TY - JOUR
T1 - Design and validation of a knowledge-based system for screening product innovations
AU - Ram, Sudha
AU - Ram, Sundaresan
N1 - Funding Information:
Manuscript received September 1, 1993; revised August 20, 1994, and March 11, 1995. This work was supported in part by a grant from the Marketing Science Institute, Cambridge, MA 02138 USA. Sudha Ram is with the Department of Management Information Systems, College of Business and Public Administration, University of Arizona, Tucson, AZ 85721 USA (e-mail: [email protected]). Sundaresan Ram is with the Department of World Business, American Graduate School of International Management, Glendale, AZ 85036 USA. Publisher Item Identifier S 1083-4427(96)01395-1.
PY - 1996
Y1 - 1996
N2 - Our research goal is to develop and validate an expert system that screens innovations prior to commercialization. This is an important research issue because business corporations are highly dependent on innovations for their growth and profitability, yet most corporations suffer from a high rate of new product failure. Few of the existing decision support systems have alleviated this problem, partly because of their inability to deal with nonmathematical (logical) relationships. An expert system for new product planning could save organizations tremendous amounts of resources (such as dollars, time and scientific talent) spent on product failures. The design of the proposed knowledge-based system is built upon our earlier work in this area [20]-[22]. We have addressed several critical research issues in the development of such a system: choice of the appropriate sources of knowledge, resolution of conflict among human experts chosen for knowledge acquisition, use of knowledge programming techniques that can accommodate uncertainty, and multiple methods of system validation. The research makes several contributions to marketing theory and practice. Most notably, the development of such systems contributes to effective product planning in organizations and enhances resource efficiency. Further, it generates guidelines for capturing and using expertise in highly unstructured decision-making situations such as product management.
AB - Our research goal is to develop and validate an expert system that screens innovations prior to commercialization. This is an important research issue because business corporations are highly dependent on innovations for their growth and profitability, yet most corporations suffer from a high rate of new product failure. Few of the existing decision support systems have alleviated this problem, partly because of their inability to deal with nonmathematical (logical) relationships. An expert system for new product planning could save organizations tremendous amounts of resources (such as dollars, time and scientific talent) spent on product failures. The design of the proposed knowledge-based system is built upon our earlier work in this area [20]-[22]. We have addressed several critical research issues in the development of such a system: choice of the appropriate sources of knowledge, resolution of conflict among human experts chosen for knowledge acquisition, use of knowledge programming techniques that can accommodate uncertainty, and multiple methods of system validation. The research makes several contributions to marketing theory and practice. Most notably, the development of such systems contributes to effective product planning in organizations and enhances resource efficiency. Further, it generates guidelines for capturing and using expertise in highly unstructured decision-making situations such as product management.
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U2 - 10.1109/3468.485747
DO - 10.1109/3468.485747
M3 - Article
AN - SCOPUS:0030108966
SN - 1083-4427
VL - 26
SP - 213
EP - 221
JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans.
IS - 2
ER -