Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Most studies of consumer preferences and expectations for home robots focus on either older adults or single-person households (SPHs). However, with the rise in voluntary SPHs among young adults and seniors, it is critical to compare both age and household types in robot research. This study explored perceptions of home robots and willingness to use their features based on age and household type, in the context of the expanding home robot market in Republic of Korea. An online survey of 400 individuals was conducted, targeting young SPHs and multi-person households (MPHs) in their 20s and 30s as well as older SPHs and MPHs in their 50s and 60s. The survey covered four robot task categories, with 40 items derived from previous research: household chores (20 items), personal care (seven items), leisure/companion (nine items), and health (four items). The results helped predict the main target groups for each in-home robot task by identifying items that showed differences in responses between groups and interpreting these based on age, household type, and their combination. The study provides valuable data on consumer expectations, highlighting differences in responses according to both age and household type, offering insights for the robotics industry to effectively target their products.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11591169 | PMC |
http://dx.doi.org/10.3390/bs14111070 | DOI Listing |
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