What are the optimal hybrid work-from-home days and how do we coordinate it

Last registered on October 19, 2024

View Trial History

Pre-Trial

Trial Information

General Information

Title

What are the optimal hybrid work-from-home days and how do we coordinate it

RCT ID

AEARCTR-0012173

Initial registration date

October 18, 2024

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

October 19, 2024, 9:47 PM EDT

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

Locations

Country

China

Region

East Asia

Primary Investigator

Name

ruobing han

Affiliation

Stanford Economics

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Nicholas Bloom

PI Affiliation

Stanford

Contact Investigator

PI Name

James (Jianzhang) Liang

PI Affiliation

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2023-10-23

End date

2024-06-30

Keywords

Firms & Productivity, Labor, Welfare

Additional Keywords

working from home, organization, telework

JEL code(s)

D24, L23, L84, M11, M54, O31

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

As businesses and everyday life slowly return to pre-pandemic activity, one point is becoming clear: The home office isn’t about to shut down. In his research and discussions with hundreds of managers across different industries, Prof.Nicholas Bloom finds that about 70 percent of firms — from tiny companies to massive multinationals like Apple, Google, Citi, and HSBC — plan to implement some form of hybrid working arrangements so their employees can divide their time between collaborating with colleagues on-site and working from home.

Hybrid arrangements balance the benefits of being in the office in person — greater ability to collaborate, innovate, and build a culture — with the benefits of quiet and the lack of commuting that comes from working from home. There is a big question of how many days and also what happens if you have MF together.

We are conducting a hybrid WFH experiment at Qunar, a 1000+ employee, public-listed Chinese travel agency. 800 qualified managerial and IT-professional employees form more than 50 project teams, and the teams were randomly assigned into four groups (0 days WFH – control; 1 day WFH – Friday; 2 days WFH – Wednesday and Friday; 3 days WFH – Monday Wednesday and Friday), either to exercise this hybrid working option or in the office for 9 months.

External Link(s)

Registration Citation

Citation

Bloom, Nicholas, ruobing han and James (Jianzhang) Liang. 2024. "What are the optimal hybrid work-from-home days and how do we coordinate it." AEA RCT Registry. October 19. https://doi.org/10.1257/rct.12173-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We are going to collect information on participants' creativity, efficiency, productivity, and happiness. We will also track participants' performance, attrition, promotion, and switches of WFH status in the longer term. With this information collected, we will check the longer-term equilibrium effect of this hybrid option, the heterogeneous effect across different subgroups, and indirect effects.

Intervention (Hidden)

Intervention Start Date

2023-10-23

Intervention End Date

2024-06-30

Primary Outcomes

Primary Outcomes (end points)

Impact on employee performance, productivity and promotion, Impact on employee satisfaction, Employee and company learning. Variations by employee type (e.g. gender, age, education, location, role, manager etc).

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

The experiment took place in Qunar in Beijing, China. The experiment lasted roughly nine months, and mandatory mid-term and post-experiment surveys were conducted.

Experimental Design Details

Randomization Method

This selection of even birthdates into the treatment group was randomly determined by a lottery draw.

Randomization Unit

Team level

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

1192 employees

Sample size: planned number of observations

1192 employees

Sample size (or number of clusters) by treatment arms

319 Control group employees have no WFH rights, 271 WFH on Tuesday, Wednesday, and Friday per week per week, 287 WFH on Wednesday and Friday per week, and 315 WFH on Friday per week.

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

In the 2015 study, we had 125 in treatment and control and picked up significant effects. Each of the four groups should have around 200 employees. So since this is the largest possible sample and about tripple the prior sample we have not run any formal power calcuations.

Supporting Documents and Materials

IRB