scholarly journals Short and/or long-term investment choice: Artificial intelligence analysis of the role of both or-ganizational and behavioral determinants

2022 ◽  
Vol 6 (1) ◽  
pp. 155-164 ◽  
Author(s):  
Fadhila Hamza
Keyword(s):  
Artificial Intelligence ◽  
Locus Of Control ◽  
Important Variable ◽  
Intelligence Analysis ◽  
Investment Horizon ◽  
Behavioral Determinants ◽  
Investment Choice ◽  
Organizational Determinants ◽  
The Impact

This paper shows empirically the impact of organizational and behavioral determinants on the CEO's investment horizon choice, using artificial intelligence explanatory methods. We apply our approach to 100 Saudi firms. We test the effect of three organizational determinants: ownership concentration, board independence, and CEO remuneration system; and three behavioral determinants: myopia, the locus of control and commitment, on the CEO's investment horizon choice. The study’s key finding is that executives' commitment bias is the most important variable in terms of modal value that affects firms' long-term investment choice. We also find a positive and significant relationship between myopia and long-term investment choice, whereas the lowliest determinant of the horizon choice is the locus of control. More generally, these results show that CEOs who are likely to be the most myopic may display long-term behavior with the existence of high cognitive involvement.

The Impact of Artificial Intelligence and Virtual Personal Assistants on Marketing

2018 ◽  
pp. 5748-5756 ◽  
Author(s):  
Christina L. McDowell Marinchak ◽  
Edward Forrest ◽  
Bogdan Hoanca
Keyword(s):  
Artificial Intelligence ◽  
Customer Satisfaction ◽  
Security Requirements ◽  
Marketing Effort ◽  
Ethical Implications ◽  
Personal Assistants ◽  
Customer Trust ◽  
The Impact

This entry will review the state of the art in AI, with a particular focus on applications in marketing. Based on the current capabilities of AI in marketing, the author's explore the new rules of engagement. Rather than simply targeting consumers, the marketing effort will also be directed at the algorithms controlling the consumers' virtual personal assistants (VPAs). Rather than exploiting human desires and weakness, marketing will need to focus on meeting the user's actual needs. The level of customer satisfaction will be even more critical as marketing will need to focus on establishing and maintaining a reputation in competition with those of similar offerings in the marketplace. This entry concludes with thoughts on the long-term implications, exploring the role of customer trust in the adoption of AI agents, the security requirements for agents and the ethical implications of access to such agents.

Artificial Intelligence, Smart Classrooms and Online Education in the 21st Century

2019 ◽  
Vol 21 (3) ◽  
pp. 66-79 ◽  
Author(s):  
Ikedinachi A. P. WOGU ◽  
Sanjay Misra ◽  
Patrick A. Assibong ◽  
Esther Fadeke Olu-Owolabi ◽  
Rytis Maskeliūnas ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Online Education ◽  
Human Development ◽  
21St Century ◽  
Education Sector ◽  
Factor Method ◽  
Ex Post ◽  
The Impact ◽  
Smart Classrooms

The advent of artificial intelligence (AI) technology in the education sector has largely taken over conventional classrooms and revolutionized the way education is conducted to the admiration of many. Other scholars however, believe that such early celebration of AI benefits is unfounded and inimical to the education sector since the adoption of modern AI teaching systems now raises long-term issues about the relevance of teachers and their classrooms in 21st Century AI education. The Marxian Alienation Theory was adopted for the article. The Ex-post factor method and Derrida's critical method of analysis was utilized for attaining the objectives of the article. The article faults recent attempts at eulogizing the impact of AI innovations in the education sector and on human development. Extensive research is proposed as necessary for contemporary scholars of AI and education technologist before proper appropriation can be made about its gains in education and on human development.

scholarly journals Yet another lockdown? A large-scale study on people's unwillingness to be confined during the first 5 months of the COVID-19 pandemic in Spain

2021 ◽  
Author(s):  
Marina Martinez-Garcia ◽  
Alejandro Rabasa ◽  
Xavier Barber ◽  
Kristina Polotskaya ◽  
Kristof Roomp ◽  
...  
Keyword(s):  
Large Scale ◽  
Psychological Impact ◽  
Important Variable ◽  
Decision Makers ◽  
Policy Makers ◽  
Time Period ◽  
Economic Support ◽  
Gender And Age ◽  
The Impact

Population confinements have been one of the most widely adopted non-pharmaceutical interventions (NPIs) implemented by governments across the globe to help contain the spread of the SARS-CoV-2 virus. While confinement measures have been proven to be effective to reduce the number of infections, they entail significant economic and social costs. Thus, different policy makers and social groups have exhibited varying levels of acceptance of this type of measures. In this context, understanding the factors that determine the willingness of individuals to be confined during a pandemic is of paramount importance, particularly, to policy and decision-makers. In this paper, we study the factors that influence the unwillingness to be confined during the COVID-19 pandemic by means of a large-scale, online population survey deployed in Spain. We apply both quantitative (logistic regression) and qualitative (automatic pattern discovery) methods and consider socio-demographic, economic and psychological factors, together with the 14-day cumulative incidence per 100,000 inhabitants. Our analysis of 109,515 answers to the survey covers data spanning over a 5-month time period to shed light on the impact of the passage of time. We find evidence of pandemic fatigue as the percentage of those who report an unwillingness to be in confinement increases over time; we identify significant gender differences, with women being generally less likely than men to be able to sustain long-term confinement of at least 6 months; we uncover that the psychological impact was the most important factor to determine the willingness to be in confinement at the beginning of the pandemic, to be replaced by the economic impact as the most important variable towards the end of our period of study. Our results highlight the need to design gender and age specific public policies, to implement psychological and economic support programs and to address the evident pandemic fatigue as the success of potential future confinements will depend on the population's willingness to comply with them.

scholarly journals Exploring the impact of Artificial Intelligence and robots on higher education through literature-based design fictions

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
A. M. Cox
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Future Scenarios ◽  
Narrative Literature ◽  
Narrative Literature Review ◽  
Long Term Impact ◽  
The Impact ◽  
And Robotics ◽  
Potential Use

AbstractArtificial Intelligence (AI) and robotics are likely to have a significant long-term impact on higher education (HE). The scope of this impact is hard to grasp partly because the literature is siloed, as well as the changing meaning of the concepts themselves. But developments are surrounded by controversies in terms of what is technically possible, what is practical to implement and what is desirable, pedagogically or for the good of society. Design fictions that vividly imagine future scenarios of AI or robotics in use offer a means both to explain and query the technological possibilities. The paper describes the use of a wide-ranging narrative literature review to develop eight such design fictions that capture the range of potential use of AI and robots in learning, administration and research. They prompt wider discussion by instantiating such issues as how they might enable teaching of high order skills or change staff roles, as well as exploring the impact on human agency and the nature of datafication.

scholarly journals The Discerning Ear: Cardiac Auscultation in the Era of Artificial Intelligence and Telemedicine

2021 ◽  
Author(s):  
Vivek Jani ◽  
David A Danford ◽  
W Reid Thompson ◽  
Andreas Schuster ◽  
Cedric Manlhiot ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Computer Assisted ◽  
Cardiac Auscultation ◽  
Cardiac Murmur ◽  
New Era ◽  
History Of ◽  
The Impact ◽  
Paradigm Shifting ◽  
Insight Into

Abstract Heart murmur, a thoracic auscultatory finding of cardiovascular origin, is extremely common in childhood and can appear at any age from premature newborn to late adolescence. The objective of this review is to provide a modern examination and update of cardiac murmur auscultation in this new era of artificial intelligence and telemedicine. First, we provide a comprehensive review of the causes and differential diagnosis, clinical features, evaluation, and long-term management of pediatric heart murmurs. Next, we provide a brief history of computer-assisted auscultation and murmur analysis, along with insight into the engineering design of the digital stethoscope. We conclude with a discussion of the paradigm shifting impact of deep learning on murmur analysis, artificial intelligence assisted auscultation, and the implications of these technologies on telemedicine in pediatric cardiology. It is our hope that this article provides an updated perspective on the impact of artificial intelligence on cardiac auscultation for the modern pediatric cardiologist.

Interwell Saturation Prediction by Artificial Intelligence Analysis of Well Logs

2021 ◽  
Author(s):  
Dmitry Kovalev ◽  
Sergey Safonov ◽  
Klemens Katterbauer ◽  
Alberto Marsala
Keyword(s):  
Artificial Intelligence ◽  
Model Parameters ◽  
Intelligence Analysis ◽  
Network Architectures ◽  
Multiple Sampling ◽  
Primary Fluid ◽  
Local Saturation ◽  
Well Log Analysis ◽  
Improved Accuracy ◽  
The Impact

Abstract Well log analysis, through deploying advanced artificial intelligence (AI) algorithms, is key for wellbore geological studies. By analyzing different well characteristics with modern AI tools it becomes possible to estimate interwell saturation with improved accuracy, outlining primary fluid channels and saturation propagations in the reservoirs interwell region. The development of modern deep learning and artificial intelligence methods allows analysts to predict interwell saturation as a function of observed data in the near wellbore logged geological layers. This work addresses the use of deep neural network architectures as well as tensor regression models for predicting interwell saturation from other well characteristics, such as resistivity and porosity, as well as local near-well saturation. Several algorithms are compared in terms of both accuracy and computational efficiency. Sensitivity analysis for model parameters is carried out, which is based on the wells’ geometry, radius, and multiple sampling techniques. Additionally, the impact of local saturation prior knowledge on the model accuracy is analyzed. A reservoir box model encompassing volumetric interwell porosity, resistivity and saturation data was utilized for the validating and testing of the AI algorithms. A prototype is developed with Python 3.6 programming language.

A new typology of health behaviours for personality‐health predictions: The case of locus of control

1991 ◽  
Vol 5 (2) ◽  
pp. 151-168
Author(s):  
Tina K. Rosolack ◽  
Sarah E. Hampson
Keyword(s):  
Health Care ◽  
Locus Of Control ◽  
Perceived Control ◽  
Predictor Variable ◽  
Health Behaviours ◽  
Personal Control ◽  
Personality Variables ◽  
The Impact ◽  
Perceived Personal Control

Psychological investigations of the impact of personality on health behaviours have tended to emphasize fine distinctions among personality variables while failing to distinguish among different kinds of behaviours. For example, theoretical treatments of perceived personal control are quite sophisticated; in contrast, only one well‐known analysis of health behaviours exists. We propose four categories of health‐enhancing behaviours, which take into account contemporary views of the shift in health care from acute and physician‐directed actions to long‐term and patient‐directed efforts. In addition, we suggest that perceived control (we emphasize locus of control because of its generality and parsimony) is an important predictor variable when combined with other factors common to current models of health behaviour.

scholarly journals The Impact of Big Data Processing Framework for Artificial Intelligence within Corporate Marketing Communication

2018 ◽  
Vol 7 (4.34) ◽  
pp. 384
Author(s):  
Muhamad Fazil Ahmad
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Marketing Communication ◽  
Short Term ◽  
The Impact ◽  
Processing Framework

This research examines what impact the Big Data Processing Framework (BDPF) has on Artificial Intelligence (AI) applications within Corporate Marketing Communication (CMC), and thereby the research question stated is: What is the potential impact of the BDPF on AI applications within the CMC tactical and managerial functions? To fulfill the purpose of this research, a qualitative research strategy was applied, including semi-structured interviews with experts within the different fields of examination: management, AI technology and CMC. The findings were analyzed through performing a thematic analysis, where coding was conducted in two steps. AI has many useful applications within CMC, which currently mainly are of the basic form of AI, so-called rule-based systems. However, the more complicated communication systems are used in some areas. Based on these findings, the impact of the BDPF on AI applications is assessed by examining different characteristics of the processing frameworks. The BDPF initially imposes both an administrative and compliance burden on organizations within this industry, and is particularly severe when machine learning is used. These burdens foremost stem from the general restriction of processing personal data and the data erasure requirement. However, in the long term, these burdens instead contribute to a positive impact on machine learning. The timeframe until enforcement contributes to a somewhat negative impact in the short term, which is also true for the uncertainty around interpretations of the BDPF requirements. Yet, the BDPF provides flexibility in how to become compliant, which is favorable for AI applications. Finally, BDPF compliance can increase company value, and thereby incentivize investments into AI models of higher transparency. The impact of the BDPF is quite insignificant for the basic forms of AI applications, which are currently most common within CMC. However, for the more complicated applications that are used, the BDPF is found to have a more severe negative impact in the short term, while it instead has a positive impact in the long term.   

The Impact of Artificial Intelligence and Virtual Personal Assistants on Marketing

2019 ◽  
pp. 610-619
Author(s):  
Christina L. McDowell Marinchak ◽  
Edward Forrest ◽  
Bogdan Hoanca
Keyword(s):  
Artificial Intelligence ◽  
Customer Satisfaction ◽  
Security Requirements ◽  
Marketing Effort ◽  
Ethical Implications ◽  
Personal Assistants ◽  
Customer Trust ◽  
The Impact

This chapter will review the state of the art in AI, with a particular focus on applications in marketing. Based on the current capabilities of AI in marketing, the authors explore the new rules of engagement. Rather than simply targeting consumers, the marketing effort will also be directed at the algorithms controlling the consumers' virtual personal assistants (VPAs). Rather than exploiting human desires and weaknesses, marketing will need to focus on meeting the user's actual needs. The level of customer satisfaction will be even more critical as marketing will need to focus on establishing and maintaining a reputation in competition with those of similar offerings in the marketplace. This chapter concludes with thoughts on the long-term implications, exploring the role of customer trust in the adoption of AI agents, the security requirements for agents, and the ethical implications of access to such agents.

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