Can Artificial Intelligence Help Optimize the Public Budgeting Process? Lessons about Smartness and Public Value from the Mexican Federal Government

2020 ◽  
Author(s):  
Vanessa Fernandez-Cortez ◽  
David Valle-Cruz ◽  
J. Ramon Gil-Garcia
Keyword(s):  
Artificial Intelligence ◽  
Federal Government ◽  
Public Budgeting ◽  
Public Value ◽  
The Public ◽  
Budgeting Process

Public budgetary roles in Iran: perceptions and consequences

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farzaneh Jalali Aliabadi ◽  
Graham Gal ◽  
Bita Mashyekhi
Keyword(s):  
Transition Process ◽  
Budget Process ◽  
Public Budgeting ◽  
Content Type ◽  
Roles And Responsibilities ◽  
The Public ◽  
The Government ◽  
The Impact ◽  
Practical Implications ◽  
Budgeting Process

Purpose This study aims to examine the public budgeting process in the higher education and research sectors of Iran. It focuses on the actors’ budgetary roles and uses their perspectives to identify deficiencies in the budgeting process that cause delays in the transition to a performance-based system. Design/methodology/approach This study uses an interpretive research paradigm. It applies the grounded theory methodology to analyze the interviews conducted with those responsible for budgeting at Iranian public universities and research institutes (PURI). The results are interpreted using Wildavsky’s (1964) budgetary roles paradigm. Findings Using Wildavsky’s (1964) paradigm, “spenders” and “guardians” are identified and their perceptions about the public budgeting process are described. The results suggest a decoupling between the actors’ perceptions based on their budgetary roles. Spenders consider budgeting as a negotiation-based process, while guardians’ decisions are largely based on “outputs” and “information.” This study demonstrates that the disagreement over the perceived budget process was due to different budgetary roles. This disagreement leads to delays in the transformation of the budget process in Iranian PURI. Research limitations/implications While efforts are made to obtain a sample of individuals with different roles and responsibilities, the selection is limited by subjects’ willingness and availability. Therefore, sample size and diversity are potential limitations of this study. Practical implications When organizations attempt to transition to performance-based budgeting (PBB), it is critical to understand the current budgeting process to identify potential impediments. Understanding these impediments allows for alternate approaches to be considered. This is particularly important for universities that are mostly funded by the government (such as those in Iran). The results of this study show that the contradictory perceptions among budget actors have a significant impact on budgeting transition and require attention to understand budgeting decisions. Originality/value This study contributes to the budgeting literature in three ways. First, it examines the impact of endogenized shared values among budget participants on the budgeting transition process. Second, by focusing on budgetary roles, it contributes to the literature by examining disagreement on the perceived budgeting process and its implications for transforming the process into PBB. Finally, to the authors’ knowledge, this is the first study to examine the public budgeting process in a developing country – Iran.

Big Data and the Economics of TV Broadcasting. Where is the Public Value?

MedienJournal ◽  
2017 ◽  
Vol 41 (3) ◽  
pp. 15-28 ◽  
Author(s):  
Paul Clemens Murschetz
Keyword(s):  
Big Data ◽  
Public Value ◽  
The Public ◽  
Tv Broadcasting

Der vorliegende Beitrag untersucht Potenziale und Risiken von Big Data für das Leitmedium Fernsehen. Er nimmt dabei eine betont kritisch-normative Perspektive aus Sicht der Medienökonomie ein und analysiert diese anhand des Beispiels Konvergenzfernsehen. Eine der vielen Dimensionen von Big Data ist nämlich die Analyse des Nutzungsverhaltens einer Vielzahl von Konsumenten. Big Data-Dienste verwenden die Analyseergebnisse nicht nur dazu, individuelle Filmempfehlungen zu geben, sondern entscheiden vielmehr darüber, welche Inhalte überhaupt in das Portfolio eines Anbieters aufgenommen bzw. produziert werden. Auch wenn diese Dienste zu einer Optimierung von TV-Vermarktung führen, ist bis heute umstritten, inwiefern Big Data auch Mehrwert für Nutzer generiert. Auf der Sollseite stehen Überwachung, die Frageder Individualisierung und Rationalisierung des Konsums und generell die Kommodifizierung des Mediums.

Motivations of Federal Workers to Volunteer In Public Sector Special Events

2020 ◽  
Vol 24 (1) ◽  
pp. 33-46
Author(s):  
Keon Artis ◽  
Seung Hyun Lee
Keyword(s):  
Public Sector ◽  
Federal Government ◽  
Event Management ◽  
Theoretical Contribution ◽  
The Public ◽  
Factors Associated ◽  
Special Event ◽  
Special Events ◽  
Public Sector Employees ◽  
Government Workers

Volunteers are considered a core component of special events and they have proved to be an asset to the execution of special events. Although motivations of volunteers have received a great deal of attention from many organizations and individuals in the private sector, little research has been done on motivations of volunteers in the public sector, or within the federal government. Therefore, this article identified motivational factors that prompt federal government workers to volunteer at a government-related special event. A survey was used to gather data from a volunteer sample of 263 individuals who had volunteered for public sector special events in recent years. Exploratory factor analysis and t test were employed to establish motivations that stimulate public sector employees to volunteer for special events and further determine the differences in motivation between females and males. The results showed that government workers mostly volunteer for purposive motive and external motive. In addition, gender played significant roles on egotistic and purposive motives. Thus, this research provides a unique theoretical contribution to research in event management by advancing our understanding of the process by which factors associated with motivation can lead to federal government workers volunteering at a government-related special event; subsequently, impacting how event planners and organizers of public sector special events market to and recruit volunteers.

Towards a Customized¬ Awareness Campaign to Educate the Public about COVID-19: Development and Validation of a Messaging Campaign to Promote Precautionary Behavior Using Geospatial Intelligence in Saudi Arabia (Preprint)

2020 ◽  
Author(s):  
Mayda Alrige ◽  
Hind Bitar Bitar ◽  
Maram Meccawi ◽  
Balakrishnan Mullachery
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Content Validity ◽  
Awareness Campaign ◽  
Artificial Intelligence Technique ◽  
The Public ◽  
High Infection ◽  
Local Map ◽  
The City ◽  
Intelligence Technique

BACKGROUND Designing a health promotion campaign is never an easy task, especially during a pandemic of a highly infectious disease, such as Covid-19. In Saudi Arabia, many attempts have been made toward raising the public awareness about Covid-19 infection-level and its precautionary health measures that have to be taken. Although this is useful, most of the health information delivered through the national dashboard and the awareness campaign are very generic and not necessarily make the impact we like to see on individuals’ behavior. OBJECTIVE The objective of this study is to build and validate a customized awareness campaign to promote precautionary health behavior during the COVID-19 pandemic. The customization is realized by utilizing a geospatial artificial intelligence technique called Space-Time Cube (STC) technique. METHODS This research has been conducted in two sequential phases. In the first phase, an initial library of thirty-two messages was developed and validated to promote precautionary messages during the COVID-19 pandemic. This phase was guided by the Fogg Behavior Model (FBM) for behavior change. In phase 2, we applied STC as a Geospatial Artificial Intelligence technique to create a local map for one city representing three different profiles for the city districts. The model was built using COVID-19 clinical data. RESULTS Thirty-two messages were developed based on resources from the World Health Organization and the Ministry of Health in Saudi Arabia. The enumerated content validity of the messages was established through the utilization of Content Validity Index (CVI). Thirty-two messages were found to have acceptable content validity (I-CVI=.87). The geospatial intelligence technique that we used showed three profiles for the districts of Jeddah city: one for high infection, another for moderate infection, and the third for low infection. Combining the results from the first and second phases, a customized awareness campaign was created. This awareness campaign would be used to educate the public regarding the precautionary health behaviors that should be taken, and hence help in reducing the number of positive cases in the city of Jeddah. CONCLUSIONS This research delineates the two main phases to developing a health awareness messaging campaign. The messaging campaign, grounded in FBM, was customized by utilizing Geospatial Artificial Intelligence to create a local map with three district profiles: high-infection, moderate-infection, and low-infection. Locals of each district will be targeted by the campaign based on the level of infection in their district as well as other shared characteristics. Customizing health messages is very prominent in health communication research. This research provides a legitimate approach to customize health messages during the pandemic of COVID-19.

The New Economic Populism and the Future of Inequality in the United States

2017 ◽  
Author(s):  
William W. Franko ◽  
Christopher Witko
Keyword(s):  
United States ◽  
Federal Government ◽  
Labor Unions ◽  
Republican Party ◽  
The United States ◽  
The Public ◽  
Empirical Results ◽  
Income Disparities ◽  
The Face ◽  
Over Time

The authors conclude the book by recapping their arguments and empirical results, and discussing the possibilities for the “new economic populism” to promote egalitarian economic outcomes in the face of continuing gridlock and the dominance of Washington, DC’s policymaking institutions by business and the wealthy, and a conservative Republican Party. Many states are actually addressing inequality now, and these policies are working. Admittedly, many states also continue to embrace the policies that have contributed to growing inequality, such as tax cuts for the wealthy or attempting to weaken labor unions. But as the public grows more concerned about inequality, the authors argue, policies that help to address these income disparities will become more popular, and policies that exacerbate inequality will become less so. Over time, if history is a guide, more egalitarian policies will spread across the states, and ultimately to the federal government.

Living machines in our cultural imagination

2018 ◽  
Author(s):  
Michael Szollosy
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Public Perceptions ◽  
Human Condition ◽  
Cultural Imagination ◽  
The Public ◽  
The Enlightenment ◽  
The Future ◽  
Public Imagination ◽  
The Human Condition

Public perceptions of robots and artificial intelligence (AI)—both positive and negative—are hopelessly misinformed, based far too much on science fiction rather than science fact. However, these fictions can be instructive, and reveal to us important anxieties that exist in the public imagination, both towards robots and AI and about the human condition more generally. These anxieties are based on little-understood processes (such as anthropomorphization and projection), but cannot be dismissed merely as inaccuracies in need of correction. Our demonization of robots and AI illustrate two-hundred-year-old fears about the consequences of the Enlightenment and industrialization. Idealistic hopes projected onto robots and AI, in contrast, reveal other anxieties, about our mortality—and the transhumanist desire to transcend the limitations of our physical bodies—and about the future of our species. This chapter reviews these issues and considers some of their broader implications for our future lives with living machines.

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

2021 ◽  
pp. 1-11
Author(s):  
Lei Wu ◽  
Juan Wang ◽  
Long Jin ◽  
P. Hemalatha ◽  
R Premalatha
Keyword(s):  
Artificial Intelligence ◽  
Vital Role ◽  
Performance Ratio ◽  
Psychological Experience ◽  
The Public ◽  
Usable Knowledge ◽  
Intelligent Analysis ◽  
Accuracy Ratio ◽  
Depression Level ◽  
Predictive Research

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

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