Sequential Decisions from Sampling: Inductive Generation of Stopping Decisions Using Instance-Based Learning Theory

Sequential decisions from sampling are common in daily life: we often explore alternatives sequentially, decide when to stop such exploration process, and use the experience acquired during sampling to make a choice for what is expected to be the best option. In decisions from experience, theories of sampling and experiential choice are unable to explain the decision of when to stop the sequential exploration of alternatives. In this chapter, we propose a mechanism to inductively generate stopping decisions, and we demonstrate its plausibility in a large and diverse human data set of the binary choice sampling paradigm. Our proposed stopping mechanism relies on the choice process of a theory of experiential choice, Instance-Based Learning Theory (IBLT). The new stopping mechanism tracks the relative prediction errors of the two options during sampling, and stops when such difference is close to zero. Our results from simulation are able to accurately predict human stopping decisions distributions in the dataset. This model provides an integrated theoretical account of decisions from experience, where the stopping decisions are generated inductively from the sampling process.

Consistency in identity-related sequential decisions

Consumers often make decisions that reflect either personal or social identities. In many cases, such decisions are made along a sequence. Our research introduces a central factor that influences consumers’ likelihood of expressing a consistent identity type along a sequence of decisions: the extent to which their usage of the product involved in the first decision is expected to be observable by others (the product’s expected visibility). A field experiment, and four lab studies, coupled with an internal meta-analysis, show that when the product involved in the first decision has high (as opposed to low) expected visibility, consumers are more likely to make a subsequent decision that is consistent with the first. Results show that self-presentation mediates this effect, and suggest that low integration between the identities involved in the decisions might attenuate it. Our findings offer implications for identity research and practical implications for marketers seeking to develop products and design communications that encourage consistent (or inconsistent) behavior.

D Minus Months: Strategic Planning for Weather-Sensitive Decisions

General Eisenhower’s decisions to postpone and, one day later, to launch the “D-Day” invasion of Normandy are a gripping illustration of sequential decisions under uncertainty, suitable for any introductory decision analysis class. They’re also the archetypal example of weather-sensitive decision making using a forecast. This paper develops a framework for analyzing weather-sensitive decisions with a focus on the less-familiar strategic decisions that determine how forecasts are produced and what operational alternatives are available so that decision makers can extract value from forecasts. We tell the story of the decisions made in the months before D-Day regarding how to set up the forecasting process and the myriad decisions implicating nation-level resources that prepared Allied forces not just to invade, but to hold open that decision until the last possible hour so that Eisenhower and his staff could use the critical forecasts. Finally, we overview the current state of the weather-forecasting enterprise, the current challenges of interest to decision analysts, and what this means for decision analysts seeking opportunities to help the weather enterprise improve forecasts and to help operational decision makers extract more value from modern weather forecasts.

Group-Managed Real Options

We study a standard real-option problem in which sequential decisions are made through voting by a group of members with heterogeneous beliefs. We show that, when facing both investment and abandonment timing decisions, the group behavior cannot be replicated by that of a representative “median” member. As a result, members’ disagreement generates inertia—the group delays investment relative to a single-agent case—and underinvestment—the group rejects projects that are supported by a majority of members, acting in autarky. These coordination frictions hold in groups of any size, for general voting protocols, and are exacerbated by belief polarization.

Distributed functions of prefrontal and parietal cortices during sequential categorical decisions

Comparing sequential stimuli is crucial for guiding complex behaviors. To understand mechanisms underlying sequential decisions, we compared neuronal responses in the prefrontal cortex (PFC), the lateral intraparietal (LIP), and medial intraparietal (MIP) areas in monkeys trained to decide whether sequentially presented stimuli were from matching (M) or nonmatching (NM) categories. We found that PFC leads M/NM decisions, whereas LIP and MIP appear more involved in stimulus evaluation and motor planning, respectively. Compared to LIP, PFC showed greater nonlinear integration of currently visible and remembered stimuli, which correlated with the monkeys’ M/NM decisions. Furthermore, multi-module recurrent networks trained on the same task exhibited key features of PFC and LIP encoding, including nonlinear integration in the PFC-like module, which was causally involved in the networks’ decisions. Network analysis found that nonlinear units have stronger and more widespread connections with input, output, and within-area units, indicating putative circuit-level mechanisms for sequential decisions.

EXPRESS: We Succeeded Together, Now What: Relationship Power and Sequential Decisions in Couples' Joint Goal Pursuits

Research has demonstrated that after making high goal progress consumers feel liberated to engage in goal-inconsistent behaviors. But what happens after consumers make high progress in the context of joint goal pursuit? We examine how jointly-made progress towards a joint goal pursued by couples affects subsequent individually-made goal-relevant decisions. Across five experiments with both lab-created couples and married participants and financial data from a couples' money management mobile app, we show that after making high progress on a joint goal (vs. low or no progress), higher relationship power partners are more likely to disengage from the joint goal to pursue personal concerns (e.g., indulge themselves or pursue individual goals), whereas lower relationship power partners do not disengage from the joint goal and continue engaging in goal-consistent actions that maintain its pursuit. We elucidate the underlying mechanism, providing evidence that the joint goal progress boosts the relational self-concept of high (but not low) relationship power partners and this drives the effects. Importantly, we demonstrate the effectiveness of two theory-grounded and easily implementable interventions which promote goal-consistent behaviors among high relationship power consumers in the context of joint savings goals.

Sequential Decision-Making in Ants and Implications to the Evidence Accumulation Decision Model

Cooperative transport of large food loads by Paratrechina longicornis ants demands repeated decision-making. Inspired by the Evidence Accumulation (EA) model classically used to describe decision-making in the brain, we conducted a binary choice experiment where carrying ants rely on social information to choose between two paths. We found that the carried load performs a biased random walk that continuously alternates between the two options. We show that this motion constitutes a physical realization of the abstract EA model and exhibits an emergent version of the psychophysical Weber’s law. In contrast to the EA model, we found that the load’s random step size is not fixed but, rather, varies with both evidence and circumstances. Using theoretical modeling we show that variable step size expands the scope of the EA model from isolated to sequential decisions. We hypothesize that this phenomenon may also be relevant in neuronal circuits that perform sequential decisions.