برنامه گردشگری سیار مبتنی بر موقعیت شخصی
ترجمه نشده

برنامه گردشگری سیار مبتنی بر موقعیت شخصی

عنوان فارسی مقاله: تعیین کنندگان تصمیم رفتاری برای استفاده از برنامه گردشگری سیار مبتنی بر موقعیت شخصی: یک مطالعه تجربی توسط ادغام TAM با ISSM
عنوان انگلیسی مقاله: Determinants of behavioral intention to use the Personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM
مجله/کنفرانس: سیستم های کامپیوتری نسل آینده-Future Generation Computer Systems
رشته های تحصیلی مرتبط: گردشگری و توریسم و جهانگردی، مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: طراحی و تولید نرم افزار، مهندسی نرم افزار
کلمات کلیدی فارسی: خدمات مبتنی بر موقعیت، بهینه سازی الگوریتم کلونی مورچه (Ant)، مدل پذیرش تکنولوژی، مدل موفقیت سیستم اطلاعات
کلمات کلیدی انگلیسی: Location-based Services, Ant Colony Optimization, Technology Acceptance Model, Information System Success Model
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): http://dx.doi.org/10.1016/j.future.2017.02.028
دانشگاه: Department of Management Information Systems, National Chung Hsing University, Taichung 402, Taiwan, R.O.C
صفحات مقاله انگلیسی: 41
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 7.007 در سال 2018
شاخص H_index: 93 در سال 2019
شاخص SJR: 0.835 در سال 2018
شناسه ISSN: 0167-739X
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
کد محصول: E12086
فهرست مطالب (انگلیسی)

Abstract

1. Introduction

2. Literature review

3. System design and performance evaluation

4. Assessment of intention to use

5. Result and analysis

6. Conclusion

Acknowledgment

References

بخشی از مقاله (انگلیسی)

Abstract

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).