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The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Individuals' stress in responding to the current COVID-19 pandemic may be exacerbated by information uncertainty driven by inconsistent, unverified, and conflicting news from various sources. The current study aims to test if information uncertainty during the COVID-19 outbreak was related to acute stress disorder (ASD) over and above other psychosocial stressors., Methods: An anonymous online survey was conducted with 7800 college students throughout China from January 31 through February 11, 2020. Existing scales were modified to measure ASD and six potential stressors including information uncertainty during the COVID-19 outbreak. Hierarchical regression analysis was conducted to assess the unique association of information uncertainty with ASD. To minimize the effect of large sample size and also to get a sense of whether the effects of information uncertainty were similar to people at the center of the epidemic, we repeated the hierarchical regression among 10% of the students who were randomly selected from the entire sample ("10% random sample"; n = 780) and 226 students from Hubei Province where the outbreak started., Results: Information uncertainty was highly prevalent among the respondents (64%). It was significantly associated with ASD beyond other key variables and potential stressors across three samples. In the hierarchical regression among the entire sample, demographic variables accounted for 9.4% of the variance in ASD. The other five stressors added 5.1% of the variance. The information uncertainty (β = .159; p < .001) explained an additional 2.1% of the variance. Likewise, the information uncertainty explained an additional 2.1 and 3.4% of the variance in ASD beyond all other variables among the 10% random sample (β = .165; p < .001) and the Hubei sample (β = .196; p < .01), respectively., Conclusion: Information uncertainty is a unique correlate of psychological stress during the COVID-19 outbreak. Reducing information uncertainty is essential not only for halting virus transmission but also for mitigating negative impacts of the pandemic on people's psychosocial wellbeing. Transparent, timely, and accurate communication can reduce public confusion, fear, and stress. Capacity building in governments, communities, and media outlets to prevent, reduce and manage information uncertainty should be a critical part of the response to an emerging global health crisis such as the COVID-19 pandemic.

• We construct a new measure of firm-level information uncertainty. • In aggregate, our uncertainty measure comoves with other uncertainty measures. • This measure positively predicts future stock returns. • This measure primarily captures the idiosyncratic component in the cross-section. Firm-level uncertainty is difficult to measure in nature. We construct a new measure of firm-level information uncertainty based on uncertainty premium implied by earnings announcement returns. This new measure fundamentally differs from other firm-level uncertainty measures. We find that high-uncertainty firms outperform low-uncertainty firms by 9.59 % per annum on a risk-adjusted basis. Furthermore, this return predictability persists for up to five quarters. Our uncertainty measure and its return predictability are primarily driven by the idiosyncratic component. Overall, our results support the existence of an uncertainty premium and cast doubt on the hedgeability of uncertainty. [ABSTRACT FROM AUTHOR]

This study employed deep learning to analyze a substantial data set of 109.13 million COVID-19-related microblogs, leading to the construction of a specialized risk perception indicator dictionary. Employing this dictionary, we were able to capture the dynamic fluctuations in risk perception within online communities across various cities in real time. This approach highlighted the varying intensities of public response to the evolving crisis during the isolation and normalization stages of the pandemic. We observed that COVID-19-related transmission threat and information uncertainty significantly influenced public risk perception at different stages of the pandemic. Innovatively, our study quantifies public psychological resilience within online communities by examining the equilibrium between public risk perception and objective COVID-19-related risks. This equilibrium is conceptualized as the alignment of public perception with the evolving reality of COVID-19 threat and information. We investigated psychological resilience in two dimensions: adaptability, indicated by the extent of deviation from this equilibrium, and agility, reflected in the rate at which equilibrium is reestablished. Our study not only unveils new insights into the intricate relationship among public risk perception, the evolving risks, and psychological resilience but also offers empirical evidence to inform risk management strategies in online communities at different stages of a crisis. Practical Applications: This research provides essential insights into how public perception and emotional responses during health crises like COVID-19 can be monitored and analyzed through social media data. By utilizing advanced analytical methods, including natural language processing (NLP) and panel vector error correction (PVEC) modeling, the study successfully quantified the psychological resilience of online communities. These methods allow for the real-time assessment of how communities adapt and respond to evolving risks, such as transmission threats and information uncertainty. For policymakers and crisis managers, these findings offer valuable tools for understanding public sentiment during different phases of a crisis. This understanding is crucial for shaping effective communication strategies and tailoring public health responses to specific community needs. The study's methodology is adaptable across different cultural contexts and can be applied to various crisis scenarios, making it a versatile tool in global crisis management. The study's approach demonstrates the potential of using social media analytics not only for academic research but also for practical, real-time crisis management. By providing a framework for measuring and interpreting public risk perception and resilience, the research aids in the development of more responsive and effective public health strategies. Overall, this research contributes significantly to both theory and practice in the field of crisis management, offering novel methods for assessing community resilience and guiding decision-making during public health emergencies. [ABSTRACT FROM AUTHOR]

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.

This paper considers a problem of source data uncertainty concerning the technical state of gas supply systems. Decision-making in the region of managing and development planning of the gas supply systems (production, transport, distribution, storage), as a rule, occurs by lacking of information, and the validity of some data is questionable. We propose to formalize the information uncertainty in terms of membership functions of the fuzzy sets. Mathematical models and algorithms for solving the various modelling and optimization problems of the natural gas transport are worked out. The results of calculations demonstrate the potential of the technique. • Fuzzy models for the technical state parameters of pipelines and compressors. • An algorithm for calculating the maximum flow capacity of a gas-transport system with fuzzily-assigned parameters. • An optimization algorithm of the operation modes of a gas transport system with fuzzily-assigned parameters. • Application of the proposed models and algorithms to the illustrative and real-world gas transport systems. [ABSTRACT FROM AUTHOR]

An attribute reduct, an important concept of rough set theory, is a subset that is sufficient and individually necessary for preserving a particular property of the given information system. In this study, we present a proposed method to calculate the accuracy of data by using the concepts of pre-open and semi-open. We also compared the results of accuracies in the proposed method with the accuracies in Yao and Pawlak methods. Our study revealed that the new model calculating the degree of accuracy was better than the previous models. Additionally, we provided a new insight into the application of the attribute reduction and we used MATLAB programming to obtain the result. [ABSTRACT FROM AUTHOR]

Vehicular fog computing has emerged as a cost-efficient solution for task processing in vehicular networks. However, how to realize effective server recruitment and reliable task offloading under information asymmetry and uncertainty remains a critical challenge. In this paper, we adopt a two-stage task offloading framework to address this challenge. First, we propose a convex–concave-procedure-based contract optimization algorithm for server recruitment, which aims to maximize the expected utility of the operator with asymmetric information. Then, a low-complexity and stable task offloading mechanism is proposed to minimize the total network delay based on the pricing-based matching. Furthermore, we extend the work to the scenario of information uncertainty and develop a matching-learning-based task offloading mechanism, which takes both occurrence awareness and conflict awareness into consideration. Simulation results demonstrate that the proposed algorithm can effectively motivate resource sharing and guarantee bounded deviation from the optimal performance without the global information. [ABSTRACT FROM AUTHOR]

There is substantial evidence of short-term stock price continuation, which the prior literature often attributes to investor behavioral biases such as underreaction to new information. This paper investigates the role of information uncertainty in price continuation anomalies and cross-sectional variations in stock returns. If short-term price continuation is due to investor behavioral biases, we should observe greater price drift when there is greater information uncertainty. As a result, greater information uncertainty should produce relatively higher expected returns following good news and relatively lower expected returns following bad news. My evidence supports this hypothesis. [ABSTRACT FROM AUTHOR]

Prior literature observes that information uncertainty exacerbates investor underreaction behavior. In this paper, I investigate whether, as professional investment intermediaries, sellside analysts suffer more behavioral biases in cases of greater information uncertainty. I show that greater information uncertainty predicts more positive (negative) forecast errors and subsequent forecast revisions following good (bad) news, which corroborates previous findings on the post-analyst-revision drift. The opposite effects of information uncertainty on forecast errors and subsequent forecast revisions following good versus bad news support the analyst underreaction hypothesis and are inconsistent with analyst forecast rationality or optimism suggested in prior literature. [ABSTRACT FROM AUTHOR]

Fault diagnosis is of great significance in maintaining the safe and stable operation of a system. Fast and precise location of faults is important for restoring power supply systems. In this paper, considering the interference of information uncertainty to fault diagnosis under different weather conditions, a fault diagnosis model based on Bayesian network is proposed. The model inherits the capability of processing uncertain information of a Bayesian network and divides the information into historical information and evidence information. The uncertainty of historical information is reduced by modifying the parameters through improving parameter learning formulas, while that of evidence information can be reduced by logical judgment. A fault simulation model based on Monte Carlo method is used to generate simulation data for parameter learning, and a case study confirms the correctness of the proposed fault diagnosis and fault simulation models. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Results indicated that expectant mothers had relatively high uncertainty about what to expect during labor and delivery as well as needed more information about breast feeding. Too much information was given on smoking and drinking, and patients felt they got too much written information. High information uncertainty was significantly related to patient dissatisfaction, and a variety of demographic factors were found to be correlated with information uncertainty and satisfaction with the physician. [ABSTRACT FROM AUTHOR]

• AV utilitarian protocols implies some predictability. • If AV decision process is perfectly known then is manipulable. • Sufficiently high levels of uncertainty are necessary. • Uncertainty decreases the risk of successful manipulation. • (but) Uncertainty decrease the quality of the decision process, efficiency and welfare. In an avoidable harmful situation, autonomous vehicles systems are expected to choose the course of action that causes the less damage to everybody. However, this behavioral protocol implies some predictability. In this context, we show that if the autonomous vehicle decision process is perfectly known then malicious, opportunistic, terrorist, criminal and non-civic individuals may have incentives to manipulate it. Consequently, some levels of uncertainty are necessary for the system to be manipulation proof. Uncertainty removes the misbehavior incentives because it increases the risk and likelihood of unsuccessful manipulation. However, uncertainty may also decrease the quality of the decision process with negative impact in terms of efficiency and welfare for the society. We also discuss other possible solutions to this problem. [ABSTRACT FROM AUTHOR]

The green vehicle routing problem of distributing gasoline to retail gasoline stations in a way that is not just the most cost-effective overall but also reduces its own carbon emissions needs to account for uncertainty from multiple sources. Therefore, in this paper we study how to do this, simultaneously reducing the cost and minimizing the environmental impact in the presence of information uncertainty. Among the sources of uncertainty are random demand by gas stations and uncertain travel time to them by tankers, which we build into our model. We also design a three-stage heuristic algorithm. In the first stage, the chance constraints of the model are converted into their deterministic equivalents. In the second stage, gas stations are clustered, based on their distance and demand for gasoline. In the third stage, we use a genetic algorithm to solve the model based on the first two stages. Finally, we use our simulation results to propose how gas stations can optimize their cost of gasoline distribution. [ABSTRACT FROM AUTHOR]

SUMMARY: The Public Company Accounting Oversight Board (PCAOB) has expressed concern that audit reports do not contain sufficient variation to provide useful information to the market. Using a sample of financially stressed initial public offering (IPO) firms, we investigate whether information uncertainty is affected by (1) three different types of audit reports—unqualified (clean), hybrid (with explanatory language about financial stress), and going concern (GCAR)—and (2) audit report disclosures. We provide evidence that audit reports (hybrid and GCAR) and audit report disclosures provide useful information to the market by finding a significant reduction in information uncertainty. Just as important, we find that management discretionary going concern disclosures do not complement or substitute for the reduction in information uncertainty associated with hybrid audit reports and GCARs. We provide evidence that current audit report types and disclosures of financially stressed IPO firms provide information to the market. JEL Classifications: M40; M42; G14. Data Availability: The data used in this study are available from public sources indicated in the paper. [ABSTRACT FROM AUTHOR]

Uncertainty about capabilities, intent, or resolve has long been linked to war. More recently, the bargaining model of war has established uncertainty, also referred to as asymmetric information, as one of the two major causes of costly conflict, the other being the dynamics of commitment in anarchy. A growing theoretical literature has made significant strides in fleshing out causal mechanisms and expanding our understanding of the role of information in conflict onset and how it relates to crisis bargaining and arms races. This article reviews these theoretical developments and describes current efforts to better understand the relationships between information, uncertainty, and war. [ABSTRACT FROM AUTHOR]

The authors examine whether a cognitive bias influences dividend policy. They find that managers use a heaping heuristic when choosing the amount of their firm's dividend. Heaping is a human error or bias to round numbers even though precise values are desired. This bias leads to dividend distributions clustered at specific amounts. Dividend size and the level of information uncertainty faced by management help explain the likelihood of heaping. The authors also observe that heaped dividends are "sticky" and altered less frequently, and when there is a dividend change, heaped dividends are more often switched to another heaped amount. [ABSTRACT FROM AUTHOR]

The paper presents problems of decision-making for planning and implementation of vehicle service system supplies with spare parts under incomplete information. The lack of effective supply planning models using artificial intelligence principles contributes to widening the gap in the problem. The analyses confirm that information uncertainty is one of the main factors in supply failures leading to financial losses for both vehicle service stations and supply companies. Authors structured national vehicle service system by classifying its three different segments. This allowed the identification of risks of making incorrect logistics decisions in each of defined segments. It has been shown that the supply planning process in each of segments is carried out according to different rules. Authorial decision models for each of segments are then presented. The models can be used as a tool to support and improve supplying vehicle service stations in conditions of information uncertainty. In the application part, a proprietary algorithm has been developed to solve proposed models. [ABSTRACT FROM AUTHOR]

This paper examines two potential key drivers of the financial strength (F-Score) investment strategy: information uncertainty and liquidity. We use novel, direct measures of information uncertainty related to the variability of financial strength signals themselves. However, financial strength strategy returns are not generally strongly related to these information uncertainty proxies. We also examine two proxies for liquidity. Financial strength strategy returns are generally substantially larger for illiquid firms. A zero-cost arbitrage strategy based on F-Score generates a 20% return in illiquid UK stocks and 12% in liquid UK stocks. The enhanced F-Score effect is driven by a flight from illiquidity amongst financially weak stocks. Overall, the profitability of the F-Score investment strategy appears more closely related to liquidity than to information uncertainty. [ABSTRACT FROM AUTHOR]

This paper presents an unobservable single-server queueing system with three types of uncertainty, where the service rate, or waiting cost or service quality is random variable that may obtainn(n> 2) values. The information about the realised values of parameters is only known to the server. We are concerned about the server’s behaviour: revealing or concealing the information to customers. Then-value assumption and the server’s behaviour enable us to consider various pricing strategies. In this paper, we analyse the effect of information and uncertainty on profits and make comparisons between the profits under different pricing strategies. Moreover, as for parameter variability reflected by the number of each parameter’s possible choicesn, we observe the effect of variablenon all types of profits and find that revealing the parameter information can much more benefit the server with the increase ofn. [ABSTRACT FROM AUTHOR]

We investigate how firms use information technology (IT) implementation to mitigate an anomaly in capital markets: investors underreacting to new public information. The theory of information uncertainty (IU) suggests that the anomaly is amplified with IU; that is, with ambiguity in information about firm value. We theorize that a firm's IT in general—and enterprise systems (ES) in particular—can mitigate IU, thus reducing the IU-induced underreaction anomaly. Based on a difference-in-differences analysis of a sample of 572 ES implementations, our main finding is that ES implementation does reduce IU-induced underreaction anomaly. This is achieved through a reduction in the firm's fundamentals volatility and an improvement in information quality. We also find that firms with greater IT capability are better positioned to realize the anomaly-reducing benefits of ES implementation and that ES's anomaly-reducing effect is most pronounced when high levels of both functional and operational ES modules are implemented. We obtain remarkably consistent results when using alternate empirical design, samples, and measures of news. Such IT impacts are economically highly consequential because they improve capital market efficiency. This paper was accepted by Anandhi Bharadwaj, information systems. [ABSTRACT FROM AUTHOR]

An implicit premise of much empirical research is that the individual role and the collective role of a financial reporting quality (quality) measure are the same, in the sense that the impacts of a quality measure on a dependent variable, without and with considering the trade-off/interaction and combination with other quality measures, are the same. I question whether the two roles are really the same. I conduct my investigation in the context of information uncertainty. I employ conventional statistical methods to explore the individual role of quality measures and use the decision tree method to explore their collective role. My findings reveal some significant differences between the two roles. Further, the findings indicate that the collective role of a quality measure can differ in accordance with the group to which the quality measure belongs. Overall, the findings reject this premise that the individual and collective roles of quality measures are the same. Moreover, the findings enhance the understanding of the collective role of quality measures. [ABSTRACT FROM AUTHOR]

We propose a shift from the current paradigm of electricity markets treating stochastic producers similarly to conventional ones in terms of their offers. We argue that the producers' offers should be probabilistic to reflect the limited predictability of renewable energy generation, while we should design market mechanisms to accommodate such offers. We argue that the transition from deterministic offers is a natural next step in electricity markets, by analytically proving our proposal's equivalence with a two-price conventional market. [ABSTRACT FROM PUBLISHER]

The paper examines the effectiveness and efficiency of innovative projects under conditions of uncertain information. It discusses classification of the classical types of economies and technological structures through human history; proposes a classification of uncertainty types; discusses the advantages and disadvantages of existing effectiveness and efficiency evaluation methods; and presents an algorithm of innovative strategy formation. Previous studies by the authors of the current paper [Okorokov et al., 2014] analyzed the drawbacks of effectiveness evaluation methods for existing innovative projects. The current study aims to develop the methodology for effectiveness evaluation of innovative projects in the circumstances of increasing amounts of information and uncertainty. For this purpose, the authors used a combination of real options and fuzzy sets approaches, which allowed them to take into account all the necessary information. This paper presents net present value fuzzy evaluation. The proposed technique was implemented in real medium- and large-sized industrial organizations in one of the most innovative regions of Russia -- Saint-Petersburg. The technique allows correction of the innovative projects as they are being implemented. [ABSTRACT FROM AUTHOR]

This paper develops a model of optimal pricing under information uncertainty for fixed-odds betting markets. The model suggests that bookmakers require a premium for quoting the odds several days before an event. This premium reflects the uncertainty of public information that can be exploited by expert bettors. The model predicts that when bookmakers set optimal prices, expected returns to bettors increase as a monotonic function of winning probabilities. In this manner, an information-based explanation is given for the celebrated favourite-longshot bias in fixed-odds. Using an extensive data-set of football odds from two major European bookmakers, we estimate the probability of informed betting. [ABSTRACT FROM AUTHOR]

We examine and compare the extent to which the reaction of investors to earnings announcements is influenced by a firm's governance profile and prevailing market conditions. We find that firms with better governance characteristics experience a larger initial reaction to both good and bad earnings announcements regardless of the prevailing sentiment and uncertainty conditions. However, the influence of governance is constrained to the announcement period. We demonstrate that changes in market uncertainty and/or investor sentiment are related to the post-earnings announcement drift. We also find that a major channel through which greater corporate governance influences the market response to unexpected earnings news is by lowering information uncertainty and so providing greater clarity of the implication of the news for firm value. Finally, we establish that two types of uncertainties (market and information) have very different influence on investor's response to information signals. JEL Classification: D81, G10, G14, G30, G32 [ABSTRACT FROM AUTHOR]

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I provide a risk-based rational explanation for the seasonal regularity of January in stock returns by suggesting a common risk factor related to the information uncertainty caused by earnings volatility. When the two-factor model with the market risk factor and this common risk factor is used, there is a remarkable improvement in explaining the January effect. With the adjustment of raw returns for risk through this two-factor model, the systematic pattern in the residual returns across firm size disappears. This risk factor also dominates the other risk factors in explaining the cross section of stock returns in January. [ABSTRACT FROM AUTHOR]

Purpose – Prior research has documented the role of information uncertainty in the cross-sectional variation in stock returns. Miller (1977) hypothesizes that if information uncertainty is caused by differences of opinion, prices will reflect only the positive beliefs due to short-sale constraints. These anomalous stock price behaviors may result from mispricing. In contrast, Merton (1974) asserts that default risk is a function of the uncertainty in the asset value process. Information uncertainty may be subsumed by credit or default risk. The paper aims to discuss these issues. Design/methodology/approach – The authors employ various sorting techniques and Fama-MacBeth Regressions to test the hypotheses. Findings – The authors provide empirical evidence consistent with Merton’s (1974) default risk hypothesis and inconsistent with Miller’s (1977) mispricing hypothesis. Research limitations/implications – Risk aversion and not misplacing is the primary factor driving information-related anomalies in equities markets. Practical implications – It would be quite difficult to find arbitrage opportunities in equities markets because there appears to be little, if any, mis-pricing due to information uncertainties. Originality/value – This study provides important information about the primary underlying information-related source of certain empirical anomalies in the cross-section of stock returns. [ABSTRACT FROM AUTHOR]

The analysis demonstrates that the relevant focus of economics is on the middle ground between perfect knowledge and total ignorance. Individual action always involves uncertainty because, as Mises emphasizes, uncertainty about the future and human action are two aspects of the same thing. The implications of uncertainty for human action are explored in a number of different contexts. Under uncertainty, profit maximization loses meaning as a guide to action and 'market failure' loses meaning and relevance as a guide for public policy. The paradox of omniscience, considered as perfect knowledge or the absence of uncertainty, is explored for individual decision making, profits and public policy. The findings support Hayek's thesis that knowledge is likely to be used most effectively if information is controlled by those whose knowledge and success depend on it. [ABSTRACT FROM PUBLISHER]

Background and objective: The need for long-term treatment and frequent visits to treatment centers for hemodialysis can lead to psychological problems such as Uncertainty about Disease and Treatment (UC about D&T) in patients with chronic kidney failure. In order to understand uncertainty about disease and treatment and to plan for preventive measures and care interventions in various dimensions, there is a need for reliable and valid tools. The present study was conducted to design and psychometrically evaluate the Uncertainty about Disease and Treatment Scale (UC about D&TS) in patients undergoing hemodialysis. Methods: This study is of a methodological type and conducted in two stages. The first stage included a deductive (literature review) and an inductive approach (face-to-face interviews). In the second stage, psychometric indices of the UC about D&TS, including face validity (qualitative-quantitative), content validity (qualitative-quantitative), construct validity (exploratory factor analysis), and reliability (using Cronbach's alpha and McDonald's omega) were examined. Results: In the literature review stage, 66 items were extracted, and in the qualitative stage, 48 items were extracted. After merging similar items, 29 items were entered into the psychometric process. No items were removed in the face and content validity stages. In the construct validity stage, five factors were extracted, including self-uncertainty, uncertain situation, uncertain future, uncertainty of treatment outcomes, and information uncertainty, which constituted a total of 82.16% of the total variance. In this stage, five items were removed from the study due to a corrected item-total correlation below 0.32, and four items were removed due to cross-loading. The α and Ω were calculated as 0.828 and 0.818, respectively. The measurement stability and standard error of measurement were estimated at 0.977 and 2.019, respectively. Conclusion: The results showed that the UC about D&TS is a valid and reliable measure for patients undergoing hemodialysis. This scale is specifically designed to measure UC about D&T in hemodialysis patients, and it is recommended that healthcare providers (Hcps) use this scale in follow-up visits. [ABSTRACT FROM AUTHOR]

We investigate the joint effects of analyst reputation, uncertainty and guidance news valence on analysts' reliance on management guidance. We find that, compared to less reputable analysts, reputable analysts rely less on guidance when they issue earnings forecasts. This analyst reputation effect is stronger when earnings and information uncertainty are higher or when the guidance contains good news. Further analysis suggests that both reputable and less reputable analysts sacrifice their forecast accuracy when they rely less on guidance; however, reputable analysts are compensated to a greater extent by the increased informativeness of their forecasts. Finally, we find that analysts' future career advancement is enhanced when their reliance is low. [ABSTRACT FROM AUTHOR]

Technological innovation within the firm can be modelled as a process of uncertainty reduction. The four major sources of uncertainty are user needs, technological environments, competitive environments, and organizational resources. Reducing these uncertainties is the responsibility of the marketing and R&D functions within the firm. Because these functions are reciprocally interdependent, their success in reducing uncertainty requires integration and collaboration between them. A contingency framework is developed which shows the effect and the determinants of interfunctional information transfer. It is argued that the synergistic results of integration can best be understood as a within-role increase of uncertainty reduction, and a between-role convergence of functional uncertainty reduction. The implications of the model are discussed. [ABSTRACT FROM AUTHOR]

This study examines the determinants of goodwill overstatement at the time of mergers in a Korean setting. In the Korean M&A market, there are two types of mergers: mergers between independent companies (non‐affiliated mergers) and mergers between companies under common control (affiliated mergers). This study extends the literature by examining the factors likely to cause goodwill overstatement in both types of mergers. The results reveal that in affiliated mergers, goodwill at the time of a merger tends to be overstated when controlling owners have higher equity ownership in the target than in the acquirer. By contrast, information uncertainty in the target value causes initial goodwill overstatement in non‐affiliated mergers. We also find that monitoring of independent institutional investors with concentrated holdings against overpaying for the target is more pronounced when controlling owners in affiliated mergers have incentives to overpay for the target. In affiliated mergers, acquirers tend to write off goodwill more frequently when controlling owners have higher equity ownership in the target than in the acquirer. In non‐affiliated mergers, information uncertainty in the target value is significantly associated with subsequent goodwill write‐offs. These results suggest that the type of merger has important consequences for initial goodwill recognition and subsequent impairment. [ABSTRACT FROM AUTHOR]

The purpose of this study was to understand the communication patterns of leaders at the Faculty of Economics in responding to information uncertainty at the University of South Sumatra, and to find out the driving and inhibiting factors. The phenomenon of the transfer of leadership from one group of actors to another is a big enough problem, that between the Dean and subordinates in terms of organizational structure, there is no one-unit relationship within the organization. Types of qualitative research. The number of informants was 6 people, using a purposive sampling technique. The data collection tool is interview. Data analysis techniques according to iMiles and Huberman. This research uses Weick's organizational communication theory with 3 dimensions namely, Enactment, Selection, and Retention. The results of the study, (1) Enactment, show that communication between leaders and subordinates in informing campus policies is not optimal with the presence of miss communication, the delivery of information is still to certain members (2) Selection, showing the dean is not optimal in providing clarity of information so that the information received is less relevant to the task being performed. (3) Retention, that everyone working at the University of South Sumatra already has their respective duties and structures within the organization. Obstacle factors occur in the Faculty of Management organization such as miscommunication, bad weather causing difficulties to communicate from long distances. Besides that, things to support are the policies and work programs of the Dean so that he has the right to manage his subordinates, the facilities are given by the foundation, and a salary. [ABSTRACT FROM AUTHOR]

Although individuals generally avoid negative information, recent research documents that they voluntarily explore negative information to resolve uncertainty. However, it remains unclear (a) whether uncertainty facilitates exploration similarly when exploration is expected to lead to negative, neutral, or positive information, and (b) whether older adults seek negative information to reduce uncertainty like younger adults do. This study addresses the two issues across four experimental studies (N = 407). The results indicate that individuals are more likely to expose themselves to negative information when uncertainty is high. In contrast, when information was expected to be neutral or positive, the uncertainty surrounding it did not significantly alter individuals' exploration behavior. Furthermore, we found that uncertainty increased the exploration of negative information in both older and younger adults. In addition, both younger and older adults chose to explore negative information to reduce uncertainty, even when there were positive or neutral alternatives. In contrast to the age-related similarities in these behavioral measures, older adults demonstrated reduced scores in questionnaires on sensation seeking and curiosity, relative to their counterparts who were younger. These results suggest that information uncertainty has a selective facilitation effect on exploration for negative information and that normal aging does not alter this tendency, despite age-related reductions in self-reported measures of personality traits relevant to information seeking. [ABSTRACT FROM AUTHOR]