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Field
Abstract
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Before
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.
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After
How to motivate the implementation of better management practices? Benchmarking -- comparing relative performance and practices -- is a widely advocated but under-studied strategy. Theoretically, managers fail to leverage existing information and do not implement better management practices, mainly due to two reasons. For one, managers might suffer from information frictions and do not know the existence of better management practices. For the other, managers might pay limited attention to some practices and hold false beliefs over how those practices contribute to performance. Benchmarking works under both scenarios and motivates managers to implement better management practice by directly providing information as well as demonstrating the relationship between practices and performance. Following this line of reasoning, benchmarking is more likely to facilitate practice implementation for businesses with lower performance. Also, benchmarking has a stronger effect on practices to which business owners are more inattentive. To investigate the causal impact of benchmarking, we carried out a randomized controlled experiment among small business owners operating cooked food stalls in Singapore. Every owner was informed of their own performance. Additionally, treatment owners were offered with their relative performance and practices of top performers. The experiment will conclude in 2021 with visits to observe the treatment effect on practices and performance.
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Trial End Date
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Before
January 31, 2021
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After
September 30, 2021
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Last Published
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Before
November 22, 2019 07:37 PM
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After
September 18, 2020 10:29 PM
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Field
Primary Outcomes (End Points)
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Before
Sales revenue; cost; owner productivity; management practice implementations
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After
Sales revenue; cost; owner productivity; management practice implementations; exit
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Field
Primary Outcomes (Explanation)
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Before
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
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After
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
5. The decisions to exit from the market
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Field
Experimental Design (Public)
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Before
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.
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After
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).
8 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.
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Field
Pi as first author
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Before
No
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After
Yes
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