Running Head: ONLINE CONSUMER BEHAVIORS 1 Online Consumer Behaviors 2 Online Consumer Behaviors John A. Smith & Jane L. Doe Kitchen Light University Abstract Internet usage has skyrocketed in the past few decades, along with this increase comes the increase in internet shopping by consumers. This research examines the following: · behaviors · motivations · attitudes All this are new form of consumer entity. Online consumer behavior has been studied for over 20 years and will undoubtedly be the source of many future researches as internet consumerism expands. This paper will examine the following research questions: 1. How do factors previously researched affect the online purchasing behavior of consumers? 2. What are the significant consumer behaviors both positive and negative that affect internet consumerism? By identifying these factors and variables, new strategies can be formulated and both consumer and supplier can gain knowledge and understanding of behaviors which exist. The purpose of this research paper is to integrate the varied research information together and draw coherent linkages to how consumer thoughts, attitudes and motivational behavior affect online buying, thus building a broader framework of analysis in which to build upon. Online Consumer Behaviors The Internet has been accessible to the public for over twenty years. It came upon the scene and has exploded in popularity like few things have ever done in the history of the world. Since the introduction of the World Wide Web, the interest in the value of commerce and individuals has been growing. Skeptical at first, online consumerism has steadily increased and along with it has come some positive and negative behaviors. The purpose of this research is to understand how individual behaviors affect online consumerism. According to Lars Perner, consumer behavior is defined as “the study of individuals, groups, or organizations and the processes they use to select, secure, use, and dispose of products, services, experiences, or ideas to satisfy needs and the impacts that these processes have on the consumer and society” (2008). By identifying the behaviors that support buying online and those which do not, businesses can help to increase profits and will help to assure their share of the market, as electronic trade may well out-step traditional buying in the not too distant future. Internet consumerism There are many variables to consider when outlining behaviors of Internet consumerism. 1. According to Delia Vazquez and Xingang XU, online consumer behavior is affected by five main things: · Attitudes towards online shopping · Motivations, such as price · Convenience · Hedonic motivations · Online information search (2009, p.409) If a person is positive about the experience of shopping on the Internet then that attitude will affect the outcome of purchasing online. Also online consumers feel more in control when they can search with relative ease, price.

1. Running Head: ONLINE CONSUMER BEHAVIORS
1
Online Consumer Behaviors
2
Online Consumer Behaviors
John A. Smith & Jane L. Doe
Kitchen Light University
Abstract
Internet usage has skyrocketed in the past few decades, along
with this increase comes the increase in internet shopping by
consumers.
This research examines the following:
· behaviors
· motivations
· attitudes
All this are new form of consumer entity. Online consumer
behavior has been studied for over 20 years and will
undoubtedly be the source of many future researches as internet
consumerism expands. This paper will examine the following
research questions:
1. How do factors previously researched affect the online
purchasing behavior of consumers?
2. What are the significant consumer behaviors both positive
and negative that affect internet consumerism?

2. By identifying these factors and variables, new strategies can be
formulated and both consumer and supplier can gain knowledge
and understanding of behaviors which exist. The purpose of this
research paper is to integrate the varied research information
together and draw coherent linkages to how consumer thoughts,
attitudes and motivational behavior affect online buying, thus
building a broader framework of analysis in which to build
upon.
Online Consumer Behaviors
The Internet has been accessible to the public for over twenty
years. It came upon the scene and has exploded in popularity
like few things have ever done in the history of the world. Since
the introduction of the World Wide Web, the interest in the
value of commerce and individuals has been growing. Skeptical
at first, online consumerism has steadily increased and along
with it has come some positive and negative behaviors. The
purpose of this research is to understand how individual
behaviors affect online consumerism.
According to Lars Perner, consumer behavior is defined as “the
study of individuals, groups, or organizations and the processes
they use to select, secure, use, and dispose of products,
services, experiences, or ideas to satisfy needs and the impacts
that these processes have on the consumer and society” (2008).
By identifying the behaviors that support buying online and
those which do not, businesses can help to increase profits and
will help to assure their share of the market, as electronic trade
may well out-step traditional buying in the not too distant
future.
Internet consumerism
There are many variables to consider when outlining behaviors
of Internet consumerism.
1. According to Delia Vazquez and Xingang XU, online
consumer behavior is affected by five main things:
· Attitudes towards online shopping
· Motivations, such as price

3. · Convenience
· Hedonic motivations
· Online information search (2009, p.409)
If a person is positive about the experience of shopping on the
Internet then that attitude will affect the outcome of purchasing
online. Also online consumers feel more in control when they
can search with relative ease, prices and special offers. This
price comparison is in itself, a great motivational tool. The fact
that more information is available online concerning products
also allows the consumer to feel that better information, will
lead to better decision making on their part.
Research was conducted through a self-given online
questionnaire. Important data was collected concerning the
scale items of attitude, motivations and searches of information.
The group consisted of students in three different age
categories.
1. The first were between 15 and 24.
2. The second group was between 25-34 years old.
3. The last group fell between the ages of 35 and 44.
· The 35-44 year old group was rated as first in Internet buying.
· The 25-30 year olds were next, followed by the younger
group.
· A further study was done through the use of email and
administered questionnaires.
· Two hundred students were surveyed in person and 300
students were asked to fill in an email survey.
· Between the two groups, 406 responded and participated in
the research.
Data analysis using a quantitative approach was used.
Reliability analysis was formulated and used to test the data
obtained. Canonical analysis was also used to help understand
the data and build a framework around online consumer
behavior.

4. The analysis showed that 49.8% of those surveyed were women
and 50% were male. The group under age 24 made up a little
less than two thirds of the total. Those over 24 accounted for
the rest. Respondents who had used the Internet for five years
or more represented 79% of the study. The results clearly
showed that online shopping motivations, information searches,
and attitude all had a significant affect on online purchases.
2. Other variables to consider in online consumer behavior are
online experience, sexual
preference and the primary place in which the Internet is
accessed. In a study performed by Koyuncu and Lien, research
showed that all three of these had “large statistically significant
effects on online shopping” (2003, p.721). They concluded that
consumers, who had more experience with the internet, felt
more comfortable navigating it. Consumers also felt safer in
using the internet at their residence or on the job, rather than
community computers. Sexual preference, according to their
research, showed that bisexuals bought online in greater
numbers than heterosexuals. This behavior may have resulted
because of the bias against this portion of the population that is
present in society. The survey which supports this data was
conducted by Georgia Institute of Technology. There were over
10,000 participants. The total amount of samples used was
8717. Data such as an individual’s demographic; economics,
sexual preferences, and primary places of online access were
collected. The findings showed 7026 considered themselves
online shoppers, while 1691 did not. The average for education
was considered, “some college” for both groups. Online
shoppers’ income was between $50 and $74K. The non-online
shoppers’ income was between $30 and $40K. The average ages
of both groups were between 36 and 40 years old. Almost 90%
were white and 60% were male. A little under half of all the
participants were married.

5. The conclusion of this research clearly identified that both the
primary place to access the Internet and sexual preference had
very important positive effects on online shopping.
Online shopping
Unlike shopping in a store on-site, making purchases online has
other positives associated with it. According to Anthony
Ammeter and Donghyun Kim, they stated “one of the most
important traits of online shopping is bidirectional
communication capability” (2008, p.9). They go on further to
explain how online shoppers have greater assess to
communicate with those they are buying from. This
communication can take place in such ways as bulletin boards
and e-mails. This gives consumers a perception of personalized
assistance. In contrast to this scenario, is the fact that we are
losing our ability to maintain a high level of customer service
on-site.
The employees many shoppers encounter seem more to be
filling a spot than actively engaging in helping consumers with
purchases or becoming knowledgeable about what they sell.
Online consumerism is not however without its apprehensions.
Set forth in the research by Janda Swinder were concerns. She
stated in her article that there were, “four consumer online
concerns, identified as privacy, security, credibility, and virtual
experience” (2008, p. 339). Each of these factors is considered
when people think of making online purchases. Privacy issues,
security, credibility and virtual experience have all shown to
have negative effects on consumer purchasing. It is relatively
simple for information to be collected from consumers
whenever one logs onto a site or makes a purchase.
Some information, such as name, address, phone number and
credit card, is gathered through direct questioning and other
information is gathered through tracking software.
This transference of information makes some consumers
nervous and they do not want to take the risk. Another point to
consider is the credibility of the person or business in which

6. one is dealing with. Questions arise about trust, description of
merchandise, warranties, shipment, returns, and follow-up
correspondence. Although this concern, though valid, has
according to research, had very limited negative effect on
consumer buying habits (2008).
Another negative behavioral pattern well documented is that of
compulsive buying tendencies. These tendencies to over buy can
have detrimental affects on the consumer, notably affecting
monies, feelings, and relationships. According to “The
Relationship Between Consumers’ Tendencies to Buy
Compulsively and Their Motivation to Shop and Buy on the
Internet,” somewhere between 5 and 9 percent of America’s
population could be identified as people who have a propensity
to compulsively buy (Kukar-Kinney, Ridgway, and Monroe,
2009). Motivators of this type of behavior include the very key
ingredients of online shopping. These motivations are the
following; items may be purchased at any time, shopping can be
done frequently, a broader variety exists, and also purchases
may be brought in private.
The actual detailed research conducted involved many aspects.
The first method of
research was a survey of over 300 people in 42 states. As
quoted from the article, “the sample consisted of 98.5% women,
63% of the respondents were married, the average age was 53
years, and the average household income was $82,000” (2009,
p.300). The penchant to buy compulsively was measured using a
buying scale that included six focuses. These scale items
included, unopened packages at home, labeled by others as a
shopaholic, how much time actually spent shopping, buying
unneeded items, buying unplanned items, and if the surveyed
considered themselves an impulse buyer.
Research was also conducted using a 22 statement survey in
which the surveyed agreed or disagreed with the following
statement, “In comparison to retail stores, I shop on the Internet

7. when buying clothing and accessories for myself because”
(2009, p.301). The 22 statements included areas that linked to,
“buying unobserved, product variety, social interaction, and
immediate positive feelings.” An analyses of the information
was obtained through a series of “linear regression analysis,
with individual shopping and buying motivations in the role of
the dependent variable, and compulsive buying index as an
independent variable” (2009, p.302).
The final research was defined as cluster analysis. Taken into
account were such categories as
· Demographics
· Age
· Gender
· Income
· Education level
· Marital status
· Average income spent at retail and internet stores
· Frequency of purchase
· The number of credit cards used
All of this research data was well defined and explained. The
findings of each method was then charted and analyzed with
easy to understand tables and terminology. In keeping with the
theme of the method section, the interpretations and conclusions
made by these researchers were very detailed and data
supported.
The results showed that compulsive online consumer behavior
was in part explained by motivations of the shopper. All
motives set forth in this study exhibited an important positive

8. connection to the compulsive buying scale except for one and
that was the product variety motive. The overall findings
concluded, as the researchers had hypothesized that
compulsive buying strongly affected consumers’ decisions to
make purchases using the Internet.
This research group acknowledges that one of its weaknesses
was the sampling of consumers used. Subjects were relatively
wealthy women, who frequented expensive internet retailers. I
believe, as they do, that this assessment represents a bias in the
general population. The research also only tracked the behavior
of women. Compulsive online consumer behaviors are not
gender specific and therefore this research, in my opinion, is
somewhat flawed. Another weakness noted in this study was the
amount of people surveyed in the first example with a total
number of a little over 300. I do however think that one of this
study’s greatest strengths was the broad base of surveys
conducted (2009).
Types of online behavior
There are differences in online behaviors as identified by
gender in the research of Janda (2008). Main differences
account for shopping behaviors, attitudes to technology, and
processing of information. Women were found to be more
venerable to risks and perceived risks as higher than that of the
male population. It was also found that women used the Internet
less often and were less confident about their online ability.
Females were found to enjoy the experience of shopping more
than men. Women leaned more toward the sites which provided
information and education about items.
The data for this gender research was gathered through surveys
that were handed out. The opinions were taken from a quota
sampling of different age groups. Responses totaling 404 were
collected. The sample included a total of 196 men and 208
women. The median age was 32.8 years old. Another noted
point was that the participants each had a history of Internet

9. usage for about five years (2008). This is valuable research and
asserts that these differences must be addressed in order for
online distributors to appeal to both sexes in a meaningful way.
In research done by Christy Crutsinger, Sua Jeon, and Haejung
Kim, they identified seven motivators of online auction
participants. These motivators were, “search costs, product
assortment and price, brand equity, transaction costs, customer
orientation, perceived quality, and social interaction” (2008,
p.31). Never before has there been such a vehicle for buying
and selling merchandise and services. Online auctions are
tapping into this relatively new trend.
More than 1,660 sites have been procured and are available to
cater to this type of consumer. The study on online auctions was
done through a questionnaire, based on 36 auction motivators,
online behavior, and demographics of participants. The Likert
scale was used to determine responses. These participants
totaled 410 and were selected from a pool of college students.
Data was retrieved from 341 responses. There was 74.8% female
and 42.6% were labeled as white. The ages ranged from 18 to 40
years old. The collected data revealed 90.9% were regular
users of the Internet. A low 20% revealed they had no online
auction experience. The remaining who did have experience
with online auctions were identified as follows; 5.3% used the
Internet daily, 15.2% weekly, 29.9% monthly, and 29.3% said
one to two times per year. An interesting note to this research
was that although most of those surveyed had participated in
online auctions, the majority of them (80.6%) conveyed that
they had never sold anything online.
Discussion
According to this research the following results showed that,
“search costs were the most important motivation, followed by
product assortment/price, brand equity, transaction costs,
customer orientation, and perceived quality. Social interaction
was the least important motivation associated with online
auction behaviors” (2008, p. 36). There is no doubt that college
students

10. are very involved Internet participants. Studies like this one
show the need for businesses to see the value of online auctions
and use this prospect to increase their customer base. This
research, however did not address the negative component of
online auction consumer behavior. These types of behavior may
fall into one of two categories, such as impulse buying or
compulsive buying. Further research would need to be done in
order to fully understand online consumer
auction behavior.
A major part of esthetics is how information is arranged on the
web page. Too much information can overwhelm a consumer,
too little can decrease consumer confidence. J.M. Stibel
conducted research which included this topic of interest. Tests
performed by him showed how online information presentation
failed in many ways. His results showed clearly that “category
information presented in an alphabetical list allowed consumers
the ability to navigate to their destination much faster than
when they were asked to traverse a hyperlinked hierarchy”
(2005, p.
149). Simplicity is the key. Consumers want to navigate with
the least amount of effort. Clarity in the web design gives
consumers the confidence in their ability to do so. This research
led Stibel to identify a mental model of consumers, which
concluded that people wanted information presented in concise
and understanding ways.
Conclusion
The ability of online businesses to do this is imperative because
it leads to a “more intuitive and compelling online experience
(2005, p.149). There is a sub-group of online consumers that
have been recently identified. This group has been termed, the
“net-geners or net generation.” This term is defined as,
“individuals born between 1977 and 1997 and is the first
generation to grow up surrounded by digital media and the
Internet” (Donghyun Kim & Anthony Ammeter 2008, p.7). This
group understands technology and is comfortable with Internet

11. commerce. The net-geners are the first generation that will
actually surpass the baby-boomers in population size. Because
of their knowledge and their numbers, it is safe to say that
business as usual is in for a transformation. As the elderly
portion of our population die and new individuals are born, this
new way of doing business will be the reality that is known
throughout life. The sky is indeed the limit in the progression of
online consumerism.
References
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auction behaviors and
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Koyuncu, C. & Lien, D. (2003). E-commerce and consumer’s
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