• 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.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.19-36
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• 2020

The bidding phase for logistics outsourcing services is critical for both shippers and logistics companies. According to the logistics bidding phase, the shipper should provide logistics operation information to logistics companies to resolve uncertainty. In addition, the logistics company can win the contract volume that was placed in the bid by expressing their experience and know-how, and proposing to share the risks and benefits of the shipper's logistics operation. Therefore, it is necessary to examine the factors that can be identified during the bidding phase for logistics outsourcing and how these factors affect the satisfaction of logistics outsourcing services. Based on the factors identified in the preceding studies on logistics outsourcing partnership factors and those on logistics outsourcing determinants, a survey was conducted on experts engaged in logistics companies, performing logistics for domestic shippers and analyzed using Smart-PLS. This study presents the following implications. First, in the logistics bidding phase, the shipper should provide its logistics operation information to logistics firms to resolve uncertainties. Details An in-depth explanation of the operation details will be presented via the bidding presentation, and on-site tours of manufacturing plants and logistics centers should also be carried out if necessary. Second, in the bidding phase, logistics companies should appeal through proposals to their competitiveness, such as experience and knowledge of the logistics of the shipper, and also consider alliances with other logistics companies to supplement their insufficient logistics services. Third, logistics companies should make proposals to share profits and risks through logistics outsourcing during the bidding phase, propose accepting risks from environmental uncertainties of the shipper within its capacity to an acceptable extent, and share the benefits of carrying out the shipper's logistics.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.155-159
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• 2004

Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.2
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• pp.275-281
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• 2018

It is known that he pollutant emitted from the combustion process of marine fuel oil causes air pollution and harmful effects to the human body. Accordingly, IMO regulates pollutants emitted from ships. However, the regulation of Particulate Matter (PM) is still in the process of debate, so preemptive action is needed. Fundamental research on PM is essential. In this study, the Dimensionless Light Extinction Constant ($K_e$) of fuel oil used in marine diesel engines was measured and analyzed to construct the basic data of the PM generated from marine-based fuel oil. The fuel oil used in the land diesel engine was measured in the same way for character comparison. Both fuel oils differ in sulfur content and density. The $K_e$ was measured via the optical method using a 633 nm laser and was determined by using the volume fraction of PM collected by the gravimetric filter method. The $K_e$ of the PM discharged from marine fuel oil is 8.28, and the land fuel oil is 8.44. The $K_e$ of two fuel oils was similar within the measurement uncertainty range. However, it was found by comparison with the value obtained by the Rayleigh-Limit solution that the light scattering portion could be large. Also, it was found that light extinction characteristics could be different due to the relationship between light transmittance and collected mass.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.419-429
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• 2023

The objective of this study was to determine the management water level of an estuary reservoir considering three aspects: the water use, flood control and water quality, and to use a robust decision-making to consider uncertainty due to climate change. The watershed-reservoir linkage model was used to simulate changes in inflow due to climate change, and changes in reservoir water level and water quality. Five management level alternatives ranging from -1.7 El.m to 0.2 El.m were evaluated under the SSP1, 2, 3, and 5 scenariosof the ACCESS-CM2 Global Climate Model. Performance indicators based on period-reliability were calculated for robust decision-making considering the three aspects, and regret was used as a decision indicator to identify the alternatives with the minimum maximum regret. Flood control failure increased as the management level increased, while the probability of water use failure increased as the management level decreased. The highest number of failures occurred under the SSP5 scenario. In the water quality sector, the change in water quality was relatively small with an increase in the management level due to the increase in reservoir volume. Conversely, a decrease in the management level resulted in a more significant change in water quality. In the study area, the estuary reservoir was found to be problematic when the change in water quality was small, resulting in more failures.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.23-35
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• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.