A contemporary paradigm of travel industry: determinants of sharing economy adoption

• Main Authors: Ng, Qin En, Fong, Zhi Xin, How, Xun Hang, Ng, Hui Jie, Seow, Khai Jun
• Format: Final Year Project / Dissertation / Thesis
• Published: 2019
• Subjects: HF Commerce
• Online Access: http://eprints.utar.edu.my/3509/1/fyp_AC_2019_NQE.pdf; http://eprints.utar.edu.my/3509/

The phenomenal growth of technology has created a vibrant new domain for sharing economy (SE) in Malaysia travel industry. Despite of numerous limitations exist such as lack of rules and regulations established to safeguard consumers’ right in SE, it is still highly acceptable by the Malaysian. Consumer perception is always an issue in the acceptance towards SE adoption. Besides, mobile technology acceptability is a significant enabling part in SE as most of the SE online platforms are being accessed through mobile devices. Therefore, a research was conducted to examine how they affect consumer behavioral intention (BI) and SE adoption. The research objective is to study the determinants which influence SE participation in the travel industry. In this study, an enhanced framework was created by integrating Mobile Technology Acceptance Model (MTAM) with Extended Valence Framework for the purpose of establishing a comprehensive study pertaining to the determinants influencing SE adoption in the travel industry. It was proposed that perceived benefits (i.e. epistemic benefit & convenience), trust, mobile ease of use (MEU) and mobile usefulness (MU) have positive effects towards consumers BI in SE adoption, while perceived risk (i.e. psychological risk & physical risk) are negatively related to the BI in SE adoption. This research was a cross-sectional study with 500 sets of questionnaire delivered to travelers from Federal Territory of Kuala Lumpur, Selangor, Perak, Pahang, Kedah, and Johor which were rated by Department of Statistics Malaysia (DOSM) as the states with higher percentage of visitors. Each target respondent was selected based on their experience in travel and whether they had the basic knowledge about SE. Transportation hubs and airports were chosen as the sampling location in this study. Moreover, purposive sampling technique was applied and SAS Enterprise Guide 7.1 was adopted to perform analysis of data.