Improving Farmers' Income on Online Agri-platforms: Theory and Field Implementation of a Two-stage Auction

26 Pages Posted: 26 Nov 2019 Last revised: 27 Jul 2020

See all articles by Retsef Levi

Retsef Levi

MIT Sloan School of Management - Operations Research Center

Manoj Rajan

Rashtriya e Market Services

Somya Singhvi

Massachusetts Institute of Technology (MIT)

Yanchong Zheng

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: July 24, 2020

Abstract

In order to improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched online agri-platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and more generally how they can be leveraged to enable more efficient agricultural supply chains and markets. This paper describes work conducted in close collaboration with the state government of Karnataka, India, to design, implement, and assess the impact of a new two-stage auction on the state's online agri-platform, the United Market Platform (UMP). The auction design aims to intensify anticipated regret of the traders to increase the farmers' revenue. To ensure implementability and protect farmers' revenue, the design process is guided by theory-informed, semi-structured interviews with a majority of the traders in the field and carefully accounts for operational constraints. The interviews suggest that both anticipated regret and anchoring would likely affect the traders' bidding strategies in a two-stage auction. A new behavioral auction model is thus developed to capture these factors and determine when the two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 4.7% price increase with an impact on farmer profitability ranging 60%--158%, affecting over 10,000 farmers who traded in the treatment market. The results from this paper offer tangible insights into how innovative price discovery mechanisms could be enabled by online agri-platforms in resource constrained environments. Importantly, the success of these designs critically depends on systemic behavioral and operational considerations that affect trades in the physical agri-markets.

Keywords: Poverty alleviation, smallholder farmers, two-stage auction, anticipated regret, anchoring, field implementation, developing countries, difference-in-differences, multi-method, behavioral economics

Suggested Citation

Levi, Retsef and Rajan, Manoj and Singhvi, Somya and Zheng, Yanchong, Improving Farmers' Income on Online Agri-platforms: Theory and Field Implementation of a Two-stage Auction (July 24, 2020). Available at SSRN: https://ssrn.com/abstract=3486623 or http://dx.doi.org/10.2139/ssrn.3486623

Retsef Levi

MIT Sloan School of Management - Operations Research Center ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

Manoj Rajan

Rashtriya e Market Services ( email )

Karnataka State Agricultural Marketing Board
2nd Raj Bhavan Road
Bengaluru, Karnataka 560001
India

Somya Singhvi

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Yanchong Zheng (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

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