.

Venkatraman, M. P. 1991. The impact of innovativeness and innovation type onadoption. Journal of Retailing 67 (1): 51–67.

Venkatraman, M. P., and L. L. Price. 1990. Differentiating between cognitive and sen-sory innovativeness: Concepts, measurements, and implications. Journal ofBusiness Research 20 (4): 293–315.

184 A. Khare et al.

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014

Vij, R. 2007. Above 45? Why marketers don’t age gracefully online. Digital andOnline Marketing. http://digital.afaqs.com/perl/digital/news/index.html?-sid=18801 (accessed May 21, 2010).

Vijayasarathy, L. R., and J. M. Jones. 2000. Print and Internet catalog shopping: Asses-sing attitudes and intentions. Journal of Internet Research 10 (3): 191–202.

Wang, H., J. G. Pallister, and G. R. Foxall. 2006. Innovativeness and involvement asdeterminants of Website loyalty: I. A test of the style=involvement model in thecontext of Internet buying. Technovation 26 (12): 1357–1365.

Online Shopping Behavior Among Indian Youth 185

Dow

nloa

ded

by [

Uni

vers

ity o

f L

iver

pool

] at

01:

42 0

6 O

ctob

er 2

014