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Developing a Backcasting Approach for Systemic Transformations towards Sustainable Mobility – The Case of the Automotive Industry in Germany Martin Zimmermann,

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Presentation on theme: "Developing a Backcasting Approach for Systemic Transformations towards Sustainable Mobility – The Case of the Automotive Industry in Germany Martin Zimmermann,"— Presentation transcript:

1 Developing a Backcasting Approach for Systemic Transformations towards Sustainable Mobility – The Case of the Automotive Industry in Germany Martin Zimmermann, Johannes Warth, Heiko von der Gracht, Inga-Lena Darkow Center for Futures Studies and Knowledge Management EBS Business School, Wiesbaden, Germany The 4th International Seville Conference on Future-Oriented Technology Analysis (FTA) 12 & 13 May 2011

2 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Motivation & Objective Backcasting Combination of Delphi, Scenario Planning and Backcasting Delphi-based 4-step Backcasting Methodological Discussion Limitations & Further Research 6 2

3 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Motivation & Objective Radical systemic changes to current systems of mobility necessary to achieve sustainable development (Nykvist & Whitmarsh, 2008) German government to establish up to 1 million electric vehicles on the streets until 2020 and over 5 million vehicles until 2030 (Federal Ministry of Transport, Building and Urban Development, 2009) Combinations of technological, cultural, societal, institutional, and organizational changes required for such transformations (Quist & Vergragt, 2006) Approach for achieving transitions towards a sustainable future is backcasting (Dreborg, 1996) Motivation Demonstration of an innovative qualitative backcasting approach (Delphi & Semi-structured interviews) to analyze transformations to sustainable mobility / facilitate future-oriented decision making Advantages of combining these two methods will be highlighted and critically reflected Usage of Backcasting as best practice for Competitiveness Monitor (CoMo) research project Objective 3 The content of this presentation is based on the joint research project Competitiveness Monitor, funded by the German Federal Ministry of Education and Research (project reference number: 01IC10L18 A). Project duration: 06/2010 – 05/2013. Responsibility for the content is with the author(s).

4 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Backcasting Present Desired Future Probable Future = Drivers= Obstacles 2030 = Overall Trends Plausibility Check Dreborg (1996): Backcasting particularly useful when… complex and persistent problems are in focus, dominant trends are part of the problem, external factors are present, the need for major change exists, the time frame and thematic focus allow for radical changes. 4

5 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Combination of Delphi, Scenario Planning and Backcasting Strategic Problem Orientation Develop future vision Backcasting analysis Elaborate future alternative & define follow- up agenda Embed results and agenda & stimulate follow-up Development of projections Evaluation of projections Scenario Writing Development of Factors Expert Check Delphi (von der Gracht & Darkow, 2010) Backcasting (Quist, 2007) Scenario Development Scenario Transfer Generic Scenario Planning (Bishop et al, 2007; Shermack et al., 2001) 5

6 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Delphi-based 4-step Backcasting Strategic problem orientation Development of 20 projections according to STEP Execution of a RealTime Delphi Survey Structured desk research / Expert workshops Development of a Desirable Scenario Scenario development technique Development of 9 main influential factors Coding of Delphi arguments Backcasting – Assessing the way towards the desirable scenario Semi-structured interviews Systematic identification of hot topics/patterns Descriptive Coding / Grounded Coding approach Pattern coding Follow-up activities Workshops, lectures, CoMo, etc Strategic problem orientation Development of future images and influencing factors Development of measuresContinuation 6

7 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Strategic problem orientation 1 Identification of fundamental research issues to be addressed Several stakeholder workshops with participants from OEMs, suppliers, government, academics Enrichment of findings of the workshop by comprehensive desk research activities Focus on German governments plans: Reduction of carbon dioxide emissions until 2020 by 40%, compared to 1990 (Federal Ministry of Economics and Technology, 2007) Key pillar: Strengthening e-mobility until 2030 Strategic Problem Orientation STEP analysis (social, technological, economical and political factors) In-depth analysis of a sample of academic studies and governmental-related reports Future workshop with 11 business and six academic experts Formulation of 20 projections in short, descriptive and provoking propositions Development of future projections 7

8 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Development of future images and influencing factors 2 Group communication process (Linstone & Turoff, 1975) Based on expert knowledge Anonymous survey process Feedback after each round Statistical & qualitative analysis Consensus seeking Results represent adequate substitute for lack of empirical data (Dalkey & Helmer, 1963) Characteristics of DelphiOnline-based, real-time Delphi tool 8

9 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany 2 Participation of 140 experts Response rate of 31% (of 441 invitations) Diverse sample of experts from 15 different groups Delphi Participants Coding of more than 2,000 qualitative arguments in order to identify the influencing factors Identification of nine main factors Expert check for validation Identification of influencing factors Energy mix for vehicle operation Germany's competitiveness Comodal mobility Changing market structure Technological maturityGovernment intervention Raw material supplyCustomer preferences Infrastructural conditions 9 Development of future images and influencing factors

10 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Development of future images and influencing factors 2 Desirable Scenario 2030: Electric Mobilitys Dominance 10

11 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Development of future images and influencing factors 2 Electric drives (especially battery-electric vehicles, range extender and plug-in hybrids) dominate the number of new registrations in Germany. Conventional power trains cannot keep up with electrical drives with regard to essential performance indicators. The success of electric vehicles was supported by three key developments: (1) the increased willingness of customers to pay more for these drive systems, (2) a large part of energy obtained for new drive concepts originates from renewable sources (3) the comprehensive provision of efficient and cheap charging facilities for electric drives In the segments of medium and light commercial vehicles partially or fully electric drives are standard. The market for new drive concepts is dominated by manufacturers from Europe and Asia alike. In this case the raw material supply does not constitute a bottleneck in the dissemination of new drive concepts. Customers mainly use an optimally coordinated network of comodal mobility services. Desirable Scenario 2030: Electric Mobilitys Dominance 11

12 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Development of measures 3 Identification of measures that need to be taken in order to realize the desirable scenario Identification of actors that need to become active in order to make the change happen Determination of the timeliness of the different measures Main goals 43 interviews with experts proceeding from 15 Delphi interest groups Alignment of the interview samples distribution Descriptive / Pattern Coding with Nvivo Software Process 12

13 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Development of measures 3 Incentivisation for customers vs. industry (R&D) support Role of established vs. new companies / co-operations Role of comodal mobility for electric mobility scenario Selected discussed topics Follow-up of backcasting exercises very important to actually use and implement the content that has been generated (Quist & Vergragt, 2006) Multiple workshops with stakeholders from the automotive industry Contribution to the joint research project Competitiveness Monitor (CoMo) within the EffizienzCluster LogistikRuhr of the German Federal Ministry of Education and Research Process Continuation 4 13

14 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Methodological Discussion So far, (qualitative) participatory backcasting approaches mostly executed with the help of workshops and focus group discussions (Carlsson-Kanyama, 2011; Dreborg, Moll, & Padovan, 2008; Kok et al., 2006; Svenfelt et al., 2011). Aim of our backcasting exercise: Inclusion of a diverse group of stakeholders not only in the development of the scenarios, but also in the backcasting step itself. Combination of an innovative Delphi survey with individual semi-structured expert interviews and following structured coding By using the web-based real-time Delphi approach we were able to invite a broad number of participants (140) to the study which enabled us to reach experts from 15 different user groups. Our approach enables us to both include a large number of different stakeholders and still having a structured and comprehensible process (coding) of how the results are analysed and further used 14

15 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Limitations & Further Research Broad range of opinions in both Delphi and interviews step did not allow for a consensus in all cases e.g. when developing the scenarios or elaborating on the measures Difficulties in elaborating on timeliness of single measures due to variety of topics discussed Limitations Optimisation of structured stakeholder inclusion in 3rd step (backcasting) Combination of several Delphis for 1) scenario creation and 2) backcasting analysis Recruitment of opposing party discussion panels based on Delphi data Expert vs. non-expert validation of scenarios etc. Further Research 15

16 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Thank you! 16 Center for Futures Studies and Knowledge Management EBS Business School Soehnleinstr. 8 F D Wiesbaden / Germany Tel Fax

17 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Backup 17

18 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Mission Create the future together Center for Futures Studies Research and Knowledge Management Research Achievements Network Part of EBS Network with 180 partner universities and 200 business partners worldwide Anchored in the Foresight-Community: Network for Future Studies Research, European Foresight Network, World Future Society, Oxford Scenario Network, EIRAC Present in emerging markets (Russia, India and China) Key Aspects To pursue scientifically-established research in Futures Studies and manage its quality To generate futures knowledge to support decision-making processes on governmental, economic and scientific issues To establish Futures Studies research as an academic discipline / strategic instrument in business practice Contract research with business partners (futures studies, tool development) Scenario transfer: turn research results into strategy Collaborate in public sector research projects High diversity in team (mix of expertise) Methodical and professional competence Scenario and Delphi Analyses Roadmapping & Backcasting Early Warning and Risk Management Wildcard Analyses Futures Studies Workshops Method Integration (Scenario-Toolbox) Timeframe Scenario 2 Scenario 3 Scenario 4 Scenario 1 Center for Futures Studies. Shaping the future together! Methodological Lead

19 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Sources Åkerman, J., & Höjer, M. (2006). How much transport can the climate stand?--Sweden on a sustainable path in Energy Policy, 34(14), Armstrong, J. S. (2001). Principles of Forecasting: A Handbook for Researchers and Practitioners. Boston et al.: Kluwer Academic Publishers. Carlsson-Kanyama, A., Dreborg, K. H., Moll, H. C., & Padovan, D. (2008). Participative backcasting: A tool for involving stakeholders in local sustainability planning. Futures, 40(1), Cuhls, K. (2002). Participative foresight – How to involve stakeholders in the modelling process. Paper presented at the Innovation Policy Conference July 11, 2002, Brussels, Belgium. Delbecq, A., Van de Ven, A. H., & Gustafson, D. H. (1986). Group Techniques for Program Planning: a guide to nominal group and delphi processes. Middleton: Green Briar Press. Dreborg, K. H. (1996). Essence of backcasting. Futures, 28(9), Dunn, W. N. (2004). Public Policy Analysis. An Introduction (3 ed.). New Jersey: Pearson Prentice Hall. Eames, M., & Egmose, J. (2011). Community foresight for urban sustainability: Insights from the Citizens Science for Sustainability (SuScit) project. Technological Forecasting and Social Change, In Press, Corrected Proof. Ebert, J. E. J., Gilbert, D. T., & Wilson, T. D. (2009). Forecasting and Backcasting: Predicting the Impact of Events on the Future. Journal of Consumer Research, 36(3), Engels, T. C. E., & Powell Kennedy, H. (2007). Enhancing a Delphi study on family-focused prevention. Technological Forecasting and Social Change, 74(4), Federal Ministry of Economics and Technology. (2007). Bericht zur Umsetzung der in der Kabinettsklausur am 23./ in Meseberg beschlossenen Eckpunkte für ein Integriertes Energie- und Klimaprogramm. Berlin: Federal Ministry of Economics and Technology. Federal Ministry of Transport, Building and Urban Development. (2009). German Federal Governments National Electromobility Development Plan. Retrieved from Giurco, D., Cohen, B., Langham, E., & Warnken, M. (2011). Backcasting energy futures using industrial ecology. Technological Forecasting and Social Change, In Press, Corrected Proof. Gordon, T., & Pease, A. (2006). RT Delphi: An efficient, "round-less" almost real time Delphi method. Technological Forecasting and Social Change, 73(4), Green, K., & Vergragt, P. (2002). Towards sustainable households: a methodology for developing sustainable technological and social innovations. Futures, 34(5), Henderson, N. R. (2009). Managing Moderator Stress: Take a Deep Breath. You Can Do This! Marketing Research, 21(1), Höjer, M. (1998). Transport telematics in urban systems--a backcasting Delphi study. Transportation Research Part D: Transport and Environment, 3(6), Höjer, M., Gullberg, A., & Pettersson, R. (2011). Backcasting images of the future city--Time and space for sustainable development in Stockholm. Technological Forecasting and Social Change, In Press, Corrected Proof. Höjer, M., & Mattsson, L.-G. (2000). Determinism and backcasting in future studies. Futures, 32(7), Holmberg, J., & Robèrt, K.-H. (2000). Backcasting a framework for strategic planning. International Journal of Sustainable Development & World Ecology, 7(4), Jungk, R., & Muellert, N. (1987). Future workshops: How to Create Desirable Futures. London, England: Institute for Social Inventions. 19

20 Developing a Backcasting Approach for Systemic Transformations Towards Sustainable Mobility – The Case of the Automotive Industry in Germany Sources Kok, K., Patel, M., Rothman, D. S., & Quaranta, G. (2006). Multi-scale narratives from an IA perspective: Part II. Participatory local scenario development. Futures, 38(3), Landeta, J., Matey, J., Ruíz, V., & Galter, J. (2008). Results of a Delphi survey in drawing up the input-output tables for Catalonia. Technological Forecasting and Social Change, 75(1), Lovins, A. B. (1976). ENERGY STRATEGY: THE ROAD NOT TAKEN?. Foreign Affairs, 55(1), Nykvist, B., & Whitmarsh, L. (2008). A multi-level analysis of sustainable mobility transitions: Niche development in the UK and Sweden. Technological Forecasting and Social Change, 75(9), Peard, E. (2011). German summit tackles the E10 biofuel 'debacle'. The China Post. Retrieved from summit.htm Quist, J. (2007). Backcasting for a Sustainable Future - The impact after 10 years. Eburon. Quist, J., & Vergragt, P. (2006). Past and future of backcasting: The shift to stakeholder participation and a proposal for a methodological framework. Futures, 38(9), Reed, J., & Soble, J. (2010). Electric and hybrid: Sales feed off hype and subsidy. Financial Times. Retrieved from feab49a.html#axzz1G1Pd5Cgz Robinson, J. B. (1982). Energy backcasting A proposed method of policy analysis. Energy Policy, 10(4), Robinson, J. B. (1988). Unlearning and backcasting: Rethinking some of the questions we ask about the future. Technological Forecasting and Social Change, 33(4), Robinson, J. B. (1990). Futures under glass : A recipe for people who hate to predict. Futures, 22(8), Rowe, G., Wright, G., & Bolger, F. (1991). Delphi: A reevaluation of research and theory. Technological Forecasting and Social Change, 39(3), Scapolo, F., & Cahill, E. (2004). New Horizons and Challenges for Future–oriented Technology Analysis Proceedings of the EU-US Scientific Seminar: New Technology Foresight, Forecasting & Assessment Methods. Paper presented at the European Commission DG JRC-IPTS Seville. Svenfelt, Å., Engström, R., & Svane, Ö. (2011). Decreasing energy use in buildings by 50% by A backcasting study using stakeholder groups. Technological Forecasting and Social Change, In Press, Corrected Proof. Tapio, P. (2002). Climate and traffic: prospects for Finland. Global Environmental Change, 12(1), Vergragt, P. J., & van Grootveld, G. (1994). Sustainable technology development in the Netherlands: the first phase of the Dutch STD programme. Journal of Cleaner Production, 2(3- 4), von der Gracht, H. A., & Darkow, I.-L. (2010). Scenarios for the logistics services industry: A Delphi-based analysis for International Journal of Production Economics, 127(1), von der Gracht, H. A., Gnatzy, T., Darkow, I.-L., Gordon, T. J., & Glenn, J. (2011). New Frontiers in Delphi Research – Experiences with Real Time Delphi in Foresight. Paper to be presented at the World Future Society Conference, July 2011, Vancouver, Canada. Zapata, C., & Nieuwenhuis, P. (2010). Exploring innovation in the automotive industry: new technologies for cleaner cars. Journal of Cleaner Production, 18(1),


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