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Artificial intelligence (AI) competencies for organizational performance : a B2B marketing capabilities perspective
ID
Mikalef, Patrick
(
Author
),
ID
Islam, Najmul
(
Author
),
ID
Parida, Vinit
(
Author
),
ID
Singh, Harkamaljit
(
Author
),
ID
Altwaijry, Najwa
(
Author
)
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https://www.sciencedirect.com/science/article/pii/S0148296323003569?via%3Dihub
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Abstract
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.
Language:
English
Keywords:
marketing
,
artificial intelligence
,
company performance
,
B2B marketing
,
AI competencies
,
core competencies theory
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
EF - School of Economics and Business
Publication status:
Published
Publication version:
Version of Record
Year:
2023
Number of pages:
11 str.
Numbering:
Vol. 164, article no. ǂ113998
PID:
20.500.12556/RUL-148235
UDC:
339.138
ISSN on article:
0148-2963
DOI:
10.1016/j.jbusres.2023.113998
COBISS.SI-ID:
151685891
Publication date in RUL:
04.08.2023
Views:
498
Downloads:
61
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Record is a part of a journal
Title:
Journal of business research
Shortened title:
J. bus. res.
Publisher:
Elsevier
ISSN:
0148-2963
COBISS.SI-ID:
25694208
Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Secondary language
Language:
Slovenian
Keywords:
trženje
,
umetna inteligenca
,
poslovanje podjetja
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P5–0441
Name:
Regeneracija ekonomije in posla
Funder:
Other - Other funder or multiple funders
Funding programme:
Distinguished Scientist Fellowship Program (DSFP) at King Saud University, Riyadh, Saudi Arabia
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