Published

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.

In 2004 and 2005, the then Ministry of Economic Affairs issued innovation vouchers to SMEs to promote cooperation and knowledge exchange between companies and knowledge institutes in the field of innovation. The underlying idea was that more new products, services and/or processes can be developed with more knowledge exchange. This innovation can in turn lead to an increase in turnover and productivity, which ultimately leads to more prosperity.

Purpose

This article reports the results of a randomized field experiment that tested the effects of a new business intervention among managers of small- and medium-sized enterprises (SMEs) in England.

Design/methodology/approach

Individual managers (learners) were randomly assigned in clusters (companies) to either an intervention group (265 learners; 40 SMEs) receiving a novel virtual, blended training program designed to stimulate a change in management behavior or a no-intervention group (118 learners; 22 SMEs).

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.

Many have advocated for the expansion of peer review to improve scientific judgments in law and public policy. One such test case is the patent examination process, with numerous commentators arguing that scientific peer review can solve informational deficits in patent determinations. We present results from a novel randomized field experiment, carried out over the course of three years, in which 336 prominent scientific experts agreed to provide input on U.S. patent applications. Their input was edited for compliance with submission requirements and submitted to the U.S.

Interference across competing firms in RCTs can be informative about market structure. An experiment that subsidizes a random subset of traders who buy cocoa from farmers in Sierra Leone illustrates this idea. Interpreting treatment-control differences in prices and quantities purchased from farmers through a model of Cournot competition reveals differentiation between traders is low. Combining this result with quasi-experimental variation in world prices shows that the number of traders competing is 50 percent higher than the number operating in a village.

Drawing the attention of innovators to climate change is important for green innovation. We report an email field experiment with MIT using messages about the impact of climate change to invite innovators (SBIR grantees) to apply to a technology competition. We vary our messages on the time frame and scale of the human cost of climate change across scientifically valid scenarios. Innovator attention (clicks) is sensitive to climate change messaging. These changes in clicks also predict higher application rates.

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.

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.

We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a field experiment at a medical research symposium, where we exogenously varied opportunities for face-to-face encounters among 15,817 scientist-pairs. Our data include direct observations of interaction patterns collected using sociometric badges, and detailed, longitudinal data of the scientists' postsymposium publication records over 6 years.