Decision Support Systems and Electronic Commerce

ISSN: 0167-9236
Imprint: NORTH-HOLLAND

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Impact Factor: 1.119
Issues per year: 8

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Decision Support Systems welcomes contributions on the concepts and operational basis for DSSs, techniques for implementing and evaluating DSSs, DSS experiences, and related studies. In treating DSS topics, manuscripts may delve into, draw-on, or expand such diverse areas as artificial intelligence, cognitive science, computer supported ... click here for full Aims & Scope

Decision Support Systems welcomes contributions on the concepts and operational basis for DSSs, techniques for implementing and evaluating DSSs, DSS experiences, and related studies. In treating DSS topics, manuscripts may delve into, draw-on, or expand such diverse areas as artificial intelligence, cognitive science, computer supported cooperative work, data base management, decision theory, economics, linguistics, management science, mathematical modeling, operations management psychology, user interface management systems, and others. The common thread of articles published in the journal will be their relevance to theoretical, technical DSS issues.

Authors planning to submit papers to the journal should ensure that their work is relevant to the topics normally considered to be part of the field of decision support systems.

The Journal's research papers tend to fall into the following six topic departments:

1. DSS Foundations. e.g. DSS principles, concepts, and theories; frameworks, formal languages, and methods for DSS research; tutorials about the nature of DSS; assessments of the DSS field.

2. DSS Development-Functionality. e.g. methods, tools, and techniques for developing the underlying functional aspects of a DSS; solver/model management; data management in DSSs; rule management and AI in DSSs; coordinating a DSS's functionality within its user interface.

3. DSS Development-Interfaces. e.g. methods, tools, and techniques for developing the overt user interface of a DSS; managing linguistic, presentation, and user knowledge in a DSS; DSS help facilities; coordinating a DSS's interface events with its functionality events.

4. DSS Impacts and Evaluation. e.g. DSS economics; DSS measurement; DSS impacts on individual users, multiparticipant users, organizations, and societies; evaluating/justifying DSSs.

5. DSS Reference Studies. e.g. reference discipline tutorials for DSS researchers; emerging technologies relevant to DSS characteristics or DSS development; related studies on such topics as communication support systems, computer supported cooperative work, negotiation support systems, research support systems, task support systems.

6. DSS Experiences, Management, and Education. e.g. experiences in developing or operating DSSs; systems solutions to specific decision support needs; approaches to managing DSSs; DSS instruction/training approaches.

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Recent | Top 10 Cited | Most Downloaded

Fri Dec 26 09:47:01 GMT 2008

1. Semantic Web Constraint Language and Its Application to an Intelligent Shopping Agent
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 25 December 2008
   Hak-Jin, Kim , Wooju, Kim , Myungjin, Lee
   
   
   
   Semantic Web society was initially focused only on data, but then gradually moved toward knowledge. If a vision of the Semantic Web is to enhance humans' decision-making assisted by machines, a missing but important part is knowledge about constraints on data and concepts represented by ontology. This paper proposes a Semantic Web Constraint Language (SWCL) based on OWL, and shows its effectiveness in representing and solving an internet shopper's decision-making problems by implementing a shopping agent in the Semantic Web environment.
2. Software Project Effort Estimation with Voting Rules
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 24 December 2008
   Stefan, Koch , Johann, Mitlöhner
   
   Abstract: Social choice deals with aggregating the preferences of a number of voters into a collective preference. We will use this idea for software project effort estimation, substituting the voters by project attributes. Therefore, instead of supplying numeric values for various project attributes that are then used in regression or similar methods, a new project only needs to be placed into one ranking per attribute, necessitating only ordinal values. Using the resulting aggregate ranking the new project is a gain placed between other projects whose actual expended effort can be used to derive an estimation. In this paper we will present...
3. Editorial Board
   Publication year: 2009
   Source: Decision Support Systems, Volume 46, Issue 2, January 2009, Page IFC
   [No author name available]
4. Avatar e-mail versus traditional e-mail: Perceptual difference and media selection difference
   Publication year: 2009
   Source: Decision Support Systems, Volume 46, Issue 2, January 2009, Pages 451-467
   Younghwa, Lee , Kenneth A., Kozar , Kai R., Larsen
   
   The study investigates how knowledge workers perceive avatar e-mail differently from traditional e-mail, and how they select traditional versus avatar e-mail when different levels of task equivocality and different types of communication direction are present. Three field studies were conducted with knowledge workers who have used avatar and traditional e-mail. This study demonstrates that overall perception toward avatar e-mail is significantly different from traditional e-mail with respect to media richness and social presence characteristics. In addition, this study found individuals used different e-mail selection approaches when conducting tasks with different equivocality (high versus low equivocal tasks) and tasks for different...
5. Understanding Risk-taking Behavior of Groups: A "Decision Analysis" Perspective
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 24 December 2008
   Joseph S., Valacich , Saonee, Sarker , Jamie, Pratt , Mike, Groomer
   
   Past research has extensively investigated the effect of media, especially focusing on how anonymity increases risk-related behaviors of groups when using computer-mediated communication (CMC). This study extends prior research by examining the differences in group risk-taking behaviors between face-to-face groups and completely non-anonymous CMC groups (i.e., groups working in a fully identified, synchronous CMC environment similar to popular instant messaging systems utilized widely within organizations). Drawing on the "decision analysis" perspective, a key framework for understanding organizational decision-making, the study also examines the effects of the firm's risk preferences as well as the type of information distribution amongst group members...
6. Software Project Effort Estimation with Voting Rules
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 24 December 2008
   Stefan, Koch , Johann, Mitlöhner
   
   Abstract: Social choice deals with aggregating the preferences of a number of voters into a collective preference. We will use this idea for software project effort estimation, substituting the voters by project attributes. Therefore, instead of supplying numeric values for various project attributes that are then used in regression or similar methods, a new project only needs to be placed into one ranking per attribute, necessitating only ordinal values. Using the resulting aggregate ranking the new project is a gain placed between other projects whose actual expended effort can be used to derive an estimation. In this paper we will present...
7. Introducing functional classification theory to land use planning by means of decision tables
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 10 December 2008
   Frank, Witlox , Marc, Antrop , Peter, Bogaert , Philippe, De Maeyer , Ben, Derudder , ...
8. Classification Algorithm Sensitivity to Training Data with Non Representative Attribute Noise
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 3 December 2008
   Michael, Mannino , Yanjuan, Yang , Young, Ryu
9. Classification Algorithm Sensitivity to Training Data with Non Representative Attribute Noise
   Publication year: 2008
   Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 3 December 2008
   Michael, Mannino , Yanjuan, Yang , Young, Ryu
10. Visualized Cognitive Knowledge Map Integration for P2P Networks
    Publication year: 2008
    Source: Decision Support Systems, In Press, Accepted Manuscript, Available online 3 December 2008
    Fu-ren, Lin , Jen-Hung, Yu

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