• Journal of Digital Convergence
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• v.15 no.3
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• pp.77-86
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• 2017

This study selected car-related mobile apps for app developers suffering from low revenue and classified car apps assisting users in driving or managing a car. A total of 697 car apps were classified into eight categories. Most apps are in four categories: car news & information (28%), locating service (23%), car rental service (15%), safe/efficient driving service (12%). The remaining categories are buying & selling, driver's communication, maintenance management, and expenses monitoring. Many apps are simple and too similar in their main functions. Only a few apps are designed to be more comprehensive and have functions in two or more categories. For the practicality of the categorization scheme, this study checked the inter-rater reliability in two tests and got 0.886 and 0.828. The result from this study suggests functions that are not implemented yet or need to be combined. Future research will focus on identifying promising car apps or designing multi-functional car apps.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.201-217
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• 2019

Cars have become a necessity in modern life. It is widely used to transport people or products to a destination conveniently. However, the addition of a navigation service that provides route information and more makes driving more convenient and safer. Recent developments in the mobile app ecosystem encourages people to adopt not only an installation-type car navigation, but also a mobile app navigation, supporting connected car concepts. It should be noted that mobile apps with mobile Internet can be a significant linkage between information acquired online and offline business. This study demonstrates the impact of the app use experience for a driver in the context of applying artificial intelligence service. As a result, the introduction of artificial intelligence services has a statistically significant moderating effect on the use of mobile navigation apps. This seminal research is valuable as it evaluates the role of artificial intelligence applied to mobile navigation apps.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.35-48
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• 2021

With the advent of the Fourth Industrial Revolution, startups are leading the proliferation of logistics in life services in countries across the world. Logistics in life startups aim to differentiate themselves for traditional logistics companies by offering customized services that penetrate niche logistics market and enhance customer convenience and satisfaction. Through the development of mobile applications(apps) and platform a variety of life-enhancing services are becoming increasingly available to customers, such as on-demand, online-to-offline, convenience, reverse logistics, as well as last-mile delivery. In particular, logistics in life services are expanding into areas that include food delivery, home moving, cargo transport, laundry delivery, car washing, and car repair. In order for the logistics in life startups to succeed, they needs to offer highly usable apps to increase customer satisfaction and loyalty. Due to the nature of mobile phones, different evaluation criteria than those for websits should be used to determine the usability of apps. The purpose of this study is to evaluate the usability of representative Korean logistics in life apps through usability testing, discuss implications and offer improvement recommendations. Finally, the best Korean logistics app is compared with a top ranked app on Google Play for benchmarking purposes.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.173-184
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• 2024

The connected car services are one of the most widely used services in the Internet of Things environment, and they provide numerous services to existing vehicles by connecting them through networks inside and outside the vehicle. However, although vehicle manufacturers are developing services considering the means to secure the connected car services, concerns about the security of the connected car services are growing due to the increasing number of attack cases. In this study, we reviewed the research related to the connected car services that have been announced so far, and we identified the threats that may exist in the connected car services through security threat modeling to improve the fundamental security level of the connected car services. As a result of performing the test to the applications for connected car services developed by four manufacturers, we found that all four companies' applications excessively requested unnecessary permissions for application operation, and the apps did not obfuscate the source code. Additionally, we found that there were still vulnerabilities in application items such as exposing error messages and debugging information.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.89-95
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• 2017

There are a variety of apps that are finding their way. And in car navigation, we launched a product that reflects Augmented Reality technology this year. However, existing apps have problems. It is implemented in 2D or 3D, has a large error range because it has been modified in most vehicles, is not updated in real time, and car augmented reality navigation is a vehicle, and a separate device is required, etc. In this study, we implemented a smartphone app for walking directions using augmented reality, and made it possible to intuitively use a route service from a user 's location to a destination. The Dijkstra algorithm is applied to calculate the shortest path to solve the problem of finding the route with the least cost. By using this application, it is possible to use the route search service even in a data-free environment, to solve the inconvenience of the language barrier, and to update in real time, so that the latest information can be always maintained. In the future, we want to develop an app that can be commercialized by using a character in the path to promote it.

• The Journal of Information Systems
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• v.27 no.2
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• pp.1-28
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• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.93-101
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• 2021

The study aims to test the model of Yang et al. (2017) for the overall assessment of the transportation sector in the sharing economy and add some new elements on the benefits of customer loyalty from some previous studies that were not mentioned in Yang's model. This study will take examples from the two big brands of car-sharing apps in the sharing economy in Vietnam - Uber, and Grab. This research focuses on customer loyalty in the sharing economy with Uber and Grab as the transport sector in Ho Chi Minh City. Based on the survey data of 380 customers in Vietnam, the research results show that two independent factors positively impact commitment and satisfaction: social benefits and economic benefits. Simultaneously, economic benefit has a positive effect on satisfaction while trust benefit has a negative effect on commitment. Finally, commitment has a positive impact on customer loyalty in the sharing economy. As a result, companies in the sharing economy can identify which are the key factors that strongly influence customer satisfaction, commitment, trust, and loyalty to help managers to devise the appropriate solutions for promoting the strengths or overcoming limitations to contribute to perfecting and improving the quality of the company's services.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.918-923
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• 2016

IoT should be considered security risk environments such as various platforms and services including smart devices that can be mounted on household electric appliances, healthcare, car, and heterogeneous networks that are connected to the Internet, cloud services and mobile Apps.. In this paper, we provide analysis of new security threats, caused by open-platform of IoT and sensors via the Internet. Also, we present the key recovery mechanism that is applied to IoT. It results to have compatibility with given research, reduces network overhead, and performs key recovery without depending on key escrow agencies or authorized party.

• International Journal of High-Rise Buildings
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• v.12 no.2
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• pp.169-177
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• 2023

The massive increase in elevator usage and a severe demand for energy efficiency have prompted manufacturers to develop various innovative technologies, including AC and gearless motors, machine-room-less (MRL) technologies, regenerative drives, elevator ropes, and LED lighting. In addition, manufacturers are providing software solution systems such as destination dispatching systems, people flow solutions, standby mode, and predictive maintenance applications. Future technologies include electromagnetic levitation, circulating multi-car elevator systems, robotization, and drones. This article outlines elevators' technological advancements. It discusses how to harness new technologies and apply them to aging, modern, and future buildings.