Environmental Management

, Volume 59, Issue 6, pp 956–965 | Cite as

How Decision Support Systems Can Benefit from a Theory of Change Approach

  • Will Allen
  • Jennyffer Cruz
  • Bruce Warburton


Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders’ expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can “contribute” to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.


Environmental management Logic models Policy support Rabbit management Theory of change (ToC) 



The authors thank the late David Choquenot, Bob Frame, Simon Howard, NSW Local Land Services, Meat and Livestock Association, Australian Wool Innovation, Jessica Marsh, Michael Reid and wool production farmers of the Centre Tablelands region of NSW for their contributions to the production land Decision Support Systems (DSS). The authors also thank Brent Glentworth, Oliver Orgil and Alison McInnes for their contribution to the conservation land DSS. The authors thank the Invasive Animals Cooperative Research Centre for funding. The authors also thank Margaret Kilvington, Marina Apgar, Chris Jones, Phil Cowan and two anonymous reviewers for their helpful and insightful comments on earlier versions of this manuscript.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interests.


  1. Allen CR, Fontaine JJ, Pope KL, Garmestani AS (2011) Adaptive management for a turbulent future. J Environ Manage 92(5):1339–1345CrossRefGoogle Scholar
  2. Allen W et al. (2014) Bridging disciplines, knowledge systems and cultures in pest management. Environ Manage 52:429–440CrossRefGoogle Scholar
  3. Allen W, Bosch O, Kilvington M, Oliver J, Gilbert M (2001) Benefits of collaborative learning for environmental management: applying the integrated systems for knowledge management approach to support animal pest control. Environ Manage 27:215–223CrossRefGoogle Scholar
  4. Anderson AA (2005) The community builder’s approach to theory of change: a practical guide to theory development. Aspen Institute Roundtable on Community Change, New YorkGoogle Scholar
  5. Blackstock KL, Kelly GJ, Horsey BL (2007) Developing and applying a framework to evaluate participatory research for sustainability. Ecol Econ 604:726–742CrossRefGoogle Scholar
  6. Campbell LM (2005) Overcoming obstacles to interdisciplinary research. Conserv Biol 19:574–577CrossRefGoogle Scholar
  7. Carmona G, Varela-Ortega C, Bromley J (2013) Participatory modelling to support decision making in water management under uncertainty: two comparative case studies in the Guadiana river basin, Spain. J Environ Manage 128:400–412CrossRefGoogle Scholar
  8. Connell JP, Kubisch AC (1998) Applying a theory of change approach to the evaluation of comprehensive community initiatives: progress, prospects, and problems. In: Fullbright-Anderson K, Kubisch AC, Connell JP (eds) New approaches to evaluating community initiatives: theory, measurement, and analysis, vol 2. The Aspen Institute, Washington, DC, pp 15–44Google Scholar
  9. Cooke B (2002) Rabbit haemorrhagic disease: field epidemiology and the management of wild rabbit populations. Rev Sci Tech OIE 21:347–358CrossRefGoogle Scholar
  10. Cooke BD (2012) Planning landscape-scale rabbit control. Invasive Animal Cooperative Research Centre, CanberraGoogle Scholar
  11. Cox PG (1996) Some issues in the design of agricultural decision support systems. Agr Sys 52:355–381CrossRefGoogle Scholar
  12. Cruz J, Howard S, Choquenot D, Allen W, Warburton B (2016) Decision support systems for improving invasive rabbit management in Australia. In: Proceedings from the 27th Vertebrate Pest Conference (2016), University of California, Davis (In review)Google Scholar
  13. Cvitanovic C, McDonald J, Hobday AJ (2016) From science to action: principles for undertaking environmental research that enables knowledge exchange and evidence-based decision-making. J Environ Manage 183:864–874CrossRefGoogle Scholar
  14. Davies KK, Fisher KT, Dickson ME, Thrush SF, Le Heron R (2015) Improving ecosystem service frameworks to address wicked problems. Ecol Soc 20(2):37CrossRefGoogle Scholar
  15. van Delden H, Seppelt R, White R, Jakeman AJ (2011) A methodology for the design and development of integrated models for policy support. Environ Modell and Softw 26:266–279CrossRefGoogle Scholar
  16. Díez E, McIntosh BS (2009) A review of the factors which influence the use and usefulness of information systems. Environ Modell Softw 24:588–602CrossRefGoogle Scholar
  17. Haapasaari P, Kulmala S, Kuikka S (2012) Growing into interdisciplinarity: how to converge biology, economics, and social science in fisheries research? Ecol Soc 17:6Google Scholar
  18. Hayman PT, Easdown WJ (2002) An ecology of a DSS: reflections on managing wheat crops in the northeastern Australian grains region with WHEATMAN. Agr Syst 74:57–77CrossRefGoogle Scholar
  19. Hearn AB, Bange MP (2002) SIRATAC and CottonLOGIC: persevering with DSSs in the Australian cotton industry. Agr Syst 74:27–56CrossRefGoogle Scholar
  20. Hernandez M (2000) Using logic models and program theory to build outcome accountability. Educ Treat Children 23:24–40Google Scholar
  21. Jakeman AJ, Sawah S, Guillaume JHA, Pierce SA (2011) Making progress in integrated modelling and environmental decision support. In: Hřebíček J, Schimak G, Denzer R (eds) Environmental Software Systems. Frameworks of eEnvironment: 9th IFIP WG 5.11 International Symposium, ISESS 2011, Brno, Czech Republic, June 27-29, 2011. Proceedings. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 15–25Google Scholar
  22. Jakku E, Thorburn P (2010) A conceptual framework for guiding the participatory development of agricultural decision support systems. Agr Syst 103:675–682CrossRefGoogle Scholar
  23. James C (2011) Theory of change review: A report commissioned by Comic Relief. Comic Relief, LondonGoogle Scholar
  24. Jones C, Cowan P, Allen W (2012) Setting outcomes, and measuring and reporting performance of regional council pest and weed management programmes. Landcare Research, Lincoln, New ZealandGoogle Scholar
  25. Kellogg WK (2004) Logic Model Development Guide. W.K Kellogg Foundation, MichiganGoogle Scholar
  26. Kerr D (2004) Factors influencing the development and adoption of knowledge based decision support systems for small, owner-operated rural businesses. Artif Intell Rev 22:127–147CrossRefGoogle Scholar
  27. Lees AC, Bell DJ (2008) A conservation paradox for the 21st century: the European wild rabbit Oryctolagus cuniculus, an invasive alien and an endangered native species. Mammal Rev 38:304–320CrossRefGoogle Scholar
  28. Matthews KB, Rivington M, Blackstock KL, McCrum G, Miller DG (2011) Raising the bar ?: the challenges of evaluating the outcomes of environmental modelling and software. Environ Modell and Softw 26:247–257CrossRefGoogle Scholar
  29. Matthews KB, Schwarz G, Buchan K, Rivington M, Miller D (2008) Wither agricultural DSS ? Comput Electron Agr 61:149–159CrossRefGoogle Scholar
  30. McCown RL (2002a) Changing systems for supporting farmers’ decisions: problems, paradigms, and prospects. Agr Syst 74:179–220CrossRefGoogle Scholar
  31. McCown RL (2002b) Locating agricultural decision support systems in the troubled past and socio-technical complexity of ‘model for management’. Agr Syst 74:11–25CrossRefGoogle Scholar
  32. McCown RL, Carberry PS, Hochman Z, Dalgliesh NP, Foale MA (2009) Re-inventing model-based decision support with Australian dryland farmers. 1. Changing intervention concepts during 17 years of action research. Crop Pasture Sci 60:1017–1030CrossRefGoogle Scholar
  33. McGlinchy A (2011) Review of existing decision support systems for rabbit management. Landcare Research, Lincoln, New ZealandGoogle Scholar
  34. Van Meensel J, Lauwers L, Kempen I, Dessein J, Van Huylenbroeck G (2012) Effect of a participatory approach on the successful development of agricultural decision support systems: the case of Pigs2win. Decis Support Syst 54:164–172CrossRefGoogle Scholar
  35. Morra Imas LG, Rist RC (2009) The road to results: designing and conducting effective development evaluations. The World Bank, WA, DCCrossRefGoogle Scholar
  36. Murray JV, Berman DM, van Klinken RD (2014) Predictive modelling to aid the regional-scale management of a vertebrate pest. Biol Invasions 16:2403–2425CrossRefGoogle Scholar
  37. Mutze G, Cooke B, Alexander P (1998) The initial impact of rabbit haemorrhagic disease on European rabbit populations in South Australia. J Wildlife Dis 34:221–227CrossRefGoogle Scholar
  38. Norbury G, Reddiex B (2005) European rabbit. In: King CM (ed) The handbook of New Zealand mammals, 2nd edn. Oxford University Press, Melbourne, pp 131–151Google Scholar
  39. Parker C, Sinclair M (2001) User-centred design does make a difference: the case of decision support systems in crop production. Behav Inform Technol 20:449–460CrossRefGoogle Scholar
  40. Patterson JJ, Smith C, Bellamy J (2015) Enabling and enacting ‘practical action’in catchments: responding to the ‘Wicked Problem’of nonpoint source pollution in coastal subtropical Australia. Environ Manage 55(2):479–495CrossRefGoogle Scholar
  41. Ratcliffe FN, Myers K, Fennessy BV, Calaby JH (1952) Myxomatosis in Australia: a step towards the biological control of the rabbit. Nature 170:7–11CrossRefGoogle Scholar
  42. Rittel HW, Webber MM (1973) Dilemmas in a general theory of planning. Policy Sci 4(2):155–169CrossRefGoogle Scholar
  43. Rogers PJ (2008) Using programme theory to evaluate complicated and complex aspects of interventions. Evaluation 14:29–48Google Scholar
  44. Shtienberg D (2013) Will decision-support systems be widely used for the management of plant diseases? Annu Rev Phytopathol 51:1–16CrossRefGoogle Scholar
  45. Stein D, Valters C (2012) Understanding ‘Theory of Change’ in international development: a review of existing knowledge’. JSRP and The Asia Foundation, London, JSRP Paper 1Google Scholar
  46. Stem C, Margoluis R, Salafsky N, Brown M (2005) Monitoring and evaluation in conservation: a review of trends and approaches. Conserv Biol 19(2):295–309CrossRefGoogle Scholar
  47. Taplin DH, Clark H, Collins I, Colby DC (2013) Theory of change technical papers: a series of papers to support devlopment of theories of change based on practice in the field. ActKnowledge, New YorkGoogle Scholar
  48. Vere DT, Jones RE, Saunders G (2004) The economic benefits of rabbit control in Australian temperate pastures by the introduction of rabbit haemorrhagic disease. Agr Econ 30:143–155CrossRefGoogle Scholar
  49. Vogel I (2012a) ESPA guide to working with Theory of Change for research projects. ESPA Directorate, EdinburghGoogle Scholar
  50. Vogel I (2012b) Review of the Use of ‘Theory of Change’ in International Development. Review Report. DFID, LondonGoogle Scholar
  51. Voinov A, Brown Gaddis EJ (2008) Lessons for successful participatory watershed modeling: a perspective from modeling practitioners. Ecol Model 216:197–207CrossRefGoogle Scholar
  52. Volk M, Lautenbach S, van Delden H, Newham LTH, Seppelt R (2010) How can we make progress with decision support systems in landscape and river basin management ?: lessons learned from a comparative analysis of four different decision support systems. Environ Manage 46:834–849CrossRefGoogle Scholar
  53. Walker DH (2002) Decision support, learning and rural resource management. Agr Syst 73:113–127CrossRefGoogle Scholar
  54. Walters CJ, Holling CS (1990) Large-scale management experiments and learning by doing. Ecology 71(6):2060–2068CrossRefGoogle Scholar
  55. Weiss CH (1995) Applying a theory of change approach to the evaluation of comprehensive community initiatives: progress, prospects, and problems. In: Fullbright-Anderson K, Kubisch AC, Connell JP (eds) New approaches to evaluating community initiatives: concepts, methods and contexts, vol 1. The Aspen Institute, pp 65–92Google Scholar
  56. Williams K, Parer I, Coman B, Burley J, Braysher M (1995) Managing vertebrate pests: rabbits. Bureau of Resource Sciences and CSIRO Division of Wildlife and Ecology, CanberraGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Learning for SustainabilityChristchurchNew Zealand
  2. 2.Landcare ResearchLincolnNew Zealand

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