Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries

Augmented reality in support of intelligent manufacturing - a systematic literature review

The integrated effect of Big Data Analytics, Lean Six Sigma and Green Manufacturing on the environmental performance of manufacturing companies: The case of North Africa

Big data is one of the most recent business and technical issues in the age of technology. Hundreds of millions of events occur every day. The financial field is deeply involved in the calculation of big data events. As a result, hundreds of millions of financial transactions occur in the financial world each day. Therefore, financial practitioners and analysts consider it an emerging issue of the data management and analytics of different financial products and services. Also, big data has significant impacts on financial products and services. Therefore, identifying the financial issues where big data has a significant influence is also an important issue to explore with the influences. Based on these concepts, the objective of this paper was to show the current landscape of finance dealing with big data, and also to show how big data influences different financial sectors, more specifically, its impact on financial markets, financial institutions, and the relationship with internet finance, financial management, internet credit service companies, fraud detection, risk analysis, financial application management, and so on. The connection between big data and financial-related components will be revealed in an exploratory literature review of secondary data sources. Since big data in the financial field is an extremely new concept, future research directions will be pointed out at the end of this study.

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Current landscape and influence of big data on finance

Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP) The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT) The developed framework was evaluated using a structural equation modeling (SEM) approach Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon

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Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation

Sha'ri Mohd Yusof

Papers

Understanding Big Data Analytics for Manufacturing Processes: Insights from Literature Review and Multiple Case Studies