A dissent-based approach for multi-stakeholder scenario development - The future of electric drive vehicles

Technological Forecasting and Social Change

Volumn 80, Issue 4, 2013, Pages 566-583

  Warth, Johannes ^a   Von der Gracht, Heiko A ^a   Darkow, Inga Lena ^a  

^a EBS BUSINESS SCHOOL   (Germany)

Author keywords

Delphi; Dissent; Electric drive vehicles; Multi stakeholder; Scenarios

Indexed keywords

DELPHI; DISSENT; ELECTRIC-DRIVE VEHICLES; MULTI-STAKEHOLDER; SCENARIOS;

ELECTRIC DRIVES; INTERNAL COMBUSTION ENGINES; SURVEYS;

DIGITAL STORAGE;

CLUSTER ANALYSIS; DELPHI ANALYSIS; ELECTRIC VEHICLE; STAKEHOLDER; TECHNOLOGY;

EID: 84875376171     PISSN: 00401625     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.techfore.2012.04.005     Document Type: Article

References (96)

1. Sousanis J. World Vehicle Population Tops 1Billion Units, in WardsAuto, 15th August 2011. http://wardsauto.com/ar/world_vehicle_population_110815.
2. van Mierlo J., Magetto G., Lataire P. Which energy source for road transport in the future? A comparison of batter, hybrid and fuel cell vehicles. Energy Convers. Manage. 2006, 47:2748-2760.
3. Nieuwenhuis P., Wells P., Vergragt P.J. Technological change and regulation in the car industry. Greener Manage. Int. 2004, 47:5-11.
4. Köhler J., Whitmarsh L., Nykvist B., Schilperoord M., Bergman N., Haxeltine A. A transitions model for sustainable mobility. Ecol. Econ. 2009, 68:2985-2995.
5. Schreyer C., Maibach M., Sutter D., Doll C., Bickel P. Externe Kosten des Verkehrs in Deutschland - Aufdatierung 2005 2007, INFRAS, Zürich.
6. Nakicenovic N. The automobile road to technological change: diffusion of the automobile as a process of technological substitution. Technol. Forecast. Soc. Chang. 1986, 29:309-340.
7. Dyerson R., Pilkington A. Innovation in complex systems: regulation and technology towards the electric vehicle. Int. J. Innov. Manag. 2000, 4:33-49.
8. Köhler J., Wietschel M., Whitmarsh L., Keles D., Schade W. Infrastructure investment for a transition to hydrogen automobiles. Technol. Forecast. Soc. Chang. 2010, 77:1237-1248.
9. Nykvist B., Whitmarsh L. A multi-level analysis of sustainable mobility transitions: niche development in the UK and Sweden. Technol. Forecast. Soc. Chang. 2008, 75:1373-1387.
10. Kemp R., Rotmans J. Managing the transition to sustainable mobility. System Innovation and the Transition to Sustainability: Theory, Evidence and Policy 2004, 137-167. Edward Elgar Publishers, Camberely. B. Elzen, F.W. Geels, K. Green (Eds.).
11. Åhman M., Nilsson L.J. Path dependency and the future of advanced vehicles and biofuels. Util. Policy 2008, 16:80-89.
12. Offer G.J., Howey D., Contestabile M., Clague R., Brandon N.P. Comparative analysis of battery electric, hydrogen fuel cell and hybrid vehicles in a future sustainable road transport system. Energy Policy 2010, 38:24-29.
13. Steenhof P.A., McInnis B.C. A comparison of alternative technologies to de-carbonize Canada's passenger transportation sector. Technol. Forecast. Soc. Chang. 2008, 75:1260-1278.
14. Baker E., Chon H., Keisler J. Battery technology for electric and hybrid vehicles: expert views about prospects for advancement. Technol. Forecast. Soc. Chang. 2010, 77:1139-1146.
15. Zhang T.G., Gensler S., Garcia R. A study of the diffusion of alternative fuel vehicles: an agent-based modeling approach. J. Prod. Innov. Manag. 2011, 28:152-168.
16. Loose W., Mohr M., Nobis C. Assessment of the future development of car sharing in Germany and related opportunities. Transp. Rev. 2006, 26:365-382.
17. Geels F.W. Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. Res. Policy 2002, 31:1257-1274.
18. Elzen B., Wieczorek A. Transitions towards sustainability through system innovation. Technol. Forecast. Soc. Chang. 2005, 72:651-661.
19. Rotmans J., Kemp R., van Asselt M. More evolution than revolution: transition management in public policy. Foresight 2001, 3:15-31.
20. Wilkinson A. Scenario practices: in search of theory. Int. J. Futures Stud. 2009, 13:107-114.
21. Curry A. Acting on the future. Scenarios for Success: Turning insights in to Action 2007, 339-372. John Wiley & Sons, Chichester. B. Sharpe, K. Van Der Heijden (Eds.).
22. Chermack T.J., Nimon K. The effects of scenario planning on participant decision-making style. Hum. Resour. Dev. Q. 2008, 19:351-372.
23. Shirin E. Conceptions of fairness and forming the common ground. Business Planning in Turbulent Times: New Methods for Applying Scenarios 2008, 223-242. Earthscan, London. R. Ramirez, J.W. Selsky, K. van Der Heijden (Eds.).
24. Arblaster K., Reed M.S., Fraser E., Potter C. Using scenarios to explore UK upland futures. Drivers of Environmental Change in Uplands 2009, 358-376. Routledge Series. A. Bonn, T. Allott, K. Hubacek, J. Stewart (Eds.).
25. Berkhout F., Hertin J., Tyteca D., Carlens J., Olsthoorn X., van Druinen M., van der Woerd F., Azzone G., Noci G., Jasch C., Wehrmeyer W., Wagner M., Gameson T., Wolf O., Eames M. MEPI-Measuring Environmental Performance of Industry. EC Environment and Climate Research Programme 2001, SPRU, University of Sussex, Sussex.
26. Gordon T., Pease A. RT Delphi: an efficient, "round-less" almost real time Delphi method. Technol. Forecast. Soc. Chang. 2006, 73:321-333.
27. Gnatzy T., Warth J., von der Gracht H., Darkow I.-L. Validating an innovative real-time Delphi approach - a methodological comparison between real-time and conventional Delphi studies. Technol. Forecast. Soc. Chang. 2011, 78:1681-1694.
28. Shiftan Y., Kaplan S., Hakkert S. Scenario building as a tool for planning a sustainable transportation system. Transp. Res. Part D: Transp. Environ. 2003, 8:323-342.
29. Rikkonen P., Aakkula J., Kaivo-Oja J. How can future long-term changes in Finnish agriculture and agricultural policy be faced? Defining strategic agendas on the basis of a Delphi study. Eur. Plan. Stud. 2006, 14:147-167.
30. Cowan R., Hultén S. Escaping lock-in: the case of the electric vehicle. Technol. Forecast. Soc. Chang. 1996, 53:61-79.
31. Struben J., Sterman J. Transition challenges for alternative fuel vehicle and transportation systems. Environ. Plann. B Plann. Des. 2008, 35:1070-1097.
32. Mills M.K. Environmentally-active consumers' preferences for zero-emission vehicles: public sector and marketing implications. J. Nonprofit Public Sect. Mark. 2008, 19:1-33.
33. Eggers F., Eggers F. Where have all the flowers gone? Forecasting green trends in the automobile industry with a choice-based conjoint adoption model. Technol. Forecast. Soc. Chang. 2010, 78:51-62.
34. Segal R. Forecasting the market for electric vehicles in California using conjoint analysis. Energy J. 1995, 16:89-111.
35. Bunch D.S., Bradley M., Golob T.F., Kitamura R., Occhiuzzo G.P. Demand for clean-fuel vehicles in California: a discrete-choice stated preference pilot project. Tranps. Res. A: Policy Pract. 1993, 27:237-253.
36. Dagsvik J.K., Wennemo T., Wetterwald D.G., Aaberge R. Potential demand for alternative fuel vehicles. Transp. Res. B: Methodol. 2002, 36:361-384.
37. Orbach Y., Fruchter G. Forecasting sales and product evolution: The case of the hybrid/electric car. Technol. Forecast. Soc. Chang. 2011, 78:1210-1226.
38. Mau P., Eyzaguirre J., Jaccard M., Collins-Dodd C., Tiedemann K. The neighbor effect: simulating dynamics in consumer preferences for new vehicle technologies. Ecol. Econ. 2008, 68:504-516.
39. Avadikyan A., Llerena P. A real options reasoning approach to hybrid vehicle investments. Technol. Forecast. Soc. Chang. 2010, 77:649-661.
40. Hillman K.M., Sandén B.A. Exploring technology paths: the development of alternative transport fuels in Sweden 2007-2020. Technol. Forecast. Soc. Chang. 2008, 75:1279-1302.
41. Turton H. Sustainable global automobile transport in the 21st century: an integrated scenario analysis. Technol. Forecast. Soc. Chang. 2006, 73:607-629.
42. van Bree B., Verbong G.P.J., Kramer G.J. A multi-level perspective on the introduction of hydrogen and battery-electric vehicles. Technol. Forecast. Soc. Chang. 2010, 77:529-540.
43. Weiller C. Plug-in hybrid electric vehicle impacts on hourly electricity demand in the United States. Energy Policy 2011, 39:3766-3778.
44. Turton H., Moura F. Vehicle-to-grid systems for sustainable development: an integrated energy analysis. Technol. Forecast. Soc. Chang. 2008, 75:1091-1108.
45. Cairns G., Wright G., Bradfield R., van der Heijden K., Burt G. Exploring e-government futures through the application of scenario planning. Technol. Forecast. Soc. Chang. 2004, 71:217-238.
46. Cairns G., Wright G., Van der Heijden K., Bradfield R., Burt G. Enhancing foresight between multiple agencies: issues in the use of scenario thinking to overcome fragmentation. Futures 2006, 38:1010-1025.
47. Wright G., Cairns G. Scenario Thinking Practical Approaches to the Future 2011, Palgrave MacMillan, Chippenham.
48. Varum C.A., Melo C. Directions in scenario planning literature - a review of the past decades. Futures 2010, 42:355-369.
49. Akkermans H.A., Bogerd P., Yücesan E., van Wassenhove L.N. The impact of ERP on supply chain management: exploratory findings from a European Delphi study. Eur. J. Oper. Res. 2003, 146:284-301.
50. von der Gracht H.A., Darkow I.-L. Scenarios for the logistics services industry: a Delphi-based analysis for 2025. Int. J. Prod. Econ. 2010, 127:46-59.
51. Gray P., Helmer O. The use of futures analysis for transportation research planning. Transp. J. 1976, 16:5-12.
52. Lynch M.E., Imada S.J., Bookbinder J. The future of logistics in Canada: a Delphi-based forecast. Logist. Transp. Rev. 1994, 30:95-112.
53. Ogden J.A., Petersen K.J., Carter J.R., Monczka R.M. Supply management strategies for the future: a Delphi study. J. Supply Chain Manag. 2005, 41:29-48.
54. Webler T., Levine D., Rakel H., Renn O. A novel approach to reducing uncertainty: the group Delphi. Technol. Forecast. Soc. Chang. 1991, 39:253-263.
55. Linstone H.A., Turoff M. Delphi: a brief look backward and forward. Technol. Forecast. Soc. Chang. 2011, 78:1712-1719.
56. Loveridge D. On Delphi questions. Ideas in Progress 2002, The University of Manchester, Manchester.
57. Elzen B., Geels F.W., Hofman P.S. Sociotechnical Scenarios (STSc): Development and Evaluation of a New Methodology to Explore Transitions towards a Sustainable energy Supply 2002, University of Twente, Enschede.
58. Parenté F.J., Anderson-Parenté J.K. Delphi inquiry systems. Judgemental Forecasting 1987, 129-156. John Wiley & Sons, Chichester. G. Wright, P. Ayton (Eds.).
59. Hasson F., Keeney S. Enhancing rigour in the Delphi technique research. Technol. Forecast. Soc. Chang. 2011, 78:1695-1704.
60. Okoli C., Pawlowski S.D. The Delphi method as a research tool: an example, design considerations and applications. Inf. Manag. 2004, 42:15-29.
61. Mitchell V.W. The Delphi technique: an exposition and application. Technol. Anal. Strat. Manag. 1991, 3:333-358.
62. Brown S., Pyke D., Steenhof P. Electric vehicles: the role and importance of standards in an emerging market. Energy Policy 2010, 38:3797-3806.
63. Frenken K., Hekkert M., Godfroij P. R&D portfolios in environmentally friendly automotive propulsion: variety, competition and policy implications. Technol. Forecast. Soc. Chang. 2004, 71:485-507.
64. Hermann W., Bosshard P. A Technical Assessment of High-Energy Batteries for Light-Duty Electric Vehicles 2006, Stanford University.
65. International Energy Agency, World energy outlook 2010 factsheet, International Energy Agency, Paris, 2010.
66. German Federal Ministry of Transportation Interim Report of the National Platform on Electric Mobility, Berlin 2010.
67. Huétnik F.J., van der Vooren A., Alkemade F. Initial infrastructure development strategies for the transition to sustainable mobility. Technol. Forecast. Soc. Chang. 2010, 77:1270-1281.
68. Farrell A.E., Keith D.W., Corbett J.J. A strategy for introducing hydrogen into transportation. Energy Policy 2003, 31:1357-1367.
69. European Commission Study on Urban Access Restrictions 2010, Rome.
70. Ernst, Young Gauging Interest for Plug-In Hybrid and Electric Vehicles in Selected Markets 2010, E&Y.
71. Gould J., Golob T.F. Clean air forever? A longitudinal analysis of opinions about air pollution and electric vehicles. Transp. Res. Part D: Transp. Environ. 1998, 3:157-169.
72. Dijk M., Yarime M. The emergence of hybrid-electric cars: innovation path creation through co-evolution of supply and demand. Technol. Forecast. Soc. Chang. 2010, 77:1371-1390.
73. A. Gutsch, Elektroautos erreicht Benziner-Leistung in frühestens 50 Jahren, in: Daily Green, 31st May 2011, 2011. http://www.dailygreen.de/2011/05/31/elektroautos-erreicht-benziner-leistung-in-fruhestens-50-jahren-23296.html.
74. Arthur D. Little, E-Mobilität: Ansatzpunkte und Herausforderungen 2010, ADL.
75. Berggren C., Mangusson T., Sushandoyo D. Hybrids, diesel or both? The forgotten technological competition for sustainable solutions in the global automotive industry. Int. J. Automot. Technol. Manag. 2009, 9:148-173.
76. Moldrop C., Morgal J.M. Risks of future drugs: a Danish expert Delphi. Technol. Forecast. Soc. Chang. 2001, 67:273-289.
77. Tersine R.J., Riggs W.E. The Delphi technqiue: a long-range planning tool. Bus. Horiz. 1976, 19:51-56.
78. Welty G. Problems of selecting experts for Delphi exercises. Acad. Manag. J. 1972, 15:121-124.
79. Holtz G., Brugnach M., Pahl-Wostl C. Specifying "regime" - a framework for defining and describing regimes in transition research. Technol. Forecast. Soc. Chang. 2008, 75:623-643.
80. Adler M., Ziglio E. Gazing into the Oracle: The Delphi Method and its Application to Social Policy and Public Health 1996, Jessica Kingsley Publishers, London.
81. Geist M.R. Using the Delphi method to engage stakeholders: a comparison of two studies. Eval. Program Plann. 2010, 33:147-154.
82. Rowe G., Wright G. The impact of task characteristics on the performance of structured group forecasting techniques. Int. J. Forecast. 1996, 15:353-375.
83. Best R.J. An experiment in delphi estimation in marketing decision making. J. Mark. Res. 1974, 11:448-452.
84. Armstrong J.S., Overton T.S. Estimating nonresponse bias in mail surveys. J. Mark. Res. 1977, 14:396-402.
85. Hahn E.J., Rayens M.K. Consensus for tobacco policy among former state legislators using the policy Delphi method. Tob. Control. 1999, 8:137-140.
86. Scheibe M., Skutsch M., Schofer J. Experiments in Delphi methodology. The Delphi Method Techniques and Applications 1975, 262-287. Addison-Wesley Reading. H.A. Linstone, M. Turoff (Eds.).
87. Heath C., Gonzalez R. Interaction with others increases decision confidence but not decision quality: evidence against information collection views of interactive decision making. Organ. Behav. Hum. Decis. Process. 1995, 61:305-326.
88. Ecken P., Gnatzy T., von der Gracht H.A. Desirability bias in foresight: consequences for decision quality based on Delphi results. Technol. Forecast. Soc. Chang. 2011, 78:1654-1670.
89. Field A. Discovering Statistics Using SPSS 2005, Sage Publications, London.
90. Magidson J., Vermunt J.K. Latent class models. The Sage Handbook of Qualitative Methodology for the Social Sciences 2004, 175-198. Sage Publications, Thousand Oaks. D. Kaplan (Ed.).
91. Murtagh F., Raftery A.E. Fitting straight lines to point patterns. Pattern Recognit. 1984, 17:479-483.
92. Banfield J.D., Raftery A.E. Model-based Gaussian and non-Gaussian clustering. Biometrics 1993, 49:803-821.
93. Dunn K.M., Jordan K., Croft P.R. Characterizing the course of low back pain: a latent class analysis. Am. J. Epidemiol. 2006, 163:754-761.
94. Vermunt J.K., Magidson J. Latent Gold 4.0 User's Guide 2005, Statistical Innovations Inc., Belmont, Massachusetts.
95. Schwartz G. Estimating the dimension of a model. Ann. Stat. 1978, 6:461-464.
96. Wright G., Goodwin P. Decision making and planning under low levels of predictability: enhancing the scenario method. Int. J. Forecast. 2009, 25:813-825.