Institution
University of British Columbia
Education•Vancouver, British Columbia, Canada•
About: University of British Columbia is a education organization based out in Vancouver, British Columbia, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 89939 authors who have published 209679 publications receiving 9226862 citations. The organization is also known as: UBC & The University of British Columbia.
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TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
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TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
9,282 citations
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Northern Arizona University1, National Institutes of Health2, University of Minnesota3, Woods Hole Oceanographic Institution4, University of California, Davis5, Massachusetts Institute of Technology6, University of Copenhagen7, University of Trento8, Chinese Academy of Sciences9, University of California, San Francisco10, University of Pennsylvania11, Pacific Northwest National Laboratory12, North Carolina State University13, University of California, San Diego14, Institute for Systems Biology15, Dalhousie University16, University of British Columbia17, Statens Serum Institut18, Anschutz Medical Campus19, University of Washington20, Michigan State University21, Stanford University22, Broad Institute23, Harvard University24, Australian National University25, University of Düsseldorf26, University of New South Wales27, Sookmyung Women's University28, San Diego State University29, Howard Hughes Medical Institute30, Cornell University31, Max Planck Society32, Colorado State University33, Google34, Syracuse University35, Webster University36, United States Department of Agriculture37, University of Arkansas for Medical Sciences38, Colorado School of Mines39, University of Southern Mississippi40, National Oceanic and Atmospheric Administration41, University of California, Merced42, Wageningen University and Research Centre43, University of Arizona44, Environment Agency45, University of Florida46, Merck & Co.47
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.
8,821 citations
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TL;DR: The development of an instrument designed to measure the various perceptions that an individual may have of adopting an information technology IT innovation, comprising eight scales which provides a useful tool for the study of the initial adoption and diffusion of innovations.
Abstract: This paper reports on the development of an instrument designed to measure the various perceptions that an individual may have of adopting an information technology IT innovation. This instrument is intended to be a tool for the study of the initial adoption and eventual diffusion of IT innovations within organizations. While the adoption of information technologies by individuals and organizations has been an area of substantial research interest since the early days of computerization, research efforts to date have led to mixed and inconclusive outcomes. The lack of a theoretical foundation for such research and inadequate definition and measurement of constructs have been identified as major causes for such outcomes. In a recent study examining the diffusion of new end-user IT, we decided to focus on measuring the potential adopters' perceptions of the technology. Measuring such perceptions has been termed a "classic issue" in the innovation diffusion literature, and a key to integrating the various findings of diffusion research. The perceptions of adopting were initially based on the five characteristics of innovations derived by Rogers 1983 from the diffusion of innovations literature, plus two developed specifically within this study. Of the existing scales for measuring these characteristics, very few had the requisite levels of validity and reliability. For this study, both newly created and existing items were placed in a common pool and subjected to four rounds of sorting by judges to establish which items should be in the various scales. The objective was to verify the convergent and discriminant validity of the scales by examining how the items were sorted into various construct categories. Analysis of inter-judge agreement about item placement identified both bad items as well as weaknesses in some of the constructs' original definitions. These were subsequently redefined. Scales for the resulting constructs were subjected to three separate field tests. Following the final test, the scales all demonstrated acceptable levels of reliability. Their validity was further checked using factor analysis, as well as conducting discriminant analysis comparing responses between adopters and nonadopters of the innovation. The result is a parsimonious, 38-item instrument comprising eight scales which provides a useful tool for the study of the initial adoption and diffusion of innovations. A short, 25 item, version of the instrument is also suggested.
8,586 citations
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TL;DR: In this article, the authors focus on the linkages between the industry analysis framework, the resource-based view of the firm, behavioral decision biases and organizational implementation issues, and connect the concept of Strategic Industry Factors at the market level with the notion of Strategic Assets at the firm level.
Abstract: We build on an emerging strategy literature that views the firm as a bundle of resources and capabilities, and examine conditions that contribute to the realization of sustainable economic rents. Because of (1) resource-market imperfections and (2) discretionary managerial decisions about resource development and deployment, we expect firms to differ (in and out of equilibrium) in the resources and capabilities they control. This asymmetry in turn can be a source of sustainable economic rent. The paper focuses on the linkages between the industry analysis framework, the resource-based view of the firm, behavioral decision biases and organizational implementation issues. It connects the concept of Strategic Industry Factors at the market level with the notion of Strategic Assets at the firm level. Organizational rent is shown to stem from imperfect and discretionary decisions to develop and deploy selected resources and capabilities, made by boundedly rational managers facing high uncertainty, complexity, and intrafirm conflict.
8,121 citations
Authors
Showing all 90682 results
Name | H-index | Papers | Citations |
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Gordon H. Guyatt | 231 | 1620 | 228631 |
John C. Morris | 183 | 1441 | 168413 |
Douglas Scott | 178 | 1111 | 185229 |
John R. Yates | 177 | 1036 | 129029 |
Deborah J. Cook | 173 | 907 | 148928 |
Richard A. Gibbs | 172 | 889 | 249708 |
Evan E. Eichler | 170 | 567 | 150409 |
James F. Sallis | 169 | 825 | 144836 |
Michael Snyder | 169 | 840 | 130225 |
Jiawei Han | 168 | 1233 | 143427 |
Michael Kramer | 167 | 1713 | 127224 |
Bruce L. Miller | 163 | 1153 | 115975 |
Peter A. R. Ade | 162 | 1387 | 138051 |
Marc W. Kirschner | 162 | 457 | 102145 |
Kaj Blennow | 160 | 1845 | 116237 |