Design Models for Hierarchical Organizations: Computation, Information, and Decentralization
Richard M. Burton, Borge Obel
Springer Science & Business Media, Sep 30, 1995 - Business & Economics - 279 pages
Design Models for Hierarchical Organizations: Computation, Information, and Decentralization provides state-of-the-art research on organizational design models, and in particular on mathematical models. Each chapter views the organization as an information processing entity. Thus, mathematical models are used to examine information flow and decision procedures, which in turn, form the basis for evaluating organization designs. Each chapters stands alone as a contribution to organization design and the modeling approach to design. Moreover, the chapters fit together and that totality gives us a good understanding of where we are with this approach to organizational design issues and where we should focus our research efforts in the future.
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aggregate problem algorithm allocation aspiration levels base-level Benders bounded rationality central unit common resources computation consider constraints convergence convergence tests coordination criterion Dantzig-Wolfe Dantzig-Wolfe decomposition decentralized decision makers decision process decision variables decomposition approaches directive iterative aggregation discussed divisions dual decomposition duality effort level equilibrium equs example example-scenarios feasible solution firm fuzzy Fuzzy Logic fuzzy sets headquarters hierarchical negotiation hierarchical planning incentive contracts information flow interaction iterative aggregation approaches Lagrangean level of spillovers linear programming lower bound M-form manager marginal cost master problem mathematical models mathematical programming Obel objective function objective function value Operations Research optimal solution organization organizational design organizational structure pack-size planning problem price directive primal principal-agent principal-agent problem probability of success product group Production Planning production quantities resource-class scenarios scheme situation solve stochastic student subproblem subunit tandem process theory tion top-level update upper bound upper problem