Background
The technological developments we witness today are the aftermath of the different stages of industrial revolution which started with the use of water and steam power as energy sources in production. The Third Industrial Revolution was characterized by the use of electronics and information technology (IT) to automate production (Hussain, 2019; Jee, 2017). The Fourth Industrial Revolution (also known as industry 4.0) which is considered as a continuation of the Third, is a digital revolution which has been occurring since the middle of the 20th century (Morrar & Mousa, 2017; Oztemel & Gursev, 2020; Schwab, 2016). According to Schwab (2016), the process “is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres” (para. 2).
Opportunities for billions of people connected by mobile devices with larger processing power and storage capacity are innumerable. As identified by Schwab (2016), the opportunities are as a result of the several breakthroughs in fields such as “artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing” (para. 4). For instance, investments in research have resulted in the development of self-driving cars, drones and virtual assistant software among other technologies.
With the emergence of the Fourth Industrial Revolution, numerous companies have been developed to continue providing the vast population with up to date products and services. According to Skawińska and Zalewski (2020), the concept of startups started in the 1970s when they were referred to as “emerging high-tech micro companies, active mainly in the field of electronics and computer technologies” (p. 1). These companies formed the basis of the subsequent emergence of companies such as the IT-based company in the Silicon Valley and the biotech-based company in San Francisco, among others (Skawińska & Zalewski, 2020). As business models and structures are transforming function to technological advancement, technological startups are increasingly creating employment opportunities and innovation (Choi et al., 2020; Kemell et al., 2020; Pandey, 2019; Peter et al., 2020; Spender et al., 2017). Consistent with Skawińska and Zalewski (2020), Etla (2019), and Baldridge (2021), Choi et al. (2020) states that one significant motivation for these companies is that drastic innovation which can result in increase in employment levels. However there are concerns to balance macroeconomic benefits and individual contentment with advanced technology.
Many startup projects are launched on a daily basis across the world. Rufig and Wang (2020) estimate that about 100 million startups are each year all over the world. However, for each successful one, several of them fail due to a variety of reasons (Gonzalez, 2017; Nair & Blomquist, 2019). Research previously done by Wang et al. (2016) reveal that 60 percent of startups do not go beyond the five years of operation while 75 percent of venture capital funded startups fail. Mimaroglu (2020) states that “in the information technology startup, high birth rates go hand in hand with a high risk of failure” (p. 1). India which has a considerably large ecosystem for startups, 90 percent of them were failures due lack of strategic thinking, inadequate technological innovations, and the absence of unique business models (Muramalla & Al-Hazza, 2019). Some startups also start well but fail to sustain the business and as a result, they quit the market (Bednar & Tariskova, 2017; Kalyanasundaram, 2018). Table 1 shows some infamous startup failure which have occurred in the past years due to poor project management skills.
Table 1: Most Infamous Startup Failures
Numerous researchers have identified the problems facing startups and their importance to the economy. However, there is little evidence about the elements and infrastructures needed to create a successful ecosystem for technological startups and this research gap will form the basis of this study (Tripathi et al., 2019). In so far as Tripathi et al. are concerned, the closest study is the one by Torres and Souza (2016) which used the snowball sampling technique to determine the elements of a technological startup. Therefore, the objective of this research is to define a startup ecosystem and identify the elements which constitutes the ecosystem of technological startups. To guide the study, this paper proposes the research question that “what factors determine the success of technological startup in the economy?” To answer the question, this paper will perform a comprehensive review of literature relevant to the topic and augment the findings with an analysis of real-world companies in Singapore, Malta, and the Silicon Valley.
Literature Review
To understand the various factors which can promote a successful ecosystem for technological startups, it is imperative to understand what a technology startup is. A widely acceptable definition by Ries (as cited in Wang et al., 2016) states that a startup is “human institution designed to deliver a new product or service under the conditions of extreme uncertainty” (p. 170). It follows that any young company developing new products and services in extreme uncertainty is regarded as a startup (Bednar et al., 2018; Kim et al., 2018; Lim et al., 2018; Perry et al., 2018). Jain (2016) defines a startup as a young company which searches for an unknown business models to disrupt the market. According to Gupta et al. (2020), startups “are temporary organizations that are continuously experimenting to identify a business model, which is scalable and repeatable, thereafter they attain higher growth levels and returns” (p. 2). Kim et al. (2018) defines a startup as a “new business that entrepreneurs initiate by combining business ideas and resources” (p. 2). Therefore, technological startups are those which focus on leveraging innovative technology to create unique products and services.
Small firms that begin their operations in new markets or products have variations based on how their operations. From the definitions, startups generally have no or limited history (Salamzadeh & Kesim, 2017; Lim et al., 2020; Wang et al., 2016). Ries’s definition further highlights the chaotic environment characterized by uncertainties in which startups expect to operate in as they venture the market (Da Camara et al., 2020; Pandey, 2019; Wang et al., 2016). Research by Tripathi et al. (2019) already identified that little evidence of systematic and elaborate study which provides an overview of the startup ecosystem and related literature is limited or unknown. Scattered evidence exist on the factors which would influence the continuity of startups upon their implementation. Before reviewing other researchers’ understanding of the ecosystem elements which determine the success of startups, it is imperative to understand the meaning of an ecosystem in the context of startups.
Various scholars have different understanding of small businesses, which begin to operate in new markets. Singh et al. (2019a) defines a startup ecosystem as a socio-economic structure whereby various actors collaborate to promote a startup. According to Tripathi et al. (2019), a startup ecosystem refers to a “phenomenon in which startups and their supporting elements interact in an environment that is built to foster these startups’ development and growth” (p. 56). Cukier and Lyons (2016) defines a startup ecosystem as:
A limited region within 30 miles (or one-hour travel) range, formed by people, their startups, and various types of supporting organizations, interacting as a complex system to create new startup companies and evolve the existing ones (p. 2).
In the word of Pandey (2019), a startup ecosystem is defined as a “society of founders with ideas and skills, young companies at early stages with talent, incubators with mentors and capital, early adopters and the media” (p. 237). Pandey adds that the objective of any startup ecosystem is to create a self-sustaining network of talent and resources which can fulfill the needs of the larger community.
Although the whole concept about startup ecosystem revolves around the social-economic factors which stand to bolster the development and growth of a startup, researchers hold different opinions. According to some researchers, the key factors making up a startup ecosystem include firms, physical infrastructure, network, incubation programs, culture, support services, and higher education institutions such as universities and colleges (Roundy et al., 2017; Junttila, 2020; Sing et al., 2019a; Singh et al., 2019b; Spigel, 2017; Zhavoronkova et al., 2021). According to Pandey (2019), an ecosystem is made up of entrepreneurial stakeholders and they are members, startups, and service providers (see Figure 1). The members include entrepreneurs, private investors and advisors (Haines, 2016; Hernandez & Gonzalez, 2017; Karim et al., 2018). Service providers include Business to Business (B2B) product and service providers, funders, entrepreneurial associations, knowledge and government institutions (Pandey, 2019).
Pandey underscores that entrepreneurs, private investors, and advisors are the main members of an ecosystem which are key for its success. However, at the initial stages of startup funding, the experience, skills, time, and funds are essential ecosystem components worth considering (Crisan et al., 2019; Kupp et al., 2017). Literature review by Tripathi et al.(2019) indicates that in a software ecosystem, which is one kind of a technology startup system, different stakeholders such as companies, competitors, and customers collaborate to avail product and services to customers. Some researcher find a connection between entrepreneurship and startups since they are both based on identifying new business opportunities and pursuing them (Cantamessa et al., 2018; Tripathi et al., 2019). However, software startups are rapidly growing but still at an immature stage and are most of them are bound to fail in the first few years (Bui, 2016; Manikas, 2016; Santisteban & Mauricio, 2017).
Research Method
This research will apply the case study and literature review methodologies to answer the research question. The study will be conducted between April 2021 and August 2021. The case study method will be suitable as an empirical method because it aims at investigating contemporary phenomena in their context and it is appropriate for this type of business research (Rashid et al., 2019; Ridder, 2017). The fact that it is hard to study the target objects in isolation and that case studies are appropriate for real-world settings makes this research method the most suitable. Literature review will be used since it provide a rich and ready source of evidence which will help in achieving the research objectives (Paul & Criado, 2020; Snyder, 2019).
The study intends to analyze the case studies of three companies in Singapore, Malta and the Silicon Valley. In Singapore, Attune Technologies’ case study will be analyzed whereas in the Silicon Valley, the Cardiva Medical Inc. will be studied. Since most of Maltese startups leverage modern technology such as artificial intelligence to provide financial services, this research cannot easily locate a medical device startup in Malta. However, the closest startup which can be identified is the Cannapharm Technologies as highlighted by Seedtable (2021). The case of each of the three companies is narrated below.
Attune Technologies
Attune Technologies was founded in 2008 by Anand Gnanaraj, Arvind Kumar, Mohanaraj Paramagurusamy, and Ramakrishnan Venkataraman (Attune Technologies, n.d.). Its funding amounts to a total of 26 million dollars. The company has about 202 employees, as of 2021. Throughout its existence, it has launched cloud-based products designed to help the healthcare sector. The company’s products integrate labs, hospitals, pharmacies, blood banks, radiology, insurance companies, and medical devices (Internet of Things) hence boosting revenue and efficiency of operations. Attune’s solutions are deployable across various kinds of organizations making it the largest cloud-based healthcare IT service provider in Singapore (Attune Technologies, n.d.). The company is funded by Norwest Venture Partners and Qualcomm Ventures. With headquarters located in Singapore, Attune supports customers across 15 countries in other parts of Asia and Africa. The company is determined to create a global healthcare network through the concept of Internet of Things.
Cardiva Medical Company
Cardiva Medical Inc. was founded in 2002 in the Silicon Valley by Gordon Epstein and Zia Yassinzadeh as a medical device company focusing cardiovascular procedures. The company’s VASCADE vascular closure system which was PMA-approved by FDA since 2013 is indicated for vessel closure following 5-7F arterial and venous procedures (Cardiva Medical, n.d.). The company’s latest portfolio is the VASCADE MVP Venous Vascular Closure System which is the only marketed vessel closure technology designed exclusively for electrophysiology procedures (Cardiva Medical, n.d.). The company’s total funding is 182.2 million dollars with about 154 employees and it has its headquarters at Silicon Valley in San Francisco. The company is funded by 12 investor, however Evidity Health Capital and Luther King Capital Management are the most recent.
Cannapharm Technologies Malta
Founded in 2018 by Denis Orlov, Cannapharm Technologies Malta (CTM) is an agriculture-based, manufacturing, and genetics Maltese company specializing in producing a variety of pharmaceutical, cosmetics and cannabis based products (CTM, n.d.). It partners with hospital management companies and pharmaceutical distributors. The company’s ecosystem enables it to implement systems such as the genetic bank and research, cultivation and processing, application programs interface (API) manufacturing, research and development (R&D) clinical trials, and welfare programs (CTM, n.d.). Although CTM originates from Malta, it is based at the European Union headquarters.
Data Analysis
A hybrid data analysis approach which entails published data and comparison of each of the case studies presented for each company in Singapore, Malta, and the Silicon Valley, will be used. It is imperative to complement the case study analysis with literature review since each of them do not provide concrete information when used independently. According to Yin (as cited in Carolan et al., 2016), data analysis is the least developed aspect of case study hence the need to incorporate qualitative mixed methods. By using the two methods together, bias is minimized using the triangulation technique (Dzuigol, 2020; Fusch et al., 2017a; Kern, 2018). Fusch et al. (2018b) explains that “triangulation involves the employment of multiple external data collection methods concerning the same events” (p. 20). Fusch et al. asserts that triangulation ensures the reliability of data. This analysis involves assessing the factors which could have led to the success of the case companies since previous evidence show that dysfunctional startups usually fail by the second year. Since all of them have been in existence for more than two years the paper assumes that the companies have succeeded. The identified factors should be supported by existing evidence in the literature review.
Research Limitations
Evidence about the elements and infrastructure which determines the success of startups in their ecosystem is little or unknown. Although the literature review serves to augment the case study analysis, it presents limited evidence resulting from the inadequacy of the latter. The scarcity of the sources could be caused by the priority given to materials published later than 2015 thus excluding the outdated sources. Another limitation of this study is that only three case studies are selected for analysis. The limited number of companies makes the application of the findings on other companies a matter of unrealistic generalization. The selection also lacks geographic diversity in that the three startups were selected from Asia, Europe, and the US leaving out South America, Africa, and Australia which also have large number of startup companies.
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