• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1963-1978
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• 2015

With the advancement of mobile web environments, identification and analysis of the user behavior play a significant role and remains a challenging task to implement with variations observed in the model. This paper presents an efficient method for mining optimized user behavior prediction model using genetic algorithm on mobile web structure. The framework of optimized user behavior prediction model integrates the temporary and permanent register information and is stored immediately in the form of integrated logs which have higher precision and minimize the time for determining user behavior. Then by applying the temporal characteristics, suitable time interval table is obtained by segmenting the logs. The suitable time interval table that split the huge data logs is obtained using genetic algorithm. Existing cluster based temporal mobile sequential arrangement provide efficiency without bringing down the accuracy but compromise precision during the prediction of user behavior. To efficiently discover the mobile users' behavior, prediction model is associated with region and requested services, a method called optimized user behavior Prediction Model using Genetic Algorithm (PM-GA) on mobile web structure is introduced. This paper also provides a technique called MAA during the increase in the number of models related to the region and requested services are observed. Based on our analysis, we content that PM-GA provides improved performance in terms of precision, number of mobile models generated, execution time and increasing the prediction accuracy. Experiments are conducted with different parameter on real dataset in mobile web environment. Analytical and empirical result offers an efficient and effective mining and prediction of user behavior prediction model on mobile web structure.

• Journal of Information Science Theory and Practice
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• v.2 no.2
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• pp.33-47
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• 2014

Mobile devices are the most important equipment for accessing various kinds of services. These services are accessed using wireless signals, the same used for mobile calls. Today mobile services provide a fast and excellent way to access all kinds of information via mobile phones. Mobile service providers are interested to know the access behavior pattern of the users from different locations at different timings. In this paper, we have introduced an associated tree for analyzing user behavior patterns while moving from one location to another. We have used four different parameters, namely user, location, dwell time, and services. These parameters provide stronger frequent accessing patterns by matching joins. These generated patterns are valuable for improving web services, recommending new services, and predicting useful services for individuals or groups of users. In addition, an experimental evaluation has been conducted on simulated data. Finally, performance of the proposed approach has been measured in terms of efficiency and scalability. The proposed approach produces excellent results.

• The Journal of Information Systems
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• v.28 no.2
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• pp.129-152
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• 2019

Purpose The purpose of this study is to empirically identify the risky behavior of mobile device users using the Internet of Things on a situational perspective. Design/methodology/approach This study made a design of the research model based on model of the determinants of risk behavior. Data were collected through a survey including hypothetical scenario. SmartPLS 2.0 was used for the structural model analysis and t-test was conducted to compare the between normal and situational behavior. Findings The results were as follows. First, the central roles of risk propriety and risk perception were verified empirically. Second, we identified the role of locus of control as a new factor of impact on risky behavior. Third, mobile risk propensity has been shown to increase risk perception. Fouth, it has been shown that risk perception does not directly affect risky behavior and reduce the relationship between mobile risk propensity and risk behavior. According to the empirical analysis result, Determinants of risk behavior for mobile users were identified based on a theoretical framework. And it raised the need to pay attention to the impact of locus of control on risk behavior in the IS security field. It provided direction to the approach to risky behavior of mobile device users. In addition, this study confirmed that there was a possibility of taking risky behavior in the actual decision-making.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3972-3985
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• 2016

Organizations have been implementing mobile applications that actually connect to their backend enterprise applications (e.g. ERP, SCM, etc.) in order to increase the enterprise mobility. However, most of the organizations are still struggling to fully satisfy their mobile application users with the enterprise mobility. Even though it has been regarded as the right direction that the traditional enterprise system should move on, the studies on the success model for mobile enterprise applications in user's acceptance perspective can hardly be found. Thus, this study focused not only to redefine the success of the mobile enterprise application in user's acceptance persepective, but also to find the impacts of the factors on user's usage behavior of the mobile enterprise applications. In order to achieve this, we adopted the Technology Acceptance Model 2 (TAM2) as a model to figure out the user's behavior on mobile applications. Among various mobile enterprise applications, this study chose mobile ERP since it is the most representing enterprise applications that many organizations have implemented in their backend. This study found that not all the constructs defined by Davis in TAM2 have a significant influence on user's behavior of the mobile-ERP applications. However, it is also found that most social influence processes of TAM2 influence user's perception of the degree of interaction by mobile-ERP applications.

• Fashion & Textile Research Journal
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• v.18 no.2
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• pp.158-166
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• 2016

This study investigates the impact of fashion product attributes and mobile shopping mall attributes on impulse buying behavior and mobile shopping satisfaction. The findings provide new information to marketers on marketing strategy for mobile shopping malls. We obtained 283 usable questionnaires from college students. Data were analyzed by frequency analysis, correlation analysis, factor analysis using SPSS for Window 21.0 and confirmatory factor analysis and structural equation model analysis by AMOS 21.0. The results were as follows. The utility of fashion products attributes had the greatest impact on impulse buying behavior when buying fashion products in a mobile mall. Utility had a negative effect on impulsive buying behavior and exhibitionistic had a positive effect on impulsive buying behavior. Next, continuous management of mobile shopping mall attributes influenced impulse buying behavior. In addition, impulse buying behavior showed that the positive effect on satisfaction. Fashion product attributes had a greater impact on impulsive buying behavior than mobile mall properties when buying fashion products in the mobile mall; in addition, impulse buying facilitated customer satisfaction.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.735-744
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• 2016

Recently, personal information leakage incidents with increased usage of mobile services are increasing. Personal information leakage incidents can have a significant impact on an individual's mobile banking services. Accordingly, we examine relationships among individual's psychological characteristics, intention and behavior regarding compliance in an individual's perception on personal information leakage incidents in mobile banking contexts. In this study, for explaining our research model and understanding with personal psychology and behavior in mobile banking contexts, we adopted two theories, theory of interpersonal behavior and stimulus-response theory. We collected the 55 data using online surveyor and then analyzed structural equation model in order to find causal relationships among research variables. The results of this study should be useful to the mobile banking services companies in promoting service users to follow the information privacy policies.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.2
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• pp.335-353
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• 2015

The purpose of this study is to analyze the middle-aged adults' mobile information behavior focused on their demographic characteristics. To achieve the aim of this study data were collected from 50 to 64 years old middle-aged adults who live in different size of cities and towns in Korea using self-designed questionnaire through online and offline survey. Gender, academic background, income level, size of residential zone, physical condition, and occupation were adopted as demographic characteristics, and type of mobile contents use, hour of mobile use, ability of mobile use, persistency of mobile use, and usability of mobile were used as the mobile information behavior in this study. Total of 191 valid data were analysed using SPSS Ver. 21. The results of this empirical study revealed that there exist a significant difference between some of their demographical characteristics (e.g., academic backgrounds, income level, and occupation) and mobile information behaviors particularly in their contents use.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.113-125
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• 2019

Mobile social commerce is one of the fastest growing distribution channels in recent years. Therefore, it is important to understand customer's buying behavior in mobile social commerce in order to continuously grow in the competitive mobile social commerce market. To achieve the purpose of this study is to investigate how impulsive buying behaviors are applied in mobile shopping and how factors affect impulse purchasing in online shopping. In order to verify the hypothesis, we surveyed the customers who have experiences of using mobile social commerce and analyzed 280 valid data by Smart PLS 3.0. As a result, it was confirmed that consumers' innovation and purchasing experience influenced impulse purchase in mobile social commerce, and scarcity messages among information attributes affect impulse buying. Through this study, impulsive buying behavior which is a frequently analyzed variable in an online shopping context will be extended to the mobile shopping context. and it will provide practical implications for customer strategy establishment in mobile social commerce market.

• Journal of the Korean Home Economics Association
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• v.46 no.3
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• pp.13-26
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• 2008

This study aims to offer basic data for consumer education regarding the use of mobile phones by adolescent consumers in a correct way by researching and analyzing the consumption value and consumption behavior of adolescent consumers for mobile phones to see how they use mobile phone as consumers, which is a serious of user behaviors according to their plan, purchase, use, and disposal. Based on the research results, the study proposes the following in relation to the correct use of mobile phones by adolescent consumers. First, in the purchase or use of mobile phones, a more demonstrative consumption pattern was more likely for males than females and for those who are in higher grades than those who are not. Therefore, it is necessary to offer consumer education given the gender and school year rather than stereotyped consumer education. Second, it is necessary to offer objective information and give consumer education for checking the instant desire for something new in order to prevent an impulsive purchase based upon advertisements given the characteristics of adolescent consumers who prefer new designs or functions. Third, regarding the disposal of mobile phones, it is necessary to seek strategies for recycling mobile phones usefully at an administrative level to prevent mobile phones from being thrown away without being recycled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5673-5691
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• 2019

Information centric mobile network can significantly improve the data retrieving efficiency by caching contents at mobile edge. However, the cache pollution attack can affect the data obtaining process severely by requiring unpopular contents deliberately. To tackle the problem, we design an algorithm of mitigating cache pollution attacks in information centric mobile network. Particularly, the content popularity distribution statistic is proposed to detect abnormal behavior. Then a probabilistic caching strategy based on abnormal behavior is applied to dynamically maintain the steady-state distribution for content visiting probability and achieve the purpose of defense. The experimental results show that the proposed scheme can achieve higher request hit ratio and smaller latency for false locality content pollution attack than the CacheShield approach and the baseline approach where no mitigation approach is applied.