Faculty of Economics and Business
Bachelor’s thesis Business Administration
The moderation effect of sustainable entrepreneurship on the
relationship between different business sizes and business’ vitality
Focusing on the entrepreneurial ecosystem of Amsterdam
Author: Jasper Tonn
Student number: 10324968
Supervisor: Roel. C.W. van der Voort
Statement of Originality
This document is written by student Jasper Tonn, who declares to take full
responsibility for the contents of this document.
I declare that the text and the work presented in this document are
original and that no sources other than those mentioned in the text and
its references have been used in creating it. The Faculty of Economics and
Business is responsible solely for the supervision of completion of the
work, not for the content
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Acknowledgement
With the completion of this thesis, I have reached the final step of attaining my Bachelor’s degree in Business Administration at the University of Amsterdam. This research provided me the opportunity to apply and combine many aspects I have learned during this study and it allowed me to put my skills into practice. For this reason and because it was a great experience to get a taste of executing
my own research, I really enjoyed writing my bachelor’s thesis.
I would firstly like to thank my supervisor Mr. R.C.W. van der Voort, for providing me the opportunity to choose this subject for my research. His guidance during the research process and critical insights
helped me to write this thesis. Secondly, I would like to thank the course coordinator Mr. R. van Hemert, for his support and involvement when this was needed. Furthermore, I would like to extend my thanks to Ms. R.E. van Geffen, for her valuable lessons and suggestions concerning data statistical analysis. In addition, I would like to express my appreciation to the respondents who have taken the trouble to participate in the survey, which provided the necessary data for this research. Last but not
least, I am very grateful to my family and friends for their support. Especially to my loving girlfriend Debby, who was always there to help me and has been putting everything aside for me to
successfully graduate.
I sincerely hope you enjoy reading this thesis. Kind regards,
Jasper Tonn
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Abstract
Recent decades, human activities are increasingly threatening to bring irreversible damage to the environment, its resources and life sustaining ecosystems. The current economic system is the main cause of the enormous pressure that is put on the planet. Therefore, companies will have to develop innovative solutions by means of sustainable entrepreneurship. This is also important for the companies themselves, to remain successful and create a vital entrepreneurial ecosystem in the future. The aim of this study is to gain insights, regarding this topic, into the entrepreneurial ecosystem of Amsterdam. The goal is to find out if sustainable entrepreneurship improves the vitality of businesses in this ecosystem. This would be a good incentive towards a more sustainable future. The following research question is formulated: Moderated by degree of sustainable entrepreneurship, how do different business sizes relate to the business’ vitality, focusing on the entrepreneurial ecosystem of Amsterdam? To answer this question, a cross-sectional study was conducted by means of an online survey, completed by 31 respondents. The survey was developed on basis of current developed frameworks measuring business’ sizes, degree of sustainability and vitality. The study reveals that larger businesses are more vital than smaller businesses in Amsterdam and thus have a greater positive influence on the vitality of the Amsterdam Entrepreneurial Ecosystem. However, no positive relation is found on a business’ degree of sustainability and its vitality. Also, no moderating effect of sustainability was found on the relationship between different business sizes and business’ vitality. Nevertheless, the developed research methodology forms a good foundation for further research on this topic and in extension, opened a door for applying similar research on different types of ecosystems.
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Catalogue
1. Introduction ... 4 2. Literature review and development of conceptual model... 7
2.1 Conceptual model and hypotheses 7
2.2 Definition of (variable) concepts, their measures and indicators 8 2.2.1 Defining the concept of 'Entrepreneurial ecosystem' 8
2.2.2 Theory on measuring business size 9
2.2.3 Theory on measuring business vitality 10
2.2.4 Theory on measuring sustainable entrepreneurship 13 3. Methodology ...15
3.1 The survey 15
3.2 Business size 15
3.3 Measuring degree of sustainability 15
3.4 Measuring vitality 16
3.5 Data collection approach 17
4. Results ...18
4.1 Recoding, reliability and scale means 18
4.2 Descriptive statistics 19
4.3 Analysis of main effects and interaction effect 20
5. Discussion & conclusion ...22 5.1 The relationship between different business sizes and the business' vitality 22 5.2 The relation between a business' degree of sustainability and the vitality of
businesses in Amsterdam 23
5.3 The moderating effect of a business' degree of sustainability on the relation
between different sizes and the vitality of businesses in Amsterdam 24
5.4 All-encompassing limitations and recommendations 25
5.5 Conclusion 26
References ...28 Appendix 1 ...30 Appendix 2 ...34
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1. Introduction
Recent decades, human activities are increasingly threatening to bring irreversible damage to the environment, its resources and life sustaining ecosystems. Due to this, critical stress is already clearly manifested in the air, water and ground, not to mention Earth’s climate, plant and animal species. The current economic system, which can be seen as the main cause of the enormous pressure that is put on the planet, is only able to provide the needs for a quarter of the people that live on Earth. Even more worrying is that over the next decade, due to huge population growth, there will be twice as many consumers and producers (UN World population prospects, 2015). It is therefore of great importance that the current economy changes to a more sustainable economy. Its conventional ways of consuming the earth must be improved by focusing on sustainable and innovative developments. According to Nidumolu, Prahalad & Rangaswami (2009), traditional approaches to business will therefore collapse. Companies will have to develop innovative solutions by means of sustainable entrepreneurship, in order to prevent further environmental pollution, climate change and other damage to quality of life. Sustainable entrepreneurship moreover, is no longer about the environment and climate alone. Nowadays, sustainable development within companies can save a lot of costs, builds trust and a good reputation, plus it leads to innovation (Cohen et al., 2007; Weidinger et al., 2013;). For these reasons, sustainable entrepreneurship can also be important for the companies themselves, to remain successful and create a vital entrepreneurial ecosystem in the future. Nidumolu, Prahalad & Rangaswami (2009) therefore state, that executives must recognize “a simple truth”, that sustainability is innovation. Stam & Spigel (2016) define entrepreneurial activity as the process by which individuals create opportunities for innovation. This innovation will eventually lead to new value in society. Therefore, entrepreneurial activity is a more intermediary output, and this new value is the ultimate outcome of a vital entrepreneurial ecosystem (Stam & Spigel, 2016).
So, in short, Stam & Spigel (2016) say that entrepreneurial activity within a vital entrepreneurial ecosystem leads to innovation and Nidumolu, Prahalad & Rangaswami (2009) say that sustainability is the most essential form of innovation. This could lead to the following questions that form the basis for this research. Is it possible that a vital entrepreneurial ecosystem leads to sustainable development? But more importantly as a driving force to a sustainable vital ecosystem: What does sustainable entrepreneurship add to the vitality of an entrepreneurial ecosystem? Innovation is often accompanied by more vitality in business (Stangler & Bell-Masterson, 2015; Taich et al., 2016). Hence, is sustainable entrepreneurship, besides that it is essential is for the preservation of the earth and for
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ensuring adequate quality of life in the future, also adding value to the vitality of an entrepreneurial ecosystem? Is it possible that, if entrepreneurial activity focuses on sustainable development, this has a positive effect on sustainable vitality of an entrepreneurial ecosystem? That would make sustainable entrepreneurship even more attractive for business.
This thesis is about answering these questions, focusing on the entrepreneurial ecosystem of Amsterdam. Amsterdam can be seen as an entrepreneurial ecosystem, in a way that interdependent actors form a community that enables and supports entrepreneurial action within a certain environment (i.e. city of Amsterdam) by which entrepreneurship is enabled or constrained (Stam, 2014). The research aims to identify the moderating effect of sustainable entrepreneurship on the relationship among different sizes of businesses in Amsterdam and their vitality. Also, it will examine whether sustainable entrepreneurship has a positive relation with the vitality of the Amsterdam entrepreneurial ecosystem on its own. The ecosystem’s vitality will be determined by measuring multiple vitality indicators and measuring the degree of sustainability of businesses operating in that ecosystem. Vitality will be measured through a framework of indicators that is developed and tested by Stangler & Bell-Masterson (2015) and Taich et al. (2016). Sustainability will be measured through multiple sustainable business model archetypes, provided by Bocken et al. (2014).
As Stangler & Bell-Masterson (2015) indicate, it is intended that their research can be used for future work like this, focussing on developing measures for specific programs and actions within an ecosystem. Bocken et al. (2014) also developed their framework of sustainable business model archetypes, with the intention to be used in future research practice as common language. Because these theories and frameworks that are developed in this work are relatively new, little research has been done and the corresponding frameworks have not been applied yet on this particular ecosystem of Amsterdam. A sustainable and vital environment of Amsterdam, which fosters entrepreneurship and a prosperous viability in the city is in the interest of the municipality of Amsterdam, as well as other stakeholders (i.e. inhabitants; non-profit organisations; entrepreneurs). Therefore, it is interesting from a scientific, as well as a contemporary social and economic point of view, to fill this knowledge gap with regard to Amsterdam. Multiple parties could benefit from the findings of this study.
To ensure that the entrepreneurial ecosystem of Amsterdam is examined as completely as possible and to prevent that the results are biased, businesses of different sizes will be involved in the data collection. The different businesses involved will be divided by research in three sizes, according to the EU classifications of business size. Data collection will be done through issuing surveys to a sample of
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100 different supervisors of businesses within the entrepreneurial ecosystem of Amsterdam. These surveys will measure the size, degree of sustainability and vitality of all the businesses involved. We structure this research in the following chapters. The next section will mainly provide a review of the literature on measuring vitality of a business (environment) and measuring the degree of sustainable entrepreneurship within a business. Furthermore, literature on defining an entrepreneurial ecosystem will be discussed. Thereafter, to solve the research question based on those theories, the conceptual model with its hypotheses will be formulated and explained. Subsequently, another section will describe the research design and methodology. The results of the study will then be analyzed and clarified, whereafter another section will discuss these results and will come to a conclusion.
RQ: Moderated by degree of sustainable entrepreneurship, how do different business sizes relate to the business’ vitality, focusing on the entrepreneurial ecosystem of Amsterdam?
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2. Literature review and development of conceptual model
Based on the research question, a conceptual model is developed. This was done by translating the research question into several constructs. Subsequently, the constructs were implemented in a model. In order to properly understand the context of these constructs and to get a clear overall image of this research, several important concepts will have to be defined and furtherly explained. This will be done as follows. An explanation of the conceptual model will be given, which serves as the fundament to this research. Thereafter, a literature review will follow for clarification of the context and for conformation of the accuracy of the model.2.1 Conceptual model and hypotheses
As mentioned earlier, Amsterdam’s entrepreneurial ecosystem is key subject to this research. More specifically, this thesis will examine how vital the entrepreneurial ecosystem of Amsterdam is and to what extent this vitality is determined by sustainable entrepreneurship. The research seeks to answer the question whether sustainable entrepreneurship benefits the vitality of the ecosystem with respect to conventional entrepreneurship and to what extent this ecosystem is (sustainable) vital. To investigate this, the following conceptual model was designed, as illustrated in figure 1.
The model divides the businesses participating in the research into three groups, namely small, medium-sized and large businesses. Subsequently, the vitality of these businesses will be determined, after which there will be examined whether there is a (positive) relation between a business’ size and its vitality. Next, it will be examined whether the degree of sustainable entrepreneurship within the businesses has a moderating effect on this relationship and whether this variable has a direct positive effect on the vitality of the businesses. The businesses in this model, function as a sample of the population (which is the entrepreneurial ecosystem of Amsterdam) and measure in this way its (sustainable) vitality. Based on this model, the following hypotheses have been drawn up.
Medium sized businesses Small businesses Large businesses Degree of business’ sustainability Vitality of businesses Amsterdam’s Entrepreneurial Ecosystem Population H1 H2 H3
Independent variable (IV)
Dependent variable (DV) Moderator variable (MV)
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H1: Larger businesses in Amsterdam are more vital than smaller businesses in Amsterdam and thus have a greater positive influence on the vitality of the Amsterdam Entrepreneurial Ecosystem. H2: The degree of sustainability of a business has a positive influence on the vitality of Amsterdam
businesses, and thus on the Amsterdam Entrepreneurial Ecosytem.
H3: Sustainable entrepreneurship has a moderating effect on the relationship between different business sizes and business’ vitality. So, sustainability leads to greater vitality for larger businesses, and thus to a more vital Amsterdam Entrepreneurial Ecosytem.
2.2 Definition of (variable) concepts, their measures and indicators
2.2.1 Defining the concept of ‘Entrepreneurial ecosystem’
In recent years, studies in the field of entrepreneurship, economic geography, urban economics, and the economics of entrepreneurship have moved closer to each other. This has come through research on the context of entrepreneurship, the increasing interest in entrepreneurship within urban and regional economics and the growing recognition that not all types of entrepreneurship are equally important for economic growth (Stam & Spigel, 2016; Auerswald, 2015). These developments, and the need for understanding the dynamics of entrepreneurial innovation in relation to economic growth, have culminated in development of an integral framework: the entrepreneurial ecosystem (Auerswald, 2015). Stam (2014) defines this construct as “an interdependent set of actors that is governed in such a way that it enables entrepreneurial action. It puts entrepreneurs center stage, but emphasizes the (environmental) context by which entrepreneurship is enabled or constrained”. However, the entrepreneurial ecosystem is a rather new concept and therefore, there is no generally accepted definition yet and not all aspects of the concept are yet defined. The way Stam (2014) has approached defining the concept of ‘entrepreneurial ecosystem’ is by analyzing its two components, ‘entrepreneurial’ and ‘ecosystem’. ‘Entrepreneurial’ refers to entrepreneurship, which according to his theoretical research, is defined as a process by which opportunities to create novel goods and services are discovered, evaluated and exploited. In other words, individuals create opportunities for innovation, that will eventually lead to new value in society. (This is also where for this research the link can be made with sustainability within businesses, because sustainability is now often seen as the key driver of innovation (Nidumolu, Prahalad & Rangaswami, 2009)). The second component, ‘ecosystem’, emphasizes that entrepreneurship takes place in a community of interdependent actors, which is where Stam (2014) refers to in the second part of his definition.
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So, with regard to this research, an important difference between the entrepreneurial ecosystem approach and other economic development concepts, is the role of entrepreneurship. Namely, it recognizes entrepreneurship as key process in generating and maintaining the ecosystem, rather than just seeing it as an outcome of the ecosystem. Also, it sees the direct role of the government as more limited than in previous approaches (Stam, 2014). This makes it interesting to investigate the vitality of different types of entrepreneurship and their influence on the vitality of an entrepreneurial ecosystem itself. Furthermore, literature is not clear about what the adequate unit of analysis is of an entrepreneurial ecosystem and an appropriate scale is not yet defined. This could be the national economy, the regional economy, a sector, or a corporate system. All scales could be relevant. In this research, the regional economy of Amsterdam is used as scale.
2.2.2 Theory on measuring business size
In Amsterdam, businesses of all types and sizes are active and interacting with each other. They form the Amsterdam entrepreneurial ecosystem. These businesses each have their own contribution to the vitality of that ecosystem. One business is more vital and/or more sustainable than the other. Whether the degree of vitality and sustainability are related to each other, is not yet clear. The vitality of a business could also be based on its growth stage and size. For instance, could it be that large companies are generally more vital thanks to their volume, than small businesses and that they are therefore of greater value to a vital entrepreneurial ecosystem? Or is it the opposite, are small companies more vital for some reason? According to Audretsch (2012), a consistent and compelling set of results have emerged regarding business size and growth: 1. Growth rates are higher for smaller businesses; 2. Growth rates are higher for younger businesses; 3. Growth rates are even higher for small and young businesses in knowledge-intensive industries. Business growth is an important indicator for the vitality of a business (Stangler & Bell-Masterson, 2015; Taich et al., 2016). For this research, it is therefore interesting to weigh small and large companies against each other, with regard to their vitality. But what is the difference between a large business and a small business? How can size be measured? Figure 2 shows a classification of the size of firms defined by the European Union, according to turnover, the number of employees and the capital employed. These measures will be used in this research for measuring the sizes of businesses in Amsterdam.
10 2.2.3 Theory on measuring business vitality
In addition to measuring the size of the businesses, this research will also have to measure the vitality of businesses. This is because they serve as a sample that assesses the vitality of Amsterdam's entire entrepreneurial ecosystem. As mentioned above, one of the indicators to measure vitality is thus business growth. Stangler & Bell-Masterson (2015) provided a theoretical framework for measuring the vitality of an entrepreneurial ecosystem. They identified twelve measures across four indicators (density, fluidity, connectivity and diversity). Taich et al. (2016) used this theoretical framework to do further research on what the indicators of an entrepreneurial ecosystem are and which of these, best reflect the ecosystem’s vitality. Also in this research, Taich et al. (2016) investigated what indicators of entrepreneurial ecosystems are most valuable for entrepreneurs. Through answering these research questions, they modified three measures from the original framework of indicators (connectivity: quality of network, traded industries, and university presence) – and found four new important measures (bachelor’s degree attainment, business environment, entrepreneurial finance, and patents). Based on the studies of Stangler & Bell-Masterson (2015) and Taich et al. (2016), a framework of indicators could be set up, that provided the essential measures, for measuring the ‘business vitality variable’ in this study. Here is an overview of the indicators, explaining why these are important and how they will be measured in this research.
Density: This indicator is defined by Stangler & Bell-Masterson (2015) as the number of new and young businesses in a given area, the share of employment in those businesses and the density of new young businesses in the high-tech sector of a given area. According to Taich et al. (2016), density is an important indicator because it represents and creates momentum, in the sense that the degree of entrepreneurial presence indicates success of entrepreneurship in the given area, which means that opportunities exist. This also entails a “sense of energy” and more potential business activity. In this research however, the density of new businesses in the high-tech sector is disregarded, because it is very difficult to measure in this research scope. But the other measures should give a sufficient image of the density indicator.
Fluidity: this second indicator is measured by Stangler & Bell-Masterson (2015) through population flux, labor market reallocation and the presence of high-growth firms (in this study explained by another indicator). They state that, because individuals move between cities or regions, these cities/regions “re-sort and react adaptively” to collisions of those individuals. Those collisions are key to idea generation. Namely, an important resource of entrepreneurship is people and vibrancy of entrepreneurship is stimulated through (re)mixing those different people, that have varied perspectives and knowledge obtained from their individual background.
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An opposing view on fluidity however, emphasized by Taich et al. (2016), is that many entrepreneurs simply do not see a lot of movement of people either across sectors or geographically. And given the increased degree of connectivity and “fewer boundaries” (in e.g. communication), knowledge sharing can now be done through many other ways than relocation. Therefore, this is not necessarily an essential indicator for entrepreneurial vitality within a certain region. That is why these measures are taken into account, but more emphasis will be placed on other indicators (modified by Taich et al., 2016).
Connectivity: Both Stangler & Bell-Masterson (2015) and Taich et al. (2016) emphasized that this indicator is extremely important for entrepreneurial vitality. Stangler & Bell-Masterson (2015) state, that “the connections between the elements (of a vibrant entrepreneurial ecosystem) matter just as much as the elements themselves, because it helps entrepreneurs to solve problems, find talent, attract funding, and build the relationships that translate into customers and product innovation.” However, this indicator is difficult to measure due to lack of concrete quantification (Taich et al., 2016). The most important subjects to measure for connectivity anyway, were connections of businesses between programs and resources, the rate of spin-off businesses and mapping dealmaker networks (Stangler and Bell-Masterson, 2015). The latter one is too difficult to measure in this research, but the previous two are still very relevant for measuring connectivity and several more general questions about connectivity of businesses are also added to the survey, to get a reliable image on this indicator. Diversity: Research of Stangler & Bell-Masterson (2015) and Taich et al. (2016) showed that diversity matters as an indicator, because it is a source for entrepreneurship and it indicates a vibrant area. At a national level, research has shown that economic complexity is correlated with growth and innovation (Hidalgo & Hausmann, 2009). Nevertheless, for cities and regions it is also common to specialize in certain economic activities, because specialization brings comparative advantage and economic gains (Stangler & Bell-Masterson, 2015). But a region with a more diverse scope of economic specializations will have even better entrepreneurial outcomes (Stangler & Bell-Masterson, 2015). Therefore, an interesting measure for the diversity indicator, is the diversity of specializations within Amsterdam. The other way diversity will be measured, is in economic mobility (measuring the probability of a business, moving up/down the economic ladder) and the diversity of people working in Amsterdam. Historically, immigrants have a very high entrepreneurial propensity. In the United States for example, immigrants are more than twice as likely to become entrepreneurs as native-born Americans (Reedy, 2015). Hence, the question that will be asked is how many immigrants are working within the businesses participating in this research.
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Centers of commerce: As mentioned before, Taich et al. (2016) used the study of Stangler & Bell-Masterson (2015) as a theoretical framework to do further research on what the indicators of an entrepreneurial ecosystem are and which of these, best reflect the ecosystem’s vitality. In their research, they modified and added some measures from/to the original framework of indicators. This also created two new essential indicators. One of which was ‘Centers of commerce’, measured by the business environment, University presence and the number of high-growth firms. The latter one, accounting for a small share of companies, is responsible for a disproportionate share of job creation and innovation and therefore an important measure (Stangler and Bell-Masterson, 2015). The presence of universities and connecting to them is favorable for solving problems, finding talent, attracting fundings and building relationships that translate into customers and product innovation (Taich et al., 2016). One last measure to this indicator is the cost of doing business, defined as ‘Business environments’. Business environments with relatively low costs of doing business (e.g. low rent, taxes and salaries), reduce the barriers to entry and make it easier to succeed.
Innovation: The second indicator provided by Taich et al. (2016) is ‘innovation’, measured by bachelor’s degree attainment, number of patents issued and other entrepreneurial finance data of businesses within an entrepreneurial ecosystem. Taich et al. (2016) state, that the more individuals with a bachelor’s degree are present within the entrepreneurial region, the easier it is to find talent that entrepreneurs need (for innovation). Another measure for innovation is the number of patents issued by businesses. In many studies, such as in Taich et al. (2016) and Crosby (2000), patents are used to proxy the amount of innovation. However, consider that other studies question the reliability of patents as a measure for innovation, because not all patented inventions prove to be innovations and not all innovations are always patented (Acs & Audretsch, 1989). Finally, other entrepreneurial finance data, such as the amount of capital employed, turnover and profit rate, are interesting for measuring innovation. Because limited sources and too narrow markets for (financial) distribution are harmful and do not foster innovation, while good financial systems improve the probability of successful innovation and growth (Taich et al., 2016; King & Levine, 1993).
13 2.2.4 Theory on measuring sustainable entrepreneurship
In order to ultimately measure the moderation effect of sustainable entrepreneurship on the relationship between different business sizes and the business’ vitality, it is necessary to measure the degree of sustainable entrepreneurship within the participating businesses. There have been multiple researches about shaping and measuring sustainable entrepreneurship. Bocken et al. (2014) have collected and analysed a wide range of examples of mechanisms and solutions that can contribute to business model innovation for sustainability. This was done, in order to identify defining patterns and attributes that might facilitate categorization of innovative approaches towards sustainable entrepreneurship. As a result, Bocken et al. (2014) have developed and introduced sustainable business model archetypes, to describe groupings of mechanisms and solutions that may contribute to building up the business model for sustainability (Bocken et al., 2014). But these archetypes are also relevant for identifying and measuring sustainable businesses within an entrepreneurial ecosystem. Therefore, they are very useful to this study and they will be used as variables to this purpose. Figure 3 summarizes the archetypes and explains how they will be measured in this research. Bocken et al. (2014) classified the archetypes in higher order groupings, which describe the main type of business model innovation: technological, social and organizational oriented innovations.
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As shown in the figure, the archetypes can be measured by means of the examples below them. According to Bocken et al. (2014), these ‘examples’ are the most relevant and essential components for measuring the archetypes. The archetypes and their measures1 boil down to the following
principles explained by Cooney (2009), for generating green/sustainable entrepreneurship: 1. The business incorporates principles of sustainability into each of itsbusinessdecisions; 2. The business suppliesenvironmentally friendlyproducts or services that replaces demand for non-green products and/or services; 3. The business is greener than traditional competition, (which means it applies one or more of the examples that measure the archetypes in their business (market) where other competition does less or not); 4. The business has made an enduring commitment to environmental principles in its business operations (Cooney, 2009).
Based on this literature review it can be said that the conceptual model has been accurately shaped in a correct context for this research. This confirms that the model can be used for this study.
1A more detailed explanation of the archetypes can be found in appendix 1. Measures are explained in detail within the
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3. Methodology
As described in the previous section, in order to answer the research question, the following variables need to be examined: (1) business size, (2) degree of sustainable entrepreneurship within these businesses and (3) their vitality. With the focus on the entrepreneurial ecosystem of Amsterdam, the best way to examine these variables is to issue a survey to businesses within this ecosystem. First of all, it is important to explain how the survey is designed and from where the measures are obtained. Thereafter, the data collection approach will be described.
3.1 The survey
The methodology of this research consists of a rather complex survey. The survey has a relatively complex question structure. It contains many different questions to measure the indicators, that determine the degree of vitality and sustainability of a business, as well as possible. The survey questions thereby contain multiple difficult terms (terminology), for which an explanatory concept list is attached to the survey. The use of these terms is inevitable and essential for obtaining the right information. Because variables like business sustainability and vitality are not easy to measure and many factors play a role in this, it is important that all these questions are being asked. The analysis of the studies by Bocken et al. (2014), Stangler & Bell-Masterson (2015) and Taich et al. (2016) ultimately resulted in a methodology of high quality that could also be applied for measuring other (entrepreneurial) ecosystems.
3.2 Business size
To get a complete and unbiased sample of the population, which in this case is the entrepreneurial ecosystem of Amsterdam, it is important that businesses of all different sizes within this ecosystem are included in the research (see previous section for further explanation). Therefore, when approaching businesses to fill in the survey, special attention is paid to the spread of different business sizes in the sample. Subsequently, the participating businesses first need to answer multiple questions in the survey that will determine their actual size. These questions are based on official measurements and definitions of business size according to the European Union (EU). The EU classifies the size of firms according to turnover, the number of employees, the capital employed and market share. The exact classifications are explained in the theoretical framework section2.
3.3 Measuring degree of sustainability
Furthermore, because it is necessary for this research to measure the degree of sustainable entrepreneurship, it is important that businesses are included, executing different degrees in sustainable entrepreneurship. This means that non-sustainable businesses should be included, as well as moderately and very sustainable businesses, that are operating within the entrepreneurial
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ecosystem of Amsterdam. Therefore, when approaching businesses to fill in the survey, special attention is paid to the spread of different degrees in sustainability. Subsequently, the participating businesses need to answer multiple questions in the survey that will determine their degree of sustainability. These questions are based on sustainable business model archetypes, developed and tested by Bocken et al. (2014), by which the degree of sustainability within a business can be measured. The structure of this model with archetypes, measurements and how it was developed, is explained in the theoretical framework. The model of Bocken et al. (2014), also functions as the basic structure of how the questions are asked within the survey. The questions namely, are produced according to the stated examples by which the different archetypes can be measured. These are approximately five to eight measures per archetype, which means that five to eight questions per archetype are asked in the survey. The archetypes are then classified in higher order groupings, which describe the main type of business model innovation (Technological, Social, and Organisational oriented innovations), as a framework of the survey. Most questions measure the different archetypes according to 5-point rating scales (1 = Not at all, 5 = Extremely). Some questions measure the archetypes according to multiple choice (single answer, as well as multiple answer) questions2.
3.4 Measuring vitality
The last section of the survey is in the interest of measuring the vitality of all the participating businesses. Therefore, these businesses need to answer multiple questions in the survey that will determine the degree of vitality. These questions are based on a framework of indicators of a vibrant entrepreneurial ecosystem, developed and tested by Bell-Masterson & Stangler (2015) and Taich et al. (2016). The structure of this model with indicators and how it was developed, is explained in the theoretical framework. The model of Bell-Masterson & Stangler (2015) and Taich et al. (2016), also functions as the basic structure of the questions that are asked within the survey, regarding business vitality. The questions themselves, are produced on the basis of the indicators within the model. Most questions measure the different indicators according to 5-point rating scales (1 = Never, 5 = Always or 1 = 0% - 20%, 5 = 81% - 100%). Although, several questions measure the indicators according to multiple choice (single answer, as well as multiple answer) questions2.
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3.5 Data collection approach
The survey is issued to at least 100 different supervisors (n ≤ 100), representing businesses within the entrepreneurial ecosystem of Amsterdam. This a sample of the entrepreneurial ecosystem of Amsterdam, as the population to be examined. The participants are collected through desk research, by means of several different online databases that contain and make track of (sustainable) businesses/start-ups within the entrepreneurial ecosystem of Amsterdam. The websites on which these databases can be found, are listed under the reference section. From these databases, businesses with all different combinations of characteristics needed (from small to big; from non-sustainable to very non-sustainable), were randomly picked. Then, contact information (e-mail and/or phone number) of supervisors within the selected businesses were looked up, which gave the opportunity to ask for participating in the survey. When the supervisors agreed to participate, an(other) e-mail was send with the link to the survey. Encouragement was especially important for this data collection, because the survey takes some time and contains difficult terms/terminology. The encouragement for the businesses in this case, was that the vitality and degree of sustainability of the business were to be examined. This of course, is quite interesting to businesses.
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4. Results
In this chapter, primary analysis is done for testing reliability of the scale items and further analyses in SPSS has tested the research hypotheses (Field, 2009).
4.1 Recoding, reliability and scale means
All variables that are involved in this research are checked for missing data. Since all questions in the survey were mandatory to answer, there were no missing data so recoding was not necessary. For analysis of the third hypothesis, to test the moderating effect, it was necessary to make a (new) interaction variable. In order to do this, the independent variable and moderator variable was centered. This was done by calculating the mean of the variables (i.e. ‘Business’ size, vitality and sustainability’). Subsequently, the means of both the independent (size) and moderator (sustainability) variable, were subtracted from its own variable. The interaction variable could then be created by multiplying these two new centered variables.
*. Correlation is significant at the 0.05 level (2-tailed). Reliabilities are displayed on the diagonal.
Testing for reliability can be explained as examining the internal consistency of the measurement scales. The Cronbach’s alpha, which represents the estimator of the internal consistency, has been tested to verify whether all the items in one scale measure are the same. If this is not the case, it could occur that some questions should not be used for analysis. As indicated in table 1, the variables ‘business size’ and ‘business sustainability’ have a Cronbach’s alpha of respectively (4 items; α = .868) and (52 items; α = .906), which is both >.80. This indicates a high level of internal consistency. The variable ‘business vitality’ however, has a Cronbach’s alpha of (30 items; α = .662), which is (.60 < α < .80) less good, but still reasonable. Therefore, recoding was again not necessary.
M SD 1 2 3 1. Size Business 2. Vitality Business 3. Sustainability Business 1.93 2.69 2.14 0.89 0.29 0.51 (.868) .382* .054 (.662),081 (.906) Table 1. Descriptive statistics: Mean, Standard deviation and correlations of variables
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4.2 Descriptive statistics
Unfortunately, this research did not succeed in reaching the desired sample target (n ≥ 100). Instead, a sample of (n = 31) has now been used. For this reason, it is important to check whether the variables are normally distributed, inter alia because Pearson's correlation coefficient requires a normal distribution of variables. Figure 4a, b and c show that all variables are (sufficiently) normally distributed. It is therefore possible to continue with the analysis of results.
Table 1 also shows the means, standard deviations and correlations for all (combinations of) variables. As shown in Figure 4a, in which the distribution is slightly skewed to the right, the mean size of the businesses is relatively smaller (M = 1.93) within the taken sample. This means that smaller sized companies have participated in this research more, than medium or large sized companies. Although, this variable has a standard deviation of (SD = 0.89), so in general, there seems to be enough spread within the sample of different business sizes. Looking at vitality, the mean is somewhat higher as opposed to the centre (M = 2.69). As shown in Figure 4b, which is a little skewed to the left, more companies have relatively good vitality scores. The distribution of business sustainability is almost symmetric, with the mean at the centre and has little extreme values with a standard deviation of (SD
Figure 4a. Histogram with normal distribution graphic
of the IV ‘Business Size’.
Figure 4b. Histogram with normal distribution graphic of the DV ‘’Business vitality’.
Figuur 4c. Histogram with normal distribution graphic of the MV ‘Business sustainability’.
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= 0.51), which means that there is enough variation in the companies’ degree of sustainability within the sample.
Furthermore, in Table 1, it is clear that ‘DV Business vitality' has a significant strong positive correlation with the ‘IV Business size' (r = 0.382, p <0.05). The remaining possible connections do not stand. Namely, the IV with the MV and the DV with the MV have a weak non-significant association of respectively (r = 0.054, p> 0.05) and (r = 0.081, p> 0.05).
4.3 Analysis of main effects and interaction effect
*. Correlation is significant at the 0.05 level (2-tailed).
Table 2 shows the regression results regarding the relationship between the dependent variable 'Business vitality' and the 'IV size Business' and 'MV Sustainability Business' listed in the table. In this table, two models are explained, one without the interaction variable (model 1) and one including the interaction variable (model 2). The latter one analyses whether the degree of sustainability of businesses has a moderating effect on the first main effect (H1). The table shows that the addition of the interaction effect has little effect on the two main effects. Below follows an explanation.
The main effect (H1) 'Linear Regression on Size Business - Vitality Business', shows the relationship between the size and vitality of businesses. The following significance is associated with this relationship: in Model 1 this is 'Size business' (B = .125, p = 0.039). Thus, larger business size increases the vitality of a company. Each point higher on size leads to 0.125 more points vitality. Because (p <0.05), this relationship is significant. In Model 2, 'Size business' is (B = .150, p = 0.018). So again, larger business size increases the vitality of a company. Each point higher on size leads to 0.150 more points vitality. Because (p <0.05), this relationship is significant. For this relationship, a small improvement occurs when the interaction effect is included, but this is not an interesting improvement as the conclusion remains the same.
Table 2. Regression results
Model Unstandardized
B Coefficients Std Error Coefficients Beta Standardized Sig. 1 (Constant) Size Business Sustainability Business 2.694 .125* .035 .050 .058 .102 .397 .060 .000 .039 .733 2 (Constant) Size Business Sustainability Business
Interaction Size – Sustainability
2.690 .150* .055 .172 .050 .059 .101 .123 .454 .095 .254 .000 .018 .587 .175
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The main effect (H2) 'Linear regression on Sustainability Business - Vitality Business’, shows the relationship between the degree of sustainability and vitality of businesses. The following significance is associated with this relationship: in Model 1 this is 'Sustainability business' (B = .035, p = 0.733). Thus, the degree of sustainability hardly increases the vitality of a company. Each point higher on sustainability leads to 0.035 more points vitality. This outcome is very weak and thus negligible. Because (p> 0.05), this relationship is also not significant. In Model 2, 'Sustainability business' is (B = .055, p = 0.587). So again, the degree of sustainability does not increase the vitality of a company. Each point higher on sustainability leads to 0.055 more points vitality. Because (p> 0.05), this relationship is again not significant. So again, for this relationship, it does not matter when the interaction effect is included, the conclusion remains the same.
The interaction effect (H3) 'Linear regression - Interaction Size - Sustainability on Business Vitality' shows whether there is a moderating effect of variable business sustainability on the relationship between business size and vitality. The following significance is associated with model 2: 'Interaction Size - Sustainability' is (B = .172, p = 0.175). Hence, the degree of sustainability reinforces the relationship effect between size and vitality by 0.172 per point sustainability. However, because (p> 0.05), this relationship is not significant.
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5. Discussion & conclusion
Table 3: summary table of hypotheses
Looking at the results of this research, the above conclusions (in table 3) can be drawn. As Table 3 illustrates, this research has not been able to prove most theoretical hypotheses. For this reason, the research question will be discussed and answered as follows.
RQ: Moderated by degree of sustainable entrepreneurship, how do different business sizes relate to the business’ vitality, focusing on the entrepreneurial ecosystem of Amsterdam?
5.1 The relationship between different business sizes and the business’ vitality
This research has found that there is indeed a positive relationship on the main effect between the size of a business and its vitality. Former research has shown that business growth rates, which are important indicators of the vitality of a business, are higher for younger and smaller sized businesses (especially in knowledge intensive industries) than for large(r) sized businesses (Stangler & Bell-Masterson, 2015; Taich et al., 2016; Audretsch, 2012). Moreover, Reedy (2015) emphasizes that New, young, and growing businesses represent the principal sources of job creation and innovation in the United States. Startups are thereby responsible for a disproportionate share of innovative activity. This would create wealth and better life standards for entrepreneurs as well as for everyone else within the concerning ecosystem. Because growth rates of a business are such important indicators of vitality, this was initially seen as a strong argument against the first hypothesis. However, the opposite has been proven and thus H1 is supported. The following reasons may be the cause.
Hypothesis Conclusion
H1: Larger businesses in Amsterdam are more vital than smaller businesses in Amsterdam and thus have a greater positive influence on the vitality of the Amsterdam Entrepreneurial Ecosystem.
Supported H2: The degree of sustainability of a business has a positive influence on the vitality
of Amsterdam businesses, and thus on the Amsterdam Entrepreneurial Ecosystem. Not supported H3: Sustainable entrepreneurship has a moderating effect on the relationship
between different business sizes and business’ vitality. So, sustainability leads to greater vitality for larger businesses, and thus to a more vital Amsterdam Entrepreneurial Ecosytem.
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Data from this study show that small(er) businesses indeed generally grow more often and faster than large businesses. (E.g. this research has revealed that all high-growth firms were only smaller firms.) Of the six different indicators (Density; Fluidity; Connectivity; Diversity; Centers of commerce; innovation), especially the last three have many interfaces with the growth rate of businesses (Stangler & Bell-Masterson, 2015; Taich et al., 2016). However, not all measures of these indicators are related to growth. Moreover, this is only half of the indicators, which means that the others that are not correlated with, or measured by growth, also affect the vitality of a business. Data from this study show that large(r) businesses on average score higher on measures of other indicators (Density; Fluidity; Connectivity; Diversity) than small businesses. Given the fact that in this study, relatively more small businesses have participated than large ones, one could also conclude that this distribution of different business sizes is additional evidence for the support of this hypothesis. A smaller participation of large businesses, who afterwards in this research still prove to be more vital, gives indeed a strong sign that the hypothesis is supported. However, it is advisable for future research that the distribution of different business sizes within the sample is even better maintained, for optimal results.
5.2 The relationship between the degree of sustainability of a business and the vitality of businesses in Amsterdam
Unfortunately, this research has not proven that there is a positive relationship between the degree of sustainability of a business and the vitality of businesses in Amsterdam. From earlier research, however, it has been found that sustainable development within companies can save a lot of costs, builds trust and a good reputation, plus it leads to innovation (Weidinger et al., 2013). For these reasons, it can be said that sustainable entrepreneurship could also be important for the companies themselves, to remain successful and create a vital entrepreneurial ecosystem in the future. This sounds plausible, but how come that this research does not prove this to be the case?
The measurements and indicators of the variables 'business sustainability' and 'business vitality' consist of good basis frameworks on their own. They have been tested several times by e.g. Bocken et al. (2014), Stangler & Bell-Masterson (2015) and Taich et al. (2016). Moreover, they have already been used in practice multiple times. A possible reason for the lack of a significant positive relationship between the variables, is that measures and indicators of sustainability do not match well in their essence, regarding to those used for business vitality. Consequently, this may show a distorted image of the result, which is therefore not (sufficiently) valid. In the end, there are more ways to measure vitality or sustainability. It is possible that these frameworks do not cause relationship, whereas other frameworks for measuring these variables do. Previously, the connection was made between Stam & Spigel (2016) their research, (who say that entrepreneurial activity within a vital entrepreneurial
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ecosystem leads to innovation) and Nidumolu, Prahalad & Rangaswami (2009), (who say that sustainability is the most essential form of innovation). This led to the following reasoning:
“Innovation is often accompanied by more vitality in business (Stangler & Bell-Masterson, 2015; Taich et al., 2016). Hence, is sustainable entrepreneurship, besides that it is essential is for the preservation of the earth and for ensuring adequate quality of life in the future, also adding value to the vitality of an entrepreneurial ecosystem? Is it possible that, if entrepreneurial activity focuses on sustainable development, this has a positive effect on sustainable vitality of an entrepreneurial ecosystem? That would make sustainable entrepreneurship even more attractive for business.”
So, how could this train of thought be better approached in subsequent studies than in this study? How could a better match be made between the two variables, for better validity that could prove a significant relation? An example could be, adding (an) extra indicator(s) on business vitality, such as for measuring risk management and cost reduction, concerning future climate and environmental issues that companies will face due to (government/climate) policy (Hoffman, 2015; NRT/NBS, 2011). Vitality therefore, could have been measured by an additional indicator for business ‘flexibility and resilience’. This would have been an additional interface with the measuring framework for sustainability. If the indicators of both variables had more (valid) interface like this, perhaps there might have been a stronger significant relation.
5.3 The moderating effect of the degree of a business’ sustainability on the relation between different sizes and the vitality of businesses in Amsterdam.
This study has also failed to find a moderating interaction effect, by which the degree of business sustainability has a positive effect on the significant positive relation between different sizes and the vitality of businesses in Amsterdam. Given the fact from this study that there is no positive relationship between the degree of sustainability and the vitality of businesses in Amsterdam, it seems obvious that sustainability does not have a moderating effect, that affects the strength of the relationship between business’ size and their vitality. After all, when there is no relation between the degree of sustainability of a company and its vitality, one can assume that the size of the company will make little difference.
A beforehand assumption could have been, that larger businesses are more vital than smaller sized businesses. And when these larger businesses are thereby more sustainable, they could be even more vital, because of the extra positive impact they have on their environment. Vice versa, the impact of sustainability would then be invigorated by the size of the business, which would provide a higher vitality. Namely from other theories, it is possible to recall that the sustainable impact of a business on
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the environment has a positive relation to vitality indicators (Gibbs, 20018; Bocken et al., 2014). As made clear, this study finds that larger businesses are more vital and therefore score higher on those same indicators (of vitality) than small businesses. So, when these indicators of vitality score high because of the business size and the company is sustainable at the same time, there is a bigger chance of a higher positive impact and thus an even higher rate of vitality. Therefore, sustainability gives an accelerating effect. At this point, however, this is only speculation and no further evidence has been found with this study. The reasons for this will largely be in line with the findings why the second hypothesis does not hold. Also, it could be the result of other all-encompassing limitations (discussed in the next section) that could have influenced the results. Therefore, it is strongly recommended to do more research on these hypotheses.
5.4 All-encompassing limitations and recommendations
This research broaches topics, that could be very relevant and decisive for the development of vital entrepreneurial ecosystems around the world and in view of a green and sustainable future. This research made use of a detailed literature study, in order to create a new model within the methodology that is able to analyse the degree of sustainability and vitality of a certain (entrepreneurial) ecosystem. This way, future research on ecosystems can be improved. Namely, common language can be created that could be used to make better comparisons and thereby accelerate the development of such studies. Although it is important and conducive for mapping entrepreneurial ecosystems and creating a green, sustainable economy, that this research format is developed, the results of this study are not all satisfactory. Several possible theoretical reasons have been discussed for this, in previous subheadings. However, multiple crucial practical bottlenecks have not yet been discussed. The following bottlenecks are all compassing for (the course of) this research. The first bottleneck is that ultimately, the sample for this research has become too small. The aim was to provide a complete image of Amsterdam's entire entrepreneurial ecosystem as a population. In order to do this with a reliable and valid outcome, as many entrepreneurs as possible operating in Amsterdam, had to be questioned by means of a survey. It was hereby important, that these entrepreneurs all had very wide spread, different characteristics. This was both important for sketching a good image of the Amsterdam entrepreneurial ecosystem, as well as for answering the hypotheses in the research itself. This way, a good image would have been created of the degree of vitality and sustainability, of all different types and sizes of businesses. (This includes small businesses as well as the largest multinational companies operating in Amsterdam. From conventional/conservative to very sustainable and green oriented businesses.) It was planned to work with a sample target of 100 to 150 businesses (n ≤ 100). However, this seemed to be too ambitious at some point, which meant that the target had to be adjusted to a sample of 31 companies (n = 31). Given this enormous difference with
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regard to a realistic sample size for this study, this could be the main reason that most hypotheses have not been proven. Therefore, it is recommended to aim at a bigger sample in future studies, which provides more data.
Another possible bottleneck in this research that could influence the results, is that many companies in Amsterdam provide services. The provision of services can only be sustainable in a limited number of ways. Consequently, sustainability is difficult to measure in many sectors. This means that in this study, sustainability has been measured more often from a selective group of sectors. This complicates the hypothesis that sustainable entrepreneurship provides more vitality to Amsterdam's entrepreneurial ecosystem and can therefore cause errors. Namely, in some sectors this is feasible to investigate, while in other sectors it is not. This bottleneck is not inevitable. E.g., this can be taken into account, by adding or possibly reshaping some of the survey questions concerning service businesses, as well as by applying some recoding during the analysis of the data.
Furthermore, this research is relying on cross-sectional data instead of longitudinal
data. Generally, this is a good fitting research approach, because this way one observes what naturally goes on in the world without interfering with it. In this case, data come from businesses at different grow stages, with different businesses representing each growth stage (Field, 2013). However, this could (sometimes) lead to unstable relationships between sample data. It is difficult for cross-sectional studies to provide definite information about cause-and-effect relationships and therefore, it is difficult to control participants of the sample that may generate errors (Vu, 2015). E.g., a business that has just undergone a transition from a low level of sustainability to high(er) level of sustainability, could be less vital at this moment in time then it was before (when it exercised a conventional form of entrepreneurship). Namely, such a transition can have a temporary negative impact on the (vitality of the) business. In a later moment in time, this could be compensated, but this will now not be measured. A longitudinal study could have identified this better (Field, 2013). Therefore, it could be recommended to also carry out a longitudinal study on the same subject, in the future.
Conclusion
In general, we already own good knowledge about ecosystems. But there is still more information needed for specific ways to measure certain characteristics of an ecosystem. That way, e.g. behavior of actors and trends within the ecosystem can be better predicted and controlled. This study is an example of such a measuring model. It can be concluded that this study has succeeded in setting up a methodology of good quality, based on the discussed literature and frameworks, for this kind of research on (entrepreneurial) ecosystems. For this, studies of Stangler & Bell-Masterson (2015) and Taich et al. (2016) have contributed to the realization of a method for measuring the vitality of an
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ecosystem. In addition, the research of Bocken et al. (2014) has contributed to the realization of a method for measuring ecosystem sustainability. The research survey did well regarding Cronbach's reliability test. The survey forms a good basis for the methodology and would also be useful in examining other ecosystems. It was unfortunate that in this study the number of respondents was small. Consequently, the results were less satisfactory. Except for the proven significant positive relationship between business size and business vitality. For this reason, we provisionally should assume that sustainability does not have a positive relationship with the vitality of Amsterdam's entrepreneurial ecosystem. Also, it does not have a moderating effect on the relationship between business size and business vitality. However, this research has hopefully laid a good foundation for further research on this topic and in extension, opened a door for similar research on other different types of ecosystems.
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References
Audretsch, D. B. (2012), Determinants of High-Growth Entrepreneurship, OECD/DBA International Workshop on “High-growth firms: local policies and local determinants”
Auerswald, P.E. (2015) Enabling Entrepreneurial Ecosystems: insights from ecology to inform effective entrepreneurship policy
Bell-Masterson, J., & Stangler, D. (2015). Measuring an entrepreneurial ecosystem.
Bocken, N. M. P., Short, S. W., Rana, P., & Evans, S. (2014). A literature and practice review to develop sustainable business model archetypes.Journal of cleaner production,65, 42-56.
Cesar A. Hidalgo and Ricardo Hausmann, “The Building Blocks of Economic Complexity,” Proceedings of the National Academy of Sciences (June 2009).
Cohen, B., & Winn, M. I. (2007). Market imperfections, opportunity and sustainable entrepreneurship. Journal of Business Venturing, 22(1), 29-49.
Cooney, S. (2009). Build a green small business: Profitable ways to become an ecopreneur. McGraw-Hill.
Crosby, M. (2000). Patents, innovation and growth.Economic Record,76(234), 255-262. C. Taich et al., (2016) Measuring Entrepreneurial Ecosystems, Urban publications
E.J. Reedy (2015) Making Entrepreneurial Growth Vibrant Again, Ewing Marion Kauffman Foundation Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
Gibbs, D. (2008). Sustainability entrepreneurs, ecopreneurs and the development of a sustainable economy. Greener Management International, 55, 63-78.
Hoffman, A. J. (2005). Climate change strategy: The business logic behind voluntary greenhouse gas reductions. California Management Review, 47(3), 21-46.
J. Acs, Z., & Audretsch, D. B. (1989). Patents as a measure of innovative activity.Kyklos,42(2), 171-180. King, R. G., & Levine, R. (1993). Finance, entrepreneurship and growth.Journal of Monetary economics,32(3), 513-542.
National Round Table & Network for Business Sustainability (2011), Managing the business risks and opportunities of a changing climate: A primer for executives on adaptation to climate change
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Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation.Harvard business review,87(9), 56-64.
Reedy, E.J. (2015) Making Entrepreneurial Growth Vibrant Again Stam, E. (2014). The Dutch entrepreneurial ecosystem.
Stam, F. C., & Spigel, B. (2016). Entrepreneurial ecosystems.USE Discussion paper series,16(13). Weidinger, C., Fischler, F., & Schmidpeter, R. (Eds.). (2013). Sustainable entrepreneurship: business success through sustainability. Springer Science & Business Media.
Vu, U. (2015) At work: Inspectations with penalties linked to lower injuries. Institute for work & health, issue 81
UN World population prospects (2015) Revision of World Population Prospects - DESA/Population division (https://esa.un.org/unpd/wpp/)
Database websites for finding participants for data collection
http://amsterdam.startups-list.com/
https://startupmap.iamsterdam.com/map
https://thenextgeneration.nl/ecopreneurs/
https://www.bewustamsterdam.nl/duurzaamheid
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Appendix 1
Explanation of sustainable business model archetypes
Archetype 1: Maximise material productivity and energy efficiency
Definition: Do more with fewer resources, generating less waste, emissions and pollution. Figure 3.1 explains the value proposition, value creation and delivery and value capture of the ‘Maximise material productivity and energy efficiency’ archetype.
Figure 3.1 Explanation of ‘Maximise material productivity and energy efficiency’ archetype.
Archetype 2: Create value from ‘waste’
Definition: The concept of ‘waste’ is eliminated by turning waste streams into useful and valuable input to other production and making better use of under-utilised capacity.
Figure 3.2 explains the value proposition, value creation and delivery and value capture of the ‘create value from waste’ archetype.
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Archetype 3: Substitute with renewables and natural processes
Definition: Reduce environmental impacts and increase business resilience by addressing resource constraints ‘limits to growth’ associated with non-renewable resources and current production systems.
Figure 3.3 explains the value proposition, value creation and delivery and value capture of the ‘Substitute with renewables and natural processes’ archetype.
Figure 3.3 Explanation of ‘Substitute with renewables and natural processes’ archetype.
Archetype 4: Deliver functionality, rather than ownership
Definition: Provide services that satisfy users’ needs without having to own physical products. Figure 3.4 explains the value proposition, value creation and delivery and value capture of the ‘deliver functionality, rather than ownership’ archetype.
Figure 3.4 Explanation of ‘deliver functionality, rather than ownership’ archetype.
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Archetype 5: Adopt a stewardship role
Definition: Proactively engaging with all stakeholders to ensure their long-term health and well-being.
Figure 3.5 explains the value proposition, value creation and delivery and value capture of the ‘adopt a stewardship role’ archetype.
Figure 3.5 explanation of ‘adopt a stewardship role’ archetype.
Archetype 6: Encourage sufficiency
Definition: Solutions that actively seek to reduce consumption and production.
Figure 3.6 explains the value proposition, value creation and delivery and value capture of the ‘encourage sufficiency’ archetype.
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Archetype 7: Re-purpose the business for society/environment
Definition: Prioritizing delivery of social and environmental benefits rather than economic profit (i.e. shareholder value) maximisation, through close integration between the firm and local communities and other stakeholder groups. The traditional business model, where the customer is the primary beneficiary may shift.
Figure 3.7 explains the value proposition, value creation and delivery and value capture of the ‘Re-purpose the business for society/environment’ archetype.
Archetype 8: Develop scale-up solutions
Definition: Delivering sustainable solutions at a large scale to maximise benefits for society and the environment.
Figure 3.8 explains the value proposition, value creation and delivery and value capture of the ‘Develop scale-up solutions’ archetype.
Figure 3.8 explanation of ‘Develop scale-up solutions’archetype.
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Appendix 2
Survey with full list of measures/items and exact application of design
Survey for mapping the degree of sustainability and vitality of different
size businesses within the Amsterdam Entrepreneurial Ecosystem
Measuring business size according to EU definitions of size
The following questions are aimed at determining the size of the business in which you work.
Turnover
The turnover of this business is: A) <€10m B) €10m – €50m C) >€50m
Number of employees
A) <50 B) 50 – 249 C) >249Amount of capital employed
A) < €10m B) €10m – €43m C) >€43m
Market share
A) Very low B) low C) Average D) Above average E) High35
How sustainable is your business?
The following questions are intended to determine how sustainable the business is you work for. This will be done by measuring eight different sustainable business model archetypes. The archetypes are classified in higher order grouping, which describe the main type of business model
innovation: technological, social and organizational oriented innovations. This part of the survey contains multiple difficult terms (terminology), which you may not directly understand. Therefore, an explanatory concept list is attached to the e-mail in which you found the link to this survey.
Technological
Maximize material productivity and energy efficiency
Business uses low carbon manufacturing/solutions. (This means using power with substantially lower amounts of carbon dioxide emissions than is emitted from conventional fossil fuel power generation. Examples are hydroelectric power, nuclear power, wind power, solar power, geothermal power, tidal power, carbon capture and storage):
A) Not at all B) Slightly C) Moderately D) Very E) Extremely
Business uses lean manufacturing. (Philosophy that identifies and seeks to minimize waste in production processes, e.g. physical waste of materials/energy, over-production, materials handling, over-processing, inventory, defects and rework):
A) Not at all B) Slightly C) Moderately D) Very E) Extremely
Business uses Additive Manufacturing (AM). (With AM, complex products can be manufactured quickly and efficiently):
A) Not at all B) Slightly C) Moderately D) Very E) Extremely
Application of dematerialization (of products/packaging) within your business: A) Not at all
B) Slightly C) Moderately D) Very
