An examination of the factors influencing consumers' intention to use smart home appliances within the technology acceptance model framework
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
The emergence of new smart home technologies has brought about applications that can simplify our everyday activities. It is crucial for manufacturers to comprehend the reasons why these innovative applications are either accepted or rejected by consumers. Numerous models have been put forth to identify these reasons, with the Technology Acceptance Model (TAM) being the most prevalent one. This study aims to utilize the TAM to analyze the fundamental factors that impact users' willingness to adopt smart home technologies that are becoming more prevalent in our lives. Data were collected by a online survey instrument in Turkey from 350 smart appliances owners. Structural equation modeling(SEM) and Confirmatory factor analyses (CFA) were used to examine the research hypothesis. Findings showed trust, usefulness and ease of use play a vital role to increase positive attitudes toward intention to use.
Author
İsmail Keskin
How to Cite
İsmail Keskin (Master Thesis). An examination of the factors influencing consumers' intention to use smart home appliances within the technology acceptance model framework, 2023, Bahçeşehir University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Bahçeşehir University
- Use of artificial intelligence in marketing communication and brand posting and the use of artificial intelligence in advertising communication(2023)
- A proposal for a method to serve musical quality through linguistic elements in jazz vocal music(2023)
- Data-driven financial technologies and personal data protection law(2023)
- Fabrication and characterization of a biodegradable Cannabis sativa oil-based poly(lactic acid) (PLA) wound dressing and investigation of its antibacterial and wound healing properties(2023)
- The effect of gold nanoparticles synthesized by green synthesis method on GSK-3 beta mRNA expression in human neuroblastoma cell line(2023)
- Predicting potential resignations in the companies using machine learning techniques(2023)