Evaluating Precision, Privacy, and Representation with Cell Phone Data: Evidence from Recreational Demand for Cape Cod Beaches.

Mobility data are a promising tool for valuing recreation, but reliability depends on how data are processed and protected. This study evaluates how data practices affect recreation demand estimation. Using a random utility model of visits to Cape Cod beaches from 2019 to 2022, we estimate the margi...

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Bibliographic Details
Published in:Land Economics Vol. 102; no. 3; pp. 471 - 497
Main Authors: Connolly, Cristina, Steinbach, Sandro, Vo, Mike, Wan, Xibo
Format: Article
Published: University of Wisconsin Press Aug2026
Subjects:
Online Access:View this record in EBSCOhost
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        atl: Evaluating Precision, Privacy, and Representation with Cell Phone Data: Evidence from Recreational Demand for Cape Cod Beaches.
      aug:
        au:
          Connolly, Cristina
          Steinbach, Sandro
          Vo, Mike
          Wan, Xibo
      su:
        Cape Cod (Mass.)
        Privacy
        Leisure
        Electronic data processing
        Willingness to pay
        Beaches
        Location data
        Fecal contamination
      sug:
        subj:
          Privacy
          Leisure
          Electronic data processing
          Cape Cod (Mass.)
          All Other Amusement and Recreation Industries
          Data Processing, Hosting, and Related Services
          Willingness to pay
          Beaches
          Location data
          Fecal contamination
      ab: Mobility data are a promising tool for valuing recreation, but reliability depends on how data are processed and protected. This study evaluates how data practices affect recreation demand estimation. Using a random utility model of visits to Cape Cod beaches from 2019 to 2022, we estimate the marginal willingness to pay (MWTP) for avoiding fecal bacteria contamination. Under recommended practices, MWTP averages $8.92 per visit. Relaxing dwell-time thresholds and applying differential privacy reduce MWTP by 57% and 65%, while short-term choice sets inflate estimates by 10%. These results highlight the need for transparent mobility data practices.
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    language: English
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