Abstract
This paper considers the International Joint Ventures (IJVs) problem using interval-valued fuzzy sets and the compositional rule of inference in the statistical sense. We consider the performance effects of evaluation criteria facts and weights based on fuzzy set theory to determine the performance ranking among IJVs. Due to the lack of precise information based on some fuzzy language is used in the evaluation criterion.We use the statistical confidence-interval estimates and apply the signed distance method to defuzzify.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kaufmann, A., Gupta, M.M.: Introduction to Fuzzy Arithmetic Theory and Applications. Van Nostrand Reinhold, New York (1991)
Dang, T.: Ownership, Control and Performance of the Multinational Corporation. A study of US Wholly-owned Subsidiaries and Joint Ventures in the Philippines and Taiwan. Unpublished Doctoral Dissertation, University of California at Los Angeles, 1-28 (1977)
Franco, L.: Joint venture Survival in Multinational Corporations. Praeger, New York (1971)
Glaister, K.W., Buckley, P.J.: Performance Relationships in UK International Alliances. Management International Review 39(2), 123–147 (1999)
Gomes-Casseres, B.: Joint Venture Instability: Is it a problem? Columbia Journal of World Business 22(2), 97–102 (1987)
Good, L.: US Joint Ventures and Manufacturing Firms in Monterey, Mexico: Comparative styles of management. Unpublished doctoral dissertation, Cornell University (1972)
Harrigan, K.R.: Strategic Alliances and Partner Asymmetries. In: Contractor, F., Lorange, P. (eds.) Cooperative Strategies in International Business. Lexington, New York (1988)
Yao, J.-S., Wu, K.-M.: Ranking Fuzzy Numbers Based on Decomposition Principle and Signed Distance. Fuzzy Sets and Systems 116, 275–288 (2000)
Killing, P.: Strategies for Joint Venture Success. Praeger, New York (1983)
Kogut, B.: Joint Ventures: Theoretical and Empirical Perspective. Strategic Management Journal 9, 319–332 (1988)
Gorzalezany, M.B.: A Method of Inference in Approximate Reasoning Based on Interval – Valued Fuzzy Sets. Fuzzy Sets and Systems 21, 1–17 (1987)
Shieh, T.-S., Su, J.-S., Lee, H.-M.: Fuzzy Decision Making Performance Evaluation for International Joint Venture. ICIC Express Letters 3(4B), 1197–1202 (2009)
Zimmermann, H.-J.: Fuzzy Set Theory and Its Applications, 4th edn. Kluwer Academic Publishers, Boston (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, HM., Shih, TS., Su, JS., Lin, L. (2010). Fuzzy Decision Making for IJV Performance Based on Statistical Confidence-Interval Estimates. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6422. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16732-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-16732-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16731-7
Online ISBN: 978-3-642-16732-4
eBook Packages: Computer ScienceComputer Science (R0)