Organizational learning in production networks

Taudes, Alfred and Trcka, Michael and Lukanowicz, Martin (1999) Organizational learning in production networks. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 38. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.


Download (280kB)


If one accepts that a firm's behavior is determined by history-dependent capabilities that adapt in a goal-directed way one would like to know how a firm's organizational structure influences the way in which this distributed and partially tacit organizational memory evolves over time. In this paper, we study the impact that alternative information systems, incentive systems and modes of learning co-ordination have on the efficiency and generality of priority rules for job shop scheduling which are learnt by a network of production agents modeled by neural networks. When modeling the alternative organizational structures by different input layers, feedback and training methods, we find that efficient rules evolve when global incentives and synchronized learning are employed even if the system state is only partially known to an agent. However, organizational learning fails when it is performed asynchronously with local goals. (author's abstract)

Item Type: Paper
Keywords: PPS / Reihenfolgeproblem / organisatorisches Lernen
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 08 Mar 2002 09:51
Last Modified: 22 Oct 2019 00:41


View Item View Item


Downloads per month over past year

View more statistics