Abstract
Studies indicate that mergers and acquisitions are characterized by a high failure rate, often attributed to an inability on the part of the acquiring firm management to effectively evaluate potential acquisition candidates. This is not surprising given the considerable uncertainties surrounding both the relationships among factors in the evaluation process and also in the assessment of evidence. This paper develops a conceptual framework for acquisition and merger decisions using evidential reasoning approach under the belief function framework. It seeks to illustrate how expert knowledge of relevant factors can be mapped and how an evidential network can be used by decision makers to incorporate uncertainties in the evidence. Also highlighted is the fact that the nature and extent of evidence that needs to be collected depends on the rules assumed to govern relationships among input variables. Implications for theory and practice are discussed.
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References
Lajoux, A.R. and J. F. Weston (1998). Do deals deliver on postmerger performance? Mergers and Acquisitions, 33 (2), pp. 34 - 37.
Ravenscraft, D.J. and F.M. Scherer (1989). The profitability of mergers, International Journal of Industrial Organization, 7, pp. 101-116..
Datta, D.K., V.K. Narayanan and G.E. Pinches (1992). Factors Influencing Wealth Creation in Mergers and Acquisitions: A Meta-analysis’, Strategic Management Journal, 13 (1), pp. 67 - 84.
Datta, D.K., and G. Puia (1995). Cross-border acquisitions: An examination of the influence of strategic and cultural fit on shareholder value creation in U.S. acquiring firms’. Management International Review, 35 (4), pp. 325 - 336.
Achtmeyer, W.F., and M.H. Daniell (1988). How advanced planning widens acquisition rewards Mergers and Acquisitions, 23, pp. 37 - 42.
Rappaport, A. (1979). Strategic analysis for more profitable acquisitions. Harvard Business Review, 57, pp. 99 - 110.
Reilly, R.F. (1982). Planning for an Acquisition Strategy. Managerial Planning, 30 (5), pp. 36 - 42.
Curley, S. P., and J. I. Golden (1994). Using belief functions to represent degrees of belief. Organizational Behavior and Human Decision Processes 58 (2), pp. 271 - 303.
Harrison, K. (1999). Evaluation and Aggregation of Audit Evidence under Uncertainty: An Empirical Study of Belief Functions. Ph.D. Dissertation, School of Business, University of Kansas.
Cohen, P. R. (1987). The control reasoning under uncertainty: A discussion of some programs, The Knowledge Engineering Review, Cambridge University Press.
Duda, R. O., P. E. Hart, and N. J. Nilsson (1976). Subjective Bayesian Methods For Rule-Based Inference Systems, Proceedings National Computer Conference (AFIPS), 15.
Lauritzen, S. L., and Spiegelhalter, D. J. (1988). Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems (with discussion), Journal of the Royal Statistical Society, series B, 50 (2), pp. 157 - 224.
Pearl, J. (1988). Bayesian and Belief-Functions Formalisms for Evidential Reasoning: A Conceptual Analysis, Proceedings of the 5th Israeli Symposium on Artificial Intelligence, Tele-Aviv.
Shenoy, P. P. and G. Shafer (1990). Axioms for Probability and Belief- Function Propagation, in Uncertainty in Artificial Intelligence, Elsevier Science Publishers.
Andersen, S. K., K. G. Olsen, F. V. Jensen, and F. Jensen (1989). HUGIN A Shell for Building Bayesian Belief Universes for Expert Systems, Proceedings of the Tenth International Joint Conference on Artificial Intelligence.
Saffiotti, A, and E. Umkehrer (1991). Pulcinella: A General Tool for Propagating Uncertainty in Valuation Networks, Proceedings of the Seventh National Conference on Artificial Intelligence, University of California, Los Angeles, pp. 323 - 331.
Shafer, G., P. P. Shenoy, and R. P. Srivastava (1988). AUDITOR’S ASSISTANT: A Knowledge Engineering Tool For Audit Decisions, Proceedings of the 1988 Touche Ross University of Kansas Symposium on Auditing Problems.
Zarley, D., Y.-T. Hsia, and G. Shafer (1988). Evidential Reasoning using DELIEF, Proceedings of the National Conference of Artificial Intelligence.
Srivastava, R.P., S.K. Dutta, and R. Johns (1996). An Expert System Approach to Audit Planning and Evaluation in the Belief-Function Framework, International Journal of Intelligent Systems in Accounting, Finance and Management.
Rappaport, A. (1988) Calculating the value-creation potential of a deal. Mergers and Acquisitions, 33 (1), pp. 33 - 44.
Roll, R. (1986). The Hubris Hypothesis of Corporate Takeovers. Journal of Business, 59, pp. 197 - 216.
Barney, J.B. (1995). Gaining and Sustaining Competitive Advantage, Reading, MA: Addison-Wesley.
Markides, C. and P.J. Williamson. (1994). Related Diversification, Core Competencies and Corporate Performance, Strategic Management Journal, 15, pp. 149 - 165.
Porter, M. (1980). Competitive Strategy. New York: Free Press.
Scherer, F.M. (1980). Industrial Market Structure and Economic performance, Chicago: Rand McNally.
Lisle, C. and J. Bartlam (1999). Can the target pass the competitive intelligence test? Mergers & Acquisitions, 33 (4), pp. 27 - 32
Wernerfelt, B. and C.A. Montgomery (1986). What is an attractive industry? Management Science, 32 (10).
Hitt, M.A., R. Hoskisson and D. Ireland (1990). Mergers and Acquisitions and Managerial Commitment to Innovation in M-Form Firms, Strategic Management Journal, 11, pp. 29 - 47
Porter, M.E. (1985). Competitive Advantage: Creating and sustaining superior performance, New York: Free Press.
Porter, M.E. (1987). From competitive advantage to corporate strategy. Harvard Business Review, 65 (3), pp. 43 - 59.
Bielinski, D.W. (1992). Putting a realistic dollar value on acquisition synergies, Mergers and Acquisitions, November-December, pp. 9 - 12.
Datta, D.K. (1986). Assimilation of Acquired Organizations: An Empirical Assessment of the Impact of Selected Organizational and Behavioral Factors on Acquisition Performance, Unpublished Doctoral Dissertation, University of Pittsburgh.
Jensen, M.C. and R.S. Ruback (1983). The Market for Corporate Control: The Scientific Evidence, Journal of Financial Economics, 11, pp. 5 - 50.
Salter, M.S., and W.A. Weinhold (1979). Diversification through acquisitions: Strategies for creating economic value, New York: The Free Press.
Singh, H. and C. Montgomery (1987). Corporate acquisition strategies and economic performance, Strategic Management Journal, 8, pp. 377-386.
Sirower, M.L. (1997). The Synergy Trap: How Companies Lose in the Acquisition game. New York; The Free Press.
Datta, D.K. (1991). Organizational Fit and Acquisition Performance: Effects of Post-Acquisition Integration, Strategic Management Journal, 12 (4), pp. 281 - 298.
Datta, D.K. and J.H. Grant (1990). The relationship between type of acquisition, the autonomy given to the acquired firm and acquisitions success: An empirical analysis, Journal of Management, 16 (1), pp. 2944.
Jemison, D.B. and S.B. Sitkin (1986). Corporate Acquisitions: A Process perspective, Academy of Management Review, 11 (1), pp. 145 - 163.
Slowinski, G. (1992). The human touch in successful strategic alliances, Mergers and Acquisitions, 27 (1), pp. 44 - 47.
Marks, M.L. (1999). Adding cultural fit to your diligence checklist, Mergers and Acquisitions, 34 (3), pp. 14 - 20.
Buono, A.F., Bowditch, J.L., and J.W. Lewis (1985). When cultures collide: The anatomy of a merger, Human Relations, 38 (5), pp. 477 - 500.
Srivastava, R. P., and K. O. Cogger (1995). Algorithm for Converting Beliefs on Individual Variables from a Single Source of Evidence to m-values on the Joint Space, Working Paper, School of Business, The University of Kansas.
Smets, P. (2001). Decision making in a Context where Uncertainty is Represented by Belief Functions. Belief Functions in Business Decisions. Edited by R. Srivastava and T. Mock. Springer-Verlag, Inc (forthcoming).
Smets, P. (1990a). The Combination of Evidence in the Transferable Belief Model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12, 5 (May).
Smets, P. (1990b). Constructing the Pignistic Probability Function in a Context of Uncertainty. Uncertainty in Artificial Intelligence 5. ed. by Henrion, M., Shachter, R.D., Kanal, L.N., and Lemmer, J.F. North-Holland: Elsevier Science Publishers B. V.
Smets, P. (1998). The Transferable Belief Model For Quantified Belief Representation. Quantified Representation for Uncertainty and Imprecision, Vol. 1. Edited by P. Smets. Kluwer Academic Publishers
Shafer, G. (1976). AMathematical Theory of Evidence, Princeton University Press.
Yager, R. R, J. Kacprzyk, and M. Fedrizzi. (1994). Advances in the Dempster-Shafer Theory of Evidence, John Wiley & Sons, New York, NY
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Srivastava, R.P., Datta, D.K. (2002). Evaluating Mergers and Acquisitions: A Belief Function Approach. In: Srivastava, R.P., Mock, T.J. (eds) Belief Functions in Business Decisions. Studies in Fuzziness and Soft Computing, vol 88. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1798-0_8
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DOI: https://doi.org/10.1007/978-3-7908-1798-0_8
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