Menu
Notably, entrepreneurial actions and entrepreneurs do not evolve in separation instead in an extremely integrated and typical system with numerous actors. It is said that the extent of entrepreneurship’s contribution to socio-economic development is unpredicted upon the particular nation’s entrepreneurial facilitating settings (ecosystems) (Scheidgen 2021). As the recently evolved research area, the entrepreneurial ecosystem has progressively seized the attention of researchers, policymakers, and practitioners. Besides, this concept has been employed to express and explain the outlines of how entrepreneurs and startups collaborate with other participants (Xu and Dobson 2019). The victory of the entrepreneurs is powered by favorable entrepreneurial supporting settings attributed to numerous interrelated participants who provide valuable assets to them. Therefore, the event of entrepreneurial ecosystems is currently been utilized as an outline to define and elucidate the integrated nature of economic, political, social, and cultural areas which increase the development of imaginative novel businesses and advocate high-risk activities (Audretsch et al. 2019).
It is noteworthy that entrepreneurial ecosystems and networks have currently started to delve into the entrepreneurial area of study. It is stated that during the COVID-19 crisis, the majority of individuals lost their jobs since businesses feared a momentous loss of revenue on profits because of the decrease in client demand for some goods and services (Scott et al. 2021). Additionally, technology and information systems have been vital in forming the economy in respect of it being integrated into businesses' processes and routine activities. It can be said that loss of income sources; work from home; and novel technologies are deemed as drivers that directly contribute to an increase in novel entrepreneurial startups that are mainly established virtually and greatly depend on technical progressions for them to thrive. Such technical progressions can together be regarded as ecosystems accessible for such startups to use and make something of themselves by developing into large brands (Henry et al. 2020).
Silicon Valley is a popular home for technology and innovation and houses some of the biggest global organizations in the world of technology today such as Google; and Apple. There have also been other numerous startups such as Tempus, Nuro, and Wing that have come up and continue to thrive today in this industry in Silicon Valley (Etzkowitz 2019). Hence, it can be said that there exists intense competition and it is likely that technology startups might fail to take off since the large businesses beat them at competing for the clients' attention. It subsequently raises the question of what ecosystems exist in Silicon Valley that endure to support the growth of technology startups and how such systems lead to the victory of the startups. Research into both ecosystems and networks couldn't have emerged at a better time than now when many technological startups are coming into the market offering a range of services and products (Greco 2023). Often, when entrepreneurs begin their journey, they have little knowledge of how things will turn out in the end or whether their business will be able to weather any storms that come up within the industrial environments they venture into (Fine et al. 2022). This research will change that by helping them gain a better understanding of what entrepreneurial networks and ecosystems exist in the industry they choose to participate in and how they can help them succeed.
This research aims to uncover the causes of the continued success of technological businesses in Silicon Valley. Both large companies such as Apple, Meta, and Google and small companies such as Nuro, Tempus, and Wing have continued to thrive in the Silicon Valley environment even though they are all technological companies. They collaborate and co-exist without one pushing the other out of the market. This research aims to understand what ecosystems and network systems have been put in place in Silicon Valley help to maintain this status and how they help to improve the survival rates of startups. In addition, it will investigate whether other factors contribute to their success other than the ecosystems and networking in place. For research to be considered successful, it should be able to be applied to several other regions and industries. Therefore, this research will also aim to investigate how other industries use ecosystems and networks to increase the survival rates of startups and how they differ in different industries.
The research objectives for this study are as follows:
The research questions are as follows:
Through this research, investors will be able to identify promising investment opportunities. They will be able to make informed decisions about where to invest their money because of the confidence they will have as existing businesses already have the necessary ecosystems and network systems to help them succeed. By supporting the growth of promising startups investors can generate high returns on their investments. Policymakers will benefit as this project will inform the development of policies that support the growth of entrepreneurial ecosystems. This knowledge can help them invest in the right resources and programs to support entrepreneurs creating a more supportive environment for entrepreneurs. This can help to attract and retain talented entrepreneurs in their communities.
Following the introduction section, this study presents another four sections namely the literature review; methodology; analysis and findings; and conclusion chapter. The literature review chapter forms the research model for the study. The methodology chapter offers a comprehensive description of how the research is carried out. The analysis and findings chapter depicts the findings and critically analyzes the empirical outcomes. The last conclusion chapter covers the conclusion, recommendations, scope for future studies, and limitations.
Philosophy for research work is defined by the medium used to examine social occurrences in which an individual can investigate explanations and get a deep understanding of the specific activity. It is specified as a belief in the way data about an occurrence must be collated, analyzed, and used. There exist four major research philosophies viz positivism; interpretivism; pragmatism; and critical realism (Kirongo and Odoyo, 2020).
In this study, the scholar has chosen the interpretivism paradigm as appropriate to analyze the role of the entrepreneurial ecosystem in tech startup success. This is selected as it has facilitated the scholar to know the subjective engagements, attitudes, and beliefs of notable stakeholders. Also, it has enabled the scholar to develop a more significant understanding and interpretation of different environments and social worlds. This paradigm supposes that human establishes meanings and because of the complexity linked with such a process, they may be lost when they are investigated like physical events (Al-Ababneh 2020).
There are three types of research approaches to the development of theory: inductive, abductive, and deductive. It is said that deduction follows the scientific method since it entails theory development that ultimately might have to be put under a test. The phases of undertaking this approach entail hypothesis design from the main theory and placing it in a test. After, there comes an understanding and analysis of the consequences and modification of theory in the quest for findings (Sileyew 2019).
Since the focus of this research is not to take out a hypothesis from it, like in the case of using a deductive approach, therefore an inductive approach is found as the best-fit method for this study. Further, the selected approach enables the researcher to foresee inferences identified from the outcomes by determining themes that produce novel theories. It is chosen further as it is focused on knowing the nature of the problem through collating qualitative data that can contribute to the theoretical suggestions based on the data analyzing results. It also enabled the researcher to collate data, assess it, and formulate theory later. It is deemed useful for this study since it is aligned with the interpretivism paradigm (Kyngäs 2020).
There are three methodological choices viz qualitative; quantitative; and mixed-method. It is said that the quantitative method is suitable when intending to generalize the findings and adapt them to a massive population which may not be possible with the qualitative method. Moreover, such a method is deemed a technique to collect and assess numeral data and is usually associated with the positivism philosophy and deductive strategy. Hence, such a method is not suitable for the current study. The qualitative method can't be used to generalize the outcomes as the focus is more on the interpretations of an individual's world. A mixed-method approach incorporates qualitative as well as quantitative data (Taherdoost, 2022).
For this study, the scholar chose qualitative methodological choice as this method is closely related to the interpretivism philosophy and inductive approach which directed the current study. Also, the qualitative method is typically attributed to extracting the conclusions or inferences to be investigated from words, not having participants, and collecting data via semi-structured methods. This is chosen as the attained findings from the qualitative method can be realized in different ways (Chivanga and Monyai 2021).
As per Mfinanga et al. (2019), a research strategy consists of choices such as when the research will follow qualitative, quantitative, or mixed-method techniques. It specifies how the scholar intends to conduct the study. Typically, the research strategies can be case studies, surveys, grounded theory, and more. The current study chose grounded theory as the suitable research strategy as it is mainly employed in qualitative research to make a theoretic understanding of the common social procedures. This is employed with the different kinds of data including secondary data. It is further deemed as an organized inductive technique to conduct qualitative research to make a theory. This is selected as an appropriate technique as it contributes to findings that are more proximity reflected in reality. The main objective of this approach is to develop a theory that explains the event being investigated which is based on the data collected and analyzed rather than preconceived notions. It is considered suitable as it has advocated the data-gathering technique utilized which is document analysis. It has facilitated the scholar to assess current documents such as policies, reporters, and more which are relevant to the subject being investigated. It further does not have a pre-established understanding of occurrences before the initiation of the qualitative research (Bakker 2019).
The sampling method is considered an important approach to make the study successful. Such a technique specifies an item, set, object, or individual who is engaged in the survey or interview process or the ones who help to give the primary data (Khan 2020).
For this study, the scholar needs to measure whole features and views to make a proper outcome. As the whole study is based entirely on secondary data instead of primary data, there was no requirement to choose a sample size and sampling method.
The time horizon specifies the timeline wherein the research project is intended to be completed. Two time horizons namely cross-sectional and longitudinal are there for the research work. The cross-sectional is where there is a pre-established time for the data collection. Also, it is based on the gathering of data regarding the development at a period. Besides, the longitudinal time horizon specifies collecting data repetitively over an elongated period (Spector 2019).
For the current study, the scholar chose a cross-sectional time horizon that facilitated him to collate data in just a time, maybe a day, or month to fulfill the study aims and objectives. It is chosen by the scholar to investigate numerous variables at a point in time. Further, it is chosen since this time horizon is considered economical, and quick, facilitates future study, may gather data from different variables, and so on. Supposing the timeline of this study is of 5 months, a cross-sectional time horizon was deemed more suitable that is the situation when the research project is time-bounded (Hunziker et al. 2021).
Data collection specifies a method to collect whole data and information from reliable sources. This method can help the scholar understand the research objectives and remove any problems confronted during the study and provides a suitable inference also. There are two types of data collection namely primary and secondary data. The secondary data is the one that has already been gathered for other motives while primary data is called first-hand data. Though secondary data is not deemed as original, it can still assist the scholar in responding to the research question (Taherdoost 2021). This entails raw data and published summaries. The scholar decided to conduct a qualitative secondary study for the selected interpretivism paradigm. Only secondary data was collected for this study. There exist three types of secondary data namely surveys; multiple sources; and documentaries. Moreover, being a mixed-method study, the scholar employed all these stated types of secondary data as a base for the analysis. Specifically, data was gathered using peer-reviewed journal articles and books. The search terms that were utilized to determine the types of journals to be used entail "theoretical concepts of entrepreneurial systems and networks," "entrepreneurial ecosystems and networks," and "startups and entrepreneurial ecosystems and networks." The keywords which were used in such a search entail entrepreneurial ecosystems", "entrepreneurial networks", and "startups. The search was restricted to peer-reviewed journals to certify that the data gathered is precise and has been reviewed. Additionally, data was limited to articles published in the past ten years to certify that the data is current and applies to today's market.
The secondary data that was collected through the secondary sources has surged the accuracy of this research. It is said that secondary data is useful since it can offer data for the scholar to understand, explain, and solve the research issues. For this study, the scholar specifically focused on the document analysis technique since it has facilitated the scholar to typically review the prior literature as part of this research and put that in the research report. The previous studies are deemed the effectual sources of data provided that the researcher relies on the interpretations and descriptions of the data rather than having the raw information as a basis of analysis. Besides, such a data gathering technique generates data in the form of whole passages that are then handled into important themes and categorized particularly through thematic analysis (Mazhar et al. 2021).
Data analysis in a study is an intricate procedure that demands clear and vital process thinking and approaches. It further entails recognizing themes and organizing data gathered by the scholar on the study topic. The data analysis in this secondary qualitative study usually uses the thematic analysis method which is used to figure out the patterns and themes in the data gathered from previous study investigations in the establishment of this qualitative secondary study (Dubey and Kothari 2022). The starting phase in the thematic analysis is to comprehend the data. To entirely understand the data, research is required to read documents many times. The researcher then initiated to allocate codes or labels to important ideas or themes that surface from data. This is selected as an appropriate technique of assessment in this study as it specifies the process of reflexivity in which the researcher's subjective involvements are at the center of making sense of the data. This analysis technique is considered a flexible approach to qualitative assessment that allows the researcher to produce new viewpoints and theories emanating from the data. This activity enabled the scholar to identify the main themes and subthemes (Peel 2020).
The scholars in this study encounter a few challenges like researcher bias from the collected secondary sources. It can be mitigated by utilizing only peer-reviewed journals. While the document analysis technique is deemed a robust approach for data collection in the qualitative secondary paradigm, its findings can rarely be generalized of how the scope of document analysis is bounded. Further, the problem related with subjectivity might occur when carrying out qualitative study and using a general inductive approach. The generalizability of the collected data and the dearth of study in the chosen area mainly about the entrepreneurial ecosystem also found the study's limitations. The data gathering using secondary sources might not be fully reliable as certain sources may consist of random data. To address such issues, further forthcoming research may be conducted based on the quantitative strategy and by collecting the primary data. Further, it is suggested to utilize a mixed-method strategy to attain generalized findings.
Ethics is considered vital in the process of data analysis. The current study obeys the ethical norms. It is important to consider prospective ethical considerations while carrying out the qualitative study as the data interpretations and the outcomes are more subjective. The scholar ensures that the research is carried out responsibly and respectfully by adhering to ethical rules and accrediting the actual data sources. The research also ensures that the research outcomes are elucidated precisely and that the findings are reliable by addressing the research's limitations. The research before gathering the internal data of the selected company should obtain consent from the senior management of the case startups. Lastly, the study is carried out by considering the plagiarism aspects. Since the current study uses only secondary data sources, there are no ethical issues related to human privacy, confidentiality, transparency, informed consent, and potential for harm. It is ensured that the entire data used in the secondary study is secured and maintained securely. Moreover, it was vital to appropriately credit the original researchers and their efforts when using the data from secondary sources (Suri 2020).
As per Stam and Van de Ven (2021), the ecosystem is indicated as a system that entails all living creatures in a region and its physical environment operating collectively as a unit. Another scholar defined it as an intricate and multifaceted array of relations among the living resources, accommodations, and civilians of a region, whose operational objective is to preserve an equilibrium-sustaining state. An ecosystem is found to contain numerous heterogeneous elements that collaborate in parallel and possess a set of usual attributes linked with any intricate adaptive system. A study by Ratten (2020) asserted that the ecosystem is described as an economic community that is advocated by a basis of cooperating companies and individuals. Further, an economic ecosystem indicates a natural mixing of businesses, people, and other participants who collaborate their competencies and resources and incorporate their dedications to formulate supplementary value and improve efficiency. It is found that the success of a startup business relies not just on the competency of the entrepreneur, but also on how effectually the entrepreneur integrates and embodies the complementing know-how, assets, and competencies in the entrepreneurial ecosystem (Zaidi et al. 2023).
According to the study by Hakala et al. (2020), the concept of an entrepreneurial ecosystem is robustly debated in the academic literature. As per the study by Tiba (2020), an entrepreneurial ecosystem (EE) is defined as an array of interrelated entrepreneurial participants, companies, establishments, and corporate procedures that systematically and irregularly come together to associate, liaise, and govern efficiency within the native entrepreneurial setting. It is considered a special economic community that focuses on talented pioneers like engineers, scholars, investors, and associated assets, prospects, capital, and policies dedicated to developing entrepreneurial businesses. Another scholar Carayannis et al. (2022) found that EE entails numerous sorts of participants, startups, venture capital, and others that enable the entry, development, and exit of novel businesses. It has identified that there are six major areas in the EE namely culture; institutional support; accessibility of sufficient funds; policies & leadership; excellent human resources; and venture capital. Therefore, every ecosystem evolves under an exclusive range of situations and circumstances. Besides, these are common areas consisting of myriad components and collaborating in greatly intricate and distinctive manners.
Another scholar Cavallo et al. (2019) found that entrepreneurial endeavors mainly for venture development are outcomes from an overtime coexistence of complementing components in the vibrant entrepreneurial ecosystem. It is also stipulated that entrepreneurship entails an accumulation of know-how, assets, institutions, and registered events consisting of numerous actors who go beyond the boundaries of various public and private companies. The imaginative procedures and emerging infrastructure in entrepreneurial ecosystems such as Silicon Valley is such competence that appeal to talent explorers, value know-how, and fiscal assets globally to collect together. It has been found by Rovito et al. (2021) that talent explorers entailing investors, engineers, scholars, and others go to Silicon Valley concurrently with different backgrounds and unique motivations, formulating professional channels for venture development. It is also found that the condensed networks, and ties in the ecosystem exchange information, and spread know-how, demands, and supplements, enabling the fit and match of complementing assets and surging the entrepreneurial prospect recognition. Based on a unified and all-inclusive viewpoint, entrepreneurial ecosystem theory might increase the identification and understanding of the forces and variables in the venture creation procedure.
The key elements that are needed by the majority of the entrepreneurial ecosystem entail financial capital; social capital; knowledge capital; and human capital.
It is stated by Noelia and Rosalia ((2020) that a startup is defined as a newly developed business. It is further described as the procedure of initiating or making something start that indicates starting a novel business. It has been stated by Marcon and Ribeiro (2021) that a novel venture is not always a startup except when the major motive of its creation is to launch novel goods in the marketplace. Another scholar asserted that when an individual initiates a novel restaurant company, then it is not deemed a startup since the business is not at higher risk or possesses the scalability of a startup. As opined by Thomas et al. (2019), startups are deemed as human establishments made for performing under situations of extreme uncertainty to develop a novel good or service. Moreover, scholars compare effective startups as disruptive techniques as they act under extremely uncertain conditions and are effective in promptly changing good and market approaches to adjust, develop, and beat the market.
As per a study by Thomas et al. (2019), a tech startup is deemed one that utilizes technology to bring goods or services into the market to resolve an issue. Because of the huge development and spread of digitized technology, the majority of startups today are considered tech startups. It has further been found by Wagner (2021) that tech startups are the momentous sources that assist in flaring innovation, helping to surge productivity and offer more employment prospects. It has been found that the third industrial revolution and the fourth industrial revolution (IoT; AI; Robotics; and more) bring forth disruptive variations in all sectors because of which more startups in current times are tech-based. Startups launch new offerings resulting from a superior notion in a complex and risky setting. The startup is deemed a temporary company hunting for an innovative, memorable, fruitful business model and at the start of the startup corporate model is a canvas with notions but it possesses no clients and minimum client know-how. It is further defined as the human establishment made to develop a novel good or service under uncertain situations. It is found that as startups have the intrinsic attributes of higher risk and higher development, it is vital to develop a setting wherein promising startups might be capitalized in a timely way.
It has been asserted by Korreck (2019) that tech startups are typically developed by an entrepreneur which is an individual in business who is ready to take economic threats to make a profit. These startups provide technological goods or services to the marketplace. These businesses can develop tech-based goods and services to serve society by utilizing imaginative or high-tech technologies. It is found that a startup business is a sort of entrepreneurial activity that attempts to address a marketplace demand by forming an effective marketing approach around novel goods, services, techniques, and systems. It is a business developed to create and verify an effective business. The success of a business is described in numerous forms. It has been found that the SC (supply chain) integration; firm's age; founding team's size; fiscal resources; market scope; patent security; and more are considered forces leading to the success of technology startups. It is suggested that success must be described in such a way that it offers credibility to the engaging businesses and develops a measurable factor for this study and the business positioning. The factors that are affecting successful tech startups include the following:
It has been asserted by Etzkowitz and Steiber (2019) that Silicon Valley, as the topmost ecosystem of the globe, is termed the hometown of the current information technology startups. It indicates a 1500-square-mile region of North California. This area has a vibrant history and culture, blue sky, and constant moderate temperature. It is said by Chapple and Jeon (2021) that Silicon Valley is an area in the South San Francisco Bay Area that is considered the headquarters of numerous tech businesses and technical innovations. It has been the globe's premier high-tech hotspot for imagination and entrepreneurship. It has more start-ups than any other area on the globe and has managed to continuously renew itself. Moreover, it is defined as a center for high-technology startup businesses that desire to prosper, and its corporate culture is based on the exclusive mix of talent, notions, innovations, competitiveness, persistence, and passion since it possesses the greatest concentration of startups worldwide. It further emphasizes AI (artificial intelligence) technology as a forthcoming innovation engine. This has been preventively endorsing the AI startup ecosystem, entailing capitalization in AI startups and enlargement of M&A (merger and acquisitions), reinforcing industry-university collaboration, and refinement in data accessibility. Moreover, it is leading the worldwide market by quickly endorsing research and industrialization from the origin of technology to the application service department. Technical clusters such as Silicon Valley are an evident attribute of numerous nationwide, regional, and state economies mainly the progressive economy. It has been stated that a cluster entails an ecology of interconnected technology firms with which businesses can contest both nationally and globally, and linked institutes that surge efficiency (Moretti 2021). The Silicon Valley region is deemed an ecology with skilled individuals entailing scholars, entrepreneurs, and shareholders who cooperate to establish, and initiate novel businesses, and generate products and services. Cluster further indicates regional sectoral network systems, a part of the assessment, and pre-existing sectoral structures contained regional ecology which produces present industrial businesses and imaginative notions (Harima et al. 2021). Policymakers and scholars use trade theories to assess the advantages of the industrial system to the civilians and economy. The presence of major establishments of research to industrial network systems impacted the development of electronic-linked businesses, and produced present industrial clusters, and imaginative notions in no small measure (Yagüe-Perales et al. 2019).
As per the findings of Piqué et al. (2020), Silicon Valley serves as a sowing ground for notions wherein pupils become inventors, diffusers, and part of the staff. Innovators and early adopters are willingly accessible to promote imaginative techniques or goods in Silicon Valley to assure other clients. It has been found that business failure might be under-appreciated in other places but permitted in Silicon Valley as a vital means to improve learning and iteration in the area of entrepreneurship and innovation. It is found as a prominent technology cluster, open innovation differentiates Silicon Valley while rivalry from other clusters is traced behind. As opined by Armstrong et al. (2023), startups demonstrate a main factor in the economic aspects of Silicon Valley. The forces that assisted in endorsing the success of this region's innovation and entrepreneurship entail diversified talents; free flow of capital; skilled labour; governmental support; and risk appetite. The entrepreneurs in this area developed and formed technological businesses for international markets in education, transportation, retail, and more since shareholders fund deals quicker in Silicon Valley than in other areas. The fast turnaround in deal funding led to the evolution of businesses like Facebook moving to Silicon Valley after being initiated elsewhere (Skawińska and Zalewski, 2020).
Another major factor that endures to play an essential role in the success of Silicon Valley has been governmental R&D spending on the region's institutes. Governmental support for R&D at the universities is vital to Silicon Valley, and the US economy. This region is considered home to a massive pool of competent population of Chinese and Indian immigrants with technological competencies and expertise in computing and electronics. Silicon Valley's startups rise beyond all sectors quicker than other technological clusters across the globe. Shifting a startup company into an effective business is mainly challenging for an unskilled entrepreneur (Etzkowitz 2019). The approach for entrepreneurs is to recognize and choose a mentor to nurture the growth of the mentee and make it simple for the mentee to succeed in the business. An activity of a tech startup entrepreneur is to move the challenges confronting the startup into constructive developments and corporate outcomes. Mentoring has become a progressively famous practice in tech startup entrepreneurship wherein expertise is vibrant and contextual. A cause tech startup entrepreneur drifts to Silicon Valley is the accessibility of intellectual assistance entailing the accessibility of mentors. It has been found that mentoring offers a learning prospect for mentees to attain corporate know-how from mentors who have chosen the pathway of initiating a novel business and confronted challenges linked with the activity. It is asserted that growth-driven companies of all sizes and sectors are confronting a major shortage of advanced innovators making it essential for startup entrepreneurs to start relations with mentors for skills development, performance refinement, increase of potential, and the realization of a dream (Stephens et al. 2019).
Silicon Valley is the essence of novel technologies that individuals thought would transform such as computing devices, telecommunications, manufacturing, and warfare. Moreover, it is a magnet for high-tech startup entrepreneurs who desire to thrive, and its corporate climate is based on an exclusive mixture of talent, notions, creativity, appeal, perseverance, and passion. It symbolizes higher-risk companies attributed with quick successes or failures, enormous job mobility, and informal actions (Tabe, 2022). Besides, it is deemed a stimulating location for individuals with the competencies and vision to use its offerings, and entrepreneurs in the area are called to constantly hunt novel notions and develop novel prospects. It got its name from the silicon-linked microprocessor, incorporated circuits, and semiconductors that were established in this area between 1939 and the early 1980s. Regardless of facing the worldwide economic crisis of 2007-08, the Silicon Valley ecosystem has changed the technology industry, shifted the emphasis of higher growth startup companies, and offered a setting to nurture startups which have shifted to some of the rich businesses in the globe. Silicon Valley is deemed as headquarters of prominent high-tech companies like Apple; Cisco; Uber; Twitter; Salesforce; and so on (Adams 2021). These innovative businesses have altered individuals' lifestyles, and their very manner of thinking, functioning, and conversing, and they all started as small but ardent startups. These have had an extraordinary societal and economic influence and have stimulated numerous eager startups to try their luck as well (Kantis and Federico 2020).
The attributes of the early Silicon Valley electronics businesses equate to the structure of Silicon Valleny’s industry business of today, for instance:
It has been described by Fuerlinger and Garzik (2022) that the attributes of the Silicon Valley ecosystem are significant and argued that it is not the neo-classical viewpoint of the inputs like land, labor, technologies, and capital that is figuring out the output. Rather, it specifies the mixture of those components which is the variance between success and failure. It is further stated that a dysfunctional ecosystem is developing societal blockages emanating from transactional costs like geographical distances, absence of faith, ineffective social channels, and variances in languages, and cultures. Moreover, it is found that Silicon Valley has prospered evading them via a range of social behaviors, emphasizing evading individual short-run gain in exchange for common long-run gains.
A successful setting for startups needs them to access markets for their imaginative offerings. It can be said that the primary buyers of such firms's offerings, other than consumers, are large businesses. It entails conventional large-scale businesses that have existed for a long like HP; and IBM; and firms which become large relatively currently, ranging from Apple to Google. Large-scale companies offer market access for startup businesses in two major ways. Firstly, they might act in conventional client roles. It is mainly vital when large-scale businesses become the initial clients or reference clients to startups. Secondly, large-scale businesses might acquire startup businesses via merger and acquisition activity. Such companies can offer their assets to make the notion of the acquired startup business attain even higher and more prompt market success than the startup might attain otherwise (Hulthen and Graff 2020). The function of the government as a main lead buyer for offerings of startups in Silicon Valley is usually understated in evaluations of Silicon Valley mainly amongst numerous participants in Silicon Valley (Baron and Freiling 2019).
It has been found by Kwon and Sorenson (2023) that technology startup entrepreneurship with developmental strength introduced in Silicon Valley endorses unparalleled prosperity amongst people and businesses within the region, state, and nation. It is said that the engineers and business persons who assess if certain notions are technically feasible originate from an identical pool of technology entrepreneurship. It has been found that in Silicon Valley, capitalizing in startup firms might develop wealth for the shareholders and entrepreneurs. Moreover, it has been asserted by Mungila Hillemane (2020) that the attributes of an effective startup developed in the Silicon Valley area entail special talents, appetite for threats, external sources of capital, R&D via governmental support, and reputed academic institutes, particularly Stanford University and the University of Berkeley. Such attributes assimilate to offer Silicon Valley a benefit over other technological clusters across the globe. Besides, the startup firms based in this region were accountable for the success of Apple, Facebook, Oracle, and identical firms. The vital components in the success of technology startups rely on resolving a higher value issue for a widespread number of clients; hiring a skilled founding team; and accessibility of adequate capital (Acs et al. 2021).
Daniel et al., (2018) argue that the concept of entrepreneurial ecosystems has gained prominence in recent years as a framework for understanding the factors that contribute to entrepreneurial success. Their study unravels the complexities of entrepreneurial ecosystems as it is a fairly new subject that has recently gained traction in business research. They compared systems theory and business networks to better understand the subject and determined that different concepts of place and dynamics are particular to entrepreneurial ecosystems which then guide research and policy creation in the same field. This paper is important to this research as it helps in the identification of gaps that are yet to be covered when it comes to investigating entrepreneurial ecosystems and networks.
Another major scholar Spigel and Harrison (2018) argued that entrepreneurial systems have only just emerged in entrepreneurship policy communities. Their paper delves into the different ecosystems and how their success or failure can be used as learning opportunities to help in the creation of future successful entrepreneurial ventures. They argue that the failure of a startup may be interpreted negatively at the surface level and labeled as a failure and that should not always be the case. Instead, their paper asserts that they lead to the creation of entrepreneurial knowledge, investment capital, and skilled workers. Pioneers of failed startups can successfully use the lessons learned to create a new successful venture in the future. Others could also learn from these lessons and utilize the skills they had obtained in establishing better ventures. This paper supports this research by highlighting the entrepreneurial ecosystems that could lead to the potential failure of ventures and how future entrepreneurs can navigate them successfully.
The previous studies of the scholars are found to lag behind in exploring the relation between entrepreneurship ecosystems and the businesses’ sustainable performance. The current study is able to investigate the empirical associations between the latent variables of the research. The outcomes of this study were able to benefit the management of companies to address the issues and improve the businesses’ competitiveness for business growth and development. The previous studies are found to include the most cited articles, ignores the concerned of geographic viewpoint of entrepreneurial ecosystem which imply that its framework does not consider the variance of every community, nation, and region. The previous scholars further pointed out gaps in the literature on whether mutual entrepreneurial narratives in underdeveloped and new entrepreneurial ecosystems might impact owners’ choices and inspire or hamper them from using effective and casual logic.
It has been found that entrepreneurial intentions are deemed an impetus to attain startup activation. It is asserted that based on the competencies needed for startups and entrepreneurial intents, business persons become a way to activate startups via prompt entrepreneurial endeavors, entrepreneurial orientation pushes them and hence impacts the development of entrepreneurial ecosystems. Hence, it can be interpreted that to develop an entrepreneurial ecosystem wherein startups proactively seem, attempts are required to surge entrepreneur orientations and entrepreneur assets. Moreover, it can be said that as evolving markets are resistant to vary and are committed to preserving the status quo particularly emphasizing enlarging their markets, it is essential to propose revitalizing startups and altering the ecosystem framework via an entrepreneurial orientation.
Mason and Brown (2014) articulate that developing and supporting high-growth firms (HGFs) has become a major goal for developed countries. They argue that current efforts which include creating supportive environments and policies and providing funding are insufficient in ensuring the growth of startup firms which would eventually lead to HGFs. In addition, they posit that to nurture the growth of startups, there is a need to meet certain factors other than funding and favorable environments to support them. These factors include entrepreneurial recycling which essentially relates to having the successful HGF entrepreneurs helping startup entrepreneurs by re-investing their time, money, and expertise in support of their startup firms. As per literature findings, other factors include the presence of large firms preferably in the same industry, and universities to provide a constant supply of talent, culture, and service providers. Therefore, it is analyzed that the findings contribute to the study of how the ecosystem can be built so that it not only supports startups but also holds and supports them through the growth phases to become high-growth firms as well as creating a cycle that goes on and on.
One of the key challenges startups experience is marketing for their products. Ritala, and Gustafsson, (2018) discuss how marketing can be incorporated into entrepreneurial systems. They argue that most entrepreneurs approach marketing differently than High Growth Firms do. Entrepreneurs'' marketing approaches are more innovative. The paper examines four fundamental marketing to show how entrepreneurial marketing varies from conventional marketing by HGFs. They argue that entrepreneurs are often inspired by fresh concepts and an instinctive sense of the market. As an alternative to depending on "top-down" segmentation, targeting, and positioning procedures, they target markets through "bottom-up" self-selection and suggestions from customers and other influence groups. Compared to the conventional combination of the four or seven "P's," they favor interactive marketing techniques. Rather than using formalized intelligence systems, they obtain information through informal networking. For any business venture to be successful it has to be able to reach its target markets and in a manner that encourages these markets to purchase their products and services. This paper is important to this research as it looks into how entrepreneurial networks come into play regarding marketing to support startups in amassing their customer base and keeping the competition healthy.
According to findings by Fernandes and Ferreira (2022)., it has been found that entrepreneurial networks offer a corporate operation and cooperation channel amongst peers. Likewise, the networks can drive disruptive innovation. It is found further that a startup ecosystem is crucial for startup firms to thrive and scale, demonstrating their viewpoint on this area. It is also reflected that the ecosystem serves as a driver to convert the initial corporate notion into reality. Such startups and entrepreneurial communities are performing a crucial job in offering mentoring and workshops that ultimately assist in forming a robust network and contacts that are extremely vital for entrepreneurs. It is stated that when the entrepreneurial ecosystem of an organization is not present or operating, their business might not be capable of functioning this effectually and might take three times longer to even start any functions. The literature findings suggested the entrepreneur ecosystem advocates not just existing business persons but also stimulates prospective entrepreneurs to join the community. Also, it has made it simple for them to approach the worldwide startup community and other ecosystems across the globe, either for cooperation, know-how exchange, enlarging the company or to get capitalization from global investors. It reflects that a startup ecosystem is essential for startups to thrive and succeed. It can be analyzed that with a firm's network density and associations between firms increase, it can surge know-how, learning impacts, and the disruption it attains. Moreover, it is interpreted that through collaborations within entrepreneurial ecosystems and networks, startup businesses can converse with unique partners and then develop an exclusive blending of technologies and other resources. Such collaboration and interactions are found to assist businesses in comprehending one another, subsequently improving their tactical profile and assisting novel ventures in establishing superior solutions to launch novel goods. The diverse data and resources exchanged by heterogeneous networking individuals that might surge a business's understanding of the market can assist the novel ventures grabbing entrepreneurial prospects more effectively and refining disruptive innovation efficiency. It can be said that impulsive communication amongst the people of heterogeneous systems automatically enlarges know-how sources, facilitating startups to refine their capabilities to establish know-how and technology and acquire other resources. Therefore, with enlarged possibilities, startup businesses might develop an exclusive value network and business model that might appeal to main clients and hence endorse disruptive innovation.
Other scholars' findings Neumeyer et al. (2019) suggest that entrepreneurial networks facilitate startup businesses and interrelated participants to investigate and incorporate resources for superior performance. It has also shown that accessing external assets might not confirm success. The literature findings suggest that entrepreneurial victory needs business persons to not just access external assets via their associations but also to accurately comprehend the varying desires that link with businesses' innovative paths and corporate approaches at the diverse venture phases. It can be interpreted from the findings that knowing how to equate partners proactively and form a cost-efficient entrepreneurial system intentionally are essential tactical decisions.
As per the findings by Radosevic and Yoruk, (2013), it can be asserted that entrepreneurship is not just a property of individual entrepreneurs but also of the economy and innovation systems. Moreover, literature review findings argue that different entrepreneurial systems are not solely influenced by the interaction of individuals with external factors of the enterprise but other factors such as knowledge-intensive enterprises and innovation systems also contribute to the entrepreneurial ecosystems. Therefore, it can be said that entrepreneurial ventures should be able to accelerate other economic activities that will eventually lead to the growth of more innovative entrepreneurial ventures. These findings can unravel the different entrepreneurial ventures that can result from a knowledge-intensive entrepreneurial environment. Moreover, these are important to this research as it investigates whether other factors contribute to the success of startups.
As per Bala Subrahmanya (2022), Silicon Valley possesses numerous corporate companies and establishments that create a corporate setting that has been considered to be greatly conducive to the effective creation of startups, disruptive corporate models, and leadership in a myriad of high-tech areas. The attributes of Silicon Valley entail a dual ecosystem of massive businesses and startups; venture capital; business infrastructure; international topmost level human resources for entire phases of startups; higher financial returns for effective entrepreneurs and startups' early workforces; and so on. It has been found that the mindset in Silicon Valley is what the scholar perceives is an important attribute of the ecosystem. It is asserted that the manner individuals are functioning in a spirit that is enormous regarding assisting others out as a main issue is focused in the literature review findings. The scholar perceives that the mindset simplest the cooperation in the ecosystem and functions as a foundation in the exchange of notions and know-how through the ecosystem. It can be said that the attributes of exchanging know-how and contacts without anticipating anything in return have been reflected in the literature review findings and the empirical data. Another major area wherein the literature review and secondary data are synchronized is the relevance of a great presence of capital that usually comes from venture capitalists. It has been found that venture capitalist businesses are involved a lot in the ecosystem and are advocating numerous startup firms. Such businesses are termed to be ready to accept higher threats in their investments that subsequently enable the entrepreneurial mind reflected above. Such firms are further found to play a crucial role by leading to appeal entrepreneurs and well-skilled individuals from all around the globe. The literature findings suggest that having well-skilled individuals is a requisite for developing an effective ecosystem. The secondary and literature findings support the fact that the talent in Silicon Valley is well-skilled but also diversified and that the diversified talent develops chances for numerous diverse disciplines to encounter. The secondary findings show that a higher density of talented people makes it likely for the ecosystem's businesses and startups to recruit higher-caliber individuals.
As per the study by Piqué et al. (2020), it has been found that though the influence of high-tech startups on the economy is significant, they possess a reverse side also. Such businesses frequently face an extremely high failure rate which can be attributed to numerous forces. The major factor is the liability of originality. It means that as the businesses are attempting to develop an exclusive offering that has no precedence, there exists a significant level of uncertainty about the forthcoming. Besides, such businesses are developed on a smaller scale with limited resources and confront massive and experienced rivals in the open market. Henceforth, their capability to resist sustained losses is typically extremely restricted. The literature findings suggested that despite such daunting challenges, startup firms have emerged with disruptive innovations and effectively taken on the giants in their pertinent areas. It has been stated that certain of the prominent businesses in the technology sector currently such as Intel, Apple, and more were set as small startups during their early years. Therefore, it can be interpreted that it is vital to evidently comprehend the range of forces that help the growth of higher-tech startups and also recognize the ones that appear to be the major obstacles.
It has been found by Song (2019) that the Silicon Valley ecosystem lessens the complexity of launching a new technological business. It has been asserted that under a long -time of function and optimization, the policies, rules., culture, establishments, and other associated infrastructure in the entrepreneurial ecosystem can embrace the venture development. The literature findings are synchronized with the secondary findings. It can be interpreted that the friendly atmosphere can lessen the intricacy of launching a novel technology and foster the development of startup businesses. Moreover, it can be said that the gathered managerial abilities and experiences in the entrepreneurial ecosystem might assist novel startups to overcome numerous mutual issues, surging the survival rate, and growth rate.
The scholars Pique, Berbegal-Mirabent, and Etzkowitz, (2018) look into the success of technology companies in Silicon Valley and their evolution over ten years. In doing so, they examine how Triple Helix Agents have been major players in contributing to the success of companies within this area. Triple Helix Agents include academia, the industry, and the government. They assert that in the Triple Helix model, the industry is the production center, the government is the source of contractual relations, and the academia (universities) provides a steady source of knowledge and hence innovation. These three agents retain their initial roles often but sometimes, there is an overlap in the roles they play. As per the literature findings, the universities support startups during their incubation and acceleration phases which is a primary role of the industry. Therefore, it can be interpreted that the findings are important to this research as they provide a detailed analysis of what ecosystems have contributed to the success of big companies in Silicon Valley as well as why startups continue to thrive in this environment.
In conclusion, this research offers valued perceptions into the role of entrepreneurial ecosystems on startup performance and success mainly for tech startups. The above discussion concludes that entrepreneurship is deemed a vital facilitator of employment across the globe, not just for the entrepreneur but for those employed by the entrepreneur. It has been concluded further that since entrepreneurship is an important economic driver for societies via the surge of the positive impacts that tech startups might bring to the societies wherein the business reside, nurturing more entrepreneurial firms cab just serve to suge opportunities and to make communities robust via the development of constructive operational relations. It is inferred that only via the establishment of a constructive co-existence and coherent relation amongst the numerous stakeholders engaged will entrepreneurial businesses survive and communities, wherein the businesses exist, thrive as well. Besides, the results specify that well-developed entrepreneurial ecosystems play an essential role in the success of startups by offering access to funds, assets, and talent and facilitating the leverage of network impacts and technologies. It can be said that the outcomes possess noteworthy implications for policy-makers, entrepreneurs, and others and underline the relevance of constant capitalization in ecosystems to advocate the development and success of tech startups.
Moreover, it was concluded that startups are fundamental for technical development, job opportunities, creativity, and economic development. These have become an essential factor for the nation's development as the volume of startups has momentously surged over the past times, while leading to regional growth by stimulating innovation, increasing institutional and structural variations, surging efficiency, and announcing novel offerings to the market. It can be inferred further that startups are extremely volatile and can not thrive on their own and require the direction of the ecosystem since it assists the entrepreneurs in polishing the essential abilities and offers assets to thrive and sustain their venture. It concludes that the ecosystem is necessary to appeal, to not just business persons but also other individuals such as investors, service providers, and mentors that assist the startups to scale. Moreover, the outcomes of secondary data collection have further reflected that the role of the ecosystem is essential not just after a startup has started its functions, but also before and during the formulation of a startup. It has been concluded also that the vital players of the ecosystem entail incubators, universities, and investors which are fundamental to building the startup ecosystem. Besides, the ecosystem might be preserved when entrepreneurs with a long-run dedication to the startup community lead the ecosystem.
It is concluded that the entrepreneurs in Silicon Valley used their channels by discussing their schedules and marketing their offerings. Due to this, the entrepreneurs were able to leverage the advocacy and support provided in such networks. It includes that the effectual communication and support in such networks can cause high race growth amongst the startups in Silicon Valley. With such advantages, the policymakers, universities, and others must penetrate entrepreneurial ecosystems and networks and offer entrepreneurs with the know-how and assistance required for developing and enlarging ventures.
Based on the current study, the following are a few recommendations for the management of tech startups and other firms.
The above-mentioned suggestions would go a long way to strengthen and promote entrepreneurial ecosystems, tech startups, and their attractiveness not just at the phase of evolution but more vitally at the phase of stability and scale-up. It might further enable the evolution of a surging number of unicorns in a short period with more job prospects, innovative offerings, income, and exports.
This study has certain limitations which can stimulate future studies to establish the entrepreneurial ecosystem literature. The current study is limited to literature linked with the entrepreneurial ecosystem and tech startups. The forthcoming studies can be enlarged by bringing the concepts such as innovation systems, and clusters into account. Also, the research suggests more empirical study since the current literature on entrepreneurial ecosystems is mainly conceptual. The forthcoming study linked with women in the entrepreneurial ecosystem is also suggested. The empirical data for this data was gathered using secondary sources only not based on any organization or nation. Therefore, future studies could benefit from investigating the subject considering diverse sectors, different contexts, and nations. Further, this study is cross-sectional as an ecosystem is formed, emerges, and established over time. Henceforth, prospective longitudinal researchers are suggested to enhance the understanding of the dynamics of an ecosystem since it can surge the understanding of the dynamic nature of roles and how network identity is developed. Multi-case study is suggested for future research since this technique can offer more influential arguments for the robustness of a theory. As a substitute technique, a survey questionnaire to assess and complement the outcomes might be feasible in forthcoming studies on the entrepreneurial ecosystem. The boundaries of this study restrict the scholar from investigating just the tech startups, but future studies can be carried out to examine the success forces and the framework's use in non-tech startup environments to subsequently enlarge the applicability of the findings.
Acs, Z.J., Song, A.K., Szerb, L., Audretsch, D.B. and Komlosi, E., 2021. The evolution of the global digital platform economy: 1971–2021. Small Business Economics, 57, pp.1629-1659.
Adams, S.B., 2021. From orchards to chips: Silicon Valley’s evolving entrepreneurial ecosystem. Entrepreneurship & Regional Development, 33(1-2), pp.15-35.
Al-Ababneh, M., 2020. Linking ontology, epistemology, and research methodology. Science & Philosophy, 8(1), pp.75-91.
Armstrong, K.E., Class, L., Leidinger, K.P., Martinelli, L. and Schulze, L., 2023. Overdependence in Silicon Valley on the Technology Industry. In The Strategic Management of Place at Work: Why, What, How and Where (pp. 343-356). Cham: Springer Nature Switzerland.
Attygalle, T.I., Withanaarachchi, A.S. and Jayalal, S., 2023, June. Factors Influencing the Success of Software Startups in Sri Lanka: A Comparative Analysis using SmartPLS & SEMinR. In 2023 International Research Conference on Smart Computing and Systems Engineering (SCSE) (Vol. 6, pp. 1-8). IEEE.
Audretsch, D.B., Cunningham, J.A., Kuratko, D.F., Lehmann, E.E. and Menter, M., 2019. Entrepreneurial ecosystems: economic, technological, and societal impacts. The Journal of Technology Transfer, 44, pp.313-325
Bakker, J.I., 2019. Grounded theory methodology and grounded theory method: Introduction to the special issue. Sociological Focus, 52(2), pp.91-106.
Bala Subrahmanya, M.H., 2022. Competitiveness of high-tech start-ups and entrepreneurial ecosystems: An overview. International Journal of Global Business and Competitiveness, 17(1), pp.1-10.
Baron, T. and Freiling, J., 2019. Blueprint Silicon Valley? Explaining Idiosyncrasy of Startup Ecosystems. Problemy Zarządzania, (1/2019 (81), pp.54-76.
Carayannis, E.G., Grigoroudis, E. and Wurth, B., 2022. OR for entrepreneurial ecosystems: A problem-oriented review and agenda. European Journal of Operational Research, 300(3), pp.791-808.
Cavallo, A., Ghezzi, A. and Balocco, R., 2019. Entrepreneurial ecosystem research: Present debates and future directions. International entrepreneurship and management journal, 15, pp.1291-1321.
Chapple, K. and Jeon, J.S., 2021. Big tech on the block: examining the impact of tech campuses on local housing markets in the San Francisco Bay area. Economic Development Quarterly, 35(4), pp.351-369.
Chivanga, S.Y. and Monyai, P.B., 2021. Back to basics: Qualitative research methodology for beginners. Journal of Critical Reviews, 8(2), pp.11-17.
Daniel, L., Medlin, C.J., O’Connor, A., Statsenko, L., Vnuk, R. and Hancock, G., 2018. Deconstructing the entrepreneurial ecosystem concept. Entrepreneurial ecosystems: Place-based transformations and transitions, pp.23-44.
Dubey, U.K.B. and Kothari, D.P., 2022. Research methodology: Techniques and trends. CRC Press.
Etzkowitz, H., 2019. Is Silicon Valley a global model or a unique anomaly? Industry and higher education, 33(2), pp.83-95.
Etzkowitz, H., 2019. Is Silicon Valley a global model or a unique anomaly? Industry and higher education, 33(2), pp.83-95.
Etzkowitz, H. and Steiber, A., 2019. Silicon Valley: too much success. Computing Predictive Analytics, Business Intelligence, and Economics: Modeling Techniques with Start-ups and Incubators. Oakville, Canada: Apple Academic Press Inc, pp.155-170.
Fernandes, A.J. and Ferreira, J.J., 2022. Entrepreneurial ecosystems and networks: a literature review and research agenda. Review of Managerial Science, 16(1), pp.189-247.
Fine, C.H., Padurean, L. and Naumov, S., 2022. Operations for entrepreneurs: Can Operations Management Make a difference in Entrepreneurial Theory and practice? Production and Operations Management, 31(12), pp.4599-4615.
Fuerlinger, G. and Garzik, L., 2022. Silicon Valley Innovation System. Successful Innovation Systems: A Resource-oriented and Regional Perspective for Policy and Practice, pp.225-247.
Greco, F., 2023. International Benchmark for Italian Start-Up Ecosystems. In Startup Ecosystems: Components for an Interpretative Model and International Benchmarks (pp. 79-118). Cham: Springer Nature Switzerland.
Hakala, H., O'Shea, G., Farny, S. and Luoto, S., 2020. Re‐storying the business, innovation and entrepreneurial ecosystem concepts: The model‐narrative review method. International Journal of Management Reviews, 22(1), pp.10-32.
Harima, A., Harima, J. and Freiling, J., 2021. The injection of resources by transnational entrepreneurs: Towards a model of the early evolution of an entrepreneurial ecosystem. Entrepreneurship & Regional Development, 33(1-2), pp.80-107.
Henry, M., Bauwens, T., Hekkert, M. and Kirchherr, J., 2020. A typology of circular start-ups: An Analysis of 128 circular business models. Journal of cleaner production, 245, p.118528.
Hulthen, P. and Graff, G., 2020. Migration of venture-capital funded startups from regional entrepreneurial ecosystems: comparing Colorado's Front Range and California's Silicon Valley (Doctoral dissertation, Colorado State University. Libraries).
Hunziker, S., Blankenagel, M., Hunziker, S. and Blankenagel, M., 2021. Cross-Sectional Research Design. Research Design in Business and Management: A Practical Guide for Students and Researchers, pp.187-199.
Kantis, H. and Federico, J., 2020. A dynamic model of entrepreneurial ecosystems evolution. Journal of Evolutionary Studies in Business, 5(1), pp.182-220.
Khan, N., 2020. Critical review of sampling techniques in the research process in the world. Available at SSRN 3572336.
Kirongo, A. and Odoyo, C., 2020. Research philosophy design and methodologies: A systematic review of research paradigms in information technology.
Korreck, S., 2019. The Indian startup ecosystem: Drivers, challenges and pillars of support. ORF Occasional Paper, 210.
Kwon, D. and Sorenson, O., 2023. The Silicon Valley Syndrome. Entrepreneurship Theory and Practice, 47(2), pp.344-368.
Kyngäs, H., 2020. Inductive content analysis. The application of content analysis in nursing science research, pp.13-21.
Marcon, A. and Ribeiro, J.L.D., 2021. How do startups manage external resources in innovation ecosystems? A resource perspective of startups’ lifecycle. Technological Forecasting and Social Change, 171, p.120965.
Mazhar, S.A., Anjum, R., Anwar, A.I. and Khan, A.A., 2021. Methods of data collection: A fundamental tool of research. Journal of Integrated Community Health (ISSN 2319-9113), 10(1), pp.6-10.
Mfinanga, F.A., Mrosso, R.M. and Bishibura, S., 2019. Comparing case study and grounded theory as qualitative research approaches. Focus, 2(05), pp.51-56.
Moretti, E., 2021. The effect of high-tech clusters on the productivity of top inventors. American Economic Review, 111(10), pp.3328-3375.
Mungila Hillemane, B.S., 2020. Entrepreneurial ecosystem for tech start-ups in Bangalore: an exploration of structure and gap. Journal of Small Business and Enterprise Development, 27(7), pp.1167-1185.
Neumeyer, X., Santos, S.C. and Morris, M.H., 2019. Who is left out: exploring social boundaries in entrepreneurial ecosystems. The Journal of Technology Transfer, 44, pp.462-484.
Noelia, F.L. and Rosalia, D.C., 2020. A dynamic analysis of the role of entrepreneurial ecosystems in reducing innovation obstacles for startups. Journal of Business Venturing Insights, 14, p.e00192.
Peel, K.L., 2020. A beginner's guide to applied educational research using thematic analysis. Practical Assessment, Research, and Evaluation, 25(1), p.2.
Piqué, J.M., Berbegal-Mirabent, J. and Etzkowitz, H., 2020. The role of universities in shaping the evolution of Silicon Valley’s ecosystem of innovation. Triple Helix, 7(2-3), pp.277-321.
Piqué, J.M., Berbegal-Mirabent, J. and Etzkowitz, H., 2020. The role of universities in shaping the evolution of Silicon Valley’s ecosystem of innovation. Triple Helix, 7(2-3), pp.277-321.
Radosevic, S. and Yoruk, E. 2013. The entrepreneurial propensity of innovation systems: Theory, methodology, and evidence. Research Policy, 42(5), pp.1015–1038. doi:https://doi.org/10.1016/j.respol.2013.01.011.
Ratten, V., 2020. Entrepreneurial ecosystems. Thunderbird International Business Review, 62(5), pp.447-455.
Ritala, P. and Gustafsson, R., 2018. Q&A. Innovation and entrepreneurial ecosystem research: where are we now and how do we move forward? Technology Innovation Management Review, 8(7).
Rovito, S., Kaushik, D. and Aggarwal, S.D., 2021. The impact of international scientists, engineers, and students on US research outputs and global competitiveness. MIT Science Policy Review, 2, pp.15-25.
Scheidgen, K., 2021. Degrees of integration: how a fragmented entrepreneurial ecosystem promotes different types of entrepreneurs. Entrepreneurship & Regional Development, 33(1-2), pp.54-79.
Scott, S., Hughes, M. and Ribeiro-Soriano, D., 2021. Towards a network-based view of effective entrepreneurial ecosystems. Review of Managerial Science, pp.1-31.
Sileyew, K.J., 2019. Research design and methodology. Cyberspace, pp.1-12.
Skawińska, E. and Zalewski, R.I., 2020. Success factors of startups in the EU—A comparative study. Sustainability, 12(19), p.8200.
Song, A.K., 2019. The Digital Entrepreneurial Ecosystem—a critique and reconfiguration. Small Business Economics, 53(3), pp.569-590.
Spector, P.E., 2019. Do not cross me: Optimizing the use of cross-sectional designs. Journal of Business and Psychology, 34(2), pp.125-137.
Spigel, B. and Harrison, R. 2018. Toward a process theory of entrepreneurial ecosystems. Strategic Entrepreneurship Journal, 12(1), pp.151–168. doi:https://doi.org/10.1002/sej.1268.
Stam, E. and Van de Ven, A., 2021. Entrepreneurial ecosystem elements. Small business economics, 56, pp.809-832.
Stephens, B., Butler, J.S., Garg, R. and Gibson, D.V., 2019. Austin, Boston, Silicon Valley, and New York: Case studies in the location choices of entrepreneurs in maintaining the Technopolis. Technological Forecasting and Social Change, 146, pp.267-280.
Suri, H., 2020. Ethical considerations of conducting systematic reviews in educational research. Systematic reviews in educational research: Methodology, perspectives and application, pp.41-54.
Tabel, J., 2022. Silicon Valley's" AI Revolution": A revolutionary narrative serving the status quo (Bachelor's thesis, University of Twente).
Taherdoost, H., 2021. Data Collection Methods and Tools for Research; A Step-by-Step Guide to Choose Data Collection Technique for Academic and Business Research Projects. International Journal of Academic Research in Management (IJARM), 10(1), pp.10-38.
Taherdoost, H., 2022. What are different research approaches? Comprehensive Review of Qualitative, quantitative, and mixed method research, their applications, types, and limitations. Journal of Management Science & Engineering Research, 5(1), pp.53-63.
Thomas, A., Passaro, R. and Quinto, I., 2019. Developing entrepreneurship in the digital economy: The ecosystem strategy for startup growth. Strategy and Behaviors in the Digital Economy, pp.1-20.
Tiba, S., 2020. Sustainability startups and where to find them: How entrepreneurial ecosystems impact their sustainability startups (Doctoral dissertation, Utrecht University).
Torres, P. and Godinho, P., 2022. Levels of the necessity of entrepreneurial ecosystems elements. Small Business Economics, 59(1), pp.29-45.
Wagner, S.M., 2021. Startups in the supply chain ecosystem: an organizing framework and research opportunities. International Journal of Physical Distribution & Logistics Management, 51(10), pp.1130-1157.
Wynn, A.T., 2020. Pathways toward change: ideologies and gender equality in a Silicon Valley technology company. Gender & Society, 34(1), pp.106-130.
Xu, Z. and Dobson, S., 2019. Challenges of building entrepreneurial ecosystems in peripheral places. Journal of Entrepreneurship and Public Policy, 8(3), pp.408-430.
Yagüe-Perales, R.M., Perez-Ledo, P. and March-Chordà, I., 2019. Keys to success in investment rounds by immigrant entrepreneurs in Silicon Valley. International Entrepreneurship and Management Journal, 15, pp.1153-1177.
Zaidi, R.A., Khan, M.M., Khan, R.A. and Mujtaba, B.G., 2023. Do entrepreneurship ecosystem and managerial skills contribute to startup development? South Asian Journal of Business Studies, 12(1), pp.25-5
You Might Also Like
Business Management Assignment Help
Top 10 Canadian Universities to Study a Management Program
1,212,718Orders
4.9/5Rating
5,063Experts
Turnitin Report
$10.00Proofreading and Editing
$9.00Per PageConsultation with Expert
$35.00Per HourLive Session 1-on-1
$40.00Per 30 min.Quality Check
$25.00Total
FreeGet
500 Words Free
on your assignment today
Get
500 Words Free
on your assignment today
Doing your Assignment with our samples is simple, take Expert assistance to ensure HD Grades. Here you Go....
🚨Don't Leave Empty-Handed!🚨
Snag a Sweet 70% OFF on Your Assignments! 📚💡
Grab it while it's hot!🔥
Claim Your DiscountHurry, Offer Expires Soon 🚀🚀
+61 483 954 335
+61483987786