Communicating Complex Incentives
Last registered on December 06, 2019

Pre-Trial

Trial Information
General Information
Title
Communicating Complex Incentives
RCT ID
AEARCTR-0004985
Initial registration date
December 06, 2019
Last updated
December 06, 2019 10:21 AM EST
Location(s)

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Primary Investigator
Affiliation
University of Essex
Other Primary Investigator(s)
PI Affiliation
LMU Munich
PI Affiliation
LMU Munich
PI Affiliation
LMU Munich
Additional Trial Information
Status
In development
Start date
2019-12-10
End date
2021-12-31
Secondary IDs
Abstract
Incentive schemes are extensively used in firms and often contain various dimensions for a multi-tasking job. While the bonus structure might become more complex in design for an increasingly multifaceted task, recent evidence suggests that complexity leads to inefficient choices. It is important to understand how these complex bonuses can be communicated to ensure that they are effective and do not entail adverse effects. In a setting with a highly complex incentive system, we study two different ways of communicating such incentives and analyze the effects on effort choices and performance.
External Link(s)
Registration Citation
Citation
Czura, Kristina et al. 2019. "Communicating Complex Incentives." AEA RCT Registry. December 06. https://doi.org/10.1257/rct.4985-1.0.
Experimental Details
Interventions
Intervention(s)
Our interventions are implemented in the HR management app that our partner organization is using. We implement different information pages within this app to better communicate the performance of loan officers given their incentive schemes. For example, we provide information on the exact bonus attainment, how it is calculated and on which dimensions loan officers have to improve their performance to reach the next bonus level.
Intervention Start Date
2020-01-01
Intervention End Date
2020-06-30
Primary Outcomes
Primary Outcomes (end points)
We will analyze changes in performance in the incentivized dimensions: number of clients, increase in number of clients, number of loans disbursed, loan collection/ repayment performance and cross-selling products, as well as bonus attainment.
Primary Outcomes (explanation)
Primary outcomes are measures of performance on which the bonus payment is based. We will use data on these five dimensions in the following way: 1) binary variable for bonus attainment, 2) performance index based on all five dimensions, 3) each dimension as an outcome variable.
Secondary Outcomes
Secondary Outcomes (end points)
We will use the following secondary outcomes to assess the channels through which our intervention can affect performance: understanding of the incentive structure, effort, management practices, work satisfaction and work related stress.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We partner with a microfinance institution in Northern India to conduct a randomized controlled trial to examine how complex incentives can be communicated effectively in a field setting. This setting has three main advantages: first, it provides an environment with complex tasks and corresponding incentives. Second, the focus on a microfinance institution can also help understand how services can be provided more effectively, potentially increasing the overall effectiveness of microfinance. Third, we target our intervention at a rather low educated population who, in the face of automation, will also increasingly be confronted with complex tasks.
Experimental Design Details
Not available
Randomization Method
Randomization was done in office by a computer
Randomization Unit
The unit of randomization is the branch.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
188 branches
Sample size: planned number of observations
887 loan officers
Sample size (or number of clusters) by treatment arms
1) control group: 49 branches
2) breakdown: 50 branches
3) target: 49 branches
4) pure control group: 37 branches
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
see pre-analysis plan
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Ethics Commission, Department of Economics, University of Munich
IRB Approval Date
2019-06-28
IRB Approval Number
2019-06