ǂa ǂB2B marketing capabilities perspective
Patrick Mikalef (Avtor), Najmul Islam (Avtor), Vinit Parida (Avtor), Harkamaljit Singh (Avtor), Najwa Altwaijry (Avtor)

Povzetek

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.

Ključne besede

trženje;umetna inteligenca;poslovanje podjetja;marketing;artificial intelligence;company performance;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL EF - Ekonomska fakulteta
UDK: 339.138
COBISS: 151685891 Povezava se bo odprla v novem oknu
ISSN: 0148-2963
Št. ogledov: 19
Št. prenosov: 10
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarne ključne besede: trženje;umetna inteligenca;poslovanje podjetja;
Vrsta dela (COBISS): Članek v reviji
Strani: 11 str.
Letnik: ǂVol. ǂ164
Zvezek: ǂarticle no. ǂ113998
Čas izdaje: Sep. 2023
DOI: 10.1016/j.jbusres.2023.113998
ID: 19721379