• Information Systems Review
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• v.20 no.2
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• pp.21-37
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• 2018

Under ubiquitous work environment, innovative changes occur in work process with ICT. The work process for collaboration through mobile devices and network should be investigated. The research model consists of two major antecedents: autonomy and interdependence as a task characteristic and job satisfaction as ultimate consequence followed by work design theory. To elaborate work design theory, smartwork application (app) use, communication extent, and work-life balance were reviewed from the literature. Data were collected from three ICT firms, which adopted certain smartwork app, and a partial least squares analysis was made on 175 data points. The analysis results show that task interdependence exerts a statistically significant effect on the level of smartwork app usage. Communication extent directly affects job satisfaction and work-life balance. The remarkable point is that smartwork app usage does not affect employees' work-life balance; the former can only affect the latter indirectly by increasing communication extent. This study attempts to explain the organizational impact by considering smartwork app and the effects simultaneously. We proposed and empirically tested the extended work design theory including information technology and its environment. Based on the results, other theoretical and practical contributions are discussed at the end with limitations and further studies.

• 대한공업교육학회지
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• v.41 no.2
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• pp.89-118
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• 2016

In this study, the model of Turtle Ship, which is evaluated as one of the world's first ironclad ship in battle as well as the traditional scientific and technological heritage in Korea, was combined with the Physical Computing Platform(Arduino and App Inventor) that enables students to learn the basic concepts of IT in an easy and fun way. Thus, this study contrived the Physical Computing Platform-based Turtle Ship model which will make the students of Industrial Specialized High School develop the technological literacy and humanities-based knowledge through flexible education out of stereotype and single subject as well as enhance the potential of creative convergence education. The following is a summary of the main results obtained through this study: First, Arduino-based Main-controller design and making is helpful to learn of the hardware and software knowledge about EEC(Electron Electronics Control) and to confirm the basic characteristics and performance of interaction of Arduino and actuators. Second, The fundamental Instructional environments of abilities such as implementing EEC systems, thinking logically, and problem-solving skills were provided by designing of pattern diagram, designing an actuator circuit and making, the creation of sketches as technical programming and developing of mobile app. Thirdly, This is physical computing platform based Turtle ship model that will enable students to bring up their technological literacy and interest in the cultural heritage.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.59-87
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• 2014

In MIS field, the researches on payment services are focused on adoption factors of payment service using behavior theories such as TRA(Theory of Reasoned Action), TAM(Technology Acceptance Model), and TPB (Theory of Planned Behavior). The previous researches presented various adoption factors according to types of payment service, nations, culture and so on even though adoption factors of identical payment service were presented differently by researchers. The payment service industry relatively has strong path dependency to the existing payment methods so that the research results on the identical payment service are different due to payment culture of nation. This paper aims to suggest a successful adoption factor of noble payment service regardless of nation's culture and characteristics of payment and prove it. In previous researches, common adoption factors of payment service are convenience, ease of use, security, convenience, speed etc. But real cases prove the fact that adoption factors that the previous researches present are not always critical to success to penetrate a market. For example, PayByPhone, NFC based parking payment service, successfully has penetrated to early market and grown. In contrast, Google Wallet service failed to be adopted to users despite NFC based payment method which provides convenience, security, ease of use. As shown in upper case, there remains an unexplained aspect. Therefore, the present research question emerged from the question: "What is the more essential and fundamental factor that should takes precedence over factors such as provides convenience, security, ease of use for successful penetration to market". With these cases, this paper analyzes four cases predicted on the following hypothesis and demonstrates it. "To successfully penetrate a market and sustainably grow, new payment service should find non-customer of the existing payment service and provide noble payment method so that they can use payment method". We give plausible explanations for the hypothesis using multiple case studies. Diners club, Danal, PayPal, Square were selected as a typical and successful cases in each category of payment service. The discussion on cases is primarily non-customer analysis that noble payment service targets on to find the most crucial factor in the early market, we does not attempt to consider factors for business growth. We clarified three-tier non-customer of the payment method that new payment service targets on and elaborated how new payment service satisfy them. In case of credit card, this payment service target first tier of non-customer who can't pay for because they don't have any cash temporarily but they have regular income. So credit card provides an opportunity which they can do economic activities by delaying the date of payment. In a result of wireless phone payment's case study, this service targets on second of non-customer who can't use online payment because they concern about security or have to take a complex process and learn how to use online payment method. Therefore, wireless phone payment provides very convenient payment method. Especially, it made group of young pay for a little money without a credit card. Case study result of PayPal, online payment service, shows that it targets on second tier of non-customer who reject to use online payment service because of concern about sensitive information leaks such as passwords and credit card details. Accordingly, PayPal service allows users to pay online without a provision of sensitive information. Final Square case result, Mobile POS -based payment service, also shows that it targets on second tier of non-customer who can't individually transact offline because of cash's shortness. Hence, Square provides dongle which function as POS by putting dongle in earphone terminal. As a result, four cases made non-customer their customer so that they could penetrate early market and had been extended their market share. Consequently, all cases supported the hypothesis and it is highly probable according to 'analytic generation' that case study methodology suggests. We present for judging the quality of research designs the following. Construct validity, internal validity, external validity, reliability are common to all social science methods, these have been summarized in numerous textbooks(Yin, 2014). In case study methodology, these also have served as a framework for assessing a large group of case studies (Gibbert, Ruigrok & Wicki, 2008). Construct validity is to identify correct operational measures for the concepts being studied. To satisfy construct validity, we use multiple sources of evidence such as the academic journals, magazine and articles etc. Internal validity is to seek to establish a causal relationship, whereby certain conditions are believed to lead to other conditions, as distinguished from spurious relationships. To satisfy internal validity, we do explanation building through four cases analysis. External validity is to define the domain to which a study's findings can be generalized. To satisfy this, replication logic in multiple case studies is used. Reliability is to demonstrate that the operations of a study -such as the data collection procedures- can be repeated, with the same results. To satisfy this, we use case study protocol. In Korea, the competition among stakeholders over mobile payment industry is intensifying. Not only main three Telecom Companies but also Smartphone companies and service provider like KakaoTalk announced that they would enter into mobile payment industry. Mobile payment industry is getting competitive. But it doesn't still have momentum effect notwithstanding positive presumptions that will grow very fast. Mobile payment services are categorized into various technology based payment service such as IC mobile card and Application payment service of cloud based, NFC, sound wave, BLE(Bluetooth Low Energy), Biometric recognition technology etc. Especially, mobile payment service is discontinuous innovations that users should change their behavior and noble infrastructure should be installed. These require users to learn how to use it and cause infra-installation cost to shopkeepers. Additionally, payment industry has the strong path dependency. In spite of these obstacles, mobile payment service which should provide dramatically improved value as a products and service of discontinuous innovations is focusing on convenience and security, convenience and so on. We suggest the following to success mobile payment service. First, non-customers of the existing payment service need to be identified. Second, needs of them should be taken. Then, noble payment service provides non-customer who can't pay by the previous payment method to payment method. In conclusion, mobile payment service can create new market and will result in extension of payment market.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.49-61
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• 2011

In recent, library is considered as an integrated knowledge convergence center that can respond to various requests about information service of users. Therefor it is necessary to establish a novel information system based on information communications technologies of the era. In other words, it is currently required to develop mobile information service available in portable devices such as smart phones or tablet PCs, and to establish information system reflecting cloud computing, SaaS, Annotation, and Library 2.0 etc. In this paper we design and implement a library information system using collective intelligence and cloud computing. This information system can be adapted for the varieties of mobile service paradigm and abruptly increasing amount of electronic materials. Advantages of this concept model are resource sharing, multi-tenant supporting, configuration, and meta-data supporting etc. In addition it can offer software on-demand type user services. In order to test the performance of our system, we perform an effectiveness analysis and TTA authentication test. The average response time corresponding to variance of data reveals 0.692 seconds which is very good performance in timing effectiveness point of view. And we detect maturity level-3 or 4 authentication in TTA tests such as SaaS maturity, performance, and application programs.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.21-26
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• 2004

Recently, many people want to know their state of health, such as a body fat rate, anywhere and anytime. The Personal Digital Assistance(PDA) is the portable wireless apparatus that has become widely popular. There are many application areas of the IDA to be in mobile care devices. In this study, we developed the PDA based body fat measurement system, composed of a cradle type measurement module and a WindowCE operated software module, a regression equation for predicting lean body mass (LBM). Sixty-three weight-stable subjects (53 men, 10 women) aged 20∼32yr participated in this study. A regression model, LBM ＝ (0.0005＊Height2 - 0.0160＊Impedance ＋ 0.3920＊Weight - 0.0684＊Age - 5.8141＊Sex ＋ 25.984, was found. The correlation coefficient( r) of body fat rate between developed system and HTM1000plus(BionetTM) was 0.928. HTM1000plus is a commercially available and approved by KFDA. These results indicated that developed system is reliable for estimation of body fat rate. Although developed system is the PDA based miniaturized, it shows good performance comparing with other commercial product.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.121-136
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• 2008

Although domestic research funding organizations require patented technologies as an outcome of financial aids, they have much difficulty in evaluating qualitative value of the patented technology due to lack of systematic methods. Especially, because citation data is not essential to patent application in Korea, it is very difficult to evaluate a patent using the incomplete citation data. This study proposes a method for evaluating technology importance of a patent when there is no or insufficient citation data in patents. The technology importance of a patent can be evaluated objectively and quantitatively by the proposed method which consists of 5 steps such as selection of a target patent, collection of related patents, preparation of key word vector, clustering patents, and technological importance assessment. The method was applied to a patent on 'user identification method for payment using mobile terminal' in order to evaluate technology importance and demonstrate how the method works.

• Journal of Information Technology Services
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• v.18 no.5
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• pp.17-30
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• 2019

With the advent of the Fourth Industrial Revolution, virtual reality, a technology that has recently attracted attention, is emerging as a core technology that will lead the future industry by changing the paradigm of various industries. The development of 3D rendering, computer graphics, and mobile technologies enabled the development of various smart devices and led to the popularization of virtual reality services using them. Recently, with the development of virtual reality-related technology, various devices and contents such as VR-related HMDs are being developed and released. However, since the classification for VR technology has not yet been established, it is difficult to define a range of industries and services to which VR can be applied. Therefore, in this study proposes a service classification system in terms of industries that can apply VR technology and services that can be provided based on the studies on industries and services of VR technology related to the Fourth Industrial Revolution. VR's industrial classification consists of eight industries including entertainment, media, education, medical care, architecture, manufacturing, distribution, tourism and each service is divided into two service categories and composed 16 services. Through the collection and analysis of virtual reality service cases, the service distribution and characteristics of each industry can be analyzed. In addition, we can develop a virtual reality new business model and present a service case for the intersecting areas. This study is expected to be used as a basic research for the activation of virtual reality services in the future.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.81-88
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• 2020

This purpose of this study is to develop content that enables repetitive carving practice of the maxillary right central incisor (MRCI) based on augmented reality (AR). For a step-by-step practice of achieving the tooth shape, after creation of the storyboard from the square box shape in step 1 to the completed MRCI block in step 16, three-dimensional (3D) modeling data reflecting the characteristics of the mesial, distal, lingual, and labial surface of the MRCI were generated. An application was built in which 3D modeling data were output on the screen of the learner's mobile device, and image markers suitable for 3D modeling in steps 1 to 16 of the MRCI model were respectively generated. Using this information, the learner could carve a high-quality MRCI by repeatedly performing the tooth shape carving exercises. With AR, we intend to contribute to improved tooth morphology carving skills by linking the theory and practical techniques for a beginners in dentistry.