The Role of Overbilling in Hospitalss Earnings Management Decisions

2017 ◽  
Author(s):  
Jonas Heese
Keyword(s):  
Earnings Management ◽  
Management Decisions

scholarly journals Career concerns and earnings management

2020 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Elizabeth Demers ◽  
Chong Wang
Keyword(s):  
Labor Market ◽  
Earnings Management ◽  
Early Years ◽  
Career Concerns ◽  
Management Model ◽  
Earnings Manipulation ◽  
Management Decisions

Motivated by the disconnect between survey evidence documenting that executives prioritize implicit contracting (i.e., labor market-based career concerns) when making earnings management decisions (Graham et al., 2005) and the extant literature’s focus on explicit contracting to explain earnings manipulation, we analytically examine the role of managerial career concerns in earnings management. Building on Holmstrom (1982, 1999), we present a career concerns-based earnings management model that incorporates the unique reversing nature of earnings management. A key insight derived from the model is that whether the predictions of a traditional career concerns model prevail, which is to say that managers engage in more income-increasing behavior in their early years, critically depends upon the reversal characteristics of the earnings management vehicle chosen.

Text mining for economic geographical sectoral analysis of the pulp and paper industry in European Russia

2021 ◽  
Vol 71 (1) ◽  
pp. 18-33
Author(s):  
I.F. Kuzminov ◽  
P.A. Lobanova
Keyword(s):  
Text Mining ◽  
Paper Industry ◽  
Pulp And Paper Industry ◽  
Spatial Development ◽  
Pulp And Paper ◽  
European Russia ◽  
Data Sources ◽  
Management Decisions ◽  
Timber Industry

The authors show the need and some existing opportunities for analysis of non-traditional data sources to obtain a complete and more relevant picture of industries spatial development. The research methodology includes the use of text mining for economic and geographical studies. The relevance of the research is determined by insufficient completeness of official statistical data, cheapening of relevant information processing technologies and abundance of large text data sources in open access. The article discusses the role of the pulp and paper industry (as a key part of the timber industry) in economic and spatial development of modern Russia. The authors identify main trends in the economic and spatial development of the pulp and paper industry of European Russia, draw the conclusions on the expected industry trends and give recommendations for strategic management decisions to respond to industry challenges. The authors claim that the industry needs liberalization and stabilization, primarily through moratoriums on policy changes. The role of the use of big data, and in particular of text mining in economic and geographical research for reasonable and objective conclusions formation that can be used to make timely and balanced management decisions in the timber industry and the pulp and paper industry, is emphasized.

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