Tech Startup Failures in India: Causal Attributes, Life Expectancy, and Exits
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The rapid growth of tech startups delivering innovative products/services in the market has been contributing to the economic growth of nations. However, entrepreneurs driving the tech startups experience multiple challenges, and if they remain unaddressed, startups experience failure. Startup genome (2019) reports that about 90% of the tech startups experience failure globally, and India as a developing economy aspiring to grow at an exponential rate is not different. While the Indian startup ecosystem promotes more startup creations, they do not have the required information to prevent future startup failures, which justifies an empirical study. In this study, we address the following research objectives. (i) What are the causal attributes of startup failures? (ii) What is the life expectancy of a startup? (iii) How did the startup and entrepreneur exit? To explore the above three research objectives, we gathered primary data from 151 cofounders (101 who have experienced failure and 50 who are successful and continuing their operations) from India's six leading startup hubs. To analyze our research objectives, we have used the following statistical techniques: (i) Binomial logistic regression, (ii) Survival analysis, including Kaplan – Meier estimation technique, and Cox proportional hazard regression, (iii) Classifications techniques, including CHAID and neural networks. The analysis results are summarized as follows: (i) The causal attributes that differentiate failed startups from successful ones at emergence, stability, and growth stages are identified. The attributes that can elevate startups from emergence to stability and stability to growth stages are also identified. With this, a clear picture emerges on the entrepreneurial journey, while distinguishing the failed startups from the successful ones. (ii) The life expectancy is different across the startup lifecycle stages, and the attributes that influence startup life expectancy are identified. (iii) The influencers of startup exit types and entrepreneur exit types are identified. The impact of startup exits on stakeholders and the epiphanies detailing how entrepreneurs cope and advise future entrepreneurs are captured. The study has the following two key contributions. First, the significance of startup lifecycle stages across all the three research objectives was ascertained, and it provides a detailed insight into startup failures. Next, this study's theoretical framework is replicable and scalable for studying the multifaceted and multilevel startup failure phenomenon. This empirical study has practical implications for entrepreneurs, investors, policymakers, and academicians. Firstly, entrepreneurs can plan for resources and be aware of the potential pitfalls of their startup journey. Secondly, investors should establish the engagement framework, governance structure, and plan their future funding strategy. Thirdly, policymakers should design and establish progressive support mechanisms that can prevent startup failures in the future. Fourthly, academicians can plan future research based on the comprehensive conceptual framework and study the startup failure phenomenon further.