I am a Ph.D. candidate in the School of Information Systems, Singapore Management University (SMU) since 2013 under the supervision of  Prof. Robert Kauffman and Prof. Mei Lin. Prior to that, I received a B. Eng. degree in Electrical Engineering from Universitas Indonesia in 2002 and an MBA degree in International Management from the International University of Japan in 2007. My research primarily focuses on the interdisciplinary intersection of information, technology, sustainability and policy analytics. My research uses a fusion of machine-based data analysis methods and explanatory empiricism for assessing the effects of environmental policies. This aims to support decision-makers in formulating policies in order to achieve a more sustainable future.

Governments have developed policies in the form of rules, regulations, taxation, pricing schemes, advisories, and other directives to address environmental issues (e.g., pollution, endangered animal species, and resource depletion.) This dissertation aims to create a more informed and data-supported policy-making approach in environmental management by employing data analytics, mathematical programming, optimization, econometrics, and spatiotemporal analysis. It consists of three essays. Essay 1 discusses household informedness, a construct that is defined as “the degree to which household have the necessary information to make utility-maximizing decisions in their daily activities, such as managing their household waste.” It also analyses the impact of informedness on the collection and recycling of household hazardous waste (HHW) using econometric methods. Essay 2 assesses how geospatial locations affect the HHW collection and whether those effects change over time, using spatial autocorrelation analysis and geographically weighted regression. Finally, Essay 3 examines the impacts of new carbon pollution standards on electricity generation and water use in Texas using mathematical programming. These essays demonstrate the use of a variety of data analytics and management science methods that represent promising advances in policy analytics that help design data-driven policies and promote environmental sustainability and resources for future generations.

Reacting to the New Carbon Pollution Standards: Electric Power Generation Pathways and Their Water Impacts (Co-Authors: Prof. Haibo Zhai, Prof. Rob Kauffman, Prof. Ed Rubin - Carnegie Mellon University). [preliminary research poster]

Lim-Wavde, K., Kauffman, R.J. and Dawson, G.S., 2016. Policy Analytics, Household Informedness and the Collection of Household Hazardous Waste. In MATEC Web of Conferences (Vol. 68, p. 14003). EDP Sciences. [pdf]

Lim-Wavde, K., Kauffman, R.J., Kam, T.S., Dawson, G.S., 2017. Location Matters: Geospatial Policy Analytics over Time for Household Hazardous Waste Collection in California. In iConference 2017 Proceedings. [pdf]

Lim-Wavde, K., Kauffman, R.J., Dawson, G.S. 2016. Household Informedness and Policy Analytics for the Collection and Recycling of Household Hazardous Waste in California. In Resources, Conservation and Recycling. [working paper pdf]