Risk of Artificial Intelligence and International Business

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Financial Technology and Innovation".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 9791

Special Issue Editors


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Guest Editor
Discipline of International Business, University of Sydney, Sydney, NSW 2006, Australia
Interests: international risk management; management capabilities
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Guest Editor
Business School, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: international management and organizational psychology
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Guest Editor
Sustainable Real Estate Research Center, Hong Kong Shue Yan University, Hong Kong 999077, China
Interests: real estate economics; sustainable real estate; construction safety and health; applied artificial intelligence; carbon neutrality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue addresses the research agenda on the risk of artificial intelligence and international business.

Artificial intelligence (AI) has great potential to spur innovation and help firms create new business intelligence from data. The outcome of AI application reduces trade and international transaction costs. AI also shapes how people work in multinational organisations and their cross-border operations, and how to engage with the dynamism of global markets. Existing Human Resource Management (HRM) research finds that the adoption of AI is increasing because of AI’s potential to create value for consumers, staff, and organisations (Chowdhury, Dey, Joel-Edgar, Bhattacharya, Rodriguez-Espindola, Abadie, and Truong, 2022). In light of global trade, a growing interest in AI's economic and societal impacts has also prompted interest in the trade implications of this new technology (Ferencz, González, and García, 2022). It suggests the potential of AI technologies to change trade and international business models fundamentally. Bringing AI into international business management, it is not surprising that firms may deploy AI solutions globally regarding trading goods and services; analysing global data to inform the international market and business decision-making; and supporting international staffing and expatriate management.

Likewise, the adoption of artificial intelligence (AI) in international business is likely to face comprehensive challenges. This is due to a lack of managerial practice and theories in governing AI adoption. Some researchers have noticed AI's “dark side” (Castillo, Canhoto, and Said, 2021). AI could improve organizational decision-making, but it also creates organisational inefficiency associated with the "dark side" of AI. For instance, AI-powered human and machine interactions can also fail in customer service, potentially leading to anger, confusion, and customer dissatisfaction. Moreover, managers’ attitudes and personal concerns rely on firms’ facilitating conditions for adopting AI (Cao, Duan, Edwards, and Dwivedi, 2021). Moreover, poor digital infrastructure in the home country or host country may lead to the reluctance of international business practitioners to adopt AI.

Consequently, the risk of AI is poorly understood in international business operations and global settings. With these in mind, this Special Issue intends to set a new research agenda for studying international business operations and the risk of adopting AI. The object of this Special Issue is to open a scholarly discussion on international business factors that interfaces with the dark side of AI. The call for papers is open to a wide range of scholarship scopes and different methodological approaches, including qualitative, quantitative, mixed-methods, and theoretical/conceptual papers.

Potential topics include, but are not limited to, the following:

  1. Risk of adopting AI for everyday life business operations;
  2. Risks of adopting AI for fintech;
  3. Risks of selecting personnel via AI;
  4. Service failure risks in adopting AI for global markets;
  5. Financial crisis and AI for stocks forecasting;
  6. Financial risks in algorithm trading;
  7. International human resource management risk and AI;
  8. International business decision-makers resist the adoption of AI.

Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. 2021. Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106: 102312.

Castillo, D., Canhoto, A. I., & Said, E. 2021. The dark side of AI-powered service interactions: exploring the process of co-destruction from the customer perspective. The Service Industries Journal, 41(13-14): 900-25.

Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. 2022. Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review: 100899.

Ferencz, J., González, J. L., & García, I. O. 2022. Artificial Intelligence and international trade. OECD. 

Dr. David (Xuefeng) Shao
Dr. Rebecca Dong
Dr. Rita (Yi Man) Li
Guest Editors

Manuscript Submission Information

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Keywords

  • artificial intelligence (AI)
  • risk of AI
  • AI uncertainty
  • AI service failure
  • internationalization decision-making
  • global strategy
  • firm dis-performance
  • operational inefficiency
  • international business failure.

Published Papers (1 paper)

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18 pages, 1185 KiB  
Concept Paper
Artificial Intelligence-Driven Talent Management System: Exploring the Risks and Options for Constructing a Theoretical Foundation
by Ali Faqihi and Shah Jahan Miah
J. Risk Financial Manag. 2023, 16(1), 31; https://doi.org/10.3390/jrfm16010031 - 4 Jan 2023
Cited by 6 | Viewed by 8436
Abstract
AI (Artificial intelligence) has the potential to improve strategies to talent management by implementing advanced automated systems for workforce management. AI can make this improvement a reality. The objective of this study is to discover the new requirements for generating a new AI-oriented [...] Read more.
AI (Artificial intelligence) has the potential to improve strategies to talent management by implementing advanced automated systems for workforce management. AI can make this improvement a reality. The objective of this study is to discover the new requirements for generating a new AI-oriented artefact so that the issues pertaining to talent management are effectively addressed. The design artefact is an intelligent Human Resource Management (HRM) automation solution for talent career management primarily based on a talent intelligent module. Improving connections between professional assessment and planning features is the key goal of this initiative. Utilising a design science methodology we investigate the use of organised machine learning approaches. This technique is the key component of a complete AI solution framework that would be further informed through a suggested moderation of technology-organisation-environment (TOE) theory with the theory of diffusion of innovation (DOI). This framework was devised in order solve AI-related problems. Aside from the automated components available in talent management solutions, this study will make recommendations for practical approaches researchers may follow to fulfil a company’s specific requirements for talent growth. Full article
(This article belongs to the Special Issue Risk of Artificial Intelligence and International Business)
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