Fordham University

About: Fordham University is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Population & Politics. The organization has 6688 authors who have published 15650 publications receiving 371527 citations.

Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination

Abstract: Research on market orientation and organizational learning addresses how organizations adapt to their environments and develop competitive advantage. A significant void exists in current models of market orientation because none of the frameworks incorporates constructs related to innovation. The authors present a conceptual framework for incorporating constructs that pertain to innovation in market orientation research. Some of the critical relationships in this conceptual framework are tested among a sample of 9648 employees of 56 organizations in a large agency of the U.S. federal government. The results indicate that higher levels of innovativeness in the firms' culture are associated with a greater capacity for adaptation and innovation (number of innovations successfully implemented). In addition, higher levels of innovativeness are associated with cultures that emphasize learning, development, and participative decision making. The authors make recommendations for incorporating constructs related to innovation into research on market orientation and organziational learning.

Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination:

Abstract: Research on market orientation and organizational learning addresses how organizations adapt to their environments and develop competitive advantage. A significant void exists in current models of ...

Activity recognition using cell phone accelerometers

Abstract: Mobile devices are becoming increasingly sophisticated and the latest generation of smart cell phones now incorporates many diverse and powerful sensors These sensors include GPS sensors, vision sensors (ie, cameras), audio sensors (ie, microphones), light sensors, temperature sensors, direction sensors (ie, magnetic compasses), and acceleration sensors (ie, accelerometers) The availability of these sensors in mass-marketed communication devices creates exciting new opportunities for data mining and data mining applications In this paper we describe and evaluate a system that uses phone-based accelerometers to perform activity recognition, a task which involves identifying the physical activity a user is performing To implement our system we collected labeled accelerometer data from twenty-nine users as they performed daily activities such as walking, jogging, climbing stairs, sitting, and standing, and then aggregated this time series data into examples that summarize the user activity over 10- second intervals We then used the resulting training data to induce a predictive model for activity recognition This work is significant because the activity recognition model permits us to gain useful knowledge about the habits of millions of users passively---just by having them carry cell phones in their pockets Our work has a wide range of applications, including automatic customization of the mobile device's behavior based upon a user's activity (eg, sending calls directly to voicemail if a user is jogging) and generating a daily/weekly activity profile to determine if a user (perhaps an obese child) is performing a healthy amount of exercise

Big data analytics in healthcare: promise and potential

Abstract: Objective: To describe the promise and potential of big data analytics in healthcare. Methods: The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results: The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions: Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.