Click here to access the GitHub repository containing the full demo and files.
Thank you for your interest in Query Theory (QT) and the aspect-listing paradigm!
Query Theory is a prominent model of the cognitive processes that guide decision-making. According to QT, people evaluate options by sequentially “querying” their memory for thoughts that support or oppose particular choices. For example, when deciding between receiving a $40 Amazon gift card today or waiting a week for $45, you might first retrieve a thought favoring immediacy (“I want to read that new book right away”) or instead retrieve a thought supporting delay (“I don’t need anything now, so the extra $5 is worth it”). The order and content of these queries can meaningfully shape the final decision.
Aspect listing—a structured thought-listing or “think-aloud” method—allows researchers to observe these internal queries as they unfold. Participants type out their thoughts while evaluating decision options, and our Qualtrics setup automatically saves each thought. This enables researchers to later ask targeted follow-ups (e.g., “On a scale of 1–7, how strongly does Thought J support Option K?”) and to analyze the sequence and structure of thought generation.
This tool offers a flexible approach for studying how preferences are constructed across different contexts. In foundational work, Weber (2007) showed that people tend to choose the option for which they first list supportive thoughts. Subsequent research demonstrated that instructing participants to reverse their natural thought order can even eliminate the endowment effect (Johnson et al., 2017).
A demonstration of the aspect-listing interface is shown in the linked GitHub repository. To explore the full interactive setup yourself, visit the GitHub repository and download the Aspect_Listing_Demo.qsf file.