Running head: ONLINE CONSUMER BEHAVIORS
Exploring online consumer Behaviors
John A. Smith & Jane L. Doe
Liberty 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 behaviors,
motivations, and attitudes of this 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 and
(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.
Introduction
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 to distant future.
There are many variables to consider when outlining behaviors of Internet consumerism.
According to Delia Vazquez and Xingang XU, online consumer behavior is affected by three
main things: “attitudes towards online shopping, motivations, such as price, convenience and
hedonic motivations, and 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. The first were between 15 and 24.
The second group was between 25-34 years old. 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.
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.
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
Cuneyt Koyuncu and Donald 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. 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.
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 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
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, and 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 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).
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 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 were 74.8% female and 42.6% 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.
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
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 addressed 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. 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 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.
Method
Reference Page
Crutsinger, Christy. Jeon, Sua & Haejung, Kim. (2008). Exploring online auction behaviors and
motivations. Journal of Family and Consumer Sciences, 100(2), 31-40.
Janda, Swinder. (2008) Does gender moderate the effect of online concerns on purchase
likelihood? Journal of Internet Commerce, 7(3), 339-357.
Koyuncu, Cuneyt & Lien, Donald. (2003). E-commerce and consumer’s purchasing behavior.
Applied Economics, 35, 721-726.
Kukar-Kinney, M., Ridgway, N. & Monroe, K. (2009). The relationship between consumers’
tendencies to buy compulsively and their motivations to shop and buy on the internet.
Journal of Retailing: Consumer Behavior and Retailing, 85(3), 298-307.
Stibel, J. M. (2005). Mental models and online consumer behavior. Behavior & Information
Technology, 24(2), 147-150. Retrieved from
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