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Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors
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TLDR
In this paper, the authors analyzed the impact of artificial intelligence on technological innovation through logic reasoning and empirical modeling based on industrial robot data provided by the International Federation of Robotics (IFR) and the panel data of China's 14 manufacturing sectors from 2008 to 2017.About:
This article is published in Technological Forecasting and Social Change.The article was published on 2020-09-01. It has received 120 citations till now.read more
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Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities
TL;DR: In this article, the authors employed institutional theory and resource-based view theory to elucidate the way in which automotive firms configure tangible resources and workforce skills to drive technological enablement and improve sustainable manufacturing practices and furthermore develop circular economy capabilities.
Journal ArticleDOI
Sustainable industrial and operation engineering trends and challenges Toward Industry 4.0: a data driven analysis
Ming-Lang Tseng,Ming-Lang Tseng,Thi Phuong Thuy Tran,Thi Phuong Thuy Tran,Hien Minh Ha,Hien Minh Ha,Tat-Dat Bui,Ming K. Lim +7 more
TL;DR: In this article, the authors provide contributions to the existing literature with a state-of-the-art bibliometric review of sustainable industrial and operation engineering as the field moves toward Industry 4.0.
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Internationalization, digitalization, and sustainability: Are SMEs ready? A survey on synergies and substituting effects among growth paths
TL;DR: In this paper, the authors investigated the impact of Artificial Intelligence readiness on international performance and explored whether the relationship between digitalization and internationalization is affected by sustainability readiness, and found that digitalisation and sustainability are positively related, but they turn to be competing growth paths when the firm internationalizes.
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Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China
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Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review
Muzammil Khan,Muhammad Taqi Mehran,Zeeshan Ul Haq,Zahid Ullah,Salman Raza Naqvi,Mehreen Ihsan,Haider Abbass +6 more
TL;DR: In this article, the authors reviewed the research and development on state-of-the-art applications of artificial intelligence for combating the COVID-19 pandemic and highlighted the challenges associated with the use of these technologies.
References
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Book
Deep Learning
TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
Book
Econometric Analysis of Cross Section and Panel Data
TL;DR: This is the essential companion to Jeffrey Wooldridge's widely-used graduate text Econometric Analysis of Cross Section and Panel Data (MIT Press, 2001).
Book
Artificial Intelligence: A Modern Approach
Stuart Russell,Peter Norvig +1 more
TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
Book
The theory of economic development
TL;DR: Buku ini memberikan infmasi tentang aliran melingkar kehidupan ekonomi sebagaimana dikondisikan oleh keadaan tertentu, fenomena fundamental dari pembangunan EKonomi, kredit, laba wirausaha, bunga atas modal, and siklus bisnis as mentioned in this paper.
Journal ArticleDOI
How to do Xtabond2: An Introduction to Difference and System GMM in Stata
TL;DR: This pedagogic paper first introduces linear GMM, and shows how limited time span and the potential for fixed effects and endogenous regressors drive the design of the estimators of interest, offering Stata-based examples along the way.
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