TY - JOUR
T1 - Seniors’ Knowledge-Based Digital Marginalization in the Era of Information Technology Advancements
AU - Li, Yanglin
AU - Yang, Yuezheng
AU - Shi, Shuyao
AU - Wang, Bin
AU - Chen, Guangquan
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2024/9
Y1 - 2024/9
N2 - In an era marked by rapid digitalization and the ubiquity of information technology, society is witnessing a transformative shift toward more sophisticated and intelligent living and working environments. While this technological wave is readily embraced by the younger generation, who find convenience and utility in its offerings, a pressing global concern looms large—the ever-escalating challenge of population aging, which has reached unprecedented levels. The elderly, though esteemed, often find themselves grappling with the intricacies of adapting to an array of digital products and services, resulting in a stark consequence: digital exclusion and division, effectively sidelining China’s elderly citizens in an increasingly digitized and intelligent society. Against this backdrop, the harsh spotlight cast by the COVID-19 pandemic on the elderly, seemingly relegated to the margins of society, underscores the glaring dearth of research dedicated to probing the nuances of digital exclusion among China’s older adults. This study takes up the crucial mission of dissecting the multifaceted factors contributing to digital exclusion and unraveling the intricate dilemmas surrounding digital inclusion for the elderly. Employing a multifaceted research approach, including offline questionnaires and online data collection, the study harnesses statistical analysis methods to uncover the underpinnings of digital rejection among China’s elderly. This analytical journey yields a treasure trove of influential factors, culminating in the creation of a comprehensive evaluation system. The study assigns appropriate weights to these influential factors and employs a random forest model to forecast the extent of digital exclusion among the elderly residing in diverse regions of Tianjin. As a culmination of this extensive investigative endeavor, the study offers a collection of recommendations and strategies aimed at alleviating the predicament of digital exclusion encountered by China’s elderly population in the contemporary internet age.
AB - In an era marked by rapid digitalization and the ubiquity of information technology, society is witnessing a transformative shift toward more sophisticated and intelligent living and working environments. While this technological wave is readily embraced by the younger generation, who find convenience and utility in its offerings, a pressing global concern looms large—the ever-escalating challenge of population aging, which has reached unprecedented levels. The elderly, though esteemed, often find themselves grappling with the intricacies of adapting to an array of digital products and services, resulting in a stark consequence: digital exclusion and division, effectively sidelining China’s elderly citizens in an increasingly digitized and intelligent society. Against this backdrop, the harsh spotlight cast by the COVID-19 pandemic on the elderly, seemingly relegated to the margins of society, underscores the glaring dearth of research dedicated to probing the nuances of digital exclusion among China’s older adults. This study takes up the crucial mission of dissecting the multifaceted factors contributing to digital exclusion and unraveling the intricate dilemmas surrounding digital inclusion for the elderly. Employing a multifaceted research approach, including offline questionnaires and online data collection, the study harnesses statistical analysis methods to uncover the underpinnings of digital rejection among China’s elderly. This analytical journey yields a treasure trove of influential factors, culminating in the creation of a comprehensive evaluation system. The study assigns appropriate weights to these influential factors and employs a random forest model to forecast the extent of digital exclusion among the elderly residing in diverse regions of Tianjin. As a culmination of this extensive investigative endeavor, the study offers a collection of recommendations and strategies aimed at alleviating the predicament of digital exclusion encountered by China’s elderly population in the contemporary internet age.
KW - Aging population
KW - Digital exclusion factors
KW - Elderly digital inclusion
KW - Knowledge-based economy
KW - Random forest analysis
UR - http://www.scopus.com/inward/record.url?scp=85176387770&partnerID=8YFLogxK
UR - https://link.springer.com/article/10.1007/s13132-023-01600-6
U2 - 10.1007/s13132-023-01600-6
DO - 10.1007/s13132-023-01600-6
M3 - Journal article
AN - SCOPUS:85176387770
SN - 1868-7865
VL - 15
SP - 12622
EP - 12650
JO - Journal of the Knowledge Economy
JF - Journal of the Knowledge Economy
IS - 3
ER -