Past Choices Research Articles

The effect of imperfect memory recall on risk preferences

AbstractPeople often take on different levels of risk when deciding on future actions compared with when they take actions with immediate consequences. The presently reported research investigated how imperfect recall of previously chosen options influences temporal fluctuations in risk preferences. In two incentivized studies with a waiting time before decision resolution (a 4‐week waiting period from an initial decision), we observed that errors in the recall of previous choices played a substantial role in constructing risk preferences for choices that are usually resolved after a delay. More specifically, in a first study, we found that after a waiting period (i.e., after participants waited for their risky choices to be resolved), participants perceived that they took less risk during their initial choices than they actually did. Importantly, when asked about whether they would change their initial choices, participants declared that they would take riskier choices. In a second study, we tested directly whether such a shift in initial choices could also be demonstrated behaviorally. Results revealed that after beliefs about past choices were induced, participants changed their risk preferences in line with the information presented during belief induction.

AI Recommender System With ML for Agricultural Research

We describe an AI recommender system (RS) with machine learning to harness past user choices and large volumes of data, yet account for changes in weather and management decisions characteristic of agricultural systems. Our goal is to maximize the use of data relevant to solving agricultural problems and improve the efficiency of the scientific workforce while also improving the accuracy of estimates of the amount of food produced. Our example shows how the RS learns data analysis choices from user behavior for predicting agricultural production responses to rainfall and learns to identify classes of agroecosystem responses to alternative climate scenarios. We account for changes in relationships using spatial and temporal statistics. The RS provides a powerful approach to make use of the large amounts of data and scientific expertise in the agricultural enterprise to predict agroecosystem dynamics under changing environmental conditions.

Reinforcement Learning in a Cournot Oligopoly Model

This paper analyzes the learning behavior of firms in a repeated Cournot oligopoly game. Literature shows the degree of information and cognitive capacity of learning firms is a key factor that determines long run outcome of an oligopoly market. In particular, when firms possess the knowledge of market demand and are capable of computing the optimal production quantity given the output of other firms, the resulting market outcome is the Nash equilibrium. On the other hand, imitation that assumes low behavioral sophistication of firms generally favors higher output and converges to the Walrasian equilibrium. In this paper, a reinforcement learning algorithm with low cognitive requirement is adopted to model firms’ learning behavior. Reinforcement learning firms observe past production choices and fine tune them to improve profits. Analytical result shows that the Nash equilibrium is the only fixed point of the reinforcement learning process. Convergence to the Nash equilibrium is observed in computational simulations. When firms are allowed to imitate the most profitable competitor, all states between the Nash equilibrium and the Walrasian equilibrium can be reached. Furthermore, the long run outcome shifts towards the Nash equilibrium as the length of firms’ memory increases.

Measuring Tourist Satisfaction with Nautical Destinations: The Effects of Image, Loyalty, and Past Destination Choice

This article aims to analyze factors determining tourist satisfaction with nautical destinations. To this aim, survey data were collected from 255 nautical tourists visiting Cape Verde and an ordinal logit model was used. Data analysis confirms that tourists' satisfaction increases with the diversity and quality of the nautical and cultural offer, and the security offered by the destination, in line with previous research. As novelty, the affective feelings towards the nautical destination were also found as an important antecedent of nautical tourists' satisfaction conformation. The study also confirms that tourists who had been in the archipelago previously do experience a higher level of satisfaction compared with nonrepeaters. Lastly, the fact of visiting other competing nautical destinations influences the level of satisfaction of the nautical tourists in Cape Verde, although not all previously visited destinations have the same impact. This suggests that strategies for nautical tourism development should be more attentive to establish long-lasting relationships and networking structures with some key competitors, and segment their marketing plans according to tourists' past destination choice. The results are of great importance for several destinations seeking to utilize the promotion of nautical activities as a key driver for tourism competitiveness and positioning improvement.

How decisions and the desire for coherency shape subjective preferences over time

Recent findings suggest a bidirectional relationship between preferences and choices such that what is chosen can become preferred. Yet, it is still commonly held that preferences for individual items are maintained, such as caching a separate value estimate for each experienced option. Instead, we propose that all possible choice options and preferences are represented in a shared, continuous, multidimensional space that supports generalization. Decision making is cast as a learning process that seeks to align choices and preferences to maintain coherency. We formalized an error-driven learning model that updates preferences to align with past choices, which makes repeating those and related choices more likely in the future. The model correctly predicts that making a free choice increases preferences along related attributes. For example, after choosing a political candidate based on trivial information (e.g., they like cats), voters' views on abortion, immigration, and trade subsequently shifted to match their chosen candidate.

Reader response: Assessment and effect of a gap between new-onset epilepsy diagnosis and treatment in the US.

I read with interest the study by Kalilani et al.1 that identified the treatment gap in patients with newly diagnosed epilepsy in the United States and the excellent accompanying editorial by Drs. Berg and Feyissa.2 Hindsight is said to be 20/20 and, as a physician, one is able to evaluate past choices and decisions more clearly than at the time when the choice first presented. Epilepsy is no different; at the time of pathologic onset or clinical presentation, it is difficult to evaluate the course the disease will take in an individual patient. Epilepsy is also unique in that it requires long-term, at times lifelong, treatment with an anticonvulsant drug (many with potentially serious side effects). That, in my view, is a common reason why physicians may choose not to treat epilepsy at the time of clinical presentation in favor of a watchful waiting approach.

Joining a group diverts regret and responsibility away from the individual.

It has recently been proposed that a key motivation for joining groups is the protection from the negative consequences of undesirable outcomes. To test this claim, we investigated how experienced outcomes triggering loss and regret impacted people's tendency to decide alone or join a group, and how decisions differed when voluntarily made alone versus in group. Replicated across two experiments, participants (n = 125 and n = 496) selected whether to play alone or contribute their vote to a group decision. Next, they chose between two lotteries with different probabilities of winning and losing. The higher the negative outcome, the more participants switched from deciding alone to with others. When joining a group to choose the lottery, choices were less driven by outcome and regret anticipation. Moreover, negative outcomes experienced alone, not part of a group vote, led to worse subsequent choices than positive outcomes. These results suggest that the protective shield of the collective reduces the influence of negative emotions that may help individuals re-evaluate past choices.

Identification of Intertemporal Preferences in History-Dependent Dynamic Discrete Choice Models

We study the identification of intertemporal preferences in a stationary dynamic discrete decision model. We propose a new approach which focuses on problems which are intrinsically dynamic: either there is endogenous variation in the choice set, or preferences depend directly on the history. History dependence links the choices of the decision-maker across periods in a more fundamental sense standard dynamic discrete choice models typically assume. We consider both exponential discounting as well as the quasi-hyperbolic discounting models of time preferences. We show that if the utility function or the choice set depends on the current states as well as the past choices and/or states, then time preferences are non-parametrically point-identified separately from the utility function under mild conditions on the data and we may also recover the instantaneous utility function without imposing any normalization on the utility across states.

Dynamic Effects Arise Due to Consumers' Preferences Depending on Past Choices.

We analyzed a dynamic duopoly game where players adopt specific preferences. These preferences are derived from Cobb–Douglas utility function with the assumption that they depend on past choices. For this paper, we investigated two possible cases for the suggested game. The first case considers only focusing on the action done by one player. This action reduces the game’s map to a one-dimensional map, which is the logistic map. Using analytical and numerical simulation, the stability of fixed points of this map is studied. In the second case, we focus on the actions applied by both players. The fixed points, in this case, are calculated, and their stability is discussed. The conditions of stability are provided in terms of the game’s parameters. Numerical simulation is carried out to give local and global investigations of the chaotic behavior of the game’s map. In addition, we use a statistical measure, such as entropy, to get more evidences on the regularity and predictability of time series associated with this case.

The ‘genetic’ effect: Can parties’ past organizational choices condition the development of their internal distribution of power in the cartel party era? Evidence from Finland, 1983–2017

This study critically assesses the claim of the cartel party theory that the party in central office (PCO) has lost its powers to the party in public office (PPO) as parties have adapted to various changes in their operating ‘environment’. The study argues that a party’s tendency to adapt is conditioned by the party’s ‘genetic’ heritage: if the PCO assumed a prominent position during the party’s institutionalization, it can more likely stand against external pressures compared to a PCO that has been traditionally weak. The study compares the development (1983–2017) of two Finnish parties, which hail from polar ‘genetic’ traditions: a social democratic mass party and a conservative cadre party. The change of the party ‘environment’ has strongly supported PCO’s decay. Unlike earlier longitudinal studies on intra-party power balance, the study assesses all significant power dimensions and finds a contradictory development: while the distribution of leadership positions and resources increasingly favour the PPO in both parties, significant ‘genetic’ differences in the distribution of formal decision-making power have not diminished at all. If statutory regulations matter, the results suggest that the PPO cannot ‘insulate’ like the cartel model expects in parties where the PCO’s strong role has been strictly codified.

Scaling Human Effort in Idea Screening and Content Evaluation

Brands and advertisers often tap into the crowd to generate ideas for new products and ad creatives by hosting ideation contests. Content evaluators then winnow thousands of submitted ideas before a separate stakeholder, such as a manager or client, decides on a small subset to pursue. We demonstrate the information value of data generated by content evaluators in past contests and propose a proof-of-concept machine learning approach to efficiently surface the best submissions in new contests with less human effort. The approach combines ratings by different evaluators based on their correlation with the past stakeholder choices, controlling for submission characteristics and textual content features. Using field data from a crowdsourcing platform, we demonstrate that the approach improves performance by identifying nonlinear transformations and efficiently reweighting evaluator ratings. Implementing the proposed approach can affect the optimal assignment of internal experts to ideation contests. Two evaluators whose votes were a priori equally correlated with sponsor choices may provide substantially different incremental information to improve the model-based idea ranking. We provide additional support for our findings using simulations based on a product design survey.

Institutional Change and Institutional Persistence

In this essay, we provide a simple conceptual framework to elucidate the forces that lead to institutional persistence and change. Our framework is based on a dynamic game between different groups, who care both about current policies and institutions and future policies, which are themselves determined by current institutional choices, and clarifies the forces that lead to the most extreme form of institutional persistence (“institutional stasis†) and the potential drivers of institutional change. We further study the strategic stability of institutions, which arises when institutions persist because of fear of subsequent, less beneficial changes that would follow initial reforms. More importantly, we emphasize that, despite the popularity of ideas based on institutional stasis in the economics and political science literatures, most institutions are in a constant state of flux, but their trajectory may still be shaped by past institutional choices, thus exhibiting “path-dependent change†, so that initial conditions determine both the subsequent trajectories of institutions and how they respond to shocks. We conclude the essay by discussing how institutions can be designed to bolster stability, the relationship between social mobility and institutions, and the interplay between culture and institutions.

Construction of Human Motivational Profiles by Observation for Risk Analysis

This study aimed at analyzing the extent to which publicly observable pieces of information representing stakeholders' past and current choices can be utilized for the construction of motivational profiles. Motivation is operationalized by the theory of Basic Human Values, which organizes 10 values capturing distinct aspects of human motivation into a hierarchical order. The construction of motivational profiles for individual stakeholders is motivated by the need to enhance the existing decision-maker model in the Conflicting Incentives Risk Analysis (CIRA) method. This study utilized an online questionnaire to collect responses from participants (n = 331) about a wide range of habits and personal items that are easily observable in various contexts by an analyst. The validity of the set of observables as surrogate predictors of the motivational profiles is evaluated by various methods (i.e., comparison to previous results, cross-validation of models, comparison to test-retest reliability of the psychometric instrument) and techniques (calculation of prediction interval for individual profile scores). The assessment of the uncertainties associated with predicting motivational profiles is explored in detail. Additionally, an example illustrates how the profiles can be utilized for the assessment of action desirability (i.e., prediction of behavior) based on the utility calculations established in CIRA. The results contribute to an improved understanding about the accuracy with which human stakeholder motivation can be inferred from public observables and utilized within the context of information security risk analysis.

Matching in Labor Marketplaces: The Role of Experiential Information

Online labor marketplaces assign workers to short-term jobs. For some jobs, the choice of the best worker is based on ex-ante observable information (e.g., driver assignment based on location in ride-hailing). In others, the assignment is driven by experiential information, that is information obtained privately only through the worker performing the job (e.g., the fit of a childcare provider with a family). This study develops an empirical framework to impute the relative importance of each kind of information from participants' past hiring choices. Our moment inequality approach accommodates high worker turnover, varying choice sets, and limited observations of a very large number of market participants -- all key characteristics of online labor markets. We apply our framework to two markets, exploiting a natural experiment that changed marketplace commissions. Based on over 1.2M hiring decisions, we estimate that experiential information is a key driver of hiring choices, while ex-ante observable fit is relevant only for the simplest jobs. Using our estimates, we propose and evaluate alternate assignment policies. The best-performing policies prioritize repeat work and, surprisingly, ignore ex-ante observable information to instead experiment with new workers and generate experiential information. Such policies can increase buyer welfare by as much as 45.3% (47.1%) of gross revenue in the Data Entry (Web Development) market compared to the current practice of skills-based matching. Policies exploiting buyers' past revealed preferences (in repeat work) without incorporating exploration still under-perform by 18.9% in Data Entry and 8.7% in Web Development.

Confirmation bias in the utilization of others' opinion strength.

Humans tend to discount information that undermines past choices and judgments. This confirmation bias has significant impact on domains ranging from politics to science and education. Little is known about the mechanisms underlying this fundamental characteristic of belief formation. Here we report a mechanism underlying the confirmation bias. Specifically, we provide evidence for a failure to use the strength of others' disconfirming opinions to alter confidence in judgments, but adequate use when opinions are confirmatory. This bias is related to reduced neural sensitivity to the strength of others' opinions in the posterior medial prefrontal cortex when opinions are disconfirming. Our results demonstrate that existing judgments alter the neural representation of information strength, leaving the individual less likely to alter opinions in the face of disagreement.

Tracing the Resilience and Revitalisation of Historic Taro Production in Waipi`o Valley, Hawai`i

The resilience and revitalisation of taro/kalo agriculture in the Hawaiian contact period is analysed in Waipi‘o Valley, on the Big Island of Hawai‘i. Historic work has demonstrated the effects of colonial contact on the people of Waipi‘o. Documents from the Māhele period, census information and missionary records are combined to paint a picture of how life unfolded in Waipi‘o Valley over time. What is alluded to, and yet unexplored, is the changing production system and an overall trend of decreasing and fluctuating wetland taro production, where traditional cultivation is transformed by the introduction of rice farming. Later in time this too fades out, when taro again becomes dominant. Interestingly, wetland taro cultivation in Waipi‘o is still practiced today, with interest in revitalising the capacity of a once intensively cultivated valley. Here, the impact of rice, and other crop introductions, is explored in terms of revitalising these wetland traditions. This was done by generating “snapshots” of the landscape through time. Information detailing traditional owners, plot locations and pondfields metrics were derived from digitised historic survey maps, and modern remote sensing techniques such as high resolution LiDAR (Light detection and ranging) imagery. Combining this information not only catalogued the historic trend of declining wetland irrigation, but directly illustrates the influence of past agricultural choices on modern wetland revitalisation agendas.

The neural basis of shared preference learning.

During our daily lives, we often learn about the similarity of the traits and preferences of others to our own and use that information during our social interactions. However, it is unclear how the brain represents similarity between the self and others. One possible mechanism is to track similarity to oneself regardless of the identity of the other (Similarity account); an alternative is to track each other person in terms of consistency of their choice similarity with respect to the choices they have made before (consistency account). Our study combined functional Magnetic Resonance Imaging (fMRI) and computational modelling of reinforcement learning (RL) to investigate the neural processes that underlie learning about preference similarity. Participants chose which of two pieces of artwork they preferred and saw the choices of one agent who usually shared their preference and another agent who usually did not. We modelled neural activation with RL models based on the similarity and consistency accounts. Our results showed that activity in brain areas linked to reward and social cognition followed the consistency account. Our findings suggest that impressions of other people can be calculated in a person-specific manner, which assumes that each individual behaves consistently with their past choices.

Why Do We Procrastinate? Present Bias and Optimism

Research has shown that procrastination has signicant adverse effects on individuals, including lower savings and poorer health. Procrastination is typically modeled as resulting from present bias. In this paper we study an alternative: excessively optimistic beliefs about future demands on an individual's time. The models can be distinguished by how individuals respond to information on their past choices. Experimental results refute the hypothesis that present bias is the sole source of dynamic inconsistency, but they are consistent with optimism. These findings offer an explanation for low takeup of commitment and suggest that personalized information on past choices can mitigate procrastination.

Alumni Networks and Investment Strategy: Evidence from Chinese Mutual Funds

ABSTRACT While fund managers are connected by interpersonal linkages, the investment strategy of a mutual fund would follow a similar pattern due to interpersonal communications and information exchange. This paper focuses on the connection of fund managers via a shared educational network (university alumni connection) in China. Based on a manually collected dataset with the detailed transaction and manager information, our results were threefold: (1) Mutual fund managers with an alumni connection tend to have similar portfolio allocation; the network effect is heterogeneous for different manager characteristics, fund characteristics, and alumni types. (2) A dynamic learning strategy for fund managers exists where they tend to mimic the past portfolio choices of others within the alumni network. (3) The performance of connected funds is worsened by the degree of the connection.

Fight or flight? Market positions, submarket interdependencies, and strategic responses to entry threats

AbstractResearch SummaryThis paper examines how incumbent firms' market positions and interdependencies across their submarkets influence their responses to entry threats. We adapt a model of capacity deterrence to show that because premium and low‐cost incumbents face different demand functions and operating costs, they experience different tradeoffs between ignoring, deterring, and accommodating threatened entry. In addition, the interdependencies within and between a premium incumbent's submarkets influence its responses. Using data on incumbent responses to entry threats from Southwest Airlines between 2003 and 2012, we find that (a) full‐service incumbents expanded capacity while low‐cost incumbents did not respond significantly, and (b) full‐service incumbents expanded capacity less aggressively in submarkets that had less substitutable customer segments and submarkets that were more complementary with their unthreatened submarkets.Managerial SummaryAn immutable market position is a core competitive advantage. Using data on incumbent responses to entry threats from Southwest Airlines between 2003 and 2012, we find that (a) full‐service (FSC) incumbents expanded capacity while low‐cost (LCC) incumbents did not respond significantly, and (b) FSCs expanded capacity less aggressively on routes that were expected to have a large number of business passengers and routes that connected to their international hubs. These results suggest two sources of positional immutability: While one set of past choices (e.g., those about submarket substitutability or complementarity) provide a barrier against imitation, another set of past choices (e.g., those about products and costs) generate incentives for a tough defense, both deterring entry by firms from a different position.