Study helps show what’s in store for shopping center rents.

William G. Hardin III

Understanding the rent potential of shopping centers has consequences for developers and retailers alike. As developers determine where to build or redevelop and as tenants weigh their options for where to locate, the question of which spaces can expect to command premium rents—and why—needs careful attention.

Research by William G. Hardin III, a new professor in the Department of Finance in the College of Business Administration, sorts out the complexities. And there are many.

“In the retail segment, we can look at the regional mall, power center, community center, neighborhood center, and specialty center, each of which has different attributes,” said Hardin, whose most recent study focused on neighborhood and community centers and the rent potential of each. “Very little work has been done on rental rates in non-mall retail shopping centers.”

Retail real estate has language all its own.

First, some generally-used definitions:

Neighborhood centers—those with one anchor, typically a grocery store, and additional retail space. Think of a grocery chain anchor and space for other retailers.

Community centers—those normally having two or more anchors, often including a grocery store anchor, with other spaces to rent. Envision a grocery anchor, a discount store anchor, and retailers in between them.

Higher order goods—products we don’t buy all the time and which we might drive farther to get.

Lower order goods—items we purchase on a regular basis, such as groceries, and for which we tend to travel only five to fifteen minutes.

Trade area: the area from which customers come; this study analyzed both a one-mile trade area and a two-mile trade area.

Metropolitan statistical area (MSA)—a government-defined economic area where people are drawn to work and are linked economically.

The study focuses on image and economic factors.

“Everyone out there says you get higher rents in a community center,” Hardin said. “The question behind this research was, ‘Does this actually hold true in practice?’”

To get beyond the anecdotal, he and a colleague analyzed property-specific data, competing center data, and trade area data for 370 neighborhood and community centers taken from a census of retail centers for a single large MSA—Atlanta, GA.

Property-specific data included image factors from L-shaped centers versus U-shaped configurations, the appearance of the adjacent areas, whether a left turn lane existed, corner locations, and non-traditional exteriors. Having identified these and other variables, including purchasing power in the trade areas and competing centers, they then analyzed the data to see which combinations led to premium rents.

Research validates the commonly-held beliefs.

Based on the analysis, they determined that the facts in this case support the subjective assertions.

“Our analysis showed that community centers can command higher rents because they generate more sales from the site so tenants are willing to pay more,” Hardin said. “The research also showed that community and neighborhood center property types can be considered two separate product types and that community centers have systematically higher rental rates than neighborhood centers.”

In addition, the study showed the impact of the proximity of public assistance housing on rental rates.

“Higher income households, when shopping for higher order goods, may not patronize centers surrounded by relatively high concentrations of households on public assistance because people tend to ‘shop up’; that is, they go to areas more affluent than where they live,” Hardin said. “One inference from the study is that re-developers may want to look at enhancing areas adjacent to shopping centers, too.”

Titled “Disaggregating Neighborhood and Community Center Property Types,” the article appeared in the Journal of Real Estate Research, one of the most prestigious journals in the real estate field.

Looking beyond the anecdotal characterizes Hardin’s research bent. Until he dispassionately reviews relevant data, he does not accept claims based on anecdotes—even though, in this instance, his objective research findings supported them.

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