An Update to Converting Zip Code Data into Distances Using Microsoft Excel Geography Data Type, Maps, and Including Driving Distances

Eric Huggins () and Ivan Guardiola ()
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Eric Huggins: School of Business Administration, Fort Lewis College, Durango, Colorado 81301
Ivan Guardiola: School of Administration, Fort Lewis College, Durango, Colorado 81301

INFORMS Transactions on Education, 2024, vol. 25, issue 1, 35-40

Abstract: In the article “Converting Zip Code Data into Distances: A Case Study for Teaching Business Analytics” [Huggins E (2019) INFORMS Trans. Ed. 19(2):105–107], the author demonstrates how to convert a column of zip code data into approximate distances from a default zip code using standard Microsoft (MS) Excel functions and a zip code database. In this case article, we update that case in three specific areas. First, we explore using the relatively new MS Excel Geography Data Type that, in theory at least, eliminates the need to use the zip code database by accessing required information about each zip code directly from the web. Second, we show how to apply the MS Excel Maps feature to this data. Third, although the original article uses approximate straight-line distances, we show how to extract driving distances between two zip codes using public maps and an application programming interface with MS Excel’s =WEBSERVICE() function. Two of these updates are not as straightforward as one might hope: The Geography Data Type returns a significant number of errors and, although driving distances can be determined, there is no “easy” way to do so yet. We discuss these issues in the case teaching note.

Keywords: active learning; cases; developing analytical skills (search for similar items in EconPapers)
Date: 2024
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