During the three decades since its inception in 1984, the JPIM has shaped the evolution of innovation research as a scientific field. It helped create a topic landscape that is not only more diverse and rich in insights, but also more complex and fragmented in structure than ever before. We seek to map this landscape and identify salient development trajectories over time. In contrast to prior citation-based studies covering the first two decades of JPIM research, we benefit from recent advances in natural language processing and rely on a topic modeling algorithm to extract 57 distinct topics and the corresponding most common words, terms, and phrases from the entire full-text corpus of 1008 JPIM articles published between 1984 and 2013. Estimating the development trajectory of each topic based on yearly publication counts in JPIM allows us to identify “hot,” “cold,” “revival,” “evergreen,” and “wall-flower” topics. We map these topics onto the Product Development and Management Association (PDMA) Body of Knowledge categories and discover that these categories differ significantly not only in terms of their internal topic diversity and relative prevalence, but also—and arguably more importantly—in terms of their publication and citation trajectories over time. For instance, the PDMA category “Codevelopment and Alliances” exhibits only moderate topic diversity (7 out of 57 topics) and prevalence in JPIM (161 out of 1008 articles). That said, it is among the most dynamic categories featuring two evergreen topic (“Users and Innovation” and “Tools and Systems for Technology Transfer”) and three hot topics (“Open Innovation,” “Alliances and Cooperation,” and “Networks and Network Structure”) as well as a sharply growing annual number of citations received. Our findings are likely to be of interest to all those who are keen to (re)discover JPIM's topic landscape in search of hidden structures and development trajectories.

The results of an explorative study on the financing of 18 high technology Belgian startups are reported. On a counts basis, the most important sources of financing at the startup are the entrepreneurs and the banks, but the sources that provide the largest amounts of funds are the venture capital companies and private investors. Private investors and venture capitalists have a complimentary role, with the former investing mostly at the startup and the latter financing the early growth. The role of the government, universities and other companies is limited.

Investigates the impact of using cost targets during new product development (NPD), in terms of design quality, product cost and development time. An NPD environment with cost targets is compared with an NPD environment where design engineers receive no specific cost targets, but are expected to "minimize" the cost level of future products. The impact of cost targets versus no-cost targets is investigated in combination with high/low time pressure. The 2*2 factorial design was tested in a laboratory experiment that simulated a real design process, with customers asking for the highest design quality. The results demonstrate that cost targets during NPD lead to lower-cost new products, while not impairing design quality or development time. However, under high time pressure, cost targets lead design engineers to work longer on the design, without a corresponding cost decrease.