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Institution

University of Texas at Austin

EducationAustin, Texas, United States
About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.


Papers
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Journal ArticleDOI
TL;DR: This paper reviews several sources of the data inaccuracies that commonly affect retrospective data and offers guidelines for reducing the occurrence or magnitude of these inaccuracies.
Abstract: Strategic management studies frequently involve obtaining retrospective data from strategic-level managers. The use of this data acquisition methodology has received relatively little codification and little critical review or comment. This seems unfortunate, as discussion and codification of the methodology could be useful for those academic researchers and corporate staff who study strategic decisions and organizational processes and for those managers who may be asked to provide the retrospective data. This paper is an attempt to remedy the current state of affairs. In particular, the paper reviews several sources of the data inaccuracies that commonly affect retrospective data and offers guidelines for reducing the occurrence or magnitude of these inaccuracies.

1,699 citations

Journal ArticleDOI

1,696 citations

Journal ArticleDOI
TL;DR: In this paper, a set of high-redshift supernovae were used to confirm previous supernova evidence for an accelerating universe, and the supernova results were combined with independent flat-universe measurements of the mass density from CMB and galaxy redshift distortion data, they provided a measurement of $w=-1.05^{+0.15}-0.09$ if w is assumed to be constant in time.
Abstract: We report measurements of $\Omega_M$, $\Omega_\Lambda$, and w from eleven supernovae at z=0.36-0.86 with high-quality lightcurves measured using WFPC-2 on the HST. This is an independent set of high-redshift supernovae that confirms previous supernova evidence for an accelerating Universe. Combined with earlier Supernova Cosmology Project data, the new supernovae yield a flat-universe measurement of the mass density $\Omega_M=0.25^{+0.07}_{-0.06}$ (statistical) $\pm0.04$ (identified systematics), or equivalently, a cosmological constant of $\Omega_\Lambda=0.75^{+0.06}_{-0.07}$ (statistical) $\pm0.04$ (identified systematics). When the supernova results are combined with independent flat-universe measurements of $\Omega_M$ from CMB and galaxy redshift distortion data, they provide a measurement of $w=-1.05^{+0.15}_{-0.20}$ (statistical) $\pm0.09$ (identified systematic), if w is assumed to be constant in time. The new data offer greatly improved color measurements of the high-redshift supernovae, and hence improved host-galaxy extinction estimates. These extinction measurements show no anomalous negative E(B-V) at high redshift. The precision of the measurements is such that it is possible to perform a host-galaxy extinction correction directly for individual supernovae without any assumptions or priors on the parent E(B-V) distribution. Our cosmological fits using full extinction corrections confirm that dark energy is required with $P(\Omega_\Lambda>0)>0.99$, a result consistent with previous and current supernova analyses which rely upon the identification of a low-extinction subset or prior assumptions concerning the intrinsic extinction distribution.

1,687 citations

Posted Content
TL;DR: This paper examined the investment strategies of 155 mutual funds over the 1975-84 period to determine the extent to which the funds purchased stocks based on their past returns, and determine the relation of this behavior to their observed portfolio performance.
Abstract: We examine the investment strategies of 155 mutual funds over the 1975-84 period to determine the extent to which the funds purchased stocks based on their past returns, and to determine the relation of this behavior to their observed portfolio performance We find that about 77% of these mutual funds were "momentum investors", buying stocks that were past winners; however, they did not systematically sell past losers On average, these "trend-followers" realized significantly better performance than the remaining funds We also find that the mutual funds exhibited herding behavior, and that the tendency of a fund to herd in its trades was strongly correlated with its tendency to buy past winners as well as with its portfolio performance Consistent with the evidence on trend-following, herding into past winners was stronger than herding into past losers

1,685 citations

Journal ArticleDOI
TL;DR: A cross-cultural validation of an Internet consumer trust model is reported on, which examined both antecedents and consequences of consumer trust in a Web merchant and provides tentative support for the generalizability of the model.
Abstract: Many have speculated that trust plays a critical role in stimulating consumer purchases over the Internet. Most of the speculations have rallied around U.S. consumers purchasing from U.S.–based online merchants. The global nature of the Internet raises questions about the robustness of trust effects across cultures. Culture may also affect the antecedents of consumer trust; that is, consumers in different cultures might have differing expectations of what makes a web merchant trustworthy. Here we report on a cross-cultural validation of an Internet consumer trust model. The model examined both antecedents and consequences of consumer trust in a Web merchant. The results provide tentative support for the generalizability of the model.

1,684 citations


Authors

Showing all 95138 results

NameH-indexPapersCitations
George M. Whitesides2401739269833
Eugene Braunwald2301711264576
Yi Chen2174342293080
Robert J. Lefkowitz214860147995
Joseph L. Goldstein207556149527
Eric N. Olson206814144586
Hagop M. Kantarjian2043708210208
Rakesh K. Jain2001467177727
Francis S. Collins196743250787
Gordon B. Mills1871273186451
Scott M. Grundy187841231821
Michael S. Brown185422123723
Eric Boerwinkle1831321170971
Aaron R. Folsom1811118134044
Jiaguo Yu178730113300
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023304
20221,209
202110,137
202010,331
20199,727
20188,973