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A perspective on operational research prospects for agriculture

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Journal of the Operational Research Society

Abstract

This paper discusses the future of operational research (OR) for the agricultural industries in a broad sense, including horticulture and viticulture during a period of increased pressure on natural resources. The authors use their experience in the field along with published literature, to draw insights into new opportunities for OR, and how the OR community might adapt to realise these opportunities best. Trends in demand for food security and biofuels, the quest for sustainability, information technology (IT), and commercial power create new opportunities to support strategic investment and operations management within both primary production and the related supply chains. To realise such potential, the agricultural OR community needs to improve management of stakeholder relations, interdisciplinary synthesis, and the successful application of OR.

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References

  • Abdel-Malek L, Wolf C, Johnson F and Spencer III T (1999). OR practice: Survey results and reflections of practising INFORMS members. Journal of the Operational Research Society 50 (10): 994–1003.

    Article  Google Scholar 

  • Ahumada O and Villalobos JR (2009). Application of planning models in the agri-food supply chain: A review. European Journal of Operational Research 196 (1): 1–20.

    Article  Google Scholar 

  • Archer A, Thorburn PT, Hobson PA and Higgins AJ (2008). Evaluating alternate strategic options for agricultural value chains. Journal on Chain and Network Science 8 (2): 131–114.

    Article  Google Scholar 

  • Archer A, Higgins A and Thorburn P (2009). A method for comprehending and adapting complex supply chains in agriculture. Journal of Chain and Network Science 9 (1): 9–15.

    Article  Google Scholar 

  • Audsley E (1985). The development of operational research at the National Institute of Agricultural Engineering. Journal of the Operational Research Society 36 (2): 117–123.

    Article  Google Scholar 

  • Audsley E and Sandars D (2009). A review of the practice and achievements from 50 years of applying OR to agricultural systems in Britain. OR Insight 22 (1): 2–12.

    Article  Google Scholar 

  • Audsley E et al (2006). What can scenario modelling tell us about future European scale agricultural land use, and what not? Environmental Science & Policy 9 (2): 148–162.

    Article  Google Scholar 

  • Babcock B (2011). The impact of US biofuel policies on agricultural price levels and volatility. ICTSD Programme on Agricultural Trade and Sustainable Development; Issue Paper No. 35; ICTSD International Centre for Trade and Sustainable Development, Geneva, Switzerland, www.ictsd.org.

  • Ballarin A, Vecchiato D, Tempesta T, Marangon F and Troiano S (2011). Biomass energy production in agriculture: A weighted goal programming analysis. Energy Policy 39 (3): 1123–1131.

    Article  Google Scholar 

  • Barnard CS and Nix JS (1979). Farm Planning and Control. 2nd edn, Cambridge University Press: Cambridge, UK.

    Google Scholar 

  • Berensten PBM (2003). Effects of animal productivity on the costs of complying with environmental legislation in Dutch dairy farming. Livestock Production Science 84 (2): 183–194.

    Article  Google Scholar 

  • Beynon M, Rasmequan S and Russ S (2002). A new paradigm for computer-based decision support. Decision Support Systems 33 (2): 127–142.

    Article  Google Scholar 

  • Bloemhof-Ruwaard JM, van Beek P, Hordijk L and Van Wassenhove LN (1995). Interactions between operational research and environmental management. European Journal of Operational Research 85 (2): 229–243.

    Article  Google Scholar 

  • Borenstein D (1998). Towards a practical method to validate decision support systems. Decision Support Systems 23 (3): 227–239.

    Article  Google Scholar 

  • Carlsson D and Rönnqvist M (2005). Supply chain management in forestry—Case studies at Södra Cell AB. European Journal of Operational Research 163 (3): 589–616.

    Article  Google Scholar 

  • Carlsson D and Turban E (2002). DSS: Directions for the next decade. Decision Support Systems 33 (1): 105–110.

    Article  Google Scholar 

  • Charnes A, Cooper WW and Rhodes E (1978). Measuring the efficiency of decision making units. European Journal of Operational Research 2 (6): 429–444.

    Article  Google Scholar 

  • Darby-Dowman K, Barker S, Audlsey E and Parsons D (2000). A two-stage stochastic programming with recourse model for determining robust planting plans in horticulture. Journal of the Operational Research Society 51 (1): 83–89.

    Article  Google Scholar 

  • Den Ouden M, Nijsing JT, Dijkhuizen AA and Huirne RBM (1997). Economic optimization of pork production-marketing chains: I. Model input on animal welfare and costs. Livestock Production Science 48 (1): 23–37.

    Article  Google Scholar 

  • Dent JB (1979). Systems Simulation in Agriculture. Applied Science Publishers: London.

    Book  Google Scholar 

  • Department for Environment, Food and Rural Affairs (2007). Securing a Healthy Environment: An Action Plan for Embedding an Ecosystems Approach. PB12853 DEFRA: London, UK.

  • Department for Environment, Food and Rural Affairs (2008). Agriculture in the United Kingdom 2007. National Statistics: London.

  • EURO (2013). http://www.euro-online.org/web/pages/603/last-activities-list, accessed 28 March 2013.

  • European Community (2000). Directive 2000/60/EC of the European parliament and of the council of 23 October 2000 establishing a framework for community action in the field of water policy. Official Journal of the European Communities 43 (L 327): 1–73.

  • Feldman RM and Curry GL (1982). Operations research for agricultural pest management. Operations Research 30 (4): 601–618.

    Article  Google Scholar 

  • Fenske RW (1971). A taxonomy for operations research. Operations Research 19 (1): 224–248.

    Article  Google Scholar 

  • Flaten O and Lien G (2007). Stochastic utility-efficient programming of organic dairy farms. European Journal of Operational Research 181 (3): 1574–1583.

    Article  Google Scholar 

  • France J (2008). The agricultural research modellers group: Past, present and future. In: LA Crompton and TA Wheeler (eds) Proceedings of the 40th Meeting of the Agricultural Research Modellers’ Group, 11 April,The Journal of Agricultural Science 146 (6): 717–731.

    Article  Google Scholar 

  • Freeman RE (1984). Strategic Management: A Stakeholder Approach. Basic Books: New York.

    Google Scholar 

  • Garforth C et al (2006). Research to Understand and Model the Behaviour and Motivations of Farmers in Responding to Policy Change. EPES 0405-17. DEFRA: London.

    Google Scholar 

  • Gigler JK, Hendrix EMT, Heesen RA, Van Den Hazelkamp VGW and Meerdink G (2002). On optimisation of agri chains by dynamic programming. European Journal of Operational Research 139 (3): 613–625.

    Article  Google Scholar 

  • Glen JJ (1987). Mathematical models in farm planning: A survey. Operations Research 35 (5): 641–666.

    Article  Google Scholar 

  • Goul M and Corral K (2007). Enterprise model management and next generation decision support. Decision Support Systems 43 (3): 915–932.

    Article  Google Scholar 

  • Gunnarsson H, Rönnqvist M and Lundgren JT (2004). Supply chain modelling of forest fuel. European Journal of Operational Research 158 (1): 103–123.

    Article  Google Scholar 

  • Haight R and Weintraub A (2003). Models and systems in forestry. International Transactions in Operations Research 10 (5): 409–411.

    Article  Google Scholar 

  • Hartono E, Santhanam R and Holsapple CW (2007). Factors that contribute to management support system success: An analysis of field studies. Decision Support Systems 43 (1): 256–268.

    Article  Google Scholar 

  • Higgins A, Antony G, Sandell G, Davies I, Prestwidge D and Andrew B (2004). A framework for integrating a complex harvesting and transport system for sugar production. Agricultural Systems 82 (2): 99–115.

    Article  Google Scholar 

  • Higgins A, Thorburn P, Archer A and Jakku E (2007). Opportunities for value chain research in sugar industries. Agricultural Systems 94 (3): 611–621.

    Article  Google Scholar 

  • Higgins A, Miller C, Archer AA, Ton T, Fletcher CS and McAllister RRJ (2010). Challenges of operations research practice in agricultural value chains. Journal of the Operational Research Society 61 (6): 964–973.

    Article  Google Scholar 

  • Higgins A, Watson I and Chilcott C (2012). Optimising Capital Investment and Operations for the Livestock Industry in Northern Australia. In: Proceedings of Australian Rangeland Society 17th Biennial Conference, 23–27 September, Kununurra, Western Australia.

    Google Scholar 

  • Holman IP et al (2005a). A regional, multi-sectoral and integrated assessment of the impacts of climate and socio-economic change in the UK: Part II. Results. Climate Change 71 (1–2): 43–73.

    Article  Google Scholar 

  • Holman IP et al (2005b). A regional, multi-sectoral and integrated assessment of the impacts of climate and socio-economic change in the UK: Part I. Methodology. Climate Change 71 (1–2): 9–41.

    Article  Google Scholar 

  • Hovelaque V, Duvaleix-Tréguer S and Cordier J (2009). Effects of constrained supply and price contracts on agricultural cooperatives. European Journal of Operational Research 199 (3): 769–780.

    Article  Google Scholar 

  • INFORMS (2013). http://www.scienceofbetter.org/Edelman/winners.htm, accessed 28 March 2013.

  • Jang W and Klein CM (2011). Supply chain models for small agricultural enterprises. Annals of Operations Research 190 (1): 359–374.

    Article  Google Scholar 

  • Janssen S and van Ittersum MK (2007). Assessing farm innovations and responses to policies: A review of bio-economic farm models. Agricultural Systems 94 (3): 622–636.

    Article  Google Scholar 

  • Kaiser HK and Messer KD (2011). Mathematical Programming for Agricultural, Environmental, and Resource Economics. Wiley Interscience: New York.

    Google Scholar 

  • Kamp JALM (1999). Knowledge based systems: From research to practical application: Pitfalls and critical success factors. Computers & Electronics in Agriculture 22 (2–3): 243–250.

    Article  Google Scholar 

  • Keys P (1998). OR groups and the professionalisation of OR. Journal of the Operational Research Society 49 (4): 347–354.

    Article  Google Scholar 

  • Kingwell R (1996). Programming models of farm supply response: The impact of specification errors. Agricultural Systems 50 (3): 307–324.

    Article  Google Scholar 

  • Kirby MW (2007). Paradigm change in operations research: Thirty years of debate. Operations Research 55 (1): 1–13.

    Article  Google Scholar 

  • Kuhlmann F and Brodersen C (2001). Information technology and farm management: Developments and perspectives. Computers & Electronics in Agriculture 30 (1–3): 71–83.

    Article  Google Scholar 

  • Lawrence JD (2000). Industry Integration: Where Will It Leave Us? Staff General Research Papers, Iowa State University, Department of Economics.

    Google Scholar 

  • Linton JD, Klassen R and Jayaraman V (2007). Sustainable supply chains: An introduction. Journal of Operations Management 25 (6): 1075–1082.

    Article  Google Scholar 

  • Lowe P and Phillipson J (2006). Reflexive interdisciplinary research: The making of a research programme on the rural economy and land use. Journal of Agricultural Economics 57 (2): 165–184.

    Article  Google Scholar 

  • Maneta M et al (2009). A spatially distributed hydroeconomic model to assess the effects of drought on land use, farm profits, and agricultural employment. Water Resources Research 45, W11412, doi:10.1029/2008WR007534.

  • Marchioro GF, Cornou C, Kristensen AR and Madsen J (2011). Sows’ activity classification device using acceleration data—A resource constrained approach. Computers & Electronics in Agriculture 77 (1): 110–117.

    Article  Google Scholar 

  • Mar Molinero C and Xie A (2007). What do UK employers want from OR/MS? Journal of the Operational Research Society 58 (12): 1543–1553.

    Article  Google Scholar 

  • Marinoni O, Navarro Garcia J, Marvanek S, Prestwidge D, Clifford D and Laredo L (2012). Development of a system to produce maps of agricultural profit on a continental scale: An example for Australia. Agricultural Systems 105 (1): 33–45.

    Article  Google Scholar 

  • Marzano M, Carss DN and Bell S (2006). Working to make interdisciplinarity work: Investing in communication and interpersonal relationships. Journal of Agricultural Economics 57 (2): 185–197.

    Article  Google Scholar 

  • Matopoulos A, Vlachopoulou M and Manthou V (2007). A conceptual framework for supply chain collaboration: Empirical evidence from the agri-food industry. Supply Chain Management: an International Journal 12 (3): 177–186.

    Article  Google Scholar 

  • Matthews RB, Gilbert NG, Roach A, Polhill JG and Gotts NM (2007). Agent-based land-use models: A review of applications. Landscape Ecology 22 (10): 1447–1459.

    Article  Google Scholar 

  • McCown RL (2002). Locating agricultural decision support systems in the troubled past and socio-technical complexity of ‘models for management’. Agricultural Systems 74 (1): 11–25.

    Article  Google Scholar 

  • Mingers J and Rosenhead J (2004). Problem structuring methods in action. European Journal of Operational Research 152 (3): 530–554.

    Article  Google Scholar 

  • Ministerio de Medio Ambiente, Medio Rural y Marino (2008). Usos del territorio. http://www.alimentacion.es/ministerio/pags/hechoscifras/espanol/pdf/02.pdf, accessed 28 May 2008.

  • Mowrer HT (2000). Uncertainty in natural resource decision support systems: Sources, interpretation, and importance. Computers & Electronics in Agriculture 27 (1–3): 139–154.

    Article  Google Scholar 

  • Muller-Merbach H (2010). The OR/MS process: An orphan? The five sections analysis. Omega 38 (3–4): 115–117.

    Article  Google Scholar 

  • Murphy-Bokern D (2008). Personal communication reflections on the strengths of OR for science and policy development at the UK's department for environment, food and rural affairs. Lindenweg 12, Germany: Dr Donal Murphy-Bokern, Murphy-Bokern Konzepte, www.murphy-bokern.com.

  • Murray-Prior R (1998). Modelling farmer behaviour: A personal construct theory interpretation of hierarchical decision models. Agricultural Systems 57 (4): 541–556.

    Article  Google Scholar 

  • Office of Science and Technology (2006). Science review of the department for environment food and rural affairs. Annex 9 – peer reviews. http://www.berr.gov.uk/files/file35890.doc, accessed 30 May 2008.

  • Opara LU (2003). Traceability in agriculture and food supply chain: A review of basic concepts, technological implications, and future prospects. Journal of Food, Agriculture and Environment 1 (1): 101–106.

    Google Scholar 

  • ORAFM (2012a). http://orafm.udl.cat/?page_id=12, accessed 28 September 2012.

  • ORAFM (2012b). http://orafm.udl.cat/?page_id=129, accessed 21 December 2012.

  • Pannell DJ (1997). Introduction to Practical Linear Programming. Wiley Interscience: New York, p. 333.

    Google Scholar 

  • Pannell DJ (2006). Flat-earth economics: The far-reaching consequences of flat payoff functions in economic decision making. Review of Agricultural Economics 28 (4): 553–566.

    Article  Google Scholar 

  • Pannell DJ, Malcolm B and Kingwell RS (2000). Are we risking too much? Perspectives on risk in farm modelling. Agricultural Economics 23 (1): 69–78.

    Google Scholar 

  • Payraudeau S and Van Der Werf HMG (2005). Environmental impact assessment for a farming region: A review of methods. Agriculture, Ecosystems & Environment 107 (1): 1–19.

    Article  Google Scholar 

  • Philpott A and Everett G (2001). Supply chain optimisation in the paper industry. Annals of Operations Research 108 (1–4): 225–237.

    Article  Google Scholar 

  • Plà LM (2007). Review of mathematical models for sow herd management. Livestock Science 106 (2–3): 107–119.

    Article  Google Scholar 

  • Pollock S and Rothkopf MBA (1994). Preface. In: S.M. Pollock, M.H. Rothkopf and A.Barnett (eds) Handbooks in Operations Research and Management Science. Elsevier: Amsterdam, pp v–viii.

    Google Scholar 

  • Rae A (1994). Agricultural Management Economics. CAB International: Wallingford, UK.

    Google Scholar 

  • Recio B, Rubio F and Criado JA (2003). A decision support system for farm planning using AgriSupport II. Decision Support Systems 36 (2): 189–203.

    Article  Google Scholar 

  • Recio B, Ibáñez J, Rubio F and Criado JA (2005). A decision support system for analysing the impact of water restriction policies. Decision Support Systems 39 (3): 385–402.

    Article  Google Scholar 

  • Romero C and Rehman T (2003). Multiple Criteria Analysis for Agricultural Decisions. 2nd edn, Elsevier: Amsterdam.

    Google Scholar 

  • Rosenhead J (2006). Past, present and future of problem structuring methods. Journal of the Operational Research Society 57 (7): 759–765.

    Article  Google Scholar 

  • Rounsevell MDA, Annetts JE, Audsley E, Mayr T and Reginster I (2003). Modelling the spatial distribution of agricultural land use at the regional scale. Agriculture, Ecosystems and Environment 95 (2–3): 465–479.

    Article  Google Scholar 

  • Schutz N and Schmidt GH (2010). OCCASION: New planning tool for optimal climate change adaptation strategies in irrigation. Journal of Irrigation and Drainage Engineering 136(12): 836–846.

    Article  Google Scholar 

  • Sodhi MS and Son BG (2008). ASP, the art and science of practice: Skills employers want from operations research graduates. Interfaces 38 (2): 140–146.

    Article  Google Scholar 

  • Sodhi MS and Tang CS (2008). The OR/MS ecosystem: Strengths, weaknesses, opportunities, and threats. Operations Research 56 (2): 267–277.

    Article  Google Scholar 

  • Sorensen JT (1990). Validation of livestock herd simulation models: A review. Livestock Production Science 26 (2): 79–90.

    Article  Google Scholar 

  • Tao F, Yokozawa M and Zhang Z (2009). Modelling the impacts of weather and climate variability on crop productivity over a large area: A new process-based model development, optimization, and uncertainties analysis. Agricultural and Forest Meteorology 149 (5): 831–850.

    Article  Google Scholar 

  • Tedeschi LO (2006). Assessment of the adequacy of mathematical models. Agricultural Systems 89 (2–3): 225–247.

    Article  Google Scholar 

  • Thornley JHM and France J (2007). Mathematical Models in Agriculture: Quantitative Methods for the Plant, Animal and Ecological Sciences. 2nd edn, CABI: Wallingford, UK.

    Google Scholar 

  • Turner HS (2008). Government Operational Research Service: Civil OR in UK central government. Journal of the Operational Research Society 59 (2): 148–162.

    Article  Google Scholar 

  • Vastag B (2008). Postdocs & students: Assembly work. Nature 453 (7193): 422–423.

    Article  Google Scholar 

  • Weintraub A and Romero C (2006). Operations research models and the management of agricultural and forestry resources: A review and comparison. Interfaces 36 (5): 446–457.

    Article  Google Scholar 

  • Weintraub A, Romero C, Bjørndal T and Epstein R (eds) (2007). Handbook of Operations Research in Natural Resources. Springer Science+Business Media: New York.

    Book  Google Scholar 

  • White LA and Lee GJ (2009). Operational research and sustainable development: Tackling the social dimension. European Journal of Operational Research 193 (3): 683–692.

    Article  Google Scholar 

  • Williams AG, Audsley E and Sandars DL (2006). Final Report to Defra on Project IS0205 Determining the Environmental Burdens and Resource use in the Production of Agricultural and Horticultural Commodities. DEFRA: London.

    Google Scholar 

  • Williams T and Dickson K (2000). Teaching real-life OR to MSc students. Journal of the Operational Research Society 51 (12): 1440–1448.

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the members of Cranfield University's Natural Resources Management Centre Eric Audsley, David Parsons, Joe Morris, Matt Cook, and Kitty Stacey; and also Carlos Romero (Technical University of Madrid), Andres Weintraub (University of Chile), Tahir Rehman (University of Reading), and Javier Faulin (Public University of Navarre) for their comments improving the quality of the paper. Lluís M. Plà also wishes to acknowledge the financial support of the Spanish Research Program (MTM2005-09362-C03-02, AGL2009-12026 and MTM2009-14087-C04-01).

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  1. University of Lleida, Cataluña, Spain

    Lluís M Plà

  2. Cranfield University, Bedfordshire, UK

    Daniel L Sandars

  3. CSIRO, Brisbane, Australia

    Andrew J Higgins

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  1. Lluís M Plà
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Plà, L., Sandars, D. & Higgins, A. A perspective on operational research prospects for agriculture. J Oper Res Soc 65, 1078–1089 (2014). https://doi.org/10.1057/jors.2013.45

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