• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.49-58
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• 2019

In the era of the 4th Industrial Revolution, artificial intelligence (AI) has become one of the core technologies in terms of the business strategy among information technology companies. Both international and domestic major portal companies are launching AI search services. These AI search services utilize voice, images, and other unstructured data to provide different experiences from existing text-based search services. An unfamiliar experience is a factor that can hinder the usability of the service. Therefore, the usability testing of the AI search services is necessary. This study examines the usability of the AI search service on the Naver App 8.9.3 beta version by comparing it with the search services of the current Naver App and targets 30 people in their 20s and 30s, who have experience using Naver apps. The usability of Smart Lens, Smart Voice, Smart Around, and AiRS, which are the Naver App beta versions of their artificial intelligence search service, is evaluated and statistically significant usability changes are revealed. Smart Lens, Smart Voice, and Smart Around exhibited positive changes, whereas AiRS exhibited negative changes in terms of usability. This study evaluates the change in usability according to the application of the artificial intelligence search services and investigates the correlation between the evaluation factors. The obtained data are expected to be useful for the usability evaluation of services that use AI.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Journal of Service Research and Studies
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• v.9 no.2
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• pp.41-54
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• 2019

The increasing use of mobile applications is a phenomenon that has recently come to be beneficial to people in their private life due to increased income and changes in life style. In particular, analyzing customers' consumer sentiment can be seen as a pursuit form of convenience that enables efficient use of time and effort. In this study, based on previous studies, we examine the causal relation model that influences reuse intention, which is a dependent variable through perceived value as a parameter by measuring the service convenience for cafe mobile application. In order to accomplish purpose of this study, references related to service convenience, perceived value, and reuse intention were reviewed as literature research methods. For the empirical study, the research was carried out through Macro Mill Embrain Co., Ltd. Online research was conducted for one week from October 26 to November 8, 2018. There are 13 items of the collected data were excluded and 324 items suitable for irradiation were used. Study results show that service convenience of cafe mobile application has a positive effect on perceived value and reuse intention. In addition, in the relationship that cafe mobile app's service convenience has a significant (+) influence on reuse intention, perceived value proved to have meaningful results as intermediary roles. Implications of this study are as follows. First of all, this study will be helpful for cafe companies and consumers if utilize the service convenience of cafe mobile application in perceived value and reuse intention in marketing applications. Therefore, theoretically, we propose the development direction of cafe mobile application and present academic data for marketing strategy innovation and competitive advantage in the food service industry that conforms to the fourth industrial revolution era.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.329-331
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• 2013

본 어플은 사회적 문제를 기술적 패러다임에 맞춰 해결하고자 기획되었다. 일반적으로 자기 자신의 문제점보다 다른 사람의 문제점이 더 쉽게 보이고 인식하게 된다. 작은 문제로 볼 수 있지만 최근 사회적 문제로 발생하고 있는 "따돌림" 문제는 인간의 존엄성마저 잃어버리게 하고 있다. 친구들의 문제뿐 아니라 부모와 자식, 형제, 자매 등 가족들과의 의사 단절 등으로 확대되고 있으며, 이런 문제를 해결하기위하여 많은 노력들을 하고 있지만, 실제 치료의 시간도 오래 걸리고 많은 금전도 필요하게 된다. 이렇기에 최근 트랜드의 축이 되고 있는 "스마트폰"을 활용하여 시간적, 공간적 제약을 최소화하고 더불어 수익성을 고려하여 "WHO"의 어플을 기획하게 되었다. 특히, 사후문제 처리가 아닌 "예방"의 목적으로 상대방의 문제점을 파악하는 것과 자신의 문제점을 인지하고 해결하는데 중점을 두었다. 내가 아닌 지인이 나에 대한 평가를 보다 객관적인 평가를 하기 위하여 대상자를 자신의 스마트폰 주소록에 한정하였으며, 악위적인 댓글 등을 최소화하기 위하여 금지어, 입력글자 개수제한 등을 추가하였다. 평점을 줄 수 있게 하여 상대적이고 객관적인 점수로 자신의 평점을 알 수 있게 하였고 보다 빠른 인지를 위하여 별모양의 그래픽을 사용하여 평가하도록 하였다. 특히, 본 어플은 설치자만이 사용할 수 있기 때문에 주소록에 있는 명단에서 "초대하기"기능으로 설치를 유도하였다. 본 어플을 개발 후 2주간의 테스트를 통하여 어플의 기대효과에 대한 가능성에 대해 확인할 수 있었으며 추가로 개발될 어플에는 분야별 항목을 추가하여 보다 섬세한 자아평가를 가능하도록 기획하고 있다.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.195-209
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• 2016

IoT (Internet of Things) is a collective term referring to application services that provide information through sensors/devices connected to the internet. The real world application of IoT is expanding fast along with growing number of sensors/devices. However, since IoT application relies on vertical combination of sensors/devices networks, information sharing within IoT services remains unresolved challenge. Consequently, IoT sensors/devices demand high construction and maintenance costs, rendering the creation of new IoT services potentially expensive. One solution is to launch an IoT open market for information sharing similar to that of App Store for smart-phones. Doing so will efficiently allow novel IoT services to emerge across various industries, because developers can purchase licenses to access IoT resources directly via an open market. Sharing IoT resource information through an open market will create an echo-system conducive for easy utilization of resources and communication between IoT service providers, resource owners, and developers. This paper proposes the new business model of IoT open market for information sharing, and the requirements for ensuring security and standardization of open markets.

• The Journal of Information Systems
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• v.27 no.3
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• pp.25-42
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• 2018

Purpose The purpose of this study focused on adopting production systems in cognitive psychology to improve the extraction process of persuasive design characteristics for healthcare-related mobile applications. Design/Methodology/Approach A research approach with four stages was developed. We developed and updated the evaluation guideline for persuasive design characteristics (PDC). We tried to summarize and analyze each of 28 PDC and prepared related production rules. Verification process for both guideline approach and production system approach were performed. Top one hundred apps from both medical category and health and Fitness category were selected and evaluated by two approaches. By comparing the results of the two approaches, we tried to explain the improvement and reliability of introducing the production system in the PDC extraction process. Findings Based on the updated guideline for healthcare-related mobile applications, a production system in cognitive psychology was developed. By comparing the PDC extraction results by two approaches, production system showed a better improvement for evaluation precision and efficiency for decision-making process. The findings of this study can be used for researchers and app developers to apply production system to analyze, evaluate, and develop better healthcare-related apps with persuasion.

• Journal of the Korean Society of Costume
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• v.67 no.1
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• pp.40-55
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• 2017

The current new distribution environment provides the consumers to shop at anytime and any places by using mobile appliances. So, the companies which run the offline-store increase the contact point with the consumer by launching not only online-store but also the mobile application (app). Moreover, they are trying to operate the Omni-channel shopping environment. In order for this research to draw the direction of 'the Omni-Channel Strategy', which is about the changed distribution environment of the domestic fashion enterprise, the following steps were performed. First of all, the term related to 'Omni-Channel' is defined. And then, Example of the 'Omni-Channel' strategy and 'O2O' business in the domestic distributior were researched. Lastly, present condition of the 'Omni-Channel' strategy case of the domestic fashion industry was researched. At the result, the online-stores usually have several brands which can not represent their identities. It is suggested that each online-store according to each brand has their own characteristic identity. And The Omni-Channel strategy of the domestic fashion enterprise that is needed the connection point connecting the on-line and off-line. It is able to allure the customer to the off-line-store.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.8-16
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• 2015

How to measure and evaluate the performance of managing a store? Although it is important for a retailer to execute good management in a store, there are few efficient measurement tools and methods for In-store management. Also few people are trying to deal with variety of goods (number of categories), depth of a catagory (number of stock-keeping units within a category), and stock level (the number of individual items of a particular SKU) in a store. To solve the problem, this paper suggests the Customer-Retailer Collaboration (CRC) model that utilizes Gamification. By embedding gaming elements, the store management activities can be viewed as more game-like processes. Customers find some problems they encountered in the store and send the related signals via mobile APP, and the relevant store personnel copes with the signals. As the return for their collaboration, they both will obtain points and badge. This paper designs the CRC model and shows the flow of the model briefly.

• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.51-65
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• 2018

Purpose - This paper aims to identify factors that influence the users' word-of-mouth intention (WOMI) regarding mobile apps, focussing on the impacts of technology acceptance model (TAM) and social network theory. Research design, data and methodology - Based on TAM, this study integrates social network theory into the research model. The 317 sets of data collected in a survey were tested against the model using SmartPLS. Results - Our findings suggest the following: 1) Personal innovativeness positively influences perceived usefulness (PU), perceived ease of use (PEU) and perceived enjoyment (PE); 2) PEU affects PU and PE; 3) Both PU and Satisfaction are directly correlated with WOMI. Although PEU and PE has no direct impact on WOMI, they may indirectly affect WOMI via Satisfaction, as PU, PEU and PE all positively influence satisfaction; 4) Network density and network centrality both play a mediating role in the relation between PEU and WOMI. Referral Reward Program have a positive moderating effect on the relation between PU and WOMI. Conclusions - The findings of this study illustrate the traits of Apps that can promote users' WOMI, as well as the characteristics of people who are more likely to participate in the word-of-mouth process. The findings provide a theoretical basis for app developers to make word-of-mouth a marketing strategy.

• Journal of Fashion Business
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• v.25 no.5
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• pp.88-98
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• 2021

In this study, the characteristics of digital anthropometric methods were determined with case studies. These methods were broadly classified into two categories: non-wearable and wearable. Then, these categories were further classified into four types: 3D Scanning, mobile app, smart clothing, and smart tool Among the non-wearable types, the "3D scanning" technique was based on the use of 3D hardware equipment. With this technique, the body shape was measured and the internal body information was obtained. Therefore, it is used in fields of healthcare and fitness. Among the wearable types, "Smart clothing" involves a special clothing that measures human body and a smartphone application. Both the components are linked to a fashion platform, which is based on the measured sizes that help shoppers. The "Smart tool" has the characteristic of measuring only with smart tools and smartphone applications; it does not involve the measurement of images. The common advantage of digital anthropometric methods are as follows: they reduce the time and cost of measurement by enabling self-measurement. Moreover, simple measurements are used to determine the size of anthropometry. Thereafter, it accumulates this data to track the continuous changes in size. From an industrial point of view, digital anthropometric technology should be used to increase sales. The on-demand market can be expanded as global consumers would throng the Korean fashion market. For the consumer, an avatar should be created to fit the user's size. This would provide a fun experience to the user.