Location Matters: Geospatial Policy Analytics over time for Household Hazardous Waste Collection in California
Speaker (s): 
Kustini LIM-WAVDE
PhD Candidate
School of Information Systems
Singapore Management University | Date:
Time:
Venue:
| | March 14, 2017, Tuesday
09:00 am - 10:00 am
Meeting Room 4.4, Level 4
School of Information Systems
Singapore Management University
80 Stamford Road
Singapore 178902
We look forward to seeing you at this research seminar. ![]()
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About the Talk
By integrating mapping and geospatial data into a county-level dataset for exploratory analysis, we will demonstrate how to provide useful insights for waste managers and local governments regarding spatial patterns of household hazardous waste (HHW) collection and how it changes over time. We use map-based visualization to display patterns of spatial intensity and county locations for HHW collection in California from 2004 to 2015. We use exploratory spatial data analytics methods to characterize the spatial distribution of HHW collected per person. When we considered the spatial relationships, we were able to develop and estimate a geographically-weighted regression to explain how different regional factors influence the amount of HHW collected. These factors include demographic characteristics, HHW management policy instruments, and environmental quality enforcement and consideration of these factors are necessary to create a successful recycling program.
This a pre-conference talk for iConference 2017.
About the Speaker
Kustini LIM-WAVDE is a Ph.D. student in the School of Information System, Singapore Management University under the supervision of Prof. Robert J. Kauffman. She received her B.Eng. degree in Electrical Engineering from Universitas Indonesia and MBA degree in International Management from the International University of Japan. Her research lies in the interdisciplinary area of information, technology, sustainability, and policy analytics. She is interested in applying data analytics, econometrics, geospatial analysis, math programming, optimization and other relevant methodologies to support decision-makers in formulating policies for environmental sustainability.
