Institution
Boston College
Education•Boston, Massachusetts, United States•
About: Boston College is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 9749 authors who have published 25406 publications receiving 1105145 citations. The organization is also known as: BC.
Topics: Population, Poison control, Catalysis, Context (language use), Politics
Papers published on a yearly basis
Papers
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TL;DR: The authors argue that constructive deviance is an umbrella term that encompasses several different behaviors, including taking charge, creative performance, expressing voice, whistle-blowing, extra-role behaviors, prosocial behaviors and prosocial rule breaking.
213 citations
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TL;DR: In this article, the authors examine how corporate social media affects the capital market consequences of firms' disclosure in the context of consumer product recalls, and find that the negative price reaction to a recall is attenuated by the frequency of tweets by the firm, while exacerbated by other users.
Abstract: We examine how corporate social media affects the capital market consequences of firms’ disclosure in the context of consumer product recalls. Product recalls constitute a “product crisis” exposing the firm to reputational damage, loss of future sales, and legal liability. During such a crisis it is crucial for the firm to quickly and directly communicate its intended message to a wide network of stakeholders, which, in turn, renders corporate social media a potentially useful channel of disclosure. While we document that corporate social media, on average, attenuates the negative price reaction to recall announcements, the attenuation benefits of corporate social media vary with the level of control the firm has over its social media content. In particular, with the arrival of Facebook and Twitter, firms relinquished complete control over their social media content, and the attenuation benefits of corporate social media, while still significant, lessened. Detailed Twitter analysis confirms that the moderating effect of social media varies with the level of firm involvement and with the amount of control exerted by other users: the negative price reaction to a recall is attenuated by the frequency of tweets by the firm, while exacerbated by the frequency of tweets by other users.
213 citations
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TL;DR: In this article, a switching regression model of investment is developed, in which the probability of a firm facing a high premium on external finance is endogenously determined, and this approach allows on...
Abstract: In this paper we develop a switching regression model of investment, in which the probability of a firm facing a high premium on external finance is endogenously determined. This approach allows on...
213 citations
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TL;DR: This paper introduces foundational concepts in IRT, as well as commonly used models and their assumptions, and examples illustrate how IRT can be used to improve the development, refinement, and evaluation of PRO measures.
Abstract: The growing emphasis on patient-centered care has accelerated the demand for high-quality data from patient-reported outcome (PRO) measures. Traditionally, the development and validation of these measures has been guided by classical test theory. However, item response theory (IRT), an alternate measurement framework, offers promise for addressing practical measurement problems found in health-related research that have been difficult to solve through classical methods. This paper introduces foundational concepts in IRT, as well as commonly used models and their assumptions. Existing data on a combined sample (n = 636) of Korean American and Vietnamese American adults who responded to the High Blood Pressure Health Literacy Scale and the Patient Health Questionnaire-9 are used to exemplify typical applications of IRT. These examples illustrate how IRT can be used to improve the development, refinement, and evaluation of PRO measures. Greater use of methods based on this framework can increase the accuracy and efficiency with which PROs are measured.
213 citations
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TL;DR: In this paper, the authors quantify the contribution of the housing market to business fluctuations using U.S. data and Bayesian methods, and find that the spillovers from the housing markets to the broader economy are non-negligible, concentrated on consumption rather than business investment, and they have become more important over time.
Abstract: Using U.S. data and Bayesian methods, we quantify the contribution of the housing market to business fluctuations. The estimated model, which contains nominal and real rigidities and collateral constraints, is used to address two questions. First, what shocks drive the housing market? We find that the upward trend in real housing prices of the last 40 years can be explained by slow technological progress in the housing sector. Over the business cycle instead, housing demand and housing technology shocks account for roughly one-quarter each of the volatility of housing investment and housing prices. Monetary factors account for about 20 percent, but they played a major role in the housing market cycle at the turn of the century. Second, do fluctuations in the housing market propagate to other forms of expenditure? We find that the spillovers from the housing market to the broader economy are non-negligible, concentrated on consumption rather than business investment, and they have become more important over time, to the extent that financial innovation has increased the marginal availability of funds for credit-constrained agents.
213 citations
Authors
Showing all 9922 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eric J. Topol | 193 | 1373 | 151025 |
Gang Chen | 167 | 3372 | 149819 |
Wei Li | 158 | 1855 | 124748 |
Daniel L. Schacter | 149 | 592 | 90148 |
Asli Demirguc-Kunt | 137 | 429 | 78166 |
Stephen G. Ellis | 127 | 655 | 65073 |
James A. Russell | 124 | 1024 | 87929 |
Zhifeng Ren | 122 | 695 | 71212 |
Jeffrey J. Popma | 121 | 702 | 72455 |
Mike Clarke | 113 | 1037 | 164328 |
Kendall N. Houk | 112 | 997 | 54877 |
James M. Poterba | 107 | 487 | 44868 |
Gregory C. Fu | 106 | 381 | 32248 |
Myles Brown | 105 | 348 | 52423 |
Richard R. Schrock | 103 | 724 | 43919 |