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Strategies of Product and Process Innovation: A Loglinear Analysis
Author(s) -
Calantone Roger J.,
Di Benedetto C. Anthony,
Meloche Martin S.
Publication year - 1988
Publication title -
randd management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.253
H-Index - 102
eISSN - 1467-9310
pISSN - 0033-6807
DOI - 10.1111/j.1467-9310.1988.tb00559.x
Subject(s) - log linear model , product (mathematics) , product innovation , econometrics , regression analysis , process (computing) , set (abstract data type) , relation (database) , mathematics , statistics , computer science , economics , industrial organization , linear model , data mining , geometry , programming language , operating system
Utterback and Abernathy (1975) developed a dynamic innovation model to explain the patterns of product and process innovation and to show which types of innovation would be most strategically appropriate for firms with particular objectives. In this paper the relation‐ships between type and/or source of innovation and a number of firm‐characteristic variables are examined. Loglinear regression is employed to determine the extent of the postulated relationships in a set of actual industry data on product innovation. The loglinear model provided results which were highly consistent with predictions made on the basis of previous research into product and process innovation.