Determinants of Recent Online Purchasing and the Percentage of Income Spent Online

The recent stagnation of electronic commerce highlights the need to understand contemporary online consumer behavior. This study incorporates current user demographics and emerging Internet activities to dynamically model the determinants of two key measurements of recent online shopping, a purchase within the last year and the novel dependent variable, percentage of income spent online in the last three months. Logistic regression is applied to a nationally representative 2007 survey of the U.S. online population. Determinants of a recent online purchase include, ownership of a credit card, an online payment account (PayPalTM), listening to podcasts, participating in online auctions, and for the first time, female gender. In a second regression, positive determinants for the percentage of income spent online include male gender, educational attainment, online auctions, instant messenging and online dating. Online spending increases with time online and appears to compete with other forms of online entertainment and social networking. Stratification of the data by gender yields higher estimates for the explained variance in the percentage of income spent online for men than for women. Males are novelty shoppers, and online purchasing competes with watching television, playing games online and blogging. They strongly prefer products perceived as new and innovative and are not motivated by value. Further stratification by income and age reveals that possession of an online deferred account is the strongest determinant for all men except the highest earners. In contrast, women are convenience-oriented but not novelty or value shoppers. High-spending women are technologically sophisticated, using the Internet to obtain stock quotes, participate in online auctions and make deferred payments. These results produce snapshots of contemporary online shoppers that can be used by electronic retailers to determine which product characteristics to highlight for greatest impact, and to efficiently target specific activities, such as entertainment, podcast and social network websites, to develop new and robust marketing platforms