T he authors study the takeoff of 16 new products across 31 countries (430 categories) to analyze how and why takeoff varies across products and countries. They test the effect of 12 hypothesized drivers of takeoff using a parametric hazard model. The authors find that the average time to takeoff varies substantially between developed and developing countries, between work and fun products, across cultural clusters, and over calendar time. Products take off fastest in Japan and Norway, followed by other Nordic countries, the United States, and some countries of Midwestern Europe. Takeoff is driven by culture and wealth plus product class, product vintage, and prior takeoff. Most importantly, time to takeoff is shortening over time and takeoff is converging across countries. The authors discuss the implications of these findings.

Despite a growing interest in the phenomenon of open innovation (OI), empirical evidence documenting the link between new product development capabilities, OI practices, and new product innovativeness is scarce. Eminent scholars have called for large-scale studies that systematically investigate the OI paradigm. Drawing on the knowledgebased view of the firm, new product development, and NPD capabilities literature streams, we conceptualize a framework in which OI practices are disentangled according to the stage of the new product development process in which they occur (development stage or commercialization stage). We identify two major types of OI practices: development-centric OI ( w h i c h o c c u r s i n t h e d e v e l o p m e n t s t a g e ) a n d commercialization-centric OI (which occurs in the commercialization stage). Specific types of NPD capabilities-R&D, market information management, and launch-are expected to both influence the extent to which each OI practice is implemented and moderate the effect of each OI practice on product portfolio innovativeness and firm performance. The empirical analysis combines primary data from a survey of 239 firms with secondary data on innovation and financial outcomes. Our results support our hypotheses and indicate a need to differentiate among the different kinds of OI practices while elaborating on the complex role played by NPD capabilities in influencing OI practices.

We critically examine alternate models of the diffusion of new products and the turning points of the diffusion curve. On each of these topics, we focus on the drivers, specifications, and estimation methods researched in the literature. We discover important generalizations about the shape, parameters, and turning points of the diffusion curve and the characteristics of diffusion across early stages of the product life cycle. We point out directions for future research.Because new products affect every aspect of the life of individuals, communities, countries, and economies, the study of the diffusion of innovations is of vital importance. Researchers have studied this topic in various disciplines, including marketing, economics, medicine, agriculture, sociology, anthropology, geography, and technology management. We present a critical review of research on the diffusion of new products primarily in the marketing literature, but also in the economics and geography literature. We use the word product broadly to cover any good, service, idea, or person. We distinguish the term new product from the broader term innovation, which refers to both new product and new method, practice, institution, or social entity. Even though we restrict our review to the marketing literature, which focuses on the diffusion of new products, the implications of our review may hold as well as for the study of the diffusion of innovations in other disciplines. The marketing literature on this topic is vast, dating back at least as early as the publication by Fourt and Woodlock (1960).The term diffusion has been used differently in two groups of literatures. Within economics and most nonmarketing disciplines, diffusion is defined as the spread of an innovation across social groups over time (Brown, 1981;Stoneman, 2002). As such, the phenomenon is separate from the drivers, which can be consumer income, the product's price, word-of-mouth communication, and so on. In marketing and communication, diffusion typically has come to mean the communication of an innovation through the population (Golder and Tellis

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The authors examine an increasingly popular open innovation practice, “design crowdsourcing,” wherein firms seek external inputs in the form of functional design solutions for new product development from the “crowd.” They investigate conditions under which managers crowdsource design and determine whether such decisions subsequently boost product sales. The empirical analysis is guided by qualitative insights gathered from executive interviews. The authors use a novel data set from a pioneering crowdsourcing firm and find that three concept design characteristics—perceived usability, reliability, and technical complexity—are associated with the decision to crowdsource design. They use an instrumental variable method accounting for the endogenous nature of crowdsourcing decisions to understand when such a decision affects downstream sales. The authors find that design crowdsourcing is positively related to unit sales and that this effect is moderated by the idea quality of the initial product concept. Using a change-score analysis of consumer ratings, they find that design crowdsourcing enhances perceived reliability and usability. They discuss the strategic implications of involving the crowd, beyond ideation, in helping transform ideas into effective products.