Reducing Negative Production Externalities Using Integrated Consumer Ratings

Last registered on August 25, 2022

Pre-Trial

Trial Information

General Information

Title
Reducing Negative Production Externalities Using Integrated Consumer Ratings
RCT ID
AEARCTR-0009962
Initial registration date
August 23, 2022

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
August 25, 2022, 2:57 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
University of Bergen, department of economics

Other Primary Investigator(s)

PI Affiliation
BI Oslo and Stavanger

Additional Trial Information

Status
In development
Start date
2022-08-24
End date
2022-10-31
Secondary IDs
D82
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Consumer purchase decisions for goods and services increasingly take place on a platform that features a vendor reputation indicator based on past consumer experience of the product quality. At the same time, there has been a growth of added certification indicators to signal other aspects of a product or its production methods, such as indicators of environmental friendliness (ecolabels). The idea is that information provided via these extra indicators function as ‘green nudges’ to persuade consumers to buy more responsible ‘low externality’ products, which would in turn put market pressure on firms to invest in more responsible production methods.

A question arises in what forms information regarding production externalities can be presented to increase the market pressure on firms to reduce them. Specifically, will any pressure on producers always have to come only from ‘activist’ consumers who are willing to pay for externality reduction, or are there ways in which firms could feel pressure to reduce externalities from all consumers?
In this project, we investigate how information regarding production externalities (ecolabels) can be presented to create market pressure on firms to reduce them. Specifically and novelly, we ask whether reducing the dimensionality of different certificates and consumer experience ratings into one rating, can result in firms feeling pressure to reduce externalities from all consumers, not just ‘activist’ consumers. We address this question in two ways.

First, we set up a theoretical model where firms privately choose current product quality and production externality level. Consumers learn about firms’ past behavior through a product quality rating and an ecolabel, or via a single rating which combines product quality and externality concerns. When consumers separately observe both a product quality rating and an externality, firms either ignore the externality dimension, or invest in externality reduction, but only sell to ‘activist’ consumers. In contrast, if the two concerns are combined into one indicator, there exists an equilibrium in which, regardless of there existing enough ‘activist’ consumers, a firm both invests in high product quality and low negative externality.

Second, we plan to test our hypotheses by running an incentivized economics laboratory experiment. In the experiment, we will create a small dynamic market setup similar to that in our theoretical model. We plan two treatments: One where consumers observe a firm’s reputation reflected in both a product quality and product externality rating, and one where the consumers observe only one combined rating to inform their choices.

We believe that results from this project will have important implications for how information to consumers can be presented in order to increase the market pressure on firms to reduce negative externalities.
External Link(s)

Registration Citation

Citation
de Haan, Thomas and Magnus Knutsen. 2022. "Reducing Negative Production Externalities Using Integrated Consumer Ratings." AEA RCT Registry. August 25. https://doi.org/10.1257/rct.9962-1.0
Experimental Details

Interventions

Intervention(s)
First, we set up a theoretical model of an experience good market where firms privately choose current product quality and production externality level. Consumers learn about firms’ past behavior through a product quality rating and an ecolabel, or a single rating which combines product quality and externality concerns. When consumers separately observe both a product quality rating and an externality., firms either ignore the externality dimension, or invest in externality reduction, but only to sell to the share of ‘activist’ consumers. In contrast, if the two concerns are combined into one indicator, there exists an equilibrium in which, regardless of there being enough ‘activist’ consumers, a firm both invests in high product quality and low negative externality level.
Second, we plan to test our hypotheses by running an incentivized economics laboratory experiment. In the experiment we will create a small scale dynamic market setup similar to that in our theoretical model. We plan two initial treatments: One where consumers observe a firm’s reputation reflected in both a product quality and product externality rating, and one where the consumers observe only one combined rating to inform their choices. After analyzing this setup, we hope to investigate some more dimensions by adding treatments which address the influence of for example explicit vendor competition or the ability for consumers to acquire more information so they could disentangle the summarized ratings against a cost.
Intervention Start Date
2022-08-24
Intervention End Date
2022-10-31

Primary Outcomes

Primary Outcomes (end points)
The key outcome is the degree to which producers in the experiment invest in "damage reduction" and thereby reduce negative externalities. Related to that we will also look at overall welfare (as measured by experiment participant income) generated by the markets in the different treatments.
Primary Outcomes (explanation)
The key outcome is the degree to which producers in the experiment invest in "damage reduction" and thereby reduce negative externalities. Related to that we will also look at overall welfare (as measured by experiment participant income) generated by the markets in the different treatments.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment is planned to be run at the economic experimental lab at BI Oslo and data collection is planned to start in August 2022. It will be run using zTree software (Fishbacher 2007). In the experiment participants are randomly assigned the role of producers and consumers and divided in matching groups of 6 (3 Producers, 3 Consumers). They will be randomly matched within their matching groups over approximately 48 rounds.
Each round a producer chooses whether to invest in high product quality at a cost of 15 points and whether to invest in production damage reduction at a cost of 10 points. Each round a consumer also chooses whether to buy the offered product in a round at a price of 60 points or not.
Consumers receive 100 points if they purchase a high-quality product. Furthermore, consumers (and producers) lose 0.25 points for each percent of producers that did not invest in damage-reduction. Consumers are not aware of these round decisions by the producer they are matched with. However, they will observe ratings inform them on the average of past investment decisions from the matched producer.

There will be two treatments and treatments will be randomized also within an experimental session. In one treatment the consumers will observe two separate ratings, one summarizing the past relative frequency of quality investment and the other the past relative frequency of damage reduction investments. In a second treatment the consumers only observe one rating for each matched producer which will be the weighted sum of the past relative frequency of investment for both kinds of investment. These ratings will be reset at three random times during the experiment.
The three resets mean that there will be 4 stretches of rounds when the reputations are accumulating over. These stretches are always a minimum of 5 rounds long and after round 5 have a 87.5% of continuation of another round. This leads to an expected 12 number of rounds for each stretch and a total of 48 rounds average over the experiment. The number of rounds for each reputation stretch are drawn before a session.
At the end of the experiment 1 point will be exchanged for 0.25 NOK and participants will be anonymously paid out.
Experimental Design Details
Randomization Method
Randomisation is done via both the computer (to determine the number of rounds in a session) and via a randomized entry procedure in the lab to assign people to seats.
Randomization Unit
The relevant data point will be matching groups consisting of 6 participants (3 in the role of producer, 3 in the role of consumer)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
We plan to collect between 20-25 matching group data points per treatment
Sample size: planned number of observations
We plan to collect between 20-25 matching group data points per treatment, this will likely have us recruit between 200 and 300 participants
Sample size (or number of clusters) by treatment arms
We plan to collect between 20-25 matching group data points per treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
See attached pre plan document
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials