Povezave med pripomočki umetne inteligence in zaznave pravičnosti in delovne zavzetosti zaposlenih v računovodski dejavnosti

Pečoler, Sara

| | SLO | ENG | Cookies and privacy

Bigger font | Smaller font

First page > Show document

Show document

Title:	Povezave med pripomočki umetne inteligence in zaznave pravičnosti in delovne zavzetosti zaposlenih v računovodski dejavnosti
Authors:	ID Pečoler, Sara (Author) ID Kolar, Iztok (Mentor) More about this mentor...
Files:	UN_Pecoler_Sara_2026.pdf (1,05 MB) MD5: FCAD02C139F038D1D0F17B1B3DC185B0
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	EPF - Faculty of Business and Economics
Abstract:	Umetna inteligenca postaja vse pomembnejši del sodobnih organizacij in kadrovskih sistemov. Njena uporaba prinaša številne koristi, hkrati pa odpira vprašanja pravičnosti in tveganja pristranskosti. Zaznava pravičnosti pri tem pomembno vpliva na odzive zaposlenih, njihovo zadovoljstvo ter delovno zavzetost. V zadnjih letih se zato vse več pozornosti namenja vprašanju, kako zaposleni dojemajo uporabo umetne inteligence pri ocenjevanju uspešnosti. V empiričnem delu diplomskega dela smo s pomočjo anketnega vprašalnika raziskovali, ali zaposleni v računovodski dejavnosti ocenjevanje uspešnosti, ki ga poda umetna inteligenca, dojemajo drugače kot ocenjevanje s strani vodje. V raziskavi je sodelovalo 44 zaposlenih v računovodski dejavnosti. Ugotovili smo, da anketiranci sistemov ocenjevanja, ki temeljijo na uporabi umetne inteligence, ne dojemajo kot bolj pravičnih od sistemov, v katerih oceno poda vodja. Prav tako rezultati niso pokazali razlik niti v pripravljenosti zaposlenih za izboljšanje delovne uspešnosti po prejeti slabi oceni niti v privlačnosti organizacije za zaposlitev ali ostanek v njej glede na vrsto ocenjevalca.
Keywords:	umetna inteligenca, ocenjevanje uspešnosti, organizacijska pravičnost, delovna zavzetost, upravljanje človeških virov.
Place of publishing:	Maribor
Publisher:	S. Pečoler]
Year of publishing:	2026
PID:	20.500.12556/DKUM-98974
UDC:	331.101.62
COBISS.SI-ID:	290324995
Publication date in DKUM:	08.09.2026
Views:	104
Downloads:	8
Metadata:
Categories:	EPF
:	Copy citation

Average score:	(0 votes)
Your score:	Voting is allowed only for logged in users.
Share:

Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.

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.
Licensing start date:	23.07.2026

Secondary language

Language:	English
Title:	Connections between artificial intelligence tools and perceptions of fairness and employee engagement in the accounting profession
Abstract:	Artificial intelligence is becoming an increasingly important part of moder organizations and human resource management systems. Its use offers numerous benefits while also raising concerns about fairness and the risk of bias. Perceptions of fairness play an important role in shaping employees' reactions, job satisfaction and work engagement. Consequently, in recent years, growing attention has been devoted to understanding how employees perceive the use of artificial intelligence in performance appraisal. In the empirical part of this thesis, we used a questionnaire survey to examine whether employees in the accounting sector perceive performance evaluations conducted by artificial intelligence differently from those conducted by a supervisor. The study included 44 employees working in the accounting sector. The findings revealed that respondents did not perceive AI-based performance appraisal systems as fairer than systems in which evaluations were conducted by a supervisor. Furthermore, the results showed no differences in employees' willingness to improve their job performance after receiving a poor evaluation, nor in the attractiveness of an organization as a place to seek or remain employed, depending on whether the evaluation was provided by artificial intelligence or by a supervisor
Keywords:	artificial intelligence, performance evaluation, organizational justice, work engagement, human resource management.

Comments

Leave comment

You must log in to leave a comment.

Comments (0)

0 - 0 / 0

There are no comments!

Back