| Keywords [eng] |
Deep tech, market timing, startup strategies, market fit, market readiness, timing strategy, technology market alignment, new venture success, contingency theory, aukštųjų technologijų startuoliai, startuolių sėkmės strategijos. |
| Abstract [eng] |
Summary VILNIUS UNIVERSITY BUSINESS SCHOOL DEEP TECH ENTREPRENEURSHIP PROGRAMME Kornelijus Ruskonis Boris Kim Market Timing in Deep-Tech: Strategies for Startup Success Supervisor Prof. Dr. Saulė Mačiukaitė-Žvinienė Vilnius, 2025 Scope of Master’s thesis (project) – 81 pages. Number of tables used in Master’s thesis – 14 pcs. tables Number of figures used in the Master’s thesis - 4 pcs. figures Number of bibliography and references - 98 pcs. references The Master’s thesis described in brief: In this Master's Thesis, we investigate timing for markets by startups using deep technologies and analyze whether and to what extent the relationship between internal organizational aspects (factors) and external market elements (conditions), affect market fit and start-up success. The research is focused on start-ups that rely on scientific basis and therefore are characterized by high uncertainty, very long product development time frames, as well as strong regulatory and ecosystem dependency. The research provides an integrated theoretical-experimental explanation of why successful commercialization in deep-technological environments depend on coordinating timing of market entry rather than uncoordinated individual strategic decisions. Problem, objective and tasks of the Master’s thesis: The research problem addresses the limited understanding of how deep-tech startups align internal capabilities with external conditions to achieve market fit and success. The objective of the thesis is to evaluate the impact of market timing, internal alignment, and adaptation on startup success through the mediating role of market fit. The tasks include examining theoretical approaches to market timing in deep-tech ventures, identifying key internal and external factors affecting market fit, developing a research model based on contingency theory, conducting empirical research, and integrating quantitative and qualitative findings. Research methods used in the Master’s thesis: The research applies a mixed-method design. A systematic analysis of scientific literature provides the theoretical foundation. Quantitative data are collected through an online questionnaire survey of deep-tech startup employees. Qualitative data are gathered through semi-structured interviews with founders and senior decision-makers. Triangulation is used to integrate results from both methods. Research and results obtained: Quantitative research found significant positive correlation between internal alignment, adaptability & responsiveness to the perceived market fit. Although, market timing is less connected to internal alignment. The qualitative results of the study also revealed that the founders see the timing as an ongoing, iterative, and adaptive process based on market information. Additionally, triangulation confirms that the findings are consistent across all methods used in this study. Conclusions of the Master’s thesis: Timing can function as a process of constant, iterative alignment between a deep-tech startup's team and its target markets. A market's "fit" mediates all timing-related influences on the success of a deep-tech startup. Whether or not a deep-tech startup successfully converts outside opportunity into actual results depends on the internal alignment and adaptability of its team. |
