
handle: 10630/28771
Customers strongly base their e-commerce decisions on the opinions of others by checking reviews and ratings provided by other users. These assessments are overall opinions about the product or service, and it is not possible to establish why they perceive it as good or bad. To understand this “why”, it is necessary an expert’s analysis concerning the relevant factors of the product or service. Frequently, these two visions are not coincident and the best product for experts may not be the best one for users. For this reason, trustworthy decision-making methods that integrate the mentioned views are highly desirable. This article proposes a multi-criteria decision analysis model based on the integration of users’ preferences and experts’ opinions. It combines the majority’s opinion and criteria synergy to provide a unified perspective in order to support consumers’ ranking-based decisions in social media environments. At the same time, the model supplies useful information for managers about strengths and weaknesses of their product or service according to users’ experience and experts’ judgment. The aggregation processes and synergy criteria are modeled in order to obtain an adequate consensus mechanism. Finally, in order to test the proposed model, several simulations using hotel valuations are performed.
Project UTN4058 of National Technological University (Argentine) Fellowship for Short Term Postdoctoral Stays at University of Malaga – International Campus of Excellence Andalucía Tech
Social media, Criteria coalition synergy, 330, Multi-criteria decision analysis, Majority aggregation, Decision making, Toma de decisiones
Social media, Criteria coalition synergy, 330, Multi-criteria decision analysis, Majority aggregation, Decision making, Toma de decisiones
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
