• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.4
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• pp.127-142
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• 2020

This study compared the domestic and international commercial design patterns and domestic consumer preferences for wetsuit designs to develop a user-centered wetsuit design. An analysis of the domestic and international design elements for 1,802 wetsuits sold online over the past three years showed that the most frequent shapes, dominant colors, and patterns were the same, as consumers tended to buy full suits that were black or had geometric patterns. Dominant colors and assort/accent colors were different from the survey results. Men's wetsuits used fewer colors and patterns than women's suits. Domestic wetsuits used fewer patterns than those sold abroad; in addition, colors were applied differently. A consumer preference survey conducted on 213 male and female consumers in their 20s and their 50s in Korea indicated that 53.5% of respondents were the most affected by the shape when choosing a wetsuit design. The preferred color scheme was two colors, with a vivid tone used as an accent color. The factor analysis results on wetsuit design preference uncovered the six factors: individuality, display, function, acceptance, imitation, and comparison. An independent sample t-test also showed that men perceive individuality, imitations, and comparison factors higher than women.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.1-20
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• 2008

Based on the multi-attribute utility theory (MAUT), we present a survey method to measure consumer preferences. The multi-attribute utility theory has been used to make decisions in OR/MS field; however, we show that the method can be effectively used to estimate the demand for new services by measuring individual level utility function. Because conjoint method has been widely used to measure consumer preferences for new products and services, we compare the pros and cons of two consumer preference survey methods. Further, we illustrate how swing weighing method can be effectively used to elicit customer preferences especially for new telecommunications services, Multi-attribute utility theory is a compositional approach for modeling customer preference, in which researchers calculate overall service utility by summing up the evaluation results for each attribute. On the contrary, conjoint method is a decompositional approach, which requires holistic evaluations for profiles. Partworth for each attribute is derived or estimated based on the evaluation, and finally consumer preferences for each profile are calculated. However, if the profiles are quite new and unfamiliar to the survey respondents, they will find it very difficult to accurately evaluate the profiles. We believe that the multi-attribute utility theory-based survey method is more appropriate than the conjoint method, because respondents only need to assess attribute level preferences and not holistic assessment. We chose swing weighting method among many weight assessment methods in multi-attribute utility theory, because it is designed to perform in a simple and fast manner. As illustrated in Clemen and Reilly (2001), to assess swing weights, the first step is to create the worst possible outcome as a benchmark by setting the worst level on each of the attributes. Then, each of the succeeding rows "swings" one of the attributes from worst to best. Upon constructing the swing table, respondents rank order the outcomes (rows). The next step is to rate the outcomes in which the rating for the benchmark is set to be 0 and the rating for the best outcome to be 100, and the ratings for other outcomes are determined in the ranges between 0 and 100. In calculating weight for each attribute, ratings are normalized by the total sum of all ratings. To demonstrate the applicability of the approach, we elicited and analyzed individual-level customer preference for new telecommunication services-WiBro and HSDPA. We began with a randomly selected 800 interviewees, and reduced them to 432 because other remaining ones were related to the people who did not show strong intention for subscription to new telecommunications services. For each combination of content and handset, number of responses which favored WiBro and HSDPA were counted, respectively. It was assumed that interviewee favors a specific service when expected utility is greater than that of competing service(s). Then, the market share of each service was calculated by normalizing the total number of responses which preferred each service. Holistic evaluation of new and unfamiliar service is a tough challenge for survey respondents. We have developed a simple and easy method to assess individual level preference by estimating weight of each attribute. Swing method was applied for this purpose. We believe that estimating individual level preference will be quite flexibly used to predict market performance of new services in many different business environments.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.93-115
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• 2017

The ability of smartphones to facilitate various services like mobile banking, e-commerce and mobile payments has made them part of consumers' lives. Conjoint analysis (CA) is a marketing research approach used to assess how consumers' preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in marketing research. The purpose of this study is to utilise CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers' smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.

• The International Journal of Costume Culture
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• v.2 no.1
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• pp.62-76
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• 1999

The objectives of this study are to investigate consumer experiences with premiums, consumer preferences in premiums offered for clothing and the effect of premiums on clothing purchasing behaviors. A self-administered questionnaire survey was conducted to 610 men and women from ages 15 to 59 living in the Seoul metropolitan area from February 25 to March 9, 1999 ; 548 were used for the data analysis. Data was analyzed by descriptive statistics, t-test, ANOVA, chi-square analysis and Duncan's multiple range tests. Significant differences were found among selected demographic groups in information sources used for premium offers, experiences of receiving premiums, purchasing experiences due to premium offers, preferences between discount and premiums, additional purchase intentions because of premiums, and the premiums'influences. The groups with purchase experiences or brand and stores selecting experiences due to premium, showed significant differences in premiums'influences and the satisfaction levels with premiums. Regarding preferences between discount and premiums, significant differences were found in and the satisfaction levels with premiums.

• Korean Journal of Agricultural Science
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• v.45 no.4
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• pp.905-916
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• 2018

The purpose of this study was to analyze factors affecting US beef consumption intention in the future, to identify the causes of US beef import growth and to derive implications and strategies for domestic beef producers. Since the KORUS FTA was signed in 2012, US beef imports in 2017 totaled 379,064 tons, an annual increase of 3.5 percent. US beef imports have been steadily increasing due to cuts in FTA tariffs and changes in consumer preferences. The data used in this study utilized a sample of 3,290 grocery purchasers from the Korea Rural Economic Institute's 2016 Food Consumption Behavior Survey. The analytical method used the Ordered Logit Model to analyze what factors influence a consumer's subjective evaluation. As a result, the major factors affecting US beef consumption intention in the future are price, taste and safety. In particular, it has to do with the recent surge in U.S. imports of good-tasting chilled meat. Because chilled meat does not differentiate the market from Hanwoo beef produced in Korea, it is necessary to have differentiated taste and low price through cost reduction. By age and family group, people aged 30 - 40 years and single-person households are the main consumption group. As a result of this study, it is necessary to establish marketing strategies for producers such as rational pricing, safety, taste promotion, and small-scale sales to extend the demand for Hanwoo beef in the younger generation to enhance the competitiveness of the domestic beef market.

• Korean Journal of Community Nutrition
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• v.29 no.4
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• pp.318-335
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• 2024

Objectives: Despite the growing market share of online grocery shopping, there is a need to understand customer perceived value due to the ongoing advancements in information technology. This study explores the connections between attributes, consequences, and values. Additionally, it conducts a cross-country comparison of consumers' online grocery shopping behaviors to gain a deeper understanding of consumer market segments and any potential variations among them. Methods: Data was collected through an online questionnaire survey conducted from May 1 to 15, 2024, targeting 400 consumers in Seoul, Korea, and Shanghai, China, who have experience with online grocery shopping. The survey utilized the Means-End Chain theory and association pattern technique hard laddering. Data collation and analysis were conducted using the IBM SPSS Statistics 28.0 program. The LadderUX software was employed to analyze the links between attributes, consequences, and values and create the consumer purchasing process's implication matrix and hierarchical value map (HVM). Results: The study identified key attributes that influence online grocery shopping decisions, including delivery service, price, freshness, and quality. Korean consumers demonstrated a higher sensitivity to price (19.0%) and delivery service (17.0%). In contrast, Chinese consumers prioritized delivery service (15.0%) and after-sales service (14.8%). Commonly cited consequences included time saving (12.6% for Koreans, 11.3% for Chinese), whereas prevalent values encompassed convenience (36.8% for Koreans, 19.6% for Chinese) and economic value (26.6% for Koreans, 14.7% for Chinese). The HVM underscored these insights, highlighting diverse consumer preferences and country-specific nuances. Conclusions: The findings highlight the current state of online food consumption and consumers' value systems, revealing variations among countries. These findings offer empirical insights that can be used to create customized global marketing strategies that resonate with various consumer preferences and market dynamics.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.465-473
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• 2021

This study is the application of a choice experiment to assess Mekong Delta urban households' preferences and motivations for ecosystem conservation in the U Minh forest. The study applied a choice modeling approach to estimate the economic values of the proposed ecosystem conservation program in the U Minh forest by accessing urban consumer preferences and their willingness to pay for the project. Discrete choice experimental data was collected from 450 residents in the cities of the Vietnamese Mekong Delta. The multinomial logit model was employed to identify consumer's stated preferences for the environmental and sustainability attributes of the conservation project. The results showed that Mekong Delta urban residents paid much attention to the proposed project to protect and develop the U Minh forest. In addition, the results showed that higher education, income, and knowledge of the U Minh forest revealed a higher likelihood of selecting the project, while the older residents would select the status quo more than the younger ones. The study also proved that the effect of participation had a strong impact on the willingness to pay for the project. The findings could be useful for policymakers to take action to raise resident's awareness and willingness to pay for the U Minh forest project.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.3_4
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• pp.322-332
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• 2003

The purpose of this study was to segment the consumer market for women's street clothes based on benefit sought. The sample was taken from 1106 middle class women who were in their 30's-40's living in Gwangju city. Consumers were classified into three groups by honest sought. The groups were practical benefit seeking group(36.7%), multi-benefit seeking group(32.6%) and symbolic/aesthetic benefit seeking group(30.7%). ANOVA, $\chi$$^2$-test revealed differences among groups according to benefit sought, use of information sources, purchasing behavior variables and demographic variables As a result of comparison for two market segmentations, benefit segmentation was proven to be more useful than segmentations using clothes image preference. But there were differences in psychological variables and demographic variables among the same benefit segments. Therefore hybrid approach on segmentation using clothes images preferences and benefit sought is neccesary.

• Food Science of Animal Resources
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• v.32 no.4
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• pp.458-466
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• 2012

In this study, consumer preferences toward traditional cheeses were investigated with Tulum cheese sample which is one of the traditional cheeses of Turkey. Type of milk used for Tulum cheese making was identified as the most important factor, followed by Tulum cheese's texture, price, salinity, fat content, origin and flavour. The ideal Tulum cheese profile for the overall consumers was made with cow milk, a hard texture, a price of 20 TL per kg, a low salt cheese, a full fat cheese, the regional cheese which belongs to Izmir region and a mild-flavoured cheese.A cluster analysis revealed there were two clusters with different ideal product profiles. Cluster 1's ideal Tulum cheese comprised a soft texture, a mild-flavoured cheese, a cheese made with cow milk, a full fat cheese, a low salt cheese, the regional cheese which belongs to Izmir region and a price of 10 TL per kg. Cluster 2 differed from cluster 1 in that its ideal Tulum cheese was a hard textured cheese and priced at 20 TL per kg. The consumers in cluster 2 were less price sensitive than those in cluster 1. In addition to, the consumers in both segments are ready to pay extra money for regional Tulum cheese versus non-regional Tulum cheese. We found that the older ones were more willing to pay as compared to younger individuals. Young people are critical target consumers for Tulum cheese marketers. The findings on cluster 1's ideal Tulum cheese of this study could therefore provide guidance to marketing managers.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.556-571
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• 2020

This study predicts consumer preference for social clothing at work, excluding uniforms using the self-product congruence theory that also establishes a model to predict the preference for recommended products that match the consumer's own image. A total of 490 Korean male office workers participated in this study. Participants' self-image and the product images of 20 apparel items were measured using nine adjective semantic scales (namely elegant, stable, sincere, refined, intense, luxury, bold, conspicuous, and polite). A model was then constructed to predict the consumer preferences using a neural network with Python and TensorFlow. The resulting Predict Preference Model using Product Image (PPMPI) was trained using product image and the preference of each product. Current research confirms that product preference can be predicted by the self-image instead of by entering the product image. The prediction accuracy rate of the PPMPI was over 80%. We used 490 items of test data consisting of self-images to predict the consumer preferences for using the PPMPI. The test of the PPMPI showed that the prediction rate differed depending on product attributes. The prediction rate of work apparel with normative images was over 70% and higher than for other forms of apparel.