87,825 research outputs found
Organizational speed as a dynamic capability: Toward a holistic perspective
Current research on organizational speed has been disjointed, which has left organizational speed as an underdeveloped area of study. In this essay, we expand the view of organizational speed as a multidimensional gestalt-like construct that may influence firm performance and competitive advantage. We offer a capability-based definition of organizational speed and identify and review the building blocks of organizational speed. We propose new avenues and questions for future research based on our perspective
Complexity in the Context of Information Systems Project Management
Complexity is an inherent attribute of any project. The purpose of defining and documenting complexity is to enable a project team to foresee resulting challenges in a timely manner, and take steps to alleviate them.The main contribution of this article is to present a systematic view of complexity in project management by identifying its key attributes and classifying complexity by these attributes. A “complexity taxonomy” is developed and discussed within three levels: the product, the project and the external environment.Complexity types are described through simple real-life examples. Then a framework (tool) is developed for applying the notion of complexity as an early warning tool.The article is intended for researchers in complexity, project management, information systems, technology solutions and business management, and also for information specialists, project managers, program managers, financial staff and technology directors
Video Question Answering via Attribute-Augmented Attention Network Learning
Video Question Answering is a challenging problem in visual information
retrieval, which provides the answer to the referenced video content according
to the question. However, the existing visual question answering approaches
mainly tackle the problem of static image question, which may be ineffectively
for video question answering due to the insufficiency of modeling the temporal
dynamics of video contents. In this paper, we study the problem of video
question answering by modeling its temporal dynamics with frame-level attention
mechanism. We propose the attribute-augmented attention network learning
framework that enables the joint frame-level attribute detection and unified
video representation learning for video question answering. We then incorporate
the multi-step reasoning process for our proposed attention network to further
improve the performance. We construct a large-scale video question answering
dataset. We conduct the experiments on both multiple-choice and open-ended
video question answering tasks to show the effectiveness of the proposed
method.Comment: Accepted for SIGIR 201
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