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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Assessing the Role of Critical Value Factors (CVFs) on Users’ Resistance of Urban Search and Rescue Robotics

Brown, Marion A. 01 January 2018 (has links)
Natural and manmade disasters have brought urban search and rescue (USAR) robots to the technology forefront as a means of providing additional support for search and rescue workers. The loss of life among victims and rescue workers necessitates the need for a wider acceptance of this assistive technology. Disasters, such as hurricane Harvey in 2017, hurricane Sandy in 2012, the 2012 United States tornadoes that devastated 17 states, the 2011 Australian floods, the 2011 Japan and 2010 Haiti earthquakes, the 2010 West Virginia coal mine explosions, the 2009 Typhoon caused mudslides in Taiwan, the 2001 Collapse of the World Trade Center, the 2005 Hurricane Katrina, the 1995 Oklahoma City bombing, and the 1995 Kobe Japan earthquake all benefited from the use of USAR. While there has been a push for use of USAR for disaster, user resistance to such technology is still significantly understudied. This study applied a mixed quantitative and qualitative approach to identify important system characteristics and critical value factors (CVFs) that contribute to team members’ resistance to use such technology. The populations for this study included 2,500 USAR team members from the Houston Professional Fire Fighters Association (HPFFA), and the expected sample size of approximately 250 respondents. The main goal of this quantitative study was to examine system characteristics and CVFs that contribute to USAR team members’ resistance to use such technology. System characteristics and CVFs are associated with USAR. Furthermore, the study utilized multivariate linear regression (MLR) and multivariate analysis of covariance (ANCOVA) to determine if, and to what extent, CVFs and computer self-efficacy (CSE) interact to influence USAR team members’ resistance to use such technology. This quantitative study will test for significant differences on CVF’s, CSE, and resistance to use such technology based on age, gender, prior experience with USAR events, years of USAR experience, and organizational role. The contribution of this study was to reduce USAR team members’ resistance to use such technology in an effort minimize risk to USAR team members while maintaining their lifesaving capability.

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