Impact of organisational facilitators and perceived HR effectiveness on acceptance of AI-augmented HRM: an integrated TAM and TPB perspective DOI
Verma Prikshat, Sanjeev Kumar, Parth Patel

и другие.

Personnel Review, Год журнала: 2024, Номер unknown

Опубликована: Сен. 20, 2024

Purpose Drawing on the integrative perspective of technology acceptance model (TAM) and theory planned behaviour (TPB) extending it further by examining role organisational facilitators perceived HR effectiveness in this perspective, we examine professionals’ AI-augmented HRM (HRM (AI) ) research. Design/methodology/approach The data (N=375) were collected from professionals working different organisations India. Structural equation modelling (SEM) was employed to analyse data. Findings results study suggest that along with facilitator antecedents relevant components both TAM TPB, also enhanced levels professionals. Practical implications research findings are expected contribute understanding factors influence organizations. may help identify can enhance adoption implementation Finally, provides a composite TAM-TPB theoretical framework guide future HRM. Originality/value To best our knowledge, is one first attempts factor effect contextual (i.e. effectiveness) TPB equations.

Язык: Английский

A Qualitative Examination of Human Resource Information Systems (HRISs): A Strategic Tool for SMEs in Northern Thailand DOI
Mahmoud Moussa,

Frank Nyamrunda,

Ehsan Abedin

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
The Impact of Technological Advancements on Human Resource Management Practices: Adapting to the Digital Era DOI Creative Commons

Amer Hani Al-Qassem,

Hazim Ryad Momani,

Zeyad Alkhazali

и другие.

Data & Metadata, Год журнала: 2025, Номер 4, С. 731 - 731

Опубликована: Март 19, 2025

Introduction: In today's digital era, the process of digitalization has increasingly become a significant factor for organizations striving to enhance productivity, efficiency, and competitiveness. The adoption technologies such as Artificial Intelligence (AI), automation, cloud platforms revolutionized various business operations, especially in Human Resource Management (HRM). These have been pivotal transforming HR practices by improving data management, enhancing staff training, streamlining communication processes. This research aims examine role impact on HRM practices, with focus making these processes more efficient faster age.Methods: A mixed-methods approach was adopted this research. Qualitative collected through review journals articles accessed via Google Scholar, which provided insights into broader trends technology use HRM. For quantitative data, survey conducted using Forms, targeting 200 managers across different industries, including retail, automobile, others. consisted 10 close-ended questions capture extent practices. qualitative analyzed thematic analysis, identifying recurring themes patterns responses, while processed statistical analysis SPSS tool.Results: study revealed that play vital industries. streamline key functions recruitment talent acquisition, enabling informed decision-making. Additionally, they contribute significantly automating training development processes, well performance management. Overall, essential effectiveness, strategic capabilities HRM.Conclusions: underscores critical diverse By functions, enable make decisions, reduce operational costs, improve overall performance. Organizations should continue embrace transformation remain competitive meet evolving demands workforce. findings offer valuable benefits provide foundation further exploration integration within organizations.

Язык: Английский

Процитировано

0
Adapting to Generation AI: Navigating the Future of Business and Technology DOI

T Mangaiyarkarasi,

S. Catherine,

K. Kalaiselvi

и другие.

Emerald Publishing Limited eBooks, Год журнала: 2025, Номер unknown, С. 13 - 33

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0
Artificial Intelligence Models Accuracy for Odontogenic Keratocyst Detection From Panoramic View Radiographs: A Systematic Review and Meta‐Analysis DOI Creative Commons
Reyhaneh Shoorgashti, Mohadeseh Alimohammadi, Sana Baghizadeh

и другие.

Health Science Reports, Год журнала: 2025, Номер 8(4)

Опубликована: Март 31, 2025

ABSTRACT Background and Aims Odontogenic keratocyst (OKC) is a radiolucent jaw lesion often mistaken for similar conditions like ameloblastomas on panoramic radiographs. Accurate diagnosis vital effective management, but manual image interpretation can be inconsistent. While deep learning algorithms in AI have shown promise improving diagnostic accuracy OKCs, their performance across studies still unclear. This systematic review meta‐analysis aimed to evaluate the of models detecting OKC from Methods A search was performed 5 databases. Studies were included if they examined PICO question whether (I) could improve (O) radiographs (P) compared reference standards (C). Key metrics including sensitivity, specificity, accuracy, area under curve (AUC) extracted pooled using random‐effects models. Meta‐regression subgroup analyses conducted identify sources heterogeneity. Publication bias evaluated through funnel plots Egger's test. Results Eight meta‐analysis. The sensitivity all 83.66% (95% CI:73.75%–93.57%) specificity 82.89% CI:70.31%–95.47%). YOLO‐based demonstrated superior with 96.4% 96.0%, other architectures. analysis indicated that model architecture significant predictor performance, accounting portion observed However, also revealed publication high variability (Egger's test, p = 0.042). Conclusion models, particularly architectures, OKCs shows strong capabilities simple cases, it should complement, not replace, human expertise, especially complex situations.

Язык: Английский

Процитировано

0
How AI‐Enabled Drivers Inspire Sustainability‐Oriented Entrepreneurial Intentions: Unraveling the (In)congruent Effects of Perceived Desirability and Feasibility From the Entrepreneurial Event Model Perspective DOI
Cong Doanh Duong

Sustainable Development, Год журнала: 2025, Номер unknown

Опубликована: Апрель 4, 2025

ABSTRACT This study aims to examine how generative artificial intelligence adoption and perceived capacities influence sustainability‐oriented entrepreneurial intentions through psychological mechanisms, including desirability feasibility. Despite growing research interest in entrepreneurship, the role of technological enablers, particularly intelligence, shaping has been underexplored. To achieve this objective, an advanced approach—polynomial regression with response surface analysis—was employed test formulated hypotheses using data from 385 participants. The further shows that improve significantly when feasibility are aligned but remain unaffected by misalignment. Generative shown directly indirectly enhance feasibility, highlighting dual as a practical enabler motivator. These findings contribute extent literature indicating technologies foster entrepreneurship. Moreover, these provide valuable insights for policymakers, educators, organizations demonstrating can be leveraged promote sustainable innovation By integrating into education policy frameworks, stakeholders better support development entrepreneurs advance global sustainability goals.

Язык: Английский

Процитировано

0
A Bibliometric Review on the Use of Artificial Intelligence in Human Resources Management DOI
Gültekin Altuntaş, Yelda İNANÇ HOŞ, İlknur Çevik Tekin

и другие.

Advances in human resources management and organizational development book series, Год журнала: 2025, Номер unknown, С. 1 - 46

Опубликована: Янв. 31, 2025

This study aims to investigate studies on the use of artificial intelligence in human resources management last 10 years using bibliometric method. By searching keywords “Human Resources Management”, Resource Resources”, Resource”, “Artificial Intelligence”, “Machine Learning”, “Deep Narrow General Super “Generative Artificial AI”, and their abbreviations such as HRM, AI, so Web Science Core Collection database July 22, 2024, 47,955 scholar works have been accessed. The filtering process has yielded a data set consisting 949 publications, which analyzed analysis method by software, VOSviewer with version 1.6.20. reveals leading authors institutions significant contributions provides holistic view AI applications highlighting both opportunities challenges an interdisciplinary perspective.

Язык: Английский

Процитировано

0
Identifying Enablers and Barriers to Using Artificial Intelligence in Human Resource Management Practices DOI
Shravan Chandak, Ruchi Sao, Parihar Suresh Dahake

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Inteligencia artificial en la mejora del talento humano y gestión del conocimiento en organizaciones: una revisión sistemática en Scopus DOI Creative Commons

J. Urbina

Revista Cientifica de Sistemas e Informatica, Год журнала: 2025, Номер 5(1), С. e889 - e889

Опубликована: Янв. 20, 2025

Este estudio analiza la aplicación de inteligencia artificial (IA) en gestión del talento humano y el conocimiento organizacional mediante una revisión sistemática 50 artículos científicos indexados Scopus. Se empleó metodología documental con criterios selección basados relevancia actualidad. identificaron las principales aplicaciones IA optimización procesos administrativos, personalización programas formación toma decisiones estratégicas basadas datos. Entre los enfoques analizados destacan aprendizaje automático, minería datos sistemas expertos, cuales han mejorado evaluación desempeño, personal conocimiento. Los resultados evidencian que ha incrementado eficiencia talento, aunque persisten desafíos como calidad datos, resistencia sesgos algoritmos selección. concluye adopción recursos humanos sigue crecimiento, promoviendo modelos más adaptativos. Sin embargo, es necesario abordar sus limitaciones marcos normativos estrategias supervisión garanticen implementación ética, equitativa alineada objetivos organizacionales.

Процитировано

0
New forms of integration between universities and employers in the context of staff shortage in the region DOI Open Access

E. A. Sysoeva,

I. F. Maltseva,

Н. В. Шевцов

и другие.

Russian Journal of Industrial Economics, Год журнала: 2025, Номер 18(1), С. 149 - 161

Опубликована: Фев. 26, 2025

The staff shortage is becoming increasingly acute. In some regions, the number of open vacancies several times higher than amount submitted resumes from applicants. All this makes it necessary to organize system work in sphere employment. Obviously, essential ensure medium- and long-term planning staffing requirement regional sectoral context. Currently, Russian experts are only working out unified approaches making forecasts labor market needs for qualified specialists workers. Development a method forecasting will make possible reduce labour disbalance future, generate admission control figures certain specializations more reasonably. Interaction with students young context companies search new forms cooperation educational institutions. authors article present their own classification existing employeruniversity Three groups identified as regular (dual Master’s degree, targeted training, etc.), irregular (virtual internships, field trips, case studies, design analysis sessions, etc.) platforms aimed at facilitation reveal peculiar features each presented group adduce results survey on topic employment conducted among employers, they also study impact artificial intelligence market.

Язык: Английский

Процитировано

0
Harnessing artificial intelligence for human resources management: Tools, advantages, and risks in the energy sector DOI Creative Commons

Fawzieh Mohammed Masa’d,

Tamara Adel Al-maaitah,

Dirar Abdelaziz Al-Maaitah

и другие.

E3S Web of Conferences, Год журнала: 2024, Номер 541, С. 02004 - 02004

Опубликована: Янв. 1, 2024

The main goal of the study is aimed at determining features use artificial intelligence in HR energy sector. relevance and necessity due to increasing intensity introduction all sectors world economy, which necessitates need improve existing search for new management approaches companies technologies into business processes justified. Artificial tools are considered, advantages disadvantages each them highlighted. focus on companies: personnel training development. ways using its impact efficiency prospects development systems, difficulties, dangers risks covered. results can be used practice when organizing a human resource strategy company sector trending ensure these processes.

Язык: Английский

Процитировано

3