• 한국항행학회논문지
• /
• 제22권2호
• /
• pp.168-172
• /
• 2018

HACCP이란 식품의 원재료부터 제조, 가공, 보존, 유통, 조리단계를 거쳐 최종소비자가 섭취하기 전까지의 각 단계에서 발생할 우려가 있는 위해요소를 규명하고, 이를 중점적으로 관리하기 위한 중요관리점을 결정하여 자율적이며 체계적이고 효율적인 관리로 식품의 안전성을 확보하기 위한 과학적인 위생관리체계라고 할 수 있다. 본 논문에서는 HACCP의 체계적이고 효율적인 관리를 위해 식품의 유통 단계인 운송과정에서의 온도 및 습도를 측정하고, 이 정보를 통신망을 이용하여 주기적으로 서버에 전송하는 모니터링 단말기 및 이를 구현하는 firmware를 설계하였다. Sub-net에서 측정된 정보를 포함하여 단말기에서 전송된 데이터가 서버에 잘 저장되었으며 서버에서 보낸 응답도 단말기에 잘 수신됨을 확인하였다. 향후 이를 이용하여 식품의 이력관리 및 데이터 추적, 통계자료로 활용할 수 있을 것으로 기대된다. 또한 본 시스템은 학교나 직장 등 단체 급식소, 원재료나 식품 보관 등의 물류창고 등에서도 응용할 수 있는 시스템이 될 것으로 사료된다.

• 한국콘텐츠학회논문지
• /
• 제20권12호
• /
• pp.519-528
• /
• 2020

본 연구는 미용업체에 대한 브랜드 신뢰가 소비자 충성행동으로 이어지는 관계에 관한 연구로 브랜드신뢰의 중요성을 알아보고 브랜드 인지정도의 조절효과를 검증하였다. 설문대상은 헤어미용서비스 이용경험이 있는 소비자이며, 2019년 12월 15일부터 2019년 12월 30일까지 자기기입식 설문을 진행하였다. 총 288부의 응답데이터가 분석에 사용되었으며, SPSS 21.0 통계패키지프로그램을 활용하였다. 헤어숍 브랜드 신뢰는 전문성, 호의성, 정직성으로 구분하였으며, 분석결과 전문성은 경제적 충성행동에 유의한 영향을 미치고, 정직성은 경제적 충성행동과 사회적 충성행동에 유의한 영향관계를 보였다. 호의성은 영향관계가 나타나지 않았다. 브랜드 인지정도의 조절효과를 검증해 본 결과 전문성과 정직성은 사회적 충성행동 간의 영향관계에서 조절작용을 하는 것으로 나타났다. 본 연구는 빠르게 변화하는 경쟁 환경 속에서 헤어숍의 브랜드 신뢰와 고객의 관계를 안정적으로 구축하기 위한 효과적인 방향을 제시하고자 한다.

• 아태비즈니스연구
• /
• 제10권3호
• /
• pp.113-124
• /
• 2019

With the decline in the college student population and the increase in the youth unemployment rate, the university began to be interested in starting a business. Under the initiative of the government, the start-up support project was reflected in the university's educational programs, which led to the university students receiving various start-up support benefits. In response to the expansion of entrepreneurship education, various entrepreneurship education programs and support programs were applied in line with the government's efforts to start college students. As a result, students' entrepreneurial competence and willingness to start up increased. College student entrepreneurs and entrepreneurs are increasing. The increase of university student start-up companies is taking place in the entrepreneurial education environment within the university, and the support of university, community, and start-up support institutions for university student start-up, the starting point of the start-up ecosystem, is paying off. It can be seen that the youth entrepreneurship ecosystem based on university entrepreneurship education is in place. The university supports the entire business process from idea development, such as start-up classes, start-up club support, patent application support, prototype development support, and investment linkage. However, there is a university that develops and operates a unique program for each school and a university that does not. Therefore, it is necessary to develop an education program that can produce efficient results. The purpose of this study is to support the start-up program of the university to be the consumer-centered start-up support.

• 한국산업정보학회논문지
• /
• 제27권3호
• /
• pp.11-20
• /
• 2022

현재 광고 분야 등에 널리 사용되고 있는 흑백 QR코드의 정보 저장 용량을 증가시키기 위해 칼라 QR코드에 대한 연구가 활발히 진행되고 있다. 그러나 칼라 QR코드는 프린팅 또는 스캐닝 과정에 의해 복재가 될 수 있으며, 이 과정에서 불충분한 조도에 의한 색상 왜곡과 잡음, 카메라의 낮은 해상도와 기하학적 변형의 가능성이 있다. 이러한 일련의 복합적인 과정들은 품질 저하와 인식률 저하를 초래한다. 이러한 문제점을 극복하기 위해 본 논문에서는 칼라 QR코드에 패턴 삽입을 고려하고, 이를 위한 효과적인 인식 방법을 제안한다. 또한, 제안한 방법을 통해 기존에 다루어진 대표적인 패턴을 도입하고, 인식률 측면에서 실험을 수행하여 그 결과를 비교 분석한다. 즉, 인식과정에 있어서 쉽게 초래되는 가우시안 잡음과 블러링, 기하학적 변형 등의 잡음을 고려하여 성능을 비교 분석한다. 다양한 실험을 통해 가우시안 잡음과 블러 측면에서 단순한 패턴의 칼라 QR코드가 우수한 성능을 보이는 것을 확인할 수 있다.

• 산업진흥연구
• /
• 제7권1호
• /
• pp.9-15
• /
• 2022

본 연구는 한국 커피산업에서 경쟁력 있는 기업인 스타벅스의 성장배경을 분석하고자 하였다. 이에 STEEP 분석기법을 활용하여 기업이 보유한 각각의 경쟁력을 분석하고 결과를 경쟁력 요소를 도출하고자 하였다. 연구 결과는 다음과 같다. 사회적인 측면을 살펴보면 경제성장에 따른 생활수준이 높아져옴에 따라 여성에 경제적 활동이 기폭제 역할을 해왔다. 또한 과거 커피문화의 경우 자판기 믹스커피 문화에서 문화공간적인 측면을 강조하는 소비시장으로 변모함을 간파해온 스타벅스 대응전략이 유효하였다. 기술적인 측면을 살펴보면 프랜차이점 원두 맛에 일률적 표준화를 확보하여 편차를 줄여왔으며 매장을 직영으로 운영함으로서 표준화된 운영 시스템 운영이 가능하였다. 그리고 경제적인 측면을 살펴보면, 커피 소비시장이 확장세를 이어옴에 따라 시장전체 크기 또한 비례적으로 커져 안정적인 성장환경이 형성되어왔다는 점이다. 마지막으로 환경적, 정책적 측면을 살펴보면, 최근 친환경성을 강조한 정책방향을 간파하고 시장 선두기업으로서 친환경 기업으로서의 정책 활동에 기초한 마케팅 전략방향이 주요해왔다는 점이다.

• 한국IT서비스학회지
• /
• 제21권4호
• /
• pp.123-140
• /
• 2022

In the ever-increasing online secondhand product market, the perceived risk of online used products purchase was identified as a factor influencing consumer purchase intention. The results of this study are as follows. First, the relationship between the perceived risk of online secondhand purchase and purchase intention was presented with somewhat different results for each sub-risk factor. First of all, a significant negative causal relationship between physical risk, time loss risk, psychological risk, social risk and online used product purchase intention was verified. On the other hand, financial risk and functional risk did not show a statistically significant relationship with online used products purchase intention. Second, as a result of research on the moderating effect of purchasing experience, offline purchasing experience of used products and online purchasing experience were verified differently. First of all, the moderating effect of the online purchase experience of used products was significant only in the relationship between psychological and social risks on the intention to purchase used products online. The experience of purchasing used products online is believed to reduce uncertainty about the surrounding response to purchasing used products online and weaken the intention to purchase used products online by reducing tension and concerns about purchasing them. Other risks, such as financial risk, performance risk, physical risk, time loss risk, and online purchase experience of used products, were verified to have no significant effect on online used products purchase intention. In addition, the offline purchase experience of used products did not verify a significant moderating effect on the effect of all perceived risks on online used product purchase intention.

• 한국의류산업학회지
• /
• 제23권2호
• /
• pp.200-211
• /
• 2021

This study examines the effects of fashion influencers' body types (realistic versus ideal body types) on self-expression, self-representation, and recommendation intentions, as mediated by familiarity toward influencers. Although fashion influencers lead to a positive consumer response compared to traditional advertisements, previous research on the effects of fashion influencers on consumers is limited. Thus, this study tests the role of consumers' socio-psychological aspects in understanding how and why fashion influencers affect consumers' behavioral intentions associated with self-expression, self-representation, and influencer recommendation. A total of 180 women in their 20s and 30s participated in the survey. The responses were collected after showing them stimuli featuring fashion influencers with either ideal or realistic body shapes. The data were analyzed using SPSS18.0 for descriptive statistics, and AMOS 18.0 for confirmatory factor analysis and structural equation modeling. The results showed that participants who were shown realistic body types perceived familiarity, which generated positive effects on self-expression, self-representation, and recommendation intentions. Hence, the effects of influencers' body types on recommendation intention are mediated by familiarity. Self-expression and self-representation intentions also increase influencer recommendation intention. Comparatively, participants who were shown ideal body types only induced higher self-representation intention, which increased their recommendation intention. The current findings can help fashion marketers select the appropriate influencers who fit their target customers as promotional models, as well as to induce changes in consumers' behavioral intention.

• International Journal of Computer Science & Network Security
• /
• 제23권9호
• /
• pp.1-7
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
• /
• 제23권8호
• /
• pp.210-216
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• 한국의류학회지
• /
• 제47권4호
• /
• pp.625-645
• /
• 2023

This study examined newspaper articles from 2012 to the first quarter of 2021 to explore how interest in and response to veganism have evolved in the fashion and beauty industries over the past decade. By analyzing keywords and word correlations, we discovered a steady increase in veganism-related articles in both English- and Korean-language newspapers published in Korea, especially since 2019. Since 2012, consumer interest in vegan fashion materials has grown, with fashion and beauty emerging in 2018 as significant vegan-related keywords. As a result, brands have adopted vegan certification systems and introduced vegan product lines, and new vegan brands have emerged. Since 2020, companies have been promoting environmental, social, and governance (ESG) management practices and working toward eco-management that reflects vegan trends in all areas, such as cruelty-free product/packaging materials, brands, policies, and services. It is also notable that fashion/beauty consumers have been more actively starting to adopt eco-friendly lifestyles and participate in vegan-related movements since that time. Our findings offer important insights into the evolution of veganism in Korea and can help researchers and industry practitioners to develop future business strategies in the vegan fashion and beauty industries.