Technological innovations and novel applications in unprecedented areas are changing the way organizations and the society at large consume data and information. For instance, big data created by social media computing and the Internet of Things (IoT) is revolutionizing the way individuals communicate and live. It has led to the need for the creation of new and innovative tools and techniques for advanced analytics to gain valuable insights for organizations. The ability to manage (big) data, information and knowledge to gain competitive advantage, and the importance of business analytics for this process has been well established. Information and knowledge created through analytics driven by big data has become necessary for innovation and survival in the current business environment.
Since this is a rapidly evolving area, organizations continue to expend time and resources to enhance and develop new decision support applications and advance analytics to garner insights and knowledge. Research contributions in this space inform industry on how to handle the various organizational and technical opportunities and challenges when working with big data, knowledge management and analytics. From research on managerial concerns (such as strategy, governance, leadership), process-centric approaches and inter-organizational aspects of decision support to research on technical considerations when incorporating new data sources and new frameworks for big data, analytics and knowledge management, academic endeavors in this space provide insights on a dynamic and highly relevant field within information systems. This research track seeks research that promotes theoretical, design science, pedagogical, and behavioral research as well as emerging applications in innovative areas of analytics, big data, and knowledge management.
Research areas in big data, analytics and knowledge management (KM) include but are not limited to: data analytics & visualization; curation, management and infrastructure for (big) data; standards, semantics, privacy, security and legal issues in big data, analytics and KM; performance analysis, intelligence and scientific discovery in big data, analytics and KM and the like; analytics applications in smart cities, sustainability, smart grids and the like; business process management applications such as process discovery, conformance and mining using analytics and KM..
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