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1 – 10 of over 3000This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the…
Abstract
This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.
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Subhodeep Mukherjee, Manish Mohan Baral, Ramji Nagariya, Venkataiah Chittipaka and Surya Kant Pal
This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A…
Abstract
Purpose
This paper aims to investigate the firm performance of micro, small and medium enterprises (MSMEs) by using artificial intelligence-based supply chain resilience strategies. A theoretical framework shows the relationship between artificial intelligence, supply chain resilience strategy and firm performance.
Design/methodology/approach
A questionnaire is developed to survey the MSMEs of India. A sample size of 307 is considered for the survey. The employees working in MSMEs are targeted responses. The conceptual model developed is tested empirically.
Findings
The study found that eight hypotheses were accepted and two were rejected. There are five mediating variables in the current study. Artificial intelligence, the independent variable, positively affects all five mediators. Then, according to the survey and analysis of the final 307 responses from MSMEs, the mediating variables significantly impact the dependent variable, firm performance.
Research limitations/implications
This study is limited to emerging markets only. Also this study used only cross sectional data collection methods.
Practical implications
This study is essential for supply chain managers and top management willing to adopt the latest technology in their organisation or firmfor a better efficient supply chain process.
Originality/value
This study investigated artificial intelligence-based supply chain resilience for improving firm performance in emerging countries like India. This study tried to fill the research gap in artificial intelligence and supply chain resilience.
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Konstantinos Kalodanis, Panagiotis Rizomiliotis and Dimosthenis Anagnostopoulos
The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate…
Abstract
Purpose
The purpose of this paper is to highlight the key technical challenges that derive from the recently proposed European Artificial Intelligence Act and specifically, to investigate the applicability of the requirements that the AI Act mandates to high-risk AI systems from the perspective of AI security.
Design/methodology/approach
This paper presents the main points of the proposed AI Act, with emphasis on the compliance requirements of high-risk systems. It matches known AI security threats with the relevant technical requirements, it demonstrates the impact that these security threats can have to the AI Act technical requirements and evaluates the applicability of these requirements based on the effectiveness of the existing security protection measures. Finally, the paper highlights the necessity for an integrated framework for AI system evaluation.
Findings
The findings of the EU AI Act technical assessment highlight the gap between the proposed requirements and the available AI security countermeasures as well as the necessity for an AI security evaluation framework.
Originality/value
AI Act, high-risk AI systems, security threats, security countermeasures.
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Alireza Amini, Seyyedeh Shima Hoseini, Arash Haqbin and Vahideh Shahin
Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of…
Abstract
Purpose
Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of entrepreneurial intelligence in female entrepreneurs, drawing on a national-level study and the international literature on this topic.
Design/methodology/approach
The present paper conducted two studies. First, 15 female entrepreneurs in the Guilan province of Iran, who were selected using purposive sampling, were interviewed to identify the characteristics of entrepreneurial intelligence nationally. The data gathered by interviews were analyzed using inductive content analysis. Then, their validity was tested using qualitative validation and analyzed using Shannon entropy. In the second study, the characteristics of female entrepreneurial intelligence were identified through a qualitative metasynthesis. The results of the two studies were compared together.
Findings
This categorized entrepreneurial intelligence into six categories, namely, entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. Ultimately the characteristics of women’s entrepreneurial intelligence in each category were compared according to the national-level study and the international literature.
Originality/value
This study has the potential to discover credible and robust approaches for further examining the contextualization of women’s entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various dimensions of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women’s entrepreneurship, this paper challenges the assumption that the characteristics of women’s entrepreneurial intelligence are uniform across the world.
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Tero Sotamaa, Arto Reiman and Osmo Kauppila
The purpose of this paper is to explore companies’ business risks and challenges across macro- and micro-environments, as well as how small and medium-sized enterprises (SMEs) can…
Abstract
Purpose
The purpose of this paper is to explore companies’ business risks and challenges across macro- and micro-environments, as well as how small and medium-sized enterprises (SMEs) can benefit from digital technologies, including artificial intelligence (AI), as part their risk-management (RM) strategies in the face of recent disruptive events.
Design/methodology/approach
We perform a literature review on risk management and business continuity (BC) in the context of SMEs, both in general and specifically in the manufacturing sector.
Findings
The critical importance of RM and BC for SMEs is highlighted. The review underscores the significant impact of recent disruptions on SMEs and reveals a range of risk factors affecting their BC. Moreover, the review recognises how SMEs, in general, and manufacturing SMEs, in particular, can benefit from using digital technologies and AI as essential components of their RM.
Originality/value
The review highlights transformative role of digital technologies and AI in enhancing RM. Through a systematic classification of risk factors within macro- and micro-environments, this novel approach provides a structured foundation for future research. It provides practical value by enabling SMEs to integrate dynamic capabilities and adaptive capacities through the adaption of digital technologies and AI into their RM.
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Roope Nyqvist, Antti Peltokorpi and Olli Seppänen
The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context…
Abstract
Purpose
The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.
Design/methodology/approach
Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.
Findings
ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.
Originality/value
This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.
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Gayatri Panda, Manoj Kumar Dash, Ashutosh Samadhiya, Anil Kumar and Eyob Mulat-weldemeskel
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore…
Abstract
Purpose
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.
Design/methodology/approach
The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.
Findings
The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.
Research limitations/implications
The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.
Originality/value
The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.
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