Preamble

New and young businesses, referred to now as ‘start-ups’, have gained growing relevance and importance among the policy makers and leaders of economies worldwide. In particular, as the developed and developing economies make the transition to knowledge-based economies, the high-technology (high-tech) sector has been the primary engine in enabling this transformation. The promotion of high-tech start-ups helps economies to generate new products, services, and business models that differentiate the nations’ output from the rest of the world and enhances the economic progress of these countries (Saxenian 2002).

Therefore, the field of high-tech start-ups has been receiving much importance within the entrepreneurship literature from the 1980s. Gries and Naude (2008) observed that these new, small firms are more likely to grow (Johnson, McMillan, and Woodruff 2000; Lingelbach, de la Vina, and Asel 2005), create new jobs (McMillan and Woodruff 2002; Audretsch, Keilbach, and Lehmann 2006), and promote new and flexible organizational forms (Kim, Aldrich, and Keister 2006). In particular, small high-tech start-ups have been recognized as being the major drivers of job creation and innovation and thus economic growth (Birch 1979; Baumol 2002; Kirchhoff and Spencer 2008).

In the USA, the 1970s and 1980s had the most impact and contribution to employment and economy from high-tech start-ups. The advent of the Internet in the USA and incremental successes in the biotechnology industry disrupted the marketplace through the creation of new start-ups that leveraged these technologies to provide new products and services in ways that were not possible before. At its peak, these entrepreneurial companies contributed 20 per cent of US employment in the 1980s. Despite being in recession, between March 2009 and March 2010, 394,000 new businesses were formed, creating 2.3 million jobs in the USA (Mutikani 2012).

Even emerging economies have benefited on account of high-tech industry-based growth strategies. Taiwan's contribution to total domestic output from the high-tech sector increased from 9.7 per cent in 1980 to 28.5 per cent in 2003. South Korea's high-tech manufacturing contribution to the total domestic manufacturing output jumped from 9.6 per cent in 1980 to 21.5 per cent in 2003 (Commission on Strategic Development 2007). In India, an average of 400 new technology start-ups were created during 2009–2012 (Microsoft Accelerator India 2012).

Introduction

High-tech start-ups are now being recognized as the engines of economic growth in the knowledge-driven society. Their ability to generate new products, services, and business models has helped nations to leapfrog its output in comparison to others (Saxenian 2002). Developed economies in particular have benefited the most by supporting and nurturing high-tech start-ups. Several studies examining economic progress of developed economies have noted small high-tech start-ups as being the major drivers of job creation and innovation and thus, the economic growth (Birch 1979; Baumol 2002; Kirchhoff and Spencer 2008).

As an example of this, in the USA, these entrepreneurial companies contributed 20 per cent of the US employment in the 1980s. Even though in recession, from March 2009 and March 2010, 394,000 new businesses were formed in the USA, creating 2.3 million jobs (Mutikani 2012). Some of the leading companies in the technology industry today, such as Apple, Cisco, eBay, Qualcomm, Intel, were incubated as tiny start-ups during their formative years (Barringer, Jones, and Neubaum 2005; Paulraj 2012).

Over the last decade, the emerging economies across the world also have witnessed a surge in the creation of high-tech start-ups. The rapid proliferation and use of the Internet across the world has accelerated the process of globalization, aided by disruptive technological changes in just a matter of a decade and half (Startup Genome 2012). India has emerged as the third-largest base for high-tech start-ups in the world, with approximately 3100 start-ups operating in the country. The start-up ecosystem in India attracted 300 VC/ private equity and 225 angel investment deals worth over US$2.3 billion since 2010 and over 20 mergers and acquisitions worth US$1 billion in the last 3 years. Over the last 12 months alone, 805 technology product/digital start-ups were set up across the country, which is projected to grow fourfold to hit 2,000 by 2020 (NASSCOM 2014).

While the aforementioned data paint an impressive picture, it must be noted that across the world, these contributions are made from a very small percentage of high-tech start-ups which have successfully managed to overcome the challenges during initial stages of the firm life cycle. It has been well established that high-tech start-ups suffer a very heavy failure rate (Stinchcombe 1965; Certo 2003). These start-ups face many unique constraints during their initial stages of operation that makes them highly amenable to failure.

Introduction

In this chapter, we discuss in detail, the factors that influence the life cycle of high-tech start-ups with respect to our total sample as a whole. Further, we ascertain the factors that are responsible for variance across the different life cycle phases of the start-ups involved in our study. To begin with, we will be specifically examining the factors that differentiate the start-ups among the three milestones of emergence, survival, and growth by way of MANOVA. We then study and identify the factors impacting the entire life cycle of start-ups by subjecting the entire data of start-ups to a multinomial regression. Further, we assess how high-tech start-ups differ between the three milestones in terms of their orientation towards the market segment that they target, the location in which they operate as well as based on the exposure of the founders.

The preceding chapters analysed the impact of entrepreneurial, firm-specific, and external environment-related factors that are influential in impacting the individual milestones of emergence, survival, and growth respectively. The focus of evaluation in those chapters was to understand what factors would help contribute towards attainment of the particular milestone under study. We grouped the data of our sample accordingly to examine each of the earlier objectives. However, in this chapter, we aim to supplement the insights obtained from the preceding chapters by enquiring if there are factors that influence the entire life cycle of high-tech start-ups. In other words, we wish to evaluate and understand whether there are factors in the entrepreneurial, firm-specific, and external environment-specific categories that pervade influence across all the key milestones of a start-up's journey. We consider the entire data of our sample to analyse this research objective. This insight would be useful for the entrepreneurs, ecosystem partners, and policymakers as well, who will then understand the key ingredients that are required to create, sustain, and grow successful high-tech start-ups.

In order to study the impact of factors affecting the life cycle of start-ups, we organize the data of start-ups that are collected during our study into three distinct categories based on their current status of the life cycle milestone achieved. The first category of start-ups would be those start-ups that have formally been incorporated, but who have not yet achieved the product-market fit.

Introduction

In this chapter, we discuss in detail the factors that influence the growth of high-tech start-ups in India. We will be specifically examining the growth of the start-ups based on three vital aspects, namely, the entrepreneur-specific factors that contribute to the growth of high-tech start-ups, the firm-specific factors that impact the growth of high-tech start-ups, and last, the external environment-specific factors that influence the growth of high-tech start-ups. We study the factors impacting growth of start-ups by grouping our sample of start-ups into two distinct categories – start-ups that have survived but not yet growing and start-ups that are growing. We then perform logistic regression analysis to understand the key factors that are responsible for growth of the high-tech start-ups in the sample.

Growth of firms has been researched extensively in the past, and even as high-tech firms emerged in the 1980s and onwards, there has been analysis of factors that influence and impact growth of these categories of firms as well. The initial key contributions to examination of firm growth can be traced back to Penrose (1959) and Stinchcombe (1965). They provided the perspective that a firm's growth pattern is dependent on its age, size, and industry affiliation. However, these were theoretical contributions only. A few decades later, scholars such as Collins and Porras (1994), Gundry and Welsch (2001), and Kirchhoff (1994) tried to provide empirical evidence to the aforementioned theoretical work but ended with different results and interpretations of growth of firms and the factors influencing the same.

Delmar, Davidsson, and Gartner (2003) observed that this substantial heterogeneity in the results was due to usage of different growth measures in their corresponding studies, and hence these results cumulatively could not help us comprehensively understand the phenomenon of growth in firms’ life cycle. After evaluating multiple firm growth measures prior to their work, they concluded that there was no single best way to measure firm growth, and that all high-growth firms do not grow in the same way. Hence, they suggested that researchers use the appropriate measure of growth that suited their approach of study, and also mentioned that the findings of such work to be restricted to enhancing knowledge, related to the theoretical stream of organizational growth.

Introduction

The phenomenon of high-tech start-up survival has been extensively studied in the entrepreneurship literature from multiple theoretical perspectives, the prominent ones being economic, strategic management and evolutionary and behavioural sciences. The motivation for all these studies are twofold. First, start-ups provide context to examine and interpret the theories of entrepreneurship. This is primarily because start-ups are a vehicle of the acts of entrepreneurship or institutional arrangements for demonstration of entrepreneurship by an entrepreneur (Shane 1995; Sarasvathy 2004). Second, small high-tech start-ups have been recognized as the major drivers of job creation and innovation and thus, economic growth (Birch 1979; Baumol 2002; Kirchhoff and Spencer 2008). Birch (1979) showed that small firms created more jobs than large firms. Scherer (1980) and Scherer and Ross (1990) showed that small firms produced disproportionately more innovations than large firms. Further, Kirchoff and Spencer (2008) hypothesized small firms as the dominant drivers of radical innovations that define new fields.

While high technology start-up firms have been credited with contributing to economic growth by way of job creation and innovation (Kirchhoff 1994; Kirchhoff and Spencer 2008), a review of the characteristics of these start-ups reveal that they have a huge failure rate (Stinchcombe 1965). Given these seemingly contradicting observations, one can infer that the contribution to economic development is through those start-up firms that have successfully managed to overcome the challenges during the initial stages of firm life cycle and emerged successful. It is, therefore, appropriate to understand the process and the characteristics of those few start-ups that braved the uncertainty and ambiguity, and challenged and managed to overcome the liability of newness.

The above-mentioned observations also underlie the shift in the focus of entrepreneurship researchers who earlier focused on explaining the phenomenon of start-up life cycle events, such as survival and success from a static perspective, to the now accepted understanding that entrepreneurship is a complex and dynamic process (Wiklund, Patzelt, and Shepherd 2009). This realization is reflected in Gregoire et al. (2006) who indicate seven major areas of convergence within the entrepreneurship literature. Their work illustrates that an entrepreneur as the central agent who initiates actions, firms as the vehicle of the acts of entrepreneurship, behavioural aspects/characteristics of the entrepreneur, firms, and environmental factors (social capital and financial capital) as the influencers form the common tenets of entrepreneurship field.

Introduction

This chapter describes the profiles and characteristics of the high-tech start-ups in our sample. To start with, we analyse the univariate profiles of the start-ups with respect to their characteristics, such as year of incorporation, number of founders at the time of creation, gender distribution of primary founders, number of founders who knew each other prior to the starting of the enterprise, and the location of operations of the start-ups.

Further, univariate and bivariate analyses of the characteristics are carried out based on the market segment that these start-ups are catering to (B2B versus B2C), the location of operations of the start-ups (North Zone versus South Zone), and the entrepreneurial background of the founders (local entrepreneurs versus transnational entrepreneurs). There are 275 start-ups that constitute our sample for the study. Out of these, 100 start-ups are informally active (not emerged), 88 of them have emerged but have not survived, 38 of them have survived but have not yet grown, and 49 of them have grown. The rest of this chapter is organized as follows. The next section discusses the results from univariate analysis. The following section analyses the bivariate relationships of the characteristics and the last section summarizes the major observations based on the univariate and bivariate analyses carried out.

Profile of the Start-ups: Univariate Analysis

The profiles of the high-tech start-ups in our sample are analysed with respect to the characteristics mentioned earlier. Each of these characteristics has been discussed in detail here.

Year of Incorporation

Figure 3.1 presents the distribution of high-tech start-ups, based on their years of incorporation. The figure indicates that there has been more or less a steady increase in formal incorporation of the start-ups post the 2008 financial crisis. In particular, the rate of inceptions of the start-ups in our sample has doubled in the past two years – consistent with the observations made by NASSCOM (2015).

Number of Founders at Inception

Figure 3.2 presents the distribution of high-tech start-ups, based on the number of founders present at the time of creation of the start-up. About 50 per cent has start-ups with two co-founders. For most of these start-ups, one of the founders focused on the technological aspect of the start-up, while the other co-founder focused on the business aspects of the start-up.

Introduction

In this chapter, we present the research objectives, the conceptual framework, the scope, and the research methodology adopted for the study. The research methodology will provide the sources of data and the definitions of key variables used in this study. It will also describe the research instrument and the method of analysis that are employed to analyse the research objectives.

Objectives

The overarching research objective of this study is to investigate the dynamics involved in the life cycle of high-tech start-ups in the context of India. The knowledge about the factors that enable the sustenance of start-ups and that act as barriers, hindering the creation, survival, and success of the firms, will help in the creation of suitable policies that promote high-tech entrepreneurship in India. The outcomes of this study will help in achieving the larger objective of higher economic growth bolstered by new jobs and wealth creation due to the promotion of high-tech start-ups.

To be able to realize these, the following research objectives are outlined: