Overcoming Status Quo Bias for Resilient Stormwater Infrastructure: Empirical Evidence in Neurocognition and Decision-Making

Abstract

Green infrastructure solutions like bio-retention systems, permeable pavements, and water harvesting programs are cost-effective for stormwater management and more adaptive to a changing climate. However, implementing green infrastructure is constrained by status quo bias. Status quo bias inhibits solutions that do not align with industry norms. The research presented in this paper tests how the formal expression of opinion by city officials for green infrastructure in a municipal resolution neutralizes the effects of status quo bias. Engineering graduate students trained in stormwater management were asked to evaluate two decision scenarios while wearing an instrument that measured brain activation. Each decision scenario included one green and one gray solution. Half of the graduate students randomly received additional information about a newly approved green infrastructure resolution. Students who received this information were significantly more willing to recommend the green over gray option. The resolution reduced their perception of risk associated with green infrastructure. Students who received the resolution perceived risk about cost and performance of green infrastructure as significantly less than the control group. The change in perception about risk was also observable in their brains. The students who received the resolution exerted significantly higher levels of neurocognitive activation in the brain regions associated with risk processing corresponding with a reduction in perceived risk. These results present both behavioral and neurocognitive evidence for how small interventions to the engineering decision-making process can significantly change how engineers construct preferences and make decisions. Municipal resolutions can help overcome status quo bias by suppressing perceptions of risk that arise when deviating from social or industry norms. These results offer a new type of data for how information about engineering is cognitively managed in the brain and how the presentation of this information influences engineering outcomes. These findings offer an initial mind–behavior relationship and opens a new avenue of research in engineering management to explore how engineers cognitively make decisions and the influence of cognitive biases on engineering design.