مقاله انگلیسی رایگان در مورد برنامه گردشگری سیار مبتنی بر موقعیت شخصی – الزویر 2019

With the advent of the two-day weekend and improvements in the public transit system, people have begun to focus on leisure activities. When the YouBike public bicycle system was installed in the city of Taichung, Taiwan, it created a convenient transportation system network that was set up perfectly for a tremendous impact on the local tourism industry. This has happened in parallel with the development and proliferation of smartphones and wireless networks. The functions of mobile applications (“apps”) have become more powerful over time, allowing people to access travel information and share their experiences almost instantaneously. Since a smartphone’s positioning system can be used to provide more personalized information and services, the development trend is heading toward location-based services (LBSs) that can bring the app’s functionality closer to the needs of the user. This study develops a personalized location-based mobile tourism application (PLMTA) for travel planning. The PLMTA combines hybrid filtering technology with the ant colony optimization (ACO) algorithm to make more efficient customized tourism recommendations. It allows users to more effectively search through travel information and arrange their trip. This study also integrates the technology acceptance model (TAM) and the information system success model (ISSM) to present a research model that explores users’ intention to use the PLMTA. The questionnaire survey method is used to collect our data, and the hypotheses are tested via structural equation modeling (SEM). The results show that information quality, perceived ease of use, and perceived usefulness significantly affect the intention to use PLMTA, while information quality and perceived convenience are found to have an influence on perceived usefulness. Information quality, system quality, and perceived convenience are found to significantly affect perceived ease of use, which consequently affects the intention to use the system.

Introduction

According to a survey by eMarketer (2014), the number of smartphone users reached 17.5 billion, globally, in 2014, having just passed 10 billion mark in 2012 [1]. In addition, the smartphone penetration rate is expected to be close to 50% in 2017 [1]. The booming development of smartphones and the increasing sophistication of positioning systems and navigation functions have spurred the constant development of new mobile apps. The smartphone’s powerful functionalities can be combined with location-based services (LBSs) which use the mobile phone’s positioning function to capture the user’s location in order to provide personalized services suitable to that location for greater convenience. The combinations of these smart technology applications and location-based services can be quite diverse. For example, retailers use indoor navigation technology to provide location-based services, using mobile “push” notifications to deliver ads, thus providing appropriate, personalized marketing based on the consumer’s location to enhance the quality of the customer experience. This kind of technology is set to become an important development trend in the future (Market Intelligence & Consulting Institute, 2015). Combining LBS and mobile phone apps has already become a global trend, providing convenient geographic information and information that relates directly to the user’s specific location. Examples include store promotions, exhibition activity information, coupons and mobile education. As location-based services have matured, Click-and-Mortar has become both a possibility and a reality (TELDAP e-Newsletter, 2010).