• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.205-209
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• 2002

인체의 피부온도는 쾌적성과 감성에 크게 영향을 미치며 의류의 개발이나 건축환경의 설계 등에 활용되고 있다. 단순히 몇몇 측정점에서의 피부온도 데이터가 아니라 인체표면에 걸친 온도분포를 파악함으로써 다양한 정보를 이용하여 보다 광범위한 응용분야에 활용될 수 있을 것이다. 현재 인체표면의 온도분포를 측정하기 위하여 대부분 적외선 열화상 카메라를 활용하고 있다 그러나 열화상 카메라는 서미스터 등을 이용한 피부온 센서에 비하여 온도분해능이 떨어지며 특히 의복내의 피부온을 측정하는 것이 불가능하고 노출된 인체표면에 대해서만 측정이 가능하다. 따라서 본 연구에서는 피부온 센서를 이용한 인체표면 온도분포 측정시스템을 개발하기 위하여 각 센서의 위치와 간격, 그리고 인체 곡면을 따라서 보간법에 따라 온도분포 결과에 미치는 영향을 파악하고 적외선 화상 결과와 비교하고자 한다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.211-215
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• 2001

실내나 의복내 열적쾌적성을 평가하기 위해서는 정밀하고, 안정성이 높으며 빠른 응답특성을 갖는 센서와 측정시스템이 필요하다. 더욱이 의복내의 온도를 측정하기 위해서는 소형, 경량으로 인체에 부착하기 쉬워야하며 측정기의 부착이 피험자에게 부담을 주어서는 안된다. 본 연구에서는 이러한 요구사항을 만족할 수 있으면서도 이동이 자유롭고 장시간 측정이 가능한 큰 Data 저장용량, 실시간 측정 기능, 손쉬운 온습도 변환장치등을 갖춘 의복내 및 실내 온습도 측정등의 다양한 분야에 활용이 가능한 온습도 측정기와 이에 필요한 센서를 개발하고 개발된 측정기의 선형특성을 평가하였다.

• Journal of Distribution Science
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• v.6 no.2
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• pp.61-79
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• 2008

This paper studies on the influence of customers' perceived store crowding, shopping emotions, shopping value, and repatronage intention. The result is as follows. First, human crowding and spatial crowding influence two dimensions of shopping emotions: positive shopping emotions and negative shopping emotions. Especially human crowding influences positively on positive shopping emotions while spatial crowding influence positively on negative shopping emotions, which means that shoppers visiting stores feel negative shopping emotions toward spatial crowding, but that shoppers' crowding in stores can arose positive shopping emotions which intrigue interest and liveliness. Second, positive shopping emotions and negative shopping emotions influence two dimensions of shopping values: hedonic shopping value and utilitarian shopping value. Especially positive shopping emotion influences positively on utilitarian shopping value and hedonic shopping value while negative shopping emotion influence negatively on utilitarian shopping value and hedonic shopping value. Third, the result shows that shoppers' shopping values influences positively on repatronage intention.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.93-104
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• 2018

Purpose - This study is to investigate the relationship among emotional intelligence, self-efficacy and job stress of foreign life insurance consultants focusing on the mediating effect of self-efficacy. Regarding job security, in general foreign life insurance companies in Korea have more severe working conditions in terms of required contract performance. For foreign life insurance consultants, they are assumed to need higher level of emotional intelligence and self efficacy to meet the conditions. In this study, focus is cast on these aspects. Research design, data, and methodology - Basically the research is conducted upon questionnaires responded by foreign life insurance consultants. That is, data are collected from 255 sample of insurance consultants who work for a foreign owned life insurance company. The Questionnaire measure the level of emotional intelligence, self-efficacy and job stress of insurance consultants. The data are analyzed using pearson's correlation coefficient and hierarchical multiple regression, descriptive statistics, t-test, ANOVA, Durbin-Watson test. Results - The general characteristics of respondents are gender, age, marital status, education level, income monthly, career length, change jobs no, working day per week, call no. per week, meeting no. with client per week, contract regularity, contract no. per month and cancellation contract per year. The mean of emotional intelligence is 2.63, self-efficacy is 3.44 and job stress is 2.20. Emotional intelligence is composed with mean value of self emotion appraisal(3.93), other's emotion appraisal(3.78), regulation of emotion(3.29) and use of emotion(3.52). The mean of self efficacy is composed with mean value of self-confidence(3.41), self-regulated efficacy(3.59) and preference task difficulty(3.30). The job stress is composed with mean value of job requirement(2.61), lack of job autonomy(1.99), conflict of personal relations(1.99), job instability(2.38), organizational system(2.19) and inappropriate compensation(2.07). There is a significant positive correlation between emotional intelligence and self-efficacy. The emotional intelligence and self-efficacy are significantly negative correlation with job stress. The self-efficacy is showed a mediating variable between emotional intelligence and job stress. Conclusions - To decrease job stress level, foreign life insurance company should find the factors to improve the emotional intelligence and self-efficacy of life insurance consultants, and develop appropriate plans using a mediating role of self- efficacy between emotional intelligence and job stress.

• Management & Information Systems Review
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• v.38 no.1
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• pp.169-180
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• 2019

The results of the present study on corporate social responsibility activities have different results for each researcher. This is considered to be the influence of the moderated variables depending on the relations among the variables. The purpose of this study is to propose anti-corporate emotion as a variable to moderate the relationship between social responsibility activities and outcome variables and to investigate its influence. The results and implications are as follows. Ethical responsibility activities and discretionary responsibility activities had effects on corporate attitude and corporate attitude affects consumers' purchase intention. This is consistent with many previous studies, which means that it is necessary to create a positive psychology for a firm or product in order to induce consumer behavior. In addition, in the group with high anti-corporate emotions, the effect is not significant even if the company has a lot of discretionary activities, but if the ethical responsibility is done, the negative attitude toward the company can be alleviated even if the anti- corporate emotion is high. This explains why many companies now have social contribution activities as an alternative to reduce the corporate crisis, but the effect is insufficient. Therefore, companies that want to carry out social responsibility activities should be interested first in the ethical management or ethical responsibility activities of companies.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.59-72
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• 2011

Since stress can cause a variety of diseases, the relaxation of stress is an important factor for preventing diseases. One way to relieve stress is to use auditory or visual materials. If auditory and visual ones are used together, the effect of stress relaxation will be maximized. In this context, we analyze mood distribution of genre of music and color distribution of mood from the mood data for musics and color data for mood words collected directly from volunteers. Based on these two distributions, we also perform the $X^2$-test with Minitab for checking that color distributions are different from genre to genre. The results show that a different genre has a different color distribution and that the distributions of color, brightness and saturation depend on mood (P<0.0001). The results will be used to develop an emotional lighting system which plays lighting according to music mood, which can be applied to psychotherapy but more data and analysis are needed for clinical trials.

• The Korean Journal of Franchise Management
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• v.9 no.2
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• pp.7-16
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• 2018

Purpose - Turnover Intention in the franchise industry is becoming a very important issue. This study examines the structural relationships between organizational justice, emotion, job satisfaction, and turnover intention in the franchise industry. In this model, emotion was classified into two sub-dimensions such as positive and negative emotion. Research design, data, methodology - The sample of this study collected from employees of a food-service franchise company is representative. Copies of the questionnaire along with a cover letter were delivered by a research assistant to the human resources manager or the general manager of the selected food-service franchise firms after they agreed to participate in the study. In order to increase the response rate of the respondents, a small gift was provided to the respondents who completed the questionnaire. A total of 300 questionnaires were distributed and 285 returned responses, 9 responses were not usable due to missing information. Thus, a total of 276 responses were used using structural equation modeling with Smartpls 3.0. Results - The results showed that organizational justice had positive significant effects on positive emotion and job satisfaction. Job satisfaction had negative a significant effect on turnover intention. And negative emotion had positive significant effect on turnover intention. Conclusions - The results of this study provide some implications. If employees feel that the franchise headquarters is fair about the methods and procedures of decision making, resource allocation, information sharing, etc., it means that employees feel better. If the franchise's decision-making processes and methods and results are transparently disclosed and processed in accordance with the internal rules of the company, the employees will be able to fully understand and accept them. The results of this study also show that positive and negative emotions of service-based franchise employees have different effects on job attitude and organizational behavior. In particular, when negative emotions of employees are passed on to others and the results are negative, employees may feel that they are disoriented or wrong. Therefore, the franchise headquarters should try to inspire employees' sense of organizational community, and should pay attention to how to relieve the job stress and the fair distribution of work and rewards.

• Journal of Distribution Science
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• v.20 no.8
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• pp.105-114
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• 2022

Purpose: The technology acceptance model (TAM) refers to a theory that maps the possibility or extent to which users can accept an innovative technology. The purpose of the current research is to investigate the mediating effect of TAM between online review and behavior intention for promoting golf app's distribution. Research design, data and methodology: In order to examine the relationship between app usage reviews, TAM, and behavioral intentions of golf app participants, the present author collected total 170 responses from South Korean participants based on web-based survey system. The main methodology which was selected by this study is mediation causality analysis that Baron and Kenny suggested. Results: The statistical findings definitely indicated that TAM mediating role exists between the positive emotion of golf app users regarding online reviews and positive behavior intention of golf app, which means that all three steps of mediation causality analysis were statistically significant. Conclusions: The present research concludes that the correct utilization of innovation in the design and implementation of the technology features translates into performance excellence. The model can be used to increase the online presence through innovation as a primary drive toward providing more convenience and accessibility to the users through mobile golf apps.

• Journal of Distribution Science
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• v.19 no.7
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• pp.51-59
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• 2021

Purpose: Anger has become one of the dominantly experienced emotions in recent years, particularly under the COVID-19 pandemic. Considering the critical role that anger plays in consumers' lives, the present research examines how feeling angry about money influences consumers' spending and money distribution decisions. Research design and methodology. Three experiments were conducted using different emotion induction methods (i.e., dictator game, autobiographical recall, and scenario). Results. Feeling angry about money decreased pro-social spending (i.e., less money distribution to the others), but it did not affect virtuous or utilitarian spending for the self-unlike past finding on negative feelings that increased utilitarian spending. Furthermore, whereas anger-tainted money decreased pro-social spending of that money, guilt-tainted money increased pro-social spending. However, the effects of guilt versus anger were not completely symmetrical. The antagonistic effect of anger was diffusive across spending on distant and close others, whereas the pro-social effect of guilt was limited to distant others. Conclusions: These findings help policy makers and financial institutions forecast how money will be distributed or circulated when it is likely to be dampened by anger under the pandemic. They also highlight the importance of examining the effects of discrete emotions (e.g., anger vs. guilt) beyond valence.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.