Benchmarking: Field Evidence from Singapore
Last registered on November 22, 2019

Pre-Trial

Trial Information
General Information
Title
Benchmarking: Field Evidence from Singapore
RCT ID
AEARCTR-0003216
Initial registration date
October 08, 2018
Last updated
November 22, 2019 7:37 PM EST
Location(s)

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Primary Investigator
Affiliation
NUS Business School
Other Primary Investigator(s)
PI Affiliation
NUS Business School
PI Affiliation
NUS Business School
Additional Trial Information
Status
On going
Start date
2019-06-01
End date
2021-01-31
Secondary IDs
Abstract
Benchmarking -- the provision of information on relative performance and best practices -- has been widely advocated as a tool to help businesses improve performance. To investigate the causal impact of benchmarking on business performance, we plan a randomized controlled trial among owners of cooked food stalls in Singapore food courts. Food courts, which are owned by the government or commercial businesses, lease stalls to individual food and beverage vendors. This context is ideal for our research as those stalls compete in well-defined niches, use similar technologies, and do not suffer from any internal principal-agent problem. Our experiment will subject stall owners to three benchmarking treatments: performance, practices, and both performance and practices. We will also investigate the channel(s) by which benchmarking motivates businesses to change management practices and adopt new technologies.
External Link(s)
Registration Citation
Citation
Hou, Yun, Ivan Png and Charmaine Tan. 2019. "Benchmarking: Field Evidence from Singapore." AEA RCT Registry. November 22. https://doi.org/10.1257/rct.3216-4.0.
Former Citation
Hou, Yun et al. 2019. "Benchmarking: Field Evidence from Singapore." AEA RCT Registry. November 22. http://www.socialscienceregistry.org/trials/3216/history/57626.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We will randomly assign the food courts to two groups, and only enroll individually-owned vendors into the experiment. All the enrolled vendors within each food centre would be assigned to the same manipulation condition.

A. Control group;
B. Benchmarking group

Stall owners in all groups will be given a report on four measures of performance -- sales volume (number of plates sold per week), average cost per plate, profit per plate, and profit per owner working hour (the latter calculated as sales revenue minus total cost divided by total hours worked by the stall owner). We would also offer all subjects with the same set of general business operation suggestions.

Apart from performance indicators, the report to stall owners in the benchmarking group will also include their performance relative to the first, second, and third quartiles of all stalls selling cooked food. Meanwhile, the benchmarking group will receive four practice suggestions: two front-of-house practices and two back-of-house practices, that are randomly selected from five front-of-house practices and back-of-house practices.
Intervention Start Date
2019-08-01
Intervention End Date
2019-08-15
Primary Outcomes
Primary Outcomes (end points)
Sales revenue; cost; owner productivity; management practice implementations
Primary Outcomes (explanation)
1. Owner productivity: We measure food stall productivity by owner productivity, calculated as the sales revenue minus total cost divided by the number of owner-hours worked.
2. Management practice implementation
3. Change intiatives
4. Social aspirations
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Our experiment will enroll individual vendors in each food court to participate in our study. We would approach about 20 hawker centres across Singapore and ideally we can recruit 10-20 subjects at each hawker centre.

At Time 0, we will conduct a pre-intervention survey to collect baseline information: sales revenue, cost, working procedures, management practices, adoption of technology, personal background, and psychological profiles.

We will compile the information from the pre-intervention survey and then calculate performance indicators as well as benchmarking information for all vendors. We will then randomly assign the food courts into control and benchmarking group.

At Time 1, upon completing data collection and analysis, we will contact the four groups and provide the corresponding information (control or treatment respectively).

3 month (Time 2), 12 months (Time 3) and 18 months (Time 4) respectively after the control/intervention visit, we will return to interview all participating vendors to collect information about changes in productivity and management and technology practices.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Randomization by each section of stalls within one food centre.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
20 food centres, 69 different sections, 200 vendors
Sample size: planned number of observations
vendors.
Sample size (or number of clusters) by treatment arms
35% vendors control and 65% vendors treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
NUS Institutional Review Board
IRB Approval Date
2018-10-03
IRB Approval Number
S-18-281E