Inferring comprehensible business/ICT alignment rules
Inferring comprehensible business/ICT alignment rules
We inferred business rules for business/ICT alignment by applying a novel rule induction algorithm on a data set containing rich alignment information polled from 641 organisations in 7 European countries. The alignment rule set was created using AntMiner+, a rule induction technique with a reputation of inducing accurate, comprehensible, and intuitive predictive models from data. Our data set consisted of 18 alignment practices distilled from an analysis of relevant publications and validated by a Delphi panel of experts. The goal of our study was to describe practical guidelines for managers in obtaining better alignment of ICT investments with business requirements. Our obtained rule set showed the multi-disciplinary nature of B/ICT alignment. We discuss implication of the alignment rules for practitioners.
business/ict alignment, alignment rule set, data mining, artificial ant systems, practical guidelines
116-124
Cumps, Bjorn
5584734d-ccd7-422d-a008-6da855b96b33
Martens, David
42e7e141-fb3d-4ead-8e3a-96b39bab65f9
De Backer, Manu
9c56870f-a34a-4eba-87ef-137fec532349
Haesen, Raf
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Viaenea, Stijn
ead04318-fea5-4257-b6b4-c5704e3041e4
Dedene, Guido
de15fcda-ec48-47e2-bf1e-e882ab48061c
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Snoeck, Monique
9aee96bc-8a57-4c37-bcd7-e83f0b173ee1
March 2009
Cumps, Bjorn
5584734d-ccd7-422d-a008-6da855b96b33
Martens, David
42e7e141-fb3d-4ead-8e3a-96b39bab65f9
De Backer, Manu
9c56870f-a34a-4eba-87ef-137fec532349
Haesen, Raf
82a78c40-85f2-4d67-9b26-b3e66b7808e3
Viaenea, Stijn
ead04318-fea5-4257-b6b4-c5704e3041e4
Dedene, Guido
de15fcda-ec48-47e2-bf1e-e882ab48061c
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Snoeck, Monique
9aee96bc-8a57-4c37-bcd7-e83f0b173ee1
Cumps, Bjorn, Martens, David, De Backer, Manu, Haesen, Raf, Viaenea, Stijn, Dedene, Guido, Baesens, Bart and Snoeck, Monique
(2009)
Inferring comprehensible business/ICT alignment rules.
Information & Management, 46 (2), .
(doi:10.1016/j.im.2008.05.005).
Abstract
We inferred business rules for business/ICT alignment by applying a novel rule induction algorithm on a data set containing rich alignment information polled from 641 organisations in 7 European countries. The alignment rule set was created using AntMiner+, a rule induction technique with a reputation of inducing accurate, comprehensible, and intuitive predictive models from data. Our data set consisted of 18 alignment practices distilled from an analysis of relevant publications and validated by a Delphi panel of experts. The goal of our study was to describe practical guidelines for managers in obtaining better alignment of ICT investments with business requirements. Our obtained rule set showed the multi-disciplinary nature of B/ICT alignment. We discuss implication of the alignment rules for practitioners.
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Published date: March 2009
Keywords:
business/ict alignment, alignment rule set, data mining, artificial ant systems, practical guidelines
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Local EPrints ID: 80427
URI: http://eprints.soton.ac.uk/id/eprint/80427
ISSN: 0378-7206
PURE UUID: 330be5ba-50b5-4741-8a24-ddaf8806384b
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Date deposited: 24 Mar 2010
Last modified: 14 Mar 2024 02:49
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Author:
Bjorn Cumps
Author:
David Martens
Author:
Manu De Backer
Author:
Raf Haesen
Author:
Stijn Viaenea
Author:
Guido Dedene
Author:
Monique Snoeck
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