The Economic Footprint of AI: A Systematic Review of Business and Development Literature
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- Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020.
"Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review,"
Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
- A. Di Vaio & R. Palladino & R. Hassan & O. Escobar, 2020. "Artificial Intelligence and Business Models in the Sustainable Development Goals Perspective: A Systematic Literature Review," Post-Print hal-04457122, HAL.
- Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
- Yong Qin & Zeshui Xu & Xinxin Wang & Marinko Skare, 2024. "Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 1736-1770, March.
- Ahmed, Raisuddin & Haggblade, Steven & Chowdhury, Tawfiq-e-Elahi, 2000. "Out of the shadow of famine: Evolving food markets and food policy in Bangladesh," IFPRI books, International Food Policy Research Institute (IFPRI), number 0-8018-6476-3 edited by Ahmed, Raisuddin; Chowdhury, Tawfiq-e-Elahi; Haggblade, Steven, June.
- Baesens, Bart & Verstraeten, Geert & Van den Poel, Dirk & Egmont-Petersen, Michael & Van Kenhove, Patrick & Vanthienen, Jan, 2004.
"Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers,"
European Journal of Operational Research, Elsevier, vol. 156(2), pages 508-523, July.
- B. Baesens & G. Verstraeten & D. Van Den Poel & M. Egmont-Petersen & P. Van Kenhove & J. Vanthienen, 2002. "Bayesian Network Classifiers for Identifying the Slope of the Customer - Lifecycle of Long-Life Customers," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 02/154, Ghent University, Faculty of Economics and Business Administration.
- Lucrezia Fanti & Dario Guarascio & Massimo Moggi, 2022. "From Heron of Alexandria to Amazon’s Alexa: a stylized history of AI and its impact on business models, organization and work," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 409-440, September.
- Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
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Keywords
; ; ; ; ; ; ;JEL classification:
- O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
- O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
- M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
- F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
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