Startups in the internet-of-things : an opportunity exploitation perspective

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Master Thesis

MSc. Business Administration: Entrepreneurship & Innovation

Startups in the Internet-of-Things

An Opportunity Exploitation Perspective

Date:

19/08/2016

Author:

Joshua Kreuger (6054897)

Joshua.kreuger@student.uva.nl

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Preface

The research I present here is my master thesis, with which I conclude the Master of Business Administration program in the Entrepreneurship and Innovation track at the University of Amsterdam. This thesis has given me the opportunity to research a subject that has been the foremost reason to continue studying after graduating for my MSc Persuasive Communications in 2015, the Internet-of-Things. I have learned a great deal about how businesses can benefit from Internet-of-Things technology, which may prove very valuable in my coming career.

Writing this thesis has been an exciting but challenging experience. I want to express my gratitude to my supervisor Emiel Eijdenberg for his time, support and valuable input during the past months. The topic of my research was overwhelming by times, but Emiel’s feedback has helped me a lot in getting this thesis together.

Statement of originality

This document is written by Student Joshua John Kreuger who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is 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

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ABSTRACT

This study examines how startups currently exploit the entrepreneurial opportunities posed by the emergence of Internet-of-Things (IoT) technology by investigating entrepreneurial orientation and business models. This study aims to contribute to the first line of research on opportunity exploitation in the IoT by investigating if startups’ entrepreneurial orientation can be linked to firm performance. In addition the business models of startups were analyzed using the Business Model Canvas (Osterwalder & Pigneur, 2004) to see how startups currently configure their business in the IoT. A quantitative approach was adopted and data collected from a sample of 37 IoT-startups from various industries and nationalities. It was expected that startups’ entrepreneurial orientation could be linked to firm performance. Results showed that startups’ entrepreneurial behavior could not be linked to firm performance, suggesting that other determinants are present. It was further hypothesized that startups would assess the business model components of value proposition, customer relationships, key partnerships and revenue streams as most important for their IoT-business model. Results showed that not one business model component was more important than other components, yet the startups’ resources were of less importance in the IoT-business model. Furthermore, the business model configurations of the startups were measured to see what configurations were recurrent in the IoT-business model. The findings are presented in an IoT-business model canvas that provides a contemporary illustration of applied IoT-business models. The research therewith is one of the first to empirically observe what the applied business model looks like and how startups currently exploit the IoT-opportunity.

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1. INTRODUCTION

Entrepreneurship is flourishing; the practice as well as its research field have gained significant popularity over the recent decades. In entrepreneurship academia, the continuing efforts to define a distinctive domain for entrepreneurship research has led scholars to shift their focus on the profile of the entrepreneur to the role of opportunities and toward an understanding of the ways entrepreneurs work to exploit opportunities (Eckhart & Shane, 2003). In fact, the scientific community now seems to increasingly ascribe an essential role to opportunities for entrepreneurship; or as Short, Ketchen, Shook and Ireland (2009) state: “Without an opportunity, there is no entrepreneurship. A potential entrepreneur can be immensely creative and hardworking, but without an opportunity to target with these characteristics, entrepreneurial activities cannot take place” (Short, Ketchen, Shook & Ireland, 2009).

Those whom witnessed the rise of the Internet will almost certainly agree that the Internet has provided fertile soil for such new venture opportunities on a tremendous scale, evidenced by the births of countless of Internet start ups, some of them growing to global players such as Google (Alphabet), Amazon and Facebook. Despite the Internet’s already significant impact on business, recent developments in sensor-technology have triggered an increasing number of scholars to predict that the Internet’s potential for business is far from stalling, and in fact is on the brink of unleashing many more opportunities (Kyriazis & Varvarigou, 2013; Haller, Karnouskos, & Schroth, 2008).

This technological development is now commonly named the Internet-of-Things (henceforth IoT): the premise of a revolutionary next phase of the Internet. It is a shift from today’s Internet, presently limited to the realm computers and smartphones, to a world in which tens of billions of everyday objects, or ‘things’, become interconnected to the web. By connecting these objects to the Internet through tiny communication technologies, the IoT promises the unprecedented ability to ‘sense’ the world around us (Gubbi et al., 2013). Above all, the IoT is not a depiction of a distant future: recent developments in sensor-technology and cloud computing have accelerated the IoT’s development tremendously over the past few years. In fact, the basic technologies that enable the IoT are readily available at increasingly feasible cost prices (Whitmore, Agarwal & Da Xu, 2015).

IoT-technology enables to continuously monitor objects’ identity, location and current status, which may be used for many innovative applications such as real-time asset management (Roussos, 2006) or predictive maintenance of machinery (Kiritsis, 2011). IoT-technology

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therewith provides fertile soil for countless of new business opportunities in almost all industries (Moriandi, Sicari, & De Pellegrini, 2012). The potential value of the IoT is huge: major strategy firms such as McKinsey (2015) and Accenture (2013) and economic institutions (WEF, 000) predict that the yearly added value of IoT-technology may grow upwards of 10 trillion dollars across a wide variety of industries by 2025. For entrepreneurs, the IoT-paradigm promises a legion of opportunities to develop innovative products and services (Fleisch, 2010). When companies and startups broadly adopt IoT-technology, the economic impact can be so powerful and universal that it will potentially stir up the business world as much the ‘traditional’ Internet has since its introduction in the early 1990s (Gubbi et al., 2013).

Precaution is obviously needed for predictions of such magnitude. Yet, these visions are now gradually seen to become a reality. In addition to the growing commitment on IoT-technology by established tech-giants such as Cisco Systems and General Electric (Kehoe, Patil, Abbeel, & Goldberg, 2015), the number of IoT-startups is growing fast. Above all, their undertakings are now becoming visible: over the past few years, pioneering IoT-startups have brought innovative products and services to market, ranging from internet-connected thermostats that can be remotely set to connected warehouse systems which can locate inventory real-time. Notably, IoT-startups are increasingly becoming the target for acquisitions at remarkably high valuations, such Google’s purchase of Nest Labs (smart thermostats) for $3.2 billion in 2014. Thus, the first line of IoT-entrepreneurs has progressed from identifying and exploring IoT-opportunities to exploiting them. Above all, the IoT is argued to considerably impact the business world in a matter of just a few years and will demand firms to adapt rapidly in order to survive (Kagerman, Osterle, & Jordan, 2010). Developing an understanding of how firms can exploit the IoT-opportunity is thus an urgent matter. Investigating how the first line of startups currently exploits the IoT-opportunity could therefore enhance the understanding of how firms can create and capture value in the domain of the IoT. Hence the following research question is central to the present research:

How do startups exploit the business opportunities posed the Internet-of-Things?

Entrepreneurial behavior of firms is increasingly considered necessary to explain the performance of firms (Stam & Elfring, 2008; Hughes & Morgan, 2007). The construct of entrepreneurial orientation regards entrepreneurial characteristics in the processes, structures and behaviors of firms and provides a useful framework to study entrepreneurial behavior and is consistently linked to firm performance (Naldi, Nordqvist, Sjörberg, & Wiklund, 2007). The entrepreneurial

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orientation might therefore be particularly useful to see what determines success full exploitation of the IoT-opportunity for business. Moreover, researchers are increasingly recognizing the relevance of the business model approach for entrepreneurship research (George & Bock, 2011). The business model approach allows analyzing those elements of the firm that in conjunction lead to value capture and creation (Baden & Fuller, 2010). How firms can exploit IoT-opportunity may therefore be fruitfully examined by observing what types of business models are currently used by IoT-startups.

Still, the body of scientific literature on entrepreneurship and business models in the IoT is considerably scant due to the novelty of the IoT. Hence, the research here aims to contribute to the first line of research on entrepreneurship and business models in the context of the IoT. Specifically, this research aims to provide preliminary insights on how firms can approach the IoT-opportunity, by observing if the presence of an entrepreneurial orientation can be related to the firm performance in IoT-startups. Importantly, data will be gathered on the business models of startups to observe what currently are prominent aspects and configurations of IoT-business models. The basic reference for this section of the research the paper by Dijkman et al. (2015), who investigated what managers thought would become important components and configurations of IoT-business model. The present study will corroborate on these findings by obtaining the same methodology, namely the Business Model Canvas (Osterwalder & Pigneur, 2004), tailored to IoT-research by Dijkman et al., (2015). Above all, the present study gathers data on IoT-business models that are currently applied. The value of these findings is twofold; researchers may use the findings to further elaborate on the IoT-business model in future research, whilst entrepreneurs can take the observations into account when starting business in the IoT. It is important to note, however, that the present research aims to yield insights on business in the IoT rather than claiming to provide recipes for success.

The structure of this thesis is as follows. First, relevant literature will be reviewed from which hypotheses will be formulated. Subsequently, the methodology section will provide an overview of the data collection procedures, the data analysis strategy, the research sample and substantiation for the variables chosen to answer the research question. Thereafter, the results of the analyses will be considered in the results section. Subsequently, the findings will be discussed and conclusions drawn regarding the research question. Lastly, limitations of the research will be considered together with suggestions for future research.

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2.1

Entrepreneurship

Entrepreneurship has long shown to be an elusive phenomenon to scholarship. Many scholars have studied entrepreneurship throughout history, still the variety in perspectives and definitions, as well as the overlap with other sub-fields of business enterprise research has long hindered the development of entrepreneurship as a distinctive research domain (Venkataraman, 1997; Wiklund, Davidsson, Audtretsch, & Karlsson, 2011). Above all, a wide range of beliefs on the meaning of entrepreneurship exists among researchers; earlier entrepreneurship scholarship is generally characterized by literature that concerns the attributes of entrepreneurial behavior (i.e. risk-taking attributes of entrepreneurs or firms) while others streams of literature considered entrepreneurship as an outcome (i.e. innovation and wealth creation) (Gartner, 1990). In a historical perspective, the development of entrepreneurship as a research field is characterized by three general disciplinary periods: the neoclassical economics period, the social science period and the managerial period. Though some overlap exists, definitions, theory and research typical to each period are reviewed hereafter.

2.1.1 Development of the entrepreneurship research field

It was in the writing Essai Sur La Nature du Commerce en General by Richard Cantillon (1680-1734), published after is death in 1755, that the concept of entrepreneurship was given considerable meaning in economics and that the role of the entrepreneur as a driver of economic development was underlined (Cornelius, Landström, & Persson, 2006). Cantillon gave entrepreneurship the basic definition of self-employment with an uncertain earning (McMullan & Long, 1990). With the exception of a few economists such as Jean-Baptiste Say (1767-1832) or John Stuart-Mill (1806-1873), economic theory largely neglected the entrepreneur. The dominant classical economic theory, based on Adam Smith’s renowned groundwork The Inquiry into the Nature and Causes of the Wealth of Nations (1776), was generally based on models assuming the principle of equilibrium. Equilibrium models center pricing as governing the dynamics between supply and demand to a perfect balance, yet do not account for structural economic change, or in other words, innovation. Equilibrium thus excludes the entrepreneur as a driver of innovation change by definition (Baumol, 2005). It was only much later in 1911 that Austrian Neoclassical economist Joseph Schumpeter explicitly opposed the equilibrium principle by explicitly describing the entrepreneur as a micro-level driver of structural economic change. According to Schumpeter (1911) the entrepreneur does not tolerate equilibrium and drives innovation through

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his continuous quest of finding and exploiting profitable opportunities in the imperfections of economic production.

Mainstream economics nonetheless continued to overlook the entrepreneur, mainly because of the strong proclivity toward equilibrium models. It were behavioral scientists, led by the pioneering work of David McClelland (1917-1998) that continued entrepreneurship research and shifted the focus of entrepreneurship as an economic function to the entrepreneur as an individual (Davidsson, 1991). In 1961, McClelland was one the first to empirically show that a country’s need for achievement and openness in its norms and values could be linked to its economic development (McClelland, 1961). Entrepreneurs, commonly characterized as individuals who have a high need for achievement, were hence recognized as drivers of societal and economic development. Other work in this domain further portrayed the entrepreneur as an individual who is comfortable with moderate risk-taking, has high self-confidence, independent problem solving skills and acceptance of responsibility. Halfway the 1970s, small business and entrepreneurship became of particular interest in management studies. At that time, large Western companies were struck hard by economic setback and unemployment levels soured (Cornelius, Landström, & Persson, 2006). Fueled by the observation that in fact small and not large firms were mostly responsible for job-creation (Birch, 1979), entrepreneurship and innovation was staged at the center of political and academic debate. Attracting researchers from many different scientific backgrounds, entrepreneurship in management studies started to emerge as a separate research field. Even though divided into many sub-disciplines that still exist today, the rise of entrepreneurship in management studies meant a shift of focus from the entrepreneur as an individual to entrepreneurship as a process. Gartner (1988) for instance, argues that entrepreneurship is ‘the creation of new organizations’ and holds that entrepreneurship is considered with what the entrepreneur does, not who the entrepreneur is. The creation of new organizations is not a conceptual requirement to all entrepreneurship disciplines, however; the domain of corporate entrepreneurship considers entrepreneurial activities in existing organizations (Sharma & Chrisman, 2007). Zahra (1995), for example, defines corporate entrepreneurship as the processes in corporate settings that result in corporate innovation, organizational renewal and new business venturing. Another discipline that is establishing in entrepreneurship research focuses on the role of opportunities that facilitate entrepreneurship. Venkataraman (1997) for instance, called entrepreneurship academia to redefine entrepreneurship as a research field that “seeks to understand how opportunities to bring into existence "future" goods and services are discovered, created, and exploited, by whom, and with what

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consequences”. Likewise, Shane and Eckhardt (2003) define entrepreneurial opportunities as “situations in which new goods, services, raw materials, markets and organizing methods can be introduced through the formation of new means, ends, or means-ends relationships’’. The strategic entrepreneurship discipline, which is rooted in the strategic management literature and closely linked to the opportunity-centric perspective of entrepreneurship, concerns entrepreneurial action in a strategic perspective. Strategic entrepreneurship can be summarized as “the integration of entrepreneurial (i.e., opportunity-seeking behavior) and strategic (i.e., advantage-seeking) perspectives in developing and taking actions designed to create wealth” (Hitt, Ireland, Camp, & Sexton, 2001). Exemplary for the strategic entrepreneurship perspective is the concept of entrepreneurial orientation. Entrepreneurial orientation research is considered with strategic entrepreneurial behavior at the firm-level and is consistently examined in relation to firm performance. This line of research is thus useful to study the determinants of firm success. The entrepreneurial orientation of firms will hence be examined in the present study to see if successful opportunity exploitation in the IoT can be explained by entrepreneurial behavior. Before going into the relationship between the entrepreneurial orientation and firm performance, it is key to understand what is meant when speaking of firm performance.

2.2

Firm performance

Firm performance is an important part of empirical research of business and the entrepreneurial firm (Naldi, Nordqvist, Sjöberg, & Wiklund, 2007). When studying different organizational structures or strategies, firm performance is often taken as the key outcome and serves the need to develop normative theory in strategic management (Dess & Robinson, 1984). Clearly defining firm performance and its measurement is therefore crucial to understand what distinguishes successful firms from failing firms (Murphy et al., 1996). Research on strategic management describes the measurement of firm performance (also termed organizational effectiveness) by three types of hierarchical constructs (Venkatraman and Ramanujan, 1986). First is the construct of financial performance and is central to research on organizational effectiveness, yet by itself is insufficient to assess overall performance (Murphy et al., 1996; Chakravarthy, 1986). The second construct is operational measures; these include market share measures and more latent operationalizations of performance, for example increased (customer) satisfaction or product quality. These measures are said to define the factors that ultimately lead to financial performance (Hofer, 1987). The third and final construct relates to the constituencies that lie beyond the performance of the firm (Kanter & Brinkerhoff 1981; Zammuto, 1984).

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Also the multidimensionality associated with the firm performance construct demands close consideration. In their meta-analysis on 71 entrepreneurship studies, Murphy, Trailer and Hill (1996) identify eight dimensions in firm performance measures. The firm performance dimensions identified by Murphy and colleagues are efficiency, growth, profit, size, liquidity of cash, success/failure, market share and leverage. Most important is the authors’ observation that the dimensions of firm performance demonstrate inconsistencies within and between the examined studies. Hence Murphy and colleagues (1996) conclude that the measurement of only one or few performance dimensions is narrow and incomplete to describe firms’ overall performance. A firm may for instance sacrifice short-term profits for long-term growth and thus perform less on one dimension in favor of the performance on another. The need to measure performance on multiple dimensions underlined by Murphy, Trailer and Hill (1996) has gained substantial support in entrepreneurship research and strategic research in general (Stam & Elfring 2008; Lumpkin & Dess, 1996; Wiklund & Shepherd, 2005; Gilley & Rasheed, 2000). Recognizing these notions, it is of the essence to clearly explicate the definition and measurement of firm performance obtained in the present study. A thorough description of the present study’s measurement of firm performance is provided in the methodology section.

2.3

Entrepreneurial Orientation

Literature on entrepreneurial orientation (henceforth ‘EO’) considers the attributes of the entrepreneurial strategic mindset at the firm-level and has proven a useful framework for studying entrepreneurial activity (Naldi, Nordqvist, Sjörberg, & Wiklund, 2007). The EO-concept originates in the fundamental work of Miller (1983), who described the entrepreneurial firm as “one that engages in product market innovation, undertakes somewhat risky ventures and is first to come up with “proactive innovations’’, beating competitors to the punch”. In line with Miller’s (1983) conception of the entrepreneurial firm, Wiklund and Shepherd (2003) state that EO can be described as an entrepreneurial mindset and hold that “EO involves a willingness to innovate to rejuvenate market offerings, take risks to try out new and uncertain products, services, and markets, and be more proactive than competitors toward new marketplace opportunities”. Lumpkin and Dess (2001) describe higher levels of EO to resemble the business objective of ‘staying ahead of competition’ while lower levels of EO can be interpreted as the objective to ‘follow the leader’.

Researchers use EO to describe a consistent set of organizational activities or processes (Naldi et al., 2007; Covin & Slevin, 1989). One of the most important writings in the EO domain is the

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extensive literature review by Lumpkin and Dess (1996) in which the authors seek to clarify the construct and constituents of EO. Lumpkin and Dess (1996) argue that EO is reflected in the strategic decision-making processes of firms’ (top) management. The authors draw a conceptual parallel to strategic management literature on the strategic decision-making processes (SMPs) of firms. According to Lumpkin and Dess, (1996), SMP literature considers “the entire range of organizational activities that involve planning, decision-making and strategic management” and specifies distinct dimensions in SMPs that characterize typical strategic mindsets in firms. The current study adheres to Lumpkin and Dess’ (1996) conceptions of EO where it has been the main reference point for most of the recent studies on EO (Rauch et al., 2009).

Researchers consistently conceptualize that the EO consists of the dimensions of innovativeness, pro-activeness and risk-taking, resembling the typical attributes of entrepreneurial behavior. These three dimensions of EO are embodied in related but distinct organizational activities and processes and are seen to drive firm performance through specific mechanisms. Hence the EO-dimensions are discussed hereafter, followed by a review of studies regarding the relationship between EO and firm performance and the possible moderators in that relationship.

2.3.1 EO-dimensions Innovativeness

The entrepreneurial firm seeks to be innovative. Hughes and Morgan (2007) state that “innovativeness represents a bias toward embracing and supporting creativity, experimentation, technological leadership, and R&D in the development of products, services, and processes to generate novel solutions to customer needs and problems” and can be seen as a firm’s capability to explore new possibilities (Hughes & Morgan, 2007). Lumpkin and Dess (1996) describe innovativeness as ‘a firm’s tendency to engage in and support new ideas, novelty, experimentation, and creative processes’ (Lumpkin & Dess, 1996). Moreno and Casillas (2008) hold that the engagement in innovation-centered activities stems from firms’ basic willingness to depart from existing technologies or practices to break with the status quo. Likewise, it has been observed that the presence of innovativeness in firms is largely determined by the trait of (top) managers of to be willing to discard old beliefs (Karagozuglu and Brown, 1988). Hurley and Hult (1998) argue that innovativeness is demonstrated when firms actively pursue the implementation of new ideas, products or processes and not just the generation thereof. Innovativeness is evidenced by firms’ decisive dedication to R&D-activities, for instance the experimentation with

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expenditures, the share of R&D-employees and innovation-centered human resource practices, for instance rewarding of experimentation pose as tangible indicators of innovativeness in firms (Miller, 1987).

Innovativeness may benefit firm performance in various ways. A focus on innovativeness enhances entry into new business domains or helps renewing a firm’s presence in an existing domain (Hughes & Morgan, 2007; Cho & Pucik, 2005; Hult & Ketchen, 2001). Innovativeness is also concluded to strengthen the capability to differentiate and develop innovative offerings that are superior to those of competitors (Avlonitis & Salavou, 2007; Hughes & Morgan, 2007). Other researchers have shown that innovativeness can increase firm performance by enhancing creative thinking in the learning activities of firms (Calantone, Cavusgil, & Zhao, 2002; Akgün, Keskin, Byrne, & Aren, 2007; Zahra, Ireland, & Hitt, 2000). Innovativeness may further benefit firm performance where it advances firms’ skills of translating market-oriented information into offerings that adhere to the needs of the market (Hurley & Hult, 1998).

Pro-activeness

The entrepreneurial firm takes initiative. Taking initiative is commonly described in the dimension of pro-activeness in EO-literature, which can be seen as an action orientation (Crant, 1996; Becherer & Maurer, 1999). This stream of theory defines the proactive individual to bring about environmental change and as one who is relatively unconstrained by limited resources. The proactive person has the tendency “to scan for opportunities, show initiative, take action and persevere until reach closure by bringing about change” (Bateman & Crant, 1993). According to Hughes and Morgan (2007), pro-activeness in EO represents a forward-looking perspective that is evidenced when a firm actively scans the environment for opportunities in order to anticipate and act upon the future needs of customers. Lumpkin and Dess (2001) state that pro-activeness is present when firms’ construct their SMPs to scan for opportunities that may or may not be in line with current operations, products and services while accepting the possibility of having to strategically eliminate current operations in order to stay ahead of competition.

Pro-active firms are seen to yield higher levels of performance because they are responsive to signals from the market (Day & Wensley, 1988). Hughes and Morgan (2007) state that by actively anticipating change, proactive firms are in a better position to seize market share and customers by mobilizing resources in advance of competitors. It is widely conceived that entry in a new market a head of competitors is associated with first-mover advantages (Vanderwerf & Mahon, 1997), predominantly the gain of large returns and market share through early access to

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consumers (Kerin et al., 1992; Liebermann & Montgomery, 1988). Venturing first into a new market also indirectly benefits firm performance through proprietary learning and experience, making the firm more attuned to change and better skilled to signal latent needs in the market (Hamel & Prahalad, 1991). Accordingly, pro-activeness is said to be demonstrated when a firm is normally first in launching an innovation to which competitors react, while a less pro-active, or reactive firm responds to the innovations introduced by competitors (i.e. Covin & Slevin, 1989). Yet, this may be a somewhat narrow view of pro-activeness. For instance, two competing firms may develop similar innovative solutions simultaneously without knowing about each other’s efforts and both bring it to market shortly after one another. It difficult to maintain that the second firm to launch the offering is not pro-active or even is reactive. This reasoning is substantiated by the empirical findings that firms second to enter a market often perform as well as the first entrant (Dobrev & Gotsopoulos, 2010; Miller & Camp, 1985). Moreover, moving first can even pose a disadvantage where the a second entrant can signal and avoid the costly mistakes made by the first-moving firm (Lieberman & Montgomery, 1998. Hence Lumpkin and Dess (1996) dismiss the popular belief that the proactive firm is generally first to the table and state that pro-activeness is rather determined by a firm’s will and foresight to seize new opportunities, despite the possibility of having been introduced by a competitor already.

Risk-taking

The entrepreneurial firm takes risks. Reflecting the risk-taking attributes associated with the entrepreneurial personality (Brockhaus, 1980), the risk-taking dimension in the EO pertains to the firm’s strategic mentality regarding actions of which the outcomes have relatively high levels of uncertainty (Wiklund & Shepherd, 2003). The meaning of risk is inherently context-dependent; a particular opportunity is less risky for the firm that has more relevant information, knowledge, experience or financial reserves at its disposal than for firms scoring less on those aspects. Risk-taking is thus a subjective matter and a more equivocal dimension than innovativeness or pro-activeness (Lumpkin & Dess, 1996). Moreover, literature distinguishes various types of taking risk that the entrepreneur may face, ranging from social risk, psychological and risk financial risk. Strategic management is primarily concerned with the financial risk, which typically defines risk as the probability of a negative outcome expressed in a risk-return rate. Accordingly, risk-taking in EO-literature is commonly described in the form of borrowing heavily, or investing a significant share of time and resources in projects, activities and offerings of which the outcomes are inherently uncertain (Lumpkin & Dess, 1996).

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When deciding to take risk, a firm has to accept one of two possible scenarios, first the risk of failing and second the risk of missing an opportunity. The decision to avoid the possibility of failure is caused by fear, whereas the decision to not act upon an opportunity is caused by inaction (Dickson & Giglierino, 1986). Central to risk-taking is the significant possibility of negative outcomes, yet it is widely posited in research that firms need to be willing to take risks in order to maintain or improve performance. Avoiding risk by not acting upon opportunities, a firm delays or omits the introduction of innovative offerings, resulting in lower performance (Hughes & Morgan, 2007). Firms that take risk combine the behavior of looking for opportunity with deliberate risk-taking to foster a tendency for exploration and exploitation (Baird & Thomas, 1990) and decisively commit resources before having a clear understanding of what action needs to be taken (Covin & Slevin, 1991). This prevents the firm from inertia, inaction and sticking to traditions (Busenitz & Barney, 1997). Such a risk-taking approach takes advantage of rapidly evolving markets where passivity in situations of heavy change lead to a quick decline in performance (Miller & Friesen, 1982). Accordingly, Eisenhardt (1989) associated timely risk-taking with strategic decision speed and concluded both to be linked to improved firm performance.

2.3.2 Research on the EO-performance relationship

To grow and maintain future profits in environments of rapid change and shorter product and business model lifecycles, firms may benefit from adopting an EO (Miller & Friesen, 1982; Lumpkin & Dess, 2001). Still, whether an EO leads to improved firm performance is influenced by many possible factors internal and external to the firm. Firstly, firms are be benefitted by adopting an EO when it aligns with their strategic objectives. Examining the boards of small and medium banks, George, Wood and Kahn (2001) found that EO is associated with proactive network strategies and higher levels of firm performance. Covin, Slevin and Schultz (1994) observed among small high-tech manufacturing firms that adopting an EO improves firm performance significantly more when orienting for growth rather than orienting for conservative strategic missions. Where younger firms aim for growth, also firm age is seen to possibly influence the EO-performance relationship. Runyan, Droge and Swinney (2008) found that EO was related to higher firm performance for firms under the age of 11 years, whilst this relationship wasn’t observed for older firms. Focusing on high-tech startups in South Korea, Lee and colleagues (2001) found also found EO to be a significant predictor of firm performance. Regarding the size of firms in relation to EO, Rauch and colleagues (2009) found from a meta-analysis that the EO-performance relationship and is stronger for micro-sized and smaller firms

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than for larger firms. Furthermore, Rauch et al. (2009) concluded that the effect of EO on firm performance is significantly higher for high-tech firm than for non-high tech firms (r = .396 vs. r = .231). Referring to the typical market conditions in which high-tech firms operate, the authors suggest that adopting an EO is beneficial in dynamic environments characterized by heavy change and development (Rauch et al., 2009). Research has further shown the EO-performance relationship to be stronger in markets that are characterized by dynamism and rapidly evolvements than for competitive and hostile markets (Lumpkin & Dess, 2001). Interestingly and to reasoning in literature, Rauch and colleagues (2009) observe that the strength of the EO-relationship does not significantly differ between studies conducted in the continents of America, Europe and Asia. Since the current study investigates young, high-tech firms that operate in the rapidly evolving domain of the Internet of Things in various industries, the following hypothesis is proposed:

H1: Entrepreneurial orientation is positively associated with firm performance

2.4

The Business Model approach

The business model approach is highly emphasized in entrepreneurial practice for quite some time, yet significant interest from researchers is relatively recent (Osterwalder, 2005). Researchers have argued that the business model is a critical construct for the understanding of how firms create value (Amit & Zott, 2001; Chesbrough & Rosenbloom, 2002). The business model concept confluences organizational design with strategy perspectives (Zott & Amit, 2007) and can be seen as an abstract representation of the firm that describes the business logic with which it creates value and delivers it to customers (Teece, 2010). The business logic is defined as a conceptual comprehension of how the firm makes money by describing what the firms offers, to whom its offers this and how it can accomplish this (Osterwalder & Pigneur, 2004). Since firms are highly heterogeneous in terms of organization, distribution of resources and behavior (Barney, 2001; Wernerfelt, 1995), the purpose of the business model is to enable the analysis of the firm in its entirety. By reducing the firm’s complexity to its essence, the business model can be seen as a scaled down version of the firm (Baden & Fuller, 2010). The business model construct therewith enables a comprehensive overview of the activities and behavior that in conjunction lead to value generation value (Baden-Fuller & Morgan, 2010; Shafer, Smith, & Linder, 2005). Importantly, the business model differs from strategy theory where the business model construct provides a snapshot description of how the firm’s components fit together in a specific moment in time, whereas strategy is also concerned with issues of competition (Osterwalder, Pigneur, & Tucci,

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2005; Magretta, 2002). The business model thus illustrates how the firm’s strategy is translated into the different aspects of the firm, which can be described as the business logic (Osterwalder & Pigneur, 2004). The business model construct therefore has both academic and practical potential; researchers can use the business model as an analytical tool to study the configuration of the firm that results from strategic considerations, whereas managers can use the business model as a strategic design tool for a current or future business model.

Researchers approach the business model concept from a wide variety of theoretical perspectives, describing it for instance as an organizational narrative (Magretta, 2002), the processes that translate innovation into value (Chesbrough & Rosenbloom, 2002), recipes for the activities of firms resembled in organizational design and strategy (Slywotzky & Wise, 2003), streams of information and resources in the firm (Timmers, 1998) and designed structures of the firm’s boundary-spanning transactions (Amit & Zott, 2001). George and Bock (2011) found from a meta-analysis on 108 business model studies that combinations of strategic and organizational topics are recurrent in the literature on the business model concept. In literature approaching the business model as a form of organizational design, researchers describe the role of managerial agency in determining the organizational structure that fits the configuration of the firm’s products, activities and markets (George & Bock, 2011). In theory on the resourced based view of the firm (RBV), business models are commonly related to the acquisition and allocation of resources (Garnsey et al., 2008) and in particular to knowledge and dynamic capabilities (Venkatraman & Henderson, 1998). This line of theory describes the business model as a dynamic capability that bridges the firm’s distinct competencies to its aspirations and outcomes (Eden & Ackermann, 2000). In this sense, the business model resembles the firm’s ability to appropriate its specific attributes in respect to its strategic objectives and ultimately in creating value.

Researchers are increasingly recognizing, however, that business models are not executed in isolation of competition (Hamel, 2000) and that firms can compete through their business models (Casadesus-Masanell, & Ricart, 2010). Developing new and effective business models can result in superior value creation (Morris et al., 2005) and replace old business models as the new standard for later generations of entrepreneurs to beat (Magretta, 2002). The business model thus poses a new source of competitive advantage (Markides & Charitou, 2004) and has been suggested to possibly play a central role in explaining firm performance (Zott, Amit, & Massa, 2011). Others have proposed that the composition of the business model is also highly contingent on technological determinants. Chesbrough and Roosenbloom (2002) define the business model

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as a coherent framework that takes characteristics and potentials of a technology as inputs that are converted to economic outputs through customers and markets, thereby conceiving it as a focusing device that bridges technological development and economic value creation. In this respect, it could be reasoned that the IoT-business model will mirror the technological attributes of IoT-technology.

Importantly, the business model concept is said to have a strong link to entrepreneurship where research is often focused on new ventures or innovation driven industries (George & Bock, 2011). Relevant to the topic of entrepreneurship is literature placing the business model in the perspective of opportunities, describing business models as the link between the entrepreneurial appraisal and exploitation of the opportunity (Fiet & Patel, 2008). Similarly, Amit & Zott (2001) describe the business model as a transactive mechanism for opportunity exploitation. Although research linking the business model to opportunity exploitation is still scant, it is argued that uncertain opportunities inherently deter the ability to predict optimal business models (Heirman & Clarysse, 2004).

A legion of new business opportunities is now emerging with the Internet-of-Things. Yet, the broad application of IoT-technology makes it hard to make detailed predictions about its business potential this early in its development. The IoT therefore is a particularly interesting domain to research business models as well as the EO of firms. What the Internet-of-Things beholds is discussed hereafter.

2.5

The Internet of Things paradigm

Multiple definitions exist on what the Internet-of-Things (IoT) paradigm entails. Mattern & Floerkemeier (2010) define that “The Internet of Things represents a vision in which the Internet extends into the real world embracing everyday objects. Physical items are no longer disconnected from the virtual world, but can be controlled remotely and can act as physical access points to Internet services”. An extensive definition of the IoT is provided by The Strategic Research Agenda of the Cluster of European Research Projects on the Internet of Things (CERP-IoT, 2009):

Internet of Things (IoT) is an integrated part of Future Internet and could be defined as a dynamic global network infrastructure with self configuring capabilities based on standard and interoperable communication protocols where physical and virtual ‘things’ have identities, physical attributes, and virtual personalities and use intelligent

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interfaces, and are seamlessly integrated into the information network. In the IoT, ‘things’ are expected to become active participants in business, information and social processes where they are enabled to interact and communicate among themselves and with the environment by exchanging data and information ‘sensed’ about the environment, while reacting autonomously to the ‘real/physical world’ events and influencing it by running processes that trigger actions and create services with or without direct human intervention. (CERP-IoT, 2009)

In an earlier definition, the ITU (2005) described that the basic idea of the IoT is that virtually every physical object in this world can become a computer that is connected to the Internet. Fleisch (2010) nuances this definition and argues that these objects do not become computers but become fitted with tiny computers, making them ‘smart’ things. Oriwoh et al. (2003) emphasize the possible functionalities of IoT, describing various purposes of IoT-technology, such as identification, tracking, communication, sensing and data collection.

Similar to early predictions on the ‘traditional’ Internet’s impact on business (i.e. Malone et al., 1987), practitioners as well as researchers project that the IoT will provide many new business opportunities that will lead to innovative products and services that over time will drastically change how firms do business in general (CERP-IoT, 2009; Atzori, Iera, &, Morabito, 2010; Gubbi et al., 2013). More specifically, it is said that the dynamic, rapidly changing and technology-rich digital environment of the IoT will provide fertile ground for products and applications that add value by exploiting a multitude of devices (Kyriazis & Varvarigou, 2013). Gubbi and colleagues (2013) state that the interconnection of objects has the potential to form ‘smart environments’ and foresee the application of IoT-technology in the domains of home and office, retail, cities, agriculture and forest, water infrastructure and transportation. The critical question remains how the IoT relates to the firm’s configuration, and how the firm can capture its potential value.

2.6

Business Models in the Internet-of-Things

The IoT has been argued to have a major influence on the nature of products and services and consequentially entire business models (Coroamã, Langheinrich, Mattern, & Rohs, 2005; El Sawy, Pereira, 2013). The Economist Intelligence Unit (2013) has stated that the foremost incentive for firms advance to the IoT is the potential financial returns, yet that capturing this new value will require novel business models that potentially make old business models obsolete. Furthermore, it has been argued that the complexity of the Internet to firms will increase even

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further with the advent of the IoT, and that new value systems and appropriate business models are needed (Westerlund, Leminen and Rajahonka (2014). Above all, as the IoT is commonly projected to visibly change the playing field in just a matter of a few years, firms will have to adapt rapidly (Kagerman, Osterle, & Jordan, 2010). Thus, capturing value with IoT-technology requests for the timely development novel types of business models.

Despite that the IoT continues to fuel a great deal of excitement, academic attention for business models in the domain of IoT has thus far resulted in only a handful of mostly prescriptive papers. Some authors have taken a structural approach on the IoT-business model by placing it in the perspective of larger digital ecosystems. For instance, researchers Turber, Vom Brocke, Gassman and Fleisch (2014) state that the complexity of the IoT will drive firms to go on multi-partner collaborations, change the customer into a co-producer of value and that reasons to collaborate can be both monetary as well as non-monetary. Turber and colleagues (2014) further state that because of the IoT, the intensified relationships between partnering firms will result in competitive advantage no longer being gained at mostly the firm level but at the level of networks of partnering firms that operate in larger ecosystems. Also endorsing this perspective, Westerlund et al. (2014) argue that the inevitably messy development of the IoT toward ecosystems of partnerships demands firms to shift focus to the business model from the firm-level to the network-level and even the larger ecosystem level, and foresee that value will be generated by both the shared and individual objectives of different actors in the network. According to Fleisch (2010) there are several value drivers in the IoT that will change business models on different levels in the firm. Fleisch (2010) distinguishes between the IoT value-drivers of that relate to the automation of previously simple manual tasks to the provision of extensive and mind-changing feedback from the environment. Fleisch (2010) formulates the impact of these drivers on business models on four different levels. In its most rudimentary form (‘level 1’) the IoT will automate but not change previously manual business processes and in full-fledged deployment (‘level 4’) will entirely overthrow the traditional business model as objects become constantly visible to firms, allowing for pay-per-use revenue models that will radically change the relationship between customer and vendor (Fleisch 2010). Bucherer and Uckelmann (2011) presented a set of specified IoT-business models based on four different scenarios of the IoT. The authors for instance described the Product-as-a-Service (PaaS) Model, referring to a pay-per-use model of products through IoT-technology, also exemplified by Fleisch (2010). Concentrating on the data collection, the ‘Information Service Providers’ business model is based on the gathering and selling of information gathered through IoT-technology, for instance providing services as real-time

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analytics and revolutionary comprehensive market research. As a result, IoT technology will demand much faster billing services between firms as paid information flows through the channels of many different shareholders in the IoT network (Bucherer & Uckelmann, 2011). 2.6.1 Research on IoT-business models

The only published paper to currently have presented thorough empirical research on IoT-business models is that of Dutch researchers Dijkman, Sprenkels, Peeters & Janssen (2015). This article hence forms the basic reference for the present research. Aiming to develop a business model framework suitable for the IoT, the authors held a dozen interviews with different IoT-professionals. Results from the interviews served as the basis for a survey among 72 managers (of which 69% stated to be expert on the topic of IoT) who worked for a variety of firms of different size and age, and operating in different industries. Dijkman et al. (2015) aimed to observe which of the different business model components would become important in the IoT and gathered their data by means of the Business Model Canvas (BMC) proposed by Osterwalder & Pigneur (2004) (for illustration of the BMC, see appendix A).

The BMC is well-received among researchers and practitioners for its practical use and theoretical foundation. The BMC is a design-approach of the firm and provides a strategic mapping tool. This tool addresses nine interrelated components that represent the essential elements of the firm’s business logic. These components are (1) the value proposition of the offering, (2) the customer segments that are targeted, (3) the customer relationships that are maintained, (4) the channels through which customers are reached, (5) the key activities that the firm conducts to offer value to the customer, (6) the key resources needed to do so, (7) the key partners of the firm, (8) the costs made and (9) the revenue streams through which the firm monetizes its created value.

Dijkman et al., (2015) found that the value proposition was perceived to be significantly more important relative to other components in the BMC. The importance of the value proposition is inline with business model literature (Chesbrough & Roosenbloom, 2002; Morris et al., 2005) and the notions on the new ways of value creation and novel value systems in the IoT (Westerlund et al., 2014; Turber et al., 2014). Yet, prescriptive literature on IoT-business models also consistently emphasizes that IoT demands firm to adopt new forms of partnerships, customer relationships and revenue streams (i.e. Westerlund, Leminen, & Rajahonka, 2014). A reason for this finding may rest in the research sample in the study by Dijkman and colleagues (2015), which consisted of managers working for established firms. This makes it likely that these

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managers have also worked with more traditional types of business models (Chesbrough, 2010; Huang, Lai, Lin, & Chen, 2013). It is possible for larger firms or corporations that the established cultures, policies, processes and systems that have led to the formation of firms’ traditional business models to spillover in the formation of new business models (Markides, 2013). Yet, the present study examines the business models of IoT-startups. As the startups in the present research initiated their business in the domain of the IoT, their business models can be expected to be less influenced by such traditional spillovers and therefore more in line with the prescriptive notions on IoT business models (i.e. Bucherer & Uckelmann, 2011). Hence the following hypothesis is formulated:

H2a: in the IoT-business models, the value proposition, key partnerships, customer relationships and revenue streams components are perceived to be significantly more important than other business model components

The before discussed literature on IoT-business models recurrently describes that the components of value proposition, key partnerships, customer relationships and revenue streams will become of significant importance in the IoT. When establishing new organizations, entrepreneurs carefully judge current and possible future business models (Perlow, Okhuysen, & Repenning, 2002). It is therefore reasonable to argue that startups focusing on these specific components are willing to try out innovative business models, which could be the result of an entrepreneurial mentality as described in EO literature. Thus, being entrepreneurially orientated focuses the firm on these particular aspects of the business model. It is therefore reasoned that more entrepreneurial firms differ from less entrepreneurial firms on this aspect. Hence the following hypothesis is proposed:

H2b: IoT-startups with higher levels of EO assess the value proposition, key partnerships, customer relationships and revenue streams business as significantly more important for their IoT-offering in comparison to IoT-startups with lower levels of EO

Looking more closely at the individual business model components, Dijkman et al. (2015) measured what specific types within the nine components were thought to become important in the IoT (for description of the component types by Dijkman et. al. (2015) see appendix B). These results thus suggest what the specific configurations within the business model components could look like in the IoT-domain. The BMC components are briefly discussed in relation to the findings of Dijkman et al. (2015).

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2.7 IoT-Business model configurations

Value Proposition

The first component in the BMC is the Value Proposition, which can be understood as a statement of the benefits the firm delivers to its customers (Bagchi & Tulskie, 2000). The value proposition is composed of a set of elementary offerings of the firm and addresses what value the firm’s products and/or services pose to customers, which of their problems it solves and what needs it fulfills. Firms must therefore specify the reasoning how the offering has value for the customer, the utility the offering has customers and the price-level at which it is offered (Osterwalder & Pigneur, 2004). Dijkman et al. (2015) observed that the value propositions of convenience/usability, getting the job done, performance, possibility for updates and comfort were assessed as significantly more important for the IoT than other types value proposition types. It was further found that the value proposition types of price, newness and brand/status were perceived as significantly less important to IoT-business models than other value proposition types. To test whether these findings are also resembled in the business models of IoT-startups in the present study, the following hypotheses are proposed:

H3a: the value proposition types of ‘convenience/usability’, ‘getting the job done’, ‘performance’, ‘possibility for updates’ and ‘comfort’ are significantly more represented in the business models than other types of value proposition

H3b: the value proposition types of ‘price’, ‘newness’ and ‘brand/status’ are significantly less represented in the business models than other customer relationship types

Customer Segment

The Customer Segment component pertains to the segmentation of the target customers. Defining the target customer allows the firm to focus resources to customers that are most inclined to its value proposition (Chesbrough & Rosenbloom, 2000). Considering the building block of Customer Segments, Dijkman et al. (2015) found no significant difference between the types of customer segments. To test this finding, the following hypothesis is proposed:

H4: none of the customer segment types is represented significantly more or less in the business models

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The Customer Relationship component concerns what type of relationship the firm builds and maintains with its customers. The goal of establishing customer relationships is to yield the profits that drive the business. These profits can be gained through the acquisition of new customers, the improvement of the profitability of the current customers or the extension of current customer relationships (Grant & Schlesinger, 1995). Every interaction with customers influences the strength of the customer relationship. Yet, as those interactions incur costs a firm must carefully consider the type of relationship it wants to establish to leverage customer equity (Osterwalder & Pigneur, 2004). Dijkman et al. (2015) observed that the customer relationship types of communities and co-creation were perceived as significantly more important to IoT-business models than other types, while the type dedicated assistance was perceived as significantly less important than other business model types. To test whether this is resembled in the business models of the IoT-startups, the following hypotheses are formulated:

H5a: the customer relationship types of ‘communities’ and ‘co-creation’ are significantly more represented in the business models than other customer relationship types

H5b: the customer relationship type of ‘dedicated assistance’ is significantly less represented in the business models than other customer relationship types

Channels

The Channels component relates to the distribution channels through which customers are reached and forms the connection between the firm’s value proposition and the target customers. A distribution channel describes how a firm gets in touch with customers and has the purpose to deliver the right quantities of the right products or services available at the right place to the right people (Berthon et al., 1999). To not spill time or resources, it is key that a firm uses distribution channels that do not compete when simultaneously reaching the same target customers (Bucklin, Thomas-Graham, & Webster, 1997). Concentrating on the business model component of Channels, Dijkman et al. (2015) only found the channel type web sales to be perceived as significantly important to IoT-business models, while the channel type own stores was perceived as significantly less important. To test whether this finding is translated in the business models of IoT-startups in the present study, the following hypotheses are proposed:

H6a: the channel type of ‘web sales’ is significantly more represented in the business model than other channel types, while

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H6b: the channel type of ‘own stores’ is significantly less represented in the business model than other channel types

Key activities

The Key Activities component describes the activities that are necessary for the firm to provide the value proposition, maintain its customer segment and receive its revenues and can be conducted by the firm itself or by partners (Osterwalder & Pigneur, 2004). A distinction is made between primary activities that directly enable the firm to create, market and deliver its value proposition, while secondary activities are those that enable the primary activities to take place such as firm infrastructure, human resource management, technology management and procurement (Porter, 1985). The BMC thus considers primary activities. Dijkman et al. (2015) found that only the activity of product development was perceived as significantly more important than other activities, whilst logistics and somewhat surprisingly also partner management was assessed as significantly less important to IoT business models. Also, the key activity of customer development and partner management was not found to be significantly more or less important than other types of key activities. This perhaps is the result of the participating managers working at larger firms, which are likely to have already built larger networks and customer relationships. Startups are likely to still be in the process of developing these aspects of the business, however (York & Danes, 2014). Therefore the following hypotheses are formulated:

H7a: the key activities types of ‘product development’, ‘partner management’ and ‘customer development’ are significantly more represented in the business model than other key activities,

H7b: the key activities type of ‘logistics’ is significantly less represented in the business model key activities

The key activities component further is particularly interesting for examining the EO-construct where it involves the willingness to innovate, take on risky projects and be pro-active. Hence it can be expected that the activities related to product development, platform development and software development are associated with EO. Hence the following hypothesis is formulated: H7c: a significant positive relationship exists between EO and the key activities ‘product development’, ‘platform development’ and ‘software development’

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The Key Resources component in the BMC describes the resources that are the source for the Key Activities of the firm to deliver its value proposition to customers. Key resources can be tangible, intangible or human-skill based (Grant, 1991) and pertains to the firm’s internal capabilities as well as the physical resources, intellectual property (i.e. brands or patents) and financial resources that enable the direct and indirect activities that are needed for the firm to create value. Dijkman et al. (2015) found that the resources described as software and employee capabilities were perceived to be of significantly more importance than other types of key resources, whilst only financial resources were perceived to be of significantly less importance. However, startups are seen to be highly dependent on financial resources (Wiklund & Shepherd, 2003). It is therefore expected that financial resources are significantly more represented in the business models of IoT-startups. Therefore the following hypothesis is formulated:

H8: the key resources types of ‘software’, ‘employee capabilities’ and ‘financial resources’ are significantly more represented in the business model than other key resources

Key partnerships

Key Partnerships relate to the cooperative agreements formed between two or more independent firms and come in the form of alliances and supplier relationships. Partnerships allow the firm to leverage certain capabilities, resources or activities required to deliver the value proposition that it does not posses itself and are (too) costly internalize. The firm’s decision to partner is contingent on the cost of transactions, central to transaction cost economics. This stream in economic theory identifies situations in which alliances are more efficient than turning to the market or internalize transactions (Williamson, 1987). In the aspect of Key Partners, Dijkman et al. (2015) concluded that many different partners were perceived as to become of significant importance for the IoT-business model, namely software developers, launching customers, data interpretation and hardware producers. Distributors, other suppliers and logistics were assessed as significantly less important to the IoT-business model. To test whether this finding is also resembled in the business models of IoT-startups, the following hypotheses are tested:

H9a: the key partner types of ‘software developers’, ‘launching customers’, ‘data interpretation’ and ‘hardware producers’ are significantly more represented in the business models than other types of key partners

H9b: the partner type of ‘distributors’, ‘other suppliers’ and ‘logistics’ are significantly less represented in the business models than other types of key partners

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Cost structure

The component of Cost Structure describes all the costs a firm makes needed to create, market and deliver the value proposition to its customers. It is composed of different accounts that define a specific type of expenditure. Keeping a close eye on incurred costs is critical for a firm’s profitability (Linder & Cantrell, 2000). Dijkman et al. (2015) found that the cost structure type of product development was assessed as significantly more important to IoT-business models than other types of cost structures. The type of logistics cost, on the other hand was assessed as significantly less important to the IoT-business model. To test this finding in the present study, the following hypotheses are formulated:

H10: the cost structure type of ‘product is significantly more represented in the business models than other cost structures

H10b: the cost structure type of ‘logistics cost’ is significantly less represented in the business models than other cost structures

Revenue streams

The Revenue Streams component refers to the firm’s revenue models and measures how the firm monetizes and receives the value it offers to customers. Revenue streams are essential to a firm’s long-term survival (Shafer et al., 2005) and can be generated through selling, lending or licensing a product or taking a cut of a transaction or advertisement (Berthon et al., 1999). Dijkman et al. (2015) found that the revenue stream types of subscription fees, usage fee and asset sale were perceived as significantly more importance, whilst the IoT-specific types of startup fees, installation fees and brokerage fees were seen as significantly less important than other types of revenue streams. Hence the following hypotheses are formulated:

H11a: the Revenue Stream types of ‘subscription fees’, ‘usage fee’ and ‘asset sale’ are significantly more represented in the business model than other types of revenue streams

H11b: the Revenue Stream types of ‘startup fees’, ‘installation fees’ and ‘brokerage fees’ are significantly less represented in the business models than other types of revenue streams

Startups in the internet-of-things : an opportunity exploitation perspective

Master Thesis

MSc. Business Administration: Entrepreneurship & Innovation