Antecedents to Privacy Concern over Ubiquitous Service in China

WANLILI,ZHANG CHAO,민대환 한국무역연구원 2013 무역연구 Vol.9 No.2

A success with online or mobile business in the domestic market does not guarantee another success in a foreign country. Information privacy is a major concern to netizens or mobile users and becomes an obstacle to adopting a new service based on Internet and mobile technologies. If a company wants to export its business into an overseas market, the company needs to understand the extent of information privacy concerns by users in a foreign country and what would affect their privacy concerns. This paper focused on information privacy concerns when using ubiquitous service that could bring significant benefits to its users, and empirically examined the factors which could affect privacy concerns by users in China. The results showed that both propensity to privacy and privacy awareness had a positive effect on privacy concerns, while perceived justice had a negative effect. However, prior negative experience and perceived effectiveness of regulation had no effect on privacy concerns. Theoretical and practical implications for ubiquitous service are discussed.

Effect of Cultural Factors on Online Privacy Concern

Wan Lili,Daihwan Min 한국데이타베이스학회 2014 Journal of information technology applications & m Vol.21 No.2

This paper has studied whether cultural factors have an effect on privacy concern of Internet users in Korea and China. The result has shown that power distance, individualism, uncertainty avoidance, and long-term orientation are positively related to privacy concern, while masculinity is negatively related to privacy concern. This study has also found some similarities and differences between the two countries. First, privacy concern of Korean Internet users is significantly higher than that of Chinese users. Second, individualism and uncertainty avoidance significantly affect privacy concern in both Korea and China, although individualism in Korea has stronger effect than that in China. Third, long term orientation has a significant effect in only Korea while power distance is significant only in China. These results suggest that an online company doing businesses in multiple countries should have country-specific privacy policies to deal with the privacy concern of Internet users in different countries.

Do Wearable Devices Change Behavior? A Study of Smart Fitness Trackers

( Wan Lili ),( Zhang Chao ) 한국정보시스템학회 2020 情報시스템硏究 Vol.29 No.1

Purpose The study focuses on the physical activity behavior change effect of smart wristband, which is the most popular type of fitness tracker nowadays. The purpose of the research is to investigate how people's workout behavior may change after wearing a smart band and examine what kind of role persuasive design plays in behavior change. Design/Methodology/Approach This research employed an experimental study to examine whether the user's workout behaviors changed after using wristband from the “Behavior Wizard” perspective. A representative smart wristband from a major vendor was selected as the objects of experimental study. In the experiment, by comparing users’ workout behavior before and after using the wristband, behavior changes of all the experiment participants were classified into one of the 15 behavior change types. Users perceived persuasive design characteristics were measured and group differences were tested among different behavior change groups. Findings This research found that nearly half of the participants changed their workout behavior while half retained their workout status or no exercise status. Half of the participants who did not do exercise in their spare time started walking in the experiment. Results also showed that participants who started working out perceived higher levels of persuasive design devised into the smart band than participants who preserved no exercise status, except for facilitation and reward strategies. Participants who retained workout and those who increased workout frequency perceived no difference in smart band persuasive design.

A Classification of Car-related Mobile Apps: For App Development from a Convergence Perspective

ZHANG CHAO,WANLILI,민대환 한국디지털정책학회 2017 디지털융복합연구 Vol.15 No.3

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.

A Feasibility Study on Adopting Individual Information Cognitive Processing as Criteria of Categorization on Apple iTunes Store

ZHANG CHAO,WANLILI 한국정보시스템학회 2018 情報시스템硏究 Vol.27 No.2

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.

Evaluation and Functionality Stems Extraction for App Categorization on Apple iTunes Store by Using Mixed Methods : Data Mining for Categorization Improvement

ZHANG CHAO,WANLILI 한국IT서비스학회 2018 한국IT서비스학회지 Vol.17 No.2

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store’s categorization in discoverability.

The Extraction Process of Durative Persuasive System Design Characteristics for Healthcare-related Mobile Applications

ZHANG CHAO,WANLILI 한국인터넷방송통신학회 2019 Journal of Advanced Smart Convergence Vol.8 No.2

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant’s long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.