Economic and Financial Aspects of Innovation

Chapter 9

Economic and Financial Aspects of Innovation INTRODUCTION The Issues The bulk of the existing published work on the economic aspects of innovation refers to the economic evaluation of the earlier stages of the innovation cycles, namely the research and technological development (RTD) stages.1 They also may refer to the wider impacts of RTD on the economy as a whole or within a specific geographic area or ecosystem. There is relatively very little by way of evaluation or assessment of whole innovation cycles or, even less so, of whole innovation ecosystems within a specific sector. In evaluating innovation, we basically try to measure the “value” of an individual innovation cycle or the value created by a whole innovation ecosystem in terms of the size of its potential technical, economic, and social impacts and compare it with the “costs” of producing this value. Ideally, we look not only for pure monetary benefits or costs but also for wider social and other nonmonetary impacts. The emphasis will depend on whose view point we take in making a specific evaluation; if it is the public sector’s viewpoint, benefits may primarily be measured in terms of the contribution to solving key societal problems (e.g., livability of cities, equal access, mitigation of climate change, etc.) as well as to affecting social behavior and attitudes. If it is the private sector’s viewpoint, then the evaluation is a more straight forward exercise mainly focusing on whether there is an economic net-benefit out of the specific investment or a sizeable “rate of return on investment” (ROI). If the economic ROI is satisfactory, then the investment has a measurable positive potential for the private sector and investors will be interested. Irrespective of the viewpoint taken, there is always a difficulty related to the need to “isolate” and identify the effects that relate to a specific innovation, or even group of similar innovations, before these can be measured and assessed. As the situation on the ground is usually influenced by many other factors and circumstances acting simultaneously, it is extremely difficult to isolate and measure the effects due to a particular innovation. For instance, the impacts and system feedback, which will result from the “autonomous car innovation revolution," will be the result of hundreds, if not thousands, of individual innovations from the autonomous car technology. These are the results of individual innovation cycles in many areas, ranging from optical and Lidar recognition to artificial intelligence and robotics that have been financed through combined innovation financing cycles and sources thus making it very difficult to isolate and evaluate them individually. The financial aspects of innovation are equally important to the economic ones. They refer to the methods and sources of financing innovation activities. The finances of innovation are connected to the economics of innovation in that the results of the latter are the primary input to the first. Without a sound economic evaluation of the potential of an innovation investment any financial involvement is normally not attempted. Under the existing increasingly variability of financial resources for innovation, both public and private sector financing bodies are increasingly looking to achieve solid economic justifications for their innovation investments. Some innovation ecosystems, including Silicon Valley, are experiencing an abundance of venture capital while others are struggling to assemble sufficient sources of investment capital. The key questions therefore that apply here and which we will attempt to answer in this chapter, are: How does one (innovation funding organization) find the “golden RTD nuggets,” that is, RTD results that are likely to produce successful

1. An innovation cycle has been defined, in Chapter 2, as the sequence of steps within an innovation ecosystem that lead to an innovation that enters the market as a specific marketable product. The sequence starts with basic or applied research; moves on to prototype development; then demonstrations and proof of concept; and from there, on to product development and market entry. The initial three stages are what normally constitute the RTD stages. According to the type of research product we have further distinguished process RTD, if the result is new methods or processes of performing a certain function or service and product RTD if the result is a new or improved physical, virtual, or web-based product or service. The Accelerating Transport Innovation Revolution. https://doi.org/10.1016/B978-0-12-813804-5.00009-7 © 2019 Elsevier Inc. All rights reserved.

159

160

SECTION

A Understanding Systemic Innovation

innovation (from the bulk of research reports and results, deliverables, and outputs)? Do we have the right “statutory environment” to facilitate such successful exploitation of research results? Do we provide sufficient incentives for investments beyond RTD? Is the creation of “innovation” a sound and well-formulated policy of government and private sector entities that rests on a comprehensive and permanent evaluation structure? Are there sufficiently effective evaluation methodologies for the whole spectrum of research and innovation (or RTD&I2) activities? Finally, what are the types and sources of financing for innovation? Most public and private sector RTD&I funding and governance bodies are now putting increased emphasis in answering these questions through concerted innovation evaluation efforts including post-RTD. The aim is to encourage research results utilization and its full market application. These policies are relatively new but they increasingly give rise to new institutional arrangements that facilitate the completion of the innovation cycles and also to an increased importance of innovation evaluation techniques that estimate “actual” pay-back circumstances for innovation investments. This trend is accentuated by the increasing involvement of capital finance markets in innovation funding and the increase in publicprivate innovation partnerships.

The Context of Innovation Evaluation “Innovation” has been defined as the introduction of new or significantly improved products (goods or services), processes, organizational, and marketing methods in the marketplace (OECD and EUROSTAT, 2005). In the “systems-oriented approach” of this book, an innovation ecosystem encompasses the “total flow of activities from basic and applied research to the development of prototypes and demos and subsequent market implementation” within a specific thematic area. The study of the complexity and diversity of innovation processes is a critical conceptual step in understanding how to assess such an ecosystem starting with all its possible inputs and outputs. As already said, most of the existing literature investigating such inputs and outputs concerns the evaluation of the research and development stages. In the following section, we will discuss the case for expanding such input/output analysis to the innovation ecosystem level while reviewing also the RTD stage evaluation methodologies and techniques used. One basic problem in expanding evaluation to the post-RTD stages is data availability and measurement especially for the outputs of the later stages of the innovation cycles. The issues related to this problem are thoroughly examined in Chapter 7. Another problem is the different perspective with which innovation investors see the pre- and the post-RTD stage within the innovation cycle continuum. A private sector industrial, commercial, or consulting company investing its own funds to produce and implement its own RTD results may accept a lower or even zero ROI because it may aim to appropriate the returns of its RTD investment through, for example, intellectual property protection or subsidies or tax incentives, etc. Rather than profit in monetary terms, such self-investing companies are motivated by the goal of establishing a market or similar intangibles. There are, however, also many private sector companies that are reluctant to invest in RTD based on the above arguments and prefer to utilize the knowledge and innovation produced by others.3 Another reason that is cited by private companies to not invest in RTD is the “leakiness” of the global innovation system, that is, the trend to have innovations copied even though they may be protected by IPR. In spite of this argument, there are many examples of large international firms that have willingly invested in innovation (i.e., post-RTD stages) in order to secure entrance into international markets despite the “leakiness” of the global innovation system. The alleged leakiness of the innovation system in China, for instance, has not deterred Apple and Google from making large-scale investments. In any case, for post-RTD activities the justification of the investment has almost always to be made on a tangible basis, that is, with calculation of a tangible ROI (which, the bigger it is the better). The reason is that these stages are usually funded by private investors who do not have a direct interest or involvement in the actual innovation being produced and see the whole operation as a case of successful (or unsuccessful) placing of their funds in order to make a profit. Therefore, the result of the post-RTD evaluation can be critical, as they may make it difficult or economically not worth it to finance the final stages of innovation. This is an aspect differentiating RTD investment assessment from whole-(innovation)-cycle investment assessment.4 2. Research Technological Development and Innovation. 3. However, according to survey evidence on the value of RTD results produced by another firm, the use of such results by manufacturing firms is not “free” but could cost as much as 50%–75% of the cost of the original invention (Levin et al., 1987; Mansfield et al., 1981). This result may induce firms back to financing their own original RTD but does not eliminate the overall incentive and justification for public investment in RTD and subsequent innovation creation. 4. For a more thorough discussion of this argument, see also Hall and Lerner (2009).

Economic and Financial Aspects of Innovation Chapter

9

161

For publicly funded RTD and/or innovation production, the above issues still apply but there, almost invariably, the evaluation will expand to consider nonmonetary outputs such as, for example, creation of new knowledge, societal equity and well-being, national security benefits, and so on. However, to the extent that “knowledge” and other intangible outputs cannot be kept secret and they disseminate freely (i.e., without “monetary returns”), even the public investment in innovation may not be easily justified simply through knowledge production and other intangibles. It will also require some evidence of monetary benefits especially if it is a mixed public-private sector investment. We will discuss the above issues under the basic distinction of public vs private sector innovation investment although the limits between the two can be blurred. As a basic rule, pure public sector funding of RTD is usually the case for basic research intended to expand knowledge in new frontiers and without visible market-related applications, while private sector funding is more for applied research focusing on a specific areas of business interest to the funding organization. There are of course many mixed cases of public or private sector funding so in the following when we refer to “public” or “private” sector innovation, we mean innovation cycles that are predominantly supported by the public or the private sector in the sense of funding, governing, or supporting.

Methodological Issues in the Literature For the initial RTD stages, there are several evaluation methodologies and theoretical frames that have been proposed and tested in the existing literature. Summary reviews of this literature can be found in Hall and Rosenberg (2010), Hall and Lerner (2009), and Salter and Martin (2001). In Hall and Rosenberg (2010), there is a large literature review from the past 50 years of economic research and the results are given in a number of interesting tables. From these tables, it becomes evident that the main issue investigated over the past 50 years or so, is the (private or public) rate of return of the investment devoted to RTD. Other issues considered are investigations of the indirect impacts of RTD investment (e.g., to the society as a whole) and the spillovers to other sectors or regions. As we cannot present here, in any detail all these results, the interested reader is referred to the above publications and also to Annex 4 where we give a brief summary of some of these findings. For the post-RTD stages of the innovation cycle, there are few evaluation examples that can be found in the literature. Among them, worth mentioning are the papers that originate from data gathered in the Community Innovation Surveys (CIS) that were mentioned in Chapter 7. The CIS surveys follow the general guidelines of the Oslo Manual (OECD and EUROSTAT, 2005) and take place regularly in many countries. Perhaps the most comprehensive CISs are the ones carried out every 2 years in the countries of the so-called European Social Survey—ESS (Eurostat, 2016). The EU-member countries’ CIS refer mainly to innovation activities in enterprises and the private sector. It provides statistics broken down by country, type of innovator, economic activity, and firm size. These have been used as the main source of data to calculate the “innovativeness” of various economic sectors by the type of enterprise and also to perform econometric analyses for the value of innovation as a whole, see, for example, Mairesse et al. (2005) and Mairesse and Mohnen (2004, 2010). In the transport sector, a recent study conducted by the Institute for Prospective Technological Studies (IPTS) of the Joint Research Center (JRC) of the European Commission (EC) can be considered as an attempt to evaluate and assess the full-innovation cycle as it tries to assess the whole spectrum of public or privately funded “research and innovation” activities in the transport sector in Europe (Wiesenthal et al., 2015). It is basically an analysis of data from the EU’s Industrial RTD Investment Scoreboard for all transport subsectors (road, rail, maritime, and air). These data are further complemented by information obtained through a systematic research of company annual reports. In 2012, the EC published a guidance document (titled “Evaluation of Innovation Activities: Guidance on methods and practices”) on the methods and practices for the evaluation of innovation activities (European Commission, 2012). This document can provide a valuable reference for innovation ecosystems evaluation as it contains guidelines for the evaluation of a number of innovation ecosystem elements and innovation by type. It contains information and methodologies for analysis in the following areas: l l l

l

l l

The innovation activities by type. The (innovation) intervention logic and expected results. An overview of the main evaluation questions and indicators that can be used (these are linked to the intervention logic and objective). How to design and manage an evaluation for a specific type of intervention, according to the focus of the evaluation (relevance, value for money, results, and impacts). The main methods that can be used for the evaluation (their pros and cons as well as possible alternatives). A summary of key “pointers” to keep in mind during the evaluation.

162

SECTION

A Understanding Systemic Innovation

While there cannot be a one-size-fits-all innovation ecosystem evaluation methodology, we can draw on the lessons from the existing RTD evaluation experience as well as on the findings of the previous chapters and the case studies of this book and based on the ecosystems theory viewpoint put forward some basic elements of an “innovation ecosystem evaluation” methodology. The context under which we will consider these issues will be at the basic methodological level with emphasis to the factors and elements that need to be considered and the critical causative factors or elements that are involved. Such context is probably the only feasible one, given that our main purpose in this book is to give the correct perspective of innovation ecosystem evaluation and not to dwell excessively in technical detail. This task is left for more “vertically” specialized publications.

RTD Evaluation Methodologies Classification of Innovation Ecosystems for Evaluation The innovation ecosystem that is to be evaluated will first need to be delineated with regard to the following three basic characteristics: A. Focus area; this is defined by the scientific field(s) of its focus and specialization, the type and extent of cooperation between its research and development stakeholders, and the type of activities that take place in it (e.g., research and prototype development or light manufacturing and production, education and training, services, etc.). B. Scope; this refers to the “size” and (expected or estimated) area of influence. It is defined by items such as the geographic area of application or influence for its products or services, the number of scientific or business sectors it involves, the number and types of infrastructures it includes, the number of stakeholders involved, and the extent of its “portfolio” of services (e.g., whether it includes incubator, mentoring, and other types of such services for its members). C. Type of impacts; these will need to be delineated in a general sense, that is, as types of expected impacts, for example, impacts on travel times, on travel behavior, or sales of products. Their full definition and measurement will of course require a thorough analysis of the market, the ecosystem itself, the type of innovation product or service, etc. It will also take data and surveys in order to be quantified. These impacts are rarely constrained by geographical barriers and invariably include “spillovers” into other fields. Correspondingly, “spill-ins” from other regions, or scientific areas, may form “inputs” to the ecosystem under evaluation and affect short- and long-term outcomes. According to the focus area, the scope, and the type of expected impacts, an innovation ecosystem evaluation methodology will have to be formulated depending also on the type and characteristics of the particular innovation ecosystem considered. As already mentioned, the nearest we have to such (ecosystem based) methodology, on which one could fit a dedicated—so to speak—innovation ecosystem evaluation methodology, are the evaluation studies performed for the RTD stages of innovation. There are a number of levels of consideration of RTD activities to which these RTD evaluation studies refer. We follow here the levels of consideration in the recent EC publication mentioned in the previous section5: 1. Individual or groups of related applied RTD projects within a specific scientific area: A research project is performed by science-industry or industry-industry consortia working together to fulfill the requirements of a specific research contract. A group of related RTD projects consists of one or more well focused and interrelated RTD projects. This is the “traditional” case of research project level evaluation. 2. Strategic research and innovation programs: These are complete programs of research based on well integrated and interrelated work plans serving specific strategic aims and objectives and involving several scientific areas or “strings” of research and innovation promotion work. 3. Overall national RTD and innovation environment: This case refers to the evaluation of the overall national environment for research and innovation (that includes all active innovation ecosystems), that is, all RTD and related infrastructures, the relevant legal and administrative frameworks, relevant policies and services provided, the advisory services, the organizational and management arrangements, the technology-transfer and training actions, and the legal requirements of subnational jurisdictions.6 5. The “innovation evaluation manual” of the EC (European Commission, 2012). 6. For example, many American states have allowed stringent noncompete clauses that constrain mobility. One of posited reasons why Silicon Valley has flourished is that the State of California has long opposed the broad use of noncompete clauses thereby facilitating technical mobility with Silicon Valley and between Silicon Valley and other innovation ecosystems in California and across the United States.

Economic and Financial Aspects of Innovation Chapter

9

163

4. Specific innovation financing cases or services: For example, innovation financing mechanisms such as an innovation grant or loan provision program, loan guarantees or interest rates financing, equity finance via venture capital (VC) or similar and other similar types of financing actions. 5. Innovation clusters: This is the case of special groupings between industrial, research, consulting, and other types of entities which form a “cluster” aimed to develop and promote innovation in a specific field, by use of all possible means and instruments. As it is evident from the above classification the more global is our level of consideration (e.g., from item (3) down, in the above list), the closer we are at the “ecosystem” concept level. We present below, a summary of the evaluation methodologies that have been used in the past for each of the above categories, pointing out—wherever possible—to their possible extensions for innovation ecosystem evaluations.

Individual, Applied RTD Projects, or Groups of Projects This type of evaluation is the one extensively referred to in the traditional RTD evaluation literature. It is typically based on econometric modeling techniques utilizing as a tool “production functions” where the “outputs” of one (or more similar) RTD projects are related to their “inputs.” Two approaches can be followed here: a. the primal approach, which estimates a production function with quantities as inputs or outputs, and b. The dual approach, which estimates the inputs and outputs by using a dual (quantitative and qualitative) approach. In both cases a system of factor demand7 equations is derived by using as “production factors” (input) resources such as— labor, capital, land, and entrepreneurship (expressed as “units,” e.g., wage rate, rental rate, etc.). The equations link these unit production factors to the level of output also expressed by factors such as sales, no. of patents, publications, etc. The willingness and ability of productive activities to hire or employ factors of production comprise the “factor demand.” In practice, both quantitative and qualitative units can be used to estimate the inputs and the outputs, that is, tangible or nontangible results of the project(s). Their identification usually entails a combination of desk research and questionnaire surveys suitably adapted to the specific nature and extent of the project(s) evaluated. The desk research part may be used to identify and clarify, mostly, the “inputs” in the form of singular or overlapping monetary or nonmonetary inputs such as the funds that were used, or some expression (nonmonetary) for the research infrastructures, or the knowledge imported from other research ecosystems. The survey part may consist of interviews with a sample of related stakeholders to locate, define, and gauge the relevant “outputs.” The questionnaire survey can also be used to identify whether the system resulted in transformational or incremental innovation, how these have affected the legacy systems, how far have the impacts been felt in the economy of the region, etc. The formulation of the questionnaire is of course the most delicate and fundamental part of this type of evaluation exercise. In its simplest form, the stakeholders are asked to provide information on their scientific papers and other outputs arising from their funded research. A more sophisticated questionnaire methodology would try to assess whether and in what ways their innovation producing work has been improved as a result of the specific funding, whether the input received has contributed to specific societal benefits with respect to a potential social network analysis, as well as broader issues such as whether they can consider and qualify the wider strategic impacts of the research, or whether the geographic area in which the work has been performed has benefited from wider geopolitical benefits and so on (European Commission, 2012). Another approach in such evaluations would be that of using a “peer review” methodology, that is, interviews by an expert panel. Typically, such panel will contain a proportion of “external” experts who are able to provide benchmark experience with comparator organizations or projects. The “Case Study” approach, can also be useful in providing a more detailed view of the activities undertaken, and comparing them with a suitable example from another research program, or country. If it is not easy to identify a suitable example to compare against, then the results may have to be compared directly with the initial goals and conditions set for the specific system examined. The use of specific indicators may also be helpful in expressing and assessing the results of the project (s) being evaluated.

7. Expressing the range of factor quantities that are demanded at a range of factor prices. For more details see Hall and Lerner (2009) and Hall and Rosenberg (2010).

164

SECTION

A Understanding Systemic Innovation

Strategic Research and Innovation Programs These are whole programs of research work—usually publicly funded—in which national governments or international ones (e.g., the EU) put forth calls of tender for several “strings” of research work to address specific societal “challenges.” The EU’s overall Research Framework Programs (FPs) (like the Horizon 2020) or the US government’s Strategic Highway Research Program (SHRP 2) or the National Cooperative Highway Research Program of the US/TRB, are typical examples of this case. Evaluations of the results of such programs are made regularly by the relevant funding authorities either before (ex ante) or in the middle (mid-term) or after the end of their life (ex post). Typically, mid-term evaluations are the most often performed evaluations of such programs simply because their results may help correct potential failures. There are several evaluation methodologies and approaches that have been used for this type of evaluation. The interested reader is referred to references such as US National Science Board (2012), Georghiou (2015), US/DoT/FHWA (2017), and European Commission (2017a,b). The traditional method is to try and calculate the ratio between the outputs of the specific program and its inputs. Typical outputs that have been used, include (see also next section): market value of the new products and services produced (for the whole evaluation period considered), number of cited papers, number of start-up companies produced, number of patents produced, number of doctoral students graduating, new employment in terms of the number of people employed due to the program, etc. Typical inputs may include monetary and nonmonetary inputs. The monetary inputs can be either a wholesome calculation of the investment absorbed by the program activities or a more detailed account of monetary inputs such as eligible costs for the various research projects in the program. The nonmonetary inputs may include spillovers from other programs, various incentives given, use of previously existing research infrastructures, etc. Data may come from regularly collected (monitoring) data or through planned surveys. This type of analysis will ultimately aim to define and measure the comparative efficiency of the evaluated program in terms of specific key performance indicators (KPIs). A most notable practice for evaluating national research and innovation production programs is the Value for Money Reviews that are conducted in Ireland. These reviews are conducted regularly by the government of Ireland to evaluate various RTD governmental funding programs in various fields. They are conducted under the supervision of the government department that oversees the specific program and the Department of Public Expenditure. In the case of general research, development, and innovation, the relevant government department that conducts the relevant reviews is the Science Foundation Ireland (SFI).8 Another interesting factor in the Irish system, the fact that the Science Foundation of Ireland has established for this innovation evaluation exercise, is a permanent system for collecting data on inputs and short- and long-term outputs of its annual strategic RTD&I programs. The permanent data that are collected include: bibliometric data, implementation monitoring data, surveys of beneficiaries and nonbeneficiaries, and case studies. The methodologies followed in the Irish “value for money reviews” and data collection can form a useful example on which a potential innovation ecosystem evaluation methodology can be based.

The National RTD&I Environment The overall national innovation promoting environment, that is, the one that supports all innovation ecosystems of a country includes the policies that are in place to support research and innovation, the governance structures, the data collection, the monitoring and controlling functions, the financing mechanisms and sources, and the infrastructures that exist to support research and innovation. The types of evaluation that are performed in this context differ from those considered previously, mainly on the number and type of impacts considered. The main difference lies in the fact that in this type of evaluations due account should be taken also of the noneconomic impacts such as system effects, behavioral changes, environmental impacts, etc. The methods used can be analytical—largely based on econometric modeling—as well as more qualitative, based on surveys (questionnaires or interviews) among the main stakeholders and program participants, or based on before-after comparisons. Especially helpful are the so-called “beneficiary surveys,” which aim at measuring changes in the behavior and attitudes of the various beneficiaries of the system. More sophisticated methodologies, such as Control Group Approaches or Social Network Analysis (SNA), have also been tried.9 Particular reference must be made here of the overall national research and innovation environment evaluation of the government of Austria. This country’s experience presents a model case of a country that started relatively lately but within 8. The interested reader can find more data and information on these evaluations, at: https://www.education.ie/en/Publications/Value-For-MoneyReviews/ (Accessed May 2018). 9. A good account at these evaluation methods and practices can be found in INNO-Appraisal project (2010).

Economic and Financial Aspects of Innovation Chapter

9

165

a short period of time has developed a solid and sophisticated research, technology, and innovation evaluation culture that is among the comprehensive in the world. It has, to our view, succeeded in becoming one of the leading European countries in such evaluations. Of pivotal role in this development was the foundation, in 1996, of the organization Platform Research and Technology Policy Evaluation (FTEVAL). This organization has worked systematically toward encouraging better and more transparent qualitative evaluations of all research and innovation activities as well as of relevant national policies in Austria. The FTEVAL uses an institutionalized network of analysts, policy makers, and program managers in the field of RTD policy and conducts regularly national level RTD&I evaluations (FTEVAL, 2007; Dinges and Schmidmayer, 2010).10 A similar example of national RTD&I system evaluation, but not performed on a permanent basis, is the one performed on behalf of the Israeli government in 2007–08 (Lach et al., 2008). For many years the Israeli government has allocated resources in building a national innovation supporting environment (see also our case study on Israel). In 2007, it assigned a study in order to conduct a national innovation evaluation to quantify how the country’s GDP was affected by the existence and operation of its national innovation environment and its related public financial support (which for the 10-year period, 1997–2007, totaled more than $1 billion). The study, conducted in 2007–08, calculated the marginal rate of return for the (national) investment and at the same time answered the question whether public funding had a multiplier effect, that is, whether it has led firms to invest more in RTD than originally planned. The methodology used was one based on a combination of qualitative (through interviews and questionnaire surveys) as well as quantitative approaches. The study made an estimate of the impacts of public research and innovation funding but maybe of more interest here are two of its suggestions as follows: (a) there are some barriers to using a fully quantitative econometric approach to such types of (national) innovation environment evaluations and (b) that such effort requires a long-term focus on collecting data over long periods of time.11 Finally, of interest is also the national innovation evaluation tool developed by the World Bank’s WBI/KAM.12 This is a “tool” that consists of a set of 76 structural variables that benchmark how an economy compares with its neighbors— competitors or countries that it wishes to emulate. It provides a quick guide to comparative evaluations between different national innovation systems (World Bank, 2004; Aubert, 2005). The data repositories and data banks used have been considered in more detail, in Chapter 7.

Specific Innovation Financing Cases or Services Evaluating specific innovation investments, for example, by a public or private funding agency for a specific project, is perhaps the easiest and most straightforward form of innovation evaluation. It refers to activities and impacts that can be well delineated, easy to quantify, and involves relatively straightforward data collection for the “inputs” and “outputs” involved. The methodologies used vary depending on whether it is public funding (usually direct funding from the national budget, or from governmental organizations and agencies) or private funding such as VC, bank loans, crowdsourcing capital, and so on. The usual practice is to use an econometric approach using a standard production function based methodology. The production function is related to the notion of “productivity.” Productivity can be defined as the ratio of an “output” to the “input” that produced it and is usually expressed by the Total Factor Productivity, or TFP, concept. In a typical TFP, an “input” normally consists of labor and capital resources while “outputs” can be increase of productivity and business efficiency (growth accounting) as well as other wider societal or environmental impacts. Relative to these concepts, “technological frontier analysis” is an additional tool that has been used to measure the technology gaps that exist, relative to a “frontier” whose estimation is based on efficiency (Perelman, 1995).13 For the transport sector, total factor productivity (TFP) using technological frontier analysis is a promising technique to reflect the impacts of innovation. The use of production functions depicting the “production” of a firm receiving innovation funding from a particular innovation financing entity (or entities) and expressing it as a function of the inputs used requires an efficient process 10. More info at: https://www.fteval.at/content/home/plattform/about/ (Accessed May 2018). 11. It also noted that very sophisticated procedures and methodologies, if used for such evaluation analyses, are not always easy for policy makers to understand and therefore may fail to convince them to adopt their findings! 12. World Bank Institute/Knowledge Assessment Methodology. 13. The idea is to estimate a “frontier” (or best practice) production functions instead of average production functions in order to decompose productivity growth into movements of the frontier and toward the frontier and then to regress the estimated changes in these two components on, among other things, RTD or innovation. The estimation of the frontier or best practice can be achieved from a cost function or from a production function—see also Hall and Lerner (2009) and Hall and Rosenberg (2010).

166

SECTION

A Understanding Systemic Innovation

of defining the “inputs” and “outputs.” These issues are discussed in detail in the following section, but the interested reader can also refer to more specialized publications such as Griliches (1979, 1998), Blundell and Bond (2000), and Hall and Rosenberg (2010).

Innovation Clusters “Innovation clusters” are the groups of industrial, research, consulting and/or other types of innovation-related entities that join forces to develop and promote innovation in a specific field. In evaluating innovation clusters it is often that a peerreview methodology is useful. The peer review is usually conducted by well-respected panels including international experts and potential end users. Such panels will gather or receive evidence and data on the output and other indicators and will conduct interviews with key stakeholders of the cluster in order to pose specific questions regarding their own views and assessments. A less direct review may be accomplished through a benchmarking exercise aimed at comparing the specific cluster funding program in question to similar programs internationally. Related input and output data can also be analyzed for all of the participating “beneficiary” firms and entities in the cluster and also benchmarked against those for nonparticipants or other regions. This approach, however, requires a broad, accurate, and complete data that is not always available. Moreover, the analysis of monitoring data and surveys can trace the changes and trends in input–output parameters and collaboration patterns, but not necessarily explain them. An analysis of company (or whole sector) stock trends over time is also a way of evaluating the performance of companies (or sectors) within innovation clusters. Precipitous drops in the value of a company’s stocks (or companies with the same or similar technological orientation) can be useful indicators of a company experiencing a short- or long-term downturn that invariably affects its ability to innovate or move innovations into the market place.

Time Lags and Spillovers The inclusion of time lags and spillover effects in innovation evaluation is probably the most complex and cumbersome task. Time lags are the time periods that should be allowed for before we can be certain that the system impacts have properly emerged and stabilized. Spillovers—a form of feedback—are the indirect impacts on other firms or parts of the society from the diffusion of the new technologies or services resulting from the innovation under evaluation. “Spillovers” can also be the impacts into other ecosystems, market sectors, outlying geographic regions or the secondary indirect impacts that can emerge by technological complementarities or rivalries that can emerge in the target markets because of the outputs of the innovation system under consideration. We have considered the potential spillover effects of innovation in the transport sector in more detail in Chapter 6. Taking into account time lags and spillovers will influence the end results of an evaluation because, depending on the particular rate of depreciation that is used in the calculation of the rates of return for the total “innovation stock,” they will affect the overall balance of “inputs” and “outputs” of the system. The different outcomes of an innovation ecosystem are subject to varying time lags and different routes to materialization. New products or services may take different “routes” and time durations until they become commercially exploited and established in the market. During these times the effects on business performance may not be so clear or accurate as it can take several business cycles for them to emerge. There may, for example, be several startups within the ecosystem that is studied may go bankrupt after the initial period of their formation. This does not necessarily mean that the evaluator should conclude that the innovation ecosystem has failed. The overall true picture of the impacts may need some more time to emerge and thus allowing for considerable time lags in which to study the potential effects is necessary. Such time lags are needed to allow the system to stabilize in the sense that new more successful start-ups may develop or the people, who worked in the failed start-ups, may yet benefit the regional economy in the long term. Moreover, the impact of an innovation support measure may result from one or only a few highly successful projects within the “ecosystem” considered and this “skewed” effect also needs to be considered in applying the evaluation methodology to be followed. To take these “multiple” impacts into account is actually a major difficulty in innovation evaluation. It entails separating the effect of the specific innovation activity being evaluated from other (external) factors that may have an influence on it. This may require the “triangulation” of evidence through a mix of evaluation methods. The determination of the appropriate time lags within which the impacts of the innovation ecosystem will be considered, has been attempted in the literature (Leonard, 1971; Hall and Rosenberg, 2010; European Commission, 2012).14 Indicatively, we can mention here that (Leonard, 1971), the effect of RTD on (economic) growth is estimated to begin on average in the second year after the initial RTD investment and continues with steadily rising influence for at least 9 years after its 14. It is reminded that these studies refer to RTD projects rather than “innovation” as a whole. This may have resulted in shorter time-lag periods.

Economic and Financial Aspects of Innovation Chapter

9

167

end. In Hall and Rosenberg (2010) we find reference to survey responses about estimated time lags for research project results. In them, 45% of the survey respondents reported a typical time lag between the beginning of RTD and the first introduction of a new product of 1–2 years, 40% reported a lag between 2 and 5 years, and 5% a lag of more than 5 years. In European Commission (2012), mention is made to the need to take long time horizons when evaluating innovation programs as the establishment of a critical mass of researchers and research activities that precede the innovation may take several years and cycles of funding before they materialize (including spillovers with other types of innovation measures).15 By also considering the spillover effects, even longer time lag periods may have to be considered. The usually lengthy periods in which an initial RTD investment may (or may not) produce “innovation,” that is, the time between the initial RTD investment and the appearance of a commercial product in the market can be a major disincentive for a firm’s initial RTD investment. However, in the mega-innovator companies such as Samsung, Google, Microsoft, Apple, etc., the internal resources available enable these firms to take the long-term view while continuing to generate significant profits. Also, as research budgets are generally reduced, many firms use their researchers not to produce indigenous innovation but rather to assimilate generic technologies from external sources (inward spillovers). Even in highly competitive industries, some companies seem to focus their efforts on reducing costs or targeting niche markets, while taking advantage of the innovations that emerge from the RTD of others.16 Again, the strategy followed is largely dependent on the internal financial resources available as well as the ease of access to external capital markets. Taking into account the spillover effects in an evaluation will involve estimation of the impacts to other firms or the society as a whole from the diffusion of the evaluated innovation to a wider economic or geographical space or innovation ecosystems. Pecuniary spillovers occur when the new or improved goods or services are sold to other firms at prices that reflect less than the full value-added they incorporate. By contrast, nonpecuniary spillovers are those that come from the “knowledge” created as it disseminates and becomes useful to other entities. Conversely, we will need to estimate and assess the impacts of “spill-ins,” that is, impacts of innovations that migrate to the particular ecosystem under study from other sectors.17 Considering the transport sector, the spillover effects of a specific innovation or innovation ecosystem were addressed in more detail in Chapter 6 where a number of sectors with a two-directional spillover/spill-in relation to the transport sector, were discussed. These sectors included: l l l l l l l

Information technology Telecommunications Energy Materials Tourism Agriculture Logistics, warehousing, and supply chain management

INNOVATION EVALUATION INPUTS AND OUTPUTS As already mentioned earlier, most of the existing methodologies for evaluating RTD (and to some degree innovation in general) rely on productivity functions that relate “inputs” to “outputs” for the specific RTD or innovation item being evaluated. The inputs usually consist of the total capital investments (including the innovation funding received), material purchases, workforce used, etc. The outputs may be expressed in terms of increased productivity, value added, market value of products produced, and the value of potential spillovers. Below, we duel in more detail in the inputs and outputs that can usefully be used in an innovation evaluation.

The “Inputs” Innovation evaluation “inputs” will primarily consist of the following two categories: 1. RTD expenditures, that is, the actual (or estimated) total funding for the relevant research and development work performed within the innovation cycle—or total ecosystem—under study (public and private sector costs) within the time period considered. 15. See especially, Fig. 6 of European Commission (2012). 16. See, for example, Tassey (2010, 2013). 17. See also Jaffe (1986).

168

SECTION

A Understanding Systemic Innovation

2. Innovation production costs, that is, the total costs for the after-RTD activities (public and private sector) that will lead to the final market product. These may consist of: a. labor costs; b. capital costs for the invested capital (e.g., from bank loans, venture financing, crowdsourcing, angel funding, etc.); c. material costs (for any relevant material purchases in these subsequent stages); d. other related costs (e.g., for patents issuance, initial publicity, legal costs, etc.). A number of data bases and repositories are being or have been developed, mainly in Europe and the United States, which can help estimate such “inputs.” Examples of databases that can be used for this purpose are the databases: StarMetrics in the United States—Research Excellence Framework (REF) in the United Kingdom—TRIMIS in the EU, which are described in more detail in Chapter 6. For the evaluation of a specific innovation ecosystem element (e.g., an innovation zone), useful input data can also be gathered by focused audits examining the quantity, quality, and current value of all relevant assets that have been used for the creation of the given ecosystem element over the time period considered. These audits must be focused and related to the innovation ecosystem being studied and the specific categories of “input” items. At the same time they can compare systematically the available technological and financial inputs, appraise the strengths and weaknesses of the supporting structures, evaluate the research and educational infrastructures used, and perform a number of other evaluation tasks. There is, so far, little experience in these types of audits. For this reason, they should be carefully designed for the specific system under consideration and performed by well experienced and “respected” bodies (preferably linked to central level administrative and judiciary authorities). These audits should ideally be conceived as a permanent process with clearly defined follow-on actions and repeated from time to time. “Inputs” to an innovation ecosystem can also be represented by a number of “indicators.” The values of these indicators will have to be defined for the specific innovation ecosystem over a specified time period by data collection from existing sources or through dedicated surveys. Examples of such “input” indicators are: l l l l l l l l l l l l l l l l

number of researchers involved in the ecosystem’s RTD; researchers in ecosystem RTD, per million population; number of university-company research collaborations; percentage of business-own RTD vs third party; total number of relevant patent applications; total expenditure for the ecosystem’s RTD18; total expenditure for the ecosystem’s RTD as % of GNP or GRP19; total public sector expenditure for ecosystem RTD; total private sector expenditure for ecosystem RTD; gross foreign direct investment (all sectors) as % of GNP or GRP; royalty and license fees payments; royalty and license fees payments/mil. population; total bank loans for ecosystem start-ups (after the RTD stage); total venture capital investments for ecosystem start-ups (after the RTD stage); total capitalization of ecosystem start-ups; total value of initial public offerings (IPOs) for companies in the ecosystem considered.

There is also the possibility to identify appropriate “proxy” variables, that is, variables that express general levels or conditions by nonquantifiable measures, for example, in a scale of low-medium-high or agree not-agree scales, etc. Examples of such proxy variables are: l l l l l

capacity of retention of educated workforces (low-medium-high); rates of creation or growth of new firms; degree of availability of venture capital; level of bureaucracy (difficulty of doing business with the government or the public sector); administration burden for start-ups, and so on.

18. Since RTD expenditures are composed of labor, capital, and material costs, care must be taken so they are not counted twice, when measuring the other (after RTD) cost inputs. 19. Gross national product or gross regional product (i.e., for the region or regions of reference of the ecosystem under study).

Economic and Financial Aspects of Innovation Chapter

9

169

For some low income/low innovation-profile countries, some of the above data categories may not exist or be relevant. Perhaps, in such cases one might rely on some general capture data (real or proxies), for example, on education levels, number of researchers, know-how transfer opportunities, newly created enterprises, etc. Three issues regarding the correct way to measure the “inputs” are relevant here20: a. the RTD double-counting issue; b. the potential bias in the estimated returns (outputs); and c. the sensitivity to corrections for quality differences in labor and capital utilization in the situations before and after the innovation.

The “Outputs” In its simplest most tangible form an “output” or “return,” in the context of an innovation cycle or ecosystem, is the economic “rewards” to a company from an innovation which it has introduced in the market. Such rewards are usually the drivers that incentivize it to finance the necessary initial RTD and/or the subsequent innovation production activities. The larger the company, the stronger the drive is for economic rewards because of the nature of large companies’ ownership and management. Besides the “economic rewards” (profit, sales, royalties, etc.) other innovation activity “outputs” may include: l l l l l

achieving better competitive position in the market; creation of new “knowledge” and “know-how”; spillover effects to other sectors; various societal impacts; user behavioral changes, and so on.

In practice, estimating the final “outcome” of an innovation process is a complex issue as these outputs are usually the product of a complex web of interactions between the innovating firm’s strategy, the competitors’ strategies, the prevailing macroeconomic environment, and others. Some of these outputs are stochastic in nature and may be quite difficult to predict at the time when a firm decides to invest in an RTD program with a view to innovate. This can be a strong dissuading factor for a firm’s initial investment decision in innovation. The escalating commitment by multinational corporations to capital liquidity has also dangerously reduced their willingness to invest in transformative innovations, thereby curtailing productivity and perpetuating slow economic growth (Erixon and Weigel, 2016).21 This trend is accentuated by the difficulties to produce ex ante estimates of an RTD investment and by the fact that even ex post results are not particularly stable over time or across sectors or countries. Furthermore, the so-called social impacts are rather intangible and cannot be easily tied to a specific innovation and its “inputs.” Innovation outputs can also differ depending on whether one considers private sector or public sector innovation. In the second case, the outputs considered are more widespread including wider social returns and thus are more difficult to quantify.22 Private sector innovation outputs are more specific and susceptible to quantification and thus can be used more easily in an economic evaluation analysis through traditional econometric modeling techniques. They typically include: a. “Gross output.” This is the gross value of the combined innovation output in terms of output-related labor and materials throughout the whole process of producing the “innovation” (prototypes and final products).23 b. “Value added.” In the context of an innovation ecosystem “value added” is the value that is installed in its products from the combined use of labor and capital to obtain marketable value. As “value-added” can be defined as the value of gross output less the value of inputs such as RTD costs, labor, materials, and infrastructures.

20. These issues are discussed in detail in Hall and Rosenberg (2010). The interested reader can also find more discussion and other relevant issues in Hall and Lerner (2009), Mairesse and Mohnen (2010), and Mairesse et al. (2005). 21. This is why firms like Apple, Microsoft, HP and others are committed to incremental enhancements of their products (e.g., the iPhone). Incremental enhancements to the iPhone have so far guaranteed less risk, higher immediate profits, and happy stockholders. Likewise, Microsoft works on incremental enhancements to its operating system and its suite of tools. 22. They are also quite asymmetric among areas, trading partners, and industries. 23. In doing so, special care must be taken to avoid double counting, for example, as would be the case of labor and materials that were used both for the initial RTD and the later stage innovation production.

170

SECTION

A Understanding Systemic Innovation

c. “Sales.” This is the most straightforward concept of “output” and is defined as the total value of sales of the produced goods or services over the period of time considered. A proper definition of “sales” according to economic theory would be the value of gross output less increases in inventories of finished goods. According to the US National Science Board, the “outputs” of publicly funded innovation (including the initial RTD part) range from the creation of new knowledge to the development of new skills or leveraging private RTD investments that would otherwise not be carried out. More details can be found in US National Science Board (2012). For public sector innovation, a useful definition of “outputs” can be found in the UK’s —REF which defines research and innovation “output” or “impact” as “an effect on, change or benefit to, the economy, society, culture, public policy or services, health, the environment or quality of life, beyond academia.” A series of case studies within the UK’s REF, in order to carry out meta-analyses on some 7000 cases of publicly funded research, may give valuable insights for government financed RTD outputs. Also for publicly funded research and innovation, the EC has defined a number of potential wider social impacts. It is of interest to summarize here these, expected, social impacts as follows24: 1. Skills development. This is seen as a mechanism for the transfer of knowledge from public research to companies, especially when this knowledge is embodied in the researcher that carries out the specific research. More precisely, one of the wider economic benefits from publicly funded basic research is associated with the ability of a scientist to migrate into the commercial sector of the innovation system. The benefits are notably associated not only with applying the latest theoretical knowledge accruing from scientific research but rather, through scientists transferring elements of problem-solving strategies that are fundamental in basic research. 2. Generation of new knowledge. This is the knowledge that results in a number of novel tools and ideas that are made available in the economy and that can support new or improved technologies, new products, services, and improved processes that generate more value-added knowledge. 3. New scientific instruments and methodologies. This includes new instruments and methodologies to resolve specific problems or, also, new scientific instruments that are necessary to advance research and innovation in a specific field. These can be incorporated in new products and processes and can be developed in collaboration with the users of such facilities or processes. 4. Increase of entrepreneurship through the creation of new products and companies. Increased entrepreneurship accruing from publicly funded research has been widely acknowledged as one of the key “public” benefits accruing from innovation production (public or privately funded). As the academics and new researchers and scientists involved in RTD&I are increasingly involved in the creation of new companies and high-technology firms and creating spinoffs, entrepreneurship in general is on the rise with multiplier effects in the economy. 5. Creation of networks with private researchers and users. This includes creating networks between public and private researchers and institutions to spur innovation of collaborative research, or contracting research and consulting as well as creating informal relationships between university, research, and business entities. These networking “outputs” that involve academic engagement and commercialization of publicly funded research can further be used by the private sector in order to develop further innovation (Perkman et al., 2013). 6. Leveraging of private sector RTD&I activities. The public funding of research and innovation activities25 enables, in many cases, the “leveraging” of private sector RTD&I, that is, the carrying out of innovation activities by the private sector that would otherwise not be carried out. Several studies have shown the positive impacts of leveraging, but as mentioned in the next section there is also some recent evidence from OECD26 countries that this is not always the case. Similar to our approach to inputs, the outputs of an innovation cycle or innovation ecosystem can also be represented by use of “indicators.” The values of these indicators will have to be defined, for the specific innovation ecosystem, over the specified time period, by data collection from existing sources or through dedicated surveys. Such “output indicators” include27:

l

economic increases in labor productivity; reignited economic growth in stagnating economies; number of patent applications granted (number of patents gained for the innovation ecosystem under consideration); number of relevant scientific and technical journal articles published;

24. 25. 26. 27.

See also European Commission (2017b), Georghiou (2015), Salter and Martin (2001), and Van Roy et al. (2015). Including incentives setting such as RTD tax incentives, RTD grants or financial schemes such as loans, guarantees, or public venture capital. Organization of Economic Cooperation and Development. See also Hall and Rosenberg (2010).

l l l

Economic and Financial Aspects of Innovation Chapter

l l l l l l l l

9

171

number of relevant scientific and technical journal articles/mil. pop. royalty and license fee receipts; royalty and license fee receipts/mil. pop.; total value of “exits” or IPOs (in the specific innovation ecosystem area); total number of “exits” or IPOs; number of jobs created (due to the specific innovation activities or ecosystem); number of jobs lost (delineated as above); quantitative expressions of the sales related to the innovation ecosystem items examined, over a given time period (e.g., value, numbers of items, VAT, etc.).

For the case of transport innovation, we can also include in the definition of “outputs” the following: l l l l l l l l

new mobility patterns and systems; economic, commercial, organizational impacts on the transport system or subsystem considered; wider impacts on economic development and productivity levels28; environmental impacts especially in urban areas; health and social welfare impacts; land use and town planning impacts; social equity and accessibility to other sectors and services; impacts on public policy, law, and services.

As it was also done for the case of “inputs,” a number of “proxy” output indicators can also be defined. Obviously, the data availability will determine the extent and depth to which these “proxy” variables can be used. Examples of such proxy variables are: l l l l l l

l l l l l

climate change mitigation; liability issues; environmental and socioeconomic impacts; social stability; extending the viability of IT and AI revolutions; sustaining the benefits of globalism in the face of a growing momentum for isolationism, protectionism, and nationalism; international political stability; social welfare; public policies, law making and services; entrepreneurship; trip making behavior; and so on.

Innovation Rates of Return Calculation of the rate of return of innovation activities is also quite a tricky issue. The stochastic nature of innovation outcomes means that there may not be a single “rate of return” (in the economic sense) but more than one according to the analysis perspective taken. There is also the need for a measure of depreciation or obsolescence to be estimated for the produced innovatory products. Such measure is necessary in order to compute the net or gross rates of return as well as in order to calculate “innovation elasticities.” On both these issues the reader is referred to more specialized publications such as Erixon and Weigel (2016), Hall and Rosenberg (2010), Lach et al. (2008), Blundell and Bond (2000), Jaffe (1986), and Cuneo and Mairesse (1983). Normally, the results of private sector innovation evaluation in terms of the resulting “economic” rates of return are greater than those for public sector evaluations. This is because in the second case the outputs that are taken into account consist of many nonquantifiable items which therefore cannot influence the economic rate of return.

28. Recently a “productivity paradox” is being detected in certain countries and regions in that productivity growth has slowed while investment in research and innovation has remained relatively stable (European Commission, 2017a). This has casted some doubts about the link between research/ innovation and productivity growth which may—in certain areas—be broken or dysfunctional.

172

SECTION

A Understanding Systemic Innovation

INNOVATION FINANCING Overview There are a number of financing sources and instruments for all stages of the innovation cycle that have been developed and tested in practice over the years. There is now sufficient experience from innovation financing sources and instruments covering all stages of the innovation cycle. Their availability and effectiveness, however, depend on the surrounding economic environment in the country or region under consideration. Large corporations usually utilize their own funds— gathered from profitable past operations—or resort to the finance of VC s or banks eager to get involved in successful innovation investments. Small and medium-sized companies (SMEs) and small entrepreneurs have to rely mainly on special (normally public) innovation funding instruments or on-the-spot market financiers. The most widespread and well-known sources of financing and the stage of the innovation cycle to which they apply most often is shown in Fig. 9.1. Relative to the contents of Fig. 9.1, we note the following: 1. Governmental funding. Up to now, these funds are normally given to finance the RTD stage and may be to some demos and presentations of early stage technology development. There are many ways and forms of governmental funding that are used for this purpose. Each government devises its own ways and methods of releasing such funding that suit its administrative rules and apparatus. Such financing is available also through the local and regional governments. In Europe, for the last decade or so, a most notable experiment in multinational funding for research and innovation

Stages in the innovation chain

Funding sources and instruments

Basic research

Applied research

Government funding via various bodies and channels (Public R&D programs—Technology labs—Small business financing, etc.)

Private corporations own funding

Proof of concept -

Venture capital/ corporate venture funds

Demo—Early stage technology development

Bank loans, equity purchase

“Angel” investors funding Product development Crowdfunding

Market introduction

Legend: : Most often used : Occasionally used

FIG. 9.1 Financing instruments and channels for the various stages of the innovation ecosystem.

Economic and Financial Aspects of Innovation Chapter

2.

3.

4. 5.

6.

9

173

has been initiated with relative success so far. It is the so-called Joint Technology Initiatives (JTIs)29 that combine the resources of several national governments as well as of public/private partnerships involving the industry and the research community in order to finance a dedicated RTD&I program that is devised and approved jointly by the funding administrations. Own funding. This is the case of large private sector corporations that have profitable operations and can afford to devote part of their profits to RTD and innovation creation in their sectors. The typical example of this type of financing is the funding of innovation by companies such as Google, Apple, or Microsoft that have invested large sums not only in their own fields of main business (i.e., IT) but also to other fields such as transport (for autonomous and cooperative mobility) and others. Venture capitals. This is one of the most well-known forms of financing innovation. The creators of a VC company are usually investment banks, individual investors, or other companies. The VC companies normally focus on financing new “start-up” companies and small businesses that are built by entrepreneurs who have a novel idea or research product and want to promote it to the market. They aim to invest in a given company—normally by buying equity—expecting that in a relatively short period of time the company will increase its value many times over. When the venture capitalists see that the value of the company has increased to a satisfactory level, they “exit,” that is, sell their shares with a profit or make the company public through an IPO. The number of such successful “exits” or IPOs as well as the average time it takes for such an exit or IPO are indicators that can be taken into account in order to assess the innovation-inducing environment in an innovation ecosystem or country or region. The typical VC invests in start-ups that are well managed and have a fully developed business plan are poised for substantial growth and usually (but not necessarily) engage in a sector familiar to the VC management. Bank loans: These are the traditional channels of finance which, however, in times of economic austerity become scarce. Angel investors. These are individuals who act as VC companies but using their own money. They are high networth individuals, that is, with wealth amassed through a variety of sources and interested to invest it in promising new companies promoting innovation. They tend to be entrepreneurs themselves, or executives recently retired from the business empires they’ve built and in their majority look to invest in companies that are well managed, have a fully developed business plan and are poised for substantial growth. Angel investors are usually coinvesting, that is, one angel investor funds a venture alongside a trusted friend or associate, often another angel investor. Angel and VC is, in essence, a special type of equity finance, typically for young, high-risk and often hightechnology firms. Crowdfunding. This is the latest trend in innovation financing. By using a “crowdfunding facility” a start-up company gains the possibility of raising smaller amounts of money from multiple backers—from individuals to pension funds and local authorities. Crowdsource financing is usually done through online platforms. Examples of crowdsourcing platforms are the Kickstarter30 and the Indiegogo31 and for the transport sector, the Crowdsourced-transport,32 and the CIPTEC for public transport.33 There are of course many others.34 Crowdsourcing is becoming an increasingly common financing solution, especially in recent times when the traditional VC financing is becoming more difficult to obtain due to the general economic situation in certain countries or regions.

This chapter cannot go into a great detail on each of these financing instruments—there are many specialized publications for that. However, it will be useful to refer here the practical application experience to date of some of the most wellknown ones.

29. 30. 31. 32. 33. 34.

See: http://ec.europa.eu/research/jti/index_en.cfm. See: https://www.kickstarter.com/ (Accessed May 2018). See: https://www.indiegogo.com/ (Accessed May 2018). See: http://crowdsourced-transport.com/ (Accessed March 2018). See: http://ciptec.eu/join-crowdsourcing.html (Accessed March 2018). For example: AngelList, CircleUp, Crowdfunder, EquityNet, Fundable, MicroVentures, Peerbackers, RocketHub, Smallknot, SeedInvest, and others.

174

SECTION

A Understanding Systemic Innovation

VC financing The provision of venture capital35 (VC) is the traditional form of funding for innovation. It takes place through a number of steps: a. Investors and start-up companies seek each other through formal and informal business networks, personal connections, paid or unpaid finders, researchers, advisers, etc. b. The start-up company provides the investment firm with a confidential business plan to secure initial interest. c. When a specific interest is developed, initial nonbinding negotiations begin. At this stage a “due diligence” exercise is normally carried out to check the legal and statutory correctness of the start-up company. d. After these previous steps, a “valuation” for the start-up company is made which, when accepted, results in signing of a Private Placement Memorandum (PPM). This is still nonbinding and is a form of letter of intent. e. After drafting a series of contracts and other legal papers that will be used to implement the transaction, the definitive legal papers that document the final transaction are signed. They include documents like “stock purchase” agreements, “buy-sell” agreements, “co-sale” agreements, “right of first refusal” documents, and others. f. Following the signing of these binding documents, the investors provide the funding and the start-up company provides stock certificates to the investors. Each time a funding occurs, it forms a so-called “funding round.” There are various types and corresponding names of funding rounds mainly relating to the class of stock being traded in each case, for example: l l l l

Seed round, where company insiders provide start-up capital; Angel round, where early outside investors buy common stock; Series A, Series B, Series C, etc., rounds occurring at various stages of the company’s development; Mezzanine finance rounds, bridge loans, and other debt instruments used to support a company between venture rounds or before its IPO.

Thomas Davis and Arthur Rock were the pioneers of VC financing having formed the first VC firm that operated in the US’s Silicon Valley in 1961, the Davis and Rock VC. Their hugely successful investments in innovating firms were followed by other VC firms of the 1960s, including Draper, Gaither & Anderson (1961), Sutton Hill (1964), and Mayfield Funds36 (1963). These pioneering VC firms found massive returns from Silicon Valley technology companies like Teledyne Technologies, Intel, Apple and many others. In 1969, the entire US VC community, which was centered in the Silicon Valley area, constituted around 20 companies. Like the rest of the valley, these early venture capitalists shared lots of ideas with each other. Moreover, there was extensive personnel crossover in these firms. The flow of personnel and ideas between venture capitalist pioneers gave rise to many of the principles embodied by technology investors today, such as focusing on the founder more than the company and hosting promising entrepreneurs as “entrepreneurs in residence” (“incubating”). By the early 1970s venture capitalists were key part of the innovation structure in the Silicon Valley. Giants like Kliener (1972), Sequoia Capital (1972), and New Enterprise Associates (1978) became a key element of the US innovation ecosystem, fueling high-technology startups. The VC is now the “rocket” fuel that powers innovation all over the world, including transport innovation. In the field of transportation, the creation of VC as powerful funding source for integrated circuit invention and production in the 1960s (in the US Silicon Valley) continues to spillover into the transportation revolutionary innovations of today. In 2017, a new wave of VC focused on autonomous and electric car technology. According to a recent article in the Financial Times37 the latest such investment came for car technology-related start-ups and has reached $1.6 billion during the first half of 2017. There is a growing number of specialized venture funds dedicated to innovative car technology—a domain that includes fully autonomous vehicles and related applications of technologies such as artificial intelligence and machine learning, mapping, and similar.

Stock Market Funding If the start-up company is progressing well and according to its business plan, it can turn to the stock exchange to file for an IPO through a stock market launch in which shares of the company are sold usually to institutional investors that in turn sell them to the general public on a securities exchange. Through this process, a privately held company transforms into a public company. 35. Or Angel investor funding in the case of individual investors. 36. Which was also formed by Thomas Rock and Wally Davis together with Stanford University. 37. July 12, 2017, by L. Hook, “Record Venture Capital cash floods into Car Technology”, available at: https://www.ft.com/content/8ec8079c-66a6-11e78526-7b38dcaef614 (Accessed November 2017).

Economic and Financial Aspects of Innovation Chapter

9

175

The stock market is thus a funding mechanism that follows the direct “funding rounds” from VCs. During the recent economic turmoil, which for some countries was an outright depression, the stock market as a mechanism of innovation funding has declined. For one thing, there have been temporary declines in the huge IPOs that were occurred especially in the United States. This caused companies to prefer staying (for quite some time) in the private market because it is not possible for them to IPO for a sum that is sufficiently higher than what they have raised in their last VC funding rounds. The huge investments and the inflated valuations of the past stock market IPOs have started giving way to more “sane” valuations.38 A more recent practice is that entrant companies stay in the stock market at ever shorter time periods and then leave, even at lower prices than those of entry. One of the reasons for this “negative returns” trend is the initial high valuations that are usually given to startups, especially those that had already raised a few funding rounds. The natural dynamic of start-up companies is to raise their valuation on paper in every funding round and this can create “bubbles.”39 Such situations have the potential of making the whole start-up funding through the stock market an equivalent to “a bubble explosion” instead of being part of a growing and healthy market. There are, therefore, risks that exist in VC and stock market funding, especially in the context of inherent volatility of the stock markets in times of economic downturn and uncertainty.

Crowdfunding This is a relatively novel innovation funding tool, which is defined40 as the practice of funding a project or venture by raising monetary contributions from a large number of people (“crowd”). This is done with the help of specialized firms which create and maintain “crowdfunding web platforms” aimed at gathering a large number of individual investors to a specific start-up company or project. The crowdfunding model is generally based on three types of actors: a. The project initiator who proposes the idea and/or project to be funded. b. The individuals or groups who support the idea. c. A moderating organization (the “platform”) that brings the parties together to launch the idea. Crowdfunding is not just an online tool to raise money, volunteers, and materials, but also a way to build a “community” around a project. A more recent version of crowdfunding is the so-called “civic crowdfunding” which focuses on local governments and civic initiatives. Municipalities take up the role of an “equal partner” which can cooperate to realize an initiative, so local governments increasingly hand over tasks and responsibilities to civil society. For example, by training citizens and professionals in civic crowdfunding, starting a local thematic crowdfunding platform, or by becoming a match-funder. Match-funding is an alternative way to distribute subsidies for social projects by contributing to crowdfunding campaigns. In this way, municipalities can strategically change their funding instruments to stimulate civic projects based on crowdfunding.

Innovation Financing in the Transport Sector All the forms of innovation financing mentioned above are also available—and adequately utilized—in the transport sector with varying degrees of intensity and success. Financing for innovation in areas of promising new technological applications in the field of transport such as new mobility services and electro-mobility may enjoy increased interest for financing but this is temporally sensitive, that is, it may change in time. The two traditional areas in the transport sector that attract the highest levels of innovation financing, are the automobile and the aviation manufacturing sectors. The sector with the lowest innovation funding is the transport infrastructure construction sector which has traditionally been considered as a critical “public good” to be provided by government. This sector enjoys high levels of funding for the actual construction work utilizing a very sophisticated array of financing instruments—see Rodrigue (2017)—but it attracts the least of funding for research and innovation. 38. An indication of this trend was given recently by the American fund Fidelity which outdid others and cut the estimated valuations of many leading companies, in November 2016, including the popular Snapchat from Silicon Valley whose value was cut by 25% (for more updated news on this, see: https://www.fidelity.co.uk). 39. If, for example, a company raised $100,000 close to its launch with a valuation of $1 million, then by the time it will raise $5 million, its valuation will be 10 times higher, that is, $50 million and when it will raise $20 million it will be worth (on paper) $200 million. This, inevitably creates a situation where the biggest investor will lose money on subsequent sales that inevitably will happen at a lower value from his initial investment. When there are many startups, there are not enough buyers and therefore valuations will be lower in the good cases and zero or very small in the bad ones. 40. According to the Oxford Dictionary definition of “Crowdfunding.”

176

SECTION

A Understanding Systemic Innovation

As regards public funding for transport research and innovation, there is a distinct difference between countries with advanced economies and those with lesser developed ones. According to a recent global survey among more than 20 countries around the world, governments, in lesser developed economies do not include transport among the fields to be financed in their national RTD&I funding programs. On the contrary, countries with more advanced economies always include transport programs in their funding (EUTRAIN, 2012). This may be due to the fact that research fields in the medical, environmental, or defense sectors are perceived—in lesser developed economies—as having higher priority and urgency in facing societal problems. Examples of public sector funding instruments in the transport sector are as follows41: In the United States: The various transport cooperative RTD&I funding programs at federal and state level. These are quite many and varied and well documented. The main ones are given via the various branches of the US Department of Transport—DoT (more than 20 separate funding programs)42 and the Transportation Research Board (TRB) of the National Academies (8 funding programs and instruments).43 l The Small Business Innovation Research Program (SBIR). The SBIR was created in 1982 through the Small Business Innovation Development Act of 1982 (Public Law 97-219). It requires federal agencies with substantial RTD budgets to provide special set asides for small business RTD. One of the underlying values of SBIR is to raise the US small businesses capabilities to meet federal RTD requirements. SBIR was reauthorized in 2000 and 2008. l Small Business Technology Transfer (STTR). The SBIR was further extended to partnerships between private firms and universities through the Small Business Technology Transfer Act of 1992, which established the Small Business Technology Transfer (STTR) program to fund cooperative research involving small businesses, universities, and federal laboratories. l The Advanced Technology Program (ATP). This was created by the Omnibus Trade and Competitiveness Act of 1988. The ATP works through formal solicitations for proposals, resulting in bottom-up submissions from industry which are selected through a peer review system. Since its establishment, the ATP has been subject to considerable criticism, including from some members of the US Congress, that “it is an unnecessary intervention by government into aspects of the innovation process that are better handled by the private sector.” As a result it was abolished by the COMPETES Act of 2007.44 l The Technology Innovation Program (TIP). This was created by the COMPETES Act and resembles the ATP. In spite this change between the ATP and the TIP programs the debate about the desirability of direct federal government financing for innovation policies is still going on in the United States. l The Industry-University Cooperative Research Centers (IUCRC) and the Engineering Research Centers (ERC). These are two initiatives of the National Science Foundation (NSF) that link education, industry, and research missions are two more government led innovation funding initiatives in the United States. Both are based around a highly competitive peer review process and are focused on particular research areas (including transport). l A further area of US federal intervention to support innovation involves the crosscutting development of human and institutional capabilities for innovation. These activities occur nationwide and also in selected lagging states and involve the funding by the federal government human resource development capabilities for innovation in states and regions that are lagging.45 l State and local innovation policies. In the United States, many states and local areas have shaped a number of dynamic “bottoms-up” innovation supporting programs several of which focus on the transport sector. In the mid-2000s, nanotechnology, energy, and clean technology areas were primarily encouraged and through them many transport applications based in these areas. The universities take a rather fundamental role in such regional innovation initiatives beyond conventional teaching and research missions by developing incubators, licensing offices and technical outreach to businesses, spin-off of start-up companies and seed capital funds. Perhaps the most well-known US state innovation program is the California Research and Innovation Initiative which amounts to a total sum of around $100 million financed through revenue bonds. l

41. We limit our consideration to the EU and US cases. For other countries such as China, Japan, Germany, Israel, and Korea see the case studies section in this book while for Japan and Korea (as well as China) see Giannopoulos (2017). 42. More in the site of the Office of the Assistant Secretary for Research and Technology at: https://www.transportation.gov/administrations/assistantsecretary-research-and-technology/ost-rs-programs. 43. See: http://www.trb.org/AboutTRB/Programs.aspx. 44. COMPETES: Creating Opportunities to Meaningfully Promote Excellence in Technology, Education and Science. 45. See Shapira and Youtie (2010).

Economic and Financial Aspects of Innovation Chapter

9

177

National funding for transport RTD&I remains strong in the United States. However, a recent report by the US National Science Board refers to a downturn in research spending by the private sector (US National Science Board, 2012), which coupled with government budget constraints at all levels, are reasons for concern. In the EU: l The 70 billion Euro, H2020 (Horizon2020) RTD&I program is the main vehicle for funding research and innovation by the EC for the 7-year period 2013–20. There is a transport line in it (transport challenge) that absorbs approximately 7% of the total budget which together with transport-related projects in other lines of the program may in total add up to a total of approximately 10%, that is, 7 billion Euros for transport-related RTD effort. As most of this funding is on a 50% funding basis (the other 50% being provided by the participants mainly the industry) the grand total of transport-related RTD&I46 that is leveraged by the EC comes to approximately 14 billion Euros for the 7-year period. It is not yet decided if the next 7-year period for research and development to be funded by the EC (the FP8 program, spanning the years 2020–26) will include a transport line as it has been the case for all previous such programs. l Significant though it is, the above funding program for RTD&I by the EC represents only approximately 5% of the total publicly available funding for RTD&I by all EU member states (i.e., in their national programs). It is not known however how much of this money goes to transport-related RTD&I. l Other European Organizations related to (or influenced by) public money that finance research and technological innovation in the transport sector, though not directly, that is, through “RTD programs,” are the European Investment Bank (EIB) and the European Bank for Reconstruction and Development (EBRD). The EIB finances projects in the urban mobility, rail, aviation, maritime, and road sectors some of which include RTD&I parts. As the bank’s site emphasizes, the focus is on projects that are climate friendly, safe, sustainable, and innovative. It does this via support for specific isolated projects in the various EU member states, but also via specific funding lines such as the “Cleaner Transport Facility” for the deployment of alternative fuels and cleaner technology in transport, the “Single European sky” for air traffic management, and similar programs for the maritime and road sectors. The EBRD, too, offers three kinds of financing for businesses in general (including those wanting to invest in innovative new products), that is, through loans, equity investments, and guarantees to promote trade.47 48 l Other EU initiatives, such as JASPERS, ELENA,49 and the support actions under the “debt instrument” of the Con50 necting Europe Facility—CEF Debt Instrument, can be used under certain circumstances. They are all taken under one financial provisions “hub” called the European Investment Advisory Hub—EIAH. This “hub” is hosted by the EIB.51 l Finally, in order to complement the shortage that is being noticed in recent years for financing through higher risk loans that compliment VC funds, both large and small innovative firms in the EU can utilize a new generation of EU financial instruments that came about as recently as June 2014. This is a joint initiative of the EC and the EIB Group52 called InnovFin (for Innovators Finance). This is the financial instrument under which the EU promotes a range of debt and equity products (and advisory services) in order to enhance the availability of finance for research and innovation activities in Europe. The InnovFin consists of a range of tailored products, for example, guarantees for intermediaries that lend to SMEs, or direct loans to enterprises, and others. It is largely associated with the current 7-year RTD program of the EU, the Horizon 2020, and builds on the success of the Risk-Sharing Finance Facility, developed under the 7FP (7th Framework Program) which—for the 7-year period 2007–13— helped provide over €11 billion of finance to 114 research and development (and to some extend Innovation) projects worth more than €30 billion.53

46. The great majority is for RTD funding only. An undefined (but relatively much lesser) amount goes for the innovation production part. 47. The European Bank for Reconstruction and Development is an international financial institution promoting transition to market economies by investing mainly in private sector development and entrepreneurship. The bank was established in 1991 by 64 countries and two intergovernmental institutions. It is the largest single investor in 34 countries from Central Europe to Central Asia. 48. Joint Assistance to Support Projects in European Regions—JASPERS is a technical assistance partnership between the European Commission, the EIB and the EBRD that provides independent advice to beneficiary countries to help prepare high-quality major projects to be co-financed by two EU Structural and Investment Funds (European Regional Development Fund and Cohesion Fund). 49. European Local Energy Assistance—ELENA provides grants for technical assistance focused on the implementation of energy efficiency, distributed renewable energy, and urban transport projects. 50. The Connecting Europe Facility (CEF) is a key EU funding instrument to promote growth, jobs and competitiveness through targeted infrastructure investment. 51. Details in: http://www.eib.org/efsi/eiah-lowlight.htm?lang¼en. 52. That is the European Investment Bank—EIB and the European Investment Fund—EIF. 53. These figures refer to all sectors not only transport.

178

SECTION

A Understanding Systemic Innovation

SUMMARY OF MAIN POINTS Economic and societal monitoring and evaluation of innovation is a necessary function of any innovation ecosystem. The “value” created by any innovation producing activity, innovation cycle, or the whole ecosystem must be measured and compared to the public or private sector inputs that were used for its creation. Unfortunately, evaluation is largely a retrospective process and it is very difficult to draw appropriate conclusions from the past that apply to the future. A simple, transparent, and commonly accepted system of innovation evaluation does not exist today. The size of the actual or potential technical and economic impacts of innovation (properly quantified in terms of commonly accepted units and methods of conversion) should be weighed against the size of the actual inputs used. Evaluation is an expensive process and many innovators and government officials would invest in innovation itself rather than in its evaluation. The societal impacts should also be capable of being “measured” in terms of their contribution to solving key societal and global problems (e.g., climate change) or in terms of the contribution to several specific societal problems like reducing social inequality, increasing social coherence, mitigating climate change, and so on. Such system of evaluation—together with the system of monitoring and data collection that was discussed in Chapter 7, must in a way become an integral part of the development and sustainability process of innovation ecosystems. In the available literature the bulk of the work so far has been on the evaluation of the earlier stages of the innovation cycles, namely the research and development ones (RTD). Most of the existing evaluation studies examine the impacts of RTD investment on the economy as a whole or within a specific geographic area. There is relatively very little by way of evaluation or assessment of the whole innovation cycle or ecosystem in a certain sector. The scarcity of innovation evaluation studies is probably the result of the difficulties in devising a proper methodology that can take account the various inputs and outputs of the particular innovation assessed and in actually distinguishing the impacts that are due to one or more innovations that interact to produce one major transformative innovation. More demanding are usually the evaluations that are made for public sector investment as in those one has to consider a wider range of impacts—not all of them quantifiable in money terms. All existing methodologies for evaluating/assessing RTD activities utilize, in one way or another, the notion of “productivity” defined as the ratio of an “output” index to an “input” one. TFP is the concept that has been used in many instances for such types of evaluation and may well be appropriate for the wider and more sophisticated type of innovation assessments advocated here. The use of “technological frontier analysis,” as described in Perelman (1995), is also used as tool here. In this chapter we gave a number of methodologies and examples of RTD and innovation evaluation frameworks that can provide useful precedents for full scale innovation ecosystem evaluations. However, we are in need of a detailed and fully documented innovation evaluation methodology that would distinguish between publicly funded and privately funded innovation. Such methodology would be coupled with a new system of innovation monitoring and data collection using techniques and technologies that are now far more powerful than before. The issues of methodological development and systematic collection of information and data on innovation is something that has to be undertaken by an international organization with the active support of national governments interested to reinforce what is known about the value of innovation and of investing in it. Innovation financing is another very important elements of innovation economics. It is intrinsically linked to the overall financing environment in a country or region with most of the problems and difficulties associated with such financing concerning new entrants and start-up firms. All traditional financing instruments are used or have been applied extensively in the past with varying degrees of success. The most frequently observed form of innovation financing is the various types of VC. The usual structure for such funding is the purchase of equity in a suitable form of start-up or corporate entity. The new entities take the form of a “limited partnership,” as this type is in some countries associated with important tax advantages. A venture partnership is another form of funding where VC buys the stock in a start-up company. Activity in the VC industry for investment in the transport sector increased dramatically in the 2000s, in the subsequent decade there were some trying times for VC firms. Commitments to the VC industry were very uneven, creating a great deal of instability resulting to the annual flow of money into venture funds being steadily declining as returns tended to fall. The same trend was observed in earlier time periods thus showing certain cyclicality in VC financing. In recent times, there is also evidence of VC financing rebounding. Government-related programs from which a start-up can draw financing for its activities are another widespread case. Such funding is particularly appropriate for financing transport innovation because the sector is basically related to basic societal goods and social services. Transport, in all its aspects and elements (infrastructures, operation, vehicles, and services), can be considered as representing what the economists call “collective” or “public” good, that is, shared and beneficial for all or most members of a given community. Collective goods, often fall prey to “free riders,” that is, entities that receive the benefits of an investment without incurring any of the costs or risks of development. The role of government in

Economic and Financial Aspects of Innovation Chapter

9

179

this case would be to ensure that there is a transparent and effective evaluation mechanism set in place that would uncover these cases and ensure equal treatment to all as well as reduce the risks associated with innovation production by providing direct or indirect financial support, through incentives. Bank loans and bank-related finance—especially under the current economic conditions in many countries—is the least preferable form of innovation finance. In most countries, existing regulations connected to banking, usually limit a banks’ ability to hold shares especially in relatively young companies. Their conservative risk-taking policies—especially when dire economic conditions exist in many countries—prevents them from investing in start-ups where they will not be able to dispose of the acquired equity freely. Banks, also, may not have the necessary skills to evaluate projects with few collateral (physical) assets and significant uncertainty associated with transport-related innovation projects.

REFERENCES Aubert, J.E., 2005. Promoting innovation in developing countries: a conceptual framework. Washington DC: World Bank Institute, World Bank Policy Research Working Paper 3554, April. Blundell, R., Bond, A., 2000. GMM Estimation with Persistent Panel Data: An Application to Production Functions. Economet. Rev. 19 (3), 321–340. Cuneo, P., Mairesse, J., 1983. Productivity and RTD at the firm level in French manufacturing. Cambridge MA: NBER (US National Bureau of Economic Research), Working Paper No. 1068, January. Dinges, M., Schmidmayer, A., 2010. Country Report: Austria. Part III, Chapter 8 of the INNO APPRAISAL Study. PRO INNO Europe, Vienna. Erixon, F., Weigel, A., 2016. The Innovation Illusion: How so Little is Created by so Many Working so Hard. Yale University Press, New Haven. European Commission, 2012. Evaluation of innovation activities: guidance on methods and practices. Evaluation Unit, DG Regional Policy, June, Brussels. Available at: http://ec.europa.eu/regional_policy/sources/docgener/evaluation/pdf/eval2007/innovation_activities/inno_activities_guidance_ en.pdf. Accessed August 2018. European Commission, 2017a. The economic rationale for public R&I funding. European Commission, Directorate General for Research and Technological Development, report March, Brussels. European Commission, 2017b. Key findings from the H2020 interim evaluation. European Commission, Directorate General for Research and Innovation, Brussels. Eurostat, 2016. EU Community Innovation Survey. Eurostat, Luxembourg. Available from:http://ec.europa.eu/eurostat/web/microdata/community-inno vation-survey. Accessed August 2018. EUTRAIN, 2012. European Transport Research Area International Cooperation Activities, Deliverable 2.1, Current practices, characteristics and issues in research collaboration. EU FP7 funded research project, coordinated by ECTRI, Brusselshttp://www.ectri.org. FTEVAL, 2007. Evaluation of Austrian Research and Technology Policies: A Summary of Austrian Evaluation Studies from 2003 to 2007. Austrian Council for Research and Technology Development—ACRTD, Platform for Research and Technology Policy Evaluation—FTEVAL, Vienna. Georghiou, L., 2015. Value of Research. European Commission, Directorate-General for Research and Innovation, Policy Paper, June, EUR 27367 EN, Brussels. Available from:https://ec.europa.eu/futurium/en/system/files/ged/60_-_rise-value_of_research-june15_1.pdf. Accessed August 2018. Giannopoulos, G.A. (Ed.), 2017. Publicly Funded Transport Research in the P. R. China, Japan, and Korea: Policies, Governance and Prospects for Cooperation With the Outside World. Springer Mobility Series. Griliches, Z., 1979. Issues in assessing the contribution of research and development to productivity. Bell J. Econ. 10, 92–116. Griliches, Z., 1998. RTD and Productivity. University of Chicago Press, Chicago. Hall, B., Lerner, A., 2009. The financing of RTD and innovation. US National Bureau of Economic Research—NBER, Working paper 15325, September, Cambridge, MA. Available from:http://www.nber.org/papers/w15325. Accessed August 2018. Hall, B., Rosenberg, N. (Eds.), 2010. Measuring the returns to RTD.In: Handbook of the Economics of Innovationpp. 1033–1082 (Chapter). INNO-Appraisal project, 2010. Perspectives on Evaluation and Monitoring Final Report, PRO-INNO Europe Community. European Commission/DG Enterprise, project contract number: 046377 February, Brussels. Jaffe, A., 1986. Technological opportunity and spillover of RTD: evidence from firms, patents, profits and market value. Am. Econ. Rev. 76 (15), 984–1001. Lach, S., Parizat, S., Wasserteil, D., 2008. The Impact of Government support to Industrial RTD on the Israeli Economy: Final Report. Israel Innovation Authority, Ministry of Economy and Industry, study performed by E.G.P. Applied Economics Ltd, Tel Aviv. Leonard, W.N., 1971. Research and development in industrial growth. J. Polit. Econ. 79 (2), 232–256. Levin, R.C., Klevorick, A.K., Nelson, R.R., Winter, S.G., 1987. Appropriating the Returns from industrial Research and Development. Brookings Pap. Econ. Act. (3), 783–832. Mairesse, J., Mohnen, A., 2004. The Importance of RTD for Innovation: A Reassessment Using French Survey Data. US/NBER (National Bureau of Economic Research), Cambridge MA. Working Paper No. w10897. Mairesse, J., Mohnen, A., 2010. Using innovation surveys for econometric analysis. United Nations University—Maastricht Economic and social Research and Training Centre on Innovation and Technology, Working Paper No. 2010-023, Maastricht. Mairesse, J., Mohnen, P., Kremp, E., 2005. The Importance of RTD and Innovation for Productivity: A Reexamination in Light of the French Innovation
Survey. Annales d’Economie et de Statistique, Contributions in memory of Zvi Griliches (July/December 2005)pp. 487–527. Mansfield, E., Schwartz, M., Wagner, S., 1981. Imitation costs and patents: an empirical study. Econ. J. 91, 907–918.

180

SECTION

A Understanding Systemic Innovation

OECD and EUROSTAT, 2005. Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data. OECD, Paris. Perelman, S., 1995. R-and-D, Technological-Progress and Efficiency Change in Industrial Activities. Rev. Income Wealth 349–366. Perkman, M., Tartari, V., McKelvey, M., Autio, E., Brostrom, A., D’Este, P., Fini, R., Geuna, A., Grimalrdi, R., Hughes, A., Krabel, S., Kitson, M., Llerena, P., Lisson, F., Salter, A., Sobrero, M., 2013. Academic engagement and commercialisation: A review of the literature on University–industry relations. Res. Pol. 42 (2), 423–442. Rodrigue, J.-P., 2017. Chapter on Financing of Transportation infrastructure. In: The geography of Transport systems. Routlege, New York, p. 440. Salter, A., Martin, B., 2001. The economic benefits of publicly funded basic research: a critical review. Res. Pol. 30 (3), 509–532. Shapira, P., Youtie, J., 2010. The innovation system and innovation policy in the United States. In: Frietsch, R., Sch€uller, M. (Eds.), Competing for Global Innovation Leadership: Innovation Systems and Policies in the USA, EU and Asia. Fraunhofer IRB Verlag, Stuttgart, pp. 5–29. Tassey, G., 2010. Rationales and mechanisms for revitalizing US manufacturing RTD strategies. J. Technol. Transf. Tassey, G., 2013. Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy. NIST Economics Staff Paper, May. Available from: https://www.nist.gov/publications/beyond-business-cycle-need-technology-based-growth-strategy1. Accessed August 2018. US National Science Board, 2012. Research and Development, Innovation and the science and engineering workforce: A companion to science and engineering indicators. Washington, DC: US/NSB. Available from:https://www.nsf.gov/nsb/publications/2012/nsb1203.pdf. Accessed August 2018. US/DoT/FHWA, 2017. Highway Safety Improvement Program (HSIP) Evaluation Guide. US Federal Highway Administration (FHWA), Department of Transportation, Safety Program, Washington, DC. Available from:https://safety.fhwa.dot.gov/hsip/docs/fhwasa17039.pdf. Accessed August 2018. Van Roy, V., Vertesy, D., Vivarelli, M.V., 2015. Innovation and Employment in Patenting Firms: Empirical Evidence from Europe. The Institute for the Study of Labor—IZA, Discussion Paper No. 9147, June, Bonn. Wiesenthal, T., et al., 2015. Innovation in the European transport sector: a review. Transport Pol. 42, 86–93. World Bank, 2004. Benchmarking Countries in the Knowledge Economy: Presentation of the Knowledge Assessment Methodology (KAM). World Bank Institute, Washington, DC. Available from:http://siteresources.worldbank.org/KFDLP/Resources/KAMBoardBriefing.pdf. Accessed August 2018.

FURTHER READING Arrow, K., 1962. Economic welfare and the allocation of resources for invention. In: Nelson, R. (Ed.), The Rate and Direction of Inventive Activity. Princeton University press, Princeton, NJ. Belitz, H., 2016. Support for Private Research and Development in OECD Countries on the Rise but Increasingly Inefficient. German Institute for Economic Research—DIW Economic Bulletin, no. 8, Berlin. Branscomb, L., Auerswald, A., 2002. Between invention and innovation: an analysis of funding for early-stage technology development. Gaithersburg, MD: US/NIST report GCR 02–841 for the NIST Advanced Technology Program. Donselaar, P., Koopmans, C., 2016. The fruits of RTD: Meta-analyses of the effects of Research and Development. Free University of Amsterdam, Faculty of Economics and Business Administration, Productivity Research Memorandum no. 2016-1, Amsterdam. Available from:https://research.vu.nl/ws/ portalfiles/portal/1403389. Accessed August 2018. European Commission, 2017. LAB-FAB-APP Investing in the European future we want. European Commission, DG Research & Innovation, Report of the independent High Level Group on maximising the impact of EU research and innovation programmes—the Lamy report, July, Brussels. Florida, R., 2016. The Rise of Global Startup Cities. A report of the Martin Prosperity Institute, published in CityLab site, January 26. Available from: https://www.citylab.com/life/2016/01/the-rise-of-global-startup-cities/426780/. Accessed August 2018. Goni, E., Maloney, A., 2014. Why don’t poor countries do RTD? World Bank Group, Policy Research working paper, no. WPS 6811, Washington, DC. Harrison, R., Jaumandreu, J., Mairesse, J., Peters, B., 2008. Does innovation stimulate employment? A firm level analysis using comparable micro-data from four European countries. US National Bureau of Economic Research (NBER), Working Paper 14216, August, Cambridge MA. Haskel, J., Wallis, A., 2013. Public support for innovation, intangible investment and productivity growth in the UK market sector. Econ. Lett. 119 (2), 195–198.  Stare, M., 2014. Impact of innovation on employment and skill upgrading. KU Leuven/Vives discussion paper 44, July, Jozˇe, P., Damijan, C., Kostevc, C., Leuven. Kerr, W.R., Lerner, J., Schoar, A., 2010. The Consequences of entrepreneurial Finance: A Regression Discontinuity Analysis. US National Bureau of Economic Research—NBER working Paper No. 15831, March, Cambridge, MA. Available from:http://www.nber.org/papers/w15831. Accessed August 2018. OECD, 2010. The OECD Innovation Strategy: Getting a Head Start on Tomorrow. OECD, Paris. Tassey, G., 2011. Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy. NIST—US National Institute of Standards and Technology, Economics Staff Paper, December. Available from:http://www.nist.gov/director/planning/upload/beyond-business-cycle.pdf. Accessed August 2018.