1 Porter, A.L., Cunningham, S.W., and Sanz, A., Extending the FIP (Forecasting Innovation Pathways) Approach through an Automotive Case Analysis, Portland International Conference on Management and Engineering Technology (PICMET), San Jose, California, 2013. Extending the FIP (Forecasting Innovation Pathways) Approach through an Automotive Case Analysis Alan L. Porter 1 , Scott W. Cunningham 2 ,Alejandro Sanz 3 1 Search Technology, Norcross, GA, and Technology Policy and Assessment Center, GeorgiaTech, USA 30332 2 Faculty of Technology, Policy and Management, DelftUniversity of Technology, Delft, The Netherlands 3 SKF B.V., Nieuwegein, The Netherlands Abstract The ”FIP” approach seeks to Forecast Innovation Pathways for an emerging technology of interest. It does so by combining empirical ”tech mining” analyses with expert opinion. Tech mining extracts intelligence from multiple sources, but especially through bibliometric and text analyses of thousands of records retrieved from global R&D publication, patent, and business/context databases. FIP blends expert opinion from multiple sources, but especially by convening a focused workshop. SKF conducted an FIP exercise on Hybrid & Electric Vehicles (HEVs) that presents special challenges. HEVs combine multiple sub-systems, advancing at different rates technologically, with complex technical and market infrastructures. Asian automotive production and markets appear vital for the future of HEVs, and various technologies & applications (e.g., two-wheelers) warrant tracking. Grappling with this complex innovation system helped extend the FIP approach. Enhancements included extending the previous innovation tiers framework to array multiple technological and contextual factors in conjunction. This is the first FIP workshop to split into small groups to address three priority market segments and three prime geographical regions, then regroup to review and develop consensus.Manifold factors influence HEV innovation paths, so technology delivery systems are more complex than those addressed in previous FIP studies. We reflect on FIP process development, with suggestions regarding scoping, identification of sub- systems, and possible opportunities to systematize certain analyses. Introduction: Forecasting Innovation Pathways A small contingent of technology analysts has been developing an approach to Forecast Innovation Pathways (“FIP”) over the past few years [32, 34]. This effort can be located as a particular type of Future- oriented Technology Analysis (“FTA” – see http://foresight.jrc.ec.europa.eu/). In 2010 they presented a 4-stage (10-step) framework, as illustrated for the case of nano-enhanced solar cells [32]. Recently they have deepened the rationale and expanded the case base by comparing FIP use for nano-enabled biosensors and Deep Brain Stimulation[34]. Several have been exploring FIP regarding Nano-Enhanced Drug Delivery [36, 37]. Each of these cases could be considered a Newly Emerging Science & Technology (“NEST”). Here we explore FIP in the context of Hybrid & Electric Vehicle (“HEV”) development. This topic poses challenges to develop the approach in terms of adaptation to diverse issues along multiple dimensions. HEVs are 1) different -- transportation technologies, as contrasted with nano- and bio-technologies; and 2) with more developed infrastructure, massive capital investment, existing global markets, and different stakeholders than the previous NESTs addressed via FIP. FIP stands apart from other FTA approaches in its strong empirical base, combined with informal expert opinion, oriented toward elucidating “pathways” forward for R&D to translate into applications. It also combines analyses of the technical advances in conjunction with key socio-economic-organizational facets that collectively compose a Technology Delivery System (“TDS”) [46] to provide products to market. Pathways are particular routes for achieving that technology development. There are a range of concepts akin to TDS modeling, including technological regimes, technology architectures, and socio-technical systems. Acknowledging the variety of possible pathways for technological development is conceptually important -- for one, because it addresses the complexity of technological development [2]. Furthermore, the use of pathways assists analysts and decision-makers in recognizing that technologies are socially, and therefore, multiply determined. As mentioned, FIP combines empirical and expert knowledge parts. The empirical part builds upon “tech mining” [31, 33] of global database search results on the topic under study. The expert knowledge component poses its own set of challenges. In general, FTA emphasizes systematic, structured methods to elicit expert opinion – i.e., interviews, surveys, and Delphi processes. We have found that FIP work is facilitated by two different modes of tapping expertise. One is informal co-option of a local topical expert to collaborate in the analyses on an ongoing basis. In work at Georgia Tech on solar cells and biosensors, one PhD student joined on each endeavor, providing critical understanding of how the technology works. Such