How Do Managers’ Beliefs about New Technologies Evolve? Informational Interventions and the Adoption of Energy-Efficient Stitching Motors in Bangladesh

Last registered on May 16, 2023

Pre-Trial

Trial Information

General Information

Title
How Do Managers’ Beliefs about New Technologies Evolve? Informational Interventions and the Adoption of Energy-Efficient Stitching Motors in Bangladesh
RCT ID
AEARCTR-0007432
Initial registration date
April 19, 2021

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
April 20, 2021, 6:32 AM EDT

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

Last updated
May 16, 2023, 10:31 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Affiliation
Johns Hopkins SAIS

Other Primary Investigator(s)

PI Affiliation
Columbia University
PI Affiliation
The World Bank
PI Affiliation
The World Bank
PI Affiliation
The World Bank

Additional Trial Information

Status
In development
Start date
2021-05-20
End date
2024-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project aims to understand the determinants of adoption of a new technology by firms in Bangladesh's leather goods and footwear industry. We will conduct an randomized control trial, providing managers with information in varying intensities about a more energy-efficient "servo" motor for stitching machines. We will test the extent to which providing information about (i) the ease of installation of energy-efficient motors on existing machines, and (ii) the associated electricity cost savings leads to (a) higher take-up of servo motors, (b) changes in the willingness to pay for servo motors, and (c) changes in beliefs about associated cost savings. We will also track the evolution of managers' beliefs and willingness to pay over time to understand the dynamics of learning about the new technology. Our results will shed light on how managers learn about new energy-efficient technologies and to what extent their reluctance to adopt new technologies is due to mistakes in information-processing versus a rational process of updating, given prior beliefs and noisy signals about the value of the new technologies.
External Link(s)

Registration Citation

Citation
Chaurey, Ritam et al. 2023. "How Do Managers’ Beliefs about New Technologies Evolve? Informational Interventions and the Adoption of Energy-Efficient Stitching Motors in Bangladesh." AEA RCT Registry. May 16. https://doi.org/10.1257/rct.7432-1.2
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-07-01
Intervention End Date
2023-09-15

Primary Outcomes

Primary Outcomes (end points)
Our primary outcomes include: willingness-to-pay for energy-efficient motors, realized electricity cost savings, adoption of energy efficient motors, and firm-level performance measures (sales, employment).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our randomization sample will comprise approximately 270 SMEs in the leather goods and footwear industry using clutch motors on at least two stitching machines and no energy-efficient “servo” motors. Our design will include two treatment arms and one control arm. Treatment arm 1 (T1) will be the “information and installation” group, and treatment arm 2 (T2) will be the “information only” group. There will also be a control group (C). The intervention will have four stages. At baseline, we will conduct a survey and elicit managers’ beliefs and willingness to pay for a servo motor. To do so, we will provide minimal information about what a servo motor is to all three groups, including the control group. We will also collect information on producers' social network links.

To elicit beliefs about cost savings, we will use methods described in Delavande, Gine, McKenzie (JDE, 2011) to elicit the probability distributions that managers assign to three things: (a) how much electricity per hour of use their existing stitching machines (with clutch motors) consume, (b) how much electricity per hour of use they believe the same machines with servo motors would consume, and (c) how much the servo motors would reduce their total monthly electricity costs. In each elicitation, we will provide firm owners with a number of beans (representing quantiles of the probability distribution) which they will put in bins (representing ranges of values of electricity use or savings).

To elicit willingness-to-pay in an incentive-compatible way, we will use a Becker-DeGroot-Marschak (BDM) mechanism (Berry et al, JPE 2020). In this procedure, we will first inform a manager that we will offer a cash grant for their participation in the study. We will then ask the manager to indicate a purchase decision for a full range of prices, or equivalently we will ask them the highest price at which they will purchase the new motor (“bid price”). A random number generator will then choose a price (from different distributions for different groups, as described below). If the random price is lower than the manager’s bid price, it will be subtracted from the participation payment and the manager will receive the servo motor.

In the BDM procedure, the distribution from which prices are drawn must have full support (to ensure that individuals have an incentive to state their true valuation) but need not necessarily be the same across groups. We will use different distributions for the three groups. For firms in Treatment 1 (T1), we will draw from a distribution that has almost all weight at very low prices (e.g. very near zero). For firms in Treatment 2 (T2) and Control (C), we will draw from a distribution that has almost all weight at a very high prices, at which we expect no firms will be willing to buy the new motor. We thus expect that all (or almost all) firms in T1 and no (or almost no) firms in T2 and C will acquire the new motor at this stage.

After the BDM procedure, firms in T2 will receive intensive information about the benefits of servo motors, including expert explanations on electricity cost savings and ease of installation on existing stitching machines using videos on an iPad. Firms in T1 will receive the information received by T2 and will also receive free installation of the servo motor (assuming it is purchased in the BDM procedure, as described above) and two electricity meters, one on the machine with the servo motor and one on a machine with a clutch motor.

Following this, we will conduct the same beliefs elicitation and BDM procedure described earlier in one midline and one endline visit, but with prices drawn from the same distribution for all three groups. We will also conduct surveys during all visits to understand adoption, electricity cost savings, and overall firm performance.


References:
Berry, James, Greg Fischer, and Raymond Guiteras. "Eliciting and utilizing willingness to pay: Evidence from field trials in Northern Ghana." Journal of Political Economy 128, no. 4 (2020): 1436-1473.
Delavande, Adeline, Xavier Giné, and David McKenzie. "Measuring subjective expectations in developing countries: A critical review and new evidence." Journal of development economics 94, no. 2 (2011): 151-163.



Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
We will randomize at the firm level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
270 firms
Sample size (or number of clusters) by treatment arms
Treatment Arm 1: 90 firms
Treatment Arm 2: 90 firms
Control Arm: 90 firms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia University IRB
IRB Approval Date
2021-02-11
IRB Approval Number
AAAT1859
IRB Name
Johns Hopkins University Homewood IRB
IRB Approval Date
2021-03-26
IRB Approval Number
HIRB00012313