IGL Trials Database

IGL curates a database with randomised controlled trials in the field of innovation, entrepreneurship and growth. Browse our list of topics, see it as a map, or use the search function below.

2023
Bloom, N., Codreanu, M.A.

This study is focused on the relationship between borrowing constraints, access to cutting-edge technology and information about cutting-edge technology on the performance of U.S. online businesses. With the help of two large U.S. technology companies we will be able to randomize access to loans and free cloud computing credits (as well as information about the potential use of technology) to otherwise identical (generally small, but fast growing) firms, to see if they will have a causal impact on firm development.

2023
Dai, W., Kim, H., Luca, M.

Measuring the returns of advertising opportunities continues to be a challenge for many businesses. We design and run a field experiment in collaboration with Yelp across 18,294 firms in the restaurant industry to understand which types of businesses gain more from digital advertising. We randomly assign 7,209 restaurants to freely receive Yelp’s standard ads package for three months. The scale of the experiment gives us a unique opportunity to assess the heterogeneity in advertising effectiveness across a variety of business attributes.

2023
Noy, S., Zhang, W.

We examine the productivity effects of a generative artificial intelligence technology—the assistive chatbot ChatGPT—in the context of mid-level professional writing tasks. In a preregistered online experiment, we assign occupation-specific, incentivized writing tasks to 444 college-educated professionals, and randomly expose half of them to ChatGPT. Our results show that ChatGPT substantially raises average productivity: time taken decreases by 0.8 SDs and output quality rises by 0.4 SDs.

2023
Bar-Gill, S., Brynjolfsson, E., Hak, N.

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.

2023
Fang, Z., Jia, N., Liao, C., Luo, X.

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.

2023
Moody, A.

Can a set of low-cost behavioural nudges encourage more small businesses to adopt productivity-raising digital technologies? This randomised controlled trial sought to test whether businesses could be nudged into using a cloud-based system to improve the efficiency of invoice processing. All participants in the trial were offered access to the system free of charge for a 12-month period, with a treatment group receiving weekly email reminders to make use of the system.

2023
Adhvaryu, A., Dhanaraj, S., Gade, S., Nyshadham, A.

India is host to 63 million Micro, Small and Medium scale Enterprises (MSMEs), contributing to a large share of employment, industrial output as well as high volume of emissions per unit of output. Therefore, adoption of energy efficient (EE) technologies by MSMEs is crucial in improving not only their competitiveness through cost reduction but also worker wellbeing and productivity through improvements in the work environment. Enterprise owners most often do not internalize the benefits of the latter; like productivity gains due to reduction in exposure of workers to heat, pollution etc.

2023
Candelon, F., Dell'Acqua, F., Kellogg, K., Krayer, L., Lakhani, K.R., Lifshitz-Assaf, H., McFowland, E., Mollick, E.R., Rajendran, S.

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.

2022
Cusolito, A.P., Darova, O., Mckenzie, D.J.

The limited market size of many small emerging economies is a key constraint to the growth of innovative small and medium enterprises. Exporting offers a potential solution, but firms may struggle to locate and appeal to foreign buyers. A six-country randomized experiment was conducted with 225 firms in the Western Balkans to test the effectiveness of 30 hours of live group-based training and 5 hours of one-on-one remote consulting in overcoming these constraints.

2022
Gorodnichenko, Y., Kumar, S., Coibion, O.

Using a new survey of firms in New Zealand, we document how exogenous variation in the macroeconomic uncertainty perceived by firms affects their economic decisions. We use randomized information treatments that provide different types of information about the first and/or second moments of future economic growth to generate exogenous changes in the perceived macroeconomic uncertainty of some firms. The effects on their decisions relative to their initial plans as well as relative to an untreated control group are measured in a follow-up survey six months later.

2022
Jibril, H., Mensmann, M., Roper, S., Scott, D.

The ‘Evolve Digital’ trial was developed with the objective of boosting digital adoption in small family firms through identifying a cost-effective, yet productivity-enhancing programme of peer group learning for small family businesses, which can be replicated throughout the country.

2022
Catalini, C., Oettl, A., Roche, M.P.

We examine the influence of physical proximity on between-startup knowledge spillovers at one of the largest technology co-working hubs in the United States. Relying on the random assignment of office space to the hub's 251 startups, we find that proximity positively influences knowledge spillovers as proxied by the likelihood of adopting an upstream web technology already used by a peer startup.

2021
Chaurey, R., Gu, Y., Nayyar, G., Sharma, S., Verhoogen, E.

This project aims to understand the determinants of adoption of a new technology by firms in Bangladesh's leather goods and footwear industry.

2020
Coville, A., Osman, A., Piza, C.

The study is an impact evaluation of a training program that induced SMEs to adopt broadband connections, establish presence on online retail and potentially export their goods or services.

2020
Jin, Y., Sun, Z.

Expansion of e-commerce presents new opportunities for small and medium enterprises (SMEs) to enter broader market at lower costs, but the SMEs face barriers to growth after entry. To facilitate new entrants to overcome these barriers, this paper explores implementing a training program as a randomized controlled experiment with over two million new sellers on a large e-commerce platform.

2020
Agarwal, R., Choudhury, P., Starr, E.

The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic behavior by agents. We theorize that domain expertise of users can complement ML by mitigating this bias. Our observational and experimental analyses in the patent examination context support this conjecture.

2020
Bettinger, E., Chirikov, I., Kizilcec, R.F., Maloshonok, N., Semenova, T.

This trial proposes to evaluate a model for scaling up affordable access to effective STEM education through national online education platforms.

2020
Aker, J., Blumenstock, J., Dillon, B.

A randomized control trial in central Tanzania, centered on the production and distribution of a ”Yellow Pages” phone directory with contact information for local enterprises.

2019
Bouguen, A., Frölich, M., Hörner, D., Wollni, M.

In this study we assess the effects of a decentralized extension program and an additional video intervention on the adoption of integrated soil fertility management (ISFM) among 2,382 farmers in Ethiopia using a randomized controlled trial. ISFM should enhance soil fertility and productivity by combining organic and inorganic soil amendments. We find that both extension-only and extension combined with video increase ISFM adoption and knowledge.

2019
Algan, Y., Crépon, B., Glover, D.

This paper analyses the impact of a large scale randomized experiment that targets firm labor demand by supporting its recruitment practices.

2018
Dalton, P., Pamuk, H., Ramrattan, R., van Soest, D., Uras, B.

What determines the adoption of electronic-payment instruments? Do these instruments impact business outcomes, in particular access to finance? To shed light on these questions, we conducted a Randomized-Controlled-Trial with Kenyan SMEs. Our experiment released barriers to adopt a novel payment instrument. We uncover that the adoption barriers were binding for a large portion of the firms and that firms' financial transparency interacted with the decision to adopt. After sixteen months, treated businesses were more likely to feel safe and had more loans.

2018
Barham, B.L., Chavas, J.P., Fitz, D., and Schechter, L.

We construct a model of technology adoption with agents differing on two dimensions: their cognitive ability and their receptiveness to advice. While cognitive ability unambiguously speeds adoption, receptiveness to advice may speed adoption for individuals with low cognitive ability, but slow adoption for individuals with high cognitive ability. We conduct economic experiments measuring US farmers' cognitive ability and receptiveness to advice and examine how these characteristics impact their speed of adoption of genetically modified (GM) corn seeds.

2017
Catalini, C., Tucker, C.

In October 2014, all 4,494 undergraduates at the Massachusetts Institute of Technology were given access to Bitcoin, a decentralized digital currency. As a unique feature of the experiment, students who would generally adopt first were placed in a situation where many of their peers received access to the technology before them, and they then had to decide whether to continue to invest in this digital currency or exit. Our results suggest that when natural early adopters are delayed relative to their peers, they are more likely to reject the technology.

2017
Atkin, D., Chaudhry, A., Chaudry, S., Khandelwal, A.

This article studies technology adoption in a cluster of soccer-ball producers in Sialkot, Pakistan. We invented a new cutting technology that reduces waste of the primary raw material and gave the technology to a random subset of producers. Despite the clear net benefits for nearly all firms, after 15 months take-up remained puzzlingly low.

2015
Iacovone, L., Mckenzie, D.

Micro-entrepreneurs in developing countries are often constraint by inefficient supply chains, facing high travel costs and high prices in purchasing their inventory. At the same time, due to their small scale, they buy in small quantities, limiting their benefit from economies of scale, whether in bulk discounts or transport efficiencies. Small-scale food vendors in Bogotá, whose customers are residents of low-income neighborhoods, face these very issues.

2014
Dupas, P.

A randomised field experiment in Kenya uses differing levels of subsidies for an innovative bed net to suggest that temporary subsidies help short-term adoption rates of new (health) technologies and can perhaps have an effect on long-term adoption rates due to the learning experience.

2011
Engle-Warnick, J., Escobal, J., Laszlo, S.

The lack of adoption of new farming technologies despite known benefits is a well-documented phenomenon in development economics. In addition to a number of market constraints, risk aversion predominates the discussion of behavioral determinants of technology adoption. We hypothesize that ambiguity aversion may also be a determinant, since farmers may have less information about the distribution of yield outcomes from new technologies compared with traditional technologies. We test this hypothesis with a laboratory experiment in the field in which we measure risk and ambiguity preferences.

2009
Giné, X., Yang, D.

In the context of farming in Malawi, reducing risk did not induce an increase in demand for credit, contrary to theoretical predictions. These results highlight the difficulties in mitigating environmental risks to poor farmers and to increase investments in better technologies.