Pramila Bharti | Aman Sehgal

28th Feb 2014

AN ANALYSIS OF BRAND VALUE AND OTHER FACTORS ON THE

PERSONALITY OF INDIAN ONLINE CONSUMER BEHAVIOR

Submitted to Prof. Devashish Das Gupta

IIM-Lucknow

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Table of Contents Abstract ........................................................................................................................................................ 5

Keywords .................................................................................................................................................. 5

Introduction .................................................................................................................................................. 6

Literature Survey .......................................................................................................................................... 7

Personality ................................................................................................................................................ 7

Influencing factors of changing personality type ................................................................................ 8

Big-Five Personality trait model .......................................................................................................... 9

Online and Offline shopping .................................................................................................................... 9

Online Shopping ................................................................................................................................. 10

Personality based online shopping .................................................................................................... 10

Consumer Behavior ................................................................................................................................ 11

Dynamic Consumer Behavior ............................................................................................................. 12

Online Consumer Behavior .................................................................................................................... 12

Factors Influencing Online Consumer Behavior ................................................................................ 15

Effect of Brand-Name in online consumer behavior ......................................................................... 16

Literature Review Table ............................................................................................................................. 18

Flowchart .................................................................................................................................................... 37

Methodology .............................................................................................................................................. 39

Research Methodology .......................................................................................................................... 39

Variables ................................................................................................................................................. 39

Scales ...................................................................................................................................................... 40

Survey Method ....................................................................................................................................... 40

Profile of respondents ............................................................................................................................ 40

Data Analysis tools ................................................................................................................................. 40

Sample Size ............................................................................................................................................. 40

Sample Design ........................................................................................................................................ 40

Results......................................................................................................................................................... 42

Importance of internal and external factors ......................................................................................... 42

Impact of Brand name ............................................................................................................................ 43

Discussion ................................................................................................................................................... 45

Impact of internal and external factors ................................................................................................. 45

Impact of the brand name ..................................................................................................................... 46

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Shopping behavior of Indian online customers .................................................................................... 47

References .................................................................................................................................................. 49

Appendix ..................................................................................................................................................... 54

Appendix 1 .............................................................................................................................................. 54

Appendix 2 .............................................................................................................................................. 54

Appendix 3 .............................................................................................................................................. 55

Appendix 4 .............................................................................................................................................. 55

Quantitative Questionnaire ................................................................................................................... 55

Result-1 ................................................................................................................................................... 60

Result-2 ................................................................................................................................................... 61

Result-3 ................................................................................................................................................... 61

Result-4 ................................................................................................................................................... 62

Result-5 ................................................................................................................................................... 62

Result-6 ................................................................................................................................................... 63

Result-7 ................................................................................................................................................... 63

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List of Tables Table 1: List of Literary works reviewed ..................................................................................................... 36

Table 2: Importance of online store features based on the personality type ............................................ 43

Table 3: Importance of Brand-name based on the personality type .......................................................... 44

Table 4: Importance of online store features based on the product category .......................................... 46

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List of Figures Figure 1: Flowchart for the study ................................................................................................................ 38

Figure 2: Relation between personality and online store features ............................................................ 43

Figure 3: Relation between personality type and product category with regard to brand-name ............. 44

Figure 4: Usage of Online shopping cart ..................................................................................................... 54

Figure 5: Online purchase intent using Personality .................................................................................... 54

Figure 6: Relation between customer satisfaction and loyalty .................................................................. 55

Figure 7: Predictors of online purchase intention ...................................................................................... 55

Figure 8: Perceptual Map for Agreeableness customers ............................................................................ 60

Figure 9: Perceptual Map for Openness customers ................................................................................... 61

Figure 10: Perceptual Map for Neuroticism customers ............................................................................. 61

Figure 11: Perceptual Map for Extraversion customers ............................................................................. 62

Figure 12: Perceptual Map for Conscientiousness customers ................................................................... 62

Figure 13: Preference map for the importance of Brand-name ................................................................. 63

Figure 14: Perceptual map to relate product categorize and personality types ........................................ 63

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Abstract The purpose of this study is to examine the online consumer behavior of Indian shoppers that might help

marketers to differentiate themselves from other retail stores. One of the objective of the study is to

understand the customer-valued features of online retail stores based on the personality type of

customers. Other objective of the study is to understand the value of “Brand-name” while shopping online

for various product categorize. We studied past literature on online consumer behavior to understand the

buying behavior of customers all over the world, and how it is different from Indian customers. To

investigate online questionnaire was filled up by 437 Indian online shoppers. Classification of customers

were done based on their personality type using Big-five personality trait model. Finally using SPSS

software, analysis was done to get the result of above mentioned objectives of the study.

The study identified that the Indian online customers are different from other customers because of price-

sensitive market. The features of an online store that they value most is return-policy and customer-

service. The Brand value is important for Indian online customers when they consider to buy Healthcare

products and electronics.

Keywords Online shoppers, personality, Big-five personality trait model, Extraversion, Openness, Neuroticism,

Agreeableness, Conscientiousness, Return Policy, Influencers, Customer services, Safe transaction,

Alternate to offline, Brand Name, Product categories.

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Introduction 21st century is known for the fast development in the area of Internet, connectivity and social media.

Customers have more option to choose from in any product category as well as they have many more

options from where they can buy.

Online shopping is becoming popular for variety of reasons. There are certainly outside factors as well,

like increasing fuel prices, over-occupied time table, which contribute to the increasing interest in online

shopping. Also, there are many benefits associated with online shopping which includes, convenience,

availability of huge variety in products, comparison among products, less time consuming, Cash-

On-Delivery payment option etc. These factors lead to high demand of online stores. Therefore, the

number of online retailers are increasing day by day. In this situation its utmost important for the

marketers to differentiate themselves from the rest of the world in terms of features which is valued by

the customer.

This paper classifies customer based on their personality type and study their online shopping behavior.

The study is divided into two parts mainly, first is to understand the customer-valued features of online

retail stores based on their personality. Second, to understand the value of “Brand-name” while shopping

online for various product categorize.

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Literature Survey

This section summarizes the relevant literatures regarding the impact of personality types on online

consumer buying behavior and impact of internal and external factors on it.

Personality

There are many available definition of Personality based on many available theories. One of such

definition is “Personality of any human being is a combination of emotional, attitudinal, and behavioral

response pattern of individuals”.

The study of Personality started with Hippocrates' four humors and gave rise to four temperaments. The

"Four Humors" theory held that a person's personality was based on the balance of bodily humors; yellow

bile, black bile, phlegm and blood. Further Personality is divided into five characteristics, famously known

as “Big Five Personality traits”. The five personality traits are Openness to experience, Conscientiousness,

Extraversion, Agreeableness and Neuroticism.

Many other personality measurement model is also available to measure and provide insights about

various personality traits. One of such measurement model is Mini-IPIP [Laverdière et al. 2013], which is

an extension of IPIP (International Personality Item Pool) Personality measurement model. The Mini-IPIP

is a brief instrument evaluating personality traits according to the Big Five models. Confirmatory factor

analyzes revealed a five-factor solution of Mini-IPIP is consistent with the Big Five model. Measurement

invariance analyses showed that the Mini-IPIP was reasonably invariant across samples, genders and age

groups. Overall, results pointed to a satisfactory factorial structure and an adequate invariance of the

measure.

Personality has a huge impact on the values, ethics and lifestyle of every individual. For example,

Personality may be among the factors contributing to individual differences in altruism. A study [Odaa, et

al., 2014] on the effect of personality on altruism have examined the relationship between donor and

recipient, and altruistic behavior in daily life. The result shows that with the exception of extraversion,

which commonly contributed to altruistic behavior toward all three types of recipients (i.e. (family

members, friends or acquaintances, and strangers), the particular traits that contributed to altruism

differed according to recipient. Conscientiousness contributed to altruism only toward family members,

agreeableness contributed to altruism only toward friends/acquaintances, and openness contributed to

altruism only toward strangers.

Changing personality traits influence the level of satisfaction from life as well [Mageea, et al., 2013].

Results on the studies shows that the increased neuroticism was associated with lower life satisfaction,

whereas increased extraversion, conscientiousness, and agreeableness were associated with higher life

satisfaction. These relationships were moderated by age, and were less evident in older adults. Hedonic

balance partially mediated the relationships between change in neuroticism and extraversion with life

satisfaction. These findings provide important insights into longitudinal associations between personality

change and life satisfaction.

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Research [Corr, et al., 2013] has linked general personality factors to social attitudes as well, specifically

approach-avoidance personality factors, especially positive-approach ones. Results revealed mainly two

points. First, positive-approach motivation is consistently related to both RWA (Right-Wing

Authoritarianism) and SDO (Social Dominance Orientation), with little contribution from negative-

avoidance motivation. Second, negative-avoidance motivation played a part in Need for Cognition

(negatively related) and Need for Closure (positively related). These data challenge previous theorizing

concerning the role of fear/anxiety in social attitude formation and prejudice more generally. In other

words, it says that the approach-related personality factors underpin the positive reinforcement of social

attitudes and prejudice.

Research [Dewberry, et al., 2013] indicates that everyday decision-making process of individuals also

varies according to their personality. The results indicates that cognitive styles offer no incremental

validity over decision-making styles in predicting decision-making competence, but that personality does

offer substantial incremental validity over general cognitive styles and decision-making styles. Jointly

decision-making styles and personality account for a substantial amount of variance in everyday decision-

making competence.

Influencing factors of changing personality type

Personality differs based on age, gender, culture, nation etc. of an individual. Many researchers studied

on the gender differences in implicit and explicit measures of the Big Five traits of personality. One of the

research paper [Vianello, et al., 2013] on this topic shows that women report higher levels of

Agreeableness, Conscientiousness, Extraversion and Neuroticism. For implicit measures, gender

differences were much smaller for all, and opposite in sign for Extraversion. Somewhat higher levels of

implicit Neuroticism and Agreeableness were observed in women, and somewhat higher levels of implicit

Extraversion and Openness were observed in men. There was no gender difference in implicit

Conscientiousness. A possible explanation is that explicit self-concepts partly reflect social norms and self-

expectations about gender roles, while implicit self-concepts may mostly reflect self-related experiences.

Research [Salmela-Aro, et al., 2012] also indicates that the personal goals and personality traits differs

among young adults based on genetic and environmental effects. Personal goals relating to education,

the respondent’s own family, friends, property, travel and self-showed primarily genetic and unique

environmental effects, whereas goals related to parents and relatives showed both shared and unique

environmental effects. The variation in goals related to health, work, hobbies and life philosophy was

attributable to non-shared environmental effects. Openness to experience and personal goals related to

family, education and property shared a significant amount of genetic influence. The same was true for

extraversion and self-related goals, and agreeableness and goals related to property.

Apart from genetic and environmental effects, context-specific achievement goals, mainly education and

work based, also varies according to Big Five personality traits [McCabe, et al., 2013]. Studies shows that

there are three sets of anticipated, consistent, and specific trait-goal relations. First, conscientiousness

was strongly and positively related to mastery-approach goals. Second, agreeableness was positively

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related to mastery-approach goals and negatively related to performance-approach goals. Third, both

avoidance goals and both performance goals were positively related to neuroticism.

Big-Five Personality trait model

Big Five Personality traits has a huge impact on learning style, academic goals and capability of achieve it

[Komarraju, et al., 2011]. Two of the Big Five traits, conscientiousness and agreeableness, were positively

related with all four learning styles (synthesis analysis, methodical study, fact retention, and elaborative

processing), whereas neuroticism was negatively related with all four learning styles. In addition,

extraversion and openness were positively related with elaborative processing. The Big Five together

explained 14% of the variance in grade point average (GPA), and learning styles explained an additional

3%, suggesting that both personality traits and learning styles contribute to academic performance.

Further, the relationship between openness and GPA was mediated by reflective learning styles

(synthesis-analysis and elaborative processing). These latter results suggest that being intellectually

curious fully enhances academic performance when students combine this scholarly interest with

thoughtful information processing.

But personality of an individual is not fixed in her or his lifespan. Research [Klimstra, et al., 2013] indicated

that it may change over changing age of an individual. Result of a research shows that the correlated

change between different personality traits is relatively stable from adolescence through adulthood, and

then increased after age 70. Second, correlated change was greater among traits that have been linked to

the same developmental processes (e.g., social investment or maturation of specific neurological

systems). Third, cognitive ability was negatively associated with correlated change. In other words, it says

personality change is partly driven by broad mechanisms affecting multiple traits. Associations with age

and cognitive ability provide important leads regarding the possible nature of these mechanisms.

Online and Offline shopping

Researchers and marketers tend to observe shoppers in online or offline stores to understand their

personality and to connect it with their decision making process. Characteristics which has impact on

offline stores are store layout, availability of products, salesperson knowledge, location of the store,

offered sales promotion tools etc. But in online store, two major characteristics which has effect on online

shopping environment are - search tool and information load – and on the descriptive characteristics of

consideration sets: size, dynamism, variety and preference dispersion [Parra, et al., 2009]. Research

results show that both information load and search tools transform the way in which consumers form

their consideration sets, resulting in smaller, more stable, and more homogenous sets, integrated by more

equally preferred alternatives. Also, interaction effects show that search tools enhance their effectiveness

in high information load settings.

Searching product information and buying goods online are becoming increasingly popular activities,

which would seem likely to affect shopping trips. However, little empirical evidence about the

relationships between e-shopping and in-store shopping is available. In a research [Farag, et al., 2007] on

how the frequencies of online searching, online buying, and non-daily shopping trips relate to each other,

the results show that searching online positively affects the frequency of shopping trips, which in its turn

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positively influences buying online. Also, an indirect positive effect of time-pressure on online buying was

found and an indirect negative effect of online searching on shopping duration. It also studied about how

these factors are influenced by attitudes, behavior, and land use features. The findings suggest that, for

some people, e-shopping could be task-oriented (a time-saving strategy), and leisure-oriented for others.

Also, urban residents shop online more often than suburban residents, because they tend to have a faster

Internet connection and the more shopping opportunities one can reach within 10 min by bicycle, the less

often one searches online.

Online Shopping

For online shopping, it is very important for customers to accept it completely before purchasing any

products from the online store. According to one of the study [Lian, et al., 2008], consumer do accept

online store but the level of acceptance vary based on personal innovativeness of information technology

(PIIT), perceived Web security, personal privacy concerns, and product involvement can influence

consumer acceptance of online shopping. Additionally, the availability of number of product categories

and subcategories influences the attitude of consumer towards the online store. According to another

study [Chang, 2011], the more subcategory options, the greater consumers' perceived variety. However,

the influence of the number of subcategory options on ease of navigation, shopping pleasure, attitudes

toward the store, and future purchase intentions indicated an inverted U-shaped pattern; moreover, the

influence is significant only among participants with low rather than high choice uncertainty.

The availability of product categories is a necessary factor for any online store and so is appropriate

product bundling strategy. To improve sales in an online store, it’s crucial for marketers to efficiently

collect not only order data but also browsing and shopping-cart data, which provide marketers with

information on the consumers’ decision-making processes, rather than only the final shopping decisions

[Yang, et at., 2006].

One of the major motivation for online shopping is usage of online shopping cart [Close, et al., 2010].

While retailers offer virtual carts as a functional holding space for intended online purchases, it also has

powerful utilitarian and hedonic motivations that explain the frequency of consumers' online cart use.

Beyond current purchase intentions, the reasons for why consumers place items in their carts include:

securing online price promotions, obtaining more information on certain products, organizing shopping

items, and entertainment [Refer Appendix 1].

Personality based online shopping

What determines the one’s willingness to shop online? Or what determines whether one purchase

products through online channel or offline store? In pursuing this line of research, several approaches

have been utilized including those based upon behavioral economics, lifestyle analysis, and merchandising

effects. While some of this work identifies the potential moderation of personality traits most of it focuses

on factors related to time, costs and benefits, and shopping context. A study [Bosnjak, et al., 2007] which

seeks to understand online purchase intent using personality constructs, uses data from an online

consumer panel to develop a hierarchical model of personality useful for predicting consumer intentions

to purchase products and services online [Refer Appendix 2].

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Online purchase intention and decision making process also varies according to the mood of the customer

which further depends on the personality of the customer. A research [Huang , et al., 2012] which

investigates whether a person’s mood can influence impulsivity in online shopping decisions, and how

involvement can regulate it, shows that incidental moods tend to increase process impulsivity, and this

effect may not be restrained by involvement. Also, the decision-making process can be separated into two

stages – orientation and evaluation. And the impact of impulsivity on these two stages suggests the

importance of mood-elicited impulsivity of purchases in e-commerce.

Consumer Behavior

Personality of any human being has a big impact on his or her decision making process or purchase

behavior. This process of selecting, securing and disposing of products, services and experiences or ideas

to satisfy needs and the impacts that these processes have on the consumer and society, is known as

Consumer Behavior. It explains the characteristics of individual consumers such as demographics and

behavioral variables in an attempt to understand people’s wants.

The impact of personality or individual identity on consumer behavior has been a famous study topic

among researchers. In one of the study [Reed II, et al., 2012] about influence of identity on consumer

behavior, the identity was explained first with the help of five variables and then showed the influence of

these variables on purchasing process. These five variables are (1) Identity Salience: identity processing

increases when the identity is an active component of the self; (2) Identity Association: the non-conscious

association of stimuli with a positive and salient identity improves a person's response to the stimuli; (3)

Identity Relevance: the deliberative evaluation of identity-linked stimuli depends on how diagnostic the

identity is in the relevant domain; (4) Identity Verification: individuals monitor their own behaviors to

manage and reinforce their identities; and (5) Identity Conflict: identity-linked behaviors help consumers

manage the relative prominence of multiple identities.

Consumer purchasing behavior can be influenced by learning and experiencing a product or service,

especially through cognitive learning [Batkoska, et al., 2012]. Cognitive learning can be done as a complex

mental process of forming opinions, attitudes, making decision for reacting either positively or negatively,

etc., which further has a huge impact on the purchasing behavior of shoppers.

Consumer behavior, as any other behavior, is goal oriented [Kopetz, et al., 2012]. Goal systems theory

outlines the principles that characterize the dynamics of goal pursuit and explores their implications for

consumer behavior. It explains goal systemic, perspective a variety of well-known phenomena in the realm

of consumer behavior including brand loyalty, variety seeking, impulsive buying, preferences, choices and

regret.

Apart from personality there are many factors which influence consumer behavior and decision making

process of shoppers, for example, according to one of the research study fundamental and evolutionary

motives influences consumer behavior to a large extent [Griskevicius, at al., 2013]. According to this

study, fundamental motives include: (1) evading physical harm, (2) avoiding disease, (3) making friends,

(4) attaining status, (5) acquiring a mate, (6) keeping a mate, and (7) caring for family. It suggested that

many consumer choices ultimately function to help fulfill one or more of these evolutionary needs. It

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shows that a person's preferences, behaviors, and decision processes change in predictable ways

depending on which fundamental motive is currently active.

Dynamic Consumer Behavior

Consumer Behavior is a very dynamic process. It changes with age, nationality, time and many more

factors. A research paper [Vag, 2007] integrates two approaches, conjoint analysis and multi-agent

simulation to simulate the changing consumer preferences. It also uses social network analysis, consumer

behavior modeling, and word-of-mouth marketing. The result is based on the assumption that one can

predict an individual's purchases on the basis of his/her measured product preferences, communication

habits and market behavior attributes. Result shows a model to simulate the association between

consumers' communication and sales.

Dynamic nature of consumer behavior and cross-cultural issues are studied by many researchers. One of

the research [Douglas, et al., 1997] examines the critical issue of defining the appropriate unit of analysis

in cross-cultural research and proposes a new definition. Result shows three alternative research designs

for cross-cultural studies based on this definition. Each design relates to a different type of research issue

and provides a different approach to dealing with the increasingly problematic issue of isolating the culti-

unit from cultural contamination to rule out alternative explanations.

Consumer behavior of any individual also changes based on his/her changing habits, behavior, personality

etc. A research [Scholderer, et al., 2008] has drawn attention to the role of past behavior and habit in the

overall structure of consumer behavior. It argued that in cross-sectional data past behavior and habit must

be confounded with present beliefs and attitudes when the behavior in question has been enacted

numerous times before. Result shows positive relation between changing habit and changing preferences

about a product.

Apart from habits, nationality etc. social influence and demand for new products also has an effect on

dynamic nature of consumer behavior. In a research paper [Cojacaru, et al., 2013], scholar has examined

the effects of heterogeneous consumer personality types (imitators, innovators), effects of changes in the

price of the variants, and effects of consumers' innate tendency to change preferences, on adoption of

new variants. It also showed that the role played by social influence in the dynamics of preference change

can slow the adoption of a variant, depending on the initial size of the variant's market, its pricing relative

to the well-known product, and its degree of “new”-ness. Results indicated that adoption of new variants

of well-established products is highest in two cases: when the proportion of innovators is small and the

imitators' preferences change based more on variant's attributes than popularity, or when the proportion

of innovators is higher and the imitators' preferences change based more on product's popularity.

Online Consumer Behavior

The decision making process differs for offline and online consumers. For online shoppers, it is mainly

related to how different online decision-making processes used by consumers, influence the complexity

of their online shopping behavior etc. In one of the study [Senecal, et al., 2005], consumers showed

significant difference between their decision-making process and their online shopping behavior.

Customers who did not consult a product recommendation had a significantly less complex online

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shopping behavior (e.g., fewer web pages viewed) than subjects who consulted the product

recommendation. Surprisingly, no differences were found between the online shopping behavior of

subjects who consulted but did not follow the product recommendation and subjects who consulted and

followed the product recommendation.

In a different study [Cai, et al., 2006], another important aspect of online consumer behavior is discussed,

which is customer value in an online store. Customer value includes process value, outcome value, and

shopping enjoyment. The results from this study showed that outcome value and process value

contributed significantly to customer satisfaction and loyalty. Also, evidences confirmed that customer

satisfaction affect customer loyalty. Enjoyment, however, had no significant positive impact on customer

satisfaction [Refer Appendix 3].

In a research [Wang, et al., 2013] about customer intention to buy online it was suggested that perceived

enjoyment, perceived usefulness, perceived fee, and ethical self-efficacy for online piracy (ESEOP) have a

significant influence on perceived value and that ESEOP can enhance the positive effect of perceived value

on purchase intention.

Another study [Escobar-Rodríguez, et al., 2013] about customer intention to shop online indicates that

the main predictors of online purchase intention are, in order of relevance, habit, price saving,

performance expectancy, and facilitating conditions. However, it shows there is no significant impact of

effort expectancy on the online purchase intention, social influence from referents; and hedonic

motivation to use the website. On the other hand, it highlight that the main predictors of use behavior

are, in order of importance, online purchase intention, habit, and facilitating conditions [Refer Appendix

4].

In an online store, customers may get influenced by web aesthetics as well. A research [Wang, et al.,

2011] about influence of web aesthetics on online consumer behavior, studied two dimensions of web

aesthetics, aesthetic formality and aesthetic appeal, and its influence on online consumers’ psychological

reactions, including perceived service quality, satisfaction, and arousal, and at last how these

psychological changes, influence online consumers’ conative tendencies. The result talks about mainly

three points. First, consumers’ cognitive, affective, and conative outcomes can be significantly evoked by

aesthetic stimuli. Second, the two dimensions of web aesthetics exhibit dissimilar patterns of influences.

And last, purchase task significantly moderates consumers’ responses in terms of magnitude and

direction.

Apart from web aesthetics, psychological and social factors can also influence online purchase behavior.

In a study [Cetină, et al., 2012] about the impact of psychological and social factors on online consumer

behavior, it is shown that the Web experience generates mutations in mental processes that trigger the

online buying decision. And therefore, marketers should acknowledge the importance these factors due

to their increasing power in the digital world.

Another major influencing factor for online customers is reviews provided by past users of the same

product. Online reviews, a form of online word-of-mouth (eWOM), have recently become one of the most

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important sources of information for modern consumers. But before following eWOM two major criteria

need to be taken care of - perceived ‘usefulness’ and perceived trustworthiness.

A research [Racherla, et al., 2012] about perceived ‘usefulness’ of online consumer reviews shows that a

combination of both reviewer and review characteristics are significantly correlated with the perceived

usefulness of reviews. The study also finds several results that are anomalous to established knowledge

related to consumers’ information consumption, both offline and online.

And a research [Utz, et al., 2012] about perceived trustworthiness of online consumer reviews shows that

user’s dispositional trust moderated the effects of reviews and assurance seals. Consumers with high trust

were more influenced by the reviews of other consumers; and only they tended to be influenced by

assurance seals. The results show that consumer reviews play an important role in consumer decision

making, indicating that online consumer communities indeed empower consumers.

In the case of online stores, trust plays an important role for customer loyalty and repeat purchase, which

is crucial for the survival and success of any store. A research [Chiu, et al., 2012] about the influence of

trust on online repeat purchase intention studied various factors for continued usage or loyalty, like,

perceived usefulness, trust, satisfaction, and perceived value. But it mainly focused on the habit of

customer and its effect on loyalty. It defined habit as the extent to which buyers tend to shop online

automatically without thinking. The results indicate that a higher level of habit reduces the effect of trust

on repeat purchase intention. Also, value, satisfaction, and familiarity are important to habit formation

and thus relevant within the context of online repeat purchasing.

Future repeat purchase also depends on the past-experience of the product/service, especially post-

purchase services. Operations glitch, like, order fulfillment delay etc. can lead to negative customer

loyalty. A study [Rao, et al., 2011] which links online order fulfillment glitches with future purchase

behavior employs expectancy disconfirmation and distributive justice theories to empirically show that

adverse post-glitch reactions are seen in several dimensions of customer shopping behavior – order

frequency and order size decrease, while customer anxiety level increases. It also demonstrates that

online retailers need to deliver on order fulfillment promises, since a failure to live up to these promises

can be detrimental.

To ensure customer retention and brand loyalty, satisfied customers are essential to maintain. One of the

way to satisfy customer’s need and make online shopping an excellent experience, online retailers need

to focus on customization of concepts. In a study [Thirumalai, et al., 2011] about conceptualize

customization, two main factors are explained. One is decision customization—the customization of the

information content delivered to customers to help them in the decision-making sub-process; and

transaction customization—the customization of the purchase transaction sub-process for each

customer. The results indicate that decision customization that provides choice assistance by way of

personalized product recommendations is positively associated with customer satisfaction with the

decision-making sub-process; and transaction customization, oriented towards making the transaction

sub-process personal, convenient, and interactive is positively associated with customer satisfaction with

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the purchase transaction sub-process. Additionally, the results indicate that both decision customization

and transaction customization are associated with overall customer satisfaction with the online purchase

process of electronic retailers.

The success of the online shopping channel depends more on post-adoption use of the channel for

purchasing an increasingly a wide range of products than on initial decision to use the channel for

shopping. A research [Liu, et al., 2011] to examine whether the early adopters of the online channel are

more likely to buy wide range of products and more frequently than the late adopters, shows that the

factor effects on predicting purchase intensity are different across the groups of early and late adopters.

Factors Influencing Online Consumer Behavior

Buying behavior of online shoppers vary based on many other factors like, social influencers,

demographics and psychographics of customers, difference in price as compared to offline and other

online stores, features and attributes of online retail website, post-purchase and added services provided

by the retailers etc.

Social influence in the case of online purchase is very important for the first-time online buyers as well as

for recommendations of the product or website. Social Influence using word-of-mouth is the most vital

one, as the word-of-mouth has the most informative effect, trustworthy and which affects consumers'

evaluation of product quality [B. Gu, et al., 2012]. So it’s important for online stores to identify the

influencers in customer network. Different centrality measures can be used for the diffusion of marketing

messages and its effect on network topology and diffusion process. These decision support systems can

be used to select influencers and spread viral marketing campaigns in a customer network [Kiss et al.,

2008].

Demographics and psychographics characteristics and consumption values of customers has substantial

impact on consumer beliefs and online purchase behavior. The beliefs and consumption values influence

purchase behavior and it can used by online retailers to formulate product positioning strategies that

create more value for consumer segments through better customization, thereby enhancing retailer

profits. Also, public policy makers can design communication strategies to help lower-income consumers

realize the same benefits of e-commerce as their higher-income counterparts [Punj, 2011]. Also, the

consumer search pattern for products to buy online depends on consumer demographics [Bhatnagar, et

al., 2003]. Consumer search behavior for products vary for customers with little or expert knowledge

about the product and its features. Also, there is a significant difference between the site type usage and

in the patterns of site type utilization between customers with expert and novice product knowledge

[Jaillet, 2001]. Other demographics characters like gender of the online shopper has little impact on the

online buying behavior. Especially there is no difference in the frequency of online browsing or purchasing

based on gender, but there is a significant difference in the types of products women and men prefer to

buy online [Sebastianelli et al., 2008].

The spending behavior of consumers can substantially help target the direct marketing of financial

products, and constitutes new information, not captured by demographics [E.Otto et al., 2009].Price

16

difference as compared to past prices leads to strong adjustments of price expectations depending on

price chart characteristics [Drechsler, et al., 2011]. Online shoppers can also be segmented based on their

spending behavior and knowledge about the production cost and market price of the products. These

segments differs in terms of trust, fairness of the price differences, willingness to buy and repurchase

intentions [Grewal, et al., 2004].

Web browsing and online shopping behavior mainly depends on website designs [Woo Tan, et al., 2006].

The website with the highest quality produced the highest business performance. The success of e-

business depends on different relative importance of each website quality factors, the relationship

between website preference and financial performance and priority of alternative websites across e-

business domains and between stakeholders [Lee, et al., 2006].

The post purchase service quality of an online store has a big impact on repeat purchase behavior and

satisfaction level of online shoppers. The service quality positively influences both perceived value and

customer satisfaction; perceived value positively influences on both customer satisfaction and post-

purchase intention; customer satisfaction positively influences post-purchase intention; service quality

has an indirect positive influence on post-purchase intention through customer satisfaction or perceived

value and among the dimensions of service quality, ‘‘customer service and system reliability” is most

influential on perceived value and customer satisfaction, and the influence of ‘‘content quality” ranks

second [Kuo, et al., 2009]. Apart from post-purchase intentions and post-recovery satisfaction among

customers, perceived justice by the customers is also important for repeat purchase behavior and

satisfaction level of online shoppers. For example, distributive justice increases positive emotions and

decreases negative ones. Also, procedural justice enhances post-recovery satisfaction as well as increases

positive emotions and decreases negative ones, while interactional justice only increases post-recovery

satisfaction of customers [Kuo, et al., 2012].

Effect of Brand-Name in online consumer behavior

Consumer psychology changes with many above mentioned internal and external factors. “Brand-Name”

is one such factor. Previously producers were market oriented, but now they learnt to make products and

promote it by brand oriented methods. One of the research paper [Urde, et al., 2013] explores the

interaction between brand orientation and market orientation. Brand orientation is an inside-out,

identity-driven approach that sees brands as a hub for an organization and its strategy. Similarly, market

orientation is an outside-in, image-driven approach. Initially, brand orientation and market orientation

appear to be two different strategic options. Though synergistic combinations are also possible, they are

not explored, nor labeled as part of branding practice and philosophy. This paper proposes a new type of

orientation, a hybrid between brand and marketing orientation. It articulates typical trajectories for

evolving the orientation and aspires to move the discussion from the tug-of-war between the two

paradigms by developing a more dynamic view.

The effect of Brand-Name on the decision making process of customer is studied by a paper [Degeratu,

et al., 2000] , which shows that brand names become more important online in some categories but not

in others depending on the extent of information available to consumers — brand names are more

valuable when information on fewer attributes is available online.

17

One of the paper [Simonian, et al., 2012] which examines the two most important type of risks in online

shopping also suggested that the product brand image is one of the important criteria while making

selection by the customer. This paper examines and compare product brand image and online store image

for perceived risks and online purchase intentions for apparel. Results show that product brand image

influences consumers' online purchase intentions both directly and indirectly by reducing various risk

perceptions and online store image impacts purchase intentions indirectly by decreasing risk perceptions.

So it can be concluded that consumers trust branded products in an online retail shop and perceive it

more useful, which ultimately enhances their brand experience. A research paper [Thomas, et al., 2013]

combines insights from marketing and information systems to arrive at an integrative model of online

brand experience. In this model emotional aspects of brand relationship supplement the dimension of

technology acceptance to arrive at a more complete understanding of consumer experience with an

online brand. The results demonstrate that trust and perceived usefulness positively affect online brand

experience. Positive experiences result in satisfaction and behavioral intentions that in turn lead to the

formation of online brand relationship. Interestingly, brand reputation emerges as an important

antecedent of trust and perceived ease of use of an online brand.

18

Literature Review Table

S.No.

Name of the Article;

Name of the Author;

Journal Name

Research

Objectives

Variables

used

Methodology

Findings

1 Factor structure and

measurement

invariance of a short

measure of the Big

Five personality traits;

Olivier Laverdière,

Alexandre J.S. Morin,

France St-Hilaire;

Personality and

Individual Differences

To assess the

factor structure

and the

measurement

invariance of

the Mini-

International

Personality

Item Pool

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness

Confirmatory

factor analysis

and

Measurement

invariance

analysis

five-factor solution

consistent with the

Big Five model and

Mini-IPIP was

reasonably invariant

across samples,

genders and age

groups

2 Personality and

altruism in daily life;

Ryo Oda, Wataru

Machii, Shinpei Takagi,

Yuta Kato,Mia

Takeda,Toko

Kiyonari,Yasuyuki

Fukukawa,Kai Hiraishi;

Personality and

Individual Differences

to investigate

the

relationship

between the

Big-Five

personality

traits and the

frequency of

altruistic

behaviors

toward various

recipients in

daily life

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness, Family,

friends,

strangers,

Conscientiousness

contributed to

altruism only

toward family

members,

agreeableness

towards friends, and

openness towards

strangers

3 Personality trait

change and life

satisfaction in adults:

The roles of age and

hedonic balance;

Christopher A. Magee,

Leonie M. Miller,

Patrick C.L. Heaven;

Personality and

Individual Differences

It examines

whether

changes in

personality

traits

influenced life

satisfaction

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness, life

satisfaction

Survey of

11,104

Australian

adults aged

18–79 years,

Latent

difference

score

modeling

technique

Result shows

increased

neuroticism was

associated with

lower life

satisfaction,

whereas increased

extraversion,

conscientiousness,

and agreeableness

were associated

with higher Life

Satisfaction

19

4 Decision-making

competence in

everyday life: The

roles of general

cognitive styles,

decision-making styles

and personality; Chris

Dewberrya,Marie

Juanchichb,Sunitha

Narendran;

Personality and

Individual Differences

It examined

the extent to

which general

cognitive styles

explain

variance in

decision-

making

competence

over and above

decision-

making styles,

and the extent

to which

personality

explains

variance in

decision-

making

competence

over and above

style variable

decision

making style,

cognitive style

355

respondents

took tests on

everyday

decision-

making

competence,

decision

styles,

cognitive

styles, and the

Big Five

personality

tests

Cognitive styles

offer no incremental

validity over

decision-making

styles in predicting

decision-making

competence, but

that personality

does offer

substantial

incremental validity

over general

cognitive styles and

decision-making

styles. Jointly

decision-making

styles and

personality account

for a substantial

amount of variance

in everyday

decision-making

competence.

5 Gender differences in

implicit and explicit

personality traits;

Michelangelo

Vianelloa,Konrad

Schnabelb,N.

Sriram,Brian Nosek;

Personality and

Individual Differences

It examines

gender

differences in

implicit and

explicit

measures of

the Big Five

traits of

personality.

male, female,

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness

Survey with

14,348

respondents

and implicit

and explicit

tests

Higher levels of

Neuroticism and

Agreeableness were

observed in women,

and higher levels of

Extraversion and

Openness were

observed in men.

There was no

gender difference in

Conscientiousness.

20

6 Personal goals and

personality traits

among young adults:

Genetic and

environmental effects;

Katariina Salmela-

Aro,Sanna Read,Jari-

Erik Nurmi,Eero

Vuoksimaa,Mari

Siltala,Danielle M.

Dick,Lea

Pulkkinenb,Jaakko

Kaprio,Richard J. Rose;

Journal of Research in

Personality

To examine

genetic and

environmental

contributions

to personal

goals

Openness,

Education,

Family,

Agreeableness

, Property,

Extraversion,

self

1279 twins

aged 20–26

filled in

Personal

Project

Analysis and

NEO-FFI

inventories

Openness to

experience and

personal goals

related to family,

education and

property shared a

significant amount

of genetic influence.

The same was true

for extraversion and

self-related goals,

and agreeableness

and goals related to

property.

7 Big Five personality

profiles of context-

specific achievement

goals; Kira O.

McCabea,Nico W. Van

Yperena,Andrew J.

Elliot,Marc Verbraakc;

Journal of Research in

Personality

checked the

relations

between the

Big Five

personality

traits and

context-

specific

achievement

goals in two

different

contexts,

school and

work

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness

Survey to test

personality

and

achievements

in work and

school life

First,

conscientiousness

was strongly and

positively related to

mastery-approach

goals. Second,

agreeableness was

positively related to

mastery-approach

goals and negatively

related to

performance-

approach goals.

Third, both

avoidance goals and

both performance

goals were

positively related to

neuroticism.

8 The Big Five

personality traits,

learning styles, and

academic

achievement; Meera

Komarraju,Steven J.

Karau,Ronald R.

Relation

between

Personality and

learning styles

synthesis

analysis,

methodical

study, fact

retention, and

elaborative

processing,

College

students (308

undergraduat

es) completed

the Five

Factor

Inventory and

Two of the Big Five

traits,

conscientiousness

and agreeableness,

were positively

related with all four

learning styles,

21

Schmeck,Alen Avdic;

Personality and

Individual Differences

Neuroticism,

Extraversion,

Openness to

Experience,

Agreeableness

,

Conscientious

ness

the Inventory

of Learning

Processes and

reported their

grade point

average

whereas

neuroticism was

negatively related

with all four

learning styles

(synthesis analysis,

methodical study,

fact retention, and

elaborative

processing),

whereas

neuroticism was

negatively related

with all four

learning styles.

9 Correlated change of

Big Five personality

traits across the

lifespan: A search for

determinants; Theo A.

Klimstra,Wiebke

Bleidorn,Jens B.

Asendorpfb,Marcel

A.G. van Aken,Jaap J.A.

Denissen; Journal of

Research in

Personality

Relation

between

Personality

development

and changing

personality

Openness,

Extraversion

Two tests to

check age

effect and

cognitive

ability

Correlated change is

relatively stable

from adolescence

through adulthood,

and then increased

after age 70.

Second, correlated

change is greater

among traits that

have been linked to

the same

developmental

processes. Third,

cognitive ability was

negatively

associated with

correlated change.

10 Consideration sets in

online shopping

environments: the

effects of search tool

and information load;

José F. Parra,Salvador

Ruiz; Electronic

Commerce Research

and Applications

To examine the

effects of

search tool and

information

load on the

descriptive

characteristics

of

consideration

set size, set

dynamism, set

variety

Simulate

online store

by

manipulated

search tool

(yes, no) and

information

load (high,

low).

both information

load and search

tools transform the

way in which

consumers form

their consideration

sets, resulting in

smaller, more

stable, and more

22

sets: size,

dynamism,

variety and

preference

dispersion

homogenous sets,

integrated by more

equally preferred

alternatives

11 Shopping online

and/or in-store? A

structural equation

model of the

relationships between

e-shopping and in-

store shopping; Sendy

Farag,Tim

Schwanen,Martin

Dijst,Jan Faber;

Transportation

Research Part A: Policy

and Practice

to describe

how the

frequencies of

online

searching,

online buying,

and non-daily

shopping trips

relate to each

other, and how

they are

influenced by

such factors as

attitudes,

behaviour, and

land use

features

online

searching,

online buying,

shopping

trips,

attitudes,

behavior, and

land use

features

826

respondents

residing in

four cities of

the

Netherlands.

Structural

equation

modelling was

used.

Searching online

positively affects the

frequency of

shopping trips,

which in its turn

positively influences

buying online. An

indirect positive

effect of time-

pressure on online

buying was found

and an indirect

negative effect of

online searching on

shopping duration.

12 Effects of consumer

characteristics on their

acceptance of online

shopping:

Comparisons among

different product

types; Jiunn-Woei

Lian, Tzu-Ming Lin;

Computers in Human

Behavior

to explore the

effects of

different

product types

on the

acceptance

factor of online

shopping

personal

innovativenes

s, Web

security,

privacy

concerns and

product

involvement

survey-based

approach and

Regression

analysis

Personal

innovativeness of

information

technology (PIIT),

perceived Web

security, personal

privacy concerns,

and product

involvement can

influence consumer

acceptance of online

shopping, but their

influence varies

according to

product types.

13 Beyond buying:

Motivations behind

consumers' online

shopping cart use;

To examine

consumers'

motivations for

placing items in

Purchase

intention,

price

promotion,

national

online survey

Beyond purchase

intentions, why

consumers place

items in their carts

23

Angeline G. Close,

Monika Kukar-Kinney;

Journal of Business

Research

an online

shopping cart

with or without

buying

entertainment

, frequency of

cart use,

frequency of

online buying

include: securing

online price

promotions,

obtaining more

information on

certain products,

organizing shopping

items, and

entertainment

14 The Impact of

Cognitive Learning on

Consumer Behaviour;

Liljana Batkoska, Elena

Koseska; Procedia -

Social and Behavioral

Sciences

To check the

impact

ofcognitive

learning on

consumer

behaviour

cognitive

learning,

consumer

behavior,

motivating

factors,

advertising

and non-

advertising

factors

opinion

polling of

consumers

There is a strong

relationship

between cognitive

learning and

consumer

personality

15 The dynamics of

consumer behavior: A

goal systemic

perspective; Catalina

E. Kopetz,Arie W.

Kruglanski,Zachary G.

Arens,Jordan

Etkin,Heather M.

Johnson; Journal of

Consumer Psychology

To check the

impact of goals

on consumer

behavior

process

goals Goal systemic

perspective has

impact on brand

loyalty, variety

seeking, impulsive

buying, preferences,

choices and regret

16 Fundamental motives:

How evolutionary

needs influence

consumer behavior;

Vladas Griskeviciusa,

Douglas T. Kenrick;

Journal of Consumer

Psychology

To test how

motives

influence

modern

behavior

7 type of

motives: (1)

evading

physical harm,

(2) avoiding

disease, (3)

making

friends, (4)

attaining

status, (5)

acquiring a

mate, (6)

detailed study

of the

evolutionary

functions of

behavior

motives influences

on consumer

behavior,

evolutionary

biology, and other

social sciences

24

keeping a

mate, and (7)

caring for

family

17 Consumers' decision-

making process and

their online shopping

behavior: a

clickstream analysis;

Sylvain Senecal, Pawel

J. Kalczynski, Jacques

Nantel; Journal of

Business Research

to investigate

how different

online

decision-

making

processes used

by consumers,

influence the

complexity of

their online

shopping

behavior

(1) clickstream

compactness,

(2) clickstream

stratum, (3)

number of

web pages

visited, (4)

revisited page

ratio (i.e.,

total number

of web pages

visited divided

by the

number of

unique web

pages visited),

(5) total

shopping

time.

online

experiment

(1) Customers who

did not consult a

product

recommendation

had a less complex

online shopping

behavior than who

consulted the

product

recommendation.

(2) no differences

were found

between the online

shopping behavior

of Customers who

consulted but did

not follow the

product

recommendation

18 What drives purchase

intention in the

context of online

content services? The

moderating role of

ethical self-efficacy for

online piracy; Yi-Shun

Wang, Ching-Hsuan

Yeh, Yi-Wen Liao;

International Journal

of Information

Management

to test the

effect of ethical

self-efficacy for

online piracy

(ESEOP) on the

relationship

between

perceived

value and

purchase

intention in the

context of

online content

services

Perceived

usefulness,

Perceived

enjoyment,

Perceived fee,

perceived

value,

purchase

intention

online survey

questionnaire

perceived

enjoyment,

perceived

usefulness,

perceived fee, and

ESEOP have a

significant influence

on perceived value

and that ESEOP can

enhance the

positive effect of

perceived value on

purchase intention

19 Aesthetics and the

online shopping

environment:

Understanding

how the two

dimensions of

web aesthetics,

aesthetic

9 variables: (1)

Aesthetic

formality (2)

Aesthetic

Survey

(sample of

140

consumers)

The results indicate:

(1) consumers’

cognitive, affective,

and conative

25

consumer responses;

Yong Jian

Wang,Michael S.

Minor,Jie Wei; Journal

of Retailing

formality and

aesthetic

appeal,

influence

online

consumers’

psychological

reactions,

appeal (3)

Satisfaction

(4) Arousal

(5)Online

service quality

(6) Purchase

(7)

consultation

(8) re-visit (9)

search on

other

websites

outcomes can be

significantly evoked

by aesthetic stimuli;

(2) the two

dimensions of web

aesthetics exhibit

dissimilar patterns

of influences; and

(3) purchase task

significantly

moderates

consumers’

responses in terms

of magnitude and

direction.

20 Psychological and

Social Factors that

Influence Online

Consumer Behavior;

Iuliana Cetină,Maria-

Cristiana

Munthiu,Violeta

Rădulescu; Procedia -

Social and Behavioral

Sciences

to test the

relation

between Web

experience and

online

consumer

behavior

consumer

behavior,

online factors,

web

experience

online survey Web experience

related to social and

psychological

factors influences

online consumer

behavior

21 Perceived ‘usefulness’

of online consumer

reviews: An

exploratory

investigation across

three services

categories; Pradeep

Racherla,Wesley

Friske; Electronic

Commerce Research

and Applications

to test the

usage and

influencing

power of

online reviews

on customers

(1) Identity

disclosure (2)

Expertise (3)

Reputation (4)

Review

elaborateness

(5) review

valence

reviews

collected from

Yelp.com

both reviewer and

review

characteristics are

significantly

correlated with the

perceived

usefulness of

reviews

22 Consumers rule: How

consumer reviews

influence perceived

trustworthiness of

online stores; Sonja

to test whether

consumer

reviews are a

more

important cue

Reputation of

the online

store

Laboratory

experiment

for review and

store

reputation

Consumer reviews

turned out as the

strongest predictor

of trustworthiness

judgments.

26

Utz,Peter

Kerkhof,Joost van den

Bos; Electronic

Commerce Research

and Applications

for judging the

trustworthines

s of an online

store than the

overall

reputation of

the store or

assurance seals

23 Re-examining the

influence of trust on

online repeat

purchase intention:

The moderating role

of habit and its

antecedents; Chao-

Min Chiu,Meng-Hsiang

Hsu,Hsiangchu

Lai,Chun-Ming Chang;

Decision Support

Systems

To test the

moderating

role of habit on

the

relationship

between trust

and repeat

purchase

intention

Utilitarian

value, hedonic

value,

familiarity,

satisfaction,

value, trust,

habit, repeat

purchase

intention

survey with

454

respondents

The results indicate

that a higher level of

habit reduces the

effect of trust on

repeat purchase

intention. Also,

value, satisfaction,

and familiarity are

important to habit

formation.

24 Failure to deliver?

Linking online order

fulfillment glitches

with future purchase

behavior; Shashank

Rao,Stanley E.

Griffis,Thomas J.

Goldsby; Journal of

Operations

Management

It investigates

operations

failures in

online retailing

order

frequency,

order size,

customer

order anxiety

online survey

by retailer

Adverse post-glitch

reactions are seen in

several dimensions

of customer

shopping behavior –

order frequency and

order size decrease,

while customer

anxiety level

increases.

25 Customization of the

online purchase

process in electronic

retailing and customer

satisfaction: An online

field study; Sriram

Thirumalai,Kingshuk K.

Sinha; Journal of

Operations

Management

It investigates

the

customization

of the online

purchase

process in

electronic

retailing

decision

customization,

transaction

customization

analysis of

online

websites of

422 retailers

The results indicate

that decision

customization is

positively associated

with decision-

making sub-process;

and transaction

customization is

positively associated

with purchase

27

transaction sub-

process.

26 Examining drivers of

online purchase

intensity: Moderating

role of adoption

duration in sustaining

post-adoption online

shopping; Chuanlan

Liu,Sandra Forsythe;

Journal of Retailing

and Consumer

Services

To examine

whether the

early adopters

of the online

channel are

more likely to

buy wide range

of products

and more

frequently than

the late

adopters.

(1)

Usefulness-

functional

performance

(2)

Enjoyment-

Hedonic

performance

(3) Internet

usage-

facilitating

conditions (4)

product risk

(5) early and

late adoption

online survey

with 789

responses

Results showed

factor effects on

predicting purchase

intensity are

different across the

groups of early and

late adopters.

27 Satisfaction and post-

purchase intentions

with service recovery

of online shopping

websites: Perspectives

on perceived justice

and emotions; Ying-

Feng Kuo,Chi-Ming

Wu; International

Journal of Information

Management

It explores

post-recovery

satisfaction

and post-

purchase

intentions from

the

perspectives

on perceived

justice and

emotions

Distributive

Justice,

Procedural

Justice,

Interactional

justice,

positive &

negative

emotions

Test on 20

scenarios (five

failures, four

recovery

strategies and

others)

distributive and

procedural justice

increases positive

emotions and

decreases negative

ones while

interactional justice

only increases post-

recovery satisfaction

of customers

28 The influence of online

word-of-mouth on

long tail formation; Bin

Gu,Qian Tang,Andrew

B. Whinston; Decision

Support Systems

It studies the

demand side

factors by

showing that

online

information

also influences

consumers'

evaluation of

product quality

Review

Volume,

Product age

and online

survey data

collection

(1) consumers tend

to ignore online

information

inconsistent with

their prior beliefs (2)

positive reviews

improve the sales of

popular products

more than the sales

of niche products,

28

while negative

reviews hurt niche

products more than

popular products

29 Identification of

influencers —

Measuring influence in

customer networks;

Christine Kiss,Martin

Bichler; Decision

Support Systems

To examine the

customer

network data

and identify

major

influencers

Customer

relationship

management,

Viral

marketing,

Centrality,

Network

theory, Word

of mouth

marketing

call data from

a telecom

company is

analyzed

There is a significant

lift when using

central customers in

message diffusion,

but also found

differences in the

various centrality

measures

depending on the

underlying network

topology and

diffusion process

30 Effect of Consumer

Beliefs on Online

Purchase Behavior:

The Influence of

Demographic

Characteristics and

Consumption Values;

Girish Punj; Journal of

Interactive Marketing

It tests the

effect of beliefs

on online

purchase

behavior by

demographic

characteristics

and by

consumption

values and the

tendency to

research

products prior

to making a

purchase.

(1)

demographic

characteristics

such as

income,

education,

and

generational

age

(2)consumptio

n values such

as the

inclination to

consider many

alternatives

before making

a choice, the

enjoyment of

shopping

telephone

interviews of

a sample of

1684 Internet

users

The higher-income

online shoppers

relate to the time-

savings features and

more educated

customers relate to

the potential these

environments offer

in finding products

31 Online information

search termination

patterns across

product categories

and consumer

demographics; Amit

It investigate

consumer

online

information

search

termination

Information

search,

consumer

learning

consumers

were asked to

recall the

exact amount

of time that

they spend

consumer learning

occurs when

consumers search

across search goods,

but not when they

29

Bhatnagar,Sanjoy

Ghose; Journal of

Retailing

patterns, and

relate the

differences to

product

categories and

consumer

characteristics

searching for

each category

search across

experience goods

32 Perceived Quality of

Online Shopping: Does

Gender Make a

Difference?; Rose

Sebastianelli,Nabil

Tamimi & Murli Rajan;

Journal of Internet

Commerce

It examined for

gender-based

differences in

perceptions

about factors

affecting the

perceived

quality of

online retailers

reliability,

accessibility,

ordering

services,

convenience,

product

content,

assurance,

and credibility

online survey women place

significantly more

importance on

assurance than do

men, rest variables

are comparable for

both gender

33 From spending to

understanding:

Analyzing customers

by their spending

behavior; Philipp E.

Otto,Greg B.

Davies,Nick

Chater,Henry Stott;

Journal of Retailing

and Consumer

Services

To find out the

relation

between

spending

behavior and

personal

characteristics

of customers

Leisure &

Travel,

General,

Maintenance,

Regulars, Risk

& Social,

Service

Orientation,

Future

Orientation

offline survey

of 370

responses

It gives a systematic

understanding of

customer behavior

and the relation

between the

spending behavior

and personal

characteristics of

customers

34 Do Price Charts

Provided by Online

Shopbots Influence

Price Expectations and

Purchase Timing

Decisions?; Wenzel

Drechsler, Martin

Natter; Journal of

Interactive Marketing

It tests

whether price

charts supports

consumers in

forming

expectations

about future

prices

Price

expectations,

Purchase

timing,

Showboats,

Price

comparison

sites,

Information

visualization

Survey while

taking

purchase

decisions after

viewing a

particular

price chart (63

participants)

The results of this

study show that the

provision of past

prices leads to

strong adjustments

of price

expectations

depending on price

chart characteristics

30

35 The effects of buyer

identification and

purchase timing on

consumers’

perceptions of trust,

price fairness, and

repurchase intentions;

Dhruv Grewal,David

M.

Hardesty,Gopalkrishna

n R. Iyer; Journal of

Interactive Marketing

It examines the

role of two

price

segmentation

tactics and

assess their

effects on

consumer

perceptions of

trust, fairness

of the price

differences,

and repurchase

intentions

consumer

perceptions of

trust, fairness

of the price

differences,

and

repurchase

intentions

online &

offline survey

data

Result shows that

consumers report

lower levels of trust,

price fairness, and

repurchase

intentions when

Internet-enabled

buyer identification

techniques are used

to segment

consumer markets

36 An empirical study of

Web browsing

behaviour: Towards an

effective Website

design; Gek Woo

Tan,Kwok Kee Wei;

Electronic Commerce

Research and

Applications

It examines

user Website

behaviour to

understand

Website design

Website

design, User

performance,

Cognitive

mapping, Way

finding

Interview of 6

users (3 male

and 3

females)

Result shows the

importance of user’s

memory on

navigation to the

visual effects of the

Website features on

the user’s

perception

37 Investigating the

effect of website

quality on e-business

success: An analytic

hierarchy process

(AHP) approach;

Younghwa

Lee,Kenneth A. Kozar;

Decision Support

Systems

It investigates

website quality

factors, their

relative

importance in

selecting the

most preferred

website, and

the

relationship

between

website

preference and

financial

performance.

(1)

Information

Quality (2)

Service

Quality (3)

Systems

Quality (4)

Vendor

Specific

Quality

field study of

156 online

customers

and 34

managers/des

igners of e-

business

companies

It identified

different relative

importance of each

website quality

factor and priority

of alternative

websites across e-

business domains

and between

stakeholders.

31

38 The relationships

among service quality,

perceived value,

customer satisfaction,

and post-purchase

intention in mobile

value-added services;

Ying-Feng Kuo,Chi-

Ming Wu,Wei-Jaw

Deng; Computers in

Human Behavior

To construct an

instrument to

evaluate

service quality

of mobile

value-added

services and

have a further

discussion of

the

relationships

among service

quality,

perceived

value,

customer

satisfaction,

and post-

purchase

intention

(1) Service

Quality

(2)Perceived

Value (3)

Customer

Satisfaction

(4) Post-

purchase

intention

Questionnaire

based survey

(1) service quality

positively influences

both perceived

value and customer

satisfaction; (2)

perceived value

positively influences

on both customer

satisfaction and

post-purchase

intention; (3)

customer

satisfaction

positively influences

post-purchase

intention; (4) service

quality has an

indirect positive

influence on post-

purchase intention

through customer

satisfaction or

perceived value; (5)

among the

dimensions of

service quality,

“customer service

and system

reliability” is most

influential on

perceived value and

customer

satisfaction; (6) the

proposed model is

proven with the

effectiveness in

explaining the

relationships among

all the variables

32

39 Simulating changing

consumer

preferences: A

dynamic conjoint

model; Andras Vag;

Journal of Business

Research

To model the

association

between

consumers'

communication

and sales

(1) Product

Preferences

(2)Post

Purchasing

satisfaction

(3) Purchasing

motivations

(4)Consumer

behavior and

ad options

Using 5

methods: (1)

conjoint

analysis, (2)

multi-agent

simulation, (3)

social network

analysis (4)

consumer

behavior

models, and

(5) word-of-

mouth

research

Result shows a time-

series of consumers'

aggregated

decisions, which

shows that

alongside the art of

surveying, a new

domain is emerging:

the art of model-

fitting, or feeding

models with specific

field data.

40 The changing dynamic

of consumer behavior:

implications for cross-

cultural research;

Susan P. Douglas, C.

Samuel Craig;

International Journal

of Research in

Marketing

This paper

examines the

critical issue of

defining the

appropriate

unit of analysis

in cross-

cultural

research and

proposes a

new definition.

Cross-cultural

research, Unit

of analysis,

Consumer

behavior,

Research

design

Analyzed

three cross-

cultural

studies

Each design relates

to a different type

of research issue

and provides a

different approach

to dealing with the

increasingly

problematic issue of

isolating the culti-

unit from cultural

contamination to

rule out alternative

explanations

41 The dynamics of

consumer behaviour:

On habit, discontent,

and other fish to fry;

Joachim

Scholderer,Torbjørn

Trondsen; Appetite

It examines the

role of past

behavior and

habit in the

overall

structure of

consumer

behavior

Consumer

attitudes,

Consumer

behavior,

Habit, Barriers

to

consumption

Survey of

4184

respondents

It shows higher

consumption of

traditional seafood

led to increasingly

negative evaluations

of the product

supply.

42 Social influence and

dynamic demand for

new products; M.-G.

Cojocaru,H. Thilleb,E.

Thommes,D. Nelson,S.

Greenhalgh;

To model of

the evolution

of consumers'

preferences for

new versions

of established

Time

dependent

Consumer

preferences,

group

dynamics,

Sensitivity

analysis of the

evolution of

consumer

preferences

Result shows

adoption of new

variants of well-

established

products is highest

in two cases: when

33

Environmental

Modelling & Software

products in a

differentiated

market setting

social

influence

the proportion of

innovators is small

and the imitators'

preferences change

based more on

variant's attributes

than popularity, or

when the

proportion of

innovators is higher

and the imitators'

preferences change

based more on

product's

popularity.

43 Personality and social

attitudes: Evidence for

positive-approach

motivation; Philip J.

Corr;Shaun

Hargreaves-Heap;Kei

Tsutsui;Alexandra

Russell;Charles Seger;

Personality and

Individual Differences

To relate social

attitudes and

related

cognitive

constructs

Social

attitudes,

Prejudice,

Personality,

Right-Wing

Authoritariani

sm, Social

Dominance

Orientation,

Need for

Cognition,

Need for

Closure

survey to

measure

personality

and social

attitude

Results revealed: (a)

positive-approach

motivation is

consistently related

to social attitudes;

and (b) negative-

avoidance

motivation played a

part in Need for

Cognition

(negatively related)

and Need for

Closure (positively

related).

44 Comparison of

product bundling

strategies on different

online shopping

behaviors; Tzyy-Ching

Yang, Hsiangchu Lai;

Electronic Commerce

Research and

Applications

To compare

the

performance of

decision-

making on

product

bundling based

on the types of

data on online

shopping

behaviors.

Online

behavior,

Product

bundling,

Shopping cart,

Market basket

analysis,

Association

rules

Survey of

1500

customers

Result shows better

decisions are made

on the bundling of

products when

browsing and

shopping-cart data

are integrated than

when only order

data or browsing

data are used.

34

45 Identity-based

consumer behavior;

Americus Reed II,

Mark R. Forehand,

Stefano Puntoni, Luk

Warlop; International

Journal of Research in

Marketing

(1) to present

an inclusive

definition of

identity

(2) to identify a

series of

important

“identity

principles” that

connect the

various

streams of

literature

(1) Identity

Salience (2)

Identity

Association

(3) Identity

Relevance (4)

Identity

Verification

and (5)

Identity

Conflict

In-depth past

literature

analysis

identity formation

and expression

depends on: (1)

Identity Salience (2)

Identity Association

(3) Identity

Relevance (4)

Identity Verification

and (5) Identity

Conflict

46 Online drivers of

consumer purchase of

website airline tickets;

Tomás Escobar-

Rodríguez, Elena

Carvajal-Trujillo;

Journal of Air

Transport

Management

to examine the

different

drivers of

online airline

ticket

purchasing

behavior and

to validate a

conceptual

framework

(1)

Performance

Expectancy

(2)Effort

Expectancy (3)

Social

Influence

(4)Facilitating

Conditions (5)

Hedonic

Motivations

(6) Price

Saving

orientation (7)

Habit (8)

Behavioral

Intention (9)

Use Behavior

English and

Spanish

Questionnaire

(1360

respondents)

Result shows that

the main predictors

of online purchase

intention are, in

order of relevance:

habit; price saving;

performance

expectancy; and

facilitating

conditions.

47 Brand orientation and

market orientation —

From alternatives to

synergy; Mats Urde,

Carsten Baumgarth,

Bill Merrilees; Journal

of Business Research

It explores the

interaction

between brand

orientation and

market

orientation

(1) Identity

driven

branding (2)

Image Driven

Branding (3)

Inside-out

approach (4)

Outside-in

approach

Intensive

literature

study

It proposes a hybrid

between brand and

marketing

orientation.

35

48 Consumer choice

behavior in online and

traditional

supermarkets: The

effects of brand name,

price, and other

search attributes;

Alexandru M.

Degeratu, Arvind

Rangaswamya, Jianan

Wu; International

Journal of Research in

Marketing

To examine the

relationship

between

Consumer

choice

behavior and

brand names,

price sensitivity

and other

search

attributes

Brand value,

Choice

models, E-

commerce,

Grocery

products,

Internet

marketing,

Price

sensitivity

Survey of 300

subscribers

and 1039

panelists who

shopped in

the grocery

chain

(1) Brand names

become more

important online in

some categories but

not in others

depending on the

extent of

information

available to

consumers. (2)

Sensory search

attributes,

particularly visual

cues about the

product, have lower

impact on choices

online, and factual

information have

higher impact on

choices online. (3)

Price sensitivity is

higher online.

49 The role of product

brand image and

online store image on

perceived risks and

online purchase

intentions for apparel;

Mariné Aghekyan-

Simonian, Sandra

Forsythe, Wi Suk

Kwon, Veena

Chattaraman; Journal

of Retailing and

Consumer Services

It examines

and compares

the impact of

two of the

most

important risk

reducers for

online apparel

shopping –

product brand

image and

online store

image – on

specific types

of perceived

risks and online

purchase

intentions for

apparel.

(1) Product

Brand image

(2) Online

store image

(3) Financial

risk (4)

Product Risk

(5) Time risk

(6) Purchase

intention

web based

survey with 73

respondents

and 37

product

brands

The results show

that product brand

image influences

consumers' online

purchase intentions

both directly and

indirectly by

reducing various risk

perceptions. Online

store image impacts

purchase intentions

indirectly by

decreasing risk

perceptions.

36

50 Beyond technology

acceptance: Brand

relationships and

online brand

experience; Anna

Morgan-Thomas,

Cleopatra Veloutsou;

Journal of Business

Research

It examines

insights from

marketing and

information

systems

research to

arrive at an

integrative

model of

online brand

experience

(1) Perceived

ease of use (2)

Brand

Reputation (3)

Perceived

usefulness (4)

trust (5)

Online brand

experience (6)

Behavioral

intentions (7)

satisfaction

(8) online

brand

relationships

survey of 456

users of

online search

engines

The results

demonstrate that

trust and perceived

usefulness positively

affect online brand

experience. Positive

experiences result in

satisfaction and

behavioral

intentions that in

turn lead to the

formation of online

brand relationship.

Table 1: List of Literary works reviewed

37

Flowchart 1. Identify Online Shoppers

2. Most preferred product category

a. Apparels

b. Accessories

c. Electronics

d. Books

e. Beauty and Personal Care

f. Furnishing

g. Computer Hardware and Software

h. Healthcare

3. Personality type of Customer (Big-Five Personality traits)

a. Openness

b. Conscientiousness

c. Extraversion

d. Agreeableness

e. Neuroticism

4. Divide online shoppers into segments based on their personality

5. Identify how each segment get effected by following factors

a. External Factors

i. Price Difference between Online and Offline products

1. Online coupons

2. Price offs

3. Buy one get one

ii. Website features

1. Design

a. Website features

b. Website theme

2. Navigation

a. Easy navigation

b. Less number of clicks

3. Content Display

a. Out-of-stock products

b. Variety of products

4. Safe transaction system

iii. Post-Purchase services

1. Return Policy

2. Delivery time

3. Customer Service

b. Internal Factors

i. Influencers

38

1. Family/Relatives

2. Friends and peers

3. Bollywood figures

4. Advertisements

ii. Demographics

1. Age

2. Income

3. Gender

4. Employment

6. Check their likeliness for branded and lesser-known branded products in online retail shop

according to product type

Above mentioned steps can be shown in a flowchart, which starts with our respondents i.e. online Indian

shoppers. Classify Indian online shoppers based on their personality type and Big-five personality trait

model. These segments are then analyzed to check the impact of “Brand-name” on various product

categorize and to check the important features of an online store.

Figure 1: Flowchart for the study

39

Methodology

Research Methodology

For the research, following steps were conducted:

1. The subject of research was decided to be “Online consumer behavior based on the personality

of Indian online shoppers”.

2. The literature survey of 55 journals was done to understand the previous work done on the

online consumer behavior.

3. Based on the findings of Literature Survey, variables were decided for the study and flowchart of

study was prepared.

4. Based on the variables from literature survey, research was divided into two parts, one research

objective to cover the importance of brand name during online shopping and the other research

objective was to cover the most preferred characteristics of online shopping.

5. Qualitative Research was done for 22 respondents, mainly of age group 20-30 years old, to

understand the current trend and shopping behavior of online customers.

6. Based on the findings on qualitative research, hypothesis was formed to test and confirm the

online shopping behavior.

7. As a part of quantitative survey, an online survey was conducted to capture the consumer

behavior of Indian online shoppers. The online survey was float mainly in Tier-I and Tier-II cities

of India.

8. Using SPSS software and Marketing Engineering software in Excel, the results of online survey

was analyzed to test the hypothesis and results were presented.

Variables Based on the study done on past available literatures of features affecting online consumer behavior

following variables were identified, which are classified into two categorize:

External factors:

o On time delivery

o Customer service

o Return Policy

o Safe transaction

o Website design

o Availability of variety

Internal factors:

o To spend time

o Price sensitive

o Influencers

o alternate to offline

Variables from literature survey for understanding the importance the brand-name on online consumer

behavior are different product categorize.

40

Scales Likert scale of point 1 to 5 is used in the online survey to gather the data from respondents.

Survey Method To understand the online consumer behavior of Indian shoppers an online survey was conducted. It

helped us understand the features that they give value to in an online store. Also, it helped us understand

the value of “Brand-name” while shopping online for different product categorize. The online survey was

float mainly in Tier-I and Tier-II cities of India.

Profile of respondents Respondents were Indian online shoppers from Tier-I and Tier-II cities.

Data Analysis tools SPSS software and Marketing engineering software in Excel are majorly used to analyze the data. It helped

in testing the hypothesis and to understand the results

Sample Size

The online survey received 243 responses in total. The variation in gender, age, personality type etc. is

maintained for the respondents.

Sample Design Our target market is Indian online shoppers of age group 15 to 45, male and female both. We maintained

the sample design according to our target market. Out of 243 responses which we received, we can classify

them into following:

Gender wise classification:

o Male: 117 respondents

o Female: 126 respondents

Age wise classification:

o 15 to 18yrs: 18 respondents

o 18 to 22 years old: 45 respondents

o 22 to 30 years old: 162 respondents

o 30 to 45 years old: 18 respondents

Personality wise classification:

o Extraversion: 14 respondents

o Agreeableness: 59 respondents

o Conscientiousness: 14 respondents

o Neuroticism: 15 respondents

o Openness: 141 respondents

Income wise classification:

o Less than 5L: 51 respondents

o 5L to 10L: 104 respondents

o 10L to 15L: 57 respondents

o 15L to 20L: 13 respondents

41

o More than 20L: 18 respondents

Employment wise classification:

o Student: 90 respondents

o Home-maker: 42 respondents

o Unemployed: 15 respondents

o Full time employee: 15 respondents

o Part time employee: 81 respondents

42

Results The results can be divided into two categories, first, importance of various factors according to the

personality of online shoppers and second, impact of brand name in the behavior of online shoppers for

various product categorize.

Importance of internal and external factors

Let’s first check the importance of various factors for different personality type of online shoppers and for

different product categories. Results for Agreeableness personality type online shoppers are shown in

Result-1. It shows that for apparels and accessories, availability of variety is the most important factor for

the customers. For Electronics, Books, Computer hardware & Software and Healthcare products customer

service is the most important feature for the customers. For the beauty and personal care products the

most important feature is time to spend online whereas for furniture influencers are important while

shopping online for Indian customers.

For Openness personality type online shoppers, following results are there. It shows the most important

factor is the return policy of the online store and the least important is that of considering online store

just as an alternative to the offline store. Refer to Result-2. It shows that for apparels, accessories and

furniture, website design and on-time delivery is the most important factor for the customers. For

Computer hardware & software and Healthcare products price is the most important feature for the

customers. For the beauty and personal care products influencers are important and for books and

electronic products availability of variety is the utmost important feature.

For Neuroticism personality type online shoppers, following results are there. It shows the most important

factor is the return policy of the online store and the least important is the safe online transaction of the

amount. Refer to Result-3. It shows that for apparels and accessories, availability of variety is the most

important factor for the customers. For Electronics and books spending time online is the most important

feature for the customers. For Computer hardware & software and Healthcare products influencers are

very important. For the beauty and personal care products the most important feature is correct price

whereas for furniture on-time delivery is the most important feature while shopping online for Indian

customers.

For Extraversion personality type online shoppers, following results are there. It shows the most important

factor is the return policy of the online store and the least important is that of considering online store

just as an alternative to the offline store. Refer to Result-4. It shows that for apparels, accessories and

electronics, online stores are an alternative to the offline stores. For the books, furniture and beauty &

personal care products the most important feature is correct price. For Computer hardware & software

on-time delivery is the most important feature whereas for Healthcare products return policy is very

important.

For Conscientiousness personality type online shoppers, following results are there. It shows the most

important factor is the return policy of the online store and the least important is the customer service

provided by the store. Refer to Result-5. It shows that for apparels and accessories, spending time online

is the most important feature for Indian customers. For Computer hardware & software and furniture

43

correct price is very important in an online store. For healthcare products safe transactions are important

and for books website design is of utmost important.

The overall results shows that the most important factor for any online shopper is the return policy

provided by the store and the least important is that of considering online store just as an alternative to

the offline store.

Table 2: Importance of online store features based on the personality type

Therefore, here we propose our model to map personality and importance given to the factors.

Figure 2: Relation between personality and online store features

Impact of Brand name The results shows that the product which has greater impact of brand name is Health care and beauty

care products whereas the products which has lesser brand name impact are books and furnishing. Refer

to Result-6.

44

The behavior of online shoppers also vary for the brand name for different product categorize. Refer to

Result-7. For Extraversion personality type customers “Brand-name” is very important while purchasing

electronics and least important while purchasing beauty & personal care products. For Agreeableness

personality type customers “Brand-name” is very important while purchasing books and least important

while purchasing electronics. For Conscientiousness personality type customers “Brand-name” is very

important while purchasing electronics and least important while purchasing books. For Neuroticism

personality type customers “Brand-name” is very important while purchasing computer software &

hardware and least important while purchasing accessories. For Openness personality type customers

“Brand-name” is very important while purchasing books and least important while purchasing electronics.

Overall the following results shows the impact of brand name for different product categorize on online

shoppers of different personality.

Table 3: Importance of Brand-name based on the personality type

Therefore, here we propose our model to map the personality and product categorize based on the

importance given to the Brand name.

Figure 3: Relation between personality type and product category with regard to brand-name

45

Discussion The primary objective of this article is to examine the impact of personality on online shopping behavior.

It examined impact of personality on majorly two terms, first, variation in shopping behavior of various

personality type customers in terms of internal as well as external factors related to online shopping,

second, importance given to the brand name by customers of different personality type in various product

categories. The findings are discussed in detail as follows.

Impact of internal and external factors Our results suggest that on the basis of their personality, people seek different attributes for different

products while making online purchase.

Overall return policy is the most important factor for people while making online purchase. Our finding

also suggests that in India only a minor portion of population sees online shopping as an alternative to

brick and mortar (by alternate we mean that customers generally don’t window shop online ,i.e, they

don’t earmark a product as to be bought later offline) . This clearly shows that most of the people have

clearly defined needs for which they resort to online shopping. This gives us a hint that Indian consumers

have evolved enough to show a distinct online buying behavior. Some of the interesting behavioral aspects

that we observed while doing our survey include: “People above 40 generally see online shopping as a

hassle”, whereas teenagers see online environment as a “hang-out spot”.

We observed that agreeable personality type deviate from other personalities in the point that for them

customer policy and return policy are the most important attribute while purchasing online, whereas, for

other personalities return policy is the only most important criteria.

All the personality types differ in their least preferred attribute, for agreeable personality influencers are

least important, for open type personality alternate to offline is the least important attribute, for

conscientious personality customer service is least important, for Neuroticism personality safe transaction

is least important. This variation doesn’t merely end here. For different product type these personality

types show different behavior. This shows that online marketer should have different web site attributes

for different products.

Overall

Agreeablen

ess

Openness Conscientious

ness

Neuroticis

m Extraversion

Apparels

Customer

Service &

Return

Policy

Availability

of variety

Website

design & on

time

delivery

To Spend

Time

Availability

of variety

Alternate to

offline

Accessories

Customer

Service &

Return

Policy

Availability

of variety

Website

design & on

time

delivery

To Spend

Time

Availability

of variety

Alternate to

offline

46

Electronics

Availability

of variety

Customer

Service

Availability

of variety &

Price

sensitive

Influencers

To Spend

Time

Alternate to

offline

Books

Customer

Service

Customer

Service

Availability

of variety

Website

design

To Spend

Time

Price

Sensitive

Beauty and

Personal

Care

Customer

Service

To Spend

Time

Influencers

On time

delivery &

return policy

Price

Sensitive

Price

Sensitive

Furnishing

Availability

of variety

Influencers

Website

design & on

time

delivery

Price Sensitive

On time

delivery &

to spend

time

Price

Sensitive

Computer

Hardware

and

Software

Price

Sensitive

Customer

Service

Price

Sensitive

Price Sensitive

Influencers

On time

delivery

Healthcare

Customer

Service

Customer

Service

Price

Sensitive

Safe

transactions

Influencers

Return

Policy

Table 4: Importance of online store features based on the product category

This table can serve as an exhaustive guide to online promotion and advertising for different products.

For example, for computer hardware, e-retail firms should focus more on giving discounts and offers than

website design. Similarly for beauty products, beauty tips and right usage method of cosmetic products

should be shown on websites.

E.g., an ideal furniture selling portal should: show variety of products, show customer feedbacks, should

give discounts and highlight on time delivery, whereas,

For beauty products, visiting the web site should be made an experience by personalized beauty tips and

consumer feedback.

Impact of the brand name

Our results show that importance of “Brand name” while purchasing online, is a function of personality

and product type. While “Brand Name” is most important in case of Health Care related products, it is not

47

as important in case of books. This can be explained by the fact that brand name in health care is

synonymous with trust. Whereas, brand of publisher does not directly affect the quality of book.

As per our findings, for Extravert Personality type customers, “Brand Name” is of prime importance in

case of Electronic products and least important for Beauty and Personal Care products. For Neuroticism

personality type customers, “Brand Name” is most important while purchasing Computer hardware and

software from an online store, but while buying accessories “Brand Name” is not as important. Agreeable

and Open Personality type customers’ shows similar behavior while buying online. For both of them Brand

Name is most important while buying books and least important for electronics, which is completely

opposite to the behavior of Extravert type customers. Conscientiousness personality type customers’

show exactly opposite behavior to that of Agreeable and Open Personality type customers’. They give high

importance to “Brand name” for electronic products and minimum value to books.

Shopping behavior of Indian online customers

From the literature survey and results of our survey, we found out that there are certain points of parity

and points of difference between Indian and western online consumers.

Similar to western customers, Indian customers also show significant difference between their online and

offline decision making process. Indian online customer buying criteria include factors like process value,

outcome value and shopping enjoyment.

Our research findings suggest that return policy is the most important criteria for Indian customers.

Whereas, very few number of Indian online shoppers see online as an alternate to offline. This finding is

opposite to the behavior of customers from western culture as they consider online store as an alternative

to the offline store.

Even though behavior changes with personality type and product type, overall, return policy, post

purchase services, availability of variety and web site design are the key influences for Indian online

consumers. These factors hint towards the fact that Indian consumers are more of experience oriented

rather than merely product oriented while online shopping.

For certain product types, factors like social influencers, spending time online and price sensitivity also

play a major role. This work clearly articulates different needs of people while purchasing different

products.

This fact again hints towards the idea that Indian consumers see an online product as a package of core

product and associated services. To be successful an e-retail marketer needs to make right combination

of product and associated service for different consumers to leave a lasting impression.

For e.g. for apparels, it is ideal to club this product with service like wide and detailed range of collection,

good and easy to navigate web-site design, opportunity to get entertained while purchasing apparels

online.

Past research works in the western countries showed that they have delved on the idea of customizing

web services to suit consumers. This study suggests to take this idea one step further to an extent where

services are customized by the personality and product type.

48

Unlike western customers, Indian customers above 35 years of age show very high resistance to purchase

online. This coupled with the fact that online reach is low in India, results in decrease in e-retail market.

To overcome this hurdle, return policy and concept like cash on delivery come in very handy.

Word of mouth oriented promotional activities for e-retail, probably even in offline environment, can be

of immense help to attract customers of age group 35+ to shop online. Therefore, the importance of

product reviews and ratings are very important for online stores.

Not much difference was found between male and female online shopping behavior. But, females tend

to be an important influencing factor for males while purchasing online. Also, for females promotional

factors are the most attractive feature of an online store and for male customers the website design and

ease of navigation is the most important feature in an online store.

Brand name plays a very important role in generating trust in the website/product for an online shopper.

But efficacy of brand name is different for different products. Whereas, it is very high in healthcare

products, it is not as high in case of books for Indian online customers. Even this behavior changes with

personality type as for openness and conscientiousness personality types, importance of brand name in

case of books is very high.

Generally, brand name is more important when information about fewer attribute of the product is

available to consumers. This explains the importance of brand name for health care in India. But in Indian

context many other factors come into play while explaining the importance of brand name.

For e.g. because of few number of pan India brands in furniture, importance of brand name is low in the

category of furniture in an online store.

49

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Appendix

Appendix 1

Figure 4: Usage of Online shopping cart

Appendix 2

Figure 5: Online purchase intent using Personality

55

Appendix 3

Figure 6: Relation between customer satisfaction and loyalty

Appendix 4

Figure 7: Predictors of online purchase intention

Quantitative Questionnaire

1. Age

a. Less than 18yrs old

b. 18yrs to 22yrs old

c. 22yrs to 30yrs old

d. 30 to 45yrs old

e. More than 45years old

2. Income (annually)

a. Less than 5L

b. 5L to 10L

c. 10L to 15L

d. 15L to 20L

e. More than 20L

3. Gender

a. Male

b. Female

56

4. Employment Status

a. Student

b. Home-maker

c. Unemployed

d. Full time employee

e. Part time employee

5. Have you ever shopped online:

a. Yes

b. No

6. I see myself as:

Disagree

Strongly

Disagree

Moderately

Disagree

a little

Neither

agree nor

disagree

Agree

a little

Agree

moderately

Agree

strongly

I like going out

and to make

friends

I remain

energetic in

regular things

I generally don’t

agree with ideas

different from

mine

I feel people can

trust me under

difficult times

I like to have a

routine in my

life

I feel uneasy

under pressing

situations

I easily get upset

I like trying out

new stuff

I like to spend

time with myself

I understand

problems of

people around

57

me and like to

help them

I generally don’t

find my things in

place

I don’t flow with

my emotions in

pressing

situations

I generally come

up with creative

solutions

For Scoring: In scoring students should reverse the numbers they place in response to items 2, 4, 6, 8, and 10 (1 = 7, 2 = 6, 3 = 5, 4 = 4, 5 = 3, 6 =

2, 7 = 1). Then they should combine the numbers for items 1 and 6 to obtain their extraversion score, 2 and 7 for agreeableness, 3 and 8 for

conscientiousness, 4 and 9 for emotional stability, and 5 and 10 for openness to experience. Scores can range from 1 to 14 for each trait, with

higher scores reflecting strong exhibition of a trait.

7. Frequency of doing online shopping for the following product are

Never Once in a

year

Once in 6

months

Once in 3

months

or more

Once in

a month

or more

Every

fortnight

Every

week

Apparels

Accessories

Electronics

Books

Beauty and Personal

Care

Furnishing

Computer Hardware

and Software

Healthcare

8. How much you agree or disagree with each of the following statements in terms of your

experience with online shopping

Disagree

Strongly

Disagree

Moderately

Disagree

a little

Neither

agree

nor

disagree

Agree

a

little

Agree

moderately

Agree

strongly

I can’t tolerate late delivery

of my order

58

Late delivery is fine if they

can inform me in advance

If I call customer service

because of any problem

they should be able to solve

it

I don’t like when customer

service people keep me in

line for a long time

Return Policy should be

there for online stores

I will be glad if they can

come to collect as a part of

return policy

Platform used for online

transaction should be

mentioned before checkout

point

Its utmost important for me

that online store provides

safe platform for online

transactions

Website design and features

of online store attracts me

to shop in it

Easy navigation between

product categories or other

pages of online store helps

me in online shopping

I use online portal only

when it is not possible to

buy something offline

Variety of products and

brands should be available

in online stores

I don’t feel comfortable

making payment online

Out-of-stock products is a

big turn-off for me

I like to spend time

shopping online

59

I prefer to buy from an

offline store, if I get the

product in less price

I use online portal so that I

can later buy those products

offline

I don’t seek variety while

purchasing online

I don’t like to navigate much

while purchasing online

I buy from an online store

which provides the product

at the least price

Minimum price is not the

deciding factor for me while

choosing the online store to

buy

My family plays an

important role in deciding

store to purchase from for

any product

I consider my friend’s

recommendations while

deciding to buy anything

I feel peer-pressure while

choosing to buy anything

I get influenced by

Bollywood actor/actress

while deciding store and

product to purchase

I chose stores to shop from

based on its advertisements

9. I am ready to pay extra price for the prominent branded products as compared to lesser known

branded products.

a. Yes

b. No

10. Please rate following products in order of PREFERRENCE for premium brand over less known

brand/unbranded

60

Not at

all

preferre

d

Moderate

ly not

preferred

Somewh

at not

preferre

d

Neutr

al

Somewh

at not

preferre

d

Moderate

ly

preferred

Complete

ly

preferred

Apparels

Accessories

Electronics

Books

Beauty and

Personal Care

Furnishing

Computer

Hardware and

Software

Healthcare

Result-1

Figure 8: Perceptual Map for Agreeableness customers

ApparelsAccessories

ElectronicsBooks

Beauty and Personal Care

Furnishing

Computer Hardware and Software

Healthcare

On time delivery

Customer serviceReturn Policy

Safe transaction

Website design

Availability of variety

To spend time

Price sensitive

Influencers

Alternate to offlineI (61.9%)

II

(20

.6%

)

Perceptual Map for Agreeableness shoppers

61

Result-2

Figure 9: Perceptual Map for Openness customers

Result-3

Figure 10: Perceptual Map for Neuroticism customers

ApparelsAccessories

ElectronicsBooks

Beauty and Personal CareFurnishing

Computer Hardware and Software

Healthcare

On time deliveryCustomer serviceReturn Policy

Safe transaction

Website design

Availability of variety

To spend time

Price sensitive

Influencers

Alternate to offline

I (71.9%)

II

(20

.5%

)

Perceptual Map for Openness shoppers

Apparels

Accessories

Electronics

Books

Beauty and Personal CareFurnishing

Computer Hardware and Software

Healthcare

On time delivery

Customer service

Return PolicySafe transaction

Website designAvailability of variety

To spend time

Price sensitive InfluencersAlternate to offline

I (46%)

II (

22

.5%

)

Perceptual Map for Neuroticism shoppers

62

Result-4

Figure 11: Perceptual Map for Extraversion customers

Result-5

Figure 12: Perceptual Map for Conscientiousness customers

Apparels

Accessories

Electronics

Books

Beauty and Personal Care

Furnishing

Computer Hardware and Software

Healthcare

On time delivery

Customer service

Return Policy

Safe transaction

Website design

Availability of variety

To spend time

Price sensitive

Influencers

Alternate to offline

I (48%)

II (

34

.4%

)

Perceptual Map for Extraversion shoppers

ApparelsAccessories

ElectronicsBooks

Beauty and Personal Care

Furnishing

Computer Hardware and Software

Healthcare

On time delivery

Customer serviceReturn Policy

Safe transaction

Website designAvailability of variety

To spend time

Price sensitive

Influencers

Alternate to offlineI (41.8%)

II

(26

.1%

)

Perceptual Map for Conscientiousness shoppers

63

Result-6

Figure 13: Preference map for the importance of Brand-name

Result-7

Figure 14: Perceptual map to relate product categorize and personality types

Apparels

Accessories

Electronics

Books

Beauty and Personal Care

Furnishing

Computer …HealthcareI

II

Preference Map

Agreeableness

ConscientiousnessExtraversion

Neuroticism

OpennessApparels

Accessories

Electronics

Books

Beauty and Personal Care

Furnishing

Computer Hardware and Software

Healthcare

I (47.5%)

II

(35

.6%

)

Perceptual Map