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Is eBay for everyone? An assessment of consumer demographics.

Introduction

Electronic commerce is becoming increasingly important to consumers, sellers, and entire economies. Though considered to be in its infancy, Internet usage and on-line marketing are growing explosively. During 2003 alone, approximately 40 million households in the U.S. made at least one purchase from the Internet, up from only six million in 1994 (American City & Country, 004; Hof, 2003). On-line marketing has become, and will continue to become, a full and complete business model for some companies. Internet firms such as Amazon.com, eBay, Yahoo!, and Netscape have proven that this type of business model can succeed. Research suggests that online sellers are making successful efforts to increase consumer usage of their Web sites (Saeed, Hwang, and Yi, 2003).

EBay began as a trading post for collectibles, such as Pez dispensers and Beanie Babies, and through 2000, those collectibles still accounted for up to 60% of its auctions. However, by 2002, collectibles accounted for only 30%. In 2001 alone, around 423 million items in about 18,000 categories were put up for auction on eBay (Bajari and Hortacsu, 2003). Buyers and sellers of many diverse products are finding eBay to be a viable marketplace. At least 30 million people bought and sold more than $20 billion in merchandise on eBay in 2003 (Hof, 2003; Lucking-Reiley, 2002). This is more than the gross domestic product (GDP) of all but 70 of the world's countries (Aldridge, 2004). Somewhere between 150,000 and 200,000 entrepreneurs will earn a full-time living selling everything from new and used underwear to diet pills to BMWs on eBay (Adler, 2002; Bradley and Porter, 2000; Hof, 2003). In fact, more automobiles are sold on eBay than are sold by Auto Nation, the volume leading car dealer in the United States (Aldridge, 2004; Bold, 2004; Hof, 2003; Strategic Direction, 2004). In addition, diverse businesses, such as pawnshop dealers, are now selling more merchandise on eBay than in their brick-and-mortar stores (Bold, 2004).

When the CEO of eBay, Margaret C. Whitman, described eBay as a "dynamic self-regulating economy," no one even blinked (Bradley and Porter, 2000; Hof, 2003). Several aspects of eBay have been specifically designed to support the principles of an almost free-standing economy. First, eBay set up a free market. Founder Pierre Omidyar let people decide what they wanted to sell, thus encouraging organic growth that continues today (Bradley and Porter, 2000; Hof, 2003). Second, eBay lets the users or "citizens" of the site dictate its direction. For example, as users plunged into consumer electronics, cars, and industrial gear, eBay followed. Today, eBay has 27,000 categories, including eight with gross sales of more than $1 billion each. Every couple of months, eBay meets with as many as a dozen sellers and buyers to ask them how they work and what else eBay needs to do. At least twice a week, it holds hour-long teleconferences to poll both buyers and sellers on almost every new feature or policy, no matter how small (Bold, 2004; Hof, 2003; Weiss, Capozzi, and Prusak, 2004).

Third, eBay has set up a "legal" system for policing itself. Promoting self-governance, eBay devised a feedback forum to let users rate one another to discourage fraud. Now, eBay is taking on a more overt governing role, writing software to catch crooks early and limiting or banning sales of certain merchandise, such as guns and Nazi memorabilia. Fourth, eBay educates its "citizens," holding constant classes (eBay University) in cities around the country to teach people how to use the site. Participants generally double their selling activity on eBay after taking one of these classes (Freedman, 2004; Hof, 2003; Mathews, 2004). Fifth, eBay has created its own banking system. Last year, eBay bought the on-line payment processing company PayPal for $1.5 billion to speed up the velocity of trade. PayPal is now offered on 84% of eBay listings, up from 69% a year ago (Aldridge, 2004; Hof, 2003). Sixth, eBay promotes free trade. Since 2000, eBay has been expanding internationally, buying sites in Germany, Great Britain, South Korea, and China. Its overseas sales now contribute 30% of revenues (Brand Strategy, 2004; Hof, 2003). Many other online auctions concentrate only on the U.S. market and currently show no interest in expanding overseas (Aitken, 2004).

EBay itself is doing what it can to increase its revenues, but it also seems to be buying into a basic business philosophy of sustaining a business--relationship marketing. EBay wants to design itself in such a way that both buyers and sellers can benefit as much as possible. Recent studies of eBay auctions identified more than 25 eBay options or tools that buyers can use to help attract bidders (Bland, and Barrett, 2004; Gilkerson and Reynolds, 2003). Though it is up to the individual sellers to determine the best combination of options, it is clear that eBay is doing its part. However, external factors may also influence eBay buyer behavior. Current eBay research has neglected external variables and has concentrated on specific elements of the auctions themselves (Aldridge, 2004). These factors may include consumer demographics, such as the size of community in which customers reside, the crime rate in their communities, the average income of their communities, the education level of the consumers, and the weather during the time of the auction.

Further, most current research on eBay examines relatively small sample sizes, concentrating on auctions for one product class over a short period of time, thus limiting the sample size. There are some exceptions: A study with a larger-than-average sample size examined 661 auctions for calculators (Bland and Barrett, 2004), while another recent study with a relatively large sample size examined 516 eBay auctions for coins (Bajari and Hortacsu, 2003). The current research examines 753 different auctions.

This study examines a large sample of eBay transactions to determine if certain external variables serve as predictors of eBay outcomes. The predictor or independent variables examined include gender of the consumer, whether the bidder lives in a rural or urban area, and in which of the six U.S. regions the bidder resides. The outcomes or dependent variables examined include the total value of the transaction and the number of purchases. Gender (Freedman, 2004; Rodgers and Harris, 2003; Van Slyke et al., 2002) and geographic residence (Roering and Block, 1977; Smith, 1999) have been found to affect Internet shopping in general, but have received little attention in eBay research.

Method

This research uses auction data from two current eBay sellers. One uses eBay as her primary source of income. Her eBay sales total over $40,000 per year, and she has been classified by eBay as a "Power Seller," a classification for those selling at least $1,000 per month. The other seller uses eBay sales to supplement his income from a separate full-time profession. His eBay sales total approximately $10,000 per year. All transactions from these two sellers were examined except those where the product was ultimately sold outside the United States. International sales were excluded from the data set considered, leaving a total of 753 transactions to be used in this study.

These two eBay sellers sell mostly brand-name used clothing obtained from their own closets, garage sales, rummage sales, flea markets, etc. Each transaction is considered to be an independent case, allowing details of each transaction to be recorded and statistically examined. Specific data were generated for each of the 753 auctions, such as the winning bidder's gender, location (rural or urban) and region (one of six), and the total value of the transaction. These data provided the information necessary to achieve the objectives of this research.

Ordinary least-squares (OLS) regression was used to examine the predictions. The results of the OLS regression analyses were then supported by individual t-tests to further isolate the effects of the predictor variables on the dependent variables.

Literature Review

Advances in technology and increasing ease of using the Internet are leading to a proliferation of online business. Consumers with access to computers can now research products easily and in a fraction of the time required in the past. However, a considerable gap exists between the practice of Internet-based marketing and sound theory-based insights and principles for guiding that practice. Parasuraman and Zinkhan (2002) suggest that understanding online customer behavior is one of the key factors causing this gap. Other factors that influence on-line consumers are marketing mix differences on the Internet, customer loyalty, online relationship marketing, e-tailing issues, and online delivery of services (Bajari and Hortacsu, 2003; Bold, 2004; Bradley and Porter, 2000; Parasuraman and Zinkhan, 2002).

In a study of Internet pharmacies, Yang, Peterson and Huang (2001) identified and examined six dimensions of consumer perceptions of service quality. These included ease of use, content on the Web site, accuracy of the content, timeliness of responses, aesthetics or attractiveness of the site, and privacy. Other researchers also echo concerns over similar issues that have a significant impact on online consumer behavior. For example, consumers are concerned about Internet security and the privacy of Internet transactions (Freedman, 2004; Mathews, 2004; Rust, Kannan, and Peng, 2002; Zeithaml, Parasuraman, and Malhotra, 2002).

Also, managing customer relations and effective on-line communication has been found to affect on-line consumer behavior (e.g., Stewart and Pavlou, 2002). Further, the ease of navigating a Web site has been shown to influence consumer behavior (Luna, Peracchio, and de Juan, 2002). Another study provided evidence that Web site content was a factor in determining consumer behavior and satisfaction (Burke, 2002). Attempts have been made to identify what marketing mixes should be used by on-line business (e.g., Kalyanam and McIntyre, 2002). All these factors are directly controllable by the businesses sponsoring the Web sites, and eBay, for one, does as much as it can to excel in these dimensions to increase the likelihood that consumers will make purchases (e.g., Aldridge, 2004; Bajari and Hortacsu, 2003; Bold, 2004; Freedman, 2004; Mathews, 2004; Strategic Direction, 2004). However, factors external to the direct control of online businesses still remain.

On-line buyer behavior. A recent study identified four categories of on-line shoppers and four of on-line nonshoppers, along with characteristics for each of these eight categories (Swinyard and Smith, 2003). The four categories of online shoppers (42% of the U.S. population) shared several characteristics, such as average age (44.0-49.6 years old), average household income ($58,300-$64,400), high proportions of college graduates (35%-88%), and average time spent on-line per week (12.0-22.8 hours). In addition, the shoppers like to browse the Web, want merchandise delivered to their homes, value keeping purchases private, search for the lowest prices possible, are concerned about online credit card risk, do not like the difficulties associated with returning merchandise purchased on-line, are sensitive to shipping charges they perceive to be excessive, and dislike being unable to see the merchandise in person before purchasing it online so they can make a better judgment about it (Swinyard and Smith, 2003). Other research found that a consumer's high need for cognition made it less likely that he or she would make an online purchase (Jones and Vijayasarathy, 1998). The same study found that influences of important other people affect the likelihood of a shopper making a purchase on the Internet.

Auction buying behavior. Although auctions have been examined extensively in disciplines such as economics and to some degree in marketing, on-line auctions are only beginning to receive research attention. Further, in both economics and marketing, the research on auctions has relied primarily on rational, economic theories (Gilkeson and Reynolds, 2003). However, the findings of this research are inconsistent. The findings from the few studies of on-line auctions, especially from the purchasers' perspective, are not only inconsistent but also negligible, with only a few examples of sizable studies. For example, Haubel and Popkowski-Leszczyc (2000), conducted a large field study using eBay and manipulating certain variables to examine general factors related to auctions in general, but not to on-line auctions specifically.

Predictions

Based on the foregoing information, most online auction research has concentrated on options offered by the auction companies to sellers. Though valuable for sellers, factors external to the auction are also important in determining the outcomes of these auctions.

U.S. regions. Americans often identify themselves as living in a particular region. These regions are cultural rather than governmental units, formed by history and geography and shaped by shared economics, literature, customs, and traditions.

New England is perhaps the best-defined region of the U.S. with more homogeneity and more of a shared heritage than the other regions. New England includes: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont. It has played a dominant role in American history. Until well into the 19th century, New England was the country's cultural and economic center. The earliest settlers were English Protestants who came in search of religious liberty. They gave the region its distinctive political format (town meetings), an outgrowth of meetings held by church elders, in which citizens gathered to discuss issues of the day. Education is another of the region's strong legacies. In their business dealings, New Englanders have a reputation for hard work, shrewdness, thrift, and ingenuity. They are enterprising individuals, and progressive in politics, but restrained in personal attitudes. The region is more open than others to ideas and values from Europe (U.S. Diplomatic Mission, 2003). As can be seen in Table 1, New England contains 4.88% of the population of the U.S. (Census, 2000).

The Mid-Atlantic includes: Delaware, Maryland, New Jersey, New York, and Pennsylvania. If New England provided the brains and dollars for 19th century American expansion, the Mid-Atlantic States provided the muscle. The regions largest states--New York and Pennsylvania-became centers of heavy industry. Into this area came millions of Europeans, forming the "melting pot." Historically, and even today, this region has served as the bridge between the north and the south. The Mid-Atlantic area is not all industry. There are more wooded hills than factory chimneys, more fields than paved roads, and more farmhouses than office buildings (U.S. Diplomatic Mission, 2003). As can be seen in Table 1, the Mid-Atlantic contains 16.22% of the U.S. population (Census, 2000).

The South includes: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia. Like New England, the South was settled by European Protestants, and the resulting conservative attitudes still prevail. It is often referred to as the "Bible Belt." The American Civil War devastated the Old South socially and economically. Slavery was the issue that divided the North and the South. The scars left by the war took decades to heal and some of the attitudes existing both before and during the war exist today. The "new" South, while still a major fanning region, has evolved into a manufacturing region and high-rise buildings crowd the skylines of its large cities. Owing to its mild weather, the South has become a popular place to retire (U.S. Diplomatic Mission, 2003). As can be seen in Table 1, the South contains 24.69% of the U.S. population (Census, 2000).

The Midwest includes: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. The region was shaped by freedom from slavery, pioneer spirit, Protestant faiths and religious experimentation, and agricultural wealth, aided by large navigable rivers. Known as the nation's "breadbasket," the region's fertile soil makes it possible for farmers to produce abundant harvests. Midwesterners are praised for being open, friendly, and straightforward, and are often stereotyped as unsophisticated and stubborn. Their politics tend to be cautious, but the caution is sometimes peppered with protest. Its pioneer, religious, and economic heritage tends toward libertarianism and freedom (U.S. Diplomatic Mission, 2003). Table 1 reveals that the Midwest contains 22.58% of the U.S. population (Census, 2000).

The Southwest includes: Arizona, New Mexico, Oklahoma and Texas. This region's climate is drier than the Midwest, and the population is less dense and, with strong Hispanic- and Native-American components. Outside the cities, the region is a land of open spaces, much of which is desert. The population is growing rapidly and portions of it now rival parts of the South as a destination for retirees. Through irrigation, the land is being increasingly utilized for crops, and through damming some of the major rivers, once small towns have become major cities (U.S. Diplomatic Mission, 2003). The Southwest contains 11.32% of the U.S. population (Census, 2000).

The West includes: Alaska, Colorado, California, Hawaii, Idaho, Montana, Nevada, Oregon,

Utah, Washington, and Wyoming. Americans have long regarded the West as the last frontier, yet, California has a history of European settlement older than most of the Midwest. More than in other regions, the western states have different economies and economic bases. In much of the West, the population is sparse and the federal government owns millions of square miles of undeveloped land, often used for recreational and commercial activities. Hawaii is the only state in which Asian Americans are the largest ethnic group, and the region is also known for its large Mexican-American population. Los Angeles is the entertainment capital of the world, while other areas have nurtured the computer age and explosion of technology. Over the history of the U.S., many people moved west to make a new start. As a result, the region's known for a "live-and-let-live" attitude (U.S. Diplomatic Mission, 2003). The West contains 20.32% of the U.S. population (Census, 2000).

Because of the cultural differences between these regions, the researcher expects consumers to behave differently when utilizing eBay. Exactly how these differences affect eBay bidding behavior is difficult to predict and is one of the major purposes of this research. Therefore, the following general prediction is offered:

[P.sub.1]: There are differences between residents in the U.S. regions on eBay bidding behavior and the value of each transaction.

Urban/rural. The U.S. Census Bureau classifies as "urban" all territory, population, and housing units located within a core census block group that has a population density of at least 1,000 people per square mile with surrounding census blocks having an overall density of at least 500 people per square mile. Everywhere else is classified as "rural." Table 1 shows that 83% of the nation's population resides in urban areas. People in urban areas may have more access to brick-and-mortar stores with name-brand items than people in rural areas. Recent research suggests that consumers in rural areas are more likely to "inshop" (shop in retail outlets located near their residence), partially because of a perceived obligation of reciprocity (Brodsky, Senuta, Weiss, and Marx, 2004; Miller and Kean, 1977). Other research suggests that rural shoppers are more likely to "outshop" through catalogs, TV, and the Internet (e.g., Gruenewald, 2003; Smith, 1999).

Related research suggests that rural consumers exert considerably more effort to obtain prepurchase information than do their urban counterparts (Gruenewald, 2003; Roering and Block, 1977). The Internet is an efficient way to find information, so a logic suggests that rural consumers would use the Internet for prepurchase information. However, it is not clear whether this tendency would hold when the information search excludes face-to-face contact with local merchants in the spirit of reciprocity.

Because of the cultural differences between urban and rural areas and possible differences in access to products, the researcher expects consumers from each type of area to behave differently when utilizing eBay--but how differently is difficult to predict and is another major purpose of this research. Therefore, the following general prediction is offered.

[P.sub.2]: There are differences between rural and urban residents in the U.S. on eBay bidding behavior and the value of each transaction.

Gender. Because of commonly-known differences between male and female consumers when they shop at brick-and-mortar stores, similar differences may occur when they shop on eBay. Table 1 shows that 51.15% of the population of the U.S. is female. Recent research suggests that although men and women are equally likely to use the Internet for business and personal purposes, men are more likely to purchase products on-line (e.g., Rodgers and Harris; Van Slyke, Comunale, and Belanger, 2002). One suggested reason for this is that women may not be ready or willing to depart from conventional shopping (Van Slyke et al., 2002). Another reason may be a difference in information processing by genders. A study by Rodgers and Harris, 2003 indicates that males rely heavily on fight-hemisphere processing, denoted by reliance on global rules and other categorical concepts. Females primarily rely on left-hemisphere processing, which concerns the specialties and intricacies represented or implied by stimulus information.

Because of these expected gender differences, the researcher expects consumers to behave differently when utilizing eBay, and identifying these gender differences is the final major purpose of this research. Therefore, the final general prediction of this study is as follows:

[P.sub.3]: There are differences between male and female consumers in the U.S. on eBay bidding behavior and the value of each transaction.

Results

OLS regression was used to examine the predictions. These findings were then backed up by individual t-tests to further isolate the effects of the predictor variables on the dependent variables.

Regions. Table 1 reveals differences in population proportions and the proportion of eBay purchases. With 4.88% of the population, New England accounted for 2.79% of total eBay purchases and 2.46% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 2.66, p = .0039) and the value of the purchases (z = 3.08, p = .0010) are statistically lower than New England's proportion of the nation's population. However, the difference between these two proportions is not statistically significant, indicating that New Englanders do not spend a different amount on each purchase than people from other regions. To further examine this relationship, Table 3 shows no significant differences between the average prices paid by New Englanders and those in other regions.

The Mid-Atlantic contains 16.22% of the population, accounted for 11.29% of total eBay purchases and 9.12% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 1.65, p = .0495) and the value of the purchases (z = 2.37, p = .0089) are statistically lower than the region's proportion of the population. Further, the difference between these two Mid-Atlantic proportions is also statistically significant, indicating that Mid-Atlantic residents spend less on each purchase than people in other regions. Table 3 shows significant differences between prices paid by residents of the Mid-Atlantic (less) and Southerners (t = 4.728, p = .031), residents of the Mid-Atlantic (less) and Southwesterners (t = 5.038, p = .026), and residents of the Mid-Atlantic (less) and Westerners (t = 7.736, p = .006).

With 24.69% of the population, the South accounted for 25.23% of total eBay purchases and 25.81% of their total value. Table 2 indicates there are no significant differences between the number and value of the purchases to the South's proportion of the population. Further, the difference between these two proportions is not statistically significant. However, further investigation shows a significant difference between prices paid by southerners (more) and residents of the Mid-Atlantic, as discussed in the previous paragraph (Table 3).

With 22.58% of the population, the Midwest accounted for 32.01% of their total eBay purchases and 31.40% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 6.19, p = .0000) and the value of the purchases (z = 5.79, p = .0000) are statistically higher than the Midwest's proportion of the nation's population. However, the difference between these two Midwest proportions is not statistically significant. Further, Table 3 shows there is no significant difference between the average prices paid by Midwesterners and people in other regions.

The Southwest contains 11.32% of the population, accounted for 11.95% of total eBay purchases and contributed 13.18% of their total value. Table 2 indicates no difference between the number of purchases and the region's proportion of the population, but, the value of the purchases (z = 1.61, p = .0537), is statistically higher than the Southwest's proportion of the nation's population. However, the difference between these two Southwest proportions is not statistically significant. Table 3, shows a significant difference between prices paid by Southwesterners (more) and the residents of the Mid-Atlantic.

The West contains 20.32% of the population and accounted for 16.73% of total eBay purchases and 18.03% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 2.45, p = .0071) and their value (z = 1.56, p = .0594) are statistically lower than the West's proportion of the population. However, the difference between these two proportions is not statistically significant, indicating that Westerners do not spend a different amount on each purchase than people in other regions. Differences between prices paid by Westerners (more) and the residents of the Mid-Atlantic are significant, as indicated in Table 3.

Urban/rural. Urban areas contain 83% of the population but accounted for only 49.54% of total eBay purchases, contributing 53.50% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 24.44, p = .0000) and their value (z = 21.55, p = .0000) are statistically lower than the proportion of the U.S. population living in urban areas. Further, the difference between these two urban proportions is statistically significant, indicating that urbanites spend more on each purchase than do people from rural areas (z = 2.17, p = .0150). Table 3 also shows that t-testing indicates a significant difference between the average prices paid by urbanites (more) and those living in rural areas (t = 9.853, p = .002).

Rural areas of the U.S. contain only 17% of the population but accounted for as much as 50.46% of their total eBay purchases and 46.50% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 24.44, p = .0000) and their value (z = 10.10, p = .0000) are statistically higher than the proportion of the rural population. Further, the difference between these two rural proportions is statistically significant, indicating that people residing in rural areas spend less on each purchase than do people from urban areas (z = 2.17, p = .0150). Table 3 indicates a significant difference between the average prices paid by people from rural areas (less) and urbanites.

Gender. Males account for 48.85% of the population but accounted for only 32.54% of total eBay purchases and 37.63% of their total value. Table 2 shows that the differences between both the number of purchases (z = 8.73, p = .0000) and their value (z = 6.16, p = .0000) are statistically lower than the male proportion of the U.S. population. Further, the difference between male proportions is statistically significant, indicating that males spend a different amount on each purchase than do females (z = 2.98, p = .0014). Table 3 also shows a significant difference between the average prices paid by males (more than females) (t = 11.028, p = .001).

Females compose for 51.15% of the U.S. population but accounted for as much as 67.46% of total eBay purchases and 62.37% of their total value. Table 2 indicates that the differences of both the number of purchases (z = 8.95, p = .0000) and their value (z = 6.16, p = .0000) are statistically higher than the female proportion of the U.S. population. The difference between these two percentages is statistically significant, indicating that females spend a different amount on each purchase than males (z = 2.98, p = .0014).

Table 3 also shows a significant difference between the average prices paid by females (less) than males, as discussed previously.

Discussion

This research offers significant new findings. As predicted, consumers from different regions tend to behave differently when it comes to eBay purchasing. This has important implications for eBay sellers and for managers of companies offering their products for sale over the Internet. This study clearly shows that people from the Southwest and the West are willing to pay significantly higher prices for the same types of products. This may reflect the geographical openness of the regions and their sparse, dispersed population. In many cases, consumers have to travel a long way to find brick-and-mortar retailers where these products are available. The value of the convenience of buying on eBay is likely greater, so they are willing to spend more money.

People from New England, the Mid-Atlantic, and the West are less likely to make purchases on eBay (and maybe the Internet) than people from other regions. This finding is surprising for New England because education and computer usage is often linked. However, the conservatism for which both New England and the Mid-Atlantic are known may provide a partial explanation. Perhaps these people are more cautious and need to see the product, or try it on, etc. For the West, the findings may be explained by the decline in openness and tolerance that it was once known for.

Residents of rural areas are more likely to purchase products on eBay than are people living in urban areas, though urbanites are willing to pay higher prices. This contradicts the principle of reciprocity and the tendency of rural residents to "inshop." However, the finding supports the characteristic of consumers from rural areas as needing more prepurchase information. The Internet offers many opportunities for product research, and eBay offers an opportunity for the bidder to gain information about the seller through the feedback feature. Also, many products are not available in rural areas, and the most convenient and efficient way for rural residents to obtain them is through the Internet.

According to this study's results, females are more likely to purchase on eBay, but males are more willing to pay higher prices. These findings contradict other research suggesting women are less likely to make Internet purchases. However, this finding may highlight the possibility that bidding on items on-line may provide a different experience than merely purchasing products on the Internet. Many women like to shop, and the excitement of the auction may replace the satisfactions of the brick-and-mortar shopping experience.

Another reason may be that women are catching up to men regarding their comfort with the Internet and computer usage and, therefore, their confidence in Internet shopping is increasing. The finding that men tend to pay more per eBay transaction supports the historical finding that men are more likely to make Internet purchases. They are more comfortable with the Internet and probably willing to risk more money per transaction.

Conclusions

This study offers conclusions based on a larger sample size than is typical of most related studies, both in on-line consumer behavior and eBay bidder behavior. This sample included all buyers purchasing products from the two eBay sellers who market primarily clothing and accessories, but also some other items, as opportunities arise. All auctions were open to bidding in all 50 states, so the buyers are representative of all U.S. eBay buyers of clothing and accessories.

The results have significant implications for sellers who search for ways to be more profitable on eBay, and also for eBay buyers, who should understand the marketing efforts used to attract them. The results offer valuable insights to buyers as they attempt to get the most for their money. The results also contribute to the body of knowledge about influences on Internet marketing success in general and eBay auctions specifically. This study scratches the surface of the many external factors that affect the success and failure of eBay auctions. The findings demonstrate that these external factors, along with the many internal factors identified in previous studies, are important to eBay success and failure.

Limitations and Future Research

This study has limitations. The eBay sellers whose information was obtained for this study sold mostly new and used name-brand clothing. Though clothing accounts for as much as 35.3% of consumer online purchases (Swinyard and Smith, 2003), these findings may not apply to consumers of other types of products sold on eBay. Additionally, eBay purchasing behavior may vary from Internet purchasing in general.

Many areas of future research may shed further light on the behavior of eBay consumers. EBay sellers suspected a difference in buyer activity depending on the weather patterns in certain areas of the country, and it would be useful to examine other consumer demographics, such as income, education, level of crime in their communities, and whether consumers pay over the Internet or by personal check.

Research should compare the influences of external factors, some of which are identified in this study, and the internal factors identified in several previous studies on the outcomes of eBay auctions. EBay sellers and buyers, as well as researchers, are constantly searching for the best combination of factors to maximize positive outcomes of these auctions. It is important to acknowledge that internal and external variables influence these outcomes, and to examine both in future research.
Table 1. Summary of Population and eBay Data

 % of US # of eBay % of Total
Variable Population Purchases Purchases

Region
 New England 4.88% 21 2.79%
 Mid-Atlantic 16.22 85 11.29
 South 24.69 190 25.23
 Midwest 22.58 241 32.01
 Southwest 11.32 90 11.95
 West 20.32 126 16.73

Rural/Urban
 Urban 83 373 49.54
 Rural 17 380 50.46

Gender
 Male 48.85 245 32.54
 Female 51.15 508 67.46

 $ Value of % of Total
Variable Purchases Purchases

Region
 New England $284.85 2.46%
 Mid-Atlantic 1,057.10 9.12
 South 2,991.94 25.81
 Midwest 3,639.46 31.40
 Southwest 1,527.63 13.18
 West 2,090.49 18.03

Rural/Urban
 Urban 6,201.97 53.50
 Rural 5,389.50 46.50

Gender
 Male 4,361.44 37.63
 Female 7,230.03 62.37

Table 2. Results of eBay Comparisons

Variable Comparison Z-Score

Region
 New England # of Purchases -2.66 ***
 Value of Purchases -3.08 ***
 Difference -0.55

 Mid-Atlantic # of Purchases -1.65 **
 Value of Purchases -2.37 ***
 Difference -1.88 **

 South # of Purchases 0.34
 Value of Purchases 0.71
 Difference 0.37

 Midwest # of Purchases 6.19 ***
 Value of Purchases 5.79 ***
 Difference -0.36

 Southwest # of Purchases 0.55
 Value of Purchases 1.61 *
 Difference 1.04

 West # of Purchases -2.45 ***
 Value of Purchases -1.56 *
 Difference 0.96

Rural/Urban
 Urban # of Purchases -24.44 ***
 Value of Purchases 21.55 ***
 Difference -2.17 **

 Rural # of Purchases 24.44 ***
 Value of Purchases -10.10 ***
 Difference -2.17 **

Gender
 Female # of Purchases 8.73 ***
 Value of Purchases 6.16 ***
 Difference -2.98 ***

 Male # of Purchases -8.95 ***
 Value of Purchases -6.16 ***
 Difference 2.98 ***

* Statistically significant at p < .10

** Statistically significant at p < .05

*** Statistically significant at p < .01

Table 3. Results of Average Price Analysis

Variables Average
Compared N Price T-Value

New England/ 21 $13.56
Mid-Atlantic 85 $12.44 0.088

New England/ 21 $13.56
South 190 $15.75 0.895

New England/ 21 $13.56
Midwest 241 $15.10 0.250

New England/ 21 $13.56
Southwest 90 $16.97 1.030

New England/ 21 $13.56
West 126 $16.59 1.510

Mid-Atlantic/ 85 $12.44
South 190 $15.75 4.728 *

Mid-Atlantic/ 85 $12.44
Midwest 241 $15.10 1.583

Mid-Atlantic/ 85 $12.44
Southwest 90 $16.97 5.038 *

Mid-Atlantic/ 85 $12.44
West 126 $16.59 7.736 **

South/ 190 $15.75
Midwest 241 $15.10 0.601

South/ 190 $15.75
Southwest 90 $16.97 0.268

South/ 190 $15.75
West 126 $16.59 0.046

Midwest/ 241 $15.10
Southwest 90 $16.97 1.108

Midwest/ 241 $15.10
West 126 $16.59 0.292

Southwest/ 90 $16.97
West 126 $16.59 0.517

Urban/ 373 $16.63
Rural 380 $14.18 9.853 **

Female/ 508 $14.25
Male 245 $17.89 11.028 **

* Statistically significant at p < .05

** Statistically significant at p < .01


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Dr. Black has presented his research findings on eBay at conferences and in published articles. He has publications in various journals.

Gregory S. Black, Texas A&M University-Corpus Christi
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