• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.135-141
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• 2019

Collaborative filtering algorithms often encounter data sparsity issues. To overcome this issue, auxiliary information of relevant items is analyzed and an item attribute matrix is derived. In this study, we combine the user-item attribute preference with the traditional similarity calculation method to develop an improved similarity calculation approach and use weights to control the importance of these two elements. A collaborative filtering algorithm based on user-item attribute preference is proposed. The experimental results show that the performance of the recommender system is the most optimal when the weight of traditional similarity is equal to that of user-item attribute preference similarity. Although the rating-matrix is sparse, better recommendation results can be obtained by adding a suitable proportion of user-item attribute preference similarity. Moreover, the mean absolute error of the proposed approach is less than that of two traditional collaborative filtering algorithms.

• Journal of the Korean Society of Food Culture
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• v.22 no.6
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• pp.794-800
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• 2007

The purpose of this study was to measure the tourists' preference for alternative restaurants with different combinations of 4 attribute levels: origin description, food type, price and service guarantee. A total of 210 questionnaires were completed from tourists who visited Kwangyang, Suncheon and Yeosu during Jan. 2 - Jan. 15, 2007. Conjoint experiment method was used to develop hypothetical restaurants. Ordinal probit model was used to measure the effects of attribute levels on the tourists' preference. Results of the study demonstrated that the ordinal probit model analysis result for the data indicated excellent model fit. The effects of attribute levels (origin description, traditional food, fusion food, price, service guarantee) on the tourists' preference were statistically significant. As expected, estimates of marginal willingness to pay for origin description(3.063), food type(2.349), and service guarantee(2.356) were statistically significant. Moreover, tourists were more willing to pay for origin description than other attribute levels. Tourists also considered the origin description as the very important attribute. In conclusion, based on conjoint analysis, a model was proposed of marginal willingness to pay of attribute levels. It should be noted that the original model was modified and should, preferably, be validated in future research.

• 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 the Korean Society of Costume
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• v.54 no.1
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• pp.53-68
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• 2004

The purposes of this study were to classify the contents of lifestyle of adolescence consumers, to examine the differences of lifestyle, importance of store attribute, preference of fashion store according to demographic variables, to test preference of fashion store and lifestyle, preference of fashion store, and to examine how the preference of fashion store was influenced by lifestyle, importance of store attribute, and demographic variables. Subjects were 317 adolescence consumers(13-24 years) in Seoul, Korea. Preference of imported & brand goods, orientation of fashion & beauty life, and family orientation had a direct effect on preference of department store($R^2$=.129). Sex had an indirect effect on preference of department store through orientation of fashion & beauty life. Search of video media & information and age(-) had a direct effect on preference of entertainment shopping center($R^2$=.150). Orientation of fashion & beauty life(-), sales promotion, sex, and reasonable consumption had a direct effect on preference of discount store(R =$^2$.109). Sex(-) had an indirect discount store through orientation of fashion & beauty life, and sex(-), search of video media & information, age(-), and reasonable consumption did through sales promotion. Sales promotion, preference of imported & brand goods(-), and store atmosphere(-) had a direct effect on preference of traditional market($R^2$=.060). Sex(-), age(-), search of video media & information, and reasonable consumption had an indirect effect on preference of traditional market through sales promotion, and search of video media & information, reasonal consumption, and acceptance of foreign culture did through store atmosphere.

• Journal of the Korean association of regional geographers
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• v.11 no.4
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• pp.497-510
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• 2005

The purpose of this study was to examine the image similarity, preference, and the attribute recognition using multidimensional scaling. The analyses were carried out by 5 spa destinations located in Choongchung area. The results were as followings: first, considering the image similarity, the image of Suanbo & Onyang and Dogo & Asan were similar except for the Yusung. Second, considering the attribute recognition, Yusung had a stronger attribute reflecting spa tradition when compared to other competitive spa destinations. Onyang showed a strong attribute of facilities. Dogo had a stronger point about use cost. Suanbo had relatively strong attributes in terms of facilities, customer service, and accessability. However, the water quality of spa destination and activities were not reflected in attribute recognition because these two attributes was farthest from the spa destination. Third, considering the preference of selecting spa destinations, package tourists had a strong preference about Yusung, individual tourists, family, incentive tourists prefer Suanbo, followed by Dogo and Yusung. Group tourists had a strong preference about Dogo.

• Journal of the East Asian Society of Dietary Life
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• v.18 no.2
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• pp.165-171
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• 2008

The purpose of this study was to measure tourists' preference for alternative restaurants with different combinations of attribute levels: grown area logo, origin description, traditional food, fusion food, national food, and price. A total of 210 questionnaires were completed. A conjoint experimental method was used to develop hypothetical restaurants, and an ordinal probit model was used to measure the effects of the attribute levels on tourists' preference. The ordinal probit model analysis results for the data indicated an excellent model fit. The effects of the attribute levels on tourists' preferences were statistically significant. As expected, estimates of the marginal willingness to pay were statistically significant Moreover, the tourists were more willing to pay for grown area logo as compared to the other attribute levels. The tourists also considered the grown area logo as a very important attribute. Withe regard to developing and testing conjoint models in the design of choice experiments involving multifactor alternatives, this study may approach a deeper understanding of the conjoint experiment. Greater understanding of the conjoint experiment can improve the managerial diagnoses of the problems as well as the opportunities for different marketing strategies including local branding programs and menu development and marketing communications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2099-2107
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• 2011

Despite the PB diffusion introduced as a strategic competitive factor from the change of a retailing business, the study of PB perceived quality in a customer aspect is poor. Therefore, this study led the influential factors to retailer attribute and product attribute through overall analysis. Also, the study found the influential attributes affecting the perceived quality and analysed the influential power linking to customer satisfaction and preference through the perceived quality. The examined results of the study have known that each attribute links to customer satisfaction via the only perceived quality. The strategic PB sales advantage should be achieved as giving customers the overall perceived quality, and has shown that it can increase the customer preference for PB.

• Culinary science and hospitality research
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• v.14 no.1
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• pp.1-10
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• 2008

The purpose of this study was to measure the estimated coefficient and marginal willingness to pay of attribute level: origin logo, origin description, traditional food, fusion food, service guarantee, and price, which influence tourist preference for restaurants. Also, the study identified the attribute which confers the highest importance to tourists. Conjoint experiment and the ordinal probit model were used for this study. A total of 210 surveys were conducted by tourists. The findings from this study were as follows. First, the effects of all attributes on tourist preference for restaurants were statistically significant. Second, tourists regarded an origin logo as the very important attribute, and were more willing to pay for the case where the menu contained origin logo. These findings suggested new marketing opportunities for restaurant managers. Although this study provides some evidence on the value of the local product brand to tourists, a similar measure has not been developed for local residents. This is an area in need of future research.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.111-126
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• 2002

This paper presents an interactive decision procedure to aggregate each group member's preferences when each group member articulates his or her preference information incompletely. An index, an indicative for the preference strength between alternatives, is derived to aid each decision maker to articulate preference information about alternatives. We develop a mathematical programming model that can establish dominance relations when the preference information about values of alternatives, attribute weights, and group member's importance weights are provided incompletely. Also, the preference relation between alternatives is to be considered in the model. Based on the preference strength measure and mathematical model, we develop an interactive group decision support procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.