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Decision conferencing for science prioritisation in the UK public sector: a dual case study

  • Case-Oriented Paper
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Journal of the Operational Research Society

Abstract

Decision Conferencing, a decision analytic approach, was introduced for science project prioritisation in two organisations of the UK public sector: the National Measurement System Programmes, Unit of the Department of Trade and Industry (now part of the National Measurement Office, an Executive Agency of the Department for Business, Innovation and Skills) and the Science Department of the Environment Agency of England and Wales. Despite some similarities between the organisations, they responded in quite different ways. We describe the organisational contexts in the two organisations, the process by which Decision Conferencing was introduced, and explore possible reasons for the differing experiences.

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References

  • Ackoff RL (1979). The future of operational research is past. J Opl Res Soc 30: 93–104.

    Article  Google Scholar 

  • Austin J and Mitchell IM (2008). Bringing value focused thinking to bear on equipment procurement. Mil Opns Res 13: 33–46.

    Article  Google Scholar 

  • Bana e Costa C, Fernandes FGF and Correia PVD (2005). Prioritisation of public investments in social infrastructures using multicriteria value and analysis and decision conferencing: A case study. Int T Opns Res 13: 279–297.

    Article  Google Scholar 

  • Beaujon GJ, Marin SP and McDonald CC (2001). Balancing and optimizing a portfolio of R&D projects. Nav Res Log 48: 18–40.

    Article  Google Scholar 

  • Belton V and Stewart TJ (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Kluwer: Boston.

    Book  Google Scholar 

  • Blau GE, Pekny JF, Varma VA and Bunch PR (2004). Managing a portfolio of interdependent new product candidates in the pharmaceutical industry. J Prod Innovat Mngt 21: 227–245.

    Article  Google Scholar 

  • Bodily SE and Allen MS (1999). A dialogue process for choosing value-creating strategies. Interfaces 29: 16–28.

    Article  Google Scholar 

  • Bordley RF (1998). R&D project selection versus R&D project generation. IEEE T Eng Mngt 45: 407–413.

    Article  Google Scholar 

  • Bowns S, Bradley I, Knee P, Williams F and Williams G (2003). Measuring the economic benefits from R&D: Improvements in the MMI model of the United Kingdom National Measurement System. Res Policy 32: 991–1002.

    Article  Google Scholar 

  • Brealey RA and Myers S (2004). Principles of Corporate Finance. McGraw-Hill: New York.

    Google Scholar 

  • Catalyze Ltd (2007). Equity Product Tour. http://www.catalyze.co.uk/products/equity/tour, accessed 20 February 2007.

  • Chien C-F (2002). A portfolio-evaluation framework for selecting R&D projects. R&D Mngt 32: 359–368.

    Google Scholar 

  • Cook WD and Seiford LM (1982). R&D project selection in a multidimensional environment—A practical approach. J Opl Res Soc 33: 397–405.

    Article  Google Scholar 

  • Cooper RG, Edgett S and Kleinschmidt EJ (2001). Portfolio Management for New Products. Perseus: New York.

    Google Scholar 

  • Danila N (1989). Strategic evaluation and selection of R&D projects. R&D Mngt 19: 47–62.

    Google Scholar 

  • Dyer JS and Sarin RK (1979). Measurable multiattribute value functions. Opns Res 27: 810–822.

    Article  Google Scholar 

  • Environment Agency (2006). Environment Agency Corporate Plan 2006–09. Environment Agency: London and Bristol.

  • Henriksen AD and Traynor AJ (1999). A practical R&D project-selection scoring. IEEE T Eng Mngt 46: 158–170.

    Article  Google Scholar 

  • Hess SW (1993). Swinging on the branch of a tree: Project selection applications. Interfaces 23: 5–12.

    Article  Google Scholar 

  • HM Treasury (2003). The Green Book: Appraisal and Evaluation in Central Government. TSO: London.

  • Keeney RL and Raiffa H (1976). Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Wiley: Chichester.

    Google Scholar 

  • Kleinmuntz DN (2007). Resource allocation decisions. In: Edwards W, Miles RF and von Winterfeldt D (eds). Advances in Decision Analysis. CUP: Cambridge, pp. 400–418.

    Chapter  Google Scholar 

  • Kusnic MW and Owen D (1992). The unifying vision process—Value beyond traditional decision-analysis in multiple-decision-maker environments. Interfaces 22: 150–166.

    Article  Google Scholar 

  • Layard R and Glaister S (1994). Cost Benefit Analysis. CUP: Cambridge.

    Book  Google Scholar 

  • Leitch S, Kuskey K, Buede D and Bresnick T (1999). Of Princes, Frogs, and Marine Corps' Budgets: Institutionalizing decision analysis over 23 Years. In: Decision Analysis Practice Award Presentation. INFORMS: Philadelphia.

    Google Scholar 

  • Liberatore MJ and Titus GJ (1983). The practice of management science in R&D project management. Mngt Sci 29: 962–974.

    Article  Google Scholar 

  • Linton JD (2002). Implementation research: State of the art and future directions. Technovation 22: 65–79.

    Article  Google Scholar 

  • Loch CH, Pich MT, Terwiesch C and Urbschat M (2001). Selecting R&D projects at BMW: A case study of adopting mathematical programming models. IEEE T Eng Mngt 48: 70–80.

    Article  Google Scholar 

  • Lorenco J, Bana e Costa C and Morton A (2008). Software packages for multi-criteria resource allocation. International Engineering Management Conference—Europe, Estoril, Portugal.

  • Mandakovic T and Souder WE (1985). An interactive decomposable heuristic for project selection. Mngt Sci 31: 1257–1271.

    Article  Google Scholar 

  • Martello S and Toth P (1990). Knapsack Problems: Algorithms and Computer Implementations. Wiley: Chichester.

    Google Scholar 

  • Martino JP (1995). R&D Project Selection. Wiley: Chichester.

    Google Scholar 

  • Matheson D and Matheson J (1998). The Smart Organisation: Creating Value Through Strategic R&D. Harvard Business School Press: Boston.

    Google Scholar 

  • McCartt A and Rohrbaugh J (1995). Managerial openness to change and the introduction of GDSS: Explaining initial success and failure in decision conferencing. Org Sci 6: 569–584.

    Article  Google Scholar 

  • McCartt AT and Rohrbaugh J (1989). Evaluating group decision support system effectiveness: A performance study of decision conferencing. Decis Support Syst 5: 243–253.

    Article  Google Scholar 

  • Morgan M (2006). Testing scope invariance in MCDA resource allocation. Unpublished MSc thesis, Department of Operational Research, London School of Economics and Political Science.

  • Morton A and Fasolo B (2009). Behavioural decision theory for multi-criteria decision analysis: A guided tour. J Opl Res Soc 60: 268–275.

    Article  Google Scholar 

  • Morton A and Phillips LD (2006). Constructing organisational preferences: A study of within-criterion weighting. Working paper. Operational Research Group, London School of Economics, London. Under review at Group Decision and Negotiation.

  • Murov L (2004). Evaluation of an Initial Use of Decision Conferencing & Resource Allocation: Tailor-fitting a Process to an Existing Organisational Culture. Department of Operational Research, London School of Economics: London.

    Google Scholar 

  • Mustajoki J, Hamalainen RP and Sinkko K (2007). Interactive computer support in decision conferencing: Two cases on off-site nuclear emergency management. Decis Support Syst 42: 2247–2260.

    Article  Google Scholar 

  • Perdue RK, McAllister WJ, King PV and Berkey BG (1999). Valuation of R&D projects using options pricing and decision analysis models. Interfaces 29: 57–74.

    Article  Google Scholar 

  • Phaal R, Farrukh CJP and Probert DR (2004). Technology roadmapping—A planning framework for evolution and revolution. Technol Forecast Soc 71: 5–26.

    Article  Google Scholar 

  • Phillips LD (2007). Decision conferencing. In: Edwards W, Miles RF and Von Winterfeldt D (eds). Advances in Decision Analysis: From Foundations to Applications. CUP: Cambridge, pp. 375–399.

    Chapter  Google Scholar 

  • Phillips LD and Bana e Costa C (2007). Transparent prioritisation budgeting and resource allocation with multi-criteria decision analysis and decision conferencing. Ann Opns Res 154: 51–68.

    Article  Google Scholar 

  • Quaddus MA and Tung LL (2002). Explaining cultural differences in decision conferencing. Commun Acm 45(8): 93–98.

    Article  Google Scholar 

  • Quaddus MA, Atkinson DJ and Levy M (1992). An application of decision conferencing to strategic-planning for a voluntary organization. Interfaces 22: 61–71.

    Article  Google Scholar 

  • Ringuest JL, Graves SB and Case RH (2004). Mean-Gini analysis in R&D portfolio selection. Eur J Opl Res 154: 157–169.

    Article  Google Scholar 

  • Schmidt RL (1993). A model for R&D project selection with combined benefit, outcome and resource interactions. IEEE T Eng Mngt 40: 403–410.

    Article  Google Scholar 

  • Schmidt RL and Freeland JR (1992). Recent progress in modeling R&D project-selection processes. IEEE T Eng Mngt 39: 189–201.

    Article  Google Scholar 

  • Sharpe P and Keelin T (1998). How SmithKline Beecham makes better resource-allocation decisions. Harvard Bus Rev 76: 45–57.

    Google Scholar 

  • Sinuany-Stern Z and Mehrez A (1987). Discrete multiattribute utility approach to project selection. J Opl Res Soc 38: 1133–1139.

    Article  Google Scholar 

  • Souder WE and Mandakovic T (1986). R&D project selection models. Res Mngt 29: 36–42.

    Google Scholar 

  • Stewart TJ (1991). A multi-criteria decision support system for R&D project selection. J Opl Res Soc 41: 17–26.

    Article  Google Scholar 

  • Sugden R and Williams A (1978). Principles of Practical Cost-benefit Analysis. OUP: Oxford.

    Google Scholar 

  • Taylor BW, Moore LJ and Clayton ER (1982). R&D project selection and manpower allocation with integer nonlinear goal programming. Mngt Sci 28: 1149–1158.

    Article  Google Scholar 

  • Thorp J and Fujitsu Consulting's Center for Strategic Leadership (2003). The Information Paradox: Realizing the Business Benefits of Information Technology. McGraw-Hill: New York.

  • Timmermans D and Vlek C (1996). Effects on decision quality of supporting multiattribute evaluation in groups. Org Behav Hum Dec 68: 158–170.

    Article  Google Scholar 

  • Vari A and Vecsenyl J (1992). Experiences with decision conferencing in Hungary. Interfaces 22(6): 72–83.

    Article  Google Scholar 

  • von Winterfeldt D and Edwards W (1986). Decision Analysis and Behavioral Research. CUP: Cambridge.

    Google Scholar 

  • Vonortas NS and Hertzfeld HR (1998). Research and development project selection in the public sector. J Pol Anal Mngt 17: 621–638.

    Article  Google Scholar 

  • Walsham G (1992). Management science and organisational change: A framework for analysis. OMEGA: The Int J Mngt Sci 20: 1–9.

    Article  Google Scholar 

  • Weinstein M and Zeckhauser R (1973). Critical ratios and efficient allocation. J Public Econ 2: 147–157.

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. London School of Economics, London, UK

    A Morton

  2. Environment Agency, Bristol, UK

    D Bird

  3. Department of Business Innovation and Skills, London, UK

    A Jones

  4. Environment Agency, Brighton, UK

    M White

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  1. A Morton
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  2. D Bird
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  3. A Jones
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  4. M White
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Correspondence to A Morton.

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Morton, A., Bird, D., Jones, A. et al. Decision conferencing for science prioritisation in the UK public sector: a dual case study. J Oper Res Soc 62, 50–59 (2011). https://doi.org/10.1057/jors.2009.184

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  • DOI: https://doi.org/10.1057/jors.2009.184

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