ICCK

Dr. Carolina Ditan

De La Salle Araneta University, Philippines/Jose Rizal University

Section 01

Academic Profile

Dr. CAROLINA D. DITAN, MBA, DBA, candidate for PhD in Human Resource Management. Dr. Ditan was the former Dean of the College of Business, Management and Accountancy of the De La Salle Araneta University and formerly the OIC- Dean of the College of San Benildo Rizal. Currently, is a professor of the Graduate School of DLSAU and Graduate School of JRU and CMU. Dr. Ditan was a former professor of the Graduate School of UMAK and PLMAR. She authored several books published by National Bookstore, Redman Printing and Anvil Publishing and a member of the Samahan ng mga Manunulat na Pilipino, Inc. She has written researches published in International Peer-Reviewed Journals and an External Reviewer of the Associations of Training Institutions for Foreign Trade in Asia and the Pacific (ATIFTAP).

Section 02

Editorial Roles

This user currently does not serve as an editor for any ICCK journals.

Section 03

ICCK Publications

Open Access | Research Article | 08 April 2026
A TAM-based Human-Machine Synergy Model for Automation and Industry 4.0 Adoption
PWU Journal of Research, Innovation, and Transformation | Volume 1, Issue 2: 65-72, 2026 | DOI: 10.62762/JRIT.2026.810897
Abstract
The acceleration of Industry 4.0 has compelled enterprises to integrate automation, cyber-physical systems, and analytics into everyday operations. Despite rapid digitalization, the effectiveness of these initiatives depends largely on the human capacity to accept and collaborate with machines. This study applies the Technology Acceptance Model (TAM) to examine behavioral and organizational factors influencing automation adoption among 900 professionals across manufacturing, logistics, and service sectors. Using descriptive-correlational design and partial least squares structural equation modeling (PLS-SEM), the study investigates how perceived usefulness (PU) and perceived ease of use (PEO... More >

Graphical Abstract
A TAM-based Human-Machine Synergy Model for Automation and Industry 4.0 Adoption