NDLI: The fit between problem solving style and perceived problem complexity as a major determinant of knowledge generation during product innovation: empirical evidence and implications for a theory of learning

Content Provider	IEEE Xplore Digital Library
Author	lo Storto, C.
Copyright Year	2001
Description	Author affiliation: Dept. of Economic & Manage. Eng., Naples Univ., Italy (lo Storto, C.)
Abstract	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.
Starting Page	291
Ending Page	302
File Size	1174294
Page Count	12
File Format	PDF
ISBN	1890843067
DOI	10.1109/PICMET.2001.952028
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Portland Int. Conf. on Management of Eng. And Tech
Subject Keyword	Problem-solving Technological innovation Innovation management Knowledge engineering Pulp manufacturing Knowledge management Engineering management Statistical analysis Research and development Character generation
Content Type	Text
Resource Type	Article

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