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Mobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.

The app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.

The high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.

The findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.

The previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.

Travelers are increasingly planning trips using smart travel planning apps to manage travel-related activities. They obtain their preferred tour itineraries with the use of these apps and subsequently choose their tour destinations. Therefore, the purpose of this study is to investigate the effects of smart tour itineraries on travelers and explain what drives the continual use of them.

Drawing on the unified theory of acceptance and the use of technology model and experiential consumption (UTAUT), the authors conducted this study in Malaysia with a sample of 307 travelers who are familiar with the use of mobile apps.

The results confirmed that all the UTAUT dimensions except the facilitating condition are significantly related to the intention to use the itinerary. Both the hedonic and utilitarian values in personal consumption significantly motivate the travelers in the behavioral intention to use the itinerary.

This paper offers a good explanation of how the itinerary plans can be used by examining the theories behind the current app’s usage. Many researchers have examined the adoption of the smart travel apps, which has rarely been tied to the antecedents that drive how the travelers use itineraries that are designed by the smart travel apps. This study contributes to the research regarding using the mobile travel apps by developing an integrative model to explain the traveler intentions to use smart travel itineraries.

游客越来越多地使用智慧旅游计划App来管理他们的旅游相关活动。他们通过这样的App获得行程从而选择他们旅游目的地。因此, 本论文旨在研究智慧旅游行程对游客的影响, 并探究哪些因素驱使他们继续使用智慧旅游行程。

本论文采用UTAUT模型, 在马拉西亚取样, 共搜集到307位熟悉移动App的游客数据。

研究论文结果肯定了UTAUT各项因素除了辅助条件, 其他因素都显著与使用智慧行程息息相关。享乐型价值和实用型价值都对游客个人使用行为有着显著效果。

本论文通过检验App使用理论解释了行程计划如何被使用。许多研究学者已经检验了智慧旅游App的使用, 但是很少真正与游客如何使用App生成行程的驱动因素相结合。本论文对理论有贡献, 通过开发整合模型以解释游客使用智慧旅游行程的行为。

The purpose of this study investigate the antecedents the adoption of tour itineraries from smart travel apps. Travelers are progressively expanding their smart travel planning applications to organize their trip-related activities. With the help of these apps, users achieve their favorite tour itineraries and choose their preferred destinations.

This study aimed to examine the results of smart tour itineraries on travelers and elucidate the motivations for their continual use and why travel experts are increasingly using smart tour itineraries. Innovation resistance and experiential consumption theories were used in this study. SmartPLS 3.2.8 was used to consider 682 valid samples using structural equation modeling (SEM).

This analysis identified the following crucial factors: usage, value, risk and traditional barriers. Moreover, utilitarian and hedonic values significantly affected barriers. Finally, theoretical and practical suggestions are presented along with future research directions.

This study encompasses the tender of innovation resistance theory to travel itineraries by integrating experiential consumption theory in the context of smart tourism apps.

This study aims to investigate tourists’ impressions of the smart destinations model from the socio-technical systems and the technology–organization–environment (TOE) perspectives. Specifically, it aims to explore how information source credibility and cloud infrastructure influence tourists’ use of intelligent technology.

This measurement development is based on prior literature; after being evaluated for face and content validity, the authors used random sampling to collect data and conducted a field survey of tourists through Taoyuan Airport and using the airport MRT between December 2022 and March 2023. After confirming that tourists knew the destination information and had experience using travel-related mobile applications to plan their itinerary, the authors further invited tourists to participate in the survey, and 512 valid questionnaires were analyzed by the structural equation modeling approach.

The finding pointed out that source credibility and intelligent technology were innovative technologies that benefitted tourists, as were mobile travel planning apps, which created a relational context based on interests and activities from the socio-technical and TOE perspectives.

Technological innovation is closely related to the development of smart cities; tourists who used travel itineraries successfully understood travel-related actions and significantly had more positive affective images of the city.

Considering the limited understanding of determinants influencing the adoption of smart mobile tourism app (SMTA) featuring augmented reality (AR) and big data analytics (BDA), privacy concern (PC) and the risk of privacy information disclosure (PI) have threatened SMTA adoption. This study aims to propose an expanded consumer acceptance and use of information technology (UTAUT2) model by including new contextual components, integrated with privacy calculus theory (PCT) model to examine the determinants influencing behavioural intention (BI) to use SMTA.

Personal innovativeness (IN) and privacy information disclosure (PI) are incorporated in UTAUT2 model to determine its effect on SMTA featuring AR and BDA technologies from smart perspective. Both privacy concern (PC) and privacy risk (PR) derived from PCT model are also included to determine its influences on an individual's willingness to disclose privacy information for better-personalised services. We collected responses from 392 targeted participants, resulting in a strong response rate of 84.66%. These responses were analysed statistically using structural equation modeling in both SPSS 22.0 and SmartPLS 3.0.

Findings showed that personal innovativeness (IN), habit (HT) and performance expectancy (PE) significantly affect behavioural intention (BI) while privacy concern (PC) significantly affect privacy information disclosure (PI) to use SMTA. In contrast, effort expectancy (EE), hedonic motivation (HM) and privacy information disclosure (PI) had no significant effects on behavioural intention (BI) while privacy risk (PR) had no significant effects on privacy information disclosure (PI) to use SMTA.

The study findings help tourism practitioners in better comprehending recent trends of SMTA adoption for establishing targeted marketing strategies on apps to improve service quality. In addition, it enables app development companies acquire app users’ preferences to enhance their app development for leading app usage.

The main objectives of this study are to (1) explore underlying components and attributes of travel applications that influence traveler usage intention and (2) investigate which contents should be prioritized to increase the efficiency of travel apps.

This study uses importance–performance map analysis (IPMA) with an innovative approach (i.e. generalized structured component analysis [GSCA]) to identify components and attributes that have relatively high and low significance for the target construct (i.e. travel app's usage intention).

An integrated model influenced by three components (i.e. entertainment, travel review and medical and emergency information is proposed to have an impact on travelers' intention to use travel apps). The IPMA results indicate that restaurant and shopping receive the utmost emphasis from Thai domestic tourists who use travel apps, and sports and attraction are regarded as less critical attributes.

The app content scales identified in this study can be used as a basic framework for app developers, service providers and tourism authorities to design a travel app. The IPMA results also help concerned practitioners to make decisions on which contents/attributes should be incorporated and improved.

This study implements IPMA using a GSCA estimator to present the standard results reporting on the path coefficients of each of the attributes of travel app services. The results not only contribute to the improvement of app features and services, but also suggest an innovative approach for generating pertinent IPMA results with GSCA, thus contributing to the theoretical and methodological advancement in hospitality and tourism areas.

The purpose of this study is to propose and test a theoretical model investigating factors that influence travelers’ intention to use travel-related information shared by other travelers through a novel category of travel-focused mobile applications, referred to as travel-tracking mobile applications (TTMAs).

Data collected from mobile app users who traveled for leisure purposes were used to test an extended version of the Unified Theory of Acceptance and Use of Technology 2, adding trust and privacy concerns as new constructs to the existing framework.

The current study found empirical and significant evidence that performance expectancy, effort expectancy, hedonic motivation and trust positively; and system privacy negatively influenced travelers’ intention to adopt TTMA to follow other travelers’ experiences.

Limitations and directions for future research are widely explored in the final section of this study.

Practical implications for tourism, travel and hospitality technology companies, TTMA developers and entrepreneurs of travel-related and/or location-based mobile applications are discussed following the empirical findings of this study.

The current study findings add to the body of knowledge in the field of travel technology acceptance, and provide practical implications, especially for entrepreneurs and tourism technology vendors.

本研究提出并测试了一个理论模型, 以探讨影响旅行者使用由其他旅行者提供的旅行相关信息的意图的因素。该信息通过一种名为“旅行追踪移动应用程序（TTMA）” 的新型旅游应用程序提供。

本研究从休闲目的旅行的移动应用用户处收集数据, 测试了扩展版的“统一技术接受与使用模型 2（UTAUT2）”, 并在现有框架中新增了信任和隐私担忧作为构建要素。

本研究发现的显著证据表明, 绩效预期、努力预期、享乐动机和信任对旅行者采用TTMA跟随其他旅行者体验的意图有正向影响; 而系统隐私对其意图有负面影响。

根据本研究的实证发现, 旅游、旅行和酒店技术公司, TTMA开发者, 以及与旅行或基于位置的移动应用相关的企业家可以从中获得实际应用启示。本研究的结果丰富了旅游技术接受领域的知识体系, 并为企业家和旅游技术供应商, 尤其是旅行科技企业家, 提供了实际应用指导。

Smart tourism is undergoing a trend of rapid development. The quality of service in smart tourism forms the basis of tourists’ evaluations, it needs to be investigated. However, as high-quality smart tourism technologies (STTs) can enhance the overall tourist experience and increase tourist satisfaction, and there is no standard service quality evaluation system for STTs. Therefore, this study aims to explore how the quality of STTs is evaluated from the tourist’s perspective.

In this study, the authors develop a measurement scale for smart tourism technology quality (STTQUAL) based on qualitative interviews, the Delphi method and a survey conducted in three cities that use smart tourism: Macau, Chengdu and Hangzhou.

The STTQUAL scale encompasses 37 measurement items in 7 dimensions: functionality, security, informativity, reliability, responsiveness, convenience and empathy. These dimensions encompass both technical and nontechnical aspects of service.

This study enriches the smart tourism research literature, provides a reference for future research and helps relevant stakeholders understand tourists’ views on STTQUAL. Recommendations are provided to governments, the tourism industry and system developers for how to proceed in future development.

This is a mixed-methods study that fulfills established logical research criteria and proposes a scale for evaluating STTQUAL. The scale is validated through exploratory factor analysis and confirmatory factor analysis.

智慧旅游正经历快速发展的趋势, 其服务质量构成了游客评价的基础, 因此需要进行深入研究。然而, 由于高质量的智慧旅游技术（STTs）可以提升游客的整体体验并提高满意度，目前尚未有针对智慧旅游技术STTs的标准服务质量评价体系。因此，本研究旨在探讨如何从游客的角度理解STTs质量的评价方式。

本研究基于定性访谈、德尔菲法以及在澳门、成都和杭州三座智慧旅游城市进行的问卷调查, 开发了一套智慧旅游技术质量（STTQUAL）测量量表。

STTQUAL量表涵盖了7个维度的37项测量指标, 包括功能性、安全性、信息性、可靠性、响应性、便利性和同理心。这些维度综合了服务的技术和非技术方面。

本研究丰富了智慧旅游研究文献, 为未来研究提供了参考, 并帮助相关利益相关者理解游客对STTQUAL的看法。研究为政府、旅游业和系统开发者在未来发展中的行动提供了建议。

本研究采用混合研究方法, 符合既定的逻辑研究标准, 并提出了一套用于评估STTQUAL的量表。通过探索性因子分析和验证性因子分析对量表进行了验证。

Smart tourism technology (STT) has become prominent in the development of the tourism industry. This study aims to propose a model that integrates the cognitive–affective–behavioral model and trust transfer theory in the context of the 2018 Taichung World Flora Exposition, a mega-event.

An integrative model incorporating a questionnaire was used as the study framework. A total of 456 valid travel survey questionnaires were obtained.

The results suggested that the antecedents (STT and perceived value [PV]) positively affected memorable tourism experience (MTE) (cognitive component). MTE positively affected destination image (DI) (affective component), and DI positively affected intentions to revisit and recommend locations (behavioral component). Finally, MTE mediated the relationships among DI, STT and PV.

This study contributes to the development of a theoretical framework that incorporates a MTE in the context of mega-events and smart tourism concepts. The findings can help governments and the tourism industry understand the effects of STT on tourists’ experiences, perceptions and behaviors.

智慧旅游科技在旅游产业发展中占有突出地位。本研究在 2018 年台中世界花博会这一大型盛会的背景下, 提出了一个将认知-情感-行为模型和信任转移理论相结合的模型。

本研究采用包含问卷的综合模型作为研究框架。共获得有效旅游调查问卷456份。

结果表明, 前因（智慧旅游科技和感知价值）对难忘的旅游体验（认知成分）产生了积极影响。难忘的旅游体验正向影响的目的地形象（情感成分）, 目的地形象正向影响重访和推荐地点的意愿（行为成分）。最后, 难忘的旅游体验在目的地形象、智慧旅游科技和感知价值之间起到中介作用。

本研究有助于建立一个在大型活动和智能旅游概念的背景下结合令人难忘的旅游体验的理论框架。这些发现可以帮助政府和旅游业了解智能旅游科技对游客体验、感知和行为的影响。

This study aims to test the effect of system quality, information quality and service quality on user engagement and its effect on smartphone travel apps’ satisfaction, love and behavioral intentions.

Using the self-selection sampling technique, data was collected from 417 respondents recruited via Amazon Mechanical Turk. Data was subjected to partial least squares based structural equation modeling.

Results indicate that system quality, information quality and service quality have a significantly positive impact on user engagement with smartphone travel apps. Moreover, user engagement has a positive and significant impact on smartphone app satisfaction, smartphone app love and behavioral intentions.

This is the first study to integrate DeLone and McLean (2003) updated information system success model and stimulus-organism-response model to propose a holistic model of user’s engagement with smartphone travel apps.

本论文旨在检测智能手机旅游app的系统质量、信息质量、和服务质量对于用户参与度的作用, 以及其对app满意度、喜爱、和行为意愿的作用。

本论文采用自选取样技术, 通过Amazon Mechanical Turk共搜集417分问卷。本论文采用PLS-SEM分析数据。

研究结果表明, 系统质量、信息质量、和服务质量对智能手机旅游app的用户参与度起到显著的积极作用。此外, 用户参与度对智能手机app的满意度、喜爱、以及行为意图起到显著的积极作用。

本论文是首篇结合Delone和McLean(2003)改良版IS Success 模型和Stimulus-Organism模型, 以建立针对智能手机旅游app用户参与度的综合类模型。