Chương 3 Phân tích hành vi của người mua (buying decision behavior)

The aim of marketing is to engage customers and affect how they think and act. To affect the whats, whens, and hows of buyer behavior, marketers must first understand the whys. final consumer buying influences and processes.

Never mind losing the pound… still got the penny! The influence of trait greed on risky decision behavior in a mixed and gain only BART

Two different reasons to show risky behavior have been identified: Risk proneness and the lack of loss aversion. So far, the number of empirical studies investigating the influence of trait greed, anxiety, and age on risky decision behavior, differentiating between risk sensitivity and loss aversion, is very limited and inconsistent findings exist. The present study investigated this issue using variants of the Balloon Analogue Risk Task (BART) in an online study. Risky decision-making behavior was then assessed by administering two versions of the BART, a gain only and a mixed gambling BART. A total of 54 male and 51 female subjects participated in the study. It could be shown that individuals with a high expression of the personality trait greed show an increased risky decision behavior due to an increased risk sensitivity and not due to a reduced loss aversion. This is partly in contrasts with previous findings in other tasks assessing risk sensitivity and loss aversion. These differences may be due to the changes of perception during the gain only task.No significant effect was found between the personality trait anxiety or age and risky decision-making behavior. This could be since no pathologically anxious subjects were used for the sample, or respectively due to an unbalanced distribution of age.

Neural codes in early sensory areas maximize fitness

It has generally been presumed that sensory information encoded by a nervous system should be as accurate as its biological limitations allow. However, perhaps counter intuitively, accurate representations of sensory signals do not necessarily maximize the organism's chances of survival. To test this hypothesis, we developed a unified normative framework for fitness-maximizing encoding by combining theoretical insights from neuroscience, computer science, and economics. Initially, we applied predictions of this model to neural responses from large monopolar cells (LMCs) in the blowfly retina. We found that neural codes that maximize reward expectation---and not accurate sensory representations---account for retinal LMC activity. We also conducted experiments in humans and find that early sensory areas flexibly adopt neural codes that promote fitness maximization in a retinotopically-specific manner, which impacted decision behavior. Thus, our results provide evidence that fitness-maximizing rules imposed by the environment are applied at the earliest stages of sensory processing.

Sources of confidence in value-based choice

"Which meal would you like, chicken or pasta? Chicken please. ...hmmm not sure. No sorry, I prefer pasta". Confidence, the subjective estimate of decision quality, is an essential component of decision making. It is necessary for learning from mistakes in the absence of immediate feedback and guiding future actions. Despite its importance, it remains unclear where confidence judgments originate from, especially for decisions that rely on individual subjective values and preferences. Here, we devised a behavioural paradigm and a computational framework that allowed us to formally tease apart the sources of confidence in value-based decisions. In line with canonical decision theories, we found that trial-to-trial fluctuations in the precision of value encoding impact economic choice consistency. Surprisingly, however, and contrary to canonical theories of confidence, this uncertainty has no influence on confidence reports. Instead, we find that confidence reflects the degree of balance and cognitive effort with which the choice alternatives have been compared. Specifically, we show that confidence emerges from endogenous attentional effort towards choice alternatives and down-stream noise in the comparison process. These findings caution a direct translation of canonical frameworks of confidence based on perceptual decision behavior into the value-based choice domain. In addition our computational framework provides an explanation for confidence miss-attributions in economic behaviour and reveals the mechanistic interplay of endogenous attentional states and subjective value for guiding decisions and metacognitive awareness.

Differential Replication for Credit Scoring in Regulated Environments

Differential replication is a method to adapt existing machine learning solutions to the demands of highly regulated environments by reusing knowledge from one generation to the next. Copying is a technique that allows differential replication by projecting a given classifier onto a new hypothesis space, in circumstances where access to both the original solution and its training data is limited. The resulting model replicates the original decision behavior while displaying new features and characteristics. In this paper, we apply this approach to a use case in the context of credit scoring. We use a private residential mortgage default dataset. We show that differential replication through copying can be exploited to adapt a given solution to the changing demands of a constrained environment such as that of the financial market. In particular, we show how copying can be used to replicate the decision behavior not only of a model, but also of a full pipeline. As a result, we can ensure the decomposability of the attributes used to provide explanations for credit scoring models and reduce the time-to-market delivery of these solutions.

Value signals in orbitofrontal cortex predict economic decisions on a trial-to-trial basis

ABSTRACTNeuroeconomics seeks to explain how neural activity contributes to decision behavior. For value-based decisions, the primate orbitofrontal cortex (OFC) is thought to have a key role; however, the mechanism by which single OFC cells contribute to choices is still unclear. Here, we show for the first time a trial-to-trial relationship between choices and population-level value representations in OFC, defined by the weighted sum of activity from many individual value-coding neurons.