Team Helping Behavior

In this study we implement a natural field experiment to investigate how effort varies in a team helping task. We build on research related to real effort, motivation, and incentives to better understand the underlying mechanisms of worker effort in the labor market and experimentally test previous theories.

2022-03-02

2022-03-30

Our primary outcomes are the total effort measured by the number of items completed for either RED or BLUE items (self effort and helping effort, respectively), as well as the total for all items completed (both RED and BLUE). See supporting materials for more specific information.

See supporting materials for more specific information.

Our secondary outcomes include the number of items attempted (for RED or BLUE), reaction times, and rate of completion for items attempted.

See supporting materials for more information.

In this natural field experiment, we are interested in how teams are motivated in a team helping task. We implement experimental conditions to motivate team effort in a data entry task.

Why do team members help one another? Economic theory predicts that freeriding will occur in teams (Holmstrom, 1982), yet team members are motivated to work together for many reasons, including monetary incentives and social preferences. Previous research finds also that equity-based (proportional) and equal incentives motivate worker effort (e.g., Maddix and Sutter, 2021), supporting the notion that agents are both inequity averse and inequality averse. Building on recent work in real effort team tasks, we design and implement a natural field experiment with a novel team helping task. We experimentally test theories of team motivation in the context of team helping behavior. Our novel team task and experimental design allow us to measure total effort when it benefits oneself (“self effort”) and effort that benefits one’s partner (“helping effort”) to overcome limitations in previous experimental studies. We measure the influence of both incentives and the interaction of team frame (individual vs. team) on helping behavior. We then explore the influence of individual differences on team helping behavior. These include pure altruism (in the dictator game), fairness as equality aversion (in the spectator game), inequity aversion (in a novel “me-vs-you” game), and risk preferences (via self-report and multiple price list elicitation).

Randomization is performed by a computer program (Qualtrics)

Individual workers

No

N/A

600

Each treatment arm will contain approximately 75 individual observations. We interact bonus payment frames (paid as individual vs. paid as a team) and pool these two arms for main effects, with 150 per treatment (out of 3 main treatments). See supporting document for more information.

A power calculation was conducted to estimate the minimal detectable effect size in G*Power software for a small-to-medium effect size (f = .16). For eight experimental conditions, we estimated power = .80 with a total sample size of 568 participants. With our sample of 600, we are powered to detect a moderately small effect size with power = .825.