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An Empirical Investigation of Online Consumer Purchasing Behavior


This article is focused on examining the factors and relationships that influence the browsing and buying behavior of individuals when they shop online. Specifically, we are interested in individual buyers using business-to-consumer sites. We are also interested in examining shopping preferences based on various demographic categories that might exhibit distinct purchasing attitudes and behaviors for certain categories of products and services. We examine these behaviors in the context of both products and services.

After a period of decline in recent months, online shopping is on the rise again. By some estimates, total U.S. spending on online sales increased to $5.7 billion in December 2001 from $3.2 billion in June of 2001 [3, 5]. By these same estimates, the number of households shopping online increased to 18.7 million in December 2001 from 13.1 million in June 2001. Consumers spent an average of $304 per person in December 2001, compared with $247 in June 2001. According to an analyst at Forrester: "The fact that online retail remained stable during ... such social and economic instability speaks volumes about how well eCommerce is positioned to stand up to a poor economy" [4].

What do consumers utilize the Internet for? Nie and Erbring suggest that 52% of the consumers use the Internet for product information, 42% for travel information, and 24% for buying [9]. Recent online consumer behavior-related research refers to any Internet-related activity associated with the consumption of goods, services, and information [6]. In the definition of Internet consumption, Goldsmith and Bridges include "gathering information passively via exposure to advertising; shopping, which includes both browsing and deliberate information search, and the selection and buying of specific goods, services, and information" [7]. For the purposes of this study, we focus on all aspects of this consumption. We include all of them because information gathering aspects of e-commerce serve to educate the consumer, which is ultimately in the interest of the online shopping industry. Further, the knowledge that consumers may be using a site for research purposes only may imply that the Web sites in this industry are not able to meet the consumer needs adequately. Similarly, both researchers and practitioners may be interested in learning whether consumers are using the Internet solely for collecting information or for purchasing specific types of products as well. Thus, online consumer behavior is of interest to consumer theorists and practitioners. Researchers may wish to examine how existing theories of consumer behavior can be applied to online consumer behavior. Practitioners are likely to be interested in examining aspects of consumer needs their sites are unable to fulfill. Thus, our findings should help the managers design online marketing strategies aimed at attracting consumers who do not yet shop online, as well as improving their online offerings for those who do.

In general, advantages of online shopping as perceived by consumers include convenience, selection, price, original services (services that may be available online but not elsewhere), personal attention (some consumers perceive that they get more personal attention from merchants by going online), easy and abundant information access, privacy (consumers may be able to view, compare, and buy items that they might be reluctant to buy in-store, and freedom from sales people). So, why are some products sold online more successfully than others? In this article, we sought to answer the following research questions:

  • Which categories of products/services are popular?
  • How much is being spent on various categories of products/services?
  • How many Web sites are visited before making a purchase?
  • Why do people buy or decide not to buy online?

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The Study

This study focuses on general online purchasing behavior of individual consumers and why they choose to buy or not buy online. Our product categories were derived from a variety of sources. Our approach is consistent with that of the leading online-shopping research company, Forrester, which uses demographic information along with attitudinal and lifestyle data to create a composite segmentation scheme that divides the market into ten segments reflecting typical purchases by high- as well as low-income levels. Our approach is also consistent with that of Modahl—who describe three motives for online shopping (career, family, entertainment)—and two technology attitude groups [8].

The study surveyed two samples to gather quantitative data. These two samples reflect two distinct groups of the population: students (n=190, 84.6% of whom were full-time undergraduate students) who are considered to be Internet savvy and less concerned about privacy [10]; and non students (n=75, 78.9% of whom were faculty or administrators) who would exhibit greater variance in their level of comfort with the Internet, and would be more concerned about privacy. Both the samples were almost evenly divided into females (56% and 50% for student and non-student samples respectively) and males (44% and 50% respectively). In both samples, over 70% of our subjects had been using the Internet for over three years. Sixty-three percent of the subjects in the student sample earned over $1000 per month while 68% of the subjects in the non-student sample earned over $3000 a month.

The questionnaire focused on online shopping behavior across eight categories to provide a good mix of products and services. The choice of these categories was guided by the Yahoo! Shopping portal (www.yahoo.com) [11]. All the above research questions were investigated across demographic groups (age and gender) to see if there were any differences in the patterns of online shopping.

What are people buying online? The survey asked respondents to indicate the frequency of purchase of items for eight different product/service categories within the last six months. The data (see Table 1) indicate that most people are not buying online. Interestingly, the same categories of products and services are popular in both the student and non-student sample. This may indicate that demographics of age, income, and occupation alone may not account for online shopping behavior [1]. Travel (53% students; 61% non students) and audio-video (43% students; 58% non students) were the most popular categories in both samples, followed by apparel and computer and computer accessories. The least purchased category was groceries (7% for both samples). This could also be due to the fact that online grocery companies like Peapod do not operate in the regions where these surveys were conducted. Travel accounted for higher spending amounts (see Table 2). Thirty-eight percent of students reported spending $100 to $500 and 11% indicated expenditures greater than $500 on travel. The corresponding numbers for the non-student sample were 40% and 15% respectively. Of all the categories that were examined in the survey, travel was the most expensive, which might account for the higher expenditures in this category.

We asked respondents about their future intentions to purchase products/service in the eight categories (Table 1). The responses follow the pattern of current purchasing behavior with travel and audio-video topping the list, followed by computers and apparel. The list is rounded off with groceries at the bottom. Interestingly, the patterns of future intent are fairly similar across both travel and audio-video categories. However, the figures are higher for students across all categories. This suggests that there is something inherent in the travel and audio-video categories, which makes them more or less desirable for online purchasing. One possible explanation is that, traditionally, products like audio-video, apparel, and computer accessories have been purchased through catalogs and other forms of direct mail. Thus, online shopping is seen as just another distribution channel. Groceries, on the other hand, have traditionally been bought in the store. Online grocery shopping requires new scripts and a different mindset. It also demands more planning and forethought and less impulse buying. Second, online grocery store deliveries are still not widely available, which might explain why people are not buying groceries online. With high profile companies like Webvan.com closing down, it might also explain the low future intent to purchase in this category. A third possibility is that there are well-established sites for travel (major airline sites), audio-video (for example, CD-Now), apparel (such as www.landsend.com) and computers (like www.dell.com). This makes it easier for people to shop online. Additionally, they have trusted brands (such as Amazon) that can ease the anxiety of shopping online.

How many sites do they visit before making a purchase decision? One of the benefits of online shopping is the ability to obtain information and make comparisons, provided consumers know how to make efficient searches [10]. However, it can lead to information overload, which in turn, might turn people off from online shopping. How do consumers balance these pressures? We looked at the number of Web sites people visit before making a purchase (see Table 3). Across the board, one to three Web sites appeared to be the popular response. The student sample had a higher percentage of people who indicated visiting more than three Web sites. In the non-student sample, travel was the only category that reached double-digit numbers (11%) for more than three Web sites visited. This may be an indication of students being aware of more Web sites, or having more time to surf for the best deal.

Motivating factors and barriers. We examined reasons why people liked to shop online (see Table 4). The primary reason for students to shop online was convenience, characterized as shopping from home and avoiding the hassles of parking, salespeople, and checkout lines (28%). Other reasons included better prices (25%) and saving time (23%). The results for the non-student sample were similar in numbers but with a different order. Convenience (31%) and saving time (27%) were cited as the top two reasons, with better prices coming in third at 23%. Availability of products/services, as in access to variety, was also indicated as a significant reason for shopping online. These statistics, suggesting that people are more interested in convenience than in price, are interesting because they contrast with popular belief. This finding has strong implications for businesses and managers working in this area and should be considered while designing e-commerce strategies as well as Web sites.

In order to determine barriers to online shopping, we asked those respondents who did not shop online, to indicate reasons for not doing so (see Table 4). The overwhelming concern in both samples was privacy and security (28% for students; 31% for non-students). The second leading reason for not buying online was the lack of customer service (22% for students; 28% for non-students). This includes the inability to reach someone if the consumer has a problem while shopping as well as post-purchase service problems. Lack of social interaction was cited as a third reason (15% for students; 9% for non-students) for not shopping online. Social interaction implies the opportunity to interact with a salesperson. It also includes the perception of shopping as a social activity with friends. The latter interpretation may also account for a higher percentage of the student group who indicated this was a problem. There was also a perception that products bought online are more expensive (13% for students; 10% for non-students). This appears to contradict the finding that better prices are a reason to shop online (see Table 4). However, we believe the Internet shopping mall is perceived to be more expensive because of shipping costs. It is also possible that people feel that they have not gotten the best deal. While comparison-shopping is possible, it is limited by the sites that the respondent visits. If the consumer feels that s/he does not have sufficient expertise to navigate the Web, s/he may also feel that the best deal has not been secured [2]. Respondents also cited lack of time (11% for students; 8% for non-students) and inability to touch and feel the product (4% for both samples) as reasons for not shopping online. Other miscellaneous reasons for not shopping online included difficult to return, too much information, and connection troubles.

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Conclusions

Our findings regarding motivators and barriers to online shopping clearly indicate that convenience and customer service can act as strong motivators when present; they can also be strong barriers when absent. Security and privacy concerns were the single biggest barriers to online shopping. Contrary to popular notion, these factors were found to be more important than price.

This study does have some limitations that need to be acknowledged and addressed in future studies. First, though these samples provide us with a good understanding of the online purchasing behavior of a highly educated and computer and Internet savvy consumer group, they may not provide insights into the behavior of a consumer who is not a regular computer user, but is nevertheless buying online. As Internet use is exploding across all demographics, it would be interesting to compare the buying behavior of these two types of populations. Secondly, this survey only asked for income and it did not specify whether it was personal or household income. We may have obtained responses from both of these income categories. However, we believe that this does not compromise the integrity of the survey since the focus is on how people spend their disposable income.

Finally, an important element of online purchasing behavior is the use of the Internet for research as well as for purchase. The Internet as a source of consumer information for offline buying has implications for how Web sites are designed, their content, and how well a site meets consumer needs. Further research should address these issues.

While other studies of online consumer expectations in the e-commerce area have been conducted, most of them are carried out by commercial organizations. To our knowledge, this is the first systematic study of this issue conducted by academic and non-biased researchers. We believe this to be a contributing factor.

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References

1. Bellman, S., Lohse, G. L., and Johnson, E. J. Predictors of online buying behavior. Commun. ACM 42, 12 (1999), 32–38.

2. Citrin, A. V., Sprott, D. E., Silverman, S. N., and Stern Jr., D. E. Adoption of Internet shopping: The role of consumer innovativeness. Industrial Management & Data Systems 100, 7 (2000), 294–300.

3. Consumers spent (2001); www.forrester.com/ER/Press/Release/0,1769,621,00.html (August 8, 2002).

4. Consumer Spending Online (2001); www.forrester.com/ER/Press/Release/0,1769,636,00.html (Aug. 8, 2002).

5. December shopping up (2002); www.forrester.com/ER/Press/Release/0,1769,678,FF.html (Aug. 8, 2002).

6. Freiden, J., Goldsmith, R. E., Hofacker, C., and Takacs, S. Information as a product: Not goods, not services. Marketing Intelligence and Planning 16, 3 (1998), 210–20.

7. Goldsmith, R., and Bridges, E. E-tailing versus retailing: Using attitudes to predict online buying behavior. Quarterly Journal of Electronic Commerce 1, 3 (2000), 245–253.

8. Modahl, M. Now or Never: How Companies Must Change Today to Win the Battle for Internet Consumers. HarperCollins, New York, NY, 2000.

9. Nie, N., and Erbring, L. Internet use. Stanford Institute for the Quantitative Study of Society, California (2000).

10. Phelps, J., Nowak, G., and Ferrell, E. Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing 19, 1 (2000), 27–41.

11. www.yahoo.com; www.yahoo.com/ (Dec. 24, 2001).

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Authors

Manju K. Ahuja ([email protected]) is an assistant professor of Management Information Systems at The Kelley School of Business, Indiana University, Bloomington, IN.

Babita Gupta ([email protected]) is an associate professor of Management Information Systems at California State University, Monterey Bay, CA.

Pushkala Raman ([email protected]) is an assistant professor of Marketing at Florida State University, Tallahassee, FL.

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Tables

T1Table 1. Who is buying—Present and future?

T2Table 2. How much are people spending?

T3Table 3. Number of Web sites visited before making a purchase.

T4Table 4. Motivating factors and barriers.

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©2003 ACM  0002-0782/03/1200  $5.00

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.

The Digital Library is published by the Association for Computing Machinery. Copyright © 2003 ACM, Inc.


 

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