The impact of peers’ behaviour on firms’ training decisions

Last registered on November 04, 2025
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Pre-Trial

Trial Information

General Information

Title
The impact of peers’ behaviour on firms’ training decisions
RCT ID
AEARCTR-0016766
Initial registration date
September 12, 2025

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
September 12, 2025, 10:49 AM EDT

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

Last updated
November 04, 2025, 3:16 AM EST

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

Locations

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Primary Investigator

Name
Alessio Tomelleri
Affiliation
FBK-IRVAPP
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Other Primary Investigator(s)

PI Name
Alessandro Tondini
PI Affiliation
FBK-IRVAPP
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PI Name
Iunio Quarto Russo
PI Affiliation
FBK-IRVAPP
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PI Name
Elisa Martini
PI Affiliation
Trento Employment Agency
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PI Name
Daniela Zampogna
PI Affiliation
Trento Employment Agency
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Additional Trial Information

Status
In development
Start date
2025-09-15
End date
2026-06-30
Keywords
Firms & Productivity
Additional Keywords
training, behavioural nudges, peer effects, craft firms
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Continuous training for workers plays a fundamental role in enabling firms to keep up with technological advancements and the resulting changes in production and organisational processes. This is particularly relevant for craft firms, where training supports adaptation to shifts in the demand for products and services while preserving the quality of products and services. Yet, compared to larger firms, craft firms tend to invest less in training (Kotey & Folker, 2007; Storey, 2004), often underestimating its benefits and overestimating its cost (Barrett & Mayson, 2007; Storey, 2004; Storey & Westhead, 1997). A key policy question is which levers are most effective in encouraging these firms to engage in training activities.
Since micro-enterprises and craft businesses typically operate in narrow and competitive local markets, where the innovation capacity is generally limited, the literature shows how they heavily rely on their peers when making important business decisions (McPherson, 1996; Nichter & Goldmark, 2009; Maté-Sánchez Val et al., 2018; Tomelleri & Billé, 2025), and this may also apply to investments in training.
In this vein, to test the extent to which craft firms' decisions to participate in training depend on the training activities undertaken by their peers, we run an information treatment experiment. In collaboration with the local Employment Agency (EA) of Trento, located in a highly productive province in Northern Italy, we randomly provide craft firms with accurate information about the training activities undertaken by their peers to evaluate the effect on training decisions. The study contributes to the literature on training behavioural nudges by examining low-cost interventions in the training markets.
External Link(s)

Registration Citation

Citation
Tomelleri, Alessio et al. 2025. "The impact of peers’ behaviour on firms’ training decisions." AEA RCT Registry. November 04. https://doi.org/10.1257/rct.16766-2.0
Sponsors & Partners

Partner

Name
Agenzia del Lavoro di Trento (Trento Employment Agency).
Type
government
URL
https://www.agenzialavoro.tn.it/

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-09-15
Intervention End Date
2026-06-30

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes are:
1. Request for additional information via email (binary, 0/1 – intermediate outcome ).
2. a. Extensive margin: Firm participation in training funded by the local employment agency (binary, 0/1) in the 2025-26 cycle (and potentially onwards); 2b) Intensive margin: number of hours of training funded by the local employment agency (continuous)
3. Qualitative margin: The type of training the firm participates in (technical vs. Soft skills, as well as other potential categorisations to be decided afterwards); whether a firm is more likely to participate in a course that falls within the category of the top 5 courses other firms have benefited from, indicated in the dashboard; 0 otherwise.

Primary Outcomes (explanation)
All primary outcomes are obtained through administrative data: the intermediate outcome (contact via e-mail to the employment agency to obtain information about the financing channel) will be provided by the local employment agency; similarly, information about firm extensive and intensive participation in the training financed by local employment agency, as well as the type of training, will be obtained from administrative datasets operated by the local employment agency.

Secondary Outcomes

Secondary Outcomes (end points)
The secondary outcomes are:
1. General attitudes toward training: This outcome is captured through a composite index based on seven survey items measuring firms’ perceptions and attitudes toward training. The items cover perceived benefits, costs, and barriers to training (continuous).
2. Total hours of training conducted in the year 2025-2026, besides the one financed through the local employment agency (continuous).
3. Percentage of firms that are aware of at least one incentive and/or subsidy provided by the Employment Agency or directly by the province. In the baseline survey, more than 50% of responding firms reported not being aware of the existence of such funding opportunities.
4. Average training expenditure within the firm, excluding contributions received from the Province or the Employment Agency.
5. Planned increase in training effort (hours and budget): Plans to increase training hours over the next 12–24 months (binary 1/0).
Secondary Outcomes (explanation)
All secondary outcomes are collected by the baseline and follow-up survey, which include measures of general attitudes toward training, perceived benefits from training in terms of productivity and experience with training in general. On top of the main analysis of administrative data for the universe of craft firms in the province, we will conduct a separate analysis on the sample of firms that respond to both the baseline (21%) and follow-up survey:

Experimental Design

Experimental Design
Our experimental design follows a stratified four-arm randomised controlled trial (three treatment groups + one control).
Experimental details will be available as soon as the trial is over.
Experimental Design Details
Not available
Randomization Method
Computer random number generator.
Randomization Unit
The randomisation unit is the individual craft firm operating in the province of Trento.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clustering.
Sample size: planned number of observations
Indicatively 12,000 craft firms (the full universe of craft firms in the province of Trento) obtained from administrative data.
Sample size (or number of clusters) by treatment arms
3 treatment groups (20% of firms each) and 1 control group (40% of firms).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Primary analysis on Administrative Data From the administrative data, we know that the baseline participation rate in financed training is equal to 5 % and the average number of hours is equal to 78.8. Considering an alpha level of 0.05 (two-sided), 80% power, allocation 60/40 (T/C), full compliance, full response rate (N = 12,000), the ITT minimum detectable effects (MDEs) would be: • Participation (binary): 1.21 pp • Hours of training (continuous, SD = 26.78 h): 1.40 h If analyses are restricted to 20% responders (20% response rate, N ≈ 2,400), the ITT MDEs worsen: 2.89 pp (participation) and 3.13 h (hours). But because only a fraction of treated firms may comply with the intervention (e.g. clicking the dashboard, engaging with the information), the ITT effect is further diluted according to the compliance rate. Below, we report the implied LATE MDEs under alternative compliance rates: Compliance rate Outcome N=12,000 (MDE) N≈2,400 (MDE) 10% Participation (pp) 12.1 28.9 10% Hours (h) 14 31.3 20% Participation (pp) 6.05 14.45 20% Hours (h) 7 7.1 15.65 30% Participation (pp) 4.03 9.63 30% Hours (h) 4.67 10.43 50% Participation (pp) 2.42 5.78 50% Hours (h) 2.8 6.26
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan