IGL database (beta)

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.

Does growth training help entrepreneurs scale-up new ventures? Our field experiment answers this question using data from 181 Singapore-based, early-growth entrepreneurs drawn from a broad range of industry sectors. Treatment content focused on three growth-catalyst tools relevant for formulating and executing innovation-led growth: business-model design, leveraging external networks, building internal teams. Treatment format comprised interactive lecture sessions and workshops on these tools supplemented by personalized coaching in applying the tools to entrepreneurs’ specific challenges.

There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-definedwriting tasks. In our field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits.

We document interest in labor reallocation among small firm owners in Ghana; 60% and 41%, respectively, self-report willingness to hire or work for the average local firm owner. Firm owners also exhibit high willingness-to-pay for information on a random subset of hiring firms and jobseeking firm owners, during a Becker-Degroot-Marschak exercise. Conditionally random variation in access to this information generates immediate labor adjustments within and between firms, though rarely of firm owners themselves, and impacts firm closure 5-months post-intervention.

As more and more activities in the economy become digitized, analytics and data-driven decision-making (DDD) are becoming increasingly important. The adoption of analytics and DDD has been slower in small-to-medium enterprises (SMEs) compared to large firms, and reliable causal estimates of the impacts of analytics tools for small businesses have been lacking. We derive experiment-based estimates of the effect of an analytics tool on SME outcomes, analyzing the randomized introduction of eBay’s Seller Hub (SH), a data-rich seller dashboard.

Although entrepreneurship training programs are designed to help necessity entrepreneurs acquire skills and capabilities to take entrepreneurial action, participants in these programs often fail to do so. In partnership with a local government agency, we conducted a randomized field experiment involving 165 entrepreneurs in rural Tanzania where in addition to providing technical-skills training, approximately half of the participants also received “growth mindset” psychological training.

Failure is widely acknowledged as a critical component of the organizational learning and innovation processs. Learning from failure, in particular, seems extremely relevant in the context of entrepreneurship, where failure often emerges as the predominant outcome. Remarkably, most entrepreneurship training programs predominantly emphasize success stories of entrepreneurs, without leveraging the learning potential that come from stories of failure.

First, we will recruit people to provide advice on whether to invest in actual start-up firms and to provide a justification for their decision. We create pairs of advisors that provide the same recommendation but differ by race and gender. Next, we recruit participants for the role of investors. Each participant is endowed with one dollar for each of the four investment rounds. The adviser provides her/his assessment and investment recommendation. The investor then decides how much to invest, and the outcome is revealed.

We study the allocation and productivity consequences of training production line supervisors in soft skills via a randomized controlled trial. Consistent with standard practice for training investments within firms, we asked middle managers – who sit above supervisors in the hierarchy – to nominate members of their supervisory team for training. Program access was randomized within these recommendation rankings. Highly recommended supervisors experienced no productivity gains; in contrast, less recommended supervisors’ productivity increased 12% relative to controls.

We evaluate the impact of a training program aimed at improving the relational atmosphere in the workplace. The program encourages prosocial behavior and the use of professional language, focusing primarily on leaders’ behavior and leader-subordinate interactions. We implement this program using a clustered randomized design involving over 3,000 headquarters employees of 20 large corporations in Turkey. We evaluate the program with respect to employee separation, pro- and antisocial behavior, the prevalence of support networks, and perceived workplace climate.

This study examines the influence of information constraints on firms’ efficiency in using digital technologies, focusing on business websites. Through two natural field experiments in the UK, we provide firms with benchmarked performance information on their websites. The experimental designs enable us to assess the salience of the information provided and heterogeneity linked to prior experience and catch-up potential.

Effective workplace management plays a crucial role in determining employee performance, retention, and subsequently, overall firm performance. While conventional management strategies often emphasize hierarchical relationships, peer-to-peer management, or "managing across," represents a promising yet largely unexplored approach. This study aims to investigate the impact of peer-to-peer management training on various employee outcomes and identify the conditions under which the intervention proves most effective.

Understanding how to design policies to effectively reduce firm-level carbon emissions while minimizing impacts on economic growth is a question of central importance in the battle to mitigate climate change. The EU is proposing a Carbon Border Adjustment Mechanism (CBAM) that will tax imports to better reflect their carbon content. This project evaluates three policies that provide firms with training and assistance obtaining loans with the goal of mitigating the impacts of CBAM on Turkish SMEs.

Climate change poses an urgent and existential threat to the wine sector. However, it is not easy for wineries and farmers to take action to reduce carbon emission comparing to adaptation. How can we encourage these actions? Farmers often seek information before take action, which influences their current risk perceptions of extreme weather condition or moral norms. Regarding the information, a positive approach focusing on empowering farmers to take action to address climate change is generally more successful at engaging people and minimizing defensive reactions.