University of North Carolina at Charlotte

About: University of North Carolina at Charlotte is a education organization based out in Charlotte, North Carolina, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 8772 authors who have published 22239 publications receiving 562529 citations. The organization is also known as: UNC Charlotte & UNCC.

Shared cognition in top management teams: implications for new venture performance

Abstract: This paper presents a study of two samples of new venture top management teams from the inc. 500. The research poses that shared strategic cognition is the outcome of group processes that occur during the development of strategy. Shared cognition in top management teams (TMTs) is the extent to which those mental models about strategy are shared. A theoretical frame is developed that links shared strategic cognition to group process and new venture performance. The results indicate that the group processes leading to the development of shared strategic cognition are more important than the outcome of shared strategic cognition in terms of predicting organizational performance. Copyright © 2001 John Wiley & Sons, Ltd.

Research Methods for Public Administrators

Abstract: This accessible, practical book introduces readers to the methodological tools administrators and policy analysts use to conduct research. Comprehensive coverage of the research process includes examples and step-by-step instructions focusing on common research techniques. This new edition is accompanied by an SPSS data disk tied directly to the exercises in the book.

Unanswered Questions about Public Service Motivation: Designing Research to Address Key Issues of Emergence and Effects

Abstract: As public service motivation research gains momentum, important questions emerge regarding its origins and consequences that are not addressed by existing research. The authors identify some fundamental public service motivation assumptions, including critical gaps in our current understanding of its basic tenets. The authors then discuss specific research studies that, by virtue of their findings and designs, may fill in and inform such apparent gaps. Their aim is to chart new concrete directions for scholarship that complements and advances existing public service motivation research.

Magicol: Indoor Localization Using Pervasive Magnetic Field and Opportunistic WiFi Sensing

Abstract: Anomalies of the omnipresent earth magnetic (i.e., geomagnetic) field in an indoor environment, caused by local disturbances due to construction materials, give rise to noisy direction sensing that hinders any dead reckoning system. In this paper, we turn this unpalatable phenomenon into a favorable one. We present Magicol, an indoor localization and tracking system that embraces the local disturbances of the geomagnetic field. We tackle the low discernibility of the magnetic field by vectorizing consecutive magnetic signals on a per-step basis, and use vectors to shape the particle distribution in the estimation process. Magicol can also incorporate WiFi signals to achieve much improved positioning accuracy for indoor environments with WiFi infrastructure. We perform an in-depth study on the fusion of magnetic and WiFi signals. We design a two-pass bidirectional particle filtering process for maximum accuracy, and propose an on-demand WiFi scan strategy for energy savings. We further propose a compliant-walking method for location database construction that drastically simplifies the site survey effort. We conduct extensive experiments at representative indoor environments, including an office building, an underground parking garage, and a supermarket in which Magicol achieved a 90 percentile localization accuracy of 5 m, 1 m, and 8 m, respectively, using the magnetic field alone. The fusion with WiFi leads to 90 percentile accuracy of 3.5 m for localization and 0.9 m for tracking in the office environment. When using only the magnetism, Magicol consumes 9 $\times$ less energy in tracking compared to WiFi-based tracking.