• Journal of Fisheries and Marine Sciences Education
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• v.27 no.5
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• pp.1499-1507
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• 2015

The aim of this study is to research on the recognitions and preferences of Puffer fish consumers with the recently increasing well-being trend. To carry out this research, the main analysis was focused on two specific points: how much consumers perceive swellfish and which kinds of Puffer fish foods are preferred by consumers. Although the consumption of Puffer fish is gradually expending, at the same time, there are also numerous obstructive elements in consuming swellfish. In this regard, this test on Puffer fish food will be able to contribute to show an outlook for the Puffer fish food market in the future and to promote consumption of Puffer fish as well. Methodologically, a statistical research was adopted to find out how people understand Puffer fish and the patterns of their choices and intensive examinations were conducted throughout the collected questionnaire. For a more effective outcome, it was necessary to divide into two groups, the Nation's capital area with Seoul as a center, the most densely populated area and Busan, the biggest marine products consumption area, examining the inclination to consume with regions. In the concrete, the detailed research survey on the Puffer fish were performed with the opinions of the five hundred people from capital area and the five hundred people from Busan area. The difference and common features of consumer's recognition about Puffer fish food were founded through cross analysis according to age, gender, regions, and income. In conclusion, this research showed the difference tastes and recognition standards toward Puffer fish among consumers from Seoul and Busan areas. If it is possible to apply this result to the efforts of improving supplier's understanding about Puffer fish consumers' features and cultivating new Puffer fish items, it could contribute to the further consumption of Puffer fish food in the long term point of view.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.27-38
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• 2018

Purpose - This study centers on field surveys aimed at deriving the customer satisfaction factors of customer support centers that are positioned between suppliers and consumers in the supply chain. They consists of manufacturing, sales, distribution, consumption and collection, and that are in charge of core functions for suppliers' customer satisfaction management and consumers' satisfaction with consuming activities. Research design, data, and methodology - The customer satisfaction factors of customer support centers were derived through literature review and expert opinion surveys, and a questionnaire was developed through a process of the refinement of variables using pilot tests and 330 questionnaire sheets were distributed. The questionnaire sheets were collected and opinions in them were analyzed using fuzzy AHP methodology. Results - Three factors, which are turnover intentions, motivation, and job satisfaction, were derived as customer satisfaction factors of customer support centers, and the ranking relationships of these three factors were analyzed. In addition, the ranking relationships among six execution variables of turnover intentions, 10 execution variables of motivation, and 10 execution variables of job satisfaction were analyzed using fuzzy AHP methodology to obtain quite significant results. Based on the results of this study, three implications in the three strategic aspects and an implication in the academic aspects are presented. Conclusions - Motivation and job satisfaction, job satisfaction and turnover intentions, and motivation and turnover intentions are not formed by independent or different factors or environments. They are in the same context with each other (maintaining high correlations) and are in the relationships of virtuous circles in which they complement each other.

• Journal of Families and Better Life
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• v.28 no.6
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• pp.207-220
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• 2010

This study is intended to create a tool which can identify the concept of consumption life level and to develop a standardized scale to measure consumption life level. Based on it, the concept and perspective of consumption life level was formed and then the scale for measuring it was developed. To develop the scale, the scale was firstly formed by extracting questions through a literature survey, and verifying validity through experts' opinions. Then the final scale was developed by conducting a questionnaire survey for consumers. A preliminary 27-item scale was developed through a literature review. 1000 consumers responded to an online survey using the preliminary scale. This research was made with the intention of not only supplying academic data on the consumer's consumption life level but also understanding the consumer's basic behavior patterns. Then a series of tests: test-retest, item-to-total correlation, and Cronbach's reliability coefficient and factor analysis were conducted using the survey data and the final 20-item scale was constructed in the end. The consumer's consumption life level scale consisted of 4 factors.

• Nutrition Research and Practice
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• v.5 no.4
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• pp.313-321
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• 2011

The Korea Food and Drug Administration (KFDA) revised the Health Functional Food Act in 2008 and extended the form of health functional foods to general food types. Therefore, this study was performed to investigate consumers' perceptions of the expanded form of health functional food and to predict consumption patterns. For this study, 1,006 male and female adults aged 19 years and older were selected nationwide by multi-stage stratified random sampling and were surveyed in 1:1 interviews. The questionnaire survey was conducted by Korea Gallup. The subjects consisted of 497 (49.4%) males and 509 (50.6%) females. About 57.9% of the subjects recognized the KFDA's permission procedures for health functional foods. Regarding the health functional foods that the subjects had consumed, red ginseng products were the highest (45.3%), followed by nutritional supplements (34.9%), ginseng products (27.9%), lactobacillus-containing products (21.0%), aloe products (20.3%), and Japanese apricot extract products (18.4%). Opinions on expanding the form of health functional foods to general food types scored 4.7 points on a 7-point scale, showing positive responses. In terms of the effects of medicine-type health functional foods versus generic health functional foods, the highest response was 'same effects if the same ingredients are contained' at a rate of 34.7%. For intake frequency by food type, the response of 'daily consistent intake' was 31.7% for capsules, tablets, and pills, and 21.7% for extracts. For general food types, 'daily consistent intake' was 44.5% for rice and 22.8% for beverages, which were higher rates than those for medicine types. From the above results, consumers had positive opinions of the expansion of health functional foods to generic forms but are not expected to maintain accurate intake frequencies or amounts. Thus, continuous promotion and education are needed for proper intake of generic health functional foods.

• Journal of Families and Better Life
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• v.27 no.3
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• pp.61-77
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• 2009

This study investigates the disposal of clothing and the purchasing behavior and usage of environmentally friendly clothing. After compiling data from 500 consumers who reside in Seoul, it was analyzed by ANOVA, t-test, Chi-square, and multiple regression analysis. The behavioral score for buying environmentally friendly clothing was lower than the average value of the three. The lowest value was for the purchase of used clothing, but the purchase of environmentally friendly clothing was also shown to have a low value. For the usage and disposal of clothing, unused clothing, which was mostly just left in dresser drawers, was the most preferable method. Also, exchange or resale via anInternet mall was shown to be lower than the other methods. The analysis between clothing purchase and usage as well as the disposal of clothing with socio-demographics, consumption tendencies, opinions of friends and groups, commercials and advertisements, and environmental perceptions points out differences among groups. There are statistically significant differences in the purchasing intentions of slow fashion according to socio-demographics. Female consumers between $20{\sim}25$ years of age were more likely to purchase slow fashion clothing. Consumers with a high consumption tendency who were highly influenced by commercials, friends, and groups were more likely to purchase slow fashion clothing. The influence of the average clothing expenditure on an environmentally friendly purchasing behavior and the influence of the age group on repairing and usagewas the most effective. All in all, contribution to an environmentally friendly perception was the most effective variable.

• Journal of Sport and Applied Science
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• v.3 no.2
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• pp.17-27
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• 2019

Purpose: This study is to conduct usability evaluations from the perspective of developing comfort-shoes for the middle-aged and elderly to identify key factors and derive implications for optimal comfort-shoes production. Research design, data, and methodology: A total of 10 middle-aged and elderly women in their 50s and 60s were selected as eligible for the rescue. For data collection, the study was conducted in a Gang Survey, where pre-explanations, shoes test, and interviews were conducted. The collected data were analyzed in a total of four stages. In step 1, the contents obtained through interviews with the subjects were recorded in text, organized and analyzed systematically, and in step 2, unnecessary vocabulary, sentences, and overlapping opinions were eliminated. In step 3, we classified areas around key functions and carried out categorization tasks. Finally, in Step 4, the results and implications of the study were derived by classifying each usability evaluation shoe as positive and negative text around categorized data. Results: There are a total of seven factors for comfort-shoes usability evaluation, which are categorized as cushion, fitting, stability, flexibility, lightweight, comfort, and pressure. Positive/negative factors for the derived usability evaluation factors were shown in the form of a positive-centered, negative-centered, and positive-mixed mix for each of the four products. Positive-focused products are VA products, which are seven times more positive than negative factors. Negative-centered products are CL and SA products, which are five times more negative than positive factors. Positive mixing was a CA product with a ratio of 1:1. Text-based usability evaluations allow us to proceed with analysis based on more scientific data rather than simply listening to opinions and judging by comments. Conclusions: The study discussed implications of developing comfort-shoes for middle-aged consumers and future directions were discussed.

• Journal of The Korea Institute of Healthcare Architecture
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• v.26 no.3
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• pp.27-35
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• 2020

Purpose: A solid system in the process of establishing guidelines can increase social acceptance and utilization. The paper aims to comparatively analyze the system in which guidelines for health care facilities in the US, Australia, and the UK and suggest implications for Korea. Method: It conducted literature analysis of the system in the framework of composition, governance, and procedure for the Facility Guidelines Institute's Guideline for US, Australia's Australasian Health Facility Guidelines for Australia, and Health Building Notes for UK. Results and Implications: First, in terms of composition, the guidelines for health care facilities can be divided into composition by space and composition by issue. It is proposed to establish a system that space and issues are clearly separated, such as Australia's AusHGF, and complete it step by step. Second, in terms of governance, despite the fact that the medical supply is privately oriented, the medical system is controlled by the government in Korea. Therefore, it is suggested to form a separate organization in the public sector that establishes, researches, and revises the guideline that will serve as a focal point for experts in various fields to participate. Third, in terms of procedure, it is suggested to establish a guideline that reflects the experiences and demands of consumers by clearly organizing procedures including collecting opinions.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.5
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• pp.466-476
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• 2006

The objective of this study was to compare and analyze the acceptability and consumption attitude for soy foods between Korean and Canadian university students as young consumers. This survey was carried out by questionnaire and the subjects were n=516 in Korea and n=502 in Canada. Opinions for soy foods in terms of general knowledge were that soy foods are healthy (86.5% in Korean and 53.4% in Canadian) or neutral (11.6% in Korean and 42.8% in Canadian), dairy foods can be substituted by soy foods (51.9% in Korean and 41.8% in Canadian), and soy foods are not only for vegetarians and milk allergy Patients but also for ordinary People (94.2% in Korean and 87.6% in Canadian). In main sources of information about soy foods, the rate by commercials on TV, radio or magazine was the highest (58.0%) for Korean students and the rate by family or friend was the highest(35.7%) for Canadian students. In consumption attitude, all of Korean students have purchased soy foods but only 55.4% of Canadian students have purchased soy foods, and soymilk was remarkably recognized and consumed then soy beverage and margarine in order. 76.4% of Korean students and 65.1% of Canadian students think soy foods are general and popular and can purchase easily, otherwise, in terms of price, soy foods were expensively recognized as 'more expensive than dairy foods' was 59.1% (Korean) and 54.7% (Canadian), and 'similar to dairy foods' was 36.8% (Korean) and 39.9% (Canadian). Major reasons for the rare consumption were 'I am not interested in soy foods' in Korean students (27.3%) and 'I prefer dairy foods to soy foods' in Canadian students (51.7%). However, consumption of soy foods in both countries are very positive and it will be increased.