Location-based Apps Research Articles

Mapping the walk: A scalable computer vision approach for generating sidewalk network datasets from aerial imagery

While cities around the world are increasingly promoting streets and public spaces that prioritize pedestrians over vehicles, significant data gaps have made pedestrian mapping, analysis, and modeling challenging to carry out. Most cities, even in industrialized economies, still lack information about the location and connectivity of their sidewalks, making it difficult to implement research on pedestrian infrastructure and holding the technology industry back from developing accurate, location-based Apps for pedestrians, wheelchair users, street vendors, and other sidewalk users. To address this gap, we have designed and implemented an end-to-end open-source tool— Tile2Net —for extracting sidewalk, crosswalk, and footpath polygons from orthorectified aerial imagery using semantic segmentation. The segmentation model, trained on aerial imagery from Cambridge, MA, Washington DC, and New York City, offers the first open-source scene classification model for pedestrian infrastructure from sub-meter resolution aerial tiles, which can be used to generate planimetric sidewalk data in North American cities. Tile2Net also generates pedestrian networks from the resulting polygons, which can be used to prepare datasets for pedestrian routing applications. The work offers a low-cost and scalable data collection methodology for systematically generating sidewalk network datasets, where orthorectified aerial imagery is available, contributing to over-due efforts to equalize data opportunities for pedestrians, particularly in cities that lack the resources necessary to collect such data using more conventional methods.

Editorial: “Serious location-based games”

Mobile devices and mobile internet have led to the recent emergence of location-based apps. based apps evaluate the current position of the hosting mobile device such as a smartphone or a tablet 17 for displaying and visualizing position-specific information or enabling interactions between users. 18Among the location-based apps that first attracted significant public attention were game apps (e.g., 19Ingress and Pokémon GO). While these games have entertainment as the primary goal, they are also 20 well suited for achieving secondary goals, such as learning (Laine, 2018;Ribeiro et al., 2021) in particular, the influencing factors. The review results will be integrated into future development 76 processes for augmented reality applications in work contexts. 77In closing this editorial, we would like to thank the authors for sharing the results of their compelling 78 research within this article collection. We would also like to express our gratitude to the reviewers for 79 their thoughtful and constructive suggestions. Finally, we truly hope that readers will experience

Acceptance of in-store apps: factors that influence the intention to adopt location-based retail apps – insights from Germany

PurposeDue to recent developments of indoor location-tracking technologies, brick-and-mortar retailers are now able to add location-based marketing capabilities to their existing retail apps, providing retailers with new opportunities to interact with customers inside of their stores. The aim of this study is to identify factors influencing the customers' adoption intention of location-based retail apps for stationary retailing.Design/methodology/approachBased on the technology acceptance model, a conceptual model was developed. A Web-based survey was conducted in Germany with a final sample of 501 cases. Structural equation modelling was performed to test the hypotheses.FindingsThe results confirmed the positive relationship between attitude and the customers' intention to use location-based retail apps. Perceived usefulness and perceived enjoyment promote a positive attitude toward location-based retail apps, while privacy concerns and fear of spam hinder the formation of a favorable attitude. Subjective norms have a positive effect on customers' usage intention.Practical implicationsThe results help retailers who want to establish location-based retail apps at the point of sale (e.g. in the context of omni-channel strategies).Originality/valueAs previous research about location-based apps has mainly used empirical data from either Chinese or American samples, less is known about the perception of European customers. Research indicates that existing findings might not be transferable to European countries due to differences in values, social norms or regulations. Also, the failure of Shopkick in Germany illustrates the need for more research. Based on this, using a German sample to answer the research question, this study aims to provide a European perspective on location-based retail apps, and thereby extend existing research.

Integrating Social Commerce Constructs into Mobile Application Service; A Structural Equation Model

The emergence and accelerated rise of digital computing and smartphones have rendered the advent of social commerce (S-commerce). The S-commerce models such as location-based apps, and social media are founded on mobile commerce. According to many professionals and academics, social commerce has a major influence on e-commerce firms and organisations. Although social commerce provides enterprises many benefits, its implementation may entail some potential risks and complex issues, such as the integration of new and existing e-commerce application systems. To confirmed the issues, this study adopted Hajli (2015) social commerce construct (including rating and review, forum and community, recommendation and referral) and tested how it affects consumers’ purchase intention. It also proposed social support construct as moderator to obtain a new findings. In addition, to collect primary data, an online survey method was used and distributed to Shopee customers via electronic questionnaire. PLS-SEM analysis using the SmartPLS 3.0 program tool was implemented to evaluate the measurement and structural models. The result revealed that the social commerce construct (including ratings and reviews, forums and communities, and recommendations and referrals) had different effects on consumer purchase intentions through the Shopee mobile application. Furthermore, the role of social supprt as a moderator was confirmed to be significant. The discussion, implications, and suggestions for future study are discussed further.

ALBA: a model-driven framework for the automatic generation of android location-based apps.

In recent years, the number of smartphone users has increased dramatically. These users download millions of apps and use them for various services. Due to the significant demand for mobile apps, developers often seek faster development methods and more effective tools and techniques to generate these apps. Many of these apps are location-based apps in which users receive services based on their geographical location. In this paper, we propose a model-driven approach for the automatic generation of Android location-based mobile apps. Our framework, called ALBA, consists of a domain-specific modeling language, a modeling tool, and a plugin which includes model to code transformations. The modeling tool enables a novice designer to model a location-based app. The model is validated against the predefined constraints and the editor prevents creating invalid models. The designer uses the plugin to generate the Android code of the app. The evaluation of our work is two fold. First, to evaluate the generalizability of the ALBA framework, we conducted an experiment which includes the generation of four industrial location-based apps. Second, to evaluate the usability and quality of both the framework and the generated apps, we conducted a case study consists of three experiments. The results of the evaluation are promising both in terms of the applicability of the framework and the quality of the generated apps.

Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study

Climate change and sea level rise have increased the frequency and severity of flooding events in coastal communities. This study quantifies transportation impacts of recurring flooding using crowdsourced traffic and flood incident data. Agency-provided continuous count station traffic volume data at 12 locations is supplemented by crowd-sourced traffic data from location-based apps in Norfolk, Virginia, to assess the impacts of recurrent flooding on traffic flow. A random forest data predictive model utilizing roadway features, traffic flow characteristics, and hydrological data as inputs scales the spatial extent of traffic volume data from 12 to 7736 roadway segments. Modeling results suggest that between January 2017 and August 2018, City of Norfolk reported flood events reduced 24 h citywide vehicle-hours of travel (VHT) by 3%, on average. To examine the temporal and spatial variation of impacts, crowdsourced flood incident reports collected by navigation app Waze between August 2017 and August 2018 were also analyzed. Modeling results at the local scale show that on weekday afternoon and evening periods, flood-impacted areas experience a statistically significant 7% reduction in VHT and 12% reduction in vehicle-miles traveled, on average. These impacts vary across roadway types, with substantial decline in traffic volumes on freeways, while principal arterials experience increased traffic volumes during flood periods. Results suggest that analyzing recurring flooding at the local scale is more prudent as the impact is temporally and spatially heterogeneous. Furthermore, countermeasures to mitigate impacts require a dynamic strategy that can adapt to conditions across various time periods and at specific locations.

A group preference-based privacy-preserving POI recommender system

Ubiquitous smartphones with their built-in location services enable people to explore various points-of-interest (POIs) through location-based apps, e.g., Yelp and Foursquare City Guide. With these apps, users can receive personalized recommendations on nearby places, e.g., restaurants and arcades, which not only saves them searching time, but also helps find POIs that are of interest to them. One issue with these apps and almost all existing recommender systems is that they require users to share their preference data with the service providers. This information, if not properly used, can leak users’ privacy. In this paper, we propose a group preference-based POI recommendation scheme which fuses matrix factorization and clustering techniques to provide quality recommendations without sacrificing users’ privacy.

Role of location-based mobile apps in city marketing: Beşiktaş as a student-friendly district

ABSTRACT In the age of globalisation and high competition among destinations, cities are empowered with new marketing tools to attract new residents and visitors while keeping their existing communities satisfied. Therefore, the main objective of the paper is to understand the role of location-based mobile applications among university students, who as members of the wired generation tend to use technology more than older generations. The secondary objective is to explore the most preferred location-based apps with their benefits and how they are used by the students to link themselves to the city and its services. Two focus groups are conducted with university students in Besiktas, which is claimed to be one of the most student-friendly environments in Istanbul. The findings reveal students’ preferences and reasoning for the use of location-based mobile apps. Apart from their satisfaction with the diversity of shopping, wayfinding, and geosocial networking apps, their concerns for digital privacy and personal data protection have become apparent. Further research is recommended for understanding the satisfaction and expectations of different user segments in the city since their evaluations might contribute to further develop and improve location-based services, and promote the city in the local and global markets.

Exploring the determinants of usage continuance willingness for location-based apps: A case study of bicycle-based exercise apps

This paper investigates how mobile app design and social media can be used to influence the intention for continued use of location-based mobile apps. Uses and gratification theory and information systems success model are used to explore the key factors of continued usage intention. Three hundred and fifty-six valid questionnaires were collected to test the research model. The results showed that perceived usefulness, enjoyment, sense of belonging would significantly influence the usage habit and satisfaction of bicycle-based exercise app. In particular, the habit and satisfaction had strong impact on the intention for continued use. This study extended the findings of exercises with mobile apps and provided implications for the developers and operators of fitness and leisure-oriented apps.

The Enthusiast, the Interested, the Sceptic, and the Cynic

We discuss the user study of a mobile cultural heritage game designed to stimulate reflection about a city's history. Aided by location-aware technology, the game fosters the serendipitous discovery of points of interest, historical images and stories, whilst players wander the city. This exploration differs from the typical precalculated path recommendations used by other location-based applications. It triggers reflection about the city's past that is as unique as its visitors. Ours is one of the first studies to attempt an understanding of the effects of serendipitous urban discovery and historic reflection-triggering technologies on user experience. We combined field trials with controlled experiments, analysing perceptions of the experience and value using responses expressed in open-ended questionnaire items. Using thematic coding and sentiment analysis, we observed types of emotional responses, indicating four potential profiles of their likelihood towards future technology adoption. Enthusiastic and Interested users appreciated the freedom of movement choice that created an autonomous experience that fostered a sense of personal accomplishment. The interface interactions of the game, designed to stimulate reflection, supported a feeling of connectedness to others. In contrast, Cynical and Sceptical users were less tolerant of perceived technological issues, requiring more perfection in functionality and design. These users are less likely to be the early adopters of serendipitous location-based apps. The game was developed as part of a large cultural informatics project but, unlike typical evaluations, we conducted this study midway through the project and not at its end. This approach (1) gave the team the possibility to take stock, pause, and reflect and (2) provided insight on future design improvements for increasing the perceived value of serendipitous urban discovery applications. Our results contribute towards a grounded understanding of user experience and help progress the development of cultural heritage applications that incorporate elements of reflection and/or place-based exploration into their functionalities.

Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention

ABSTRACTNumerous location-based services (LBS) studies have suggested that the risk of disclosing personal privacy hinders consumers from adopting LBS, whereas scant attention has focused on clarifying how to mitigate the perceived privacy risk of using LBS. This quantitative study focuses on the effects of consumer quality perceptions (i.e. information quality, system quality, and service quality) on their trust in LBS, which consequently affects perceived privacy risk and continued usage intention towards LBS. Research data were collected through a market survey website; 1399 valid questionnaires were collected. Structural equation modelling analysis was applied to the data. The results revealed that information quality, system quality, and service quality were positively related to perceived trust. Perceived trust also correlated negatively with perceived privacy risk, but positively with continued usage intention. A managerial implication drawn from the findings is that LBS providers should develop more useful user interfaces or provide timely, personalised services to reduce perceived privacy risk and strengthen LBS continued usage intention.

스마트폰의 위치기반서비스 앱을 활용한 일반인 심폐소생술 시행률 향상방안

병원 처치 전 급성 심정지 환자 발생 시 현장에서의 일반인 심폐소생술 시행률은 환자의 소생률과도 직결되어 있다. 하지만 현재 우리나라는 선진국에 비해 일반인 CPR 시행률은 저조하여 소생률도 낮은 실정이다. 따라서 본 연구에서는 이를 개선하기 위해 스마트 폰의 위치기반서비스 앱을 활용한 응급의료시스템의 적용가능성을 고려, 우선 일반인 3,800명을 대상으로 사전 설문조사를 시행하였다. 연구결과로 첫째, 심폐소생술 교육 경험은 높게 나타났으나 반대로 심폐소생술에 대한 보편성은 낮은 것으로 인식되었다. 둘째, 심폐소생술 자신감에 대해서는 연령, 학력, 직업에 따라 상의한 결과가 나왔으며 전체적으로 낮은 자신감을 보였다. 셋째, 위치기반서비스 앱을 활용한 응급의료시스템 참여도는 높게 나타났으며 심폐소생술 시행의지와 심폐소생술 자신감, 심폐소생술 교육경험에 대해서 상관관계가 있는 것으로 나타났다. When patients have acute cardiac arrest before they are hospitalized, the ratio of CPR done by the general public is directly related to patient survival ratio. However, compared with that of advanced nations, our nation has low patient survival ratio due to its low ratio of CPR done by the general public. To improve this situation, the current study conducted a pre-survey targeting 3,800 general public to find how to apply an emergent medical system using smart phone location-based service. According to its outcome, first, they have a high level of CPR experience while their recognition of CPR generality is low. Second, their self-confidence in doing CPR significantly differ according to their age, academic achievement and occupation yet with generally low self-confidence. Third, their participation in the emergent medical system using location-based service APPs is high, and has co-relation to their will for CPR, self-confidence in CPR and experience in CPR training.

Secured obfuscated queries in spatial networks

The recent drive in communication technology made smartphone users search for geographical point of interest such as nearest ATM, shopping mall and hospitals. The thirst for geo-search opens novel spatial queries in the arena of location-based apps as well as techniques that enhance the user location privacy. This paper introduces a new obfuscation technique for protecting user location based on k-means clustering. A new query called Secured Obfuscated Spatial SOS query to provide an analysis of the proposed obfuscation technique is developed to evaluate the efficiency. Finally, the experimental results validate the solution in preserving user privacy.