2026-06-30T15:29:20Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1366562026-05-12T10:14:34Zcom_20.500.14352_14col_20.500.14352_18

Navigating the Landscape of Artificial Intelligence: Computing with Words in Marketing Shu, Ziwei Carrasco González, Ramón Alberto Kerre, Etienne E. Lu, Jie Martínez, Luis Li, Tianrui Montero De Juan, Francisco Javier Flores Vidal, Pablo Arcadio 004.8 004.6 658.8 Computing with words Artificial intelligence 2-tuple linguistic model Aggregation operators Marketing Inteligencia artificial (Informática) Marketing 1203.04 Inteligencia Artificial 5311.05 Marketing (Comercialización) Artificial Intelligence (AI) is increasingly playing a vital role and transforming our lives. Explainable AI is promoted by the concept of Computing with Words (CWW), which uses a human-like analytical framework to interpret and process information. In marketing, it is crucial to transform ambiguous information from customer feedback or expert knowledge into interpretable information for effective decision-making and the creation of marketing strategies. This chapter aims to explore the application of the 2-tuple linguistic model, a widely used methodology for CWW, in the field of marketing. Through a systematic exploration of articles published from 2000 to 2003, this chapter identifies areas of investigation worthy of further exploration and analysis. Depto. de Marketing Fac. de Estudios Estadísticos TRUE pub 2026-05-12T10:14:34Z 2026-05-12T10:14:34Z 2024 book part VoR https://hdl.handle.net/20.500.14352/136656 XXXX-XXXX 10.1142/9789811294631_0054 eng World Scientific proceedings series on computer engineering and information science 14 Shu, Z. and Carrasco, R.A. (2024) ‘Navigating the Landscape of Artificial Intelligence: Computing with Words in Marketing’, en World Scientific Proceedings Series on Computer Engineering and Information Science: Intelligent Management of Data and Information in Decision Making. Singapore: World Scientific, pp. 437–444. Available at: https://doi.org/10.1142/9789811294631_0054 restricted access World Scientific