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With its high degree of autonomy, dedication, and co-location, an autonomous team as an emerging tool for new product development (NPD) has more freedom and stronger capabilities to be innovative and entrepreneurial. However, such teams are not a panacea, and implementing them can be costly and disruptive to their parent organization. Hence, in this study we ask under which circumstances an autonomous team is the best choice for NPD. Drawing on both contingency and information-processing theories, we hypothesized that autonomous teams are more effective in developing novelty technology or radical innovation. We tested and confirmed the hypotheses using data from 555 NPD projects by comparing the relative effectiveness of autonomous teams with functional, lightweight, and heavyweight teams in terms of development cost, development speed, and overall product success. The results also suggest that heavyweight teams perform better than other teams in developing incremental innovation. The findings of this study may not only have some important implications for NPD practices but also shed some light on other important topics such as disruptive innovation, new venture, corporate entrepreneurship, and ambidextrous organization.

New product development speed has become increasingly important for managing innovation in fast-changing business environments. While the existing literature has not produced consistent results regarding the relationship between speed and success for NPD projects, many scholars and practitioners assert that increasing NPD speed is virtually always important to NPD success. The purpose of this study is to examine the implicit assumption that faster is better as it relates to NPS. From the perspectives of time compression diseconomies and absorptive capacity, the authors question the assumption that speed has a linear relationship with success. The authors further argue that time compression diseconomies depend on levels of uncertainty involved in NPD projects. Using survey data of 471 NPD projects, the hypotheses were tested by hierarchical regression analysis and subgroup polynomial regression. The results of this study indicate that NPD speed has a curvilinear relationship with new product success, and the nature of the speed-success relationship varies, depending on type and level of uncertainty. When turbulence or technological newness is high, the relationship is curvilinear but when uncertainties are low, the relationship is linear. In contrast, the results of this study suggest that a curvilinear relationship under conditions of low market newness but not when market newness is high. Discussion focuses on the implications of NPD speed under the different conditions of uncertainty.

New product development speed is a key component of time-based strategy, which has becoming increasingly important for managing innovation in a fast-changing business environment. This meta-analytic review assesses the generalizability of the relationships between NPD speed and 17 of its antecedents to provide a better understanding of the salient and cross-situationally consistent factors that affect NPD speed. We grouped the antecedents into four categories of strategy, project, process, and team, and found that process and team characteristics are more generalizable and cross-situationally consistent determinants of NPD speed than strategy and project characteristics. We also conducted subgroup analyses and found that research method variables, such as level of analysis, source of data, and measurement of speed, moderate the relationships between NPD speed and its antecedents. We apply the study’s findings to assess several models of NPD speed, such as the balanced model of product development, the strategic orientation and organizational capability model, the compression vs. the experiential model, the centrifugal and centripetal model, and the product development cycle time model. We also discuss the implications of our findings for research and practice.