Extending the Choice Architecture Toolbox: The Choice Context Mapping

Abstract

The role of context in behavioral interventions is indisputable, yet few intervention studies start with a systematic mapping of the influencing contextual factors. This is mostly due to the lack of a methodology that researchers can employ for this aim. Recognizing this current limitation of the field, we developed a procedure, the Choice Context Mapping, to provide researchers a tool to examine the contextual factors of a targeted behavior. We demonstrate the steps of Choice Context Mapping on the behavioural choice situation of stairs vs. elevator use. Potential contextual factors were collected from laypeople as well as experts, and two surveys were created to measure both the behavior and choice, as well as the beliefs of participants. We estimated the effect of contextual factors on the participants’ behavior and managed to identify the most influential ones regarding their contribution to the studied choice. Using Choice Context Mapping, we obtained an accurate prediction of whether one chooses the stairs or elevator based on contextual information in 93.26% of the cases, on previously unseen data. We also ascertained that participants differed in their beliefs about what influences them in this particular choice, and that they can be divided into different groups based on their beliefs. Our results indicate that Choice Context Mapping is a useful procedure for the collection and assessment of contextual factors in a given choice setting which can help the planning of behavioral interventions by considerably lowering the number of possible interventions that are plausibly effective.

Generalizability and Effectiveness of Choice Architecture Interventions

“…The selection of these methods can be flexible, depending on available resources and the specific setting. For instance, Hajdu et al 149 used literature review, expert reports and surveys of lay people to identify the factors influencing individuals' choices between stairs and elevators, resulting in the collection of 16 potential moderators. Utilizing this information, the authors successfully predicted 93% of individuals' choices in a subsequent study, underscoring the crucial role such information plays in choice architecture interventions geared toward increasing stair usage.…”

Contextual factors predicting compliance behavior during the COVID-19 pandemic: A machine learning analysis on survey data from 16 countries

“…We define contextual factors as the physical and sociocultural environment along with the intrapersonal circumstances, such as mental states, present at the time of the choice that may affect decisions. Contextual factors can accurately predict decisions in simple situations where most of this contextual information can be identified [4]. Identifying the contextual factors of non-adherence to lockdown recommendations and exploring their relative predictive strength will provide insight into decisions that put individuals and communities at risk.…”