Search

Technological innovation occurs as an evolutionary, path-dependent and interactive searching activity of optimal alternatives and is fundamentally dominated by an intense activity addressed to identify and solve technical problems. As components recombination is a very efficient source of innovation that firms widely resort to, the capability to recombine pieces of knowledge available in the organization or transferable from the outside becomes an important lever in the technological innovation strategy of the firm. Technological innovation is conceptualised as the outcome of a change of either the technological components or a diverse combination of the components themselves. Data relative to granted patents were considered and the sub-classes of the classification standard adopted were associated to technological components. Indexes of familiarity and technological concentration are calculated to analyse innovation trajectories. The sample includes 438 patents granted between 1975 and 2004 to 15 leading firms in the optical memory devices industry.

Technological innovation is characterized by a searching activity of optimal alternatives which is fundamentally dominated by an intense activity addressed to identify and solve technical problems. As components recombination is a very efficient source of innovation that firms widely resort to, the capability to recombine pieces of knowledge available in the organization or transferable from the outside becomes an important lever in the technological innovation strategy of the firm. Here a conceptualization which considers technological innovation as an outcome of a change of either the technological components or a diverse combination of the components themselves is adopted. Data relative to granted patents were considered. The assumption is that every patent is the outcome of the combination of a number of technological components associated to the sub-classes of the classification standard adopted. These sub-classes can be indirectly utilized to observe the search and the dynamics of technological innovation strategies. The sample includes 438 patents granted between 1975 and 2004 to 15 leading firms in the optical memory devices industry. The Fleming familiarity and Herfindahl concentration indexes are calculated to analyse innovation strategies.

Summary form only given as follows. This paper has two objectives. First, we present a method for constructing cognitive maps based on the analysis of natural language and a fuzzy representation of fuzzy propositions. Second, we apply this method to study how new knowledge is created during new product development.

This paper presents the findings of a study aimed at investigating the influence that some factors describing the cognitive, social and management environment during technical problem-solving have on the generation of new knowledge in small manufacturing firms. Ninety-one cases of technical problem-solving occurred during product innovation within 35 small firms were studied. From the literature and a multiple case study analysis, the authors identified a set of factors affecting learning which were ranked by order of influence. In that analysis, they considered each factor as affecting learning independently of the others. Here, they remove the simplifying hypothesis that these factors are independent and consider the contingent effect of the learning frame in which technical problem-solving occurs. The learning frame is defined by the factors that more critically influence learning. From, their study it emerges that the learning patterns differ accordingly to different learning frames and some factors that foster learning within a specific frame can inhibit it within a diverse frame.

This paper presents the findings of an empirical study aimed at investigating the influence that some factors describing the context pattern perceived by individuals and some other factors shaping the problem solving style have on the generation of new knowledge during technical problem-solving in small manufacturing firms. In a previous study, these factors were identified. Here the effect that the fit between the first and the second group of factors has on the amount and type of knowledge generated during technical problem-solving is explored. Two relevant findings emerge from the statistical analysis of data: (1) different context patterns are more conducive than others to learning (in the study learning and the generation of knowledge are used as synonymous); (2) there exists some fit between context pattern and problem-solving style, as some practices and behaviors adopted during technical problem-solving are more effective than others in some context patterns. Ninety-one cases of technical problem-solving occurred during product innovation within 35 small firms which were studied.