Our task is to adopt a multidisciplinary view of trust within and between firms, in an effort to synthesize and give insight into a fundamental construct of organizational science. We seek to identify the shared understandings of trust across disciplines, while recognizing that the divergent meanings scholars bring to the study of trust also can add value. Disciplinary differences characterizing traditional treatments of trust suggest that inherent conflicts and divergent assumptions are at work (Fichman, 1997). Economists tend to view trust as either calculative (Williamson, 1993) or institutional (North, 1990). Psychologists commonly frame their assessments of trust in terms of attributes of trustors and trustees and focus upon a host of internal cognitions that personal attributes yield (Rotter, 1967; Tyler, 1990; see Deutsch, 1962, for an example of more calculative framing by a psychologist). Sociologists often find trust in socially embedded properties of relationships among people (Granovetter, 1985) or institutions (Zucker, 1986). These different assumptions are manifest in our divergent use oi language. To some scholars the term "contract" refers to a legal means for avoiding risk where trust is not particularly high (Smitka, 1994; Williamson, 1975); to others the We thank Paul Goodman and Bill McEvily for their helpful comments, Carole McCoy for patient word processing, and Cathy Senderling for her wonderful editing.

We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries. T he lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on 'statistically significant' findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (for example, multiple testing, P-hacking, publication bias and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: statistical standards of evidence for claiming new discoveries in many fields of science are simply too low. Associating statistically significant findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems.For fields where the threshold for defining statistical significance for new discoveries is P < 0.05, we propose a change to P < 0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called significant but do not meet the new threshold should instead be called suggestive. While statisticians have known the relative weakness of using P ≈ 0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new 1,2 , a critical mass of researchers now endorse this change.We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (for example, genomics and high-energy physics research; see the 'Potential objections' section below).We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P values. However, changing the P value threshold is simple, aligns with the training undertaken by many researchers, and might quickly achieve broad acceptance.

Neuroeconomics is the study of the neurobiological and computational basis of value-based decision making. Its goal is to provide a biologically based account of human behaviour that can be applied in both the natural and the social sciences. This Review proposes a framework to investigate different aspects of the neurobiology of decision making. The framework allows us to bring together recent findings in the field, highlight some of the most important outstanding problems, define a common lexicon that bridges the different disciplines that inform neuroeconomics, and point the way to future applications.

Dieter's Dilemma The ability to exercise self-control is central to human success and well-being. However, little is known about the neurobiological underpinnings of self-control and how or why these neural mechanisms might differ between successful and unsuccessful decision-makers. Hare et al. (p. 646 ) used brain imaging in a dieting population undergoing real-life decisions between a healthy or a tempting, yet nutritionally inferior, choice of food. Activity in the ventromedial prefrontal cortex correlated with the value of the stimulus, termed goal value. Importantly, this activity integrated both health and taste values in individuals who were able to exert self-control in their choices, while reflecting only taste in those unable to exert self-control.