A framework for time-to-market reduction in startups
Abstract
Companies need to commit to new product development (NPD) and innovation to maintain sustainable competition. An excellent indicator to measure the technological change in a market is the portfolio of start-ups, after all, these companies develop new-to-the-world products every day. They can benefit more from innovation because they have less rigid routines and, consequently, greater adaptability to change. However, the sustainability of start-ups is very fragile. It is observed a high percentage of companies that are discontinued in a short time. Therefore, it is essential to promote actions that corroborate the improvement of the performance of these companies. Start-ups should minimize the time to receive feedback from customers about the product to be successful. This implies that these companies must produce, measure and learn quickly. Currently, there is a lack of a well-structured gradual approach for establishing factors to reduce time-to-market (TTM) in startups. Being early can provide an important competitive advantage, making the TTM reduction a significant area for inquiry. To address this need, the objective of this study is to evaluate the potential for startups to reduce time-to-market. First, to point out the drivers and capabilities for reduced TTM, as well as show its main attributes and effects on performance, a systematic literature review was developed. The results indicate 5 drivers as motivators for companies to reduce this time. As well as 19 capabilities grouped into five categories, namely: team, product, process, integration and strategy. In addition, 11 performance indicators are sensitive to TTM reduction. This stage has as the main contribution the proposal of a theoretical model that synthesizes 25 years of literature. A research agenda is also presented with interesting gaps found in this topic. Then, to identify the map of the relationship between drivers and capabilities pointed out in the NPD literature and their potential effect on start-ups performance, Interpretive Structural Modelling (ISM) was used with data obtained through interviews with experts. Only from this structured model and validated by experts, it was possible to create a TTM reduction measurement scale in startups using the item classification method, which resulted in a structured questionnaire. Thus, a survey was carried out on a sample of 191 startups to empirically investigate the impact of these drivers and capabilities and test the relationship between the contours of the model. Structural Equation Modeling was used for data analysis. With the fulfillment of the research objective, the best proven and modern organizational capabilities implemented by innovative companies in the process of developing new products can serve to guide future professionals in their innovation journey.
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