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The likelihood of success in management intelligence systems: building a consultant advisory system

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thesis
posted on 26.10.2010, 09:13 by Morteza Seyed Forghani
Management Intelligence Systems are a class- of Decision Support Systems aimed at providing intelligence about an ill-structured decision to a decision-maker. The research objective was to build a 'Consultant Advisory System', a computerised model of success, to assist internal consultants in, assessing the likelihood of success for a Management Intelligence System (MINTS). The system would also be capable of allowing the consultant to identify reasons which might lead to a low likelihood of success, so that corrective action can be taken. The approach taken is different from many other studies which have concentrated on the success of a computer-based information system after implementation, rather than assessing success throughout the whole process of initiating, developing and implementing such systems. The research has been based on a detailed survey of the literature on Management Information systems (MIS), and Decision Support Systems (DSS) and 39 field investigations involving detailed interviews with the key actors involved in a MINTS project. Two phases of MINTS development were identified: (A) ensuring a right environment and (B) maintaining relationships. About 280 factors were distilled as significant for the successful development of a MINTS and these have been incorporated in a computerised advisor. Validation of MINTS in general and the advisor in particular is discussed in detail.

History

School

  • Business and Economics

Department

  • Business

Publisher

© Morteza Seyed Forghani

Publication date

1989

Notes

A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.

EThOS Persistent ID

uk.bl.ethos.262686

Language

en