Tied Together: Bundling, Bargaining, and Technology Adoption

Last registered on March 23, 2026
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Pre-Trial

Trial Information

General Information

Title
Tied Together: Bundling, Bargaining, and Technology Adoption
RCT ID
AEARCTR-0018061
Initial registration date
March 18, 2026

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 23, 2026, 7:43 AM EDT

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

Locations

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Primary Investigator

Name
Levenson Badio
Affiliation
Texas A&M
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Other Primary Investigator(s)

PI Name
Marco Palma
PI Affiliation
Texas A&M University
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PI Name
Rodolfo Nayga Jr
PI Affiliation
Texas A&M University
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PI Name
Samuel Zapata
PI Affiliation
Texas A&M University
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Additional Trial Information

Status
In development
Start date
2026-06-01
End date
2027-04-05
Keywords
Agriculture, Behavior, Environment & Energy, Gender
Additional Keywords
Intra-household bargaining; collective household model; technology adoption; commodity bundling; willingness to pay; improved cookstoves; gender; lab-in-the-field experiment
JEL code(s)
D13, O12, O33, J16, C93, Q55
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Division of labor within a household frequently results in divergent preferences over welfare-enhancing technologies. When the decision environment carries unequal bargaining power, investments that primarily benefit women often fail to materialize. This paper will extend the collective intra-household model to show that non-separable product bundling can realign incentives and attenuate the role of bargaining power in adoption decisions to improve the welfare of the entire household. We plan to demonstrate analytically that adding a technological feature that improves the labor efficiency and/or leisure of women to a male-valued attribute reduces the sensitivity of adoption to Pareto weights and shrinks the gap in individual--joint valuation without disrupting household dynamics. Unlike standard redistributive interventions, bundling technology interventions improve overall welfare in terms of labor efficiency and leisure enjoyment. We will test these predictions empirically in a within-household field experiment eliciting individual and joint willingness to pay for an improved cookstove, a solar phone charger, and an integrated bundled appliance.
External Link(s)

Registration Citation

Citation
Badio, Levenson et al. 2026. "Tied Together: Bundling, Bargaining, and Technology Adoption." AEA RCT Registry. March 23. https://doi.org/10.1257/rct.18061-1.0
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Experimental Details

Interventions

Intervention(s)
This study examines whether non-separable product bundling can align intra-household preferences and improve technology adoption decisions that improve the welfare of the household. Participating dual-spouse households in rural Haiti will complete incentivized willingness-to-pay (WTP) elicitation tasks using the Becker-DeGroot-Marschak (BDM) mechanism for three products: (i) an improved cookstove, (ii) a solar phone charger, and (iii) a non-separable bundle integrating both technologies into a single unit. Each participant completes individual valuation tasks separately from their spouse, and then jointly as a couple. The presentation order of the three technologies is randomized independently for each participant, and the order of individual versus joint tasks is randomized at the household level.
Intervention Start Date
2026-08-04
Intervention End Date
2026-09-01

Primary Outcomes

Primary Outcomes (end points)
Husband and Wife Individual and joint willingness to pay (WTP) for each of the three technologies (improved cookstove, solar phone charger, non-separable bundle), elicited using the BDM mechanism.
Primary Outcomes (explanation)
WTP is elicited via the BDM mechanism: each participant states a bid for each technology, a random price is drawn from a pre-specified uniform distribution, and the product is purchased at that price if the bid meets or exceeds it. This mechanism is incentive-compatible under standard expected utility theory, making stated bids a reliable measure of private valuations. The bargaining power index is constructed from items measuring women's decision-making authority over household expenditures, mobility, and major asset purchases, following the Abbreviated Women's Empowerment in Agriculture Index (A-WEAI; Malapit et al., 2017) and validated procedures from Nacka et al. (2024).

Secondary Outcomes

Secondary Outcomes (end points)
Gender gap in individual WTP between husbands and wives for the standalone cookstove versus the bundle (exploratory H3); complementarity premium defined as bundle WTP minus the sum of standalone WTP values; adoption rates for the bundle versus the cookstove alone; second-order beliefs about spousal valuations.
Secondary Outcomes (explanation)
The gender WTP gap is computed as the within-household difference between wives' and husbands' individual BDM bids for each technology. The complementarity premium is computed for each decision unit (wife, husband, household) as πi = wi(b) − [wi(c) + wi(s)]. Adoption rate is defined as the proportion of households whose bid meets or exceeds the randomly drawn price under the BDM rule. Second-order beliefs are elicited using an incentivized belief elicitation module in which each spouse predicts their partner's WTP bid.

Experimental Design

Experimental Design
This study employs a within-subject design in which every dual-spouse household serves as its own control. Each participant completes valuation tasks for all three technologies under both individual and joint decision conditions, yielding a fully crossed design. The order of technology presentation is randomized independently for each participant; the order of individual versus joint conditions is randomized at the household level. This two-dimensional randomization guards against order effects. Sessions are conducted in school venues across eight randomly selected villages in rural northern Haiti, with a target of 300 completed dual-spouse households across a minimum of 25 sessions.
Experimental Design Details
Not available
Randomization Method
The order of randomization will be done by the computer for individual, joint, and for order of technology presentation. However for the decision realization we will use urn to promote trust.
Randomization Unit
Two levels of randomization: (1) individual level — technology presentation order is randomized for each participant independently; (2) household level — the order of individual versus joint decision conditions is randomized at the household level. Village selection is randomized at the village level from the study region.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
600 individual participants (2 spouses × 300 households). Each participant completes 6 valuation tasks (3 technologies × 2 decision conditions), yielding up to 3,600 individual task-level observations.
Sample size (or number of clusters) by treatment arms
300 households.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
H1 (bargaining power as moderator): local f² = 0.05, corresponding to a partial R² of ~5% for the bargaining × technology interaction, at α* = 0.025 (Bonferroni-corrected) and 80% power, requiring Neff ≥ 190 households. H2 (individual–joint WTP divergence): minimum detectable divergence reduction δ = $0.72, assuming σD = $2.20, within-household correlation ρ = 0.40, at α* = 0.025 and 80% power, requiring Neff ≥ 134 households. H1 is the binding constraint. H3 (exploratory gender gap): Cohen's d = 0.47 at α = 0.05 and 80% power.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Universite D'Etat D'Haiti
IRB Approval Date
2026-02-18
IRB Approval Number
N/A
Analysis Plan

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