Abdellatif Aziki1, Moulay Hachem Fadili1. 1. Research Laboratory in Entrepreneurship, Finance and Audit (LAREFA), Ibn ZOHR University, ENCG Agadir, Morocco.
Abstract
PURPOSE: The fast development of technology and data has fueled the use of artificial intelligence (AI) in the business area, but there has been no comprehensive review to guide and assess this evolution, especially in the context of Covid-19 crisis. Our objective is to highlight the nature and scale of AI research in the business area, during the COVID-19 Pandemic. METHODS: We performed a scoping review and searched two literature databases (Scopus and MDPI) for terms related to AI and Covid-19 by focusing on scientific papers published in the field of business. We used multiple tools (Endnote, Covidence) for titles and abstracts selection, followed by full-text screening. The studies must include research on artificial intelligence and Covid-19, and then be published in English-language, between March 2020 and March 2022. RESULTS: 31 studies met eligibility criteria (of 391 studies selected). Most of the published articles refer to conceptual analysis or quantitative works, the rest of the articles used a literature review except 4 articles published using a qualitative method of analysis. In addition, we observe an evolution of the total number of publications for the 31 articles included in the analysis. CONCLUSIONS: Studying AI in the business field amid the covid-19 crisis is at an early stage of maturity, especially with the use of new AI technologies.). For the field to progress, more studies are needed in the next few years.
PURPOSE: The fast development of technology and data has fueled the use of artificial intelligence (AI) in the business area, but there has been no comprehensive review to guide and assess this evolution, especially in the context of Covid-19 crisis. Our objective is to highlight the nature and scale of AI research in the business area, during the COVID-19 Pandemic. METHODS: We performed a scoping review and searched two literature databases (Scopus and MDPI) for terms related to AI and Covid-19 by focusing on scientific papers published in the field of business. We used multiple tools (Endnote, Covidence) for titles and abstracts selection, followed by full-text screening. The studies must include research on artificial intelligence and Covid-19, and then be published in English-language, between March 2020 and March 2022. RESULTS: 31 studies met eligibility criteria (of 391 studies selected). Most of the published articles refer to conceptual analysis or quantitative works, the rest of the articles used a literature review except 4 articles published using a qualitative method of analysis. In addition, we observe an evolution of the total number of publications for the 31 articles included in the analysis. CONCLUSIONS: Studying AI in the business field amid the covid-19 crisis is at an early stage of maturity, especially with the use of new AI technologies.). For the field to progress, more studies are needed in the next few years.
Authors: Andrea C Tricco; Erin Lillie; Wasifa Zarin; Kelly K O'Brien; Heather Colquhoun; Danielle Levac; David Moher; Micah D J Peters; Tanya Horsley; Laura Weeks; Susanne Hempel; Elie A Akl; Christine Chang; Jessie McGowan; Lesley Stewart; Lisa Hartling; Adrian Aldcroft; Michael G Wilson; Chantelle Garritty; Simon Lewin; Christina M Godfrey; Marilyn T Macdonald; Etienne V Langlois; Karla Soares-Weiser; Jo Moriarty; Tammy Clifford; Özge Tunçalp; Sharon E Straus Journal: Ann Intern Med Date: 2018-09-04 Impact factor: 25.391
Authors: Mai T Pham; Andrijana Rajić; Judy D Greig; Jan M Sargeant; Andrew Papadopoulos; Scott A McEwen Journal: Res Synth Methods Date: 2014-07-24 Impact factor: 5.273