Examination of Social Disparities/Inequalities in Utilization and Quality of 311 Services

Background:

Residents use 311 services to report city-related non-emergency issues based on their observations (such as litter, illegal dumping, and water pollution). Researchers have accumulated extensive knowledge on the bias of submitting service requests resulting from persistent spatial, racial, and economic inequalities in cities (Kontokosta & Hong, 2021). Previous analysis reveals that residents in different communities of a city experienced inequitable service quality, i.e., missed or unreported potential issues, and diverse response time for addressing reported issues. Few studies focused on the service quality provided to residents with diverse social backgrounds. This study aims to identify the disparities/inequalities in the requests and delivery of 311 services in a southeast city and investigate how different individual- and community-level factors might affect residents’ utilization patterns and the quality of services received.

Methods:

This is a collaborative project among researchers from computer science, social work, and psychology using both primary and large secondary data. Secondary data combined City 311 requests data (types of services requested, priority, response time, etc.) and American Community Survey data (community-level demographics and socioeconomic data). The sample included 90,233 service users in 2016. Linear regression models were used to examine the effects of community-level factors on service quality (measured by response time) to different service requests. Primary data were collected from residents in the city via an online anonymous survey in Qualtrics to identify individual-level predictors of service utilization patterns and satisfaction (data collection is ongoing and current N= 66). Logistic regression models were used to predict the pattern of 311 service use based on individual demographics, socioeconomics, perception of communities, and civil participation.

Results:

Secondary data analysis showed that community-level factors such as population size, median age, % of the Black and % of Hispanic population, average household size, median income, and average years of houses can all predict the response time (in days) with a small effect size controlling the priority level of the requests. When controlling the types of requests, only % of Hispanic (b=.03, p<0.05) and average years of houses (b=-.02, p <0.01) are significant predictors. % of other racial groups, education attainment, and % house ownership are not significant predictors for both models. Also, predictors of response time differ across the request types (Bulk collection, trash flash, garbage container repair, and replacement, etc). Preliminary results with the limited amount of primary data showed that black Americans were more likely to request 311 services than Whites (OR=5.6, p<0.01). Employment status and income also showed potential influence on service use.

Implications:

The results suggest that there are disparities in service utilization and quality due to demographics or socioeconomic factors, however, the differences in the effects of community-level factors varied by the types of service requests. The primary data also reveals that residents want faster service delivery, expanded language options, and facilitated collaboration with other government agencies, etc. Social workers better advocate for the residents in the communities that may under-use or receive low-quality services and reduce the social inequality of 311 services based on the findings.