Resumo

E-commerce giants have proven how widespread the online market is. Moreover, the online market is also an option for retailers to expand their market and increase their profitability, given the increasing number of online shoppers. Over two billion people worldwide purchased goods and services online in 2020, representing a 6.7% increase from the previous year. Given this relevance, research has dedicated considerable effort to profiling online customers, overemphasizing the segmentation of online shoppers at the expense of better understanding the segmentation of online nonshoppers.

The failure to pay attention to the complaints of online nonshoppers leads to the loss of many potential customers, especially in Brazil (the largest e-commerce market in Latin America). Around 55 million Brazilian Internet users do not shop online for a couple of reasons. This study explores this fact by addressing the following research questions: do e-commerce nonusers all have the same reasons not to shop online or are there dissimilar behavior patterns that might lead nonusers to cluster in different groups?

In the e-commerce use literature, research generally addresses the barriers and drivers either from the perspective of the e-commerce user or by comparing online shoppers and nonshoppers. Nonshoppers are seldom addressed alone. The drawback of this general approach is that studies neglect the underlying principles of e-commerce nonusers’ behavior. Scholars argue that e-commerce nonusers are not a homogenous group. For example, some nonusers may be computer illiterate while others are relatively digitally skilled but nevertheless do not trust e-commerce.

We conducted cluster analyses on a large sample (N = 9,065) from a nationwide survey on the use of information and communication technology in Brazil. Firstly, we relied on the literature to create indicators for grouping the reasons not to shop online. Then, we combined hierarchical and nonhierarchical cluster analyses to partition the data. Next, we ran statistical analyses to validate the formation of clusters. Finally, we zoomed in on the characteristics of each cluster to identify and understand their members' behavior patterns.

We identified three clusters of e-commerce nonusers: one consisting predominantly of Generation Xers and Baby Boomers; another characterized by disbelieving postures on e-commerce; and the last one suggesting that its members have to see the product to believe it. Overall, e-commerce nonusers have different reasons not to shop online but they also share some similarities. More importantly, socioeconomic factors do not seem to affect their behavior substantially. Our findings suggest that merchants have failed to attract customers’ attention and that tangibility is the major hurdle to overcome.

Our findings support the notion that e-commerce nonusers are heterogeneous segments with at least three natural clusters. We encourage researchers to undertake further analysis to determine what other factors have the strongest effects on nonshoppers, particularly carefully examining what may have changed since the beginning of the pandemic. Perhaps people have become more susceptible to engaging in the online market and some factors may no longer be relevant.

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