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

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Darío Pérez-Campuzano ◽  
Patricio Morcillo Ortega ◽  
Luis Rubio Andrada ◽  
Antonio López-Lázaro

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.

Author(s):  
Dirk Nicolas Wagner

This chapter introduces the concept of economic AI literacy as a source of competitive advantage in a world where artificial intelligence (AI) complements and transforms business models. The purpose of economic AI literacy is to allow for enhanced strategic decision making in firms that either offer and/or use AI. Data and information goods, economics of networks, and economic agents in artificially intelligent firms are introduced as basic elements of economic AI literacy. To illustrate application, the case of TensorFlow and related cases are presented. The discussion highlights the strategic relevance of economic reasoning in the light of the expected effects of AI on business transformation.


2020 ◽  
pp. 1-11
Author(s):  
Allal MOKEDDEM

A company's environment is constantly changing, new competitive models have appeared, new tangible and intangible resources are being built and new competitive regulations form a new competitive framework which opens the field to new opportunities and new threats. With this dynamic, companies are rushing towards the development of their strategic decision system which must be powerful to follow any material (product and service) or immaterial resource (belief, knowledge, know-how) coming from one of the direct competitors. In this context, a conceptual study is carried out with the objective to analyze the evolution of cognition-based competition using artificial intelligence (AI) technology as a support for strategic decision-making; this is in order to transform the competition into an intelligent mode. The finding is presented in an intelligent approach designed to generate automatic competition rules based on deep learning techniques.


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