Artificial Intelligence potential within airlines: a review on how AI can enhance strategic decision-making in times of COVID-19

Darío Pérez-Campuzano, Patricio Morcillo Ortega, Luis Rubio Andrada, Antonio López-Lázaro
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引用次数: 3

Abstract

Purpose: Airline strategy relies on the competitive environment analysis and the management of resources. Artificial Intelligence (AI) algorithms are being increasingly deployed throughout several industries. COVID-19 has further stressed a sector where firms have historically struggled to sustain profitability.The purpose is to explore the potential of AI applications regarding strategic decision-making in airlines in times of crisis and to depict a roadmap to encourage scholars and practitioners to jointly implement these tools within corporations.Design/methodology/approach: This study firstly reviews the state-of-the-art regarding transport organization trends with focus on airline strategy and finance as well as AI tools, supported by the collaboration of a former airline digitalization strategist. Secondly, the potential of the latter to be applied in those functions is analyzed, considering different Machine Learning (ML) methods and algorithms.Findings: Some applications or pathways are identified as of particular interest for the airlines’ strategic decision-making process. Most of them are based on ML algorithms and training methods that are currently underused or disregarded in certain business areas, such as Neural Network models for unsupervised market analysis or supervised cost estimation.Research limitations/implications: Focus is on airline strategy and finance, keeping engineering or operational applications out of the scope.Practical implications: Proposed guidance may promote the deployment of AI tools which currently lack practical implementation in certain business areas.Social implications: Showcased guidance may revert into a closer collaboration between business and academia.Originality/value: Comprehensive review of current airlines’ strategic levers and identification of promising AI pathways to be further explored.
航空公司的人工智能潜力:回顾人工智能如何在2019冠状病毒病期间加强战略决策
目的:航空公司战略依赖于竞争环境分析和资源管理。人工智能(AI)算法正越来越多地应用于多个行业。COVID-19进一步强调了一个行业,该行业的企业历来难以维持盈利能力。目的是探索人工智能应用在危机时期航空公司战略决策方面的潜力,并描绘路线图,鼓励学者和从业者在公司内部共同实施这些工具。设计/方法/方法:本研究首先回顾了运输组织趋势的最新进展,重点关注航空公司战略和财务以及人工智能工具,并得到了前航空公司数字化战略家的合作支持。其次,考虑到不同的机器学习(ML)方法和算法,分析了后者在这些函数中的应用潜力。研究发现:一些应用或途径被确定为航空公司战略决策过程特别感兴趣的。其中大多数是基于ML算法和训练方法,这些算法和训练方法目前在某些业务领域未被充分利用或忽视,例如用于无监督市场分析或监督成本估计的神经网络模型。研究限制/影响:重点是航空公司战略和财务,将工程或运营应用排除在研究范围之外。实际影响:建议的指导可能会促进目前在某些业务领域缺乏实际实施的人工智能工具的部署。社会影响:展示的指导方针可能会恢复到商业和学术界之间更密切的合作。原创性/价值:全面评估当前航空公司的战略杠杆,并确定有待进一步探索的有前途的人工智能途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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