Neighborhood Perception Data and Needs Analysis: Tools for Small Business Site Selection and Retail Mix in the Discovery District in Downtown Columbus, Ohio, USA
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Date
2018-05
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The Ohio State University
Abstract
This thesis proposes two potential tools for understanding neighborhood retail mix in the Discovery District in Downtown Columbus, Ohio, USA. While downtown has been growing and gaining residents since 2010, the retention rate of businesses has remained relatively the same regardless of the increase in residents. The first tool is perception data. Both community members within a neighborhood, and citizens not affiliated with a neighborhood, have perceptions of both the community and what is in it. Perceptions can differ regardless of statistical data, built infrastructure, or resources provided. In terms of economic development, what does perception mean for business site selection in neighborhoods? Perceptions of a neighborhood can cause people to believe one neighborhood to be an economic destination before others. The second tool asks "how are we understanding what community needs are not being met in a neighborhood if a specific business type is desired"? This thesis uses Maslow's Hierarchy of Needs to use a psychological definition of "need". Then, business are assigned a level on the hierarchy to define what human need(s) the business provides. Looking at community retail mix from a "needs" perspective could provide insight into community business infill suggestions and community perception. Both perception data and the Maslow Needs analysis are proposed in this thesis to be possible improvements business infill and points of communication when the business sector and community members feel disconnected.
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neighborhood retail mix, perception data, discovery district, downtown columbus