A Comparative Study of Influencing Factors to Use Mobile Delivery Applications Based on the UTAUT Model

2018 ◽  
Vol 42 (3) ◽  
pp. 97-119
Author(s):  
Chun Cui ◽  
Sun-Hee Seo
2021 ◽  
pp. 1-34
Author(s):  
Ikram Ullah Khan ◽  
Zahid Hameed ◽  
Sajjad Nawaz Khan ◽  
Safeer Ullah Khan ◽  
Muhammad Tahir Khan

Energy ◽  
2019 ◽  
Vol 175 ◽  
pp. 1009-1020 ◽  
Author(s):  
Ya Wu ◽  
JingRong Su ◽  
Ke Li ◽  
Chuanwang Sun

2003 ◽  
Vol 117 (6) ◽  
pp. 444-448 ◽  
Author(s):  
Mangal Singh ◽  
Ashutosh Rai ◽  
Sarmishtha Bandyopadhyay ◽  
S. C. Gupta

Myringoplasty is an established procedure. However, the quest is on to improve the results further by studying the different influencing factors, that could possibly affect the outcome. In the present randomized prospective study of one year’s duration, 60 patients having dry, large and subtotal perforations of the tympanic membrane were subjected to myringoplasty, 30 by the overlay technique and 30 by the underlay technique keeping all other influencing factors constant. The graft take-up rate was found to be the same (93.3 per cent) in both techniques but the underlay technique was judged to be better because of its technical ease, better assessment of ossicular chain integrity and mobility, less time consumption (55 minutes vs 90 minutes), earlier healing of graft (four to six weeks vs six to eight weeks), hearing gain in more patients (92.8 per cent vs 57.1 per cent) and fewer minor complications (6.6 per cent vs 33.3 per cent).


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jian Chen ◽  
Rui Li ◽  
Mi Gan ◽  
Zhiyan Fu ◽  
Fatao Yuan

Driverless buses are expected to play a vital role in the future, and better public acceptance will provide a social foundation for its development. In this study, two new variables, personal innovativeness (PI) and perceived risk (PR), were incorporated into the integrated technology acceptance model (UTAUT, unified theory of acceptance and use of technology) to construct an extended model, which was then applied to explore the influencing factors for the public acceptance of driverless buses. The quality of this extended model was verified through survey data collected in Chongqing, China. The structural equation modeling (SEM) method was adopted to quantitatively describe the impact of each factor on acceptance intention (AI) as well as the mutual influence relationships between the factors. The moderating effects of demographic attributes (gender, age, and education level) on each factor in the model were also analyzed. The results showed that PI and PR are the most critical factors that affect the public’s acceptance intention; effort expectancy (EE), performance expectancy (PE), social influence (SI), and facilitating condition (FC) can also determine the acceptance intention to a certain extent; gender, age, and education level have exhibited significantly different moderating effects on the influencing factors. The explanatory power of the current research model for acceptance intention has reached 48%. This study has confirmed the applicability of the extended UTAUT model to the research of driverless bus acceptance and the research outcomes can serve as a reference basis for improving the service quality of driverless buses in China.


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