Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Suhaiza Zailani and Mohammad Iranmanesh
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general…
Abstract
Purpose
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.
Design/methodology/approach
To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.
Findings
The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.
Originality/value
This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.
Details
Keywords
Behzad Foroughi, Mohammad Iranmanesh, Morteza Ghobakhloo, Madugoda Gunaratnege Senali, Nagaletchimee Annamalai, Bita Naghmeh-Abbaspour and Abderahman Rejeb
ChatGPT is a cutting-edge chatbot powered by artificial intelligence that could revolutionise and advance the teaching and learning process. Drawing on the technology acceptance…
Abstract
Purpose
ChatGPT is a cutting-edge chatbot powered by artificial intelligence that could revolutionise and advance the teaching and learning process. Drawing on the technology acceptance model (TAM) and information system (IS) success model, this study aims to investigate determinants of students’ intention to use ChatGPT for education purposes.
Design/methodology/approach
The partial least squares technique was used to analyse 406 usable data collected from university students in Malaysia.
Findings
The results confirmed the relationships between perceived usefulness (PU), perceived ease of use (PEU), attitude and intention to use proposed by TAM. PU and PEU are influenced by system quality. Surprisingly, trust in information moderates negatively the influences of PEU and PU on attitude.
Practical implications
The findings provide insight for higher education institutions, unit instructors and ChatGPT developers on what may promote the use of ChatGPT in higher education.
Originality/value
The study contributes to the literature by exploring the determinants of ChatGPT adoption, extending the TAM model by incorporating IS success factors and assessing the moderating effect of trust in information.