“How to develop a practical tool to evaluate the business performance of technology startups in
the Netherlands – a mixed-method approach”
Master Thesis
MSc BA Strategic Innovation Management Faculty of Economics and Business
University of Groningen
25th June 2018
Supervisor: Dr. Wilfred Schoenmakers Co-assessor: Dr. Charlie Carroll
Name: Massimo Adorno Student number: S3457699 E-Mail: m.adorno@student.rug.nl
Word count main text: 13557 Word count total: 21693
Abstract
Startups play a fundamental role for the economic development of the Netherlands. Thereby, especially technology new ventures make up a big share. However, most of these startups fail during the initial stages of new venture development due to a poor decision-making by the founder. Therefore, it is essential to identify underperforming business areas within the new venture, especially in the first years after founding. The entrepreneurial literature lacks a practical tool that includes the most relevant success factors for technology startups while being able to operationalize and measure them contemporaneously. Hence, this study focuses on the practical development of such a tool, taking into account a mixed-method research approach, including the extant literature, additional interviews as well as a quantitative application. The ultimately developed tool, consisting of a 129-items questionnaire, is applied in the final research stage on 27 Dutch technology new ventures. Concluding, by means of the resulting evaluative output of this tool, startup owners and potential stakeholders are empowered to recognize underperforming, internal business areas within the new venture and consequentially address them. Ultimately, this study contributes to fill an academic gap by developing a practical artifact to solve real-life problems, what can be placed within the context of Design Science theory.
Keywords: Technology new ventures, technology startups, success factors, business performance, scanning tool, internal factors, factor operationalization
Table of Content
1. INTRODUCTION ... 5
1.1RESEARCH QUESTIONS ... 6
2. THEORETICAL BACKGROUND ... 7
2.1.DEFINITION OF A TECHNOLOGY STARTUP ... 8
2.2LITERATURE REVIEW ... 8
2.2.1 Entrepreneur Characteristics ... 10
2.2.2 Resources ... 11
2.2.3 Strategy ... 13
2.2.4 Organizational factors ... 14
2.2.5 Business performance ... 14
3. METHODOLOGY ... 18
3.1RESEARCH PHASES ... 18
2.2RELIABILITY,CONTROLLABILITY &VALIDITY ... 20
4. VALIDATION OF THEORY ... 21
5. MEASURES AND OPERATIONALIZATION ... 26
6. SCORE CALCULATION ... 27
7. RESULTS ... 29
8. DISCUSSION AND LIMITATIONS ... 32
8.1THEORETICAL CONTRIBUTION ... 34
8.2PRACTICAL IMPLICATIONS ... 35
9. FUTURE RESEARCH ... 36
10. CONCLUSION ... 37
11. REFERENCES ... 38 APPENDIX I ... I APPENDIX II ... II APPENDIX III ... VI APPENDIX IV ... XIV APPENDIX V ... XVIII APPENDIX VI ... XXVII APPENDIX VII ... XXVIII
List of Figures
Figure 1. Summarized frame of Gilbert et al. (2006) - Own creation ... 9
Figure 2. Average experts’ weightings, sorted by area and factors, n=7. ... 24
Figure 3. Weighted success factors. ... 26
Figure 4. Diagram of correlation. ... 31
List of Tables Table 1. Success area and factor list, including business performance dimensions. ... 16
Table 2. Final success area and factor list. ... 23
Table 3. Exemplary score calculation for one success area. ... 28
Table 4. Questionnaire score results. ... 31
Table 5. Regression output summary, n=27. ... 31
List of Appendices
APPENDIX I: Interviewed Experts ... I APPENDIX II: Expert-Interview Guide ... II APPENDIX III: Transcript of Expert-Interviews ... VI APPENDIX IV: Factor Operationalization and Measurement ... XIV APPENDIX V: Questionnaire (Tool) ... XVIII APPENDIX VI: Participating Startups ... XXVII APPENDIX VII: Exemplary Evaluative Report for Startup #3 ... XXVIII
1. Introduction
As is very well known, an important element of economic policy targets is represented by economic growth (Martin, Picazo, & Navarro, 2010). Entrepreneurial activities, such as startups and small businesses, are known to foster sustainable economic growth in highly developed countries (Acs &
Szerb, 2007). More specifically, entrepreneurship is able to increase innovation, foster productivity and development on a regional and local level whilst fighting against unemployment and poverty (Reynolds, Storey, & Westhead, 1994; Robson, Wijbenga, & Parker, 2009). The requirements for this growth consist of a group of people who are willing to start new firms and businesses by assuming risks and partly using own funds (Martin et al., 2010).
Nowadays, the Netherlands represent a predominantly active sector of startups and entrepreneurs. The total early-stage Entrepreneurial activity rate (TEA), which is represented by the percentage of adults between 18 and 64 years starting or already operating a business younger than 3.5 years, has increased to 9.5% (in 2014) compared to 5.1%, ten years before. This figure ranks the Netherlands eleventh of 30 innovative-driven economies worldwide, seeing Qatar as the leader with more than 16% (Span, van Stel, & van den Berg, 2015).
Particularly the technological sector is of interest as firms are globally growing there twice as fast as the world economy (Startup Genome LLC., 2017), whereas startups constitute a major share of this growth, thus emphasizing the importance of technology new ventures. Therein, technology startups delivering information and communication products or services showed to be critical for regions and their citizens to develop technological change (Startup Genome LLC., 2017).
As mentioned before, new ventures, hence startups, are a fundamental source of new jobs contributing to economic growth, meaning that assessing its performance is interesting for various parties, including the startup owners, competitors, the government as well as researchers and investors (Brush & Vanderwerf, 1992). Especially growth-oriented startups represent an important driver of job creation and development (Gilbert, McDougall, & Audretsch, 2006). However, despite this important role for the economy, many startups fail during their first years. According to Statistic Brain (2017), the number of startups that survive the second year amounts to 36%, while the amount of technology startups which failed after four years is 63% (Statistic Brain, 2017). Due to these failure rates, improving on performance in an early stage represents a critical factor to success or failure (Brush & Vanderwerf, 1992). Therefore, evaluating business performance is necessary to determine the status quo of a business which in turn can serve as a base for recommendations leading to an improved performance (Guerra- López, 2007). Hence, there are two related tasks which are important: monitoring success factors and consequentially suggesting recommendations, based on the determined potential for improvement (Guerra-López, 2007; Johri, 2010).
Generally, the literature created several holistic tools for serving the purpose of assessing the whole business. However, such tools failed to combine the two aforementioned tasks of monitoring and consequently suggesting recommendations. Either a tool is focused on simply monitoring performance
or alternatively on providing a solution-oriented approach to improve the business performance (Cadle, Paul, & Turner, 2014) as for instance the Balanced Scorecard, the Intellectual Capital approach (Bontis, Dragonetti, Jacobsen, & Roos, 1999), the SWOT analysis or the EFQM Excellence Model (Wongrassamee, Simmons, & Gardine, 2003). Tools, such as the Balanced Scorecard and the SWOT analysis, do not explain which different aspects of a business are the most relevant to consider in-depth (Chron.com, 2018; Hill & Westbrook, 1997) in influencing the business performance. Another drawback is that these tools have to be applied by experienced employees in order to create an added value for the firm. This and other individual challenges, such as for instance a high level of uncertainty for startups (Ucbasaran, Shepherd, Lockett, & Lyon, 2013) have to be taken into account while having the expertise to execute such an analysis (Johri, 2010). Assessing different success areas in new ventures which have an impact on business performance has already been done (Sandberg & Hofer, 1987; Van de Ven, Hudson, & Schroeder 1984). Yet, there is a missing consensus about the most important and efficient factors (Cooper, 1993; Gartner, 1988; VanderWerf & Brush, 1990) for especially technology startups, underscoring that there is a clear gap for practitioners. The aforementioned tools lack, due to these challenges, an applicability for startups, hence, calling for an adequate framework to assess success factors related to the business performance.
The academic relevance and contribution of this study to the literature, by creating a tool, can be placed within the exploratory Design Science theory as its research is focused on the development of an artifact that in turn can be used as a framework to solve problems, corresponding to a means to an end-solution (Holmström, Ketokivi, & Hameri, 2009). Consequently, the tool that the current study is aiming to create is classifiable as a bridge between practice and theory.
Summarizing it can be said that the scope of this research is to find the most important success factors for technology startups, while seeking out the most suitable way to measure those, by means of literature and by additional interviews. Finally, these findings shall be integrated into an applicable tool.
Hence, the overall contribution consists in creating a framework, that, on the one hand, synthesizes the relevant literature about success factors, including its measurement methods. On the other hand, this framework will serve as an applicable and practical tool for practitioners. By means of this tool, consultants, or other types of advisors, should be capable to conduct an analysis of technology startups and determine the business performance and possibly deduct useful recommendations for future actions in regard to an improvement of this very performance.
1.1 Research Questions
The introduction section shows that this research aims to finding a way to create a scanning tool for technology startups. This leads to the following research question:
How can a framework be built in order to measure the business performance which indicates the potential improvement areas of technology startups?
However, this question solely points out the way of developing this very tool. It does not include which specific success factors therefore have to be taken into account. Hence, one necessary subordinated question is:
Which success factors must this framework comprise in order to measure the business performance of technology startups?
Furthermore, in order to be able to adequately collect the data, the way to measure those factors constitutes a high relevance about the success of this study, which leads to the second subordinated question:
How can these factors be validly measured?
Thirdly, there is a lack of findings referring to the influence of success factors to business performance while considering their relative importance. Hence, the third subordinated question aims to fill the gap related to the relative contribution of every single factor:
What is the weight of every success factor?
Lastly, a high feasibility of applying the developed tool, which constitutes the added value for scholars and practitioners, leads to the fourth subordinated question:
To what extent is the result of an empirical testing of the developed tool validly interpretable?
The remainder of the paper is structured as follows: First, the theoretical background section provides fundamental definitions for the scope of this study as well as the chosen approach to determine relevant success areas which in turn will serve as a foundation for the literature review of single success factors. Secondly, the methodology section depicts the research process and its different phases of research conduction. Thereafter, the results and findings of the success factor validation through selected expert-interviews are presented. Then, the operationalization of the factors as well as the score calculation are depicted as they account for major parts of the finalized tool. The last part comprises the outcome of the tool’s application. The conclusion will complete this paper, after having elaborated on the discussion section, the limitations and future research, as well.
2. Theoretical Background
This chapter will provide a structured overview about the startup terminology, including a definition of a technology startup as well as a literature review about key success factors for startups and different dimensions how to determine business performance. First, the definition is provided. Second, a review of the extant literature related to the key success factors which are influencing the business performance of startups is provided, guided by Gilbert et al. (2006), followed by an elaboration of the success dimensions.
2.1. Definition of a Technology Startup
Startup founders strive to grow fast by applying an innovative and strategic management behavior (Burns & Dewhurst, 1996). In this connection, it is possible to distinguish between the type of business when entrepreneurs found a new venture, namely lifestyle and rapid growth companies (Morris, Schindehutte, & Allen, 2005). As the ambition to grow leads to different implications for internal competencies, resource management and competitive strategies, lifestyle ventures might not necessarily commit to those implications in the same way as growth-oriented startups do (Morris et al., 2005).
Hence, lifestyle ventures are excluded from this research. Moreover, entrepreneurial new ventures are seen as a new market entrant and simultaneously as a new supplier for customers (Gartner, 1985). This understanding of a startup is confirmed in some way by Ries (2012) defining it as “a human institution designed to create new products and services under conditions of extreme uncertainty” (p.27). There is no general agreement on what constitutes a new venture in terms of age (Amason, Shrader, &
Thompson, 2006). However, the taken decisions in the first three to five years of the startup’s history are considered to be crucial for success (Bamford, Dean & McDougall, 2004). Therefore, an age up to four years (Pena, 2002) was chosen to define a new venture for this research. Kakati (2003) specified the sectors in which technology startups operate, comprising the following industries: Telecom and data communication, IT, computer software, bio-technology, pharmaceutical as well as industrial products and machinery.
Based on these above stated descriptive elements, this study defines technology startups to comprise the following four criteria:
(1) Aim to be a fast-growing company
(2) Be a new market entrant for competitors and a new supplier for customers by delivering new products or services
(3) The startup shall be newly formed and hence not older than 4 years
(4) Executes the business in one of the following industries: Telecom and data communication, IT, computer software, bio-technology, pharmaceutical as well as industrial products and machinery.
2.2 Literature Review
This literature review is needed as a start to find answers to the challenges which are reflected in the two subordinated research questions: Which success factors must be included to measure the business performance of technology startups? and How can these factors be validly measured?
Many authors have already researched on the assessment of several success factors in new ventures which have an impact on business performance (Sandberg & Hofer 1987; Van de Ven, Hudson,
& Schroeder 1984). However, they lack a consensus about the most important and efficient factors (Cooper, 1993; Gartner, 1988; Van der Werf, 1989) for technology startups. The underlying frame used as a foundation for building the literature review of success factors is provided by Gilbert, McDougall
and Audretsch (2006) due to the following facts: To the best of my knowledge, Gilbert et al. (2006) provide the most actual and updated literature frame for success areas related to new ventures and their business performance. However, the scholars fail to state at which fine-grained and subordinated factors exactly to look at. Consequently, this makes a further synthesis by means of a literature review necessary to enfold existing findings (Pratt, 2009). In their study, Gilbert et al. (2006) synthesized 48 different empirical studies which were published in management and entrepreneurship journals between the 1980s and 2006. During this process, the scholars were not focusing on specific industries, implying that this framework represents a general foundation, which can be subject to change due to the specificity of the technology sector in the course of this study. They related new venture growth in various areas of a startup’s operations as performance measurement to success areas (Gilbert et al., 2006). A holistic coverage of all success factors of a startup’s performance would take into account both the internal and external perspectives (Barringer, Jones, & Neubaum, 2005). However, since the resulting tool of this study is expected to address areas that the startup shall influence or change, external success factors are excluded. Hence, the success areas which will serve for the literature review, identified by Gilbert et al.
(2006), are Entrepreneur Characteristics, Resources, Strategy and Organizational Factors, in turn excluding Industry context and Geographic location (see Figure 1). Through these success areas, the scholars further distinguished if growth occurs domestically or in international markets as well as internally or externally. This distinction was not taken into account as this research solely focuses on internal success factors of startups in the Netherlands.
Figure 1. Summarized frame of Gilbert et al. (2006) - Own creation
In the following, this frame will be applied to identify the single success factors in the course of the literature review. Hence, based on this framework, every success factor which emerged during the literature review will be assigned to one of the four stated success areas. Based on the reviewed factors
in the literature, and in relation to the four areas of Gilbert et al. (2006), logical subcategories were used to code the respective factors. Thus, each success factor or subcategory which was found, has been noted first. Then, after having checked if the factor’s or category’s definition fits into the research scope, the respective factor was assigned to one of the four elaborated success areas. Consequently, only the most prevalent and most often found success factors were taken into account. The following example shall clarify this procedure: For the area Strategy, the review was performed by searching for the combined terms “strategy new ventures”, “strategic approach new ventures”, “strategy startup” or similar. The most relevant results were then two different strategic approaches, namely a differentiation strategy and a focus(ed) strategy which can be both simply coded to the subcategory market strategies, which in turn obviously belong to the area Strategy. The resulting factor list, including the factors and the respective sources are depicted by Table 1.
The following sections (see 2.2.1 - 2.2.4) are structured as follows: After a brief introduction about which success factors emerged within the respective area, each factor is elaborated.
2.2.1 Entrepreneur Characteristics
Within the first area of Gilbert et al. (2006), Entrepreneurial Characteristics, several success factors were found to play a fundamental role for a startup’s performance, such as Higher education, Parents’
entrepreneurship experience, prior entrepreneurial and industry experience, founding team size, planning as well as leadership (Baum, Locke, & Smith, 2001; Brinckmann, Grichnik, & Kapsa, 2010;
Cooper, Gimeno-Gascon, & Woo, 1991; Cooper, Gimeno-Gascon, & Woo, 1994; Cooper et al., 1991;
Duchesneau & Gartner, 1990; Eisenhardt & Schoonhoven, 1990 Sapienza & Grimm, 1997),
Higher education
Several studies confirm the level of education as an existent proxy for entrepreneurial abilities, whereas college education enhances these abilities and skills comprising, for instance, imagination, foresight, computational as well as communication and search skills (Barringer et al., 2005; Watson, Hogarth-Scott, & Wilson, 1998; Sapienza & Grimm, 1997).
Parents’ entrepreneurship experience
The literature shows evidence that growing up with entrepreneurial parents stimulates the children’s desire, intention and behavior to become founders as the parents served as role models (Ucbasaran et al., 2013), leading to a greater chance of survival, but not of growth (Cooper, Gimeno- Gascon, & Woo, 1994; Lussier, 1995).
Prior entrepreneurial experience
One of the most consistent predictors of new venture performance is prior entrepreneurial experience (Barringer et al., 2005). Entrepreneurial experience is reflected by the number of startups the
entrepreneur was involved, including which role he/ she played (Stuart & Abetti, 1990). Experienced founders will probably avoid typical mistakes compared to entrepreneurs without any experience, who would in turn face a higher probability of failure (Barringer et al., 2005; Cooper & Bruno, 1977).
Prior industry experience
Higher industry experience means that the founder benefits by a better understanding of different facets of the respective startup industry (MacMillan & Day, 1987), for instance, by having previously worked in a firm serving similar products and markets, or using similar technology in relation to the founded startup (Cooper, Woo, & Dunkelberg, 1988). This experience leads to a positive impact on the performance and survival of the startup (Cooper, Gimeno-Gascon, & Woo, 1994).
Founding team size
A larger team size of founders within a new venture was found to be advantageous for the business performance as larger teams unite different aspects like more resources, professional contacts, a faster decision-making, talent, efficient task-sharing as well as the provision of psychological support to each other (Barringer et al., 2005; Barkham, 1994; Eisenhardt & Schoonhoven, 1990).
Planning
The literature suggests that new ventures which spent a significant time in thoroughly planning their business increase the chances to accomplish various business goals which have been set upfront (Barringer et al., 2005). More specifically, Duchesneau and Gartner (1990) found out that firms engaging in detailed planning activities have a decreased level of uncertainty and a facilitated decision- making process while being more successful in terms of growth (Barringer et al., 2005; Brinckmann et al., 2010).
Leadership
Literature has shown, the ability to lead others within a team has an impact on the survival of the new venture (McMillan, Siegel, & Narasimha, 1985). Moreover, founders with leadership experience were not only significantly less likely to fail, but were even able to raise larger investment capital than those without any gained leadership abilities (Brüderl, Preisedörfer, & Ziegler, 1992).
2.2.2 Resources
The second area by Gilbert et al. (2006) reflects the necessity of resources for entrepreneurs in order to be able to execute strategic decisions (Arthurs & Busenitz, 2006). Supported by the resource based view of the firm, stating that an emphasis on resources can lead to a competitive advantage (Barney, 1991;
Wernerfelt, 1984), the most important factors which emerged during the literature review and were found to be beneficial for the startup’s performance are financial capitalization, working capital,
governmental allowances, intangible assets, interorganizational relationships and access to accelerators/ incubators (Bamford et al., 2004; Barringer et al., 2005; Cooper et al., 1988; Halabi &
Lussier, 2014; Hormiga, Batista-Canino, & Sanchez-Medina, 2011; Pena, 2002).
Financial capitalization
New ventures with a higher stack of financial capital tend to be more successful in the long-run (Cooper et al., 1988) presuming that startups simply have more time at their disposal to survive by solving their issues and for supporting strategic decisions (Zahra & Bogner, 2000). Also, the amount of initial capital was associated with a higher performance (Cooper et al., 1994).
Working capital
The literature suggests to value working capital – the cash a firm requires to run through their daily operations (BusinessDictionary, 2018) - as an essential foundation for being successful as startups often face resource constraints and challenges in obtaining access to resources (Halabi & Lussier, 2014).
Compared to the factor financial capitalization, which is long-term oriented (see above), working capital can be considered thus as short-term liquidity provision.
Governmental allowances
Even though the initial stack of financial capital of a new venture may come from the founder or close relatives (Berger & Udell, 1998), the required financial resources to let the new venture further grow are not covered by the founder’s personal network of resources. Therefore, getting allowances by the government in the initial stages or alternatively having connections to other funding possibilities was found to be essential for predicting success of new ventures (Dahlqvist, Davidsson, & Wiklund, 2000; Lee, Lee, & Pennings, 2001).
Interorganizational relationships
Interorganizational relationships might comprise networks, alliances as well as trade associations (Barringer & Harrison, 2000). Participating in those relationships can have a positive impact on the new venture’s performance by getting access to its cooperation partner’s intellectual capabilities, resources and managerial talent (Barringer et al., 2005; McGee, Downling & Megginson, 1995).
Intangible assets
the literature suggests that intangible assets are very important for a competitive advantage, hence the performance, especially for new ventures in the first years (Bergmann Lichtenstein, & Brush, 2001; Hormiga, Batista-Canino, & Sanchez-Medina, 2011) while focusing less on material assets.
Intangible assets are defined as resources which can be converted into future earnings (Sullivan, 1999).
The most important types of intangible assets are information (databases, software), innovative property (R&D, patents, copyrights, designs or trademarks), and economic competencies (brand equity, networks, marketing and firm-specific knowledge) (Corrado, Hulten, & Sichel, 2006).
Access to accelerators/ incubators
Outside resources, such as competencies or a professional network from external parties, are beneficial for the business performance of a new venture (Gilbert et al., 2006). Getting into programs like incubators or accelerators provides the advantage for technology startups of getting mentorship opportunities as well as getting into contact with business partners or equity investors (Chen, 2009;
Cooper, 1985; Pauwels, Clarysse, Wright, & Van Hove, 2016).
2.2.3 Strategy
Strategy represents the third area by Gilbert et al. (2006). The choices of strategies are subject to a
“contingency” perspective, meaning that every startup has to reflect the best strategic choice, based on the products/ services they offer, the competition and the market situation (Eisenhardt & Schoonhoven, 1990; Gibson, McDowell, & Harris, 2011; Sandberg & Hofer, 1987) for positively influencing the business performance. Hence, the most influential success factors on a startup’s performance are Differentiation Strategy, Focus(ed) Strategy, Creating a Unique Value and Innovation.
Differentiation strategy
A differentiation strategy constitutes a product or service the company is offering to be perceived as qualitatively higher in the market or the specific industry compared to competitors, reflecting different facets such as design, technology, brand, features or other dimensions (Porter, 1980).
This strategy was found to have a positive impact on sales, employment and profit growth (Baum et al., 2001) in new ventures.
Focus(ed) strategy
The focus strategy serves a particular buyer group in a mostly narrow market, also called niche, meaning that the firm is able to accomplish above-average returns by serving a single product/ service more efficiently or effectively than competitors who are competing in more than one market (Porter, 1980). Focused strategies, when operationalized as higher revenue by one single product, were found to have higher sales growth rates by focusing all resources on this very product (Siegel, Siegel, &
Macmillan, 1993).
Creating unique value
By providing a more affordable or a new way of satisfying a need, accomplishing a task or solving a problem which has not been done before, a new venture is able to provide unique value to the
customer while having a positive impact on the business performance (Barringer et al., 2005; Kim &
Mauborgne, 1997).
Innovation
The literature suggests that innovation is one of the requirements of creating a unique value to the customer (Barringer et al., 2005). Being innovative can result in experimentation, creativity and idea generation in order to develop and launch unique and beyond state-of-the-art products, services or technologies, hence, increasing the positive effect on firm performance (Lumpkin & Dess, 1996; Stuart
& Abetti, 1987; Tan, 1996; Verhees & Meulenberg, 2004).
2.2.4 Organizational factors
Lastly, within the fourth area of the frame by Gilbert et al. (2006), the literature showed organizational factors to have a positive impact on business performance of new ventures, are Structural Elements as well as Incentives for Employees (Barringer et al., 2005; Gerhart & Milkovich, 1990; Gilbert et al., 2006;
Stuart & Abetti, 1987).
Structural elements
Depending on the degree of the organizational centralization, the impact on business performance is different. A functional specialization is needed for a positive business performance when a new venture has been growing for longer (Kazanjian & Drazin, 1990; Olson & Bokor, 1995). Hence, the decision-making process has to be more centralized for smaller and newer startups and decentralized for more advanced or grown ones in order to positively affect the performance (Gilbert et al., 2006;
Stuart & Abetti, 1987).
Incentives for employees
Bonus plans, profit sharing, stock options or other performance-based incentives as well as employee stock ownership plans have become increasingly important for the performance of new ventures as they are intended to help startups motivate, attract and retain employees, increase their productivity and to share the risk with them (Barringer et al., 2005; Landau & Leventhal, 1976; Zenger, 1992).
2.2.5 Business performance
This section is detached from Gilbert et al. (2006) and reviews the most common business performance dimensions of new ventures. On this, there is no common denominator which restricts the performance to one dimension as the best to apply (Brush & Vanderwerf, 1992). However, the literature points out two dimensions, namely Profitability and Growth (Brinckmann et al., 2010; Murphy, Trailer & Hill, 1996). Profitability comprises returns on investment or -equity, while growth is mostly measured by
changes in sales, employment and market share. For new ventures, to which these dimensions do not apply as they might not have yet launched a product/ service, the dimensions meeting expectations and different contributions are more relevant. Lastly, survival is also included as many studies used it as a dependent performance variable.
Return on investment/ equity
The performance of new ventures can be commonly measured by return on invest or equity (Murphy et al., 1996). Both provide information about the realized profitability - either by an investment made (Entrepreneur, 2018) or by the money of the startup’s shareholders (Investopedia, 2018).
Growth in sales/ market share/ employment:
Sales growth reflects the extent to which the customers are progressively accepting the services or products offered by the new venture, representing the most commonly stated dimension of new venture growth (Murphy et al., 1996; Robinson, 1999). However, in case some startups have no available sales figures yet, an appropriate measurement is growth of employment. The latter factor indicates that an increase in operations or the whole business takes place, hence, positively signaling about the business performance (Gilbert et al., 2006). By means of market share growth, similarly to sales growth, the acceptance of a product or a service on the market is measured. Growth in market share is commonly measured by the level of given product category or based on a whole industry (Kerin, Varadarajan, & Peterson, 1992).
Other contributions:
In contrast to financial figures which are easy identifiable, non-financial measures can range between an increase in employment to contributions to the learning curve of the firm as well as to the society (Stuart & Abetti, 1987). Therein, financially unsuccessful products or services may be called successful in non-financial terms, in case a positive contribution has been made to the development of the new venture, which in turn might result in subsequently successful products or services at a later stage (Maidique & Zirger, 1985).
Meeting expectations:
Similar to other contributions, new venture performance can be defined as meeting the founder’s or the founding team’s expectations (Stuart & Abetti, 1987). Therein, success is defined by these scholars as “the achievement of something desired, planned or attempted” (p.218).
Survival:
One frequently used success dimension of new ventures is survival since foundation (Honig &
Karlsson, 2004). For instance, Gartner, Starr, & Bhat (1999) assumed that the ability to survive at least four years can be considered as key indicator for successful new ventures.
This literature review elaborated on several factors which have an impact on the business performance of new ventures. However, these identified factors and the four areas may still not be complete as they might have to be adapted for the purpose of this study. The reason is that these factors may not guarantee a validity for explicitly technology startups due to the heterogeneity of the different startup industries within the reviewed studies. Therefore, in order to assess the validity, semi-structured interviews will be executed with entrepreneurial experts in the following phase. The elaborated success factors as well as the business performance dimensions, before being discussed with experts in the subsequent phase, are summarized in Table 1.
Table 1. Success area and factor list, including business performance dimensions.
Table 1 (continued). Success area and factor list, including business performance dimensions.
3. Methodology
This chapter will depict the methodological approach which was chosen to conduct this study, consisting of five phases for answering the afore stated research questions and ultimately to create a questionnaire which will serve as a scanning tool.
3.1 Research Phases
As the existing literature does not provide a framework that defines and monitors the success factors of explicitly technology startups, theory development is a suggested approach for creating knowledge (Van Aken, Berends & Van der Bij, 2012), which is best executed through a multiple case-study approach (Eisenhardt, 1989). For setting up a research approach that reflects the literature as well as the practical view, this study aims to include both an inductive and deductive approach, which is suitable for a mixed- method qualitative research (Creswell, 2013).
Phase 1:
The first phase comprised the literature review which was carried out by consulting computerized databases: EBSCOhost, EconLit, WorldCat, SmartCat, Elsevier Science Direct and Google Scholar. As the frame by Gilbert et al. (2006) led the research, the literature review was aligned according to the aforementioned four success areas, combining those with the terms startup and new venture. Hence, the following terms were used for finding the most relevant success factors: “Startup”, “New Venture”,
“Entrepreneur Characteristics”, “Resources”, “Strategy”, “Organizational Factors”, “Success Factor”. Thus, the success factors have been categorized according to the four stated areas (see Table 1). Initially, a total amount of 96 papers were selected after reading the title and abstract. Subsequently, 38 papers were excluded as these did not provide findings about the business performance of new ventures, or about an impact or measurement of success factors on the business performance of new ventures. This implies that 58 papers were deemed relevant.
Phase 2:
Following the first phase, which consisted of the literature review, the second phase comprises semi- structured interviews for providing the inductive input for this study, representing a highly relevant element of qualitative research (Creswell, 2013). The inclusion of experts offers the researcher a possibility to dive deep into a complex phenomenon and to obtain high-level results in a short amount of time (Bogner, Littig, & Menz, 2009; Yin, 2009). The scope of these interviews was to validate the elaborated theoretical construct of success factors and business performance by experts with entrepreneurial knowledge. Hence, the experts were chosen based on the researcher’s direct environment consisting of the personal scholar and professional network. As this very network consists of highly experienced parties in the field of entrepreneurship, either from a practical or a research-
oriented perspective concerning technology startups, it was considered to be adequate for the scope of this research. Hence, 18 experts were contacted via telephone, e-mail or LinkedIn. Thereof, 10 experts answered, what resulted in 7 executed interviews as three experts did not judge themselves to have an adequate knowledge level for this scope, implying a response rate of 38,9%. The interviews were executed on-site or alternatively via telephone/ Skype, in English, and recorded for later transcription.
An overview of the anonymized list of the participating experts, including a short description of their background as well as the transcripts can be found in the Appendix (I & III). The interviews contained open-ended and closed questions to validate the elaborated success factors and to make sure that possibly missing success factors or performance dimensions could be included. The interviews were in line with Emans’ (2004) question techniques and the interview guide was checked by the supervisor of this research. Moreover, the experts were asked to assess the success factors according to their own perceived relative importance by distributing a weighting per success area and per success factor within each area.
Based on the evaluated input by the experts, the previous theoretical construct by the literature was changed and adapted. The final factor list depicting the changes is shown in Table 2. Based on the suggestion by the experts, the applied changes consisted in renaming an area, extending factors in their meaning and description, merging factors as well as adding also a new one to an existing area. In order to implement this new success factor, the literature was reviewed again. Thereafter and due to the rearranged factor list, the experts were contacted a second time to update their previously distributed weightings for the success areas and factors. The final distribution of weightings is shown in Figure 2.
Phase 3:
After having completed the theoretical construct considering the input by the experts, the next step was to elaborate the operationalization of each success factor and business performance dimensions.
Therefore, the previous literature as well as new sources were reviewed again while seeking for scales and already utilized items/ questions to validly build the questionnaire. These items in turn shall serve to compose the tool as a questionnaire to assess technology startups. For the newly performed literature search, the applied search terms were a combination between the name of the respective factor and the terms “scale”, “measurement”, “operationalization”, “items”. In total, 37 new sources were examined for items and scales, measuring the previously elaborated success factors in new ventures. Therein, 19 papers were deemed relevant. Based on these papers, a questionnaire consisting of 129 items was developed which can be found in the Appendix (V).
Phase 4:
In this phase, the second collection of primary data is performed, by means of a completely self- administered questionnaire through the survey software Qualtrics. As this type of questionnaire has to be self-explanatory and running smoothly throughout the completion (Lavrakas, 2008), the tool was
checked upfront by the supervisor of this study and tested by one more person. The scope of this phase was to apply the developed tool on the participating startups for assessing their internal factors as well as their business performance. The participating startups had to fulfill the conditions according to the definition provided in Chapter 2.1. Moreover, it was indicated that the respondent shall be the founder/
a founding member of the new venture as it can be assumed that he/ she plays an essential role in terms of decision-making while generally knowing his/ her startup best as well. It is worth noting that a self- reporting answering of a questionnaire can result in unbiased responses when the respondent is guaranteed anonymity and is informed that the purpose is solely research (Gupta & Govindarjan, 1984).
For seeking out the startups, the databases of foundedinholland.com, foundedingroningen.com and angel.co/netherlands were used. In total, 191 technology startups were contacted via e-mail, LinkedIn or telephone. Five e-mails were automatically sent back instantly reporting a false or wrong address. In case of no received response, a second reminder e-mail or message was sent out, including the online link to directly access the questionnaire. Ultimately, 27 technology startups participated (see Appendix VI), resulting in a response rate of 14%. The collection of the data through the startups can be set equal to a multiple case study approach in order to obtain theory building out of a real-life setting (Eisenhardt, 1989; Van Aken et al., 2012).
Phase 5:
In the last stage of the study, after having assessed the startups, the evaluation of the results was performed. Firstly, a correlation between the assessment of the internal success factors and the subjectively stated business performance was investigated to make a statement about the accuracy of the developed tool. Furthermore, the scores of each startup were illustrated in diagrams, sorted by success area and factors, including the applied measurement dimensions. As there is no necessity to code the questionnaire answers due to an equal answer range for every participant, the results are comparable to each other. Finally, an individual, evaluative performance report was created for each startup. An exemplary report for Startup #3 can be found in the Appendix (VII).
2.2 Reliability, Controllability & Validity
According to van Aken, Berends, & Van der Bij (2012), results which can be characterized as intersubjective and aggregable have to be determined by examining certain criteria for the qualitative approaches of research: reliability, controllability and validity. The expert-interviews were recorded and transcribed, which shall increase both the reliability and controllability of the present study (Corbin &
Strauss, 2008; van Aken et al., 2012). The transcripts can be found in the Appendix (III). When the study is considered reliable, it should be possible to see an independence between the results and the main characteristics of the study subject (Swanborn, 1996). Another reliability issue that can occur is the instrument bias. Therefore, triangulation is used as a remedy for negative consequences, by utilizing more than one instrument (Yin, 2003), which is here achieved by combining a literature review, expert-
interviews and self-administered questionnaires. The triangulation also serves to reach a higher level of validity of the study (Yin, 2003, van Aken et al., 2012). Moreover, a respondent bias might occur in this study during the completion of the questionnaire as respondents may have a motivation to reduce a perceived gap between their own opinion and the expected outcomes of the study results (van Aken et al., 2012). Therefore, different people from the participating startups should answer the questionnaire.
However, this was not feasible as the items of the questionnaire were directly addressed to the founders/
founding members of the startups.
4. Validation of Theory
After having carried out a literature review about the most relevant success factors for new ventures, seven experts in the field were interviewed to validate the elaborated theoretical construct while generating an inductive input of data. Mainly, the experts were asked whether they agreed on the elaborated success areas and its factors as well as the business performance dimensions, including a discussion about the scope of the last-named elements. The structure of this section is based on the outline of the interview guide. Firstly, the experts described their view on defining and measuring the business performance of technology startups. Secondly, the participants discussed the success areas, including the factors, while stating how important they deemed each of both. This importance rating was executed by distributing 100 points within the four success areas. Subsequently, they were asked to distribute again 100 points within the success factors in each of the four areas.
Regarding the Business Performance of a technology startup, the interviewees indicated a high variety of answers. Generally, financial indicators such as profitability measures were not deemed important. Mostly, the experts stated that startups shall focus, within the first years, on defining and tracking milestones as well as their progresses while effectively developing a presumably well- performing product and emphasizing on growing structurally (Expert 1, personal communication, May 11, 2018; Expert 4, personal communication, May 14, 2018; Expert 6, personal communication, May 16, 2018). Overall, it was possible to assign all the answers by the interviewees to one of the elaborated business performance dimensions (profitability, growth, alternative measurements, survival), meaning that no new dimension had to be added. On this, all the experts also agreed on every elaborated dimension, despite survival, confirming their previously stated answers. Survival was seen as inappropriate for defining the performance as “it sounds that I would commit to my startup just to survive, instead, I want to grow” (Expert 1, personal communication, May 11, 2018). Moreover, one interviewee stated that profitability figures do not reflect an appropriate way to measure business performance of startups in the initial stages as they are “cash-burning companies for a long period first”
(Expert 5, personal communication, May 15, 2018).
The subsequent part of the interview served to the scope of validating the whole theoretical construct about the elaborated areas and factors. Generally, the interviewees all agreed on the four
elaborated success areas. Merely two experts were missing a special emphasis on the product itself, meaning that the dimension Strategy was enlarged and renamed to Strategy and Product, which will be discussed in the following. The interviewees also agreed on the fact that the external factors Industry Context and Geographical Location were excluded in order to focus on an internal view.
In terms of the first success area, Entrepreneurial Characteristics, all seven elaborated success factors were confirmed by the interviewees even though the factor Funding Team Size was suggested to be expanded in his statement. Thereby the suggestion was to not just focus on the mere size, but to include dimensions, such as internal dynamics and communications in the team (Expert 2, personal communication, May 11, 2018; Expert 3, personal communication, May 12, 2018). Hence, this factor was expanded and renamed funding team, including the two aforementioned facets.
Regarding the second area Resources, all the experts agreed on the proposed success factors.
Nevertheless, two experts proposed to merge the factors governmental allowances and working capital into the factor Financial Capitalization as they did not judge them as important to be listed separately, but more subordinated to the latter factor (Expert 3, personal communication, May 12, 2018, Expert 5).
Moreover, Expert 5 indicated to distinguish between selective governmental allowances and automatically granted governmental allowances, which are automatically granted when a new venture simply fulfills certain conditions. Thus, the focus shall be on selective allowances as the startup therefore has to go through a competitive application procedure to get these granted (Expert 5, personal communication, May 15, 2018).
The third success area Strategy has been subject to some changes. First of all, the emphasis on the product itself was missing according to Experts 2 and 7. Therefore the success area was renamed to Strategy & Product and additionally the factor Product Superiority was added. The literature suggests about product superiority that it facilitates the distinction compared to competitors, through various quality and performance aspects of the product, which leads to a higher chance of being a successful new venture (Barringer et al., 2005; Garvin, 1984; Roper, 1997). Moreover, Expert 4 observed that the cost-leadership strategy, within the factor Competitive Strategy was legitimately missing as startups in the initial stages are usually not able to focus on the last-named strategic approach. On top of that, some experts tended to distribute their weightings jointly to the factors Innovation and Unique Value for Customers as they perceived them to be not independent from each other. Hence, these factors were merged to Innovation & Unique Value for Customers.
The last success area Organizational Factors was the least discussed and commented area by the interviewees. Nevertheless, Experts 5 and 7 were missing the dimension communication at this point.
Hence, the factor Structural Elements got extended by reflecting the communication dimension within the structure of the startup. Generally, most of the interviewees pointed out that the factor Incentives for Employees might be very relevant for technology startups now and in the future. The final resulting and adapted success area and factor list can be seen below in Table 2.
Table 2. Final success area and factor list. 1
Ultimately, all the interviewees distributed 100 points within the four success areas and 100 points within each area for the respective factors. As some areas and factors have been subjects to change, the experts were contacted a second time after the implemented changes in order to update their original weightings. The results can be seen in Figure 2, which show the sums of average weightings, including the standard deviations.
1The areas and factors marked in bold and with a star have been adapted or added.
Success Areas
CHANGED -->
Entrepreneur Characteristics
Success Factors Higher Education
Parents Entrepreneurship Experience Prior Entrepreneurial Experience Prior Industry Experience Founding Team*
Planning Leadership
Resources Intangible Assets
Financial Capitalization*
Interorganizational Relationships Access to Accelerators/Incubators
Strategy & Product* Competitive Strategy*
Innovation and Creating Unique Value*
Product Superiority*
Organizational factors Structural Elements
Incentives For Employees*
Business Performance
Performance Dimensions Efficiency (Profitability) Growth
Alternative Measurements Survival
Figure 2. Average experts’ weightings, sorted by area and factors2, n=7.
When analyzing the submitted weightings by the experts (see Figure 2), the most important success areas are represented by Entrepreneur Characteristics as well as Strategy & Product. Hence, the experts express a conviction that either the product/ service a new venture offers shall be very unique or the entrepreneurs simply have to demonstrate to be very competent. Expert 5 summed it up like this: “From a venture-capital view, either the product is so convincing that the entrepreneur might even be replaceable or he/ she shows an impressive competence of leading the startup to success with no matter which idea/ product.” The area Resources follows the two top areas with an average score of 22.9. A reasoning behind the lower perceived importance is that the majority of resources will vary in their relevance throughout different stages of the new venture, hence, lowering its significance as a perceived success area (Expert 3, personal communication, May 12, 2018). The least important area is Organizational Factors with an average of 12.9. The argumentation by most interviewees was that they perceived the first three areas to be the most important while the last one onlyrepresents a supporting function. For each area, a low coefficient of variation has been calculated, which ranged between 0.28 and 0.42, indicating that the responses are not highly spread out around the mean as they are below 1,00
2The areas are shown by the four upper columns while the associated factors are below each respective area
(Researchgate.net, 2014), which enhances the overall validity of the answers. Moreover, this coefficient was very low for every other factor within each area as well.
When analyzing the factors within each area, the most important ones in Entrepreneurial Characteristics are Prior Entrepreneurship Experience as well as Leadership and Prior Industry Experience. Hence, the summarized factor experience occupies nearby half of the whole average distribution. The likelihood of succeeding with the startup is enhanced by experience as it leads to avoiding typical mistakes of unexperienced founders (Expert 4, personal communication, May 14, 2018).
Among Resources, the factors Intangible Assets and Financial Capitalization stand out.
However, the standard deviation for the second factor is the highest. This might indicate that the experts perceive the financial capitalization as a result of attracting capital, which in turn is based on other factors, such as personal or professional networks (Expert 5, personal communication, May 15, 2018), implying an interdependence.
The weightings within Strategy & Product were more heterogeneously distributed with Innovation and unique value being on top, scoring 44.3, in front of Product Superiority and Competitive Strategy. This heterogeneity might be caused again by a perceived interdependence between these factors. Expert 2 sums it up this way: “Mostly, one entrepreneur is not the only one having a unique idea/ product. The difference is made by entrepreneurs who apply an innovative strategy to be successful in the market.”
Eventually, within the area Organizational Factors, the experts predominantly emphasized on the factor incentive for employees which resulted in a higher score of 63.6, compared to Structural Elements. Expert 1 sums up this tendency for incentives, stating that “If we as a startup want to attract good people, it is difficult to provide a competitive salary, hence, we have to offer other types of benefits instead of the salary as an argument.”
In order to compare the factors to each other, the product of the weightings has been calculated (see Figure 3).3 Thereby, the most important factor is clearly reflected by Innovation and Unique Value with a score of 13.6, while the lowest score is Parents’ Entrepreneurial Experience (2.4). The factor Prior Entrepreneurial Experience obtained a high score as well (8.15), confirming that, together with innovation and unique value, the most important factors are entailed by the most important areas (Entrepreneur Characteristics and Strategy & Product), according to the experts’ perception.
3The calculation was executed by multiplying the factor score times the respective area score and divide this result by 100.
The division by 100 was solely done to keep the resulting figures low and clear.
Figure 3. Weighted success factors.
5. Measures and Operationalization
After having validated the elaborated literature review by the experts, in this section, the factor operationalization is developed. This will serve as a foundation for measuring each of the success factors as well as the business performance. To ensure the validity of the item which will constitute the tool, the literature was again reviewed to find adequate scales for measuring the factors. In case that appropriate scales were not available for a factor, the reviewed literature was used to develop items based on the elaborated facets or dimensions that constitute the respective factor. Hence, the items were then created by applying different Likert scales, or alternatively “Yes” or “No” as answering options. In the following, the operationalization of the first four success factors of the area Entrepreneurial Characteristics are explained exemplarily. All other remaining factors as well as the measurement of business performance can be found in the Appendix (IV). A summarized overview of the resulting 129- items questionnaire, including the questions, the scales, and the respective sources can be found in the Appendix (V).
Entrepreneurial Characteristics
The first factor higher education was operationalized by two items assessing the level of general education and whether this education is related to the founder’s actual business, using a 5-point and a 3-point Likert scale respectively (Cassar, 2012; Simon-Moya & Revuelto-Taboada, 2016).
Parents Entrepreneurship Experience was measured by one question, simply assessing whether the founder was raised by one or both parents who had started an entrepreneurial business (Geldhof et al., 2013).
