Revista de Administração Mackenzie

CALL FOR PAPERS
SPECIAL ISSUE
 
EXPLORING THE FRONTIER OF LANGUAGE-ASSOCIATED AI IN MANAGEMENT
 
RAM – REVISTA DE ADMINISTRAÇÃO MACKENZIE
Mackenzie Management Review
http://www.scielo.br/revistas/ram/iinstruc.htm
For submission use this link:
http://mc04.manuscriptcentral.com/ram-scielo
 
Invited Editors
RICARDO LIMONGI FRANÇA COELHO
Universidade Federal de Goiás
 
VICTOR MANUEL MENESES BARBOSA
Instituto Politécnico de Setúbal – Portugal
 
LUIS HERNAN CONTRERAS PINOCHET
Universidade de São Paulo
 
GUSTAVO HERMÍNIO SALATI MARCONDES DE MORAES
Universidade Estadual de Campinas

GILBERTO PEREZ
Universidade Presbiteriana Mackenzie
 
SUBMISSION NEW DEADLINE: May 5, 2024
Estimated Publication: November/December 2024
 
Overview
In the rapidly evolving landscape of artificial intelligence, language models such as Large Language Models (LLMs) have emerged as pivotal tools, influencing a broad spectrum of sectors, including management. These advanced technologies are reshaping the way organizations operate, make decisions, and interact with stakeholders. However, alongside their remarkable capabilities, these technologies present a myriad of challenges, ethical dilemmas, and limitations that warrant thorough exploration.
 
This call for papers seeks original, high-quality submissions that delve into the multifaceted implications of language-associated AI technologies in the field of management. We aim to gather a diverse array of perspectives and research that not only highlight the advancements but also critically analyze the limitations, ethical considerations, and future pathways of these technologies in management practices.
 
Research Objectives and Questions
We encourage submissions that address, but are not limited to, the following research objectives and questions:
 

• Impact Assessment: How do language-associated AI technologies like LLMs influence organizational decision-making processes and management practices?
• Innovation and Advancement: What are the cutting-edge innovations in language-associated AI that could redefine management strategies and operations?
• Ethical Considerations: What ethical dilemmas arise from the deployment of LLMs in management, and how can organizations navigate these challenges?
• Bias and Fairness: How does bias in language models manifest in management contexts, and what mechanisms can be implemented to ensure fairness and equity?
• Transparency and Explainability: How can organizations maintain transparency and explainability in AI-driven decisions, and what are the implications for management accountability?
• Regulatory Compliance: What are the implications of language-associated AI on regulatory compliance and governance in management practices?
• Human-AI Collaboration: How can effective collaboration between humans and AI be fostered in management roles to optimize decision-making and productivity?
• Cultural and Linguistic Diversity: How do language models address or fail to address cultural and linguistic diversity in global management practices?
• Data Privacy and Security: What are the challenges and solutions related to data privacy and security in the use of LLMs in management?
• Future of Work: How is the integration of language-associated AI technologies shaping the future of work and the role of managers?
• AI in Crisis Management: How can language-associated AI be leveraged in crisis management and emergency response strategies?
• Consumer Behavior Analysis: How can LLMs enhance the understanding and prediction of consumer behavior for strategic management?
• AI-Driven Change Management: How can organizations effectively manage change introduced by the rapid adoption of language-associated AI technologies?
• Sustainability and AI: How can language-associated AI contribute to sustainable management practices and corporate social responsibility?
• AI in Education and Training: What role does language-associated AI play in the education and training of future managers and business leaders?
• We welcome empirical, theoretical, and methodological papers that provide insightful analyses, foster discussions, and propose innovative solutions. The goal is to advance the understanding of language-associated AI in management and contribute to the responsible and effective integration of these technologies in practice.

 
Information for authors:

• Theoretical and theoretical-empirical papers will be accepted.
• All papers can be submitted in English, Portuguese, or Spanish.
• The authors should translate papers accepted in Portuguese, or Spanish into English.
• Title: maximum 12 words.
• Abstract: minimum 200 and maximum 250 words
• Five keywords.
• Minimum 7,600 words and maximum 8,400 words, including references.
• Submission only in WORD document.