-------- Weitergeleitete Nachricht -------- Betreff: [WI] CFP HICSS Minitrack: Organizational Issues of Business Intelligence, Business Analytics and Big Data Datum: Mon, 23 May 2016 07:10:35 +0000 Von: Barbara Dinter barbara.dinter@wirtschaft.tu-chemnitz.de Antwort an: Barbara Dinter barbara.dinter@wirtschaft.tu-chemnitz.de An: wi@aifb.uni-karlsruhe.de wi@aifb.uni-karlsruhe.de
[Apologies for cross-posting]
CFP HICSS minitrack: Organizational Issues of Business Intelligence, Business Analytics and Big Data
Track: Organizational Systems and Technology
50th Hawaii International Conference on System Sciences (HICSS-50), January 4-7, 2017 | Hilton Waikoloa Village, Hawaii
Minitrack focus:
The provision of the right data with appropriate quality according to the needs of decision makers or automated processes is crucial for successful operations of companies and government agencies. Management Information Systems, Decision Support Systems, Executive Information Systems, interactive online analysis (OLAP), data mining, dashboards and recently predictive analytics are examples for the historic advancement of business intelligence / business analytics (BI/BA) concepts for the front-end, while databases, data warehousing and increasingly ‘Big data’ are examples for the development of the underlying technical infrastructure concepts. The smart combination of task-oriented front-end innovations and technology-driven infrastructure innovations allows for enhanced decision speed, more efficient extracting, cleaning, and aggregating data from source systems, maintaining and analyzing larger data sets, and demand-oriented access to data.
From an information systems perspective, business intelligence, business analytics, and recently, big data analytics constitute a dynamic, fascinating and highly relevant field of research and practice. Examples of open research challenges include managerial considerations (BI/BA/Big data - related strategy, organization and governance, value creation, data quality management, etc.), process-centric Business Intelligence, Big data ethics and many others. As organizations continue to learn how to leverage ‘Big data’ (including social media data, mobile data, web data and network data) new innovative applications of big data analytics are expected to emerge, and with them new research challenges, yet to be discovered.
This minitrack will accept papers with a managerial, an economic, a methodological or a technical perspective on the above topics. The main emphasis is placed on the business and organizational aspects of Business Intelligence, Business Analytics and Big Data rather than technology. Contributions from the fields of theory building, design research (methods and models), action research as well as analyses of existing or innovative applications are welcome.
Topics of interest include, but are not limited to:
* Emerging Trends in Business Intelligence, Business Analytics and Big Data (with the focus on organizational issues)
- Big Data analytics
- Data/text mining and predictive analysis
- Real-time warehousing and operational business intelligence
- Mobile and pervasive BI/BA
- Qualitative BI/BA (deriving business intelligence from qualitative data including social media data)
- Innovative applications of big data and advanced business analytics
- Cloud BI/BA
- Self-service BI and rapid fire BI
- Open data
* Business Intelligence/ Business Analytics and Big Data Applications
- Collaborative BI/BA and collaborative analytics
- Performance management and dashboards
- Customer Relationship Management
- Supply Chain Management
- E-commerce
- Decision support systems
- Executive information systems
- Geographical information systems and spatial analytics
- Social BI (Social media & BI)
- BI/BA/Big data in human services (health, education, social services)
* Business, Governmental and Societal Issues
- Business/governmental/societal challenges of Big Data
- Maturity models and BI/BA strategy
- Security, privacy and ethical issues
- Industry-specific data warehousing
- Integration of structured and unstructured data
- Development methodologies
- Business value and BI/BA/Big data success
- BI/BA/Big data governance
- BI/BA/Big data challenges in NFP and other non-traditional organizations (e.g. cooperatives and mutuals)
- Data quality
- Ethical and Societal issues
Minitrack Co-Chairs:
- Olivera Marjanovic, University of Sydney Business School, Australia (Primary chair) <olivera.marjanovic@sydney.edu.au mailto:olivera.marjanovic@sydney.edu.au>
- Barbara Dinter, Chemnitz University of Technology, Germany <barbara.dinter@wirtschaft.tu-chemnitz.de mailto:barbara.dinter@wirtschaft.tu-chemnitz.de>
- Thilini Ariyachandra, Williams College of Business, Xavier University, USA <ariyachandrat@xavier.edu mailto:ariyachandrat@xavier.edu>
Deadlines:
- June 15: Submit full manuscripts for review. The review is double-blind; therefore this submission must be without author names.
- August 16: Acceptance notices are emailed to authors by the review system. At least one author of each accepted paper must immediately make plans to attend the conference, including initiating fiscal, visa, or other travel guarantees.
- September 15: Deadline for authors to submit the final manuscript of accepted papers for publication.
- October 1: Deadline for authors to register for the conference. At least one author of each paper should register by October 1 in order secure publication in the conference proceedings.
Conference website: http://www.hicss.org/
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Prof. Dr. Barbara Dinter
Chemnitz University of Technology
Faculty of Economics and Business Administration
Business Information Systems Group
Thueringer Weg 7, 09126 Chemnitz, Germany
Barbara.Dinter@wirtschaft.tu-chemnitz.de mailto:Barbara.Dinter@wirtschaft.tu-chemnitz.de
http://www.tu-chemnitz.de/wirtschaft/wi1
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