A Conceptual Framework for Crop-Based Agri-food Supply Chain Characterization Under Uncertainty

Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty.

[1]  Steven Nahmias,et al.  Perishable Inventory Theory: A Review , 1982, Oper. Res..

[2]  S. Hoekstra,et al.  Integral Logistic Structures: Developing Customer-Oriented Goods Flow , 1992 .

[3]  Matthew B. Miles,et al.  Qualitative Data Analysis: An Expanded Sourcebook , 1994 .

[4]  A. A. Dijkhuizen,et al.  Farm decision making under risk and uncertainty. , 1997 .

[5]  A. Mowat,et al.  Consumer behaviour and fruit quality: supply chain management in an emerging industry , 2000 .

[6]  J. G. A. J. van der Vorst,et al.  Effective food supply chains; generating, modelling and evaluating supply chain scenarios , 2000 .

[7]  A. M. Blanco,et al.  Operations management of a packaging plant in the fruit industry , 2005 .

[8]  A. Fearne,et al.  Towards a framework for improvement in the management of demand in agri‐food supply chains , 2006 .

[9]  M. Vlachopoulou,et al.  A conceptual framework for supply chain collaboration: empirical evidence from the agri‐food industry , 2007 .

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

[11]  Jacques H. Trienekens,et al.  Process modelling in demand-driven supply chains: A reference model for the fruit industry , 2010 .

[12]  Wilbert E. Wilhelm,et al.  OR/MS decision support models for the specialty crops industry: a literature review , 2011, Ann. Oper. Res..

[13]  M. M. E. Alemany,et al.  An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning , 2011, Comput. Ind..

[14]  Burak Kazaz,et al.  The Impact of Yield-Dependent Trading Costs on Pricing and Production Planning Under Supply Uncertainty , 2011, Manuf. Serv. Oper. Manag..

[15]  M. Kummu,et al.  Lost food, wasted resources: global food supply chain losses and their impacts on freshwater, cropland, and fertiliser use. , 2012, The Science of the total environment.

[16]  Hans-Otto Günther,et al.  Multi-objective integrated production and distribution planning of perishable products , 2012 .

[17]  J. Bloemhof-Ruwaard,et al.  A Review on Quantitative Models for Sustainable Food Logistics Management , 2012 .

[18]  M. Sabbaghi,et al.  A multi-objective analysis for import quota policy making in a perishable fruit and vegetable supply chain: A system dynamics approach , 2013 .

[19]  Sanjay Jharkharia,et al.  Agri‐fresh produce supply chain management: a state‐of‐the‐art literature review , 2013 .

[20]  R. Manzini,et al.  The new conceptual framework for food supply chain assessment , 2013 .

[21]  Eleftherios Iakovou,et al.  Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy , 2014 .

[22]  T. Drezner,et al.  Competitive supply chain network design: An overview of classifications, models, solution techniques and applications , 2014 .

[23]  Regina Berretta,et al.  Planning Models to Optimize the Agri-Fresh Food Supply Chain for Loss Minimization: A Review , 2015 .

[24]  Togar M. Simatupang,et al.  Agri-food supply chain coordination: the state-of-the-art and recent developments , 2015, Logist. Res..

[25]  G.D.H. Claassen,et al.  Multi-criteria decision making approaches for green supply chains , 2016 .

[26]  Ángel Ortiz Bas,et al.  A review of mathematical models for supporting the order promising process under Lack of Homogeneity in Product and other sources of uncertainty , 2016, Comput. Ind. Eng..

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

[28]  Valeria Borodin,et al.  Handling uncertainty in agricultural supply chain management: A state of the art , 2016, Eur. J. Oper. Res..

[29]  Ruud H. Teunter,et al.  Crop-related harvesting and processing planning: a review , 2016 .

[30]  Ángel Ortiz Bas,et al.  Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context , 2017, PRO-VE.

[31]  M. M. E. Alemany,et al.  Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products , 2017 .

[32]  J. Bloemhof-Ruwaard,et al.  Multi-criteria decision making approaches for green supply chains: a review , 2016, Flexible Services and Manufacturing Journal.

[33]  M. M. E. Alemany,et al.  Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models , 2018, Int. J. Prod. Res..

[34]  B. De Baets,et al.  Possibilistic compositions and state functions: application to the order promising process for perishables , 2019 .

[35]  Raul Poler,et al.  Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model , 2019, Int. J. Prod. Res..