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Field
Abstract
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Before
The evidence on whether small or large firms hold an advantage in innovation remains mixed. This paper revisits this question by combining lab experiments with theory to explain the "firm size effect" on inovation. We consider a setting where the principal chooses between a rigid, risk-free project, providing all agents with a uniform payoff, and a flexible, riskier project (with an option to revert to the risk-free project after observing outcomes), which offers potentially higher payoffs for each agent with a certain probability. Some agents (who fail the risky project or suffer a loss due to the principal) may perceive the principal as unfair, leading them to engage in costly punishment or "shading", direted at the principal and other agents. This act cannot be contractually prohibited ex-ante. We hypothesize that shading is more likely to occur in larger firms, generating more excellent resistance to innovation. To reduce the potential shading, we test whether screening out agents with strong shading motives ex ante can foster firm innovation.
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After
The evidence on whether small or large firms hold an advantage in innovation remains mixed. This paper revisits this question by combining lab experiments with theory to explain the "firm size effect" on innovation. We consider a setting where the principal chooses between a rigid, risk-free project, providing all agents with a uniform payoff, and a flexible, riskier project (with an option to revert to the risk-free project after observing outcomes), which offers potentially higher payoffs for each agent with a certain probability. Some agents (who fail the risky project or suffer a loss due to the principal) may perceive the principal as unfair, leading them to engage in costly punishment or "shading", directed at the principal and other agents. This act cannot be contractually prohibited ex-ante. We hypothesize that shading is more likely to occur in larger firms, generating more resistance to innovation. To reduce the potential shading, we test whether screening out agents with strong shading motives ex ante or team building activities can foster firm innovation.
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Trial End Date
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Before
December 31, 2024
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After
September 30, 2025
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Last Published
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Before
November 16, 2024 01:00 AM
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After
August 31, 2025 07:24 AM
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Intervention End Date
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Before
December 31, 2024
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After
September 30, 2025
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Experimental Design (Public)
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Before
Before the main experiment, subjects complete a real-effort task to earn initial endowments (200 ECUs) to ensure they have non-negative payoffs.
The main experiment includes three different treatments, each with a different group size (N=4, 6, or 8). Each group consists of one principal (P) and multiple agents (A), with roles randomly assigned at the start and maintained throughout the experiment.
The timeline is as follows: At the beginning each round, the principal must choose between a risk-free project (project 1) and a risky project (project 2). If the project 1 is chosen, both the principal and the agents can secure a payoff of 100 experiment currency units (ECUs, henceforth). If the project 2 is chosen, with two-thirds of the probability, an agent may succeed in the project and gets a payoff of 200 ECUs. With one-third of the probability, the agent may failure in the project and gets nothing. The principal’s payoff will be the average payoff of the agents. After checking the performance of each agent, the principal can decide whether to revert to the risk-free option by switching back to the project 1. Regardless of the choice of the principal (whether it is project 1/project 2/ project 2 → project 1), each agent is given the opportunity to impose costly punishment on others (“shading”). An agent can spend 5 ECUs to reduce the payoff of the principal or all other agents (with positive payoff) by 50 ECUs, or spend 10 ECUs to reduce the payoff of both the principal and all other agents (with positive payoff) by 50 ECUs. The game is repeated for 10 rounds and only one round is randomly selected to calculate the final payoff.
In addition to studying whether larger firms may face greater challenges in pursuing risky investment or innovation, we explore mechanisms to address this issue. To achieve this, we include an additional treatment (group size = 6), where a simple game is used to differentiate agents by testing whether they are willing to incur costs to reduce income inequality when treated unfairly. We then create groups by pairing a randomly selected principal with five agents of the same type. This pre-screening allows us to form groups with agents who have either weak or strong shading motives. Our aim is to test whether recruiting agents with weaker shading motives (or, conversely, screening out those with strong shading motives) is beneficial for fostering firm innovation.
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After
Before the main experiment, subjects complete a real-effort task to earn initial endowments (200 ECUs) to ensure they have non-negative payoffs.
The main experiment includes three different treatments, each with a different group size (N=4, 6, or 8). Each group consists of one principal (P) and multiple agents (A), with roles randomly assigned at the start and maintained throughout the experiment.
The timeline is as follows: At the beginning each round, the principal must choose between a risk-free project (project 1) and a risky project (project 2). If the project 1 is chosen, both the principal and the agents can secure a payoff of 100 experiment currency units (ECUs, henceforth). If the project 2 is chosen, with two-thirds of the probability, an agent may succeed in the project and gets a payoff of 200 ECUs. With one-third of the probability, the agent may failure in the project and gets nothing. The principal’s payoff will be the average payoff of the agents. After checking the performance of each agent, the principal can decide whether to revert to the risk-free option by switching back to the project 1. Regardless of the choice of the principal (whether it is project 1/project 2/ project 2 → project 1), each agent is given the opportunity to impose costly punishment on others (“shading”). An agent can spend 5 ECUs to reduce the payoff of the principal or all other agents (with positive payoff) by 50 ECUs, or spend 10 ECUs to reduce the payoff of both the principal and all other agents (with positive payoff) by 50 ECUs. The game is repeated for 10 rounds and only one round is randomly selected to calculate the final payoff.
In addition to examining whether larger firms may face greater challenges in pursuing risky investment or innovation, we also explore mechanisms to address these challenges. To achieve this, we run two additional treatments (group size = 6), each representing a different team management strategy. In the "screening" treatment, a simple game is used to differentiate agents by testing whether they are willing to bear costs to reduce income inequality when treated unfairly. Based on this game, groups are formed by pairing a randomly selected principal with five agents with weak shading motives. This allows us to test whether recruiting agents with weaker shading motives enhances firm innovation. In the "team building" treatment, we adapt a team building task from Jiang and Li (2019). In the randomly formed group with N=6, the principal and the five agents need to exchange their private information via group chat to solve a puzzle together, with the principal taking on the main responsibility in the solving the puzzle. Each group member receives a small reward if the puzzle is solved within the given time. We are interested in whether strengthened closeness between the principal and the agents promotes firm innovation.
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Planned Number of Clusters
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Around 180 groups in total
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Around 220 groups in total
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Planned Number of Observations
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around 980 subjects (university students)
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After
around 1320 subjects (university students)
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Sample size (or number of clusters) by treatment arms
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Before
Around 40 groups for treatment with group size = 4, 6, 8
Around 60 groups for treatment with group size = 6 (with type classification)
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After
Around 40 groups for treatment with group size = 4, 6, 8
Around 60 groups for treatment with group size = 6 (with type classification)
Around 40 groups for treatment with group size = 6 (with team building)
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Additional Keyword(s)
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Before
Firm Innovation Path Selection
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After
Firm Innovation;
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