Most applications of game theory assume equilibrium, justified by presuming either that learning will have converged to one, or that equilibrium approximates people's strategic thinking even when a ...learning justification is implausible. Yet several recent experimental and empirical studies suggest that people's initial responses to games often deviate systematically from equilibrium, and that structural nonequilibrium "level-k" or "cognitive hierarchy" models often out-predict equilibrium. Even when learning is possible and converges to equilibrium, such models allow better predictions of history-dependent limiting outcomes. This paper surveys recent theory and evidence on strategic thinking and illustrates the applications of level-k models in economics.
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BFBNIB, CEKLJ, INZLJ, IZUM, KILJ, NMLJ, NUK, ODKLJ, PILJ, PNG, SAZU, UL, UM, UPUK, ZRSKP
The importance of customer-oriented marketing has increased for companies in recent decades. With the advent of one-customer strategies, especially in e-commerce, traditional mass marketing in this ...area is becoming increasingly obsolete as customer-specific targeting becomes realizable. Such a strategy makes it essential to develop an underlying understanding of the interests and motivations of the individual customer. One method frequently used for this purpose is segmentation, which has evolved steadily in recent years. The aim of this paper is to provide a structured overview of the different segmentation methods and their current state of the art. For this purpose, we conducted an extensive literature search in which 105 publications between the years 2000 and 2022 were identified that deal with the analysis of customer behavior using segmentation methods. Based on this paper corpus, we provide a comprehensive review of the used methods. In addition, we examine the applied methods for temporal trends and for their applicability to different data set dimensionalities. Based on this paper corpus, we identified a four-phase process consisting of information (data) collection, customer representation, customer analysis via segmentation and customer targeting. With respect to customer representation and customer analysis by segmentation, we provide a comprehensive overview of the methods used in these process steps. We also take a look at temporal trends and the applicability to different dataset dimensionalities. In summary, customer representation is mainly solved by manual feature selection or RFM analysis. The most commonly used segmentation method is k-means, regardless of the use case and the amount of data. It is interesting to note that it has been widely used in recent years.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This paper reports an experiment that elicits subjects' initial responses to 16 dominance-solvable two-person guessing games. The structure is publicly announced except for varying payoff parameters, ...to which subjects are given free access. Varying the parameters allows very strong separation of the behavior implied by leading decision rules. Subjects' decisions and searches show that most subjects understood the games and sought to maximize payoffs, but many had simplified models of others' decisions that led to systematic deviations from equilibrium. The predictable component of their deviations is well explained by a structural nonequilibrium model of initial responses based on level-k thinking.
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This corrects the article DOI: 10.1371/journal.pone.0273971..This corrects the article DOI: 10.1371/journal.pone.0273971..
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5.
Choice, deferral, and consistency Costa-Gomes, Miguel A; Cueva, Carlos; Gerasimou, Georgios ...
Quantitative economics,
July 2022, Volume:
13, Issue:
3
Journal Article
Peer reviewed
Open access
We report on two novel choice experiments with real goods where subjects in one treatment are forced to choose, as is the norm in economic experiments, while in the other they are not but can instead ...incur a small cost to defer choice. Using a variety of measures, we find that the active choices (i.e., those that exclude the deferral outside option) of subjects in the nonforced-choice treatment are generally more consistent. We also find that the combined deferral and active-choice behavior of subjects in that treatment is explained better by a model of dominant choice with incomplete preferences than it is by rational choice. Our results suggest that nonforced-choice experiments and models can be helpful in separating people's rational, hesitant/not-yet-rational and genuinely irrational behavior, and can potentially offer important new insights in revealed preference analysis.
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Using data on one-shot games, we investigate whether players' actions can be viewed as responses to underlying expectations about their opponent's behaviour. In our laboratory experiments, subjects ...play a set of 14 two-person 3x3 games and state beliefs about which actions they expect their opponents to play. The data sets from the two tasks are largely inconsistent. Rather, we find evidence that the subjects perceive the games differently when they (i) choose actions and (ii) state beliefs--their stated beliefs reveal deeper strategic thinking than their actions. On average, they fail to best respond to their own stated beliefs in almost half of the games. The inconsistency is confirmed by estimates of a unified statistical model that jointly uses the actions and the belief statements. There, we can control for decision noise and formulate a statistical test that rejects consistency. Effects of the belief elicitation procedure on subsequent actions are mostly insignificant.
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We report an experiment that asks whether people in a strategic situation behave according to the Golden Rule, that is, do not treat others in ways that they find disagreeable to themselves, a ...property that we call role‐reversal consistency. Overall, we find that over three quarters of the subjects are role‐reversal consistent. Regression analysis suggests that this finding is not driven by players maximizing their subjective expected monetary earnings given their stated beliefs about their opponents' behavior. We find that subjects' stated beliefs and actions reveal mild projection bias. (JEL C78, C91)
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•Data mining framework capable of assessing the quality of heuristic solutions.•Regression model fitted with bottom-left-fill solutions and 19 predictors.•30,000 problem instances were generated to ...represent different 2D-SPP variations.•Random forest is the data mining technique with the best level of generalisation.•Data mining framework is consistent and can be applied for other problems.
In this paper, we explore the use of reference values (predictors) for the optimal objective function value of hard combinatorial optimization problems, instead of bounds, obtained by data mining techniques, and that may be used to assess the quality of heuristic solutions for the problem. With this purpose, we resort to the rectangular two-dimensional strip-packing problem (2D-SPP), which can be found in many industrial contexts. Mostly this problem is solved by heuristic methods, which provide good solutions. However, heuristic approaches do not guarantee optimality, and lower bounds are generally used to give information on the solution quality, in particular, the area lower bound. But this bound has a severe accuracy problem. Therefore, we propose a data mining-based framework capable of assessing the quality of heuristic solutions for the 2D-SPP. A regression model was fitted by comparing the strip height solutions obtained with the bottom-left-fill heuristic and 19 predictors provided by problem characteristics. Random forest was selected as the data mining technique with the best level of generalisation for the problem, and 30,000 problem instances were generated to represent different 2D-SPP variations found in real-world applications. Height predictions for new problem instances can be found in the regression model fitted. In the computational experimentation, we demonstrate that the data mining-based framework proposed is consistent, opening the doors for its application to finding predictions for other combinatorial optimisation problems, in particular, other cutting and packing problems. However, how to use a reference value instead of a bound, has still a large room for discussion and innovative ideas. Some directions for the use of reference values as a stopping criterion in search algorithms are also provided.
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Charities differ, among other things, alongside the likelihood that their interventions succeed and produce the desired outcomes and alongside the extent that such likelihood can even be articulated ...numerically. In this paper, we investigate what best explains charitable giving behaviour regarding charities that have interventions that will succeed with a quantifiable and high probability (sure-thing charities) and charities that have interventions that only have a small and hard to quantify probability of bringing about the desired end (probabilistic charities). We study individual differences in risk/ambiguity attitudes, empathy, numeracy, optimism, and donor type (warm glow vs. pure altruistic donor type) as potential predictors of this choice. We conduct a money incentivised, pre-registered experiment on Prolific on a representative UK sample (n = 1,506) to investigate participant choices (i) between these two types of charities and (ii) about one randomly selected charity. Overall, we find little to no evidence that individual differences predict choices regarding decisions about sure-thing and probabilistic charities, with the exception that a purely altruistic donor type predicts donations to probabilistic charities when participants were presented with a randomly selected charity in (ii). Conducting exploratory equivalence tests, we find that the data provide robust evidence in favour of the absence of an effect (or a negligibly small effect) where we fail to reject the null. This is corroborated by exploratory Bayesian analyses. We take this paper to be contributing to the literature on charitable giving via this comprehensive null-result in pursuit of contributing to a cumulative science.
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