Aziki Abdellatif, Fadili Moulay Hachem
Research Laboratory in Entrepreneurship, Finance and Audit (LAREFA), Ibn ZOHR University, ENCG Agadir, Morocco.
Procedia Comput Sci. 2022;203:450-455. doi: 10.1016/j.procs.2022.07.060. Epub 2022 Aug 12.
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.
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.
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.
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.
技术和数据的快速发展推动了人工智能(AI)在商业领域的应用,但目前尚无全面的综述来指导和评估这一发展,尤其是在新冠疫情危机的背景下。我们的目标是突出新冠疫情大流行期间商业领域人工智能研究的性质和规模。
我们进行了一项范围综述,通过聚焦商业领域发表的科学论文,在两个文献数据库(Scopus和MDPI)中搜索与人工智能和新冠疫情相关的术语。我们使用多种工具(Endnote、Covidence)进行标题和摘要筛选,随后进行全文筛选。这些研究必须包括关于人工智能和新冠疫情的研究,且于2020年3月至2022年3月期间以英文发表。
31项研究符合入选标准(从391项所选研究中)。大多数已发表文章涉及概念分析或定量研究,其余文章采用文献综述,只有4篇文章采用定性分析方法发表。此外,我们观察到分析中所纳入的31篇文章的发表总数呈现出一种变化趋势。
在新冠疫情危机期间,商业领域的人工智能研究尚处于早期成熟阶段,尤其是在新人工智能技术的应用方面。为推动该领域发展,未来几年需要更多的研究。