| 1. |
|
|
| 2. |
- Bednar, Peter, et al.
(författare)
-
Supporting Business Decision-making: One Professional at a Time
- 2014
-
Ingår i: DSS 2.0 – Supporting Decision Making with New Technologies. - 9781614993988 - 9781614993995 ; 261, s. 471-482
-
Bokkapitel (refereegranskat)abstract
- This paper discusses the potential for personalized, user-owned decision-support systems. It can be readily seen that there are benefits from analysis of ‘Big Data’ that could not be attained through more traditional means, e.g. insurance and credit card fraud can be detected more readily when it is possible to analyze integrated data across multiple servers owned and controlled by separate organizations. However, high-level data analysis, though useful, cannot be trusted to provide all the answers to organizational ‘questions’. Individuals need to be able to inform themselves in complex decision situations and for this purpose there can be no substitute for ‘little data’ from wherever this is to be drawn. We explore a potential type of support that could overcome the barriers to professional creativity arising through lack of trust in decision-support systems owned and controlled from senior management. The Virtual Personal Assistant described uses natural language processing to interact with a professional user in the context of messy, situated problems, and in private. It has capability to learn from user-interactions and therefore to co-evolve contextually. A ‘little data’ system such as this can therefore help to improve relevance of user understandings in a relatively risk free environment.
|
|
| 3. |
|
|
| 4. |
-
DSS 2.0 – Supporting Decision Making With New Technologies
- 2014
-
Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Advances in technology have resulted in new and advanced methods to support decision-making. For example, artificial intelligence has enabled people to make better decisions through the use of Intelligent Decision Support Systems (DSS). Emerging research in DSS demonstrates that decision makers can operate in a more timely manner using real-time data, more accurately due to data mining and 'big data' methods, more strategically by considering a greater number of factors, more precisely and inclusively due to the availability of social networking data, and with a wider media reach with video and audio technology. This book presents the proceedings of the IFIP TC8/Working Group 8. 3 conference held at the UniversitU Pierre et Marie Curie in Paris, France, in June 2014. Throughout its history the conference has aimed to present the latest innovations and achievements in Decision Support Systems. This year the conference looks to the next generation with the theme of new technologies to enable DSS2. 0. The topics covered include theoretical, empirical and design science research; case-based approaches in decision support systems; decision models in the real-world; healthcare information technology; decision making theory; knowledge management; knowledge and resource discovery; business intelligence; group decision support systems; collaborative decision making; analytics and aebig dataAE; rich language for decision support; multimedia tools for DSS; Web 2. 0 systems in decision support; context-based technologies for decision making; intelligent systems and technologies in decision support; organizational decision support; research methods in DSS 2. 0; mobile DSS; competing on analytics; and social media analytics. The book will be of interest to all those who develop or use Decision Support Systems. The variety of methods and applications illustrated by this international group of carefully reviewed papers should provide ideas and directions for future researchers and practitioners alike.
|
|
| 5. |
|
|
| 6. |
- Tona, Olgerta, et al.
(författare)
-
The Impact of the Organizing Vision on Mobile BI Adoption
- 2014
-
Ingår i: DSS 2.0 – Supporting Decision Making with New Technologies. - 0922-6389. - 9781614993988 ; 261, s. 303-313
-
Konferensbidrag (refereegranskat)abstract
- Mobile Business Intelligence (m-BI) enhances the capabilities of organizations to take decisions 'on-the-move'. M-BI emerged as an extension of BI and many companies have or are considering implementing it. Being an innovation, m-BI reflects an organizing vision, created by a broad community, which is prominent during the comprehension process of this innovation. Little is known how the organizing vision affects the decision to adopt a certain innovation, and moreover these studies are completely lacking within the m-BI area. A qualitative approach has been embraced and interviews with different organizations that have already decided to adopt m-BI have been conducted. This study revealed that industrial research reports, vendors marketing campaigns and success stories produced by the collaboration among vendors, analysts, journalist and early adopters have a strong influence on the early phases of the organizational decision-making process to adopt m-BI. Increasing internal and external legitimacy, reducing the risk to be left behind, gaining competitive advantage, following the footsteps of high-performing companies, increasing their prestige and reputation, are the main reasons for why organizations may start the decision-making process to adopt m-BI; all this under the umbrella of the organizing vision.
|
|
