• Title/Summary/Keyword: Product Data

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The Relationships between Product Quality Cues and Perceived Values based on Gender Differences at a Food Select Shop

  • Yim, Myung-Seong
    • The Journal of Industrial Distribution & Business
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    • v.11 no.10
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    • pp.59-73
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    • 2020
  • Purpose: The ultimate purpose of this work is to investigate gender differences in the relationships between product quality cues and perceived values at a food select shop. Specifically, this study examines the effects of internal and external cues, which are indicators of product quality, on emotional and social values based on gender differences. Research design, data and methodology: In this study, a questionnaire technique was used to collect the data necessary to test the proposed model. 183 data were collected through this technique. PLS SEM (Partial Least Squares Structured Equation Model) was used to test the research model. Results: First, there is no gender difference between intrinsic cue and emotional value. When using male and female data, there was no significant causal relationship between intrinsic cues and emotional values. Second, we found no gender difference between intrinsic cue and social value. When analyzed with female data, there was no significant causal relationship between intrinsic cue and social value. On the other hand, in the case of men, it was found that a weak causal relationship exists. Third, this study found gender difference between extrinsic cue and emotional value. In the case of men, it was found that a weak causal relationship exists, whereas in the case of women, a strong causal relationship exists between extrinsic cue and emotional value. Fourth, we found gender difference between extrinsic cue and social value. In the case of men, there was no causal relationship, whereas in the case of women, there was a strong causal relationship between extrinsic cue and social value. Finally, we found that there are moderating roles of gender in the relationship between external cues and perceived quality. Conclusions: As a result of analysis, it is necessary to focus on extrinsic clues of product in order to increase the perceived emotional and social values of women. On the other hand, in order to improve the perceived emotional and social values of men, it is necessary to pay attention to both intrinsic and extrinsic cues of product. Therefore, it is necessary to consider what clues and values are important to core customers.

Product Variety Modeling Based on Formal Concept Analysis

  • Kim, Tai-Oun
    • Industrial Engineering and Management Systems
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    • v.9 no.1
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    • pp.1-9
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    • 2010
  • Increasing product variety based on product family and product platform provides a company with a competitive advantage over its competitors. As products become more complex, short-life cycled and customized, the design efforts require more knowledge-intensive, collaborative and coordinating efforts for information sharing. By sharing knowledge, information, component and process across different families of products, the product realization process will be more efficient, cost-effective and quick-responsive. Formal Concept Analysis (FCA) is used for analyzing data and forming semantic structures that are formal abstractions of concepts of human thoughts. A Web Ontology Language (OWL) is designed for applications that need to process the content of information instead of simply presenting information to humans. OWL also captures the evolution of different components of the product family. The purpose of this paper is to develop product variety modeling to increase the usefulness of common platform. In constructing and analyzing product ontology, FCA is adopted for conceptual knowledge processing. For the selected product family, product variety Ontology is constructed and implemented using prot$\'{e}$g$\'{e}$-2000.

Consumer Satisfaction Formation Process of Clothing -Based on Consumer Involvement, Product Performance, and Consumption Emotion- (의류제품에 대한 소비자만족 형성과정 -소비자관여, 제품성과, 소비감정을 중심으로-)

  • 김지영;박재옥
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.5
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    • pp.663-674
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    • 2002
  • The objectives of this study were 1) to ascertain whether there was a difference in product performance (expressive or instrumental), which consumer recognized after using, related to consumer involvement toward clothing, 2) to clarify the effect of product performance on consumption emotion(positive or negative), 3) to investigate the effect of consumption emotion on satisfaction, and 4) to find out whether product performance had a direct effect on satisfaction toward product. The study was conducted in three steps. Through the two steps, measurement instruments were developed. At the last step, judgement sampling method were utilized to collect the data and subjects were 614 university students. Confirmatory factor analysis and structural equation model analysis were used to analyze the data. The results were as follows: 1) Consumer involvement had an effect on product performances but it was related to the expressive product performance more than to the instrumental product performance. 2) Product performance had positive influence on positive consumption emotion, while it had negative influence on negative consumption emotion. The results revealed that there were significant relationships between product performance and consumption emotion. 3) Positive consumption emotion had a positive effect on consumer satisfaction, on the other hand negative consumption emotion had a negative effect on consumer satisfaction. 4) Although the direct effects of product performances on satisfaction were larger than the indirect effects, product performance was greatly influential in consumption emotion and consumption emotion was strongly related to consumer satisfaction. Therefore, consumption emotion is an important determinant variable in the process of consumer satisfaction.

Implementation of a pet product recommendation system using big data (빅 데이터를 활용한 애완동물 상품 추천 시스템 구현)

  • Kim, Sam-Taek
    • Journal of the Korea Convergence Society
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    • v.11 no.11
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    • pp.19-24
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    • 2020
  • Recently, due to the rapid increase of pets, there is a need for an integrated pet-related personalized product recommendation service such as feed recommendation using a health status check of pets and various collected data. This paper implements a product recommendation system that can perform various personalized services such as collection, pre-processing, analysis, and management of pet-related data using big data. First, the sensor information worn by pets, customer purchase patterns, and SNS information are collected and stored in a database, and a platform capable of customized personalized recommendation services such as feed production and pet health management is implemented using statistical analysis. The platform can provide information to customers by outputting similarity product information about the product to be analyzed and information, and finally outputting the result of recommendation analysis.

User Sentiment Analysis on Amazon Fashion Product Review Using Word Embedding (워드 임베딩을 이용한 아마존 패션 상품 리뷰의 사용자 감성 분석)

  • Lee, Dong-yub;Jo, Jae-Choon;Lim, Heui-Seok
    • Journal of the Korea Convergence Society
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    • v.8 no.4
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    • pp.1-8
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    • 2017
  • In the modern society, the size of the fashion market is continuously increasing both overseas and domestic. When purchasing a product through e-commerce, the evaluation data for the product created by other consumers has an effect on the consumer's decision to purchase the product. By analysing the consumer's evaluation data on the product the company can reflect consumer's opinion which can leads to positive affect of performance to company. In this paper, we propose a method to construct a model to analyze user's sentiment using word embedding space formed by learning review data of amazon fashion products. Experiments were conducted by learning three SVM classifiers according to the number of positive and negative review data using the formed word embedding space which is formed by learning 5.7 million Amazon review data.. Experimental results showed the highest accuracy of 88.0% when learning SVM classifier using 50,000 positive review data and 50,000 negative review data.

Pseudo-standard and Its Implementation for the Maintenance Data of Ship and Offshore Structures (선박 및 해양 구조물에 있어서 유지보수용 데이터 교환을 위한 준표준 분석과 사례 구현)

  • Son, Gum-Jun;Lee, Jang-Hyun;Lee, Jeongyoul;Han, Eun-Jung
    • Korean Journal of Computational Design and Engineering
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    • v.18 no.4
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    • pp.267-274
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    • 2013
  • This study focuses on the data schema and data content, which includes maintenance data, data structures and illustration data relevant with the maintenance process of ship and offshore structures. Product lifecycle management (PLM) is expected to encompass all the product data generated for the operation and maintenance information as well as the design and production. This paper introduces a data exchange schema in PLM of ship and offshore, serving as the basis for the role of standards required by the middle-of-life PLM. Also this paper identifies a typology of standards relevant to PLM that addresses the schema of evolving standards and identifies a XML schema supporting the exchange of data related with maintenance operations. Technical document based on standards in accordance with S1000D and Shipdex is explained. A case study illustrating the use of standard data exchange and technical document is presented.

클릭스트림 데이터를 활용한 전자상거래에서 상품추천이 고객 행동에 미치는 영향 분석

  • Lee, Hong-Ju
    • 한국경영정보학회:학술대회논문집
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    • 2008.06a
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    • pp.135-140
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    • 2008
  • Studies of recommender systems have focused on improving their performance in terms of error rates between the actual and predicted preference values. Also, many studies have been conducted to investigate the relationships between customer information processing and the characteristics of recommender systems via surveys and web-based experiments. However, the actual impact of recommendation on product pages for customer browsing behavior and decision-making in the commercial environment has not, to the best of our knowledge, been investigated with actual clickstream data. The principal objective of this research is to assess the effects of product recommendation on customer behavior in e-Commerce, using actual clickstream data. For this purpose, we utilized an online bookstore's clickstream data prior to and after the web site renovation of the store. We compared the recommendation effects on customer behavior with the data. From these comparisons, we determined that the relevant recommendations in product pages have positive relationships with the acquisition of customer attention and elaboration. Additionally, the placing of recommended items in shopping cart is positively related to suggesting the relevant recommendations. However, the frequencies at which the recommended items were purchased did not differ prior to and after the renovation of the site.

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LDPC-LDPC Product Code Using Modified Log-likelihood Ratio for Holographic Storage System (홀로그래픽 저장장치를 위한 수정된 로그-유사도비를 이용한 LDPC-LDPC 곱부호)

  • Jeong, Seongkwon;Lee, Jaejin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.6
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    • pp.17-21
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    • 2017
  • Since holographic data storage has the advantage of high recording density and data transfer rate, it is a candidate for the next generation storage systems. However, Holographic data storage system is affected by interpage interference and two dimensional intersymbol interference. Also, burst error occurs by physical impact. In this paper, we propose an LDPC product code using modified log-likelihood ratio and extrinsic information to correct burst error and improve performance of holographic data storage. The performance of proposed LDPC product code is 0.5dB better than that of the conventional LDPC code.

Data Segmentation for a Better Prediction of Quality in a Multi-stage Process

  • Kim, Eung-Gu;Lee, Hye-Seon;Jun, Chi-Hyuek
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.2
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    • pp.609-620
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    • 2008
  • There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

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Mining Information in Automated Relational Databases for Improving Reliability in Forest Products Manufacturing

  • Young, Timothy M.;Guess, Frank M.
    • International Journal of Reliability and Applications
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    • v.3 no.4
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    • pp.155-164
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    • 2002
  • This paper focuses on how modem data mining can be integrated with real-time relational databases and commercial data warehouses to improve reliability in real-time. An important Issue for many manufacturers is the development of relational databases that link key product attributes with real-time process parameters. Helpful data for key product attributes in manufacturing may be derived from destructive reliability testing. Destructive samples are taken at periodic time intervals during manufacturing, which might create a long time-gap between key product attributes and real-time process data. A case study is briefly summarized for the medium density fiberboard (MDF) industry. MDF is a wood composite that is used extensively by the home building and furniture manufacturing industries around the world. The cost of unacceptable MDF was as large as 5% to 10% of total manufacturing costs. Prevention can result In millions of US dollars saved by using better Information systems.

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