Design Models for Hierarchical Organizations

Computation, Information, and Decentralization
Softcover Nachdruck of the original 1. Auflage 1995
ISBN: 978-1-4613-5964-7
Verlag: Springer US

Buch, Englisch, 279 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g

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.

Zielgruppe

Research

Autoren/Hrsg.

Obel, Børge

Burton, Richard M.

Fachgebiete

• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Mikroökonomie
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung

Inhaltsverzeichnis

Section 1: Mathematical Programming Models, Hierarchy and Decentralization.- Mathematical Contingency Modelling for Organizational Design: Taking Stock.- Design Insights from Alternative Decompositions.- Primal and Dual Decomposition as Organizational Design: Price and/or Resource Directive Decomposition.- Aggregation Approaches to Decentralized Planning Structures.- General Mathematical Programming Models in Multi-Level Planning.- Section 2: Hierarchical Planning Models.- A Conceptual Framework for Hierarchical Planning and Bargaining.- Hierarchical Negotiations.- Hierarchical Production Planning.- Section 3: Counterpoint; The Individual and the Emergent Structure.- The Emergence of Organizational Structures.- Technological Spillovers and Incentive Schemes for R&D.- Judging with Uncertainty in Diagnosis.