Forming Enterprise Recruitment Pattern Based on Problem-Oriented Conceptual Model

Authors: Alamro, S., Dogan, H. and Phalp, K.

Journal: Procedia Computer Science

Publisher: Elsevier

This data was imported from Scopus:

Authors: Alamro, S., Dogan, H. and Phalp, K.

Journal: Procedia Computer Science

Volume: 64

Pages: 298-305

eISSN: 1877-0509

DOI: 10.1016/j.procs.2015.08.493

© 2015 The Authors. Published by Elsevier B.V. Technological advances combined with the tightest labor market have led many organizations to change the range of tactics used to recruit new talent. Recruitment patterns can help analysts to tackle repetitive and piecemeal recruitment problems. However, they have been criticized for being applied in isolation and not easy to integrate. Therefore, enterprise recruitment pattern is recommended when building recruitment systems. When defining such pattern, support from enterprise recruitment architectures (ERAs) is needed to facilitate the reuse of that pattern in different recruitment development processes. For this reason, we present a problem-oriented conceptual model developed by the authors with the purpose of addressing the key architectural elements of the recruitment system, as well as their interdependence, in a high level of abstraction. The essence of the model is that when such architectural elements and their relationships are combined in a coherent manner, enterprise recruitment patterns can be formed based on this. The pattern here is defined by using a template where its elements correspond to the elements of the ERA depicted in the conceptual model. Our approach is demonstrated via application to an exemplar.

This data was imported from Web of Science (Lite):

Authors: Alamro, S., Dogan, H. and Phalp, K.

Journal: CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS/INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT/CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES, CENTERIS/PROJMAN / HCIST 2015

Volume: 64

Pages: 298-305

ISSN: 1877-0509

DOI: 10.1016/j.procs.2015.08.493

The data on this page was last updated at 04:51 on November 17, 2018.