Do Street Fairs Boost Local Businesses? A Quasi-Experimental Analysis Using Social Network Data

• Published in: Machine Learning and Knowledge Discovery in Databases Vol. 9853; pp. 161 - 176
• Main Authors: Zhang, Ke, Pelechrinis, Konstantinos
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Difference-in-Differences; Local businesses; Quasi-experimental design; Social media; Urban informatics
• ISBN: 9783319461304; 3319461303
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-46131-1_22

Local businesses and retail stores are a crucial part of local economy. Local governments design policies for facilitating the growth of these businesses that can consequently have positive externalities on the local community. However, many times these policies have completely opposite from the expected results (e.g., free curb parking instead of helping businesses has been illustrated to actually hurt them due to the small turnover per spot). Hence, it is important to evaluate the outcome of such policies in order to provide educated decisions for the future. In the era of social and ubiquitous computing, mobile social media, such as Foursquare, form a platform that can help towards this goal. Data from these platforms capture semantic information of human mobility from which we can distill the potential economic activities taking place. In this paper we focus on street fairs (e.g., arts festivals) and evaluate their ability to boost economic activities in their vicinity. In particular, we collected data from Foursquare for the three month period between June 2015 and August 2015 from the city of Pittsburgh. During this period several street fairs took place. Using these events as our case study we analyzed the data utilizing propensity score matching and a quasi-experimental technique inspired by the difference-in-differences method. Our results indicate that street fairs provide positive externalities to nearby businesses. We further analyzed the spatial reach of this impact and we find that it can extend up to 0.6 miles from the epicenter of the event.