A multiple case-study; The influence of government policy on innovation project success in the Dutch energy sector

(1)

A multiple case-study;

The influence of government policy on

innovation project success in the Dutch energy

sector

Master Thesis

Ma Business Administration: Strategic Innovation Management

Jan Deen (1708236)

jandeen30@hotmail.com

First supervisor: R. A. van der Eijk

Second supervisor: Dr. F. Noseleit

Word count: 15 340

(2)

Governmental influence on innovation project success in the Dutch energy sector

1

Preface

This master thesis is my final proof of competence in obtaining the Master of Science degree in

Business Administration. During my master Strategy and Innovation Management I wrote this

thesis about the influence of governmental policy on innovation projects in the Dutch energy

sector. The fast shifting energy market and the need for transition to a more sustainable energy

supply was one of my main interests before writing this thesis. Now that I have finished this

research I can say I was right; the energy sector is one of the most engaging sectors in the

Netherlands (probably in the world). Through the need for continuous innovation it is perfectly

in line with my masters’ program.

(3)

2

Executive summary

(4)

3

Therefore, the policy instrument knowledge sharing has no influence on the success in

innovation projects. This was not expected while reviewing existing literature.

In conclusion, the governmental knowledge is not sufficient to facilitate the innovation project

optimal. With their new policy concerning the Topconsortia for Knowledge and Innovation the

government tries to compensate this shortcoming.

(5)

4

1. Introduction

‘Sustainability is the development that meets the needs of the present without compromising the

ability of future generations to meet their own needs‘

(WCED, 1987)

The definition of sustainability by the World Commission on Environment and Development is the definition with the most political influence. The population of the Netherlands increasingly acknowledges the importance of sustainability. About 70% of the people consider sustainability an important aspect for organizations (Dossier Duurzaam, 2013). However, the awareness of people and organizations on the importance of sustainability is not enough. Sustainability is an elusive concept that is beyond the reach of single organizations; it cannot be achieved through a single instrument; it requires changes in policy and governance (Loorbach & Kemp, 2003). According to Dincer (1999), one of the key factors in fostering sustainable development is the energy transition because of the serious problems the energy sector faces; e.g. oil dependency, reliability and environmental problems. Only the transition to a new energy system may lead to greater improvements in environmental efficiency (Weaver et al., 2000).

1.1 Relevance of the research

1.1.1 Social

(8)

7 renewable energy has gone up to 4.7% (Rijksoverheid, 2012), but there are not many who believe that the 14% goal set for 2020 will be reached. The arrears in renewable energy put the strong export position of the Netherlands at stake (PBL, 2013).

1.1.2 Scientific

The theoretical debate about energy transition policy is being increasingly published, existing literature widely criticizes the Dutch renewables policy for having been too unstable to provide sufficient incentives for investments into renewables (Meadowcroft et al., 2005; v. Rooijen & v. Wees, 2006; Negro Hekkert et al. 2007, Kern & Smith, 2009). A new report of the Netherlands Environmental Assessment Agency (in Dutch: Planbureau voor de Leefomgeving, or PBL, 2013) suggests that the Netherlands needs a sharpened innovation policy. According to this report, companies are usually not the frontrunners for the transition to sustainable energy sources, but they are the core of the innovation system. They are the actors that set up innovation projects focused on the exploitation of chances. The government does not have sufficient knowledge to make the right choices (‘Government cannot pick the winners’), but they can give the winners the opportunity to join the race (PBL, 2013). According to Burck et al. (2011) for a successful process of sharpening the innovation policy, the impact of recent policy instruments needs to be evaluated. They state that the arrears of the Dutch renewable energy sector are partly due to very weak policy evaluation.

Due to the long timeframe between action (the use of policy instruments) and results in the energy, measuring the impact of the government’s policy is very difficult (Mickwitz, 2003). To cope with this problem, this research explores the influence of policy instruments for projects with limited duration; according to Mickwitz (2003), short-term developments are important and also provide a source of information. Loorbach and Rotmans (2009) found that only a few empirical studies have contributed to the research field of the Dutch energy transition. Because of the bottom-up aspect of governmental policy on energy transition (Loorbach and Kemp, 2006), empirical data seems to be crucial. By studying six innovation projects that have the potential to positively contribute to governmental goals this research tries to broaden the empirical basis.

1.2 Research domain and scope

(9)

8 results of the study can be seen as an evaluation of Dutch governmental policy concerning innovation projects in the energy sector in the last ten years.

1.3 Goal and research questions

The goal of this research is to discover the relationship between the Dutch government’s policy and the success of innovation projects; in order to explore the strengths and weaknesses of Dutch transition policy on project level. This aim results in the following main research question:

What is the influence of governmental policy on the success of innovation projects in the Dutch energy sector?

In order to obtain a satisfying answer to the research question, several sub-questions need to be answered. In order to investigate the possibilities of the Dutch government regarding their influence on innovation projects, the following question needs to be answered: (1) what are the policy instruments to influence innovation projects? To understand the other part of the research question we need to know: (2) how can you measure the degree of success of innovation projects? With the knowledge obtained from the previous sub-questions, it is possible to measure both parts of the research question. We need to answer the following sub-questions as well in order to answer the research question: (3) to what extent were governmental policy instruments used during these innovation projects? And (4) which innovation projects can be seen as successful?

1.4 Research outline

(10)

9

2. Literature review

This theoretical framework defines the variables of this research. The investigation of the literature will result in a conceptual model in the last paragraph.

2.1 Instruments of governmental policy

To evaluate the governmental policy, it is of interest to know the instruments of the government. This paragraph starts with a summary of the Dutch policy concerning the energy transition. After that, the historical strains about government policy instruments are reviewed. The last sub-paragraph will handle the evaluation of governmental policy in environmental issues. The history and the description of the instruments answers sub-question (1): What are the policy instruments to influence innovation projects?

2.1.2 Governmental policy

(11)

10 The key elements of transition management (Kemp, 2010):



Long-term thinking (at least 25 years) as a framework for short-term policy



Back casting: the setting of short-term and longer-term goals based on long-term sustainability visions and short-term possibilities



Thinking in terms of more than one domain and different scale levels; how developments in one domain get along with developments in other domains; trying to change the strategic orientation of regime actors



A focus on learning and the use of a special learning philosophy of ‘learning-by-doing’



An orientation towards system innovation



Learning about a variety of options

The various elements of transition management are combined into a model of multi-level governance, which consists of three interrelated levels (Loorbach, 2007):

Strategic level: visioning, strategic discussions, long term goal formulation

Tactical level: processes of agenda-building, negotiating, networking, coalition building Operational level: processes of experimenting, project-building, implementation

(12)

11

2.1.1 Policy instruments

Governments have instruments to execute their policy. These instruments of governments have been analyzed in three main ways in the public policy literature (Hood, 2006). The first approach is to view the instruments as institutions. These institutions are forms of organizations that are available for the government (public corporations, independent or private sector contractors and various forms of public-private partnership). At this moment, Salamon (2002) leads this approach. He argues that new types of institutional forms of public policy are central to a new governance paradigm of recent decades. The second well established approach focuses on the politics of the instrument selection, in the sense of the interests or ideas that shape the choice of tools (Hood, 2006). This approach is about what political, ideological or cognitive processes lead to the choice of one policy instrument rather than another, instead of considering the instruments as institutions or other form of actions. In the general public policy literature, this approach is best exemplified through Linder and Peters (1998). The third approach to the instruments of government has tended to be institution free and to focus more on cataloguing the tool kit in a generic way rather than on the politics of instrument choice (Hood, 2006). Nowadays, one of the most endorsed theories in this approach is the ‘carrots, sticks and sermons’ categorization of these policy instruments (Vedung, 2003). This approach is developed on the basis of the well-known trichotomy of types of organizational control, originally developed by Etzioni (1961). It divides policy instruments in three categories; regulations, economic means and information. This approach is used in the environmental policy evaluation (Mickwitz, 2003).

2.1.3 Environmental policy evaluation

(13)

12 The four values are:

1. Effectiveness The degree of goal realization due to the use of certain policy instruments; evaluation should also include (positive and negative) side effects of the instruments.

2. Efficiency Input/output-ratio of policy instrumentation; evaluation includes problems of implementations of programs through the devised means (evaluation of the administrative process; and two additional criteria.

3. Legality The degree of correspondence of administrative action in designing and implementing policies with the relevant formal rules as well as with the principles of proper (administrative) process.

4. Democracy The degree to which administrative action in designing and implementing policies correspond with accepted norms as to government-citizen relationships in a democratic political order.

Bemelmans-Videc, Rist & Vidung, 2000

(14)

13

2.2 Project success

In this paragraph, existing theories are reviewed in order to answer the sub-research question (2): How can you measure the degree of success of innovation projects?

2.2.1 Historical strains

(15)

(16)

15

2.2.2 A multidimensional approach

‘The objectives of public-sector projects tend to be political, military or social, whilst commercial projects have primarily economic objectives. With such a multitude of objectives, one can objectively

measure the success of a project is somewhat an illusion’

De Wit, 1988

According to De Wit (1988), using a single measure for projects that aim at the public and the private sector is impossible. Therefore, a multidimensional approach for measuring success is created for this research. Lipovetsky et al. (1997) investigated success in defense projects with a nationwide importance, which is quite similar to the innovation projects in the energy sector. As mentioned in the previous chapter they used four dimensions: meeting design goals, benefits to the customer, benefits to the developing organization and benefits to the defense and national infrastructure. Lipovetsky et al. (1998) gathered data to analyze which of these dimensions was most important. According to their findings meeting design goals and benefits to the customer were by far the most important dimensions. The study of Shenhar et al. (2001) defines quite similar dimensions as Lipovetsky et al. (1997); project efficiency, impact on the customer, direct business and organizational success and preparing for the future.

(17)

16

3. Conceptual model

In this chapter the policy instruments of the government will be linked to the dimensions of innovation project success by formulating three propositions. These three propositions are based on findings of previous studies and will be tested in the result section.

3.1 Proposition 1 - Regulations

According to Mickwitz (2003) regulations have been the most common intervention approach in environmental policy in the most industrialized countries. The effectiveness of economic and regulatory instruments is to some extend contingent upon authorities’ ability to discover and oversee the activities to be controlled (Vedung, 2003). Regulations are measures taken by governmental units to influence people. Due to the awareness (sub-paragraph 2.1.2) of the Dutch government of the importance of the energy transition it can be assumed that the use of regulations should stimulate the projects in becoming successful.

Proposition 1: The use of regulations by the government increase the chance for innovation project success on all three success dimensions

3.2 Proposition 2 - Financial support

According existing literature on financial supports for sustainable innovation, the subsidies have different consequences for the different success dimension. Agnerer (2002) stated that high subsidies increase the chance of failure, because projects with more risk are carried out. Therefore, the probability that innovation projects with more financial support fail in achieving project goals and in becoming a commercial success increases. For supporting sustainability goals this negative effect is not clear, even if projects do not succeed on the first two success dimensions they could have made a start with creating knowledge on the specific subject. This specific knowledge may contribute to the achievement of the sustainability goals. For achieving these goals financial support is also important if market pull is low (Kemp & Nill, 2009); therefore, it is expected that financial support increases the chance on the last success dimension.

(18)

17 the sector. Therefore gaining commercial advantage from an innovation project with substantial public support is difficult. The previous findings lead to the following proposition.

Proposition 2: Financial support of the government negatively influences the chance for achieving projects goals and commercial success; however it has a positive effect on the achievement of supporting the sustainability goals

3.3 Proposition 3 - Knowledge sharing

The creation of networks through governments for sharing both technological and institutional knowledge between innovators at the early stages of technology development is important, both for the direct effects of knowledge sharing and in terms of increasing shared confidence in future technological and market potential (Foxon & Pearson, 2007). According to Kern and Smith (2008) one of the goals of the Dutch government was to bring together knowledge and expertise of different companies, knowledge institutions and governments. Sharing this knowledge throughout the industry should encourage and improve the innovation projects.

Proposition 3: Knowledge sharing through the government increases the chance for innovation project success on all three success dimensions

(19)

18

3.4 Conceptual model

In the conceptual model below the relationships between the three policy instruments and the three success dimensions are displayed.

Governmental policy

Achieve project

goals Commercial success

Support sustainability goals Regulations Financial support Knowledge sharing

Innovation project success

+ + +

-

+ + + +

(20)

19

4. Methodology

In this chapter the justification of this study will be described. The goal of this chapter is to provide this research with a valid and reliable process of collecting and analyzing data.

4.1 Research design

This research will take a case study approach, as we know little about the relationship between governmental policy and success in innovation projects. Case studies may involve both qualitative data and quantitative data (Yin, 2003). However, this research uses qualitative data in order to investigate what perceptions respondents have towards the diverse governmental policy instruments. Eisenhardt (1989) argues that usually any number of cases between four and ten is sufficient for this type of study. Moreover, several academic studies stated that it is necessary to use six to ten cases in a multiple case study, in order to satisfy the requirements of the replication strategy (Zach, 2006; Yin, 2003). In line with these academic demands the research consists of six innovation projects in the Dutch energy sector. The multiple cases approach provides the opportunity to study cases that perceived different kinds of support from the government. Therefore, to investigate the influence of government’s policy on innovation project success the multiple case-study approach is highly suitable.

4.2 Case selection

(21)

20 The six selected innovation projects are displayed in the table below.

Innovation project Executing company Governmental policy

Toon; the smart thermostat Eneco Private innovation

Blue Energy Eneco Private innovation

Box Freezer Asten Vriescentrale B.V. EOS-Demonstration

High power system for PV-applications (HiPe)

Masterfold EOS-Short term

RotorFlow; for better prediction of wind turbine behavior

Energy research Center the Netherlands (ECN)

EOS-Long Term

Floating Lidar Eneco Topconsortia for Knowledge and

Innovation

4.3 Data collection

An advantage of a case study is that a broader range of data collection tools can be used in order to gather information (Yin, 1994). Through multiple sources of evidence the construct validity of this multiple case study is strengthened. The research starts with desk research, which provides several secondary sources, such as written reports, websites and literature concerning innovation projects, success measures, energy transition and governmental policies. Secondly, interviews will provide primary data. The interviews were conducted through a semi-structured approach, as this result in rich and detailed data (Pegram, 1999; Eisenhardt & Graebner, 2007). For the conducted interviews, a semi-structured interview protocol was used; starting with a general introduction of the research topic, continued by more general questions regarding the innovation project (control variables) followed by specific questions about governmental policy instruments and the success dimensions. The interview protocol is displayed in the appendix and the list of the six interviewees is displayed in the table below.

Name Function Organization Innovation project

Bijvoets, G. (Glenn) Chief Innovator Eneco Toon – The Smart

Thermostat

Bijvoets, G. (Glenn) Chief Innovator Eneco Blue energy

Hendrickx, J. (José) Director/owner Asten Vriescentrale BV Box Freezer

Van Zwam, A. A. (Arno)

Project Manager R&D Mastervolt High power system for PV-applications

(22)

Governmental influence on innovation project success in the Dutch energy sector 21 Centre of the Netherlands prediction of wind turbine behavior Heickmann, F. J. V. (Floris)

Interface Manager Eneco Floating Lidar

4.4 Variables

The variables that are used in this research are defined and operationalized in the table below.

Variable Definition Reference Operationalization/

interview question

Policy instruments

Regulations The use of measures taken by

governmental units to influence people

(formulated rules and directives which mandate receivers to act in accordance with what is ordered in these rules and directives).

Vedung, 2003

What did the government do for the project when it comes to using

regulations?

Financial support Handing out or taking away of material resources while the addressees are not obligated to take the measures involved.

Vedung, 2003

What did the government do for the project when it comes to financial support?

Knowledge sharing Attempts at influencing people through the transfer of knowledge, the communication of reasoned argument, and persuasion.

Vedung, 2003

What did the government do for the project when it comes to knowledge sharing?

Dimensions of innovation project success

Achieving project goals The achievement of the pre-determined goals of the innovation project

Lipovetski et al., 1997; Shenhar et al. 2001

Are the project goals achieved?

Commercial success To what extent the innovation project can be seen as a commercial success according to the project leaders

Did this project provide commercial success for the company?

Support sustainability goals

Contribute to achieving sustainability goals of the Dutch government that are agreed to in the EU for 2020

In which way does this project contribute in achieving the

(23)

22

4.5 Data analysis

The analysis of data is one of the most difficult aspects of case study research (Yin, 1994). In this research there is chosen for a three steps coding system for analyzing the data gathered from the interviews. This data analyzing system consists of open coding, axial coding and selective coding (Boeije, 2005).

1. Open coding: The written test is reviewed to establish the major themes in the data and to structure the first results. Themes were connected to the research questions and to subjects that were raised during the interviews.

2. Axial coding: After the major themes and concepts were structured, smaller themes and relations and insights are identified. Substance analysis of the collected data was used in order to reduce the volume and identify core consistencies and meaning. Data considered irrelevant to answering the main research question was discarded (Patton, 2002).

3. Selective coding: During the last step the analyses of the structured data is made. The data is presented in a qualitative data matrix, which is a table with two axes. The columns on the horizontal axis give the respondents; the rows on the vertical axis give the topics from the topic list that guided the interviews. The cells are filled with abbreviated statements made by respondents on subjects within the topics (Bijlsma-Frankema & Droogleever Fortuijn, 1997). With a comparative analyses it is examined how the codes relate to the innovation projects. The relations showed in the matrix give results which enable us to test the propositions and give answer to the research question. With comparative analyses the findings of the case studies are compared with already existing literature on governmental transition policy in the discussion chapter.

4.6 Optimizing the quality of the measurement

4.6.1 Reliability

(24)

23

4.6.2 Validity

According to Yin (1994) validity can be tested on three dimensions, namely: Construct validity; establishing correct measures for the concepts studied variables, internal validity; establishing a causal relationship, whereby certain conditions are shown to lead to other conditions and external validity; establishing the domain to which a study’s findings can be generalized. To maximize validity on these three dimensions this research used the following methods:

Construct validity: The construct validity of this research is strengthened by data triangulation. Data triangulation is to study the same cases with different approaches (Yin, 1994). In this research desk research and semi-structured interviews are used as the sources of evidence.

Internal validity: To increase internal validity a pattern-matching logic is used to analyze data. Pattern-matching compares pattern shown in the cases with the in the theoretical framework developed propositions If the patterns are similar, the results strengthen the case study’s internal validity (Trochim, 1989).

External validity: To maximize external validity of this research, a multiple-case design is chosen (Verschuren & Doorewaard, 2005; Yin, 1994). Cases are selected based on replication logic. Replication logic means that the cases either predicts similar results (literal replication), or contrasting results, but for predictable reasons (theoretical replication) (Yin, 1994). For the innovation projects theoretical replication is used. The governmental influence differs and therefor it is expected that results will be contrasting.

4.6.3 Generalizability

The research took place in the Dutch energy sector, which is due to the need for the transition a highly specific industry and is incomparable to any other industry, which limits it generalizability. Another limitation regarding the generalizability is the sample size. This multiple case-study consisted of six innovation projects in an industry where thousands of innovation project have taken place. The projects are selected with the most common techniques but it is hard to conclude that this sample size is representative for the whole industry.

(25)

24

5. Results

The result section is divided into the six different innovation projects. The cases are treated in order of amount of governmental support, starting from no support to much governmental support for the innovation project. Each paragraph starts with a description of the possible function of the innovation project followed by the results about the use of governmental policy instruments. These results will be the answer to the sub-research question (3): To what extent were governmental policy instruments used during innovation projects? Subsequently, the results of the innovation projects concerning the successfulness of the innovation projects are described, which will give answer to the last sub-question (4): Which innovation projects can be seen as successful? The basis of these results is the qualitative data matrix; the matrix is displayed in the last paragraph of this chapter.

5.1 Toon

Total project costs Unknown

Number of participants 2 Technical complexity High

Sector Energy - savings

Duration 2 years

Toon is an innovation project started by Eneco. It is a revolutionary thermostat that gives consumers insight into their energy use. Eneco started the innovation project with one partner, Quby, who had the technology which was needed for this innovation. The display of the thermostat shows in simple graphics and bar charts how much energy is consumed and the status of the current energy usage. The cost of the consumption is also displayed according to personal energy tariffs. This innovation could have major advantages. Consumers would have insight into their energy usage, and as a consequence, consumers are able to use less energy. This advantage corresponds with the exploiting potential energy savings goal of the European Union that the Dutch government agreed to.

(26)

25 (4) The goal of this project was to become the first energy firm with a smart thermostat and to protect this thermostat with patents. This goal is accomplished. Evidence is the KIWA-certificate; this certificate acknowledges the quality. It brings Eneco ahead of the market because they were the first energy company with the certificate for a smart thermostat. According to Bijvoets patents protect the innovation, so Eneco achieved both the project goals. Now that Toon is on the market, Eneco is able to take competitive advantage from the innovation. Eneco gives new clients the opportunity to change energy suppliers, and in exchange the customer gets a free Toon. For existing clients Toon is for sale. Other companies like NUON and Essent also anticipated on the hype that smart thermostats are, but according to several sites for comparing products, Toon is the only one who gives good insight into the total energy usage. Therefore, it is not a surprise that according to Eneco, Toon is perceived as a commercial successful innovation project. The innovation project fits perfectly in the sustainable strategy of Eneco; working together with clients for a sustainable future. The main reason for this is the live updates of Toon. They give customers insight into their energy usage and the costs for this consumption. With this insight, customers are able to compare their usage to previous hours, days or months and are able to save on their usage. Therefore, also on the third success dimension Toon can be seen as successful.

5.2 Blue energy

Total project costs 300,000 euro

Sector Energy - Water

Duration 6 months

(27)

26 (3) Eneco invested 300,000 euro in this innovation project and could have made use of one of the EOS-regulations of the Dutch government. They were positive about this innovation project because of the possible contribution to the transition in the energy sector. Just like the innovation project Toon, Eneco believed in the competitive advantage of this project. So again Eneco decided to not make use of a cost reduction option which the government offers. However, Eneco, Wetsus and Redstack needed some governmental help that did not affect competitive advantage. According to Bijvoets, the government was able and positive to give permits for the testing phase of the innovation project.

(4) The goal of the project of Eneco was to be the first energy firm that was able to extract energy out of sweet/salt water and gain a competitive advantage from the innovation. After a few months they concluded the size of the project was not sufficient to meet project goals and Eneco decided to stop the innovation project. To create a breakthrough innovation the investment needs to be increased enormously according to Bijvoets. Ending the project can immediately be seen as a failure on success dimensions one and two. With the knowledge that they already became the partners, Eneco started a new project. Nowadays blue energy is an energy source. It can thus be concluded that the innovation project Blue energy of Eneco contributed with exploring the possibilities on blue energy to governmental sustainability goals.

5.3 Box Freezer

Total project costs 3,500,000 euro

Sector Energy - Savings

Duration 1 year and 3 months

About 8-10% of the Dutch electricity consumption comes from cooling and freezing. The box freezer is an innovation project of Vriescentrale Asten BV (VCA). With the box freezer from the Australian company Milmeq and an energy efficient designed cooling installation by Cofely Refrigeration, this project wants to make freezing and cooling more efficient. This demonstration project should show the possibilities of combining existing techniques. If the demonstration project succeeds it will contribute to the energy savings and CO2 reductions goals of the EU for 2020.

(28)

27 EOS-regulation for demonstrations projects. This subsidy programs provides a contribution for the costs of the innovation with a maximum of 800,000 euro. Calculated through the methodology of the EOS regulations the project costs are set on 1,500,000 euro for assigning subsidy. With total project costs of 3,500,000 euro, the financial support of the EOS-regulation is 17% of the investment (Public report: Demonstration Box Freezer VCA). Besides this financial support of the government, VCA made use of the EIA and the VAMIL regulations which also gives financial support to the innovation project. The goal of the energy investment deduction (EIA) regulation is to support investment in sustainability. 41, 5% of the costs for investing in sustainability could be subtracted from the net profit of the company. The random depreciation environmental deduction (VAMIL) enables companies to depreciate the investment faster to create to decrease net profit and optimize tax advantage. Hendrickx stated: ‘Due to the EIA and VAMIL regulations, investing in sustainability was far more attractive for us’. There were no regulations that influenced this project. Because of the specific knowledge there was also no knowledge input in this innovation project from the government according to Hendrickx.

(4) The goal of the Box freezer was twofold; first, VCA wanted to reduce the energy usage during the freezing process; second, they wanted to make the freezing process less labor-productive. Both goals are achieved: for VCA the energy savings are 2, 7 million Kwhand the reduction of CO2 emissions are 3.183 ton a year. Also, the reduction on labor is significant. The amount of labor is reduced from seven to three employees whose productivity is increased with 25%. The result of the project is a saving of five fulltime employees (Public report: Demonstration Box Freezer VCA). According to Hendricks, the results of the innovation project are above expectations and exceed the project goals. Through the accomplished project goals, which result in energy savings and the decreased need of manpower, the payback time of the innovation project is much shorter than the life cycle of the Box Freezer. Therefore, VCA perceives this project as a commercial success. Through the savings on energy usage and the reduction of CO2 emission the innovation project positively contributes to two of the EU goals for 2020 and it can be seen as successful on success dimension 3.

5.4 HiPe

Total project costs 1 750 000 euro

Sector Energy – Solar

(29)

28 systems for PV-applications (HiPe) aim at developing a new type converter. The project is coordinated by the company Mastervolt. They executed the project with several partners: Technical University Delft, Technical University of Eindhoven, University of Barcelona, KEMA, Arsenal Research, Flex Power Grid Lab, and RvO Design. When the use of PV-systems increase the amount of energy delivered back at the energy grid also increases. Current converters deliver all generated electricity back to the grid. However, with more PV-systems in a local area this will overload the energy grid on sunny days. This new innovation projects develops a converter that controls the delivering of electricity to the grid. This ensures the well-functioning of the energy grid. When this project is fulfilled it should positively contribute to the percentage renewable energy (14% 2020). Through the new converter the concentration of PV-systems can be much higher.

(3) ‘The HiPe project chose to make use of financial support to decrease the risk of the investment in this innovation project’, as stated by Van Zwam. The project is supported by the EOS-regulation for short term research. This consists of a financial contribution for research activities and development activities. It consists of a contributing to the costs for research and developing activities. The subsidy is determined through calculating the weighted average of 50% of the research activities and 25% of the developing activities. For this project the financial support was 34% of the budgeted costs. According to Van Zwam, the budgets for projects that want to take part in the EOS program are consistently too small, companies are scared to be dismissed, and deliver a budget that will not be sufficient to execute the entire project. Therefore, the financial support of the government for this innovation project is set on 26% of the total costs. This project did not make use of any regulations or information. However; in the future Van Zwam hopes that governmental regulations make converters that control electricity delivery compulsory.

(30)

29 because of their presence on the German solar market. It is also important to mention that with the expected growth of the Dutch solar energy market, the converter of Masterfold will be needed in the Netherlands as well and contribute in that way to the governmental goals for a sustainable future. Van Zwam states: ‘We do have the knowledge and expertise; as funny as it may sound, we wait for a problem to occur in the Dutch energy grid’.

5.5 RotorFlow

Total project costs 1,000,000 euro

Sector Energy - Wind

Duration 6 years and 4 months

Most of the wind turbines are placed in offshore wind parks. The increasing size of this turbines results in relatively flexible constructions; these turbines are more sensitive for instabilities through closely spaced excitation and system frequencies. The RotorFlow project tries to significantly improve the quality of the predictions of wind turbine behavior. Through fundamentally better basic physical modeling of wind turbine aerodynamics without using the math intensive Navier-Stokes codes this should be possible. If RotorFlow points out to be a successful in predicting the behavior of the wind turbines it decreases the risk of investment in offshore wind parks and therefore it will help in achieving 14% of renewable energy in 2020.

(3) Energy research Center the Netherlands (ECN) started this project and combined their knowledge and innovation budget with the financial capabilities of the Dutch government. RotorFlow made use of the EOS regulation for long term projects. For this project, it consisted out of a financial contribution of 50% of the project costs. No governmental regulations are used during this innovation project. Information was not shared; according to Van Garrel, the government lacks the knowledge to help with such technically complex projects

(31)

well-Governmental influence on innovation project success in the Dutch energy sector

30 known problem for private/public innovation projects. A solution could be to implement two budgets; one for the technical innovation and one for the market introduction; these budgets are controlled by different people (Van Garrel). Because of the inactivity of the developed software this project is a commercial failure and it does not support the government in achieving their goals although it has the potential to succeed on both dimensions in the coming years.

5.6 Floating Lidar

Total project costs 1,500, 000 euro

Sector Energy - Offshore wind

Acknowledgement: The Floating Lidar innovation project is still running. Therefore, the results must be seen as assumptions. This project is supported by the platform FLOW. This platform is a precursor of the new policy of the Dutch government; innovation projects are supported in the same way as by the new established Topconsortia. Because this project is executed with the support of the new policy its relevance for this research is high. Therefore the decision was made to make the best prediction possible on each the three success dimensions in consultation with the project leader.

The Floating Lidar is a private/public innovation project of Eneco and RWE. It aims at reducing uncertainty in wind prediction on sea. For offshore wind parks big investments need to be made. The profitability of these investments depends heavily on the ability to predict and deliver maximum power output at competitive rates. With better prediction of wind speed, the risk of the investments can be reduced. The Floating Lidar is a mark in the sea with a laser on it. This laser measures the wind speed at all time. When succeeding in better prediction the Floating Lidar contributes to investment in offshore wind parks en therefore to the increase of renewable energy.

(32)

31 available knowledge in the sector was available for this innovation project. The consequence of the knowledge input is that all newly created knowledge has to flow back into the industry. In the testing phase government also cooperated with permits concerning marks at sea.

(4) The goal of the Floating Lidar project was to predict wind speed on sea with a laser on a buoy. Judging the first results, the project will be successful. By better predicting the wind speed, the risk for placing wind turbines on sea will be reduced and will lead to higher efficiency and returns for offshore wind parks. Even though the project goals will be achieved, Heickmann states that the size of the project is insufficient to create a commercial success: ‘the successfulness of the project must be seen in making a next step in the technology for predicting wind speed’. Through making wind energy cheaper and more attractive for customers the Floating Lidar project will contribute in the investments in offshore wind and as a consequence, in the percentage of renewable energy.

5.7 Comparative analysis

On last page of this paragraph the qualitative data matrix is displayed. On the basis of this matrix the influence of policy instruments on the success dimensions is measured through a comparative analysis. Through this analysis the three propositions that were presented in conceptual model chapter are tested.

5.7.1 The influence of regulations

Proposition 1: The use of regulations by the government increase the chance for innovation project success on all three success dimensions

Two out of the six innovation projects made use of regulations, the Blue Energy and the Floating Lidar project used permits for their testing phase. Even though both project were not successful on all three dimension the permits increased the chance for success on the dimensions. The cooperative attitude of the government is linked to the importance they give to renewable energy; the permits used in the innovation projects are not given away that easy for project that are not focused on the energy transition.

(33)

32 Commercial success is not expected but the chance for achieving this is increased due to the regulations. Due to the positive effect of the used regulations proposition 1 is supported.

5.7.2 The influence of financial support

Proposition 2: Financial support of the government negatively influences the chance for achieving projects goals and commercial success; however it has a positive effect on the achievement of supporting the sustainability goals

Four out the six innovation projects made use of subsidies. For achieving project goals we can see that all projects that are partially financed by the government succeeded on this dimension. The only project that failed on achieving project goals, Blue Energy, failed because of the high investment costs. This could have been compensated by accepting financial support of the government. For the commercial success dimension it can be seen that projects with the most governmental support are not successful on this dimension. Exception is Blue Energy; it financed with private money and also was not successful on this dimension.

For the last success dimension, supporting sustainability goals, it is remarkable to see that two of the most supported projects fail. The projects have problems with market introduction which is according to Bossink (2003) linked to the governmental influence. However, there must be stated that the RotorFlow and the Floating Lidar projects would not have been carried out without the financial support. Therefor the success of Floating Lidar is due to the financial support.

Proposition 2 is partly supported by the findings. Financial support indeed has a negative influence on commercial success. But according to our results it increases the chance for achieving project goals. For the sustainability support goals the influence is twofold. First must be acknowledged that financially supported project often fail in contributing to sustainability goals. Secondly the results show that several innovation projects would not have been carried out without financial support. Therefore the influence of financial support on success dimension three is neutral in this research.

5.7.3 The influence of sharing knowledge

Proposition 3: Knowledge sharing through the government increases the chance for innovation project success on all three success dimensions

(34)

33 that the government would not have been able to deliver this. According to the results support for establishing relationships for transferring knowledge also was not provided. When innovators needed extra knowledge external private partners are included in the innovation project. Only the Floating Lidar project gained knowledge input that was partially arranged by the government, the government created a platform, FLOW, which stimulated and criticized the project. According to Heickman this input made sure the project was criticized from the start and therefore needed an excellent preparation. However, the success of this project did not depend on the knowledge input. The specific knowledge was also not available in the platform. For none of the six innovation projects knowledge sharing increased their chance on success; therefore proposition 3 is not supported.

Propositions

Supported/ Not supported 1 The use of regulations by the government increase the chance for innovation

project success on all three success dimensions

Supported

2 Financial support of the government negatively influences the chance for achieving projects goals and commercial success; however it has a positive effect on the achievement of supporting the sustainability goals

Partly supported

3 Knowledge sharing through the government increases the chance for innovation project success on all three success dimensions

Not supported

5.7.4 Qualitative data matrix

(35)

34

Project Toon Blue energy Box Freezer HiPe RotorFlow Floating Lidar

Interviewee G. Bijvoets G. Bijvoets J. Hendrickx A. van Zwam A. van Garrel F. Heickmann Governmental influence

Regulations For this project we did not need the government help us with regulations The government was enthusiastic and helped us with permits for the testing phase

No regulations of the government influenced this project

The government could help this project by making it compulsory for individuals who invest in PV systems No regulations of the government influenced this project The government helped us in the testing phase in a very cooperative way Financial support Financial help means that knowledge needs to be shared, which would be negative for us since we invent to make money out of it

Afterwards, financial support could have been a help for succeeding this project

The financial support shortens the payback time of our

investment. The support consisted out of EOS-demonstrations, EIA and VAMIL regulations

The budget from which the financial support is calculated was too low Without the governmental financial support this project could not have been executed

From the flow project all projects are supported with 50% of the costs % of total costs 0 0 21 25 50 50 Knowledge sharing

Toon was our first innovation that led to a physical product

The knowledge was available but the investment became too big

We believed that we had the knowledge to be successful, and the government agreed With our knowledge we have the solution for a problem that could occur in the coming years

The government lacks the knowledge to help us with such technically complex projects

The platform created by the industry and the government criticizes the project from the presentation

Success dimensions Project goals We worked with

a team of specialists for two years but we achieved our goals We decided that the riskiness of the extra investment was too big

The Box Freezers performance is better than we expected The new converter is developed and is already in use The developed software is ready for market introduction The goal is to further develop the technique, which we already did Commercial success

We are the first energy supplier with a smart thermostat and there is a demand on the market We could have been able to extract energy but we are a commercial organization and we had to stop this project

The work can be done by less people losing less energy, a profitable development for a commercial organization The developed technology enables us to sell our products to the German market We exceeded the budget for the technical innovation; therefore, there is no budget to go to the market This technique is too underdeveloped to aim at commercial success Support sustainability With this thermostat, consumers are able to see where they could possibly save energy Our partners started a new project and succeeded in extracting energy from water power

This project gives us a reduction of 3,2 kton CO2 emission The converted is compulsory in Germany and supports sustainability but in the Netherlands there is no demand for our product

Since the product is not in use we are not able to reduce the riskiness of investments in the offshore wind sector By better predicting wind speed investment in off shore, wind parks will be more profitable

Made use of policy instrument/ Successful

Dit not make use of policy instrument/ Unsuccessful

(36)

35

6. Discussion

In this section impact/relevance of the findings of the research are placed in the light of the existing literature on the energy transition.

A successful innovation system entails more than pricing undesirable developments and subsidizes innovation in the right directions. A system needs to be a combination of companies, knowledge institutions, educational institutions, financial organizations, intermediaries and governments (Boschma et al., 2002). According to the previous statement this research concludes that the Dutch innovation system concerning the energy transition is unsuccessful. The influence of the government mainly consisted of financial contribution. Which was also concluded by Vedung (2003); he argued that that subsidy is a popular political tool in the Netherlands (and in whole Western Europe). The results show that projects with subsidies are more likely to achieve project goals, which conflict with the findings of Agnener (2002). He stated that high subsidies increase the chance of failure, because projects with more risk are carried out. Another finding is that the most successful innovation projects would also have been carried out without subsidy. Without financial support from the government the best innovations are still profitable. However, for some sub-sectors of the energy sector the role of the government is important. These subsectors have problems with their competitiveness and therefor market pull would be low if the government would not support these sectors. This corresponds perfectly with the findings of Kemp and Nill (2009); they stated that the importance of governmental instruments increases when market pull is low.

(37)

36 introduction, according to Van Garrel the government lacks the knowledge to value the innovation. If they had more specific knowledge the budget could be adjusted in order to introduce the innovation to the market. This corresponds with Vedung (2003); he stated that the effectiveness of economic and regulatory instruments is to some extend contingent upon authorities’ ability to discover and oversee the activities to be controlled (Vedung, 2003). The second market introduction problem concerns the HiPe project. During this project a new converter was invented to enable large scale usage of PV-systems. With the EOS-regulation the government subsidized this project, however without making this converter compulsory this innovation is useless. A stimulated market introduction by making it compulsory would fit in the transition approach of the government. This approach consists of long term thinking that should be seen as a framework for short-term policy (Kemp, 2010).

When the government provides subsidies they should concern what the contribution of the innovation project will be for the Dutch energy market. According to the results of this research it seems that they lack the knowledge and interest to do this, which was also concluded by DVEP (2013). They argue that the lack of knowledge and absolute will are the reasons for the failure of the innovation policy. While lacking knowledge the government should create an infrastructure for companies and innovators to share their knowledge (Rotmans, 2011). This is according to the findings only created with the new policy concerning the Topconsortia. This policy can be seen as an acknowledgement of the government, stating that they lack knowledge on these specific themes. The finding that in previous years the knowledge sharing instrument was not used corresponds with the findings of Hisschemöller et al. (2010). They argue that there is almost no coalition between companies, knowledge institutions and government. Which is in contrast with one of the goals of the government according to Kern and Smith (2008); they stated that one of the goals of the Dutch government was to bring together knowledge and expertise of different companies, knowledge institutions and governments. This lack of coalition is remarkable because this coalition has the potential to create breakthroughs in the energy transition (Rotmans, 2011).

(38)

37

7. Conclusion

The conclusion of this research is based on the analysis of the data in paragraph 5.7. The level of governmental influence is linked to the success in innovation project in order to provide a satisfying answer to the main research question:

What is the influence of governmental policy on the success of innovation projects in the Dutch energy sector?

The influence of the government on the success in innovation projects is complex. A major problem concerning the governmental influence according to the findings of this research is their lack of knowledge. Due to this lack of knowledge governments are not able to facilitate the innovators in an optimal way. The required specific knowledge was unavailable at the government and they also were not capable of linking sources of knowledge to each other. Concerning the input of knowledge in innovation projects the influence of government was negligible. The influence of the government concerning the use of regulations was also not optimally used. The use of regulations is a successful policy instruments in environmental policy; it influenced the innovation project in a positive way. But due to the lack of knowledge this instrument is not used to its full potential. Most of the influence of the government consisted of financial contributions. Projects that are supported financially are more likely to achieve project goals. However, these supported projects turned out to have problems in achieving commercial success. Several subsidized projects failed to introduce the innovation into the market. The incapability of the government to influence the demand side of innovation projects has big impact on the successfulness of the innovation policy. With more knowledge available at the government they could be able to screen projects beforehand. Now subsidies are given away to support projects that are (currently) not needed in the Dutch energy market. However, there must be stated that the financial contribution of the government triggers innovating projects in non-competitive sub sectors of the market and therefore is the most positive aspect of the government’s policy.

(39)

38

7.1 Implications for theory and practice

The intention of this research was to explore the relationship between government policy and innovation project success. The findings subscribe the need for a sharpened innovation policy of the Dutch government as suggested by the PBL (2013). The government needs to fulfill a facilitating role according to the transition management theory but the findings show the role consists mainly of handing out financial resources. The lack of knowledge of the government and the problems with managing the demand side correspond with findings of previous studies (Bossink, 2002; Kemp & Faber, 2005; Hisschemöller et al.; 2010; Rotmans, 2011).

The government needs to be more proactive when it comes to delivering regulations and sharing knowledge to increase the successfulness of innovation project. To fulfill this proactive attitude in a good way the knowledge level of the government needs to increase substantially. Only when this is accomplished the Dutch government will be able to facilitate innovation projects in the best possible way.

7.2 Limitations

Two acknowledgements have to be made on the gathered data. Firstly, a substantial part of the financial figures that are used in the research could not be checked by secondary sources, which decrease the construct validity. Major reason for this was the unwillingness of some of the innovation projects to share the exact financial figures due to competitive advantage. Therefore, the figures used should be seen as the best estimation possible. Secondly, innovation project Floating Lidar is still running and consequently, it is impossible to conclude the successfulness of the innovation projects. With the results achieved during the innovation projects the estimation is very close to the actual outcome.

The low generalizability of this research was already addressed in the methodology. It is due to the specific character of the industry wherein this research took place; the findings are not applicable to other industries. The other reason is the sample size; this research only reviewed six innovation projects which disables the generalizability of the results throughout the industry.

7.3 Future research

(40)

(41)

40

References

Articles

Andersen, M. S., Dengsøe N. & Brendstrup S. (1999). The Waste Tax (1987–1996) – An Ex-post Evaluation of Incentives and Environmental Effects. Working Report no. 18. Copenhagen: Environmental Protection Agency.

Baccarini, D. (1999). The logical framework method for defining project success. Project Management Journal 25-32.

Bijlsma-Frankema, K.M. & Droogleever Fortuijn, A.B. (1997), “De Kwalitatieve datamatrix als analyseinstrument” Tijdschrift voor Sociale Wetenschappen, Vol. 42 No. 4, pp. 448-59.

Boomsma, T. K., Meade, N. & Fleten, S. E. (2012). Renewable energy investments under different support schemes: A real options approach. European Journal of Operational.

Boschma R.A., Frenken K & Lambooy, J., G. (2002). Evolutionaire economie, een inleiding. Bussum: Coutinho.

Bossink, B. A. G. (2002). The development of co–innovation strategies: stages and interaction patterns in interfirm innovation. R&D Management, Wiley Online Library.

Burck, J., Bals, C. & Bohnenberger, K. (2011). Germanwatch en Climate Action Network Europe. The Climate Change Performance Index, Results 2012.

Cooper, R.G. & Kleinschmidt, E.J. (1987). New products: what separates winners from losers. Journal of Product Innovation Management, 4, pp. 169–184.

Dincer I. (2000). Renewable energy and sustainable development: a crucial review. Elsevier.

Dincer, I. (1999). Environmental impacts of energy. Elsevier.

(42)

41 Lemma BV Utrecht, (2005).

Dvir, D., Lipovetsky, S., Shenhar, A. J. & Tishler, A. (1998). In search of project classification: a non-universal approach to project success factors. Research Policy, 27 pp. 915–935.

Eisenhardt, K.M. & Graebner, M.E. (2007). Theory Building From Cases: Opportunities And Challenges. Academy of Management Journal 50(1): 25–32.

Eisenhardt, K.M. (1989). Building theories from case study research. Academy of Management Review, 14, pp. 532–550.

Etzioni, A. (1963). The epigenesis of political communities at the international level. American Journal of Sociology.

Freeman, M. & Beale, P. (1992). Measuring project success. Project Management Journal, 1 (1992), pp. 8–17.

Foxon, T. & Pearson, P. (2007). Overcoming barriers to innovation and diffusion of cleaner technologies: some features of a sustainable innovation policy regime, Journal of Cleaner Production

Funtowicz, S., Ravetz, J. R. & O’Connor, M. (1998). Challenges in the use of science for sustainable development. International Journal of Sustainable Development 1, pp. 99–107.

Geels, F. & Verbong, G. (2007). The ongoing energy transition: lessons from a socio-technical, multi- level analysis of the Dutch electricity system (1960-2004). Energy Policy, Elsevier.

Hisschemoller, M., Cuppen, E., Breukers, S. & Bergsma, E. (2010) Q methodology to select participants for a stakeholder dialogue on energy options from biomass in the Netherlands. Ecological Economics 69

Kemp, R. & Nill, J. (2009). Evolutionary approaches for sustainable innovation policies: From niche to paradigm? Research policy, Elsevier.

A multiple case-study; The influence of government policy on innovation project success in the Dutch energy sector