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J PROD INNOV MANAG 1‘?89:6:297-110
me Relationship of Creativity and Life ACcoma&, David T. Morse and Joe Khatena, The Journal of Creative Behavior (First Quarter 19891, pp. 59-65 For many years we have known that there are strong correlations between a person’s creativity and that person’s statements about biographical experience. That is. one common test asks a respondent to indicate life patterns, and that has been used to predict creativity. However, there has been no test of how well a person’s biographical report agrees with actual life experiences. independently determined. That is, do life experiences in fact also correlate with creativity? This study involved participants at a problemsolving instit&te sponsored by State University at Buffalo. First, a sample of these people filled out the customary form for measurement of actual creativity and for self-report of life productions. Second, they reported on their perceptions of their own creativity. Third, the authors gathered actual life data on the respondents by studying their biographies, apart from the respondents themselves. Ideally, it would be nice if the subjects turned out to be more creative than average (since they came to a professional creativity conference), reported themselves as productive in actual creative work, scored themselves as creative and had a biographical statement that also was judged to be heavier than average in creative accomplishments. Most of this was correct. The subjects were indeed more creative than average norms for their population group. Second, their own life reports correlated with their actual creativity. (These were the two conditions historically felt to be so.) -4nd when the authors studied biographies, the more creative people in fact have such records. For this they used eight categories: jobs, groups joined. leadership, colleague of a leading creativity association. an artistic endeavor, a music endeavor, another performing arts endeavor and an actual production in any of these three areas. These actual biographies did indeed correlate with each person’s creativity as shown ot the first battery of tests. However, there *was no correlation between each individual’s reported creativity and that shown by the tests or the
ABSTRACTS
biographical data. Pure self-claims of creativity continue inaccurate, while the lifetime trail not only does indicate creativity but can be determined by self-reporting without having to access personal biographies. The test used for this is the Khatena-Torrance Creative Perception Inventory. Rethinking the Product Portfolio: A Generalized Investment Model, Timothy M. Devinney and David W. Stewart, Management Science (September 1988), pp. 1080-1095 (TE) Among the more vexing problems of a business organization are decisions relating to the optimal allocation of resources among competing investment opportunities. These decisions include, but are not limited to, new product or product line development decisions, product or product line extension decisions, the allocation of R&D among competing products and decisions to discontinue a product or product line. In marketing and strategic management, investment opportunity decisions are usually resolved through the use of well-known portfolio models such as the BCG growth/share matrix approach, while in finance the more traditional present value ctiteria are employed. There has been little attempt at integrating these two approaches, leaving the interaction between the marketing manager’s portfolio analysis and the financial officer’s present value analysis ad hoc. This article provides an interesting integration of financial portfolio theory with product portfolio decisions. Using the Capital Asset Pricing Model (CAPM) of finance, this article provides a theoretical structure for how a firm’s product decisions affect both profitability and the market risk of the firm along with a practical method for implementing their theory. Products can be shown to fall into one of three categories based on demand and the nature of production. 9n the demand side, products can be defined as complements, substitutes and neulers. Demar?ci complements are products which possess a positive demand relationship. If t mand for one product increases, the demand for the other will increase as well. A classic example is the case of the computer software and hardware. Demand substitutes are products for which demand is negatively related. When the demand