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Artificial intelligence (AI) competencies for organizational performance : a B2B marketing capabilities perspective
ID
Mikalef, Patrick
(
Avtor
),
ID
Islam, Najmul
(
Avtor
),
ID
Parida, Vinit
(
Avtor
),
ID
Singh, Harkamaljit
(
Avtor
),
ID
Altwaijry, Najwa
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(802,46 KB)
MD5: CD3550F1D28A5BF7FCBDAE1E0B4BAD9D
URL - Izvorni URL, za dostop obiščite
https://www.sciencedirect.com/science/article/pii/S0148296323003569?via%3Dihub
Galerija slik
Izvleček
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
Število ogledov:
564
Število prenosov:
72
Metapodatki:
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Objavi na:
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
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