Research paper - Online Consumer Behaviour

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
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
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
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
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;
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
mastery-approach
goals and negatively
related to
performance-
approach goals.
Third, both
avoidance goals and
both performance
goals were
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
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
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
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
both perceived
value and customer
satisfaction; (2)
perceived value
on both customer
satisfaction and
post-purchase
intention; (3)
customer
satisfaction
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
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
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
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
 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

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

Research paper - Online Consumer Behaviour

Research paper - Online Consumer Behaviour

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