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Why do some entrepreneurs thrive while others fail? We explore whether the advice entrepreneurs receive about managing their employees influences their startup's performance. We conducted a randomized field experiment in India with 100 high‐growth technology firms whose founders received in‐person advice from other entrepreneurs who varied in their managerial style. We find that entrepreneurs who received advice from peers with a formal approach to managing people—instituting regular meetings, setting goals consistently, and providing frequent feedback to employees—grew 28% larger and were 10 percentage points less likely to fail than those who got advice from peers with an informal approach to managing people, 2 years after our intervention. Entrepreneurs with MBAs or accelerator experience did not respond to this intervention, suggesting that formal training can limit the spread of peer advice.

In this article, we attempt to resolve the tension between two sets ofconflicting hypothesizes about the role of specialization in workers’careers. Some scholars argue that specialization is a net benefit thatallows workers to get ahead, while others argue that broad experienceacross several domains is the only way to be truly exceptional. We useremarkably rich longitudinal data on the careers of Indian AdministrativeService officers, members of the Republic of India’s elite bureaucraticservice, to test both these hypotheses. We find that specializationbenefits officers throughout their career. However, multiple theoreticalaccounts are consistent with this effect. One account suggests thatspecialization benefits workers because it gives them skills that make themmore productive, while another suggests that specialization is a signal ofability and promise. Our analysis indicates that both accounts are valid,but apply at different stages of officers’ careers. The skills acquiredthrough specialization matter more in the later career; in the earlycareer, specialization is mainly a signal.

In this article we examine how social capital affects the creation of human capital. Specifically, we study how college students’ peers affect academic performance. Building on existing research, we consider the different types of peers in the academic context and the various mechanisms through which peers affect performance. We test our model using data from an engineering college in India. Our data include information about the performance of individual students as well as their randomly assigned roommates, chosen friends, and chosen study-partners. We find that students with able roommates perform better, and the magnitude of this roommate effect increases when the roommate’s skills match the student’s academic goals. We also find that students benefit equally from same- and different-caste roommates, suggesting that social similarity does not strengthen peer effects. Finally, although we do not find strong evidence for independent friendship or study-partner effects, our results suggest that roommates become study-partners, and in so doing, affect performance. Taken together, our findings demonstrate that peer effects are a consequential determinant of academic achievement.

Recent scholarship argues that experimentation should be the organizing principle for entrepreneurial strategy. Experimentation leads to organizational learning, which drives improvements in firm performance. We investigate this proposition by exploiting the time-varying adoption of A/B testing technology, which has drastically reduced the cost of testing business ideas. Our results provide the first evidence on how digital experimentation affects a large sample of high-technology start-ups using data that tracks their growth, technology use, and products. We find that, although relatively few firms adopt A/B testing, among those that do, performance improves by 30%–100% after a year of use. We then argue that this substantial effect and relatively low adoption rate arises because start-ups do not only test one-off incremental changes, but also use A/B testing as part of a broader strategy of experimentation. Qualitative insights and additional quantitative analyses show that experimentation improves organizational learning, which helps start-ups develop more new products, identify and scale promising ideas, and fail faster when they receive negative signals. These findings inform the literatures on entrepreneurial strategy, organizational learning, and data-driven decision making. This paper was accepted by Toby Stuart, entrepreneurship and innovation.