The Impact of Innovation Adoption of Emerging Digital Technologies within a collaborative ecosystem on Firm Innovation Performance- Focus on Emerging Economies (Middle East, Africa, and Asia) (Published)
In today’s fast-paced and ever-changing world, innovative technologies’ rapid emergence and integration profoundly impact organisational strategies, the industry landscape, and overall economic and societal development. This article explores the adoption of specific emerging digital technologies (Artificial Intelligence (AI), Industry 4.0( I4.0 ), and the Internet of Things (IoT). It proposes a comprehensive framework to enhance firm innovation performance in organisations. A deep understanding of the future commercial utilisation of these technologies is crucial for informed decision-making. Acknowledging the interconnected nature of emerging technologies, this research emphasises the importance of collaboration among various stakeholders such as businesses, academic institutions, research organisations, regulatory bodies, and government agencies. This collaborative effort forms a unique and interdependent ecosystem essential for effectively applying, adapting, and improving emerging digital technologies. This study highlights perspective and limitations, particularly in emerging economies, by investigating the determinants that impact their implementation, mainly focusing on emerging economies. A robust framework is developed to address the research objectives by combining existing technology models, including the Diffusion of Innovation Technology-Organisation-Environment and Technology Acceptance Model. A quantitative research survey targeted managers and above in large enterprises and multinationals within the Middle East, Africa, and Asia manufacturing industries. The collected responses (n=153) were analysed using Structural Equation Modelling and Chi-Square methods. The findings of this study emphasise the advantages of the collaborative adoption of emerging digital technologies in improving firm performance. By bridging the gaps in integrating multiple emerging technologies within the innovation ecosystem, organisations can enhance their innovation capabilities and leverage them for sustainable competitive advantage. This comprehensive framework provides valuable insights and practical guidance for organisations seeking to navigate the complex landscape of emerging digital technologies and maximise their innovation potential.
Keywords: Africa, Artificial Intelligence, Asia, Industry 4.0, Middle East, emerging digital technologies, firm innovation performance, innovation adoption, internet of things
The Impact of Artificial Intelligence Bias on Human Resource Management Functions: Systematic Literature Review and Future Research Directions (Published)
Artificial intelligence (AI) has become a valuable tool for facilitating Human Resource Management (HRM) functions. Although, it should be noted that AI has a specific character side away from other technology. Publications covering this knowledge area have grown sharply, however the scholarly covering the impact of AI bias inHRM is scarce. This paper studies this area and goes deeper to explore the future research areas by conducting a systematic literature review for 598 papers from Scopes and Emerald insight databases of which 34 articles were selected after implementing the PRISMA tool and quality evaluation stage. Results generated revealed that biased AI applications are negatively affecting performance management, compensation, staffing and training and development. Apart from that future research domains and questions have been outlined and identified from organizations’ and employees’ perspectives.
Keywords: Artificial Intelligence, Bias, HRM functions, Human Resource Management, data
Innovations in Artificial Intelligence Research Fueled by Big Data Analytics (Published)
In recent years, the exponential growth of digital data has presented a remarkable opportunity and challenge for the field of artificial intelligence (AI). This paper provides a comprehensive examination of the profound influence of big data on AI advancements. With the advent of extensive data sources and improved data processing techniques, AI has made significant strides in various domains, including machine learning, natural language processing, computer vision, and more. This study reviews key developments in the intersection of big data and AI, offering insights into the ways in which big data has reshaped the landscape of AI research, applications, and industry. It assesses how AI-driven insights from massive datasets have not only improved decision-making processes but have also transformed entire industries by unlocking new opportunities and efficiencies. The synergy between artificial intelligence (AI) and big data analytics has ushered in a new era of innovation and transformative possibilities. This abstract presents a comprehensive overview of how big data analytics is driving breakthroughs in AI research, highlighting key advancements, applications, and implications.
Keywords: Artificial Intelligence, Big Data, deep learning, machine learning