Artificial intelligence (AI) competencies for organizational performance : a B2B marketing capabilities perspective

Mikalef, Patrick (avtor), Islam, Najmul (avtor), Parida, Vinit (avtor), Singh, Harkamaljit (avtor), Altwaijry, Najwa (avtor)

The deployment of Artificial Intelligence (AI) has been accelerating in several fields over the past few years, with much focus placed on its potential in Business-to-Business (B2B) marketing. Early reports highlight promising benefits of AI in B2B marketing such as offering important insights into customer behaviors, identifying critical market insight, and streamlining operational inefficiencies. Nevertheless, there is a lack of understanding concerning how organizations should structure their AI competencies for B2B marketing, and how these ultimately influence organizational performance. Drawing on AI competencies and B2B marketing literature, this study develops a conceptual research model that explores the effect that AI competencies have on B2B marketing capabilities, and in turn on organizational performance. The proposed research model is tested using 155 survey responses from European companies and analyzed using partial least squares structural equation modeling. The results highlight the mechanisms through which AI competencies influence B2B marketing capabilities, as well as how the later impact organizational performance.

• Jezik: Angleški jezik
• Ključne besede: marketing, artificial intelligence, company performance, B2B marketing, AI competencies, core competencies theory
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: EF - Ekonomska fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: 11 str.
• Številčenje: Vol. 164, article no. ǂ113998
• PID: 20.500.12556/RUL-148235
• UDK: 339.138
• ISSN pri članku: 0148-2963
• DOI: 10.1016/j.jbusres.2023.113998
• COBISS.SI-ID: 151685891
• Datum objave v RUL: 04.08.2023

Gradivo je del revije

• Naslov: Journal of business research
• Skrajšan naslov: J. bus. res.
• Založnik: Elsevier
• ISSN: 0148-2963
• COBISS.SI-ID: 25694208

Licence

• Licenca: CC BY-NC-ND 4.0, Creative Commons Priznanje avtorstva-Nekomercialno-Brez predelav 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by-nc-nd/4.0/deed.sl
• Opis: Najbolj omejujoča licenca Creative Commons. Uporabniki lahko prenesejo in delijo delo v nekomercialne namene in ga ne smejo uporabiti za nobene druge namene.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: trženje, umetna inteligenca, poslovanje podjetja

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P5–0441
• Naslov: Regeneracija ekonomije in posla

• Financer: Drugi - Drug financer ali več financerjev
• Program financ.: Distinguished Scientist Fellowship Program (DSFP) at King Saud University, Riyadh, Saudi Arabia