Maintaining current and future infrastructure will require smart practices to help better meet user needs with fewer financial resources. The recent adoption of information communication technologies, such as, 311-call centers enables city agencies to detect and more quickly respond to real-time infrastructure system service disruptions and maintenance requests. Of the 200 or more cities that use 311, New York City's system is the largest, receiving more than 19.5 million citizen requests since 2010. Current citizen service requests made through 311 range from issues about street and sidewalk conditions to problems with their water, sanitation, snow removal, and traffic congestion. In the first manuscript, service requests were compared to socio-economics within zip codes. Zip codes were clustered by four socio-economic variables including median house value, percent of the population with a bachelor's degree, unemployment rate, and percent non-white to represent socio-economic differences between zones in the city. Results show that citizens from low socio-economic areas, meaning those with low median house values, low population with a bachelor's degree, high unemployment, and high percent non-white are burdened with significantly more infrastructure maintenance requests. When controlling for physical differences such as miles of road, total frequency of calls, and the number of people per zip code, people from low socio-economic zones are more likely to call about issues related to street conditions, sanitation, and their water system. In the second manuscript, service request response time by agency were compared based on location and socio-economic variables. The location of the call based on borough and the socio-economic characteristics of the zip code do significantly influence agency response time. Citizens reporting issues in Queens can expect to wait significantly longer, about 3 days more, to receive a response for a similar request in other boroughs of New York City. This is for issues about water, sewer, traffic lights, and street condition. The Department of Transportation, Department of Sanitation, and the New York Police Department respond significantly faster to service requests in zones classified with high and middle socio-economic groups compared to zip codes with low socio-economic groups of people. These differences in geography and socio-economic characteristics suggest unequal treatment of maintenance issues. These differences in response may expose an implicit bias in maintenance response. By recognizing these differences, city engineers can begin to prioritize maintenance issues based on how communities perceive infrastructure in need of repair, and thus better meet the needs of individual citizens in the future. / Master of Science / Infrastructure includes systems including buildings, roads, water/wastewater, trash, and various other networks that facilitate citizens everyday lives. These infrastructure systems will always require maintenance in order to keep it running effectively and efficiently. Using smart and sustainable practices in this process can help better meet user needs, while saving more money. Using more technology such as 311-call centers can allow cities to detect and more quickly respond to real-time infrastructure disruptions and maintenance issues. 311 call centers receive calls about anything from street condition problems such as potholes to problems with their drinking water. Of the 200 or more cities that use 311, New York City’s system is the largest, receiving more than 20 million citizen requests since 2010. The first manuscript looks into what certain types of people call about. Using zip codes, areas of the city were grouped together based on four socio-economic variables; median house value, percent of the population with a bachelor’s degree, unemployment rate, and percent non-white. People from low socio-economic areas, meaning those with low median house values, low population with a bachelor’s degree, high unemployment, and high percent non-white call more about infrastructure maintenance requests. When controlling for physical aspects of these areas such as miles of road, total amount of calls, and the number of people per zip code, people from low socio-economic areas are more likely to call about issues related to street conditions, sanitation, and their water system. The second manuscript looks into how long it takes government agencies to respond and resolve these calls. The location of the call based on location in the city and the socio-economic characteristics of the zip codes have an effect on agency response time. People reporting issues in Queens can expect to wait much longer, about 3 days more, to receive a response for a similar issue called from another borough of New York City. The Department of Transportation, Department of Sanitation, and the New York Police Department respond significantly faster to service requests in areas with high and middle socio-economic status groups compared to zip codes with low socio-economic groups of people. By knowing that location and socio-economic status matter when citizens call 311, city engineers can begin to use this data to help prioritize maintenance issues based on specific areas and needs of individual people in the future. These differences in location and socio-economic characteristics could possibly suggest unequal treatment of maintenance issues. However, since the differences seen in this research are with only certain variables accounted for, further research will be needed to help show possible causation for these differences.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/88492 |
| Date | 19 March 2019 |
| Creators | Bolte, Taylor Clark |
| Contributors | Civil and Environmental Engineering, Shealy, Earl W., Garvin, Michael J., Baird, Timothy D. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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