In the current competitive environment, the need for better management of all organizational resources, and specifically IT, requires comprehensive assessment of their contribution to firm performance. However, there is little empirical evidence that IT is capable of creating value, nor has a comprehensive framework of business value emerged. Many of the available studies of IT productivity and business value were conducted using firm level output measures of value. The focus on firm level output variables, while important, provides only limited understanding of how value is created using IT. This paper develops a conceptual framework of the business value outcomes of IT by synthesizing the extant literature on IT business value and IT supported organization and process design. The framework provides a basis for process oriented studies of IT business value, and enhances our understanding of the links between information technology and firm performance.

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(TUN) cosponsored the Business Intelligence Congress 3 and conducted surveys to assess academia's response to the growing market need for students with Business Intelligence (BI) and Business Analytics (BA) skill sets. This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010. The article also serves as a "call to action" for universities regarding the need to respond to emerging market needs in BI/BA, including "Big Data." The IS field continues to be well positioned to be the leader in creating the next generation BI/BA workforce. To do so, we believe that IS leaders need to continuously refine BI/BA curriculum to keep pace with the turbulent BI/BA marketplace.

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An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict payload and power constraints which limit the number and variety of sensors available to gather this information. It is desirable, therefore, to enable a UAV to gather information about potential obstacles or interesting landmarks using common and lightweight sensor systems. This paper presents a method of fast terrain mapping with a monocular camera. Features are extracted from camera images and used to update a sequential extended Kalman filter. The features locations are parameterized in inverse depth to enable fast depth convergence. Converged features are added to a persistent terrain map which can be used for obstacle avoidance and additional vehicle guidance. Simulation results and results from recorded flight test data are presented to validate the algorithm.