Results 191 to 200 of about 406,172 (396)

Bankruptcy problems with interval uncertainty [PDF]

open access: yes
In this paper, bankruptcy situations with interval data are studied. Two classical bankruptcy rules, namely the proportional rule and the rights-egalitarian rule, are extended to the interval setting.
Rodica Branzei   +1 more
core  

(Dis)trust in Digital Insurance: How Datafied Practices Shift Uncertainties and Reconfigure Trust Relations

open access: yesThe British Journal of Sociology, EarlyView.
ABSTRACT Trust is both a prerequisite and a product of insurance, as insurance contracts are built on and create trust relations that enable a risk‐averse perspective towards the future. At the same time, insurer‐policyholder relationships are characterised by a persistent distrust, rooted in insurance economics and industry reputation. In this article,
Maiju Tanninen, Gert Meyers
wiley   +1 more source

Hospital Mergers and Acquisitions From 2010 to 2019: Creating a Valid Public Use Database

open access: yesHealth Services Research, EarlyView.
ABSTRACT Objective To create, analyze, and distribute the Strategic Hospital Mergers & Acquisitions (M&A) Database, a detailed resource of hospital M&As from 2010 to 2019. Study Setting and Design We conducted more than 2000 Internet searches to supplement, verify, and correct M&A identifications of American Hospital Association (AHA) survey data.
Hyesung Oh   +4 more
wiley   +1 more source

Following the blind? Database coding policies and the case of IFRS noncompliance

open access: yesContemporary Accounting Research, EarlyView.
Abstract We present a case illustrating the pitfalls of insufficient disclosure of commercial databases' coding policies. We replicate the finding in the literature that a nontrivial percentage of firms mandated to adopt IFRS ignore this obligation. Specifically, Pownall and Wieczynska (2018, Contemporary Accounting Research, 35(2), 1029–1066) report ...
Sara Alsarghali   +3 more
wiley   +1 more source

The informational content of key audit matters: Evidence from using artificial intelligence in textual analysis

open access: yesContemporary Accounting Research, EarlyView.
Abstract This study provides empirical evidence that key audit matters (KAMs) are informative for future negative accounting outcomes. We employ FinBERT—a deep learning model designed for natural language processing that allows human‐like text comprehension—to demonstrate that goodwill‐related KAMs are predictive of firms' future impairments.
Stephan Küster   +2 more
wiley   +1 more source

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