Barriers for Adopting Artificial Intelligence in Digital Marketing of SMEs
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F22%3A43905891" target="_blank" >RIV/60076658:12510/22:43905891 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Barriers for Adopting Artificial Intelligence in Digital Marketing of SMEs
Original language description
Purpose: This study addresses the barriers SMEs face when adopting AI in digital marketing.Design/methodology/approach: The study is based on an extensive literature review conducted through the lens of theextended Technology-Organization Environment (TOE) framework .Findings: Literature review highlights several significant barriers to AI adoption relating to technology, organization,environment, and data in SMEs. AI technologies are promising for SMEs' growth and performance; however, the apparentand perceived barriers faced by SMEs hinder AI adoption in their digital marketing efforts.Practical implications: This study is useful for SME researchers who aim to escalate SME marketing performance withnew advancements in technology, particularly the usage of AI for business and digital marketing.Originality/value: Numerous studies have addressed the barriers to adopting AI in various sectors. However, the barriers toadopting AI in digital marketing for SMEs are not well researched; thus, this study focuses on this area of study. This paperpresents an integrated framework for an empirical study to quantify the barriers to AI adoption in SME digital marketing.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 40th International Business Information Management Association (IBIMA
ISBN
979-8-9867719-0-8
ISSN
2767-9640
e-ISSN
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Number of pages
10
Pages from-to
184-193
Publisher name
International Business Information Management Association
Place of publication
Seville
Event location
Seville, Spain
Event date
Nov 23, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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