Consumer attitudes and strategic marketing in the adoption of autonomous driving technologies
Is this your thesis?
This record came from a bulk archive import. If it’s yours, link it to your profile.
Abstract (EN)
The aim of this study is to gain an in-depth understanding of consumers' attitudes, perceptions, and trust levels towards autonomous driving technologies in Turkey. This thesis also provides recommendations for strategic approaches and regulations necessary to increase consumer acceptance of autonomous driving technologies in Turkey. In the first phase of the research, a survey was conducted with approximately 200 participants to collect data. In the second phase, semi-structured interviews were carried out with 20 individuals selected based on specific characteristics related to their attitudes towards technology. The qualitative data obtained were analyzed using Thematic Analysis to evaluate participants' attitudes towards technology, their awareness of autonomous driving technologies, their trust perceptions, and the potential for these technologies to be integrated into daily life. The findings indicate that participants generally find autonomous driving technologies beneficial, but factors such as loss of control, safety concerns, and infrastructure deficiencies negatively affect their trust. It was observed that among the participants, those who approached autonomous driving technologies more positively did so after hearing from friends, obtaining information through news and videos, or directly experiencing the technology.
Author
Pelin Azizoğlu Tonya
Institution
TOBB Economics and Technology University
Division of Business Administration
How to Cite
Pelin Azizoğlu Tonya (Master Thesis). Consumer attitudes and strategic marketing in the adoption of autonomous driving technologies, 2024, TOBB Economics and Technology University.
Keywords
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from TOBB Economics and Technology University
- Extracting the features of drilling foams with image processing techniques and data analysis using artificial neural networks(2007)
- Automatic web services execution engine with qos support(2007)
- Usage of information theory to control the qos and energy consumption for wireless sensor networks(2007)
- Low power techniques for superscalar microprocessors(2007)
- Hardware design for predicting widths of values produced in microprocessors(2007)
- Soft error detection by using tag comperator in microprocessors(2007)