소비자 감성기반 맞춤형 제품 분석에 관한 연구

유인진(In-Jin Yoo),서봉군(Bong-Goon Seo),박준영(Jun-Young Park),김건우(Keon-Woo Kim),박도형(Do-Hyung Park) 한국기술혁신학회 2018 한국기술혁신학회 학술대회 발표논문집 Vol.2018 No.11

본 연구에서는 SNS, 블로그 등 다양한 채널에서 공유되고 있는 개인이 작성한 제품 정보 및 후기를 바탕으로 감성분석을 활용하여 맞춤형 제품에 대한 분석을 수행하였다. 구체적으로, 제품 중 사용자의 리뷰 정보가 풍부한 화장품에 대하여 소비자 평가 상 상위 제품 100개를 선정하여 어떠한 유형의 감성 정보가 출현하는지를 확인하였고, 제품을 대표하는 공통감성과 제품별 고유감성을 확인하였다. 이후 제품과 감성간의 네트워크 분석을 통해, 제품이 네트워크에서 위치와 역할, 제품 간 유사도를 확인하였다. 마지막으로, 제품의 평점과 순위 등 객관적 정보와 소비자 감성간의 관계 도출을 통해, 순위 및 판매량에 대한 감성요인의 영향력을 확인하였으며 분석 결과 감성 네트워크를 통해 산출된 중심성 지수가 가장 큰 영향력을 가지는 것이 확인되었다. 본 연구의 결과를 통해 확인해 볼 수 있는 시자점은 다음과 같다. 첫 번째, 제품과 감성에 대한 선행연구들에 비하여 본 연구는 감성들의 강도뿐만 아니라 네트워크 분석을 통해서 감성들의 관계적인 특징을 정량화시켜 분석하는 데에 차별성이 존재한다. 두 번째, 선행 맞춤형 제품(화장품) 연구는 사용자의 피부 진단정보를 중심으로 이루어져 왔으나 ‘감성’이라는 범위를 특정하여 텍스트를 분석한 연구는 한정적으로 이는 유의미한 시도라 볼 수 있다. 이러한 소비자 감성을 활용하여 맞춤형 서비스의 고도화 및 차별화 전략 수립에 활용될 수 있을 것으로 기대된다. In this study, we tried to find meaningful insights in customized products using emotional analysis based on product information and reviews written by consumers shared in various channels such as SNS and blog. Specifically, we identified 100 kinds of top products in the consumer evaluation for “Cosmetics” with rich user review information, and confirmed what types of emotional information appeared. We also confirmed common emotions and unique emotions for each product. After analyzing the network between the product and the emotion, we found the similarity, location, role between the product and emotion in the network. Finally, the influence of emotional factors on ranking and sales volume was confirmed by deriving the relationship between objective information such as rating and ranking of products and consumer emotion, and it was confirmed that network centrality index calculated through emotional network has the greatest influence . The results of this study suggest the following theoretical and practical implications. The theoretical implications are as follows. Previous studies using data analysis have derived emotions and confirmed the impact of each individual emotional frequency. On the other hand, there is a difference in the quantification and analysis of the relational characteristics of emotions through network analysis. Practical implications are as follows. Studies on customized products that have been developed have been based on user"s skin diagnosis information. Analysis using some SNS has been performed, but research that analyzes the text by specifying the range of "emotion" is limited as in this study. Therefore, this study can be regarded as a some meaningful attempt. It is expected that this kind of consumer sensitivity will be utilized for the development of customized service and the strategy of differentiation. Finally, the research methodology presented in this study is easy to visualize the analysis results, and is easy to understand and can be used continuously through regular updates in the future. Therefore, it is an excellent methodology in terms of economic efficiency, practicality and sustainability. Therefore, it is expected that the practicality of the methodology will be high and it will bring about effective results.

중소기업 R&D 성공에 있어서 개방형 혁신의 효과에 관한 연구

유인진(In-Jin Yoo),서봉군(Bong-Goon Seo),박도형(Do-Hyung Park) 한국지능정보시스템학회 2018 지능정보연구 Vol.24 No.3

The Korean companies are intensifying competition with not only domestic companies but also foreign companies in globalization. In this environment, it is essential activities not only for large companies but also Small and Medium Enterprises (SMEs) to get and develop the core competency. Particularly, SMEs that are inferior to resources of various aspects, such as financial resources etc., can make innovation through effective R&D investment. And then, SMEs can occupy a competency and can be survive at the environment. Conventionally, the method of self-development by using only the internal resources of the company has been dominant. Recently, however, R&D method through cooperation, also called Open Innovation, is emerging. Especially SMEs are relatively short of available internal resources. Therefore, it is necessary to utilize technology and resources through cooperation with external companies(such as joint development or contract development etc.) rather than self-development R&D. In this context, we confirmed the effect of SMEs’ factors on sales in Korea. Specifically, the factors that SMEs hold are classified as `Technical characteristic`, `Company competency`, and `R&D activity` and analyzed how they influence the sales achieved as a result of R&D. The analysis was based on a two-year statistical survey conducted by the Korean government. In addition, we confirmed the influence of the factors on the sales according to the R&D method(Self-Development vs. Open Innovation), and also observed the influence change in 29 industrial categories. The results of the study are summarized as follows: First, regression analysis shows that twelve factors of SMEs have a significant effect on sales. Specifically, 15 factors included in the analysis, 12 factors excluding 3 factors were found to have significant influence. In the technical characteristic, `imitation period` and `product life cycle` of the technology were confirmed. In the company competency, `R&D led person`, `researcher number`, `intellectual property registration status`, `number of R&D attempts`, and `ratio of success to trial` were confirmed. The R&D activity was found to have a significant impact on all included factors. Second, the influence of factors on the R&D method was confirmed, and the change was confirmed in four factors. In addition, these factors were found that have different effects on sales according to the R&D method. Specifically, ‘researcher number’, ‘number of R&D attempts’, ‘performance compensation system’, and ‘R&D investment’ were found to have significant moderate effects. In other words, the moderating effect of open innovation was confirmed for four factors. Third, on the industrial classification, it is confirmed that different factors have a significant influence on each industrial classification. At this point, it was confirmed that at least one factor, up to nine factors had a significant effect on the sales according to the industrial classification. Furthermore, different moderate effects have been confirmed in the industrial classification and R&D method. In the moderate effect, up to eight significant moderate effects were confirmed according to the industrial classification. In particular, `R&D investment` and `performance compensation system` were confirmed to be the most common moderating effect by each 12 times and 11 times in all industrial classification. This study provides the following suggestions: First, it is necessary for SMEs to determine the R&D method in consideration of the characteristics of the technology to be R&D as well as the enterprise competency and the R&D activity. In addition, there is a need to identify and concentrate on the factors that increase sales in R&D decisions, which are mainly affected by the industry classification to which the company belongs. Second, governments that support SMEs’ R&D n

시계열 군집분석을 통한 디지털 음원의 순위 변화 패턴 분류

유인진(In-Jin Yoo),박도형(Do-Hyung Park) 한국지능정보시스템학회 2020 지능정보연구 Vol.26 No.3

This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the “Gaon Chart,” a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before ‘the music bulk buying phenomenon, a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the “Gaon Chart”, a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: ‘Steady Seller’ and ‘One-Hit Wonder’. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artists superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the ‘Climbing the Chart’ phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in

자원기반이론 관점에서의 벤처기업 성과에 관한 연구

유인진(In-Jin, Yoo),서봉군(Bong-Goon, Seo),박도형(Do-Hyung Park) 한국기술혁신학회 2017 한국기술혁신학회 학술대회 발표논문집 Vol.2017 No.11

중소기업 프로파일링 분석을 통한 기술유출 방지 및 보호 모형 연구

유인진 ( Yoo In-jin ),박도형 ( Park Do-hyung ) 한국정보시스템학회 2018 情報시스템硏究 Vol.27 No.1

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology’ carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME’s technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

각인각색, 각봇각색: ABOT 속성과 소비자 감성 기반 소셜로봇 디자인평가 모형 개발

하상집(Sangjip Ha),이준식(Junsik Lee),유인진(In-Jin Yoo),박도형(Do-Hyung Park) 한국지능정보시스템학회 2021 지능정보연구 Vol.27 No.2

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of todays robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing robot development methodology or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robots appearance has an important influence in the process of forming users perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumers attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumers emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.

소비자 시선 분석을 통한 소셜로봇 태도 형성 메커니즘 연구: 로봇의 얼굴을 중심으로

하상집(Sangjip Ha),이은주(Eunju Yi),유인진(In-jin Yoo),박도형(Do-Hyung Park) 한국지능정보시스템학회 2022 지능정보연구 Vol.28 No.1

In this study, eye tracking was used for the appearance of the robot during the social robot design study. During the research, each part of the social robot was designated as AOI (Areas of Interests), and the users attitude was measured through a design evaluation questionnaire to construct a design research model of the social robot. The data used in this study are Fixation, First Visit, Total Viewed, and Revisits as eye tracking indicators, and AOI (Areas of Interests) was designed with the face, eyes, lips, and body of the social robot. And as design evaluation questionnaire questions, consumer beliefs such as Face-highlighted, Human-like, and Expressive of social robots were collected and as a dependent variable was attitude toward robots. Through this, we tried to discover the mechanism that specifically forms the users attitude toward the robot, and to discover specific insights that can be referenced when designing the robot.

데이터 기반 UX 컨셉 개발 방법론 연구

박준영(Jun-Young Park),이준식(Junsik Lee),서봉군(Bong-Goon Seo),김건우(Keon-Woo Kim),유인진(In-Jin Yoo),전형준(Hyoungjun Jeon),이슬이(Seuyi Lee),이영진(Young-Jin Lee),박경희(Kyung-Hee Park),박도형(Do-Hyung Park) 한국HCI학회 2019 한국HCI학회 학술대회 Vol.2019 No.2

본 연구는 소비자 데이터에 대한 재사용성을 높이고, 기업이 보유한 데이터에 기반하여 정량적 제품 기획 및 컨셉 도출을 위한 UX 개발 방법론을 제안하고 있다. 본 연구가 제안하는 데이터 기반UX 컨셉 개발 방법론은 데이터의 분석부터 혁신서비스 컨셉 개발까지 크게 세 단계로 구성된다. 구체적으로 첫번째 단계는 Data-driven UX Segmentation & Targeting 로서, 주어진 데이터에서 의미 있는 축을 발견하여 데이터 기반의 세분화된 세그먼트를 도출하고, 어떤 세그먼트에 집중할 지 결정하는 Targeting 과정을 포함한다. 두번째 단계인 Data-driven Persona Creation & Positioning 은 타겟 세그먼트를 대표하는 데이터 기반 페르소나를 창출하고 이를 데이터에 근거한 정량적인 속성으로 기술하는 과정과 함께 UX 컨셉이 어떤 포지셔닝 전략을 가져야 하는지 결정하는 과정을 담고 있다. 마지막 단계인 Data-driven Concept Development & Validation 은 도출된 포지셔닝 전략 기반으로 Ideation 을 수행하고 컨셉을 개발한 후, 해당 컨셉이 목표 세그먼트에 어느 정도 부합하는지 기존의 데이터를 기반으로 추론하는 과정을 포함한다. 본 연구에서는 소비자 행복지수 조사데이터를 기반으로 제안한 방법론을 실제로 적용해 보았고, 그 실효성을 확인할 수 있었다.