Why would businesses help homeless individuals? Machine learning insights into the motivation of business improvement districts

Purpose - Local business communities have taken various approaches to address homelessness, some of which have been criticized for their strong-arm and short-sighted methods. A business improvement district (BID) is a local district management organization representing business communities’ interests. This study aims to explain the factors that influence BIDs’ decisions on addressing homelessness, taking community characteristics and the degree of homelessness into account. Design/methodology/approach - The authors investigate the critical factors explaining BIDs’ approaches to homelessness using survey data and machine learning. Decision trees, contingency tables and a causal loop diagram were used to identify and connect these factors conceptually. Findings - BIDs’ response to the homelessness problem is multi-layered. With limited funds, BIDs tend to respond to the severity of homelessness by investing in law enforcement. However, sufficiently funded BIDs are likely to invest in human resources, which help them implement more holistic strategies such as outreach and needs assessment of homeless individuals. Social implications - Considering BIDs’ increasing role in place management and governance, whether BIDs can be motivated to act socially responsibly raises important questions about the potential for private actors and public–private partnerships in resolving homelessness issues. Originality/value - Few studies have explored the factors that motivate or impede BIDs’ engagement with people experiencing homelessness. The authors propose a corporate social responsibility perspective to conceptualize the role of BIDs in a virtuous feedback loop, by which businesses not only help mitigate the homelessness problem but also enhance their own performance in the long term when they implement forward-thinking approaches.