Efficient organization of collective data processing


Type Research Project

Duration Feb. 1, 1999 - Oct. 31, 1999

  • Economic and Social Geography (theoratical and applied) AE (Former organization)

Tags

Press 'enter' for creating the tag
 

Abstract (German)

The project aims to analyse the application of the concept of economic efficiency to organisational issues of collective information processing in decision making. Information processing is modelled in the framework of the dynamic parallel-processing model of associative computation with an endogenous set-up cost of the processors. The model is extended to include the specific features of collective information processing in the team of decision makers which could cause an error in data analysis. In such a model, the conditions for efficient organisation of information processing are defined and the architecture of the efficient structures is considered. We show that specific features of collective decision making procedures require a broader framework for judging organisational efficiency than has traditionally been adopted. In particular, and contrary to the results presented in economic literature, we show that in human data processing (unlike in computer systems), there is no unique architecture for efficient information processing structures, but a number of various efficient forms can be observed. The results indicate that technological progress resulting in faster data processing (ceteris paribus) will lead to more regular information processing structures. However, if the relative cost of the delay in data analysis increases significantly, less regular structures could be efficient.


Abstract (English)

The project aims to analyse the application of the concept of economic efficiency to organisational issues of collective information processing in decision making. Information processing is modelled in the framework of the dynamic parallel-processing model of associative computation with an endogenous set-up cost of the processors. The model is extended to include the specific features of collective information processing in the team of decision makers which could cause an error in data analysis. In such a model, the conditions for efficient organisation of information processing are defined and the architecture of the efficient structures is considered. We show that specific features of collective decision making procedures require a broader framework for judging organisational efficiency than has traditionally been adopted. In particular, and contrary to the results presented in economic literature, we show that in human data processing (unlike in computer systems), there is no unique architecture for efficient information processing structures, but a number of various efficient forms can be observed. The results indicate that technological progress resulting in faster data processing (ceteris paribus) will lead to more regular information processing structures. However, if the relative cost of the delay in data analysis increases significantly, less regular structures could be efficient.

Publications

Classification

  • 5322 National/Political economy (Details)
  • 5335 Political economic theory (Details)
  • 5618 Regional economy (Details)

Expertise

  • organization
  • efficiency
  • data processing