Opportunity: Information Valuation

2012 ◽  
pp. 91-92
Author(s):  
Thomas Frisendal
Keyword(s):  
Information Valuation

The Knowledge Management Information Landscape — Awareness, Access, Use and Value of Sources

2015 ◽  
Vol 14 (02) ◽  
pp. 1550002 ◽  
Author(s):  
Denise A. D. Bedford
Keyword(s):  
Knowledge Management ◽  
Information Management ◽  
Critical Component ◽  
Management Information ◽  
Specific Knowledge ◽  
Public Survey ◽  
Knowledge Organisation ◽  
Information Awareness ◽  
Information Valuation ◽  
Information Landscape

Information landscape is a critical component of professional and scholarly disciplines. Established disciplines have a managed information foundation covering primary, secondary and tertiary sources, targeted search capabilities, discipline-specific knowledge organisation tools and services, and quality controlled review processes. The information landscapes of emerging disciplines may be more chaotic and unsettled, and present challenges for professionals. This research considers the information landscape of the knowledge management discipline. An open public survey of knowledge professionals provides insights into three factors that affect the landscape including: (1) information awareness; (2) information use and access; and (3) information valuation. Findings highlight key information management challenges, and offer suggestions for solutions.

Information Valuation and Confirmation Bias in Virtual Communities: Evidence from Stock Message Boards

2013 ◽  
Vol 24 (4) ◽  
pp. 1050-1067 ◽  
Author(s):  
JaeHong Park ◽  
Prabhudev Konana ◽  
Bin Gu ◽  
Alok Kumar ◽  
Rajagopal Raghunathan
Keyword(s):  
Virtual Communities ◽  
Confirmation Bias ◽  
Message Boards ◽  
Information Valuation

Information Valuation Policies for Explainable Trustworthiness Assessment in E-Services

2011 ◽  
pp. 168-197
Author(s):  
Karen K. Fullam ◽  
K. Suzanne Barber
Keyword(s):  
Information Source ◽  
Accurate Information ◽  
Service Users ◽  
Multiple Sources ◽  
Face To Face ◽  
Inaccurate Information ◽  
Assessment Decisions ◽  
Information Valuation ◽  
Information Providers ◽  
Relational History

Information e-services are useful for exchanging information among many users, whether human or automated agent; however, e-service users are susceptible to risk of inaccurate information, since users have no traditional face-to-face interaction or past relational history with information providers. To encourage use of information e-services, individuals must have technology to assess information accuracy and information source trustworthiness. This research permits automated e-service users—here called agents—acting on behalf of humans, to employ policies, or heuristics, for predicting information accuracy when numerous pieces of information are received from multiple sources. These intuitive policies draw from human strategies for evaluating the trustworthiness of information to not only identify accurate information, but also distinguish untrustworthy information providers. These policies allow the agent to build a user’s confidence in the trust assessment technology by creating justifications for trust assessment decisions and identifying particular policies integral to a given assessment decision.

Semantics-based information valuation

2008 ◽  
Author(s):  
Sinan al-Saffar ◽  
Gregory L. Heileman
Keyword(s):  
Information Valuation

scholarly journals The zoning of the risk of mass movements using information valuation methods and surface density in the ghouchan- Shirvan watershed

2020 ◽  
Vol 7 (3) ◽  
pp. 147-162
Author(s):  
Zeinab Mojarad ◽  
javad jamalabadi ◽  
Najmeh Shafiei ◽  
mohammad َAli zanganeh asadi ◽  
Kobra parak ◽  
...  
Keyword(s):  
Surface Density ◽  
Mass Movements ◽  
Valuation Methods ◽  
Information Valuation

Accruals, Accounting-Based Valuation Models, and the Prediction of Equity Values

2005 ◽  
Vol 20 (4) ◽  
pp. 311-345 ◽  
Author(s):  
Mary E. Barth ◽  
William H. Beaver ◽  
John R. M. Hand ◽  
Wayne R. Landsman
Keyword(s):  
Cash Flow ◽  
Model Parameters ◽  
Prediction Errors ◽  
Equity Values ◽  
Valuation Model ◽  
Equity Value ◽  
Out Of Sample ◽  
Other Information ◽  
Linear Information ◽  
Information Valuation

This study uses out-of-sample equity value estimates to determine whether earnings disaggregation, imposing linear information valuation model (LIM) structure and separate industry estimation of valuation model parameters aid in predicting contemporaneous equity values. We consider three levels of earnings disaggregation: aggregate earnings, cashflow and total accruals and cash flow and four major components of accruals. For pooled estimations, imposing the LIM structure results in significantly smaller prediction errors; for by-industry estimations, it does not. However, by-industry prediction errors are substantially smaller, suggesting that the by-industry estimations are better specified. Mean squared and absolute prediction errors are smallest when earnings are disaggregated into cash flow and major accrual components; median prediction errors are smallest when earnings are disaggregated into cash flow and total accruals. These findings suggest that (1) if concern is with errors in the tails of the equity value prediction error distribution, then earnings should be disaggregated into cash flow and the major accrual components; otherwise earnings should be disaggregated only into cash flow and total accruals; (2) imposing the LIM structure neither increases nor decreases prediction errors, which supports the efficacy of drawing inferences from valuation equations based on residual income models that do not impose the structure implied by the model; (3) valuation of abnormal earnings, accruals, accrual components, equity book value, and other information varies significantly across industries.

Conservative Accounting and Linear Information Valuation Models*

2006 ◽  
Vol 23 (1) ◽  
pp. 73-101 ◽  
Author(s):  
Young-Soo Choi ◽  
John F. O'Hanlon ◽  
Peter F. Pope
Keyword(s):  
Conservative Accounting ◽  
Linear Information ◽  
Information Valuation
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