Research

During my decade working in consulting, I saw firsthand how behavioral insights could transform businesses and everyday lives.

But effects often disappointed, and practitioners struggled to choose among candidate interventions. 

The problem? It's challenging to know what generalizes, or even agree on what generalization really means.

Better cumulation requires better coordination. Let's work on more integrative methods, together!

UNDER REVIEW & WORKING PAPERS 

1. Gandhi, L., Tipton, E., & Watts, D. J. “How well does the literature on behavioral interventions generalize? An empirical test.” R&R.

2. Gandhi, L. and Kiyawat, A. “A meta-analytic database of 789 choice architecture interventions from 280 experiments coded on 298 variables.”  Under Review. 

3. Gandhi, L., Huang, Y., Krishna, M., Pimienta, A., Szaszi, B., Linos, E., Tipton, E., Camerer, C., & Watts, D. “A 380k-person integrative experiment testing whether nudges generalize across behaviors, wordings, and people.”  Video Preview.  Working Paper available upon request.

4. Gandhi, L.,  Kiyawat, A., Watts, D., & Tipton, E. “The shape of the literature limits what we learn:  Evidence from mapping behavior change studies across 57 moderators.” Working Paper.

5. Gandhi, L., Duke, A., & Schweitzer, M. “Imagining Failure, Avoiding Blame: Hidden Bias within a Popular Debiasing Tool.”  In prep.

PEER-REVIEWED PUBLICATIONS

1. Hu, X. E., Whiting, M. E., Gandhi, L., Watts, D. J., & Almaatouq, A. (2026). “The task space: An integrative framework for team research.” Management Science, 0(0).

2. Gandhi, L., Kiyawat, A., Camerer, C. & Watts, D. (2025) “Hypothetical nudges provide directional but noisy estimates of real behavior change.” Communications Psychology, 3(158).

3. Gandhi, L., Manning, B.S. and Duckworth, A.L. (2024). “Effect Size Magnification: No Variable Is as Important as the One You’re Thinking About—While You’re Thinking About It”. Current Directions in Psychological Science, 33(6), pp.347-354.

Team Science Publications

4. Patel, M.S., Milkman, K.L., Gandhi, L., Graci, H.N., Gromet, D., Ho, H., Kay, J.S., Lee, T.W., Rothschild, J., Akinola, M. & Beshears, J. (2023). “A randomized trial of behavioral nudges delivered through text messages to increase influenza vaccination among patients with an upcoming primary care visit.” American Journal of Health Promotion, 37(3), pp.324-332.

5. Milkman, K., Gandhi, L., Ellis, S., Graci, H., Gromet, D., Mobarak, R., Buttenheim, A., Duckworth, A., Pope, D., Stanford, A., Thaler, R.,  & Volpp, K. (2022). “A citywide experiment testing the impact of geographically targeted, high-pay-off vaccine lotteries”. Nature Human Behaviour, 6(11), pp.1515-1524.

6. Milkman, K. L., Gandhi, L., Patel, M. S., Graci, H., Gromet, D., Ho, H., Kay, J. S., Bogard, J., Brody, I., Chabris, C., Chang, E., Chapman, G.B., Dannals, J., Goldstein, N.J., Goren, A., Hersfield, H., Hirsch, A., Hmurovic, J., Horn, S., Karlan, D. ,Kristal, A., Lamberton, C., Meyer, M.N., Oakes, A., Schweitzer, M.E., Shermohammed, M., Talloen, J.H., Warren, C., Whillans, A., Yadav, K., Zlatev, J., Berman, R., Evans, C., Snider, C., Tsukayama, E., Van den Bulte, C., Volpp, K., & Duckworth, A. (2021). “A 680,000-person megastudy of nudges to encourage vaccination in pharmacies.”  Proceedings of the National Academy of Sciences, 119(6),, p.e2115126119.

7. Milkman, K. L., Patel, M. S., Gandhi, L., Graci, H. N., Gromet, D. M., Ho, H., Kay, J. S., Lee, T.W., Akinola, M., Beshears, J., Bogard, J.D., Buttenheim, A., Chabris, C.F., Chapman, G.B., Choi, J.J., Dai, H., Fox, C., Goren, A., Hilchey, M.D., Hmurovic, J., John, L.K., Karlan, D., Kim, M., Laibson, D., Lamberton, C., Madrian, B.C., Meyer, M.N., Modanu, M., Nam, J, Rogers, T., Rondina, R., Saccardo, S., Shermohammed, M., Soman, D., Sparks, J., Warren, C., Weber, M., Berman, R., Evans, C.N., Snider, C.K., Tsukayama, E., Can den Bulte, C., Volpp, K.G., & Duckworth, A. L. (2021). “A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor’s appointment.” Proceedings of the National Academy of Sciences, 118(20), p.e2101165118 

Do nudges really work?

During my years as a behavioral science consultant, I heard growing skepticism from my clients and colleagues. Pop science promised powerful results from small, unobtrusive changes (e.g., wording) to ad campaigns and employee policies. Yet the effects we found in industry experiments were often small and inconclusive, and the investments required to design and deploy them were considerable. Replication challenges only deepened these doubts.

I left industry for academia to tackle this skepticism head-on. I believe the insights produced by behavioral economists and psychologists contain considerable potential value for brand managers, market researchers, and consumers. My goal is to help evolve how we produce, organize, evaluate, and document those insights—in order to calibrate expectations and build a more cumulative science of behavior change.

The focus of my research is generalizability: which behavior change interventions work, for which customers, under which conditions? To answer this question, I combine theories from behavioral economics and judgment and decision-making with methods from meta-science and computational social science, across three complementary streams:

1. Designing experiments for generalization: I run large-scale experiments that randomize implementation dimensions and pre-commit held-out data for out-of-sample prediction.

2. Integrating past experiments for generalization: I label, combine, and analyze past academic and practitioner experiments, quantify their collective signal, and forecast their results with prediction surveys and machine learning (ML).

3. Interrogating the building blocks of experiments: I examine whether the stimuli, measures, and effect sizes underlying our experiments support the generalizations we draw from them.