Quantitative Assessment on Investigation on the Impact of Artificial Intelligence on HR Practices and Organizational Efficiency for Industry 4.0 DOI
Aparna Sharma,

Shalu Tyagi,

Shilpa Kanthalia

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 66 - 83

Published: Dec. 22, 2024

Language: Английский

How ChatGPT adoption stimulates digital entrepreneurship: A stimulus-organism-response perspective DOI
Cong Doanh Duong, Thanh Hieu Nguyen

The International Journal of Management Education, Journal Year: 2024, Volume and Issue: 22(3), P. 101019 - 101019

Published: July 3, 2024

Language: Английский

Citations

18

Artificial intelligence technologies and entrepreneurship: a hybrid literature review DOI Creative Commons
Sebastián Uriarte, Hugo Baier-Fuentes, Jorge Espinoza Benavides

et al.

Review of Managerial Science, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 24, 2025

Language: Английский

Citations

2

ChatGPT adoption in entrepreneurship and digital entrepreneurial intention: A moderated mediation model of technostress and digital entrepreneurial self-efficacy DOI Creative Commons
Bui Huy Nhuong, Cong Doanh Duong

Equilibrium Quarterly Journal of Economics and Economic Policy, Journal Year: 2024, Volume and Issue: 19(2), P. 391 - 428

Published: June 30, 2024

Research background: In the rapidly evolving milieu of digital entrepreneurship, integration artificial intelligence (AI) technologies, exemplified by ChatGPT, has witnessed burgeoning prominence. However, there remains a dearth understanding regarding relationships between ChatGPT adoption in entrepreneurship and individuals’ cognitive career processes entrepreneurship. Purpose article: The primary aim research is to adopt Social Cognitive Career Theory moderated mediation model unravel intricate dynamics that characterize impact entrepreneurial intentions, underlying mechanism self-efficacy technostress. Methods: Drawing on sample 1326 respondents Vietnam using stratified sampling approach, first, Cronbach’s alpha confirmatory factor analysis were used test reliability validity scales; after that, Harman’s single-factor common latent employed method bias; finally, PROCESS macro approach was utilized hypothesized model. Findings & value added: Our findings reveal positive impacts intentions. Moreover, found significantly mediate intention. Furthermore, technostress emerges as significant negative moderator, influencing both This study thus contributes literature advancing our how AI technologies shape aspirations, offering valuable insights for scholars practitioners navigating transformative landscape

Language: Английский

Citations

9

Artificial intelligence in international business DOI
Vanessa Ratten, Paul Jones, Vítor Braga

et al.

Thunderbird International Business Review, Journal Year: 2024, Volume and Issue: 66(2), P. 127 - 133

Published: Feb. 19, 2024

Abstract Artificial intelligence is poised to transform international business through the adoption of new digital technology practices as part fourth industrial revolution. The how, when, and why artificial implementation in still somewhat unknown but will likely significantly influence performance outcomes, market interpretation, risk prediction, consumer interactions, technology‐based metrics. With greater emphasis on intelligence‐based tools, future practice require literacy. This means managers need improve way they analyze terms appreciating its usefulness while maintaining privacy mitigation strategies. In this editorial, we discuss current developments regarding with goal identifying research areas importance.

Language: Английский

Citations

4

The Nexus of Artificial Intelligence and Entrepreneurship Research: Bibliometric Analysis DOI Creative Commons
Atthaphon Mumi, Niramarn Ngammoh,

Asadang Suwanpakdee

et al.

Sustainable Futures, Journal Year: 2025, Volume and Issue: unknown, P. 100688 - 100688

Published: May 1, 2025

Language: Английский

Citations

0

Analysis of Research on Artificial Intelligence in Human Resources Management: A Bibliometric Analysis DOI Open Access
Edi Fajar Alidarma Wijaya, Ika Nurul Qamari

International Research Journal of Multidisciplinary Scope, Journal Year: 2024, Volume and Issue: 05(02), P. 108 - 121

Published: Jan. 1, 2024

This research aims to find contributors who have a major impact, observe the latest developments, and identify domains supporting factors that can guide future in field artificial intelligence (AI) human resource management integration. was conducted Within framework of many activities practices are present organisations. study utilises methodology involves conducting bibliometric analysis utilising Biblioshiny app. The sample for consists 298 papers obtained from Scopus database. objective is discover still relevant this theme. Three questions be identified were drawn up performed on documents retrieved scopus It found main focus very little despite impact resources enormous. Several studies investigated stakeholder perspectives practice applying application resources. hoped provide guidelines directions advancement use AI HR several organizations future.

Language: Английский

Citations

1

Emerging technologies and principle-based project management: a systematic literature review and research agenda DOI
Ammar Mohamed Aamer,

Adel Zadeh,

Prithvi Mali

et al.

Management Review Quarterly, Journal Year: 2024, Volume and Issue: unknown

Published: April 11, 2024

Language: Английский

Citations

0

Human resource management and artificial intelligence integration development and innovation DOI Creative Commons
Yang Yu

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract Artificial Intelligence is one of the important tools to realize effective management human resources. The article firstly investigates and finds out problems current salary satisfaction status employees column A a news center, designs job prediction model based on collaborative filtering algorithm separation standard Logistic regression results questionnaire, finally calculates economic benefits center. performance bonus center in 2019 showed steady upward trend as whole, with 107,908 yuan January 198,320 December. market value increased steadily 2020, reaching 171,134 230,370 In 2021, ~ June has not changed much, which 112,099 122,076 June. It can be concluded that proposed this paper high accuracy predicting column, shows an increasing year by year. seen from analysis after operating financial have been for better.

Language: Английский

Citations

0

Quantitative Assessment on Investigation on the Impact of Artificial Intelligence on HR Practices and Organizational Efficiency for Industry 4.0 DOI
Aparna Sharma,

Shalu Tyagi,

Shilpa Kanthalia

et al.

Communications in computer and information science, Journal Year: 2024, Volume and Issue: unknown, P. 66 - 83

Published: Dec. 22, 2024

Language: Английский

Citations

0