• Journal of Korean Society of Transportation
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• v.15 no.1
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• pp.63-83
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• 1997

수송비와 재고관리비는 총 물류비용의 50% 이상을 차지할 정도로 그 중요성이 크 며, 이들 두 요소는 상호 정밀하게 관련되어 있어서 비용 트레이드 오프 관계가 존재한다. 이러한 관점에서 제품을 수송하는데 소요되는 총비용을 도출하고 비용이 최소가 되는 수송 수단을 선택할 수 있다. 이같은 분석은 수요와 리드타임이 불확실한 경우 수송시간, 고객 서비스 수준, 안전재고 수준, 주문량, 물류비용 등의 관계가 복잡해지기 때문에 해를 구하는 과정이 복잡하게 된다. 따라서 리드타임 동안의 수요를 나타내는 방법과 수송 시간의 신뢰 도와 관련된 안전재고 측정 및 기준에 대한 다양한 방법이 재고이론에 근거한 화물수송수단 선택모형 연구의 주 관심사가 된다. 본 연구는 국외에서 발표된 관련 연구들을 중심으로 재 고와 수송의 상관관계에 대하여 이론적으로 고찰하여 연구 현황을 밝히고 앞으로의 연구 방 향을 제시함으로써 이 분야의 이론적인 발전에 기여하는 것을 목적으로 한다. 연구의 주안 점은 확률적 리드타임과 수요에 대한 연구에서 쟁점이 되는 리드 타임 동안의 수요를 나타 내는 방법과 안전재고를 결정하는 기준에 모아진다.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.4
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• pp.456-463
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• 2006

The purposes of this study were to extract choice attributes of bakery cafe customers and to conduct important- performance analysis (IPA) of choice attributes perceived by bakery cafe customers. The questionnaire was developed through literature review and focus group interview, and modified after pilot test. The questionnaires for main survey were distributed to 320 males and females aged 20 and over in Seoul. A total of 275 questionnaires were used for analysis (85.9%) and the statistical analyses were conducted using SPSS Win (12.0) for descriptive analyses, exploratory factor analysis, reliability analysis, and correlation analyses. The main results were as follows. 'Products', 'convenience to use', 'services and price', 'interior environments' 'brand' and 'location' dimensions were extracted as choice attributes dimensions of bakery cafe customers and customers of bakery cafe regarded 'sanitation and cleanness', 'kindness of employees', 'quality of products', 'comfortable and pleasant facilities' and 'taste of bakery products' as more important than other attributes. In addition, the results of IPA showed that marketing managers of bakery cafes should focused on the dimension of 'services and price' in the reason that this dimension was low at performance although customers regarded it very important. Overall, researchers and managers of bakery cafes should understand unique choice attributes of bakery cafe customers, and make efforts to establish marketing strategies that meet bakery cafe customers' needs.

• 한국IT서비스학회:학술대회논문집
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• 2002.06a
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• pp.147-151
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• 2002

최근 국내 SI 사업체들은 소프트웨어의 가치를 향상시키기 위해 컴포넌트를 적극 도입하고 있다. 그러나 컴포넌트 시장을 활성화 시키기 위해서는 다양한 범주의 고객이 요구하는 양질의 컴포넌트를 풍부하게 갖추고, 고객이 시스템을 직접 개발하는 것보다 적은 비용과 시간을 소모하면서도 시스템을 구축할 수는 환경을 조성해야 한다. 그러한 환경을 구축하기 위한 요소중 고객의 구매 결정과 직결되는 가장 중요한 항목은 컴포넌트의 기술적 가치와 비즈니스적 가치의 평가와 이를 위한 시험 기준이다. 객관적이고 공정한 시험 기준이 마련되지 않는 상태에서 품질 평가가 이루어 지지 못한다면, 잠재적 고객이 구매 또는 사용하고자 하는 컴포넌트가 적절한 가치를 갖고 있는 것인지 판단할 수 있는 근거가 없고 시장 형성 초기부터 불량 컴포넌트 제품이 공급됨으로 인해 신뢰성이 저하되어 컴포넌트를 구매하는 대신 다른 대안을 선택하려 할 것이다. 객관적이고, 유력한 품질 평가 시스템을 구축하기 위해서는 품질 시험 평가를 위한 기준 마련이 선결 조건이다. 품질 시험 평가 가이드라인은 고품질의 소프트웨어 컴포넌트의 생산을 가능하게 하여, 궁극적으로 소프트웨어의 신뢰도를 향상 시키는 가장 유력한 방안이 될 것이다. 이를 통해 컴포넌트 소프트웨어의 유통 촉진 및 시장 성장을 견인, 생산/개발-유통-사용에 이르는 전체 컴포넌트 산업의 완결된 서비스를 제공 할 수 있을 것이다. 본 연구에서는 이러한 기준 마련을 위한 메트릭을 제공한다.

• Journal of Korean society of Dental Hygiene
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• v.22 no.4
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• pp.231-240
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• 2022

Objectives: This study was conducted to survey the currently available fluoride-containing oral hygiene products in Korea to provide consumers with information regarding the concentration and form of fluoride in each product, as well as to determine whether the information was easy to understand. Methods: A total of 64 types of domestic commercial oral hygiene products were purchased from an offline market and evaluated. Results: The domestic commercial toothpaste products contained fluoride in the form of sodium fluoride (NaF) and sodium monofluorophosphate (SMFP). In this study, toothpaste containing 1,000 ppm fluoride compounds accounted for the largest proportion (61.5%). Toothpastes containing below 1,000 ppm fluoride accounted for 34.6%, while toothpastes with fluoride above 1,000 ppm fluoride accounted for 3.9%. Toothpaste containing more than 1,000 ppm fluoride has not been popularized domestically. Mouthwash products contained fluoride compounds at less than 300 ppm concentration. Of the five types of mouthwash products, only two types had labels indicating fluoride concentration. In addition, the location of the labels indicating fluoride concentration differed between manufacturers and even within the same manufacturer. Conclusions: It is important to popularize toothpaste with fluoride levels above 1,000 ppm so that a broader selection of toothpaste can be offered to consumers in need. Standardized information needs to be provided for consumer convenience to aid in choosing appropriate oral hygiene products.

• Food Industry
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• s.101
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• pp.59-68
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• 1989

통조림 식품의 변패 또는 품질저하를 방지하여 안정성을 높이기 위하여서는 우선 선도가 좋은 원료를 사용하여야 하고, 제품 별로 알맞는 용기를 선택하여야 하며, 내용물 중의 성분간의 반응 또는 내용물의 성분과 용기로부터 용출되는 성분과의 반응을 막기 위한 전처리가 행하여여져야 한다. 또한 탈기, 밀봉, 가열살균 및 냉각의 각 공정이 정확하게 행하여져서 공기의 유입 및 미생물의 침입이 차단되어야 하며, 가열살균공정은 공업적살균에 기준을 두되 $F_{-}$값과 $E_{-}$값이 충족되면서 $C_{-}$값이 최소화 하도록 하여야 한다

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of Korean Society for Quality Management
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• v.6 no.1
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• pp.14-17
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• 1978

In response surface experiments, a polynomial regression model is often used to fit the response surface to explore the functional relationship between a response variable and several independent variables, and to determine the optimum operating conditions, which would be desirable to control the quality of industrial products. The problem considered in this paper is that of selecting subsets of polynomial terms from a given polynomial model so as to achieve "improved" response surfaces in estimation of the response. Such improvement in fitting the response surfaces would be very helpful to determine the optimum operating conditions and to explore the functional relationship with better precision. A criterion is proposed for selection of polynomial terms and illustrated with an industrial example.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.4987-4998
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• 2014

Recently, the use of nanotechnology in products is constantly expanding, and the problems on human health hazard has emerged as a major issue. A nanomaterials regulatory policy on the products is urgently required. This study analyzed the introduction of regulatory policies of nanomaterials contained in industrial products. In this study, the AHP (Analytic Hierarchy Process) method was applied and three regulatory policies were evaluated to analyze the validity of the introduction of a nanomaterials regulatory policy. To select the optimal regulatory policy, the policy evaluation criteria were set as enforcement (effectiveness), economics, acceptability, and protection. For the regulatory policies, self-regulation, product labelling, and enforced registration were introduced and evaluated as the regulatory policies, and product labelling was selected as the optimal regulatory policy.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.107-117
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• 2011

Smartphones are widely used as a mobile communication devices with more advanced computing ability and connectivity than a contemporary feature phone. As the market expands, many brand-new smartphones are released and chosen by (potential) smartphone users. In spite of smartphone's popularity, little research of the factors affecting the evaluation of smartphones and their influences on smartphone choice have been performed. Therefore, we aim to analyze evaluation factors of smartphone selection and use in this research. We use Fuzzy Analytic Hierarchy Process method, a Multi-Criteria Decision Making (MCDM) model, to find the relative importance among the factors considering the fuzziness of pair-wise comparison using AHP. After reviewing related works and interviewing the focus group, we extract the five independent factors influencing the choice and use of a smartphone. Pair-wise comparison and triangle fuzzy numbers are used to calculate the relative importance of factors. We analyze not only the whole interviewees' responses, but the differences between smartphone users and non-users. Practical implications are delivered in concluding remarks.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.1-15
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• 2022

In this study, text analysis was performed on the mealkit product review data to identify factors affecting the evaluation of the mealkit product. The data used for the analysis were collected by scraping 334,498 reviews of mealkit products in Naver shopping site. After preprocessing the text data, wordclouds and sentiment analyses based on word frequency and normalized TF-IDF were performed. Logistic regression model was applied to predict the polarity of reviews on mealkit products. From the logistic regression models derived for each product category, the main factors that caused positive and negative emotions were identified. As a result, it was verified that text analysis can be a useful tool that provides a basis for maximizing positive factors for a specific category, menu, and material and removing negative risk factors when developing a mealkit product.