• 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.

• Environmental and Resource Economics Review
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• v.21 no.4
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• pp.921-945
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• 2012

Conditional Logit (CL) model is widely used since its model estimation and interpretation of results of the model is relatively easy, on the other hand, it has the limit of preference heterogeneity of respondents being not fully considered. In this study we used the two models, Mixed Logit (ML) Model and Latent Class Model (LCM) to explain preference heterogeneity of respondents for protection for Boryeong Dam wetland. As a result of the examination for heterogeneity in Boryeong city and six metropolitan areas, we found there was significant difference between two regions. While there was explicit preference heterogeneity within respondents in Boryeong city, we found little heterogeneity within respondents in six metropolitan areas. Thus in the case of six metropolitan areas, CL model can be used for parameter estimation while in the case of Boryeong city, WTP estimates are based on parameter estimates from ML model to reflect the heterogeneity within respondents. Additionally, ML model with interaction and 2-class LCM for respondents in Boryeong city were used to explain the sources of the heterogeneity. The ML model with interaction has advantage of explaining individual unobserved heterogeneity. However The comarison between these two models reflects the fact that LCM provided added information that was not conveyed in the ML model with interaction. Thus, Preference heterogeneity within respondents in this study may be better explained by class level through LCM rather than indiviual level through ML model.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.83-92
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• 2002

Freight mode choice models are essential to the analysis of many areas of transport research. However, observations of actual market choices have only been made in a limited number of situations. Therefore, stated preference(SP) techniques have emerged as an alternative source of actual market choices to be used for estimating freight mode choice models. Considerable confidence exists about SP data, but little consideration has been given to the potential for estimation bias. This paper has been motivated by the theoretical side of estimating SP discrete choice models, focusing on a case study of freight mode choice. Recently developed simulation methods are used to construct inherent random heterogeneity legit models, which consider individual heterogeneity, its inheritance to the next choices and overcome the independence from irrelevant alternatives (IIA) property. This Paper contributes to the development of models dealing with heterogeneity and its inheritance, and sheds light on the heterogeneity of freight transport.

• The Journal of Industrial Distribution & Business
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• v.12 no.8
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• pp.33-39
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• 2021

Purpose: The influence of age on time preference is not identified in the usual cross-sectional analysis. This study aims to test whether age affects time preference after controlling for the effects of individual heterogeneity including cohort effects. Research design, data and methodology: Drawing on a nationally representative panel dataset of Indonesians, we estimate the effects of age on time preference after controlling for unobserved individual heterogeneity as well as potential cohort effects. We measure time preference exploiting information on two sets of multiple price lists: one for a one-year delay, and the other for a five-year delay. Results: When we controlled for time-invariant individual characteristics, including birth cohort effects in a fixed effects model, the older men and women were more patient in a linear fashion, particularly when the delay was longer. To highlight the importance of controlling for individual fixed effects, we repeated the specification without controlling for individual fixed effects in OLS or censored maximum likelihood regression; we found no relation between age and impatience in men or women and for a one or five-year delay. Conclusions: The older men and women are more patient, and time preferences are correlated with unobserved individual heterogeneity.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.695-723
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• 2018

Recently, extreme weather due to climate change has become more frequent, and increase of fine dust has worsen air quality in Korea. Therefore, not only negative perception on coal-fired power generation is dominant, but also the social acceptance of nuclear power generation declines. This study aims at deriving consumer preferences on the mid and long term power mix with various energy sources. Willingness to pay for each generation source was estimated and the preference heterogeneity of consumers was examined by using mixed logit and latent class models. Mixed logit estimation results show that the preference heterogeneity of consumers is especially large for the nuclear power relative to renewable or coal energy. According to the estimation results from the latent class model, group 1 prefers renewable energy while group 2 prefers coal energy. Group 3 shows lexicographic preference which means restricted rationality. As for the policy implication, it is necessary to understand the preference heterogeneity of consumer groups in planning the mid to long term power mix.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.357-366
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• 2013

This study investigates to explain preference heterogeneity of respondents for economic valuation in washland of Upo wetland using Mixed Logit Model and Latent Class Model. Mixed Logit Model showed respondent heterogeneity in the attributes of wetland area and funds as well as some alternatives violated IIA assumption. 2-class Latent Class Model for respondents were used to explain the sources of the heterogeneity. Class 1 respondents who are located relatively close to Upo wetland had more experience and knowledge of Upo wetland and better understood the information suggested in the questionnaire than class 2 respondents in mostly metropolitan area of Seoul, Incheon.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.667-677
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• 2013

The introduction of a new transit facility affects mode share of travel alternatives. The multinomial logit model, which has been the most commonly used for estimating mode share, has difficulty in reflecting heterogeneity of travelers' choices, and it has a limitation on grasping their characteristics of mode choice. The limitation may lead to over- or under-estimation of the new transit facility and bring about significant social costs. This paper aims to find a methodology to overcome the problem of preference homogeneity. It also applies market segmentation structure of separating the whole population into direct and indirect beneficiary to consider their preference heterogeneity. A mode choice model is estimated on data from Jeju Province and statistically tested. The results show that mode transfer rate of direct beneficiaries that inhabit in downtown areas increases as the new transit facility provides more advanced services with higher costs. The results and the model suggested in this study can contribute to improving the accuracy of demand forecasting of new transit facilities by reflecting heterogeneity of mode-transfer patterns.

• Environmental and Resource Economics Review
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• v.16 no.3
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• pp.701-721
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• 2007

A key issue in the development and application of stated preference nonmarket valuation is the incorporation of unobserved heterogeneity in utility models. Two approaches to this task have dominated. The first is to include individual-specific characteristics into the estimated indirect utility functions. These characteristics are usually socioeconomic or demographic variables. The second employs generalized models such as random parameter logit or probit models to allow model parameters to vary across individuals. This paper examines a third approach: the inclusion of psychological or 'latent' variables such as general attitudes and behaviour-specific attitudes to account for heterogeneity in models of stated preferences. Attitudinal indicators are used as explanatory variables and as segmentation criteria in a choice modelling application. Results show that both the model significance and parameter estimates are influenced by the inclusion of the latent variables, and that attitudinal variables are significant factors for WTP estimates.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1389-1395
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• 2018

Hybrid is explained based on the logic of combination such as cross, melding, permeation, fusion, convergence etc. Such combination shows that it is more creative and effective in case of heterogeneity as compared to homogeneity and the same kind, and hybrid character has its meaning as a mean to produce a new creative image. In the context, this study aims to analyze influencing relationship through a practical analysis on how formative requirements for hybrid characters affects consumer preference. For the foregoing, this study conducted multiple regression analysis having familiarity, originality, meaningfulness, diversity as independent variables for formative requirements for characters, and consumer preference as a dependent variable. Analysis results show that familiarity, originality, diversity have a positive effect on consumers, whereas, meaningfulness has no significant impact on the consumer preference.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.129-148
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• 2007

Frailty estimates from the proportional hazards frailty model often lead us to conjecture the heterogeneity in frailty such that the variance of the frailty varies over different covariate groups (e.g. male group versus female group). For such systematic heterogeneity in frailty, we consider a regression model for the variance components in the proportional hazards frailty model, denoted by the MLFM. However, in many cases, the observed data do not show any statistically significant preference between the homogeneous frailty model and the heterogeneous frailty model. In this paper, we propose a Bayesian model averaging procedure with the reversible jump Markov chain Monte Carlo which selects the appropriate model automatically. The resulting regression coefficient estimate ignores the model uncertainty from the frailty distribution in view of Bayesian model averaging (Hoeting et al., 1999). Finally, the proposed model and the estimation procedure are illustrated through the analysis of the kidney infection data in McGilchrist and Aisbett (1991) and a simulation study is implemented.