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David P. Daniels is a Presidential Young Professor in NUS Business School's Department of Management and Organisation. He holds a Ph.D. in Business Administration and an M.A. in Economics from Stanford University, and an A.B. summa cum laude from Harvard University. During Fall 2023, he was a Visiting Research Scholar at the Wharton School of Business.

His research is published or forthcoming in top academic outlets such as Organization Science, Proceedings of the National Academy of Sciences, Organizational Behavior and Human Decision Processes, Journal of Consumer Research, and Research in Organizational Behavior. His research has been covered by media outlets such as Harvard Business Review, TIME, Forbes, PBS, NPR, and NBC.

His research focuses on influence, negotiation, and decision making; motivation (e.g., prosocial behavior); and groups and organizations (e.g., diversity). His primary approach involves developing and testing theories in natural field settings, using cutting-edge research designs (like field quasi-experiments and natural field experiments) and large-scale datasets to credibly estimate causal effects in natural real-world contexts — and thereby generate new insights which advance theory and inform policy.

He created a new conference, Diversity in Management and Organizations (DMO). Following the success of DMO 2023, DMO 2024 was held in-person and online on June 22, 2024. Check it out here! In 2024, he won a Best Paper Award from the Academy of Management (Conflict Management Division) for the second time. In 2023, he was selected as an APS Rising Star by the Association for Psychological Science. In 2022, he won the NUS Business School Early Career Research Excellence Award. In 2021, he won a Best Paper Award from the Academy of Management (Conflict Management Division). While at Stanford, he was a National Science Foundation Graduate Research Fellow.


He can be reached via email at bizdpd (at) nus (dot) edu (dot) sg.

Here are some articles that describe his research:

Selected Working Papers

Massive field quasi-experiments with continuous treatment variables reveal inverted-U causal links between mood and prosocial decisions

Daniels, D. P. and Kang, P. Revise and Resubmit at Proceedings of the National Academy of Sciences.

Selected Forthcoming and Published Papers

Do investors value workforce gender diversity?

Daniels, D. P., Dannals, J. E., Lys, T., and Neale, M.A. (Forthcoming). Organization Science. Click here to download the paper!


We examine whether investors value workforce gender diversity. Consistent with the view that investors believe that workforce gender diversity can be valuable in major firms, we use event studies to demonstrate that U.S. technology firms and U.S. financial firms experience more positive stock price reactions when it is revealed that they have relatively higher (versus lower) workforce gender diversity numbers. For instance, we find that Google’s revelation of relatively low workforce gender diversity numbers triggered a negative stock price reaction, whereas eBay’s revelation of relatively high workforce gender diversity numbers triggered a positive stock price reaction. These stock price reactions are both economically and statistically significant; e.g., we estimate that if a technology firm had revealed gender diversity numbers that were one standard deviation higher, its market valuation would have increased by $1.11 billion. Corroborating this plausibly causal field evidence, we also find positive investor reactions to workforce gender diversity in randomized experiments using Prolific participants with investing experience; these reactions seem to be underpinned by investors’ beliefs about potential upsides of diversity for the firm (e.g., reduced legal risks; increased creativity) but not by investors’ beliefs about potential downsides of diversity for the firm (e.g., increased conflict). Our findings highlight the importance of understanding investors’ intuitions or beliefs about major organizational phenomena such as workforce gender diversity. Our results also point towards a new type of business case for diversity, driven by investors: if major firms had more workforce gender diversity, investors may “reward” them with substantially higher valuations.

The streak-end rule: How past experiences shape decisions about future behaviors in a large-scale natural field experiment with volunteer crisis counselors

Kang, P., Daniels, D. P., and Schweitzer, M. E. (2022). Proceedings of the National Academy of Sciences, 119(45).

Decisions about future behaviors are clearly shaped by the content of past experiences, but whether the order of past experiences matters remains controversial. By analyzing the largest field experiment about prosocial behavior to date, a natural field experiment involving 14,383 volunteer crisis counselors over five years, we examine how the content and order of past experiences causally influence decisions about future behaviors – whether individuals continue volunteering or quit. Volunteers were repeatedly and randomly assigned to perform 1,976,649 prosocial behaviors that were either harder (suicide conversations) or easier (non-suicide conversations). We found that the content of past experiences mattered: Harder (versus easier) behaviors encouraged quitting. However, the order of past experiences mattered far beyond their content alone: Harder behaviors caused disproportionately more quitting if they came in long “streaks” or at the “end.” These “streak”/“end” effects reveal important practical insights for leaders and policymakers seeking to boost prosocial behavior. For instance, a reordering intervention – assigning behaviors so as to avoid creating hard “streaks” – would reduce volunteer quitting rates by at least 22%, boosting prosocial behavior and likely saving lives.

The magnitude heuristic: Larger differences increase perceived causality

Daniels, D. P. and Kupor, D. (2023). Journal of Consumer Research, 49(6), 1140-1159.

With the rise of machine learning and “big data,” many large yet spurious relationships between variables are discovered, leveraged by marketing communications, and publicized in the media. Thus, consumers, managers, and other people are increasingly exposed to many large-magnitude relationships between variables that do not signal causal effects. This exposure may carry a substantial cost. In seven studies, we demonstrate that the magnitudes of relationships between variables can distort people’s judgments about whether those relationships reflect causal effects. Specifically, people often use a magnitude heuristic: People infer that relationships with larger perceived magnitudes are more likely to reflect causal effects, even when this is not true (and even when relationships’ correlations are held constant). In many situations, relying on the magnitude heuristic will distort causality judgments, such as when large-magnitude relationships between variables are spurious, or when normatively extraneous factors (e.g., reference points) distort perceptions of magnitudes. Moreover, we show that magnitude-distorted (mis)perceptions of causality in turn distort people’s choices. Since people often encounter spurious relationships with large magnitudes in the health domain and in other consequential domains, the magnitude heuristic is likely to lead to biases in some of people’s most important decisions.

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