Abstract
The paper consists of two parts. The first part presents a new research methodology of a complex problem in business decision-making: determining the relative importance of the criteria for selecting a new product. This methodology facilitates providing recommendations for defining the relative importance of criteria and subcriteria for selecting a new product depending on the present situation in the company selecting a new product and its setting. In this manner is determined mutual dependence of the relative importance of criteria for selecting a new product on the company’s degree of success. For this reason, the whole procedure has a dynamic character, and it can be applied to various situations and at different moments of observation. Recommendations provided in this way represent the input data and support for subsequent multicriteria ranking of the alternatives for a new product.
The second part of the paper deals with the practical application and confirmation of the proposed methodology. In this part are presented the results of the research on the criteria and subcriteria for selecting a new product which are provided by applying the proposed methodology. The research showed that there is a clearly expressed mutual dependence between the importance of the criteria for selecting a new product and the company’s degree of success, and also that the observed dependence can be researched with the methodology which is presented in this paper. The obtained results have already been applied in practice and proved very useful and reliable.
The research refers to food industry and economic conditions in Serbia and Montenegro. However, this research methodology can also be applied — with certain alterations — to other industrial branches, and in conditions in economies with different levels of development. The proposed methodology is also important because of its universality, because it can also be applied to research on other problems and phenomena in management, with or without appropriate and respective adaptations.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Cooper, R.G., Kleinschmidt, E.J. (1987a). Success Factors in Product Innovation, Industrial Marketing Management, Vol. 16, Issue 3, pp. 215–223.
Cooper, R.G., Kleinschmidt, E.J. (1987b). New Products: What Separates Winners from Losers, Journal of Product Innovation Management, Vol. 4, Issue 3, pp. 169–184.
Farinwata, Sh.S., Filev, D., Langari, R. (editors) (2000). Fuzzy Control — Synthesis and Analysis, John Wiley and Sons, Chichester.
Henard, D.H., Szymanski, D.M. (2001). Why some new products are more successful than others, Journal of Marketing Research, Vol. 38, Issue 3, pp. 362–375.
Höppner, F., Klawonn, F., Kruse, R., Runkler, T. (1999). Fuzzy Cluster Analysis, John Wiley and Sons, New York.
Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making, Methods and Applications, A State-of-the-Art Survey, Lecture Notes in Economics and Mathematical Systems, Springer-Verlag, Berlin.
Larichev, O.I., Brown, R.V. (2000). Verbal and Numerical Decision Analysis: Comparison on Practical Tasks, XVth International Conference on Multiple Criteria Decision Making, Ankara.
Leskinen, P. (2000). Measurement, scales and scale independence in the analytic hierarchy process, Journal of Multi-Criteria Decision Analysis, Vol. 9, Issue 4, pp. 163–174.
Montoya-Weiss, M.M., Calantone, R. (1987). Determinants of New Products Performannce: A Review and Meta-Analysis, Journal of Product Innovation Management, Vol. 4, Issue 3, pp. 169–184.
Nikolić, M. (2004). Quantitative model for selecting a new product with research into relevant criteria, PhD thesis, University of Belgrade, Faculty of Mechanical Engineering, Belgrade.
Nikolić, M., Sajfert, Z. (2004). Widening of Saati’s scale for comparison of criteria in pairs, The 4th International Symposium On Intelligent Manufacturing Systems IMS’2004, Sakarya, Turkey.
Noghin, V.D. (1997). Relative importance of criteria: a quantitative approach, Journal of Multi-Criteria Decision Analysis, Vol. 6, Issue 6, pp. 355–363.
Parry, M.E., Song, X.M. (1994). Identifying New Product Successes in China, Journal of Product Innovation Management, Vol. 11, Issue 1, pp. 15–30.
Pedrycz, W., Gomide, F. (1998). An Introduction to Fuzzy Sets — Analysis and Design, A Bradford Book, Cambridge and Massachusetts Institute of Technology.
Podinovski, V.V. (2002). The quantitative importance of criteria for MCDA, Journal of Multi-Criteria Decision Analysis, Vol. 11, Issue l, pp. 1–15.
Royo, A.S., Verdegay, J.L. (2000). Coherence Measures on Finite Fuzzy sets, International Journal of Uncertanly, Fuzziness and Knowledge — Based Systems, Vol. 8, Issue 6, pp. 641–663.
Song, X.M., Sounder, W.E., Dyer, B. (1997). A Causal Model of the Impact of Skills, Synergy and Design Sensitivity on New Product performance, Journal of Product Innovation Management, Vol. 14, Issue 2, pp. 88–101
Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: A Comparative Study, Boston: Kluwer Academic Publishers.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Nikolić, M., Sajfert, Z. & Klarin, M. Impact of the degree of a company’s success on the importance of the criteria for selecting a new product. Oper Res Int J 7, 3–25 (2007). https://doi.org/10.1007/BF02941183
Issue Date:
DOI: https://doi.org/10.1007/BF02941183