scholarly journals Risk and emotion: measuring the effect of emotions and other visceral factors on decision making under risk

2021 ◽  
Author(s):  
Michael Geoffrey Mihalicz
Keyword(s):  
Public Relations ◽  
Loss Aversion ◽  
Risk Preference ◽  
Mathematical Psychology ◽  
Model Parameters ◽  
Individual Choice ◽  
Cognitive Limitations ◽  
Interdisciplinary Field ◽  
The Impact ◽  
Visceral Factors

The science of modelling choice preferences has evolved into an interdisciplinary field contributing to several branches of microeconomics and mathematical psychology. As theories in decision science and related fields mature, descriptive theories have emerged to explain systematic violations of rationality through cognitive mechanisms underlying the thought processes that guide human behaviour. Cognitive limitations are not, however, solely responsible for systematic deviations from rationality and there is a growing body of literature exploring the effect of visceral factors as the more dominant drivers. This study builds on the existing literature by investigating the impact of anger, sadness, happiness, anxiety, hunger, energy, tiredness and stress on three distinct elements that define risk preference: utility, decision weights and loss aversion. By decomposing the impact of visceral factors on risk preference, I am able to provide evidence supporting the proposition that a portion of the variability in individual choice preferences can be explained by interacting visceral states. My findings suggest that visceral factors have the strongest effect on loss aversion, which is a major factor in how people code and evaluate financial outcomes. Anger, sadness, happiness, anxiety, energy and tiredness each affect five or more of the model parameters, while hunger and stress are significant only in their interaction with other visceral factors. I also provide evidence to show that the generalized approaches to characterizing visceral factors and risk preference are too broad to be descriptively meaningful. The results of this study show that emotions and other drive states effect the way people process and interpret information, which is crucial in informing decision-makers of the sources and consequences of irrational behaviour. These findings will be of immediate interest to wealth management specialists, public relations advisers as well as to engineers in designing socially intelligent machines capable of interacting more effectively with humans.

scholarly journals Risk and emotion: measuring the effect of emotions and other visceral factors on decision making under risk

2021 ◽  
Author(s):  
Michael Geoffrey Mihalicz
Keyword(s):  
Public Relations ◽  
Loss Aversion ◽  
Risk Preference ◽  
Mathematical Psychology ◽  
Model Parameters ◽  
Individual Choice ◽  
Cognitive Limitations ◽  
Interdisciplinary Field ◽  
The Impact ◽  
Visceral Factors

The science of modelling choice preferences has evolved into an interdisciplinary field contributing to several branches of microeconomics and mathematical psychology. As theories in decision science and related fields mature, descriptive theories have emerged to explain systematic violations of rationality through cognitive mechanisms underlying the thought processes that guide human behaviour. Cognitive limitations are not, however, solely responsible for systematic deviations from rationality and there is a growing body of literature exploring the effect of visceral factors as the more dominant drivers. This study builds on the existing literature by investigating the impact of anger, sadness, happiness, anxiety, hunger, energy, tiredness and stress on three distinct elements that define risk preference: utility, decision weights and loss aversion. By decomposing the impact of visceral factors on risk preference, I am able to provide evidence supporting the proposition that a portion of the variability in individual choice preferences can be explained by interacting visceral states. My findings suggest that visceral factors have the strongest effect on loss aversion, which is a major factor in how people code and evaluate financial outcomes. Anger, sadness, happiness, anxiety, energy and tiredness each affect five or more of the model parameters, while hunger and stress are significant only in their interaction with other visceral factors. I also provide evidence to show that the generalized approaches to characterizing visceral factors and risk preference are too broad to be descriptively meaningful. The results of this study show that emotions and other drive states effect the way people process and interpret information, which is crucial in informing decision-makers of the sources and consequences of irrational behaviour. These findings will be of immediate interest to wealth management specialists, public relations advisers as well as to engineers in designing socially intelligent machines capable of interacting more effectively with humans.

Prinsip Kearifan Lokal dalam Pengembangan Strategi Kehumasan pada Pemerintah Daerah Kabupaten Bandung

2020 ◽  
Vol 4 (2) ◽  
pp. 229-248
Author(s):  
Betty Tresnawaty
Keyword(s):  
Public Relations ◽  
Local Knowledge ◽  
Case Study Approach ◽  
West Java ◽  
Study Approach ◽  
Positive Image ◽  
The Government ◽  
The Impact ◽  
Public Relations Strategy

Public Relations of the Bandung Regency Government realizes that its area has a lot of potential for various local wisdom and has a heterogeneous society. This study aims to explore and analyze the values of local knowledge in developing public relations strategies in the government of Bandung Regency, West Java province. This study uses a constructivist interpretive (subjective) paradigm through a case study approach. The results showed that the Bandung Regency Government runs its government based on local wisdom. Bandung Regency Public Relations utilizes local insight and the region's potential to develop a public relations strategy to build and maintain a positive image of Bandung Regency. The impact of this research is expected to become a source of new scientific references in the development of public relations strategies in every region of Indonesia, which is very rich with various philosophies.Humas Pemerintah Kabupaten Bandung menyadari wilayahnya memiliki banyak potensi kearifan lokal yang beragam, serta memiliki masyarakatnya yang heterogen. Penelitian ini bertujuan menggali dan menganalisis nilai-nilai kearifan lokal dalam pengembangan strategi kehumasan di pemerintahan Kabupaten Bandung provinsi Jawa Barat.  Penelitian ini menggunakan paradigma interpretif (subjektif) konstruktivis melalui pendekatan studi kasus. Hasil penelitian menunjukkan bahwa Pemerintah Kabupaten (Pemkab) Bandung menjalankan pemerintahannya berlandaskan pada kearifal lokal. Humas Pemkab Bandung memanfaatkan kearifan lokal dan potensi wilayahnya untuk mengembangkan strategi humas dalam membangun dan mempertahankan citra positif Kabupaten Bandung.Dampak penelitian ini diharapkan menjadi sumber rujukan ilmiah baru dalam pengembangan strategi kehumasan di setiap daerah Indonesia yang sangat kaya dengan beragam filosofi. 

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

The impact of the new media on public relations in the public administration in Kurdistan Region

2019 ◽  
Vol 7 (1) ◽  
pp. 268-288
Author(s):  
Dlan Ismail Mawlud ◽  
Hoshyar Mozafar Ali
Keyword(s):  
Information Technology ◽  
New Media ◽  
Public Relations ◽  
Public Administration ◽  
Management System ◽  
Theoretical Research ◽  
Kurdistan Region ◽  
The Public ◽  
Government Institutions ◽  
The Impact

The development of technology, information technology and various means of communication have a significant impact on public relations activity; especially in government institutions. Many government institutions have invested these means in their management system, in order to facilitate the goals of the institution, and ultimately the interaction between the internal and external public. In this theoretical research, I tried to explain the impact of the new media on public relations in the public administration, based on the views of specialists. The aim of the research is to know the use of the new media of public relations and how in the system of public administration, as well as, Explaining the role it plays in public relations activities of government institutions. Add to this, analyzing the way of how new media and public relations participate in the birth of e-government. In the results, it is clear that the new media has facilitated public relations between the public and other institutions, as it strengthened relations between them

Market Reactions to a High-Quality Auditor and Managerial Preference for Audit Quality

2019 ◽  
Vol 38 (4) ◽  
pp. 131-149 ◽  
Author(s):  
Patrick J. Hurley ◽  
Brian W. Mayhew
Keyword(s):  
Loss Aversion ◽  
Audit Quality ◽  
Data Availability ◽  
Quality Competition ◽  
High Quality ◽  
Market Reactions ◽  
Comprehensive Theory ◽  
Audit Reports ◽  
The Impact ◽  
Quality Theory

SUMMARY We insert an automated high-quality (HQ) auditor into established experimental audit markets to test the impact of high-quality competition on other auditors' supply of and managers' demand for audit quality. Theory predicts that managers will demand high levels of audit quality to avoid investors' price-protecting behavior. This demand should result in the HQ auditor dominating the market and increase other auditors' audit quality provision to compete with the HQ auditor. However, we find that the HQ auditor does not dominate the market—despite holding audit costs constant and investors placing a premium on HQ auditor reports. We also find that adding an HQ auditor results in other auditors lowering audit quality. Additional analyses indicate some managers demand lower audit quality to avoid negative audit reports, consistent with loss aversion as a potential explanation. Our findings indicate a need to develop a more comprehensive theory of the demand for auditing. Data Availability: The laboratory market data used in this study are available from the authors upon request.

scholarly journals Evolution of disease transmission during the COVID-19 pandemic: patterns and determinants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Clustering Algorithm ◽  
Health Interventions ◽  
Transmission Model ◽  
Model Parameters ◽  
Public Health Interventions ◽  
Forecasting Accuracy ◽  
Time Lagged ◽  
The Impact

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

scholarly journals A Model-Based Tool for Assessing the Impact of Land Use Change Scenarios on Flood Risk in Small-Scale River Systems—Part 1: Pre-Processing of Scenario Based Flood Characteristics for the Current State of Land Use

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 102
Author(s):  
Frauke Kachholz ◽  
Jens Tränckner
Keyword(s):  
Land Use ◽  
River Flow ◽  
Land Use Changes ◽  
Small Rivers ◽  
Small Scale ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Model Based ◽  
Current State ◽  
The Impact

Land use changes influence the water balance and often increase surface runoff. The resulting impacts on river flow, water level, and flood should be identified beforehand in the phase of spatial planning. In two consecutive papers, we develop a model-based decision support system for quantifying the hydrological and stream hydraulic impacts of land use changes. Part 1 presents the semi-automatic set-up of physically based hydrological and hydraulic models on the basis of geodata analysis for the current state. Appropriate hydrological model parameters for ungauged catchments are derived by a transfer from a calibrated model. In the regarded lowland river basins, parameters of surface and groundwater inflow turned out to be particularly important. While the calibration delivers very good to good model results for flow (Evol =2.4%, R = 0.84, NSE = 0.84), the model performance is good to satisfactory (Evol = −9.6%, R = 0.88, NSE = 0.59) in a different river system parametrized with the transfer procedure. After transferring the concept to a larger area with various small rivers, the current state is analyzed by running simulations based on statistical rainfall scenarios. Results include watercourse section-specific capacities and excess volumes in case of flooding. The developed approach can relatively quickly generate physically reliable and spatially high-resolution results. Part 2 builds on the data generated in part 1 and presents the subsequent approach to assess hydrologic/hydrodynamic impacts of potential land use changes.

scholarly journals Modeling Bacterial Regrowth and Trihalomethane Formation in Water Distribution Systems

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 463
Author(s):  
Gopinathan R. Abhijith ◽  
Leonid Kadinski ◽  
Avi Ostfeld
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Mechanistic Model ◽  
Water Distribution Systems ◽  
Sensitivity Study ◽  
Operating Conditions ◽  
Growth Rate Constant ◽  
Model Parameters ◽  
Bacterial Regrowth ◽  
The Impact

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.

scholarly journals Constrained Parameter Estimation for a Mechanistic Kinetic Model of Cobalt–Hydrogen Electrochemical Competition during a Cobalt Removal Process

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 387
Author(s):  
Yiting Liang ◽  
Yuanhua Zhang ◽  
Yonggang Li
Keyword(s):  
Parameter Estimation ◽  
Kinetic Model ◽  
Model Parameters ◽  
Hydrogen Ions ◽  
Removal Process ◽  
Cobalt Removal ◽  
Estimation Scheme ◽  
Zinc Hydrometallurgy ◽  
The Impact ◽  
Parameter Estimation Scheme

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.

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