Supporting Brazilian smallholder farmers decision making in supplying institutional markets

Abstract Smallholder farmers are among the most vulnerable communities in developing countries, lacking a stable income due to inconsistent access to markets. Aiming to tackle rural poverty, the Brazilian government established institutional markets for smallholder farmers to supply their produce to schools through a non-competitive bidding mechanism. However, participation of farmers is still limited due to the challenging decision-making process. Aspiring to contribute towards increasing their participation, this study aims to support farmers into two key decisions they face during sequential stages of the bidding process, namely whether to bid for each available school and product combination and whether subsequently to accept the awarded bids once the bids’ outcome is known. A decision support system, based on two sequential MILP optimisation models, was developed and applied to the case study of Canudos settlement, guiding farmers on the optimal bidding and contract acceptance strategy. This study contributes to the decision support systems field by applying OR methods to a real-life problem within a new context. It is the first application of an OR-based decision support system in the non-competitive bid/no-bid literature, defining an optimal bidding strategy through the application of optimisation methods to maximise profitability while removing subjectivity from the decision-making process. Moreover, it is the first decision support system within the bid/no-bid decision-making field being applied to the agricultural and institutional market context. The proposed approach could have a significant social impact for smallholder farmers in Brazil, improving their living conditions by providing security of income and strengthening inclusive agricultural growth.

[1]  M. Gates Bidding Strategies and Probabilities , 1967 .

[2]  Mohammad S. El-Mashaleh,et al.  Empirical Framework for Making the Bid/No-Bid Decision , 2013 .

[3]  Kiyotada Hayashi,et al.  Multicriteria analysis for agricultural resource management: A critical survey and future perspectives , 2000, Eur. J. Oper. Res..

[4]  Andrew J. Higgins,et al.  A perspective on operational research prospects for agriculture , 2014, J. Oper. Res. Soc..

[5]  Steve Wiggins,et al.  The Future of Small Farms , 2010 .

[6]  S. Ogutu,et al.  Commercialization of the small farm sector and multidimensional poverty , 2019, World Development.

[7]  M. Cheng,et al.  Bidding Decision Making for Construction Company using a Multi-criteria Prospect Model , 2011 .

[8]  Animesh Biswas,et al.  Application of fuzzy goal programming technique to land use planning in agricultural system , 2005 .

[9]  Hiroshi Honda,et al.  Hemodynamic changes under balloon occlusion of hepatic artery: predictor of the short-term therapeutic effect of balloon-occluded transcatheter arterial chemolipiodolization using miriplatin for hepatocellular carcinoma , 2016, SpringerPlus.

[10]  Agnieszka Leśniak,et al.  Modeling the Decision-Making Process Concerning Participation in Construction Bidding , 2015 .

[11]  Shabbir Ahmed,et al.  Robust strategic bidding in auction-based markets , 2019, Eur. J. Oper. Res..

[12]  Rifat Sonmez,et al.  A support vector machine method for bid/no bid decision making , 2017 .

[13]  R. Yin Case Study Research: Design and Methods , 1984 .

[14]  J. Godar,et al.  Development Conditions for Family Farming: Lessons From Brazil , 2015 .

[15]  Amr A.G. Hassanein,et al.  A bidding decision index for construction contractors , 1996 .

[16]  Marcela Cecilia González-Araya,et al.  Operational research models applied to the fresh fruit supply chain , 2016, Eur. J. Oper. Res..

[17]  Maxwell L. Chisala,et al.  Quantitative Bid or No-Bid Decision-Support Model for Contractors , 2017 .

[18]  Peter E.D. Love,et al.  Re-Examining the Association between Quality and Safety Performance in Construction: From Heterogeneous to Homogeneous Datasets , 2017 .

[19]  Mohammad S. El-Mashaleh,et al.  Decision to bid or not to bid: a data envelopment analysis approach , 2010 .

[20]  P. Hazell,et al.  The Future of Small Farms: Trajectories and Policy Priorities , 2010 .

[21]  To Bid or Not to Bid , 1975 .

[22]  Brînduşa Bîrhală,et al.  Community Supported Agriculture: A promising pathway for small family farms in Eastern Europe? A case study from Romania , 2014 .

[23]  Irtishad Ahmad Decision‐Support System for Modeling Bid/No‐Bid Decision Problem , 1990 .

[24]  Catia Grisa,et al.  Revisitando o Pronaf: velhos questionamentos, novas interpretações , 2014 .

[25]  M. Cismaru,et al.  Social marketing campaigns aimed at preventing drunk driving , 2009 .

[26]  L. Stringer,et al.  Learning from the South: common challenges and solutions for small‐scale farming , 2008 .

[27]  D. A. González-Chica,et al.  Compra de alimentos da agricultura familiar pelo Programa Nacional de Alimentação Escolar (PNAE): estudo transversal com o universo de municípios brasileiros , 2018, Ciência & Saúde Coletiva.

[28]  Mohammed Wanous,et al.  A neural network bid/no bid model: the case for contractors in Syria , 2003 .

[29]  C. Grasseni Family farmers between re-localisation and co-production , 2014 .

[30]  Gul Polat,et al.  Data Envelopment Analysis (DEA) Approach for Making the Bid/No Bid Decision: A Case Study in a Turkish Construction Contracting Company , 2017 .

[31]  Jacqueline M. Bloemhof,et al.  Integrating harvesting decisions in the design of agro-food supply chains , 2019, Eur. J. Oper. Res..

[32]  Jesus René Villalobos,et al.  Application of planning models in the agri-food supply chain: A review , 2009, Eur. J. Oper. Res..

[33]  Mohammed Wanous,et al.  To bid or not to bid: a parametric solution , 2000 .

[34]  L. Andersson,et al.  Adaptation to climate change and other stressors among commercial and small-scale South African farmers , 2013, Regional Environmental Change.

[35]  R. Triches,et al.  Interface Between Family Farming and School Feeding: barriers and coping mechanisms from the perspective of different social actors in Southern Brazil , 2017 .

[36]  Yea-Sang Kim,et al.  A bid decision-making model in the initial bidding phase for overseas construction projects , 2016 .

[37]  Marta Monjardino,et al.  Contract design in agriculture supply chains with random yield , 2019, Eur. J. Oper. Res..

[38]  Fj Curtis,et al.  Closed competitive bidding , 1973 .

[39]  Wassie Berhanu,et al.  On the power and influence of the cooperative institution: Does it secure competitive producer prices? , 2018 .

[40]  Geraldo Regis Mauri,et al.  Improved mathematical model and bounds for the crop rotation scheduling problem with adjacency constraints , 2019, Eur. J. Oper. Res..

[41]  Ching-Torng Lin,et al.  Bid/no-bid decision-making – a fuzzy linguistic approach , 2004 .

[42]  A. J. Higgins,et al.  Challenges of operations research practice in agricultural value chains , 2010, J. Oper. Res. Soc..

[43]  Liyin Shen,et al.  A fuzzy competence requirement (FCR) model for competitive bidding strategy , 2010 .

[44]  Hannah Wittman,et al.  The State of Family Farms in the World , 2016 .

[45]  Christopher S. Tang,et al.  An analysis of partially-guaranteed-price contracts between farmers and agri-food companies , 2016, Eur. J. Oper. Res..

[46]  Huawang Shi,et al.  A dynamic novel approach for bid/no-bid decision-making , 2016, SpringerPlus.

[47]  Abdulrezak N. Mohamed,et al.  SCBMD: A knowledge-based system software for strategically correct bid/no bid and mark-up size decisions , 2008 .