• The Research Journal of the Costume Culture
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• v.15 no.3 s.68
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• pp.394-404
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• 2007

The purpose of the study was to analyze the difference in knitwear purchasing behaviors of female college students in the U.S., Korea, and China. It was developed questionnaire that included knitwear purchasing behavior that is fashion information sources, evaluation criteria of knitwear products, store attributes of knitwear, knitwear buying places, and purchasing experience of foreign-made knitwear. The final sample used in this study consisted of 119 female college students in U.S., 150 female college students in Korea, and 217 female college students in China. Aged from 18 to 33. ANOVA, factor analysis, Duncan's multiple range test, frequency, and percentage as analysis methods were used. The results of the study were as follows. The preference of knitwear among the respondents was shown highly. This result is due to a world-wide trend of casual clothing, and is to prove, that knitwear is that made with flexibility, drape, and stretch, is the item that is able to satisfy consumer's desires. Knitwear preference of knitwear the U.S. respondents was shown highly, and buying intention of them was also high, not only for sweaters and t-shirts but for pants, skirts, jackets, coats, and dresses as well. Knitwear information the U.S. respondents considered important, was not only purchasing experience but also shop display and magazine advertisements. By evaluating criteria of knitwear, the U.S. respondents considered good fit, design, color, and comfort important, and they didn't consider the country of origin important. By store attributes of knitwear, the U.S. respondents specially considered the display, variety, price level, and sale frequency of merchandise. The respondents of China was shown higher than them of Korea in the intention of all items. Knitwear information the China respondents considered important, was not only purchasing experience but also shop advertisements of Newspaper and magazine and fashion articles in Newspaper and magazine. By evaluating criteria of knitwear, the China respondents considered good fit, design, color, and comfort important, and they considered fiber content and the country of origin higher than the respondents of U.S. By Store attributes of knitwear, the China respondents specially considered product knowledge and friendliness of sales personnel, Layaway payment plan, Brand names, New Fashion, and Dressing Facilities higher than the respondents of U.S. or Korea.

• 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.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.315-328
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• 2018

In this paper, we examine the methodology to predict consumer preferences using several groups of attributes of products and application to real data. In the food industry, studies are in progress to investigate the relationship between product attributes and consumer preferences; consequently, various methodologies are proposed. Among these methodologies, we consider multiple factor analysis (MFA). The result of the MFA enable the division of consumers into four clusters with similar liking and the defining of preference characteristics for each cluster. Also, using the results of multiple factor analysis, we find the partial least squares path model to predict consumer preferences through the characteristics of the product and the characteristics evaluated by consumers. We can understand the relationship between the cluster of consumers and the preferred/undesirable characteristics of products through the partial least squares path model applied to two clusters with different liking. When multiple factor analysis is used in the partial least squares path model, it is possible to investigate relationships between products and consumers by analyzing product characteristics and consumer preferences simultaneously. The results can be applied to product developments and sales which makes this methodology important and useful.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.2
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• pp.315-321
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• 2012

In this study, the product attributes that give customers the estimated benefits and products that can predict the customer's choice conjoint analysis techniques to identify the restaurant affinity markets a new dining concept was to develop. Questionnaire for this study of 400 non-response is negative and insincere characters, except for the final analysis, the questionnaire Part 309 was the target. Conjoint model used in this study Pearson's R is 0.928 ($p$<0.000), Kendall's tau is 0.750 ($p$<0.000) with an orthogonal plan was well suited for profiling attributes are extracted 16. Part of the relative importance of the value of the property to determine the result of analyzing the properties that are most important at the level of the respondents of the induct (38.46%), and followed by price (30.52%), Atmosphere (18.28%), and Exclusive space (12.73%) was followed. Portion of the property value for each analysis among industry preference for the Italian food was highest, a nature-friendly interior atmosphere had the highest affinity Average per price at 10,000 won~30,000 won or less than the amount of affinity was higher location of the restaurant alone, showed that space preferred. Through simulation in a virtual seafood restaurant nature-friendly image, average price per person ranging from 10,000 to 30,000won at an exclusive restaurant was most preferred.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.68-76
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• 2011

Due to the high interests of image quality by consumers, the concerned market becomes more heated. Recent digital camera development tendency shows to perform the higher image quality to meet consumers demand of quality satisfaction. However it is hard to confirm that development of objective image quality performance means positive subjective image quality preference. And also, we cannot find out the previous researches concerned on correlation between objective and subjective image quality comparison. Therefore, it is necessary to analyze the consumers preferred images based on objective image quality performance. Throughout this paper, we analyze statistical correlation between the objective and subjective image quality assessment methods by using ISO standards. In these results, we try to find attributes that enhance image quality. We suggest not only to analyze and reflect on customers' preferences, but also to pursue the high quality image performance practically. We expect the results of this paper to positively influence product development.

• Food Engineering Progress
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• v.15 no.1
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• pp.34-40
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• 2011

As an attempt to develop a value-added food product, purple sweet potato powder was added in a model system of steamed bread as a healthy food ingredient and physicochemical properties such as moisture content, specific volume, spread ratio, color, texture as well as consumer preferences on the attributes such as uniformity, color, flavor, elasticity, chewiness, taste, and overall preference were evaluated. Moisture content ranged from 44.16 to 44.55% (wet basis) and appeared independent on the level of purple sweet potato (PSP) powder incorporation. As a result of the addition of PSP powder, the specific volume of steamed bread decreased from 3.22 to 2.55 mL/g, and value of 4.5% sample was significantly lower than other samples (p<0.05). On the other hand, spread ratio ranged from 2.01 to 2.53, and appeared to decrease as the PSP powder concentration increased (p<0.05), indicating a significant improvement. Lightness $(L^*)$ decreased significantly as the PSP powder content increased (p<0.05) for both dough and skin of the steamed bread. In addition, an increasing trend in redness ($a^*$-value) and a decreasing trend in yellowness ($b^*$-value) were noticed. Firmness increased significantly with the addition of PSP powder regardless of concentration (p <0.05); however, firmness was not significantly different among samples containing 1.5-4.5% PSP powder (p>0.05). Consumer acceptance test indicated that incorporation of 3% PSP powder in the formulation of steamed breads would be recommended.

• The Journal of Information Systems
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• v.32 no.1
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• pp.201-221
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• 2023

Purpose Customers consider the overall experience with the company as important as the quality of the product, and companies are also paying attention to creating long-term relationships with customers through optimal customer experiences. In this study, we propose a customer experience management process called 'CX-Q', which combines customer journey map and Q-methodology to understand the importance of customer experience based on the overall customer experience. Design/methodology/approach. CX-Q is a process that combines Q-methodology and customer journey maps, allowing stakeholders to explore and improve customer experiences at each contact point while engaging with brands, products, and services. It also enables them to derive customer experience insights and important management points for each segment. To demonstrate the usefulness of the proposed CX-Q, this study analyzed the experience of customers who used the Airbnb travel platform service as an example, applying the CX-Q process. Findings A total of four customer segments were derived, and it was found that each segment valued different attributes during the customer journey stage. The customer experience analysis using the CX-Q process proposed in this study is expected to help understand customers in more detail and assist in managing and improving customer experience.

• Asia Marketing Journal
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• v.8 no.2
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• pp.1-26
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• 2006

In the growing field of green marketing there are various psychological influences that can lead to green purchase behavior. An understanding of these influences can lead to greater green marketing effectiveness. The purpose of this paper is to analyze the effects of several value types, environmental attitudes, and preference for product attributes on green purchase behavior. To this end, a conceptual model has been proposed and tested for empirical verification with the use of a survey. Data collected from 266 Korean respondents are analyzed using path analysis. Results provide support for the proposed model, demonstrating positive links among universalism, environmental attitudes, preference for environmental attribute, and green buying behavior. It indicates that individuals with universalism as a preferred value type are high in their environmental attitudes and finally, tend to buy green products through their preference for environmental attribute. The mediating role of preference for price is not significant between environmental attitudes and green purchase behavior. The present findings, in addition, contribute the width of understanding of various proenvironmental behaviors by focusing on green purchase behavior and surveying with a Korean sample. The implications for the practices of green marketing are discussed.

• Korean Journal of Food Science and Technology
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• v.33 no.1
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• pp.45-49
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• 2001

This research was conducted to study the characteristics of the extruded products prepared from blends containing fixed amounts of frozen pollack (20%) and defatted soy flour (5%) and varying amounts of rice and corn flour using laboratory-scale single-screw extruder. Extrusion conditions were set at 27% feed moisture, $160^{\circ}C$ process temperature and 170 rpm screw speed. Results showed that there was almost no difference in proximate compositions among all extruded products. The product made from 100% rice flour had the highest expansion ratio, the lowest bulk density and the lowest shear force (P<0.05). Also, this product was the highest in L value and had the highest preference in sensory evaluation. Consequently, the addition of frozen pollack and defatted soy flour to rice flour could make desirable expanded extruded products. This study will form the basis for future development of rice snacks containing frozen pollack.

• The Journal of Small Business Innovation
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• v.20 no.1
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• pp.35-46
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• 2017

The purpose of this study is to obtain the implications for establishing a marketing strategy for retailers by analyzing whether the consumer's preference for products (food) is influenced by on-line, off-line, and omni-channel preferences. The research model consisted of the effects of consumers' food selection characteristics on business preference and omni channel preference. The results of analysis based on 477 questionnaires are summarized as follows. First, food purchasing characteristics that utilize the seven characteristics of (1) freshness of food, (2) taste, (3) quality and safety, (4) tasting, (5) food function and information, (6) country of origin, and (7) brand loyalty, has various effects on types of business preference, omni-channel preference. The adopted hypotheses were selected in order of brand loyalty (5 times), freshness (3 times), tasting (3 times), and origin (1 time). The selective attributes on foods are: (1) what kind of brand, (2) how good the freshness is, (3) tasting. (4) The country of origin is to be compressed. Actually consumers seem to utilize only the core selective factors that are appropriate to the characteristics of the distribution channel rather than all of them in the shopping of the food, and there is three characteristics on Convenience Store and only one or two factors in the other types of business. Second, in the analysis of the omni-channel preference analysis, food selection characteristics has been shown to have a limited effect, which is attributed to the fact that the consumer has not yet understood the concept of omni channel. Third, the results of this study suggest that there is a need to reflect the selection characteristics of foods that have diverse influences by business type in the marketing strategies. Because consumers make reasonable consumption to use both on-line and off-line simultaneously, consumers who use Omni Channel focus on quality and safety of food, identify products through tasting, pursue brands that can trust anywhere. Customers who pursue rationality will have a high preference for using Omni Channel. Product choice characteristic has significant effect on omni-channel preference. For a few years, omni-channel strategy of retailers meets with a difficulty. This study make a first attempt to study omni-channel preference changing retailing paradigm.