Autonomy and Performance Pay - A Field Experiment with a Large Retail Chain

Last registered on March 24, 2017

View Trial History

Pre-Trial

Trial Information

General Information

Title

Autonomy and Performance Pay - A Field Experiment with a Large Retail Chain

RCT ID

AEARCTR-0002126

Initial registration date

March 24, 2017

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

March 24, 2017, 4:18 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Germany

Region

Primary Investigator

Name

Timo Vogelsang

Affiliation

Frankfurt School of Finance and Management

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Kathrin Manthei

PI Affiliation

University of Applied Science Neuss

Contact Investigator

PI Name

Dirk Sliwka

PI Affiliation

University of Cologne

Contact Investigator

Additional Trial Information

Status

In development

Start date

2017-03-24

End date

2017-12-31

Keywords

Labor

Additional Keywords

Incentives, Autonomy, Performance Pay

JEL code(s)

Secondary IDs

Abstract

Within a large retail chain we introduce a bonus payment and provide more autonomy in decision making for store managers, implementing a 2x2 experimental design. The bonus is based on the store’s profit contribution margin (= sales - costs of goods sold - inventory shrinkage - personnel costs).
Store managers in one region in South-East Germany are randomly assigned to one of four treatments. 25% of store managers receive a bonus based on the contribution margin. Another 25% of store managers receive more autonomy in their work by allowing them to decide on the items placed in front of the cash desk. 25% of store managers receive both, the bonus and the additional autonomy. The remaining 25% serve as control group.
Based on a theoretical model we study the following hypotheses: The bonus payment will increase the contribution margin and will do so to a stronger extent when it is accompanied by an increase in decision autonomy. We also hypothesize that the granting of autonomy alone (without the bonus) can have countervailing effects. On the one hand, store managers can make better use of local knowledge in decision-making and may be motivated by the increase in autonomy. On the other hand, decentral autonomy can have a cost if less able store managers cannot make effective use of their local knowledge.

External Link(s)

Registration Citation

Citation

Manthei, Kathrin, Dirk Sliwka and Timo Vogelsang. 2017. "Autonomy and Performance Pay - A Field Experiment with a Large Retail Chain." AEA RCT Registry. March 24. https://doi.org/10.1257/rct.2126-1.0

Former Citation

Manthei, Kathrin, Dirk Sliwka and Timo Vogelsang. 2017. "Autonomy and Performance Pay - A Field Experiment with a Large Retail Chain." AEA RCT Registry. March 24. https://www.socialscienceregistry.org/trials/2126/history/15407

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2017-03-24

Intervention End Date

2017-06-30

Primary Outcomes

Primary Outcomes (end points)

The contribution margin on the store level (as well as all its components), further retail key figures, questionnaire data (pre and post)

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

The intervention takes place in one region (south-east) of Germany. We randomly assign districts within each region to either TreatAUT (1), TreatBON (2), TreatAUTBON (3), or the Control group (4) using stratifications depending on the predicted contribution margin in the first treatment month. Randomization at the district level, although the unit of observation is the store level, gives us the possibility to separate treatment and control groups and only inform them concerning their specific treatment interventions.

Importantly, all store managers (including the control group) get access to an online training on the contribution margin prior to the intervention. Additionally, they receive information about the relative profit margin of each product (this is novel information to them).
All store managers further receive a monthly overview about the development of the contribution margin (and the components) apart from the possible monthly bonus notifications.

TreatBON: Store managers receive a three-month bonus for an increase of their contribution margin above 80% of its planned value (following from the accounting plan for each store). In each month, store managers receive a bonus value of 0.05 * (contribution margin in € - 80% of the plan value). Cumulative bonus values are paid out after three month (capped at zero). Store managers receive monthly feedback on the respective bonus values.

TreatAUT: Store managers receive more autonomy for the experiment’s duration of three month. More precisely, they are now allowed to place items in front of the checkstand according to what they consider best.

TreatAUTBON: Is the combination of TreatBON and TreatAUT.
Control: The control group only receives the online training and the access to information about relative profit margins. They are not made aware of the other treatment groups..
We briefed the district managers how to react to different sorts of questions concerning the experimental design.

Control: The control group only receives the online training and the access to information about relative profit margins. They are not made aware of the other treatment groups.

We briefed the district managers how to react to different sorts of questions concerning the experimental design.

The company’s worker council agreed to this intervention. This serves as an IRB substitute.

Experimental Design Details

Randomization Method

Stratification method

Randomization Unit

District

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

32 districts

Sample size: planned number of observations

228 stores

Sample size (or number of clusters) by treatment arms

Control: 58 stores
TreatBON: 59 stores
TreatAUT: 56 stores
TreatAUTBON; 55 stores

Note: There can be slight changes in the number of treated stores as pay experience has shown that the firm may reconfigure district compositions for administrative reasons at short notice. However, this should concern only very few stores and we document reasons and procedures.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB