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Service quality modeling to support optimizing facility location in a microscale environment

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  • Pludow, B. Amelia
  • Murray, Alan T.
  • Church, Richard L.

Abstract

After initial planning and implementation, many systems evolve as a byproduct of fragmented decision-making processes and incremental change over time, with little system-wide reanalysis. This lack of reevaluation means that an originally optimal system may become suboptimal with respect to demand to be served or service performance. Assessing system design and configuration provides an opportunity to enhance overall service quality as well as reduce operational costs. This paper uses location analytics, including spatial optimization and geographic information systems (GIS), to support system reassessment and planning efforts. A case study focused on wireless Internet access across a university campus is presented. The results suggest that there are varying levels of access to wireless service, this variation is driven in part by system history and fragmented decision-making processes, and there is an opportunity to significantly enhance the quality of service through planning efforts focused on optimal system reconfiguration. These findings highlight the importance of analytics based planning in design, modification, or extension of a spatial service system.

Suggested Citation

  • Pludow, B. Amelia & Murray, Alan T. & Church, Richard L., 2022. "Service quality modeling to support optimizing facility location in a microscale environment," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    • Handle: RePEc:eee:soceps:v:82:y:2022:i:pb:s0038012122000519
    DOI: 10.1016/j.seps.2022.101273
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    References listed on IDEAS

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