2nd Workshop on Big Data and Business Analytics Ecosystems (iDEATE 2017)
The notion of big data and its application in driving organizational decision making has attracted enormous attention over the past few years. As the label itself indicates, big data refers to large volumes of data generated and made available online and in digital media ecosystems. Associated with the notion of big data are aspects such as the diversity of data, the frequency by which it is updated, and the speed at which it grows. Companies are realizing that the data they own and the way they use them can differentiate them from competition, and even provide them with a competitive edge. Thus, todays companies try to collect and process as much data as possible. Big data and business analytics are also challenging existing modes of business and well-established companies. The need to harness the potential of rapidly expanding data volume, velocity, and variety, has seen a significant evolution of techniques and technologies for data storage, analysis, and visualization. Yet, there is limited understanding of how organizations need to change to embrace these technological innovations, and the business shifts they entail. Even more, the business value of big data and business analytics technologies still remain largely underexplored. As big data tools and applications spread, they will inevitably change long-standing ideas about decision making, management practices, and most importantly competitive strategy formulation. But as with any major change, the challenge of becoming a big data-driven enterprise can be enormous. Nevertheless, it’s a transition that executives need to navigate through, with limited empirical knowledge to guide their decisions.
The purpose of this workshop is to shed some light on how big data and business analytics tools are reshaping contemporary companies. The focus is on how companies should optimally deploy and exploit big data as part of their competitive strategies, as well as how the analytic methods, tools, and techniques are best utilized for supporting business operations. In this respect the workshop will be revolved on themes such as how big data are effectively leveraged in a range of contexts and industries (e.g. technology, retail, oil and gas, healthcare, telecommunications), and what critical factors drive successful diffusion. Papers that address topics on how information sources, technological infrastructure, human skills and knowledge, organizational/team structures, and management practices coalesce to achieve desired ends, are of increased interest. Furthermore, outcomes that demonstrate the organizational impact of big data and business analytics in terms of competitive performance, innovativeness, increased agility, and market capitalizing competence are encouraged. Emphasis will be placed on interdisciplinary papers that bridge the domains of organizational science, information systems strategic management, information science, marketing, and computer science. In addition, the workshop seeks to address the novel digital business strategies that emerge as part of these new technologies, and particularly the entrepreneurial wave and start-up business models that transpire due to these technological tools. Whereas much innovation is done within established organizations, a lot of the novel application of ICT is spearheaded by software start-ups. Start-up ecosystems are one of the most important economic drivers in today’s economy.
Despite the hype surrounding big data, the aforementioned predicaments still remain largely unexplored, severely hampering the business potential of big data and business analytics. The workshop aims to add in this direction and therefore welcomes quantitative, qualitative, and mixed methods papers, as well as reviews, conceptual papers, and theory development papers. Especially concerning the theory development papers, we highly encourage authors to explore how information systems, information management, and strategic management theories can be used or extended to explain big data and business analytics-related phenomena.
Topics of interest
- Emerging concepts and methodologies on big data and analytics
- Big data and management
- Organizational learning and innovation from big data and business analytics
- Data-driven competitive advantage
- Human resource management in the data-driven enterprise
- Big data digital business models
- Proactive strategy formulation from big data analytics
- Data and text mining for business analytics
- Behavioral and Recommender Systems Analytics
- Big data and analytics to create business value
- Social media analytics for business
- E-learning analytics
- Social media and learning analytics
- Data quality improvement for business analytics
- Big data and its impact on business strategy-formulation
- Digital ecosystem big data
- Full research papers: max. 12 pages
- Research in progress: max. 7 pages
Submitted papers must be original, unpublished, and not submitted to another conference or journal for consideration. Authors must follow the LNBIP formatting guidelines.
Papers approved for presentation will be published in the BIS 2017 workshop post-conference proceedings, as a volume in Lecture Notes in Business Information Processing series by Springer after a second review round.
Submissions need to be anonymized and will receive at least three reviews. Submissions have to follow the defined page limits (including figures, tables, appendices and references). Registration for the BIS 2017 conference entitles to participate in the conference, as well as in all workshops and tutorials held in conjunction with it.
At least one author of each paper needs to register for the conference for the paper to be included in proceedings.
Submission system is available at EasyChair.
- Submission deadline: Apr 9, 2017
- Notification of acceptance/rejection: May 14, 2017
- Submission of final papers: May 28, 2017
- Workshop: Jun 28-30, 2017
Organizers and Chairs
- Patrick Mikalef, Norwegian University of Science and Technology (NTNU), Norway
- Ilias O. Pappas, Norwegian University of Science and Technology (NTNU), Norway
- Michail N. Giannakos, Norwegian University of Science and Technology (NTNU), Norway
- John Krogstie, Norwegian University of Science and Technology (NTNU), Norway
- George Lekakos, Athens University of Economic and Business, Greece
- Björn Johansson, Lund University, Sweden
- Demetrios Sampson, Curtin University, Australia
- Dimitris Karlis, Athens University of Economics and Business, Greece
- Frantisek Sudzina, Aalborg University, Denmark
- Johan Versendaal, Hogeschool Utrecht, the Netherlands
- Letizia Jaccheri, Norwegian University of Science and Technology (NTNU), Norway
- Panos E. Kourouthanassis, Ionian University, Greece
- Pekka Abrahamsson, Norwegian University of Science and Technology (NTNU), Norway
- Rogier van de Wetering, Open University of the Netherlands, the Netherlands
- Remko Helms, Open University of the Netherlands, the Netherlands