Building trust to increase purchase intentions: The signaling impact of low pricing policies

We examine the differential signaling impact of two low pricing policies, Price Matching Guarantees and Everyday Low Prices, on consumers' trusting beliefs and purchase intentions. We demonstrate that both PMG and EDLP pricing policies signal stores' ability to offer lower prices. However, whether these sellers were perceived as benevolent, and—consequently—consumers' purchase intentions, varied critically depending upon price uncertainty. Perceived benevolence and purchase intentions were significantly higher [lower] for sellers offering PMG than EDLP when price dispersion was high [low]. Our findings offer insights into whether and under what conditions firms should adopt these low pricing policies.     

Rethinking reinforcement: allocation, induction, and contingency

The concept of reinforcement is at least incomplete and almost certainly incorrect. An alternative way of organizing our understanding of behavior may be built around three concepts: allocation, induction, and correlation. Allocation is the measure of behavior and captures the centrality of choice: All behavior entails choice and consists of choice. Allocation changes as a result of induction and correlation. The term induction covers phenomena such as adjunctive, interim, and terminal behavior-behavior induced in a situation by occurrence of food or another Phylogenetically Important Event (PIE) in that situation. Induction resembles stimulus control in that no one-to-one relation exists between induced behavior and the inducing event. If one allowed that some stimulus control were the result of phylogeny, then induction and stimulus control would be identical, and a PIE would resemble a discriminative stimulus. Much evidence supports the idea that a PIE induces all PIE-related activities. Research also supports the idea that stimuli correlated with PIEs become PIE-related conditional inducers. Contingencies create correlations between "operant" activity (e.g., lever pressing) and PIEs (e.g., food). Once an activity has become PIE-related, the PIE induces it along with other PIE-related activities. Contingencies also constrain possible performances. These constraints specify feedback functions, which explain phenomena such as the higher response rates on ratio schedules in comparison with interval schedules. Allocations that include a lot of operant activity are "selected" only in the sense that they generate more frequent occurrence of the PIE within the constraints of the situation; contingency and induction do the "selecting."     

有时间压力下学习率对学习时间分配议程的影响:来自眼动的证据

利用眼动分析技术,通过设置不同难度和分值的计算项目,探讨了在有时间压力下学习者的学习时间分配。结果发现:(1)在首次项目选择上,学习者优先选择学习率最高的项目;(2)在学习过程中,学习者的项目选择次序也是根据学习率由高到低。总之,在学习时间分配上,如果需要权衡难度与分值,学习者会考虑单位时间的获益,也就是以学习率为议程的主要依据。研究不仅利用眼动分析技术证实了基于议程的学习时间分配模型,而且进一步揭示了学习率是设置学习时间分配议程的重要依据。     

Some effects of stimulant medication on response allocation: a double-blind analysis

Children who are diagnosed with attention deficit hyperactivity disorder (or who engage in behavior consistent with such a diagnosis) are often prescribed stimulant medications for hyperactive or inattentive behaviors. However, the mechanisms by which stimulant medications affect individuals' behavior are rarely evaluated. The purpose of the current study was to evaluate the effects of stimulant medication on response allocation when antecedents and consequences were held constant and equated. Results indicated that the presence of an amphetamine medication (Adderall) influenced response allocation across two concurrently available responses while all other stimulus conditions were held constant.     

What Counts as Behavior? The Molar Multiscale View

Because the definition of behavior changes as our understanding of behavior changes, giving a final definition is impossible. One can, however, rule out some possibilities and propose some others based on what we currently know. Behavior is not simply movement, but must be defined by its function. Also, our understanding of behavior must agree with evolutionary theory. I suggest 4 basic principles: (a) only whole organisms behave; (b) behavior is purposive; (c) behavior takes time; and (d) behavior is choice. Saying that parts of an organism behave is nonsense, and, moreover, evolutionary theory explains the existence of organisms mainly through their adaptive behavior. Behavior is purposive in that behavior is shaped by its consequences, through an organism''s lifetime or through interactions with the environment across many generations of natural selection. Behavior takes time in that behavior is interaction with the environment that cannot take place at a moment. Moreover, at a moment in time, one cannot definitely identify the function of behavior. Identification of an activity requires a span of time. Behavior is choice in the sense that a suitable span of time always includes time spent in more than 1 activity. Activities include parts that are themselves activities on a smaller time scale and compete for time. Thus, behavior constitutes time allocation. An accounting problem arises whenever any behavior is attributed to multiple consequences. In the molar multiscale view, this raises the question of whether 2 activities can occur at the same time. The question remains open.     

The role of temporal context and expectancy in resource allocation to and perception of rapid serial events

The perception of target events presented in a rapid stream of non-targets is impaired for early target positions, but then gradually improves, a phenomenon known as attentional awakening. This phenomenon has been associated with better resource allocation. It is unclear though whether improved resource allocation and attentional awakening are a consequence of the temporal context, that is, the position of the target event in the stimulus stream, or are due to a simple expectancy or foreperiod effect. Expectancy is an alternative explanation of attentional awakening because it depends on the a posteriori probabilities, which will increase with target position when all target positions are equally likely. To differentiate between the expectancy and the temporal context account the a priori (objective) probability of target position was defined such that the a posteriori probability would be high for early and late, and low for intermediate target positions. EEG was collected and the P3 ERP evoked by target events was derived as an indicator of resource allocation. A robust attentional awakening effect was observed. The relationships between measures of performance and P3 amplitude, and respectively target position, a priori, and a posteriori probability were analyzed. Results showed that in contrast to target position, a posteriori probability had little impact on performance and did not moderate the association between P3 amplitude and performance. Results also indicated that in spite of the evident role of target position on resource allocation and the perception of target events in rapid stimulus streams, target position is likely not the only variable these are affected by. Nevertheless, the findings of the present study suggest that whereas the temporal context of a rapid serial event is a key player for resource allocation to and perception of the event, expectancy seems of very little consequence.     

Prosocial behavior in families: Moderators of resource sharing

Archival studies of within-family prosocial behavior (Judge & Hrdy, 1992; Smith, Kish, & Crawford, 1987) have shown that inheritance patterns support Hamilton’s (1964) theory of inclusive fitness, such that people will more of their estates to relatives of closer genetic relatedness. In a survey-based simulation of these studies, students allocated one of three lotteries to their blood relatives. As expected, participants allocated greater proportions of their lotteries to relatives of greater genetic relatedness. This effect became stronger with decreasing lottery amounts. Relatives of certain relatedness were favored over relatives of uncertain relatedness (via paternal uncertainty), and this effect was stronger among those with less money to allocate. Male participants tended to favor their young female relatives over their young male relatives when given the smallest lottery, but this sex preference reversed when male participants were given the largest lottery. In general, scarcer resources led to more evolutionarily conservative investment strategies.     

Make‐or‐Break: Chasing Risky Goals or Settling for Safe Rewards?

Humans regularly pursue activities characterized by dramatic success or failure outcomes where, critically, the chances of success depend on the time invested working toward it. How should people allocate time between such make‐or‐break challenges and safe alternatives, where rewards are more predictable (e.g., linear) functions of performance? We present a formal framework for studying time allocation between these two types of activities, and we explore optimal behavior in both one‐shot and dynamic versions of the problem. In the one‐shot version, we illustrate striking discontinuities in the optimal time allocation policy as we gradually change the parameters of the decision‐making problem. In the dynamic version, we formulate the optimal strategy—defined by a giving‐up threshold—which adaptively dictates when people should stop pursuing the make‐or‐break goal. We then show that this strategy is computationally inaccessible for humans, and we explore boundedly rational alternatives. We compare the performance of the optimal model against (a) a myopic giving‐up threshold that is easier to compute, and even simpler heuristic strategies that either (b) only decide whether or not to start pursuing the goal and never give up or (c) consider giving up at a fixed number of control points. Comparing strategies across environments, we investigate the cost and behavioral implications of sidestepping the computational burden of full rationality.     

How to blow the Whistle and still have a career afterwards

Filing charges of scientific misconduct can be a risky and dangerous endeavor. This article presents rules of conduct to follow when considering whether to report perceived misconduct, and a set of step-by-step procedures for responsible whistleblowing that describe how to do so once the decision to report misconduct has been made. This advice is framed within the university setting, and may not apply fully in industrial settings. Ms. Gunsalus, an attorney, has been responsible for a wide range of compliance issues and academic policy matters at her university including responding to allegations of scientific misconduct. She served on the United States Commission on Research Integrity and spent six years on the AAAS Committee on Scientific Freedom and Responsibility, four of them as chair. An earlier version of this paper was presented at the symposium entitled “Damned If You Do, Damned If You Don’t: What the Scientific Community Can Do About Whistleblowing” held during the Annual Meeting of the AAAS, Seattle, Washington, 15 February, 1997.