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Authors: Silverio Petruzzellis 1 ; Oriana Licchelli 2 ; Ignazio Palmisano 2 ; Giovanni Semeraro 2 ; Valeria Bavaro 3 and Cosimo Palmisano 3

Affiliations: 1 Cézanne Software S.p.A., Italy ; 2 Università di Bari, Italy ; 3 DIMeG, Politecnico di Bari, Italy

Keyword(s): Decision Support Systems, Knowledge Management, Machine Learning, HRM Decentralization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Industrial Applications of Artificial Intelligence ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Strategic Decision Support Systems ; Verification and Validation of Knowledge-Based Systems ; Web Information Systems and Technologies

Abstract: Total reward management (TRM) is a holistic practice that interprets the growing need in organizations for involvement and motivation of the workers. It is oriented towards pushing the use of Information Technology in supporting the improvement of both organization and people performances, by understanding employee needs and by designing customized incentives and rewards. Customization is very common in the area of e-commerce, where application of profiling and recommendation techniques makes it possible to deliver personalized recommendations for users that explicitly accept the site to store personal information such as preferences or demographic data. Our work is focused on the application of User Profiling techniques in the Total Reward Management context. In the Team Advisor project we experimented the analogies Customer/Employee, Product, Portfolio/Reward Library and Shop/Employer, in order to provide personalized reward recommendations to line managers. We found that the adopt ion of a collaborative software platform delivering a preliminary reward plan to the managers fosters collaboration and actively supports the delegation of decision-making. (More)

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Paper citation in several formats:
Petruzzellis, S.; Licchelli, O.; Palmisano, I.; Semeraro, G.; Bavaro, V. and Palmisano, C. (2006). PERSONALIZED INCENTIVE PLANS THROUGH EMPLOYEE PROFILING. In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-42-9; ISSN 2184-4992, SciTePress, pages 107-114. DOI: 10.5220/0002493401070114

@conference{iceis06,
author={Silverio Petruzzellis. and Oriana Licchelli. and Ignazio Palmisano. and Giovanni Semeraro. and Valeria Bavaro. and Cosimo Palmisano.},
title={PERSONALIZED INCENTIVE PLANS THROUGH EMPLOYEE PROFILING},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2006},
pages={107-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002493401070114},
isbn={978-972-8865-42-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - PERSONALIZED INCENTIVE PLANS THROUGH EMPLOYEE PROFILING
SN - 978-972-8865-42-9
IS - 2184-4992
AU - Petruzzellis, S.
AU - Licchelli, O.
AU - Palmisano, I.
AU - Semeraro, G.
AU - Bavaro, V.
AU - Palmisano, C.
PY - 2006
SP - 107
EP - 114
DO - 10.5220/0002493401070114
PB - SciTePress