Can chatbots represent? Examining the potential for symbolic representation in automated service agents
Datos Bibliográficos
| ID | 16775658 |
|---|---|
| Autores | Brian Stelbotsky (0000-0003-1340-1332, Boise State University, autor de correspondencia), Sanghee Park (0000-0003-0527-728X, Indiana University Indianapolis) |
| Año | 2026 |
| Volumen | 28 |
| Número | 2 |
| Páginas | 477-497 |
| Fecha de publicación | 2026-02-01 |
| Peer Reviewed | Sí |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | Public Management Review (JOURNAL) |
| Identificadores de la revista | ISSN: 1471-9037 • E-ISSN: 1471-9045 |
| Editorial | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/14719037.2024.2443064 |
| OpenAlex | W4405422909 |
| Idioma | EN |
| Citas recibidas | 5 |
| Referencias citadas | 73 |
Bureaucracy · Business · Economics · Human services · Microeconomics · Perception · Political science · Politics · Preference · Public relations · Public service · The Symbolic · AI in Service Interactions · Computer Science · Digital Economy and Work Transformation · Ethics and Social Impacts of AI · Psychology · Social Psychology · Marketing
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Using nighttime light data to assess the impact of AI pilot cities on government overtime in China
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Algorithm appreciation
Building a Stronger Casa
In AI we trust? Citizen perceptions of AI in government decision making
Representation, reputation and expectations towards bureaucracy
Automation and discretion
Bureaucrat or artificial intelligence
A representative-represented matrix
Virtual agents in the public service
Implementing AI in the public sector
Exploring artificial intelligence adoption in public organizations
Artificial intelligence, types of decisions, and street-level bureaucrats
The Dark Sides of Artificial Intelligence
What influences algorithmic decision-making? A systematic literature review on algorithm aversion
In AI we trust? Perceptions about automated decision-making by artificial intelligence
A Teacher Like Me
Humanizing chatbots
Theoretical Frontiers in Representative Bureaucracy
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Implications of the use of artificial intelligence in public governance
Data governance
How do citizens perceive the use of Artificial Intelligence in public sector decisions
AI-based self-service technology in public service delivery
A supervisor like me
Artificial Intelligence, Discretion, and Bureaucracy
Representative Bureaucracy
An Application of the Theory of Representative Bureaucracy, Gender Concordance, and Symbolic Representation in the Health Care Context
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Gender, Representative Bureaucracy, and Law Enforcement
Institutional factors driving citizen perceptions of AI in government
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The emotive effect of government branding on citizens' trust and its boundaries
The effect of human versus automated interaction on willingness to participate in government programs
Intersectionality and equity
Algorithms in the public sector. Why context matters
Understanding perception of algorithmic decisions
Machines and Mindlessness
Representative bureaucracy and organizational attractiveness
Will More Black Cops Matter? Officer Race and Police‐Involved Homicides of Black Citizens
The Pursuit of Social Equity in the Federal Government
Representative Bureaucracy
Representative Bureaucracy and the Willingness to Coproduce
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Bureaucracy, Democracy, and Race
Black or Blue
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Causal Inference in Conjoint Analysis
Does My Boss's Gender Matter? Explaining Job Satisfaction and Employee Turnover in the Public Sector
Where Did You Serve? Veteran Identity, Representative Bureaucracy, and Vocational Rehabilitation
Disentangling the Causal Mechanisms of Representative Bureaucracy
Race, Bureaucracy, and Symbolic Representation
Can Government Public Communications Elicit Undue Trust? Exploring the Interaction between Symbols and Substantive Information in Communications
Representative Bureaucracy and Attitudes Toward Automated Decision Making
Substantive Symbols
You make me wanna holler and throw up both my hands
Deciding to Discipline
Lipstick and Logarithms
| Obras citantes distintas | 5 |
|---|---|
| Citas por año | 5 |
| Intervalo de citas | 2025 - 2026 (2) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 5 |