IGL Trials Database

We are providing a preview of a project that analyzes two field experiments with 1,974 software developers at Microsoft and Accenture to evaluate the productivity impact of Generative AI. As part of our study, a random subset of developers was given access to GitHub Copilot, an AI-based coding assistant that intelligently suggests ‘completions’ for code. Our preliminary results provide suggestive evidence that these developers became more productive, completing 12.92% to 21.83% more pull requests per week at Microsoft and 7.51% to 8.69% at Accenture (depending on specification).

Social ventures that are fundraising through crowdfunding often involve major donors to influence the contributions of smaller donors. We theorize that male and female donors will respond differently to alternative major-donor contribution schemes that are commonly used by social ventures. In a field experiment, donors were randomly assigned to receive one of three solicitation messages about a pair of projects that were seeking funds through reward-based crowdfunding.

Innovating product design is crucial for firms operating in the digital sector as it is closely linked with innovation capability and, therefore, with firm performance and productivity. In this paper, we run a randomized controlled trial to assess if participating in an open innovation initiative increases SMEs’ capability to design more competitive digital products. More specifically, the intervention aimed at increasing firms’ knowledge of the Design Sprint and their readiness to implement user-centered design techniques.

In late 2021, Phoenix Group, a FTSE 100 financial services firm and long-term partner of MoreThanNow, asked us to evaluate the impact of an Inclusive Leadership Programme. Everyone involved in the project was aware of the limited evidence for the effectiveness of online diversity training, but the team at Phoenix Group were interested in whether bespoke, best-in-class, inclusivity training for leaders would change behaviour. 

Psychological safety (PsyS) is an important driver of teams’ performance and organizations are keen to foster it. However, there is little causal evidence on what drives it and how to increase it. This paper implements a randomized control trial with over 1000 teams (over 7000 employees) in a global healthcare company to evaluate the impact of individualized attention of the manager to each team member team by encouraging managers to hold frequent 1-to-1 meetings and to focus them on mechanisms expected to increase PsyS.

Gender differences in research funding exist, but bias evidence is elusive and findings are contradictory. Bias has multiple dimensions, but in evaluation processes, bias would be the outcome of the reviewers’ assessment. Evidence in observational approaches is often based either on outcome distributions or on modeling bias as the residual. Causal claims are usually mixed with simple statistical associations.

Can artificial intelligence (AI) assist human employees in increasing employee creativity? Drawing on research on AI-human collaboration, job design, and employee creativity, we examine AI assistance in the form of a sequential division of labor within organizations: in a task, AI handles the initial portion which is well-codified and repetitive, and employees focus on the subsequent portion involving higher-level problem-solving. First, we provide causal evidence from a field experiment conducted at a telemarketing company.

Structured management practices are robustly correlated with superior performance, but while some firms change practices quickly, wide dispersion of management quality persists. Uniquely, combining evidence from two novel business surveys and a failed management mentoring field experiment, we observe firms’ intentions to improve their management practices and firms’ subjective barriers to improving their management practices. We find clear evidence of positive selection into a free management mentoring scheme: the worst managed firms were the least likely to seek help.

Agricultural extension programs often train a few farmers and count on diffusion through social networks for the innovation to spread. However, if markets are imperfectly integrated, this may also inflict negative externalities. In a two-step experiment of an agronomy training program among Rwandan coffee farmers, we first randomize the concentration of trainees at the village level and then randomly select within each village. Knowledge increased, and yields were 6.7% higher for trained farmers.

Early-stage researchers (ESRs - PhDs and Post-docs) are repeatedly touted as an untapped source of high-potential entrepreneurship. However, most entrepreneurship initiatives have either focused on undergraduate students or on consolidated scientists (PIs and professors). We argue that attempts to translate these initiatives to engage early-stage researchers (ESRs) are missing the positive impact of entrepreneurship beyond the direct commercialization of scientific outputs.

Innovation plays a pivotal role in fostering economic growth, yet there is a limited understanding of whether it can be taught. I conduct a randomized evaluation of an education program implemented by a state government and a nonprofit organization, providing an opportunity to 6,224 8th-grade students from disadvantaged backgrounds to develop frugal innovations for global and local problems. To assess students’ innovative ability, I created a novel scale with inputs from experienced inventors and used a lab-in-the-field game from experimental economics.

We conducted two randomized controlled trials (RCTs) to evaluate the impact of government-guaranteed loans offered by the Chilean and Colombian governments. The public funds of these programs greatly expanded following the start of the Covid-19 pandemic and offered loans to Micro, Small and Medium Enterprises to mitigate the negative impact of the shock. Through a collaboration with private banks, we launched two experiments which offered loans to a sub-set of the 10,072 Chilean and 3,079 Colombian small businesses that took part in our experiments.

The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine the performance implications of AI on realistic, complex, and knowledge-intensive tasks. The pre-registered experiment involved 758 consultants comprising about 7% of the individual contributor-level consultants at the company.

Female innovators raise fewer resources from investors, even when their ventures are similar to those of all-male teams. Efforts to mitigate the disparities have typically focused on changing how founders seek investment. However, the causes of gender disparities are systemic: in uncertain contexts, evaluators value women’s competence or leadership potential lower than men’s, and investors inquire more about risks when facing female founders than males.