Search results

The main purpose of this study is to investigate what affects a customer's decision to use the hotel smartphone applications when he/she makes a room reservation.

A total of 266 usable data was collected through an online survey. The research model was tested using confirmatory factor analyses and structural equation modeling.

This study revealed that perceived usefulness, perceived credibility, perceived equipment risk, and perceived change risk affected customers' intention to book a hotel room using hotel smartphone apps. Perceived ease of use did not have a significant effect on behavioral intention.

This study extended TAM and the existing literature of mobile technology in the lodging industry. This article explored both existing variables and new variables in studying customers' intention to use hotel smartphone apps when booking a hotel room.

The key concern nowadays is smartphone addiction and user profiles. Following the risk and protective factors framework, the authors aim to characterize smartphone users according to two levels: (1) individual: referred to the use (i.e. boredom proneness, compulsive app downloading smartphone addiction) and (2) microsystem: referred to family and peers (i.e. family harmony and phubbing). Besides, the authors will derive useful managerial implications and strategies.

First, an extensive literature revision and in-depth interviews with experts were employed to identify the addiction-related variables at the individual and microsystem level. Second, information was collected from a sample of 275 Spanish smartphone users, and a K-means clustering algorithm was employed to classify smartphone users.

The proposed traffic lights schema identifies three users’ profiles (red, yellow and green) regarding their smartphone addiction and considering individual and microsystem critical variables.

This study proposes a practical and pioneer traffic lights schema to classify smartphone users and facilitate each cluster's strategies development.

一個大家現時頗關注的事項就是智慧型手機癮和用戶檔案。遵循著風險和保護因子框架,我們擬根據兩個層面,去描述智慧型手機使用者的特性:(一) 個人層面: 這是指手機的使用方面 (即是:無聊傾向、強制性應用程式的下載、智慧型手機癮), 以及(二)微系統層面:這是指家庭和同儕 (即是:家庭和諧和低頭族)。此外,我們也會探討從中得到管理方面的啟示和一些有用的策略。

我們首先進行廣泛的文獻回顧和深入訪問有關的專家,以確定在個人和微系統層面上與入迷成癮有關的變數。繼而從275名西班牙智慧型手機使用者中收集資料,然後以K均值聚類算法把智慧型手機使用者分類。

我們提出的紅綠燈圖表,就用戶的智慧型手機癮,並考慮了個人和微系統的關鍵變數,識別了三個用戶檔案(紅、黃、綠)。

本研究提出一個實用及有倡導性的紅綠燈圖表,把智慧型手機使用者分類,並促進每個群集戰略的制定。

The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated.

The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods).

Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns.

The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive.

An algorithm-based prediction tool would offer new perspectives to the management of tourism movements.

Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach.

This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.

To cope with the COVID-19 pandemic, contact tracing mobile apps (CTMAs) have been developed to trace contact among infected individuals and alert people at risk of infection. To disrupt virus transmission until the majority of the population has been vaccinated, achieving the herd immunity threshold, CTMA continuance usage is essential in managing the COVID-19 pandemic. This study seeks to examine what motivates individuals to continue using CTMAs.

Following the coping theory, this study proposes a research model to examine CTMA continuance usage, conceptualizing opportunity appraisals (perceived usefulness and perceived distress relief), threat appraisals (privacy concerns) and secondary appraisals (perceived response efficacy) as the predictors of individuals' CTMA continuance usage during the pandemic. In the United States, an online survey was administered to 551 respondents.

The results revealed that perceived usefulness and response efficacy motivate CTMA continuance usage, while privacy concerns do not.

This study enriches the understanding of CTMA continuance usage during a public health crisis, and it offers practical recommendations for authorities.

Technology-facilitated abuse, so-called “tech abuse,” through phones, trackers, and other emerging innovations, has a substantial impact on the nature of intimate partner violence (IPV). The current chapter examines the risks and harms posed to IPV victims/survivors from the burgeoning Internet of Things (IoT) environment. IoT systems are understood as “smart” devices such as conventional household appliances that are connected to the internet. Interdependencies between different products together with the devices' enhanced functionalities offer opportunities for coercion and control. Across the chapter, we use the example of IoT to showcase how and why tech abuse is a socio-technological issue and requires not only human-centered (i.e., societal) but also cybersecurity (i.e., technical) responses. We apply the method of “threat modeling,” which is a process used to investigate potential cybersecurity attacks, to shift the conventional technical focus from the risks to systems toward risks to people. Through the analysis of a smart lock, we highlight insufficiently designed IoT privacy and security features and uncover how seemingly neutral design decisions can constrain, shape, and facilitate coercive and controlling behaviors.

This study was conducted to identify, summarise, analyse and categorise mobile device applications (Apps), relevant to the construction industry and to explore their uses and exposure levels.

The research method involved reviewing literature and searching for Apps. The construction Apps were found by developing key phrases. These key phrases were used to develop search strategies, which were then used to find the construction Apps. The Apps found were categorised based on the similarity of their uses.

The 136 Apps identified were summarised, analysed, and categorised into 11 groups of distinct construction operations and tasks. The “Design and Drawing Apps”, “Measurement and Estimation Apps”, “Management Apps”, “All Round Apps” and “Construction Site Apps” recorded 29, 28, 26, 21 and 11 numbers of Apps, respectively. The Autodesk Sketchbook, GPS Field Area Measure, MagicPlan, Measure and TSheets were the top five in terms of the number of downloads. These Apps in terms of their exposure levels in the construction industry record 4.76%, 2.38%, 0.52%, 0.48% and 0.42%, respectively.

This paper provides a catalogue of the continuum of construction Apps for a wide variety of construction operations/activities which are available for construction professionals and provide guidance on their uses to assist in selecting appropriate Apps for specified operation/tasks/activities in the construction industry. Construction professionals may benefit from increased productivity, efficiency and ease of working.

This research investigates the use of real-time online polling to enhance university teaching and learning.

Using a case study and employing action research, this work shows how polling can improve professional practice, learner engagement and teaching performance.

Incorporating the right type of online real-time polling into lessons is a professional challenge and can be hard work for teachers but has overriding benefits.

This research reports one lecturer's experiences within two UK universities, limited to location, variety of students and lecturer technical capability. The research implications are that online polling, especially in different learning environments, is needed. Previous research is outdated or limited to real-time polling for teaching and learning during physical classes. There are research opportunities therefore in the use of polling before, during and after class.

This research finds that the field of online polling needs to be seen as a modern teaching tool that now uses students' personal technology for easier use by students and teachers: it is more than the use of archaic “clickers” which were extra classroom items to be bought and maintained. Also, online polling, before, during and after classes, can be employed usefully and have validity within teachers' toolboxes. This paper shows how such polls can be successfully deployed.

Whilst there are previous reports of polling undertaken within teaching and learning events, this paper builds upon those experiences and boosts collective understanding about the use of polling as a way to improve professional practice and increase learning.

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

This paper tries to project population distribution by modeling geo-homophily in OSNs.

The purpose of this paper is to identify the factors affecting user acceptance for NFC mobile wallets in both Korean and US markets.

The proposed model extends the UTAUT2 model with new constructs of credibility (CR) and service smartness (SS). This study was analyzed using partial least square structural equation modeling on data collected from 701 college students between the ages of 18 and 29.

The results of this study demonstrate that performance expectancy (PE), effort expectancy (EE), CR, SS and habit (HB) have strong positive relationships with a user’s behavioral intention to use NFC mobile wallets. Comparing the results of the USA and South Korea, there are different results regarding PE and CR.

This study shows that all factors except social influence (SI) have significant positive relationships with the intention to adopt NFC mobile wallets: Among the original UTUAT2 factors, PE, EE and HB are important determinants of NFC mobile wallet adoption and the new constructs, CR and SS, are significant determinants that influence BI. However, the target respondents are limited to college students of South Korea and the USA Thus, caution should be used when applying the results of this study towards less ICT developed countries and towards different age groups.

This study provides multiple practical contributions. First, this study emphasizes HB as the strongest factor for adopting NFC mobile wallets in both South Korea and the USA Second, this study also highlights the importance of SS. Third, this study reveals that SI is not associated with the adoption of NFC mobile wallets. Fourth, nationality differences between the USA and South Korea account for the differences in consumer behaviors.

This study has two main contributions: First, this study introduces a modified UTAUT2 model with two new variables (CR and SS) useful for NFC mobile wallets. Second, this study compares the results of partial least square structured equation models (PLS-SEM) of the two nationality groups, South Korea and the USA