• Asia Marketing Journal
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• v.15 no.4
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• pp.61-101
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• 2014

This study investigates when and how disagreements in online customer ratings prompt more favorable product evaluations. Among the three metrics of volume, valence, and variance that feature in the research on online customer ratings, volume and valence have exhibited consistently positive patterns in their effects on product sales or evaluations (e.g., Dellarocas, Zhang, and Awad 2007; Liu 2006). Ratings variance, or the degree of disagreement among reviewers, however, has shown rather mixed results, with some studies reporting positive effects on product sales (e.g., Clement, Proppe, and Rott 2007) while others finding negative effects on product evaluations (e.g., Zhu and Zhang 2010). This study aims to resolve these contradictory findings by introducing preference heterogeneity as a possible moderator and causal attribution as a mediator to account for the moderating effect. The main proposition of this study is that when preference heterogeneity is perceived as high, a disagreement in ratings is attributed more to reviewers' different preferences than to unreliable product quality, which in turn prompts better quality evaluations of a product. Because disagreements mostly result from differences in reviewers' tastes or the low reliability of a product's quality (Mizerski 1982; Sen and Lerman 2007), a greater level of attribution to reviewer tastes can mitigate the negative effect of disagreement on product evaluations. Specifically, if consumers infer that reviewers' heterogeneous preferences result in subjectively different experiences and thereby highly diverse ratings, they would not disregard the overall quality of a product. However, if consumers infer that reviewers' preferences are quite homogeneous and thus the low reliability of the product quality contributes to such disagreements, they would discount the overall product quality. Therefore, consumers would respond more favorably to disagreements in ratings when preference heterogeneity is perceived as high rather than low. This study furthermore extends this prediction to the various levels of average ratings. The heuristicsystematic processing model so far indicates that the engagement in effortful systematic processing occurs only when sufficient motivation is present (Hann et al. 2007; Maheswaran and Chaiken 1991; Martin and Davies 1998). One of the key factors affecting this motivation is the aspiration level of the decision maker. Only under conditions that meet or exceed his aspiration level does he tend to engage in systematic processing (Patzelt and Shepherd 2008; Stephanous and Sage 1987). Therefore, systematic causal attribution processing regarding ratings variance is likely more activated when the average rating is high enough to meet the aspiration level than when it is too low to meet it. Considering that the interaction between ratings variance and preference heterogeneity occurs through the mediation of causal attribution, this greater activation of causal attribution in high versus low average ratings would lead to more pronounced interaction between ratings variance and preference heterogeneity in high versus low average ratings. Overall, this study proposes that the interaction between ratings variance and preference heterogeneity is more pronounced when the average rating is high as compared to when it is low. Two laboratory studies lend support to these predictions. Study 1 reveals that participants exposed to a high-preference heterogeneity book title (i.e., a novel) attributed disagreement in ratings more to reviewers' tastes, and thereby more favorably evaluated books with such ratings, compared to those exposed to a low-preference heterogeneity title (i.e., an English listening practice book). Study 2 then extended these findings to the various levels of average ratings and found that this greater preference for disagreement options under high preference heterogeneity is more pronounced when the average rating is high compared to when it is low. This study makes an important theoretical contribution to the online customer ratings literature by showing that preference heterogeneity serves as a key moderator of the effect of ratings variance on product evaluations and that causal attribution acts as a mediator of this moderation effect. A more comprehensive picture of the interplay among ratings variance, preference heterogeneity, and average ratings is also provided by revealing that the interaction between ratings variance and preference heterogeneity varies as a function of the average rating. In addition, this work provides some significant managerial implications for marketers in terms of how they manage word of mouth. Because a lack of consensus creates some uncertainty and anxiety over the given information, consumers experience a psychological burden regarding their choice of a product when ratings show disagreement. The results of this study offer a way to address this problem. By explicitly clarifying that there are many more differences in tastes among reviewers than expected, marketers can allow consumers to speculate that differing tastes of reviewers rather than an uncertain or poor product quality contribute to such conflicts in ratings. Thus, when fierce disagreements are observed in the WOM arena, marketers are advised to communicate to consumers that diverse, rather than uniform, tastes govern reviews and evaluations of products.

• Physical Therapy Korea
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• v.12 no.3
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• pp.74-83
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• 2005

The purpose of this study was to produce the regression equation from non-exercise $VO_{2max}$ of healthy young adults and to develop a maximal oxygen consumption ($VO_{2max}$) regression model. This model was based on heart rate non-exercise predictor variables (rest heart rate, maximal heart rate/rest heart rate), as an extra addition to the general regression which can reflect an individual's inherent or acquired cardiorespiratory fitness. The subjects were 101 healthy young adults aged 19 to 35 years. Exercise testing was measured by using a Balke protocol for treadmill and indirect calorimetry. The prediction equation was analyzed by using stepwise multiple regression procedures. The mean of $VO_{2max}$ was $39.02{\pm}6.72\;m{\ell}/kg/min$ (mean${\pm}$SD). The greatest variable correlated to $VO_{2max}$ was %fat. The predictor variable used in the non-exercise $VO_{2max}$ included %fat, gender, habitual physical activity and $HR_{max}/HR_{rest}$. The non-exercise $VO_{2max}$ estimation was as follows: $VO_{2max}$($m{\ell}/kg/min$)=55.58-.41(%fat)+.59(physical activity rating)-2.69($HR_{max}/HR_{rest}$)-5.36 (male=0, female=1); (R=.85, SEE=3.64, R2=.72: including heart rate variable); $VO_{2max}$($m{\ell}/kg/min$)=48.47-.41(%fat)+.45(physical activity rating)-5.12 (male=0, female=1); (R=.84, SEE=3.74, R2=.70: with the exception of heart rate variable). As an added heart rate variable, there was only a 2% coefficient of determination improved. Therefore, these results demonstrated that heart rate variable correlation with a non-exercise regression model was very low. In conclusion, for healthy young korean adults, those variables that can affect non-exercise $VO_{2max}$ estimation turned out to be only % fat, gender, and physical activity. We suggest that further research of predictor variables for non-exercise $VO_{2max}$ is necessary for different patient groups who cannot perform maximal exercise or submaximal exercise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5578-5586
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• 2012

The accurate estimation of discharge is very essential as the important factor of river design for the utilization and flood control, hydraulic construction design. The present discharge production is using the stage-discharge relationship curve in the river. The rating curve uses the method by predicting the discharge based on regression analysis using the measured stage and discharge data in a flood season. The method is comparatively convenient and has especially advantages in that it can predict the discharge having the difficulty of observation in a flood season. However, this method has basically room for improvement because the method only uses the relationship between stage and discharge, and doesn't reflect the hydraulic parameters such as hydraulic radius, energy slope, roughness, topography, etc.. Therefore, in this study, discharge was predicted using the convenient calculation method with empirical parameters of the Manning and Chezy equations, which were proposed by Choo et at (2011) in KSCE as a new methodology for estimating discharge in open channel. The proposed method can conveniently estimate empirical parameters in both of Manning and Chezy equations and the discharge is estimated in the open channels. There are proved by using data measured in meandering lab. channel and India canal and the accuracies show about determination coefficient 0.8. Accordingly, this method will be used in actual field if this study is continuously conducted.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.295-303
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• 2016

The purposes of this study are to describe the process for the instrument construction and the development of scales on rating college students' adaptability and to analyze the technical qualities of the test. The primary goal of this study is to inform students and institutions what is needed to college student's adjustment process into university and college life. The scales are tested by specialty group and statistical methods, and finally composed of 142 items, which measures 8 scales, the academic integration, the social integration into college, career identity, emotional stability, learning condition's stability, relationship with professors, satisfaction degree of educational service, satisfaction degree of college education. This study analyzed 1,959 students' responses from 4 colleges and universities. This study confirms that the scales which this study developed show high concurrent evidence with the college student's adaptability inventory for Korean university and college students based on various development process, specially rapid great change of college. The result of factor analysis shows the evidence based on internal structures of the scales. The Cronbach's ${\alpha}$ of the subscales is .965, from 742 to .937. The prediction model to determine the possibility of dropout by 7 scales is statistically significant in .05, except learning condition's stability. According to CFA Model, RMSEA= .08~.09. dependence factor variance are explained by this study's CFA model. In conclusion, this study confirms that the scales which this study developed are valid and reliable instrument for Korean university and college students to predict their adaptability to college.

• Management & Information Systems Review
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• v.34 no.3
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• pp.161-177
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• 2015

Currently, the influence of the Internet portal sites that can make it quick and easy to contact the vast amount of information is increasing. Users can connect the Internet through a portal to obtain information, such as communication between Internet users, which can be used to meet a variety of purposes. People are exposed to a variety of information from other users in the search for a movie and get information. The impact on the reviews and ratings with the limited number of characters of the film allows users to form a relationship to the movie, decide whether you want to see the movie or find another movie. but, the user can not read the whole movie review. When user see the overall evaluation, the user can receive the correct information. This research conducted a study on the prediction of the rating by the use of review data. Information of reviews, is divided into two main areas: the"fact" and "opinion". "Fact" is to convey the dispassionate information and "Opinion" is, to represent the user's feelings. In this study, we built sentiment dictionary based on the assessment and evaluation of the online review and applied to evaluate other movies. In the comparative study with a simple emotion evaluation technique, we found the suggested algorithm got the more accurate results.

• Journal of the Korean Solar Energy Society
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• v.36 no.3
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• pp.75-85
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• 2016

This research aims to predict and analyze green building certification market of Korean Peninsula after unification. First, it analyzes prospected unification time period, then it forecasts number of new residential and non-residential buildings to be constructed based on estimated number of residences in short at the time in North Korea. There exists a good chance that North Korea's new building market forms similar to that of South Korea, as unification would thoroughly proceed which would result levels of economic culture social politics in quasi-equal state. Thus, assuming the ratio of residential and non-residential building against population is similar in both Korea's, the number against North Korea's house supplied population can be estimated. Based on the expected numbers in North Korea, number of proceeded Building Energy Conservation Plan, Building Energy Rating Certification, and Green Standard for Energy and Environmental Design (G-SEED) are predicted. The research shows certification market related to green building in united Korean Peninsula to be \660 billion over 10 years. Not only certifications to newly built buildings but also including existing buildings, this market is to grow to a considerable extent. As this would largely influence eco-constructive materials, energy plant/equipment, and other relevant markets as well, it would require to make thorough preparations. In sum, to stabilize green building market even before the unification, the research proposes the necessities of appropriate systems in consideration of North Korea, through in-depth discussions and establishment of technology and policy directions in green building sector, such as building energy management and emission reduction technology.

• Journal of Korea Water Resources Association
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• v.50 no.9
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• pp.587-595
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• 2017

Hydraulic characteristics affecting sediment transport capacity due to the weir operations were investigated and developed sediment rating curves for four gaging stations (Nakdong, Gumi, Waegwan, and Jindong) in Nakdong River. Analysis found that the sediment transportaion capability had been decreased and it could be proved from the field measurement records in 2013. Applicabilities of nine sediment transport prediction techniques, which are imbeded in GUIDE program, were examined and adopted for the four gaging stations. Analysis of sediment balance for Nakdong River, including 9 major tributaries, had been carried out with pseudo 2-D numerical model and found that: 1) sedimentation phenomena will be prevailed along the Nakdong River. 2) Engelund-Hansen technique shows the least error in estimation of sediment balance. 3) Engelund-Hansen technique most appropriately describes the sediment characteristics for four gaging stations. 4) Estimated error from the sediment balance for Nakdong River was smaller than the error caused by the estimation of sediment incomming from 9 tributries. Therefore, it is necessary to improve the accuracy of predicting the sediment incomming from the tributaties for better sediment balance analysis.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.121-133
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• 2017

The propose of study is to examine the characteristics of companies with high possibility to form an internal control weakness using forecasting model. This study use the actual listed/unlisted companies' data from K_financial institution. The first conclusion is that discriminant model is more valid than logit model to predict internal control weak companies. A discriminant model for predicting the vulnerability of internal control has high classification accuracy and has low the Type II error that is incorrectly classifying vulnerable companies to normal companies. The second conclusion is that the characteristic of weak internal control companies have a low credit rating, low asset soundness assessment, high delinquency rates, lower operating cash flow, high debt ratios, and minus operating profit to the net sales ratio. As not only a case of listed companies but unlisted companies which did not occur in previous studies are extended in this study, research results including the forecasting model can be used as a predictive tool of financial institutions predicting companies with high potential internal control weakness to prevent asset losses.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Journal of Hospice and Palliative Care
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• v.14 no.4
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• pp.197-203
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• 2011

Purpose: Pain is the most common and influential symptom in cancer patients. Few studies concerning pain intensity in the terminally ill cancer patients have been done. This study aimed to identify factors related with more than moderate pain. Methods: This study used secondary data of 162 terminal cancer inpatients at the palliative ward of six training hospitals in Korea. Physician-assessed pain assessment was by 10 point numeric rating scale. Substantial pain was defined more than moderate intensity by the Korean National Guideline for cancer pain. The Korean version of the MD Anderson Symptom Inventory was self-administered to assess symptoms. Survival prediction was estimated by the attending physicians at the time of admission. Results: Less than six weeks of predicted survival and more than numeric rating of six for worst drowsiness in the previous 24 h were significantly related to substantial pain (P=0.012 and P=0.046, respectively). The dose of opioid analgesics was positively related to substantial pain (P=0.004). Conclusion: Factors positively related to substantial pain were less than six weeks of predicted survival and considerable drowsiness. Careful monitoring and active preparation for pain are required in terminal cancer patients having those factors.