Dual Focus of Technology Acceptance and Technology Resistant of Older Adults: Two-phased Multi-analytical Models Tested in Sri Lanka
Vilani Sachithra *
Faculty of Management Studies and Commerce, University of Sri Jayewardenepura, Sri Lanka.
L. D. C. S. Subhashini
Faculty of Management Studies and Commerce, University of Sri Jayewardenepura, Sri Lanka.
U. S. Samarasinghe
Faculty of Management Studies and Commerce, University of Sri Jayewardenepura, Sri Lanka.
*Author to whom correspondence should be addressed.
Abstract
Aim: Digital health care service receives increasing attention and there is an extensive portion of the elders that does not utilize digital health care services. The study aims to develop an integrated model based on a human-centric view, socio- technical traits, and aging specific constructs to offer an in-depth view of older adults’ acceptance and resistance of technology.
Design: The study integrated Theory of Planned Behavior, Status quo bias, Equity-implementation model and Unified Theory of Acceptance and Use of Technology2 model to come up with a dual phenomenon conceptual model. Two-phased multi-analytical models were used. The scope of the study included older adults (people aged 65 years or older) in Sri Lanka.
Results: The multiple regression analysis and Model 4 of the PROCESS macro results revealed that human centric, socio technical and aging specific factors significantly influence on elders to use technology; interestedly, human-centric factors negatively influenced. The data is trained and tested using a deep learning approach. The model can performed F-measure of 72.85% for predicting technology acceptance or rejection.
Implications: Understanding personal variables such as human-centric and aging specific that affect the adaptation and resistant process in technology provides valuable information for inventors and social developers in the design and implementation of technology for the elder community.
Originality: The study extended the technology acceptance models based on human-centric perspective, socio-technical characteristics, and aging specific constructs for a more comprehensive understanding of consumer acceptance or resistance of technology.
Keywords: Aging Specific, deep learning, human centric, technology acceptance, technology rejection, socio technical