- Full Description
India is becoming the 'global back office' to international supply chains, creating a substantial communications and decision-support infrastructure for large and small enterprises in the global market place to utilize these resources. Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: (1) the emerging enterprise decision making processes and technologies; (2) decision making in uncertain, changing conditions; (3) the changing infrastructure in organizations and society; (4) the expanding role of web technologies; and (5) emerging theories and practices for managing knowledge and making decisions.
- Table of Contents
Table of Contents
- Overview: concepts, theories, and frameworks.
- Understanding decision support systems for global enterprises.
- Sources of unstructuredness in decision situations.
- Critical success factors for implementing of business intelligence systems.
- Support for collaborative and distributed decision making.
- Management of knowledge transfer in distributed software organizations.
- Meeting challenges: empirical studies.
- A longitudinal study of information exchange in computer
- mediated and face
- face groups.
- The email strategy investigation model (eSIM).
- Effects of knowledge management capabilities on perceived performance.
- Using social choice rule sets in multiple attribute decision making for information system selection.
- Individual’s response to security messages.
- An analysis of ERP decision making practice and consequences for subsequent system life cycle stages.
- SCOLDSS – a decision support system for the planning of solid waste collection.
- Evolving technologies: next generation systems.
- Semantic web technologies for enhancing intelligent DSS environments.
- Towards a unified representation framework for modelbases and databases.
- A multi
- attribute auction format for procurement with limited disclosure of buyer’s preference structure.
- A generic model of self
- incrementing knowledge
- based decision support system using the Bolzmann Machine.
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