Spatial Patterns and Socioeconomic Influences on m-Commerce and m-Entertainment Usage in U.S. Counties
Posted: 19 Mar 2018
Date Written: March 16, 2018
Since the early 2010’s, the use of mobile internet (MI) applications has skyrocketed among American consumers. As mobile devices become ubiquitous, Americans are increasingly using MI for a variety of purposes such as mobile communication (m-communication), mobile commerce (m-commerce), and accessing entertainment (m-entertainment). From texting, emailing, taking photos or videos, social networking, downloading apps, to buying/selling online, making banking transactions and bill payments online, to listening to music, playing games, and watching videos online, the use of MI is expanding in scope. However, despite mobile device saturation and widespread availability of smartphones, disparities in MI usage for m-commerce, m-entertainment, and other forms of MI usage by location (urban versus rural) as well as demographic and socioeconomic status is widespread.
In this paper, mobile adoption and mobile internet (MI) usage in 3,108 counties of the United States for m-commerce and m-entertainment purposes is examined. Using the Spatially Aware Technology Utilization Model (SATUM), seventeen demographic, socioeconomic, educational, affordability, innovation, and social capital indicators are posited to be associated with indicators of mobile internet use (3 dependent variables) as well as indicators of m-commerce (6 dependent variables) and m-entertainment (9 dependent variables).
Spatial patterns of mobile internet adoption and usage are explored to understand the extent of the mobile internet digital divide in the US and differences between metropolitan, micropolitan, and rural counties are examined. K-means cluster analysis identifies spatial agglomerations of high- and low-use counties for m-commerce and m-entertainment. Cluster and outlier analysis further identifies interesting patterns showing the high-use counties in rural communities are often university communities, or areas with large research and development entities, healthcare facilities, or military installations. Agglomeration of mobile access and MI use indicates possible presence of spatial autocorrelation, indicating that MI adoption and use for m-commerce and m-entertainment is spatially biased.
OLS regressions account for these biases and reveal age, urban location, education, participation in the services – more specifically professional, scientific, and technical services workforce are dominant correlates of MI use while tariffs and race and ethnicities (Hispanic and African American) are associated with varying degrees. These broadly point to the influence of key demographic, location, innovation, and affordability on MI use. Counties with higher percent urban, college graduation, and household income have elevated mobile e-commerce uses, findings which are reflected in metropolitan and micropolitan subsamples, and are consistent with extensive digital divide literature. However, the effects of college education and income weaken to only two strong effects for rural counties. Evidence of strong association of geodemographic and tariff variables emphasize the importance of market forces on mobile internet usage. Policies to bridge the mobile internet digital divide are recommended based upon the significant influence of market factors, innovation, and affordability.
Keywords: Mobile Internet, m-Commerce, m-Entertainment, Counties, Digital Divide
JEL Classification: C21; C23; L86; L96
Suggested Citation: Suggested Citation