This section discusses the academic and practical implications of the empirical findings presented in Chapter 4. The aim is to position the results of this dissertation within the broader research landscape and demonstrate their relevance for startup founders, corporate innovation managers, and the academic community.
This post represents a series of articles related to a research and dissertation called “Are corporate accelerators springboards for startups: a performance analysis of the Microsoft’s and Google’s accelerated.
ACADEMIC CONTRIBUTIONS
This study fills a key empirical gap in the literature on corporate accelerators. While existing research has examined the potential benefits of startup accelerators (specially seed accelerators), few have applied a systematic, time-sensitive analysis to corporate-run programs such as Google for Startups and Microsoft for Startups. By using one-way ANOVA across five distinct funding periods of time, this research offers a replicable and scalable model for evaluating the temporal impact of accelerator participation for other research, data and aims. Furthermore, implementing via performance over time (rather than at a single point) contributes to more nuanced theory-building in entrepreneurship and innovation studies.
Moreover, the research shifts focus from merely cumulative funding to a broader suite of performance indicators, including binary outcomes like IPOs, acquisitions, and closures. This allows a more comprehensive and complementary understanding of startup trajectories beyond monetary KPIs. In plain English, there is not just one unique way to measure success. This could lead to a remarkable difference between incremental innovation versus disruptive innovation.
The findings also challenge any simplistic assumption that accelerator affiliation guarantees success. The data show that Google-accelerated startups had stronger pre-acceleration profiles and more frequent high-status events, while Microsoft startups experienced higher closure rates. This reinforces the need for greater differentiation in the study of accelerator design, impact, specialisation, etc.
PRACTICAL CONTRIBUTIONS FOR STARTUP FOUNDERS
From a startup perspective, the study delivers concrete insights into what type of accelerator engagement might be most beneficial. For instance, early-stage startups with patents and a high degree of technical innovation may find more strategic value in programs like Google for Startups, which tends to support ventures with higher potential.
Startups can also temper their expectations. While initial funding differences were notable, no statistically significant differences persisted beyond the acceleration year until the third year recorded in this study. This highlights that accelerators may offer a strong push at the start, but long-term success still depends on internal execution, market context, and adaptability. Founders are thus encouraged to treat accelerators as a springboard, not a parachute.
STRATEGIC CONTRIBUTIONS FOR CORPORATE INNOVATION MANAGERS
For corporate sponsors and innovation strategists, the study presents actionable implications. One key finding is that early selection (like targeting startups within their first year) and patent ownership could correlate with better outcomes.
The greater success of Google-accelerated startups in IPOs, acquisitions, and survivability also suggests that program structure, mentor quality, and post-program engagement likely play a role. Microsoft’s higher closure rate invites reflection on whether the reason could have been programmatic support ends too abruptly, it is not specialised enough, lacks follow-through or else.
CONCLUDING REMARKS
This dissertation contributes both theoretically and practically to the discourse on corporate accelerators. By combining structured empirical analysis with real-world performance outcomes, it informs better research, smarter entrepreneurship, and more effective corporate innovation models. The next section (5.3) will outline the study’s limitations and suggest avenues for future research.
