Technology Monitor: Developing and Applying a Method for Alignment of Innovation Policy in the Energy Sector

Transcription

1 1 Technology Monitor: Developing and Applying a Method for Alignment of Innovation Policy in the Energy Sector Tim Foppen Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, The Netherlands. April 16, 2015 Abstract Policy alignment is a well-known problem when stimulating innovative energy technologies. In this paper policy alignment is approached from a technology perspective. Using a technology classification, based on morphological analysis and design theory, projects are classified looking at the technological function and physical artifacts. The approach is demonstrated for measurement of alignment of the Dutch Topsector Energy policy (TSE) and the Energie Investerings Aftrek (EIA). Furthermore the method could be used for aligning all activities in the Public Funding System as an indicator for misalignment. Additional attention should be given to usability and implementation of the method. Key Words: Technology Classification, Morphological Analysis, Policy Alignment, Energy Innovation 1. Introduction Technological innovation is an important determinant for long term economic growth (Solow, 1956). Porter (1990) argues that technological innovation is the main driver for the competitive advantage of nations, but also regions or companies. The Dutch national governmental even states that innovation is the beating heart of the economy (Agentschap NL, 2011). For this reason innovation is one of the classic areas in economic policy of governments all over the world. 1.1 Policy Alignment Policy alignment is a problem when stimulating innovative energy technologies (Negro, et al., 2012). Policy instruments should be consistent and complementary but they should, to a large extent, support the same or similar technologies within the energy sector. Misalignment results in the effect that investments are not used efficiently. As a consequence the economic growth, due to technological innovation is not optimized (Hekkert et al, 2007). Constant alignment of policy instruments is thus necessary, as well as the resulting alignment of innovation practices supported by policy. Alignment is thus most often a coordination effort of activities. This can be influences by hard institutional alignment (Weber & Rohracher, 2012), (Klein Woolthuis, Lankhuizen, & Gilsing, 2005) like written steering instruments (in this case policy) or soft institutional alignment and social institutional alignment like social norms and values, culture or trust (Weber & Rohracher, 2012), (Carlsson & Jacobsson, 1997). At this moment the government lacks tools and methods to deal with misalignment. 1.2 Technology Perspective on Alignment In this research alignment is approached from a technology perspective. More specifically this research looks at the horizontal technology alignment (Kathuria, Joshi, & Porth, 2007) of policy instruments. A

2 2 tool is developed to help dealing with policy misalignment. This requires mapping and classification of the content within policy instruments in a consistent way. After mapping, a comparison could be made, from which a judgement about alignment could follow. Furthermore based on the technology alignment analysis the Dutch Government could improve the hard institutional side of policy and improve the coordination as executed by the policy framework. Soft institutional alignment could follow when solving the hard institutional failure is not sufficient. 1.3 Case Study In order to demonstrate the working of the approach a case study is conducted within RVO, the Dutch Enterprise Agency that coordinates subsidy requests. Within this case study a comparison will be made between two policy instruments: the Topsector Energy Policy (TSE) and the Energie Investerings Aftrek (EIA). This comparison is special, since the instruments stimulate technologies in subsequent phases of development Figure 1 Phases of Development for Technologies according to RVO. The TSE-policy stimulates technologies in research/discovery, development and demonstration phases (RD&D). EIA stimulates the market deployment and diffusion of energy saving technologies. Mature TSE-technologies should reappear on the EIA-list. Additionally, incremental improvements to existing EIA-technologies should be reached through RD&D-effort (Henderson & Clark, 1990). This should, ideally, be stimulated by the TSE-policy. Together TSE and EIA should form an aligned combination of policy instruments that stimulate technologies from their discovery in a research laboratory, to their diffusion in society. From the market introduction on, significant returns on public investments can be reached through economic growth, CO 2 reduction and competitive advantage due to innovation. 1.4 The Research Approach This research is conducted in order to find out whether TSE and EIA policy are aligned in terms of technologies they support. For this it is necessary to have a method for technology comparison. The work in this research (Foppen, 2015) was aimed to develop an alignment measurement tool that looks the technologies as stimulated in both instruments. A classification is made that enables comparison (Bailey, 1994). Morphological analysis of technology project is the method that enables the classification. Morphology or morphological analysis (Ritchey, 2011) is used in scientific disciplines where formal structure is a central issue. Since technologies have strict formal structures, decomposition according to their configuration (or morphology), it is very relevant for technology classification. This article will elaborate on the method that is used to classify technologies for alignment. First theory and definitions are described. Secondly a conceptual classification model will be presented, this includes an application procedure. Subsequently will be reported on the results of a case study, based on this model, finally the impact of the study on the Dutch Public Research Funding System will be discussed.

3 3 2. Theoretic Considerations In order to apply a morphological analysis the problem was decomposed in smaller issues regarding to describing technologies, technology hierarchies and innovation. All aspects will be discussed in the upcoming paragraphs as they influence the way the morphological analysis should be executed. 2.1 Describing Technologies Murmann & Frenken (2006) and Baldwin & Clarke (2000) describe technologies as part of a larger technological system. Next to that a technology itself consists of multiple technologies as well and is thus a technological system of its own. Furthermore they distinguish between functional or task structures, artifacts and artifact structure and a third description talking about design structure or operational principles. System and Product design theories follow this line of thought. Suh s axiomatic design theory for systems (Suh, 1998) looks at a functional and physical domain, which are connected by technology modules. Erens & Verhulst (1997) use a similar approach in their theory about product architectures: they describe functional, physical and technology domains. 2.2 Technology Hierarchies Designers of technological products and systems make use of interrelated functional and physical hierarchies. According to Erens & Verhulst (1997) building a product from a number of components is called a productarchitecture. Products are thereby hierarchically related when looking at the sub-components they contain. What is called a product and what is called a component is dependent on the level of analysis one chooses. Suh (1998) describes technological systems as a configuration of all predefined functional requirements (FR s), design parameters (DP s), process variables (PV s) and constraints (C s). He furthermore distinguishes four domains for design; customer, functional, physical and process domains of which the functional and physical domain can be decomposed hierarchically. Functions are decomposed in a hierarchical way and are defined as the minimum set of independent requirements that the design must satisfy. Furthermore they are related to components in the physical domain, as a method for checking a consistent design on its predefined functions and vice-versa, this process is often a zigzag. Concluding, one can see none of the authors specifies a single hierarchical level, but use multiple instead. They do so because the hierarchies in products and components are often interrelated, as well as the functional and physical hierarchy. For a conceptual classification system it is thus necessary to be flexible in this. 2.3 Innovation According to Murmann & Frenken (2006) innovation takes place at all levels of the technology hierarchy. Depending on the level of analysis this can be categorized as radical or incremental innovation. It is argued that the higher in the system hierarchy an innovation takes place, the higher the impact on the system performance. Also Sood & Tellis (2005 ) talk of multiple types on innovation (design, platform and component innovation), which correspond to different aggregation levels. Arthur (2009) speaks of structural deepening of a technology. He describes the process of iterative problem solving with a technology: By adding sub-systems to reduce negative impacts or enhance positive effects the technology gets more complex over time. This

4 4 way of innovation has limitations: once a single principle reaches his adaptive stretch, novel principles need to be invented in order to improve performance. This often causes revolution and re-domaining of technologies. One could notice that new principles can occur in a technological system. This causes that new functional and physical technologies are created over time; these are often created through changes in the lowest hierarchical level or as a zigzag between physical and functional hierarchies within the current principles. This is a challenge the classification system has to deal with. 3. Defining Physical and Functional Technologies 3.1 Physical Technologies According to Erens & Verhulst the physical hierarchy consists of the consistent description of a system s part and assemblies. It describes the physical realization of a system and is strongly related to de construction of a product and can be decomposed in physical components. Suh describes design parameters in the physical domain as physical parameters, parts or assemblies. In this research one speaks of physical technologies when the technology is either an existing product or component within a product. 3.2 Functional Technologies Functions are described by Erens & Verhulst as functional requirements,, primarily listed in the Requirements Specifications in a textual form. For Suh, functions or functional requirements form the minimum set of independent requirement that completely characterize the functional needs of a product. In this research functions are used as the conceptual description of what (a group of) technology should do. Within the pillars multiple levels can be distinguished that correspond to the classification categories. Furthermore the combined levels of the physical and functional hierarchy together form a layer. In order to compare EIA and TSE this research classified technologies along two layers. If necessary these classes can be extended to higher or lower layers, depending on the detail one requires for analysis. 4. Classification For the actual classification a classification model and procedure are developed, these will be described in the next two paragraphs. 4.1 Classification model for Technology Comparison Approaching the morphological analysis as an inversed design process results in a conceptual model based on pillars, layers and levels (Figure 2). The functional and physical hierarchies form pillars for classification, while levels and layers form the actual classes. The model shows the possibility to extent the model endlessly in both upward and downward aggregation levels. The figure shows an endless sequel of interrelated functional and physical levels. In theory this allows users to break down technologies to the smallest parts possible (functional and physical level m), or, on the other side, highest aggregation level possible (functional and physical level n). This makes that it is possible to classify and compare technologies that are currently in early innovation phases and not specifically assigned to a higher level function or physical artifact. This only requires one to adapt the procedure that is basis for the classification.

5 5 Figure 3 Application Procedure Figure 2 Conceptual Classification Model 4.2 Classification Procedure Another part of the conceptualization phase is the development of a procedure to secure that repetition of the classification practice is possible. This procedure extended the original conceptual classification model for analysis of alignment, to a model with a guideline for classification of projects and technologies in RVO. For classification it is necessary to decompose the physical technologies first, before assigning a functional class. This helps to deal with multifunctional cases, to determine the core of the technology project and furthermore it to allow new users to add data for future analysis. 5. Results Furthermore the method, including the comparison model and application procedure, was used to analyze the current alignment of EIA and TSE policy. The main functional level analysis showed us the most usable results; 12 functional categories were found to be unaligned within TSE and EIA, 10 were found to have poor alignment and only 4 categories were aligned. Due to this high amount of misalignment, further desk research was conducted. This helped us to understand that his was due to deliberate policy decisions or natural circumstances like existence of a dominant design, an immature technology or policy decision to no longer support a fully developed technology or technology with limited potential. One could thus not fully rely on registration and comparison of project, but should always look for other explanations. Nonetheless it was found that managing energy is the biggest blind spot on the EIAlist. This functional category contains energy management systems that enable the implementation of smart grids.

6 6 Table 1 Alignment Analysis Results (adopted from (Foppen, 2015)) Conversion No Alignment Low Alignment High Alignment Cooling Heating Ventilating Isolating Industrial Processing Driving Drying Energy Efficiency (general) Monitoring & Controlling Lighting Reusing Energy Efficient Mobility Production No Alignment Low Alignment High Alignment Producing Geothermal Energy Producing Solar Energy Producing Bio Energy Producing Hydrogen Energy Producing Fossil Energy Producing Waste Energy Producing Wind Energy Producing Hydro Energy Producing Energy (general) Distribution No Alignment Low Alignment High Alignment Managing Energy Transporting Energy Storage No Alignment Low Alignment High Alignment Storing Hydrogen Storing Electricity Storing Fuels Storing Heat Storing Unspecified 6. Evaluation Registering projects along this methodology enables the Dutch Public Funding System (including policy makers, funding agencies and research performing organizations (Lepori, 2011)) to align its activities in the future. This is not limited to policy instruments like TSE and EIA, but also along other innovation policy instruments. Coordination of activities by policy based on the data of the classification system can contribute to enhanced evidence based policy making (Head, 2010). It is in interest of all stakeholders of in the public research funding system to contribute to align activities based on high quality data (Shaxson, 2005). Next to the promise of an aligned public research funding system, one should consider a certain amount of issues when using the classification system. First of all one should be aware that alignment of technologies is only an indicator for misalignment in policy. The method only monitors alignment. Subsequent steps need to be taken in order to actually align activities on an organizational level. Secondly in order to implement a classification system a lot of attention should be given to the implementation. A content based system is hard to implement (Hullavarad, O'Hare, & Roy, 2015). To implement one at multiple stakeholders requires even more attention. As a consequence the usability (McNamara & Kirakowski, 2006) and communication surrounding the implementation (DeSanctis & Poole, 1994) are of great importance. As a result usability should get attention before implementation by the creation of user manuals and organizing training (Kushniruk, Myers, Borycki, & Kannry, 2009). Furthermore communication of the classifications system is important during the implementation, as it explains users the strategic goals they could achieve using the content management system (DeSanctis & Poole, 1994).

7 7 7. Conclusions In this research it was chosen to approach policy alignment from a technology perspective. This meant that all technologies that are part of the policy, mostly embedded into projects, needed to be classified according to their technological content. This is something that is not done regularly, since most projects are only registered according to their policy aspect or financials. Concluding it could be said that the technological approach using a morphological analysis gave us insights to what extent the policy instruments are aligned. Using a model composed of related physical pillars and functional hierarchies, technologies can be classified and compared. The functional aspect is required as an addition to morphological analysis since also innovative technologies need to be classified. Furthermore the future comparison should be done by regularly updating the technologies in the database, according to the application procedure as used in this thesis. Usability and communication therefor are an important aspect that should gain continuous attention to make the method workable and accepted in the future. As updating and registration should be done across the full public funding system and Dutch innovation community, RVO should also research to what extent internal and external stakeholders would like to collaborate for the registration of projects. References Agentschap NL, De Innovatie Sensor meet de hartslag van de economie, s.l.: s.n. Arthur, W. B., The Nature of Technology: What it is and how it evolves. New York: Free Press. Bailey, K., Typologies and Taxonomies: An Introduction to Classification Techniques. London: Sage Publications. Baldwin, C. Y. & Clark, K. B., Design Rules. The Power of Modularity, vol 1.. Cambridge, MA, USA: MIT Press. Carlsson, B. & Jacobsson, S., In Search of Useful Public Policies Key Lessons and Issues for Policy Makers. In: Technological Systems and Industrial Dynamics. s.l.:springer US, pp DeSanctis, G. & Poole, M. S., Capturing the Complexity in Advances Technology Use: Adaptive Structuration Theory. Organization Science, pp , Vol 5, No 2. Erens, F. & Verhulst, K., Architectures for product families. Computers in Industry, pp Volume 33. Foppen, T., Technology Monitor: Design of a classification method for energy innovationprojects in the Netherlands, Delft: TU Delft. Head, B. W., Reconsidering evidence-based policy: Key issues and challenges. Policy and Society, Volume 29, pp Hekkert et al, M., Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting & Social Change, pp Henderson, R. & Clark, K., Architectural innovation: the reconfiguration of existing product technologies nad the failure of established firms. Administrative Science Quarterly, pp Volume 35. Hullavarad, S., O'Hare, R. & Roy, A. K., Enterprise Content Management solutions Roadmap strategy and implementation challenges. International Journal of Information Management, pp Kathuria, R., Joshi, M. P. & Porth, S. J., Organizational alignment and performance: past, present and future. Management Decision, 45(3), pp Klein Woolthuis, R., Lankhuizen, M. & Gilsing, V., A system failure framework for innovation policy design. Technovation, pp Kushniruk, A. W., Myers, K., Borycki, E. M. & Kannry, J., Exploring the Relationship Between Training and

8 8 Usability: A Study of the Impact of Usability Testing On Improving Training and System Deployment. Stud Health Technology Information, pp Lepori, B., Coordination modes in public funding systems. Research Policy, Volume 40, pp Murmann, J. P. & Frenken, K., Towards a systematic framework for research on dominant designs, technological innovations and industrial change. Research Policy, pp Volume 35. Negro, S. O., Hekkert, M. & Alkemade, F., Why does renewable energy diffuse so slowly. Renewable and Sustainable Energy Reviews, pp Porter, M. E., The Competitive Advantage of Nations. Cambridge (Massuchusets: Harvard Business Review. Ritchey, T., Decision Support Modelling with Morphological Analysis. In: Wicked Problems - Social Messes. Berlin: Springer-Verlag, pp Shaxson, L., Is your evidence robust enough? Questions for policy makers and practitioners. Evidence and Policy, 1(1), pp Solow, R. M., A Contribution to the Theory of Economic Growth. The Quarterly Journal of Economics, pp Vol. 70, No. 1, Feb.. Sood, A. & Tellis, G. J., Technological Evolution and Radical Innovation. Journal of Marketing, pp Vol 69, July. Suh, N. P., Axiomatic Design Theory for Systems. Research in Engineering Design, pp Volume 10. Weber, K. & Rohracher, H., Legitimizing research technology and innovation policies for transformative change, combining insights from innovation systems and multi-level prespective in a comprehensive 'failures' framework. Research Policy, pp Zwicky, F., Morphology and Nomenclature of Jet Engines. Aeronautic Engineering Review.