Network Mechanisms and Informationally Efficient            Hierarchies:  Collaborative Research (Computer and          Information Science)
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{'SignBlockName': 'Lawrence Rosenblum', 'PO_EMAI': None, 'PO_PHON': None}
This is collaborative research with Stefan Reichelstein                    at Stanford University (Grant 8704065).  The research                           concerns the design of efficient organizational schemes.  In                    particular, it considers the comparative advantages of                          hierarchical arrangements. The authors posit a group of                         agents who are to take actions in a changing environment.                       The joint action has to meet a performance standard, i.e., it                   has to lie in a set that depends on the environment.  Each                      member observes some component of the actual environment and                    chooses her action after receiving messages from others.  A                     network mechanism prescribes messages sent and actions taken                    and may be hierarchical.  A network mechanism is efficient if                   it satisfies the performance standard and no other mechanism                    does so at a smaller informational cost.  Cost is measured by                   the size of the set of messages that agents can send or                         receive.                                                                             General techniques for constructing efficient mechanisms                   have been applied to a multi-plant firm example and an                          exchange-economy example.  The broader significance of this                     work is that it seeks to generalize these results to find                       those basic properties of performance standards that make                       hierarchies efficient.  In the same context the researchers                     study: (1) dynamic issues, i.e., the number of steps until                      actions are obtained; (2) reward structures, i.e., contracts                    among the group's agents, so that hierarchies can be examined                   in light of the incentive problems; and (3) promising links                     to the "communication complexity" literature in computer                        science.
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