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Naslov:Multi-criteria measurement of ai support to project management
Avtorji:ID Čančer, Vesna (Avtor)
ID Tominc, Polona (Avtor)
ID Rožman, Maja (Avtor)
Datoteke:.pdf Cancer-2023-Multi-Criteria_Measurement_of_AI_S.pdf (4,18 MB)
MD5: 63802703739DDDC1D5CD36763E200CA2
 
URL https://ieeexplore.ieee.org/document/10355961
 
Jezik:Angleški jezik
Vrsta gradiva:Znanstveno delo
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:EPF - Ekonomsko-poslovna fakulteta
Opis:This paper aims to measure the level of artificial intelligence (AI) support to project management (PM) in selected service sector activities. The exploratory factor analysis was employed based on the extensive survey on AI in Slovenian companies and the multi-criteria measurement with an emphasis on value functions and pairwise comparisons in the analytic hierarchy process. The synthesis and performance sensitivity analysis results show that in the service sector, concerning all criteria, PM is with the level 0.276 best supported with AI in services of professional, scientific, and technical activities, which also stand out concerning the first-level goals in using AI solutions in a project with the value 0.284, and in successful project implementation using AI with the value 0.301. Although the lowest level of AI support to PM, which is 0.220, is in services of wholesale and retail trade and repair of motor vehicles and motorcycles, these services excel in adopting AI technologies in a project with a value of 0.277. Services of financial and insurance activities, with the level 0.257 second-ranked concerning all criteria, have the highest value of 0.269 concerning the first-level goal of improving the work of project leaders using AI. The paper, therefore, contributes to the comparison of AI support to PM in service sector activities. The results can help AI development policymakers determine which activities need to be supported and which should be set as an example. The presented methodological frame can serve to perform measurements and benchmarking in various research fields.
Ključne besede:artificial intelligence, factor analysis, multiple criteria, performance sensitivity, project management
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Poslano v recenzijo:17.11.2023
Datum sprejetja članka:07.12.2023
Datum objave:13.12.2023
Založnik:IEEE
Leto izida:2023
Št. strani:Str. 142816-142828
Številčenje:Letn. 11
PID:20.500.12556/DKUM-87045 Novo okno
UDK:005.8
COBISS.SI-ID:179926787 Novo okno
DOI:10.1109/ACCESS.2023.3342276 Novo okno
ISSN pri članku:2169-3536
Datum objave v DKUM:12.02.2024
Število ogledov:324
Število prenosov:24
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
Področja:Ostalo
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Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
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Gradivo je del revije

Naslov:IEEE access
Založnik:Institute of Electrical and Electronics Engineers
ISSN:2169-3536
COBISS.SI-ID:519839513 Novo okno

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P5-0023
Naslov:Podjetništvo za inovativno družbo

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:13.12.2023

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:umetna inteligenca, faktorska analiza, več meril, vodenje projektov


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