IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Group Support Systems as Tools for HR Decision Making

Group Support Systems as Tools for HR Decision Making
View Sample PDF
Author(s): James Yao (Montclair State University, USA)and John Wang (Montclair State University, USA)
Copyright: 2009
Pages: 9
Source title: E-Collaboration: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Ned Kock (Texas A&M International University, USA)
DOI: 10.4018/978-1-60566-652-5.ch044

Purchase

View Group Support Systems as Tools for HR Decision Making on the publisher's website for pricing and purchasing information.

Abstract

In the late 1960s, a new type of information system came about: model-oriented DSS or management decision systems. By the late 1970s, a number of researchers and companies had developed interactive information systems that used data and models to help managers analyze semistructured problems. These diverse systems were all called decision support systems (DSS). From those early days, it was recognized that DSS could be designed to support decision-makers at any level in an organization. DSS could support operations, financial management, and strategic decision making. Group decision support systems (GDSS) which aim at increasing some of the benefits of collaboration and reducing the inherent losses are interactive information technology-based environments that support concerted and coordinated group efforts toward completion of joint tasks (Dennis, George, Jessup, Nunamaker, & Vogel, 1998). The term group support systems (GSS) was coined at the start of the 1990s to replace the term GDSS. The reason for this is that the role of collaborative computing was expanded to more than just supporting decision making (Patrick & Garrick, 2006). For the avoidance of any ambiguities, the latter term shall be used in the discussion throughout this article. Human resources (HR) are rarely expected like other business functional areas to use synthesized data because HR groups have been primarily connected with transactional processing of getting data into the system and on record for reporting and historical purposes (Dudley, 2007). For them soft data do not win at the table; hard data do. Recently, many quantitative or qualitative techniques have been developed to support human resource management (HRM) activities, classified as management sciences/operations research, multiattribute utility theory, multicriteria decision making, ad hoc approaches, and human resource information systems (HRIS) (Byun, 2003). More importantly, HRIS can include the three systems of expert systems (ES), decision support systems (DSS), and executive information systems (EIS) in addition to transaction processing systems (TPS) and management information systems (MIS) which are conventionally accepted as an HRIS. As decision support systems, GSS are able to facilitate HR groups to gauge users’ opinions, readiness, satisfaction, and so forth, increase their HRM activity quality, and generate better group collaborations and decision makings with current or planned HRIS services. Consequently, GSS can help HR professionals exploit and make intelligent use of soft data and act tough in their decision-making process.

Related Content

Prasanna Ranjith Christodoss, Rajesh Natarajan. © 2022. 14 pages.
K. Uday Kiran, Gowtham Mamidisetti, Chandra shaker Pittala, V. Vijay, Rajeev Ratna Vallabhuni. © 2022. 12 pages.
Amalraj Irudayasamy, Prasanna Ranjith Christotodoss, Rajesh Natarajan. © 2022. 20 pages.
Koppula Srinivas Rao, S. Saravanan, Kasula Raghu, V. Rajesh, Pattem Sampath Kumar. © 2022. 15 pages.
Swapna B., Arulmozhi P., Kamalahasan M., Anuradha V., Meenaakumari M., Hemasundari H., Aathilakshmi T.. © 2022. 21 pages.
Archana K. S., Sivakumar B., Siva Prasad Reddy K.V, Arul Stephen C., Vijayalakshmi A., Ebenezer Abishek B.. © 2022. 15 pages.
Swapna B., M. Kamalahasan, S. Gayathri, S. Srinidhi, H. Hemasundari, S. Sowmiya, S. Shavan Kumar. © 2022. 12 pages.
Body Bottom