Search results for "Online review"

showing 5 items of 5 documents

Mining customer requirements from online reviews: A product improvement perspective

2016

We propose a filtering model to predict helpfulness of reviews for product design.We provide a way to use the KANO model based on online reviews.We explore how to obtain insights from Big Data through knowledge-based view. Big data commerce has become an e-commerce trend. Learning how to extract valuable and real time insights from big data to drive smarter and more profitable business decisions is a main task of big data commerce. Using online reviews as an example, manufacturers have come to value how to select helpful online reviews and what can be learned from online reviews for new product development. In this research, we first proposed an automatic filtering model to predict the help…

Big data commerceEngineeringINF/01 - Computer ScienceInformation Systems and ManagementBig data02 engineering and technologyOnline reviewManagement Information SystemsKANO0502 economics and business0202 electrical engineering electronic engineering information engineeringProduct (category theory)Robustness (economics)Product designbusiness.industry05 social sciencesSettore IUS/10 - Diritto AmministrativoData scienceConjoint analysisProduct designConjoint analysiKano modelHelpfulnessNew product development050211 marketing020201 artificial intelligence & image processingbusinessInformation Systems
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Insights into online reviews of hotel service attributes: A cross-national study of selected countries in Africa

2018

Online travel reviews are paramount to trip planning because they help consumers’ form images of destinations. Despite ample studies on hotel service attributes, knowledge is scarce regarding culturally nuanced attributes, including security perceptions. This study examines consumers’ perceptions of service attributes and security/safety concerns of hotels in Africa. Data were extracted from three hotel categories (3, 4, and 5-stars), which were based on TripAdvisor rankings from Egypt, Ghana, Kenya, Nigeria, and South Africa. A hybrid analysis revealed that hotel service attributes and security/safety are cardinal evaluation criteria for visitors to Africa. Additionally, our study reveals …

Service (business)Online reviewsTripAdvisor05 social sciencesService attributesDestinationsRevisit0502 economics and businessSecurity050211 marketingBusinessMarketingGV050212 sport leisure & tourismTrip planningCross national
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Does social climate influence positive eWOM? A study of heavy-users of online communities.

2018

Abstract This paper provides a deeper understanding of the role of social influences on positive eWOM behaviour (PeWOM) of heavy-users of online communities. Drawing on Social Interaction Utility Framework, Group Marketing and Social Learning Theories, we develop and test a research model integrating the interactions between the social climate of a website and Interpersonal Influences in PeWOM. 262 Spanish heavy-users of online communities were selected and the data analysed using partial least squares equation modelling. Overall, the model explains 59% of the variance of PeWOM on online communities. Findings reveal that interaction with other members of the online community (Social Presenc…

Word of mouthOnline reviewsInterpersonal influence05 social sciencesInterpersonal InfluenceGeneral MedicineInterpersonal communicationlcsh:BusinessModerationOnline communitySocial relationSocial Identityddc:6500502 economics and business050211 marketinglcsh:HF5001-6182Social PresencePsychologySocial identity theorySocial learning theorySocial psychology050203 business & managementSocial influenceBRQ Business Research Quarterly
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Negative online reviews and webcare strategies in social media: effects on hotel attitude and booking intentions

2018

The purpose of this research is to examine the effects of different webcare strategies (defensive, accommodative, no action) across two different types of social media (TripAdvisor and Twitter) on hotel attitude and booking intentions. The results of an experimental design show that negative electronic word-of-mouth (NWOM) has a negative effect on attitudes and booking intention. Moreover, the benefits derived from the type of response vary depending on the social media type in which NWOM appears. The findings also suggest that no response is worse than either defensive or accommodative responses.

business.industryOnline reviewsBooking intention05 social sciencesGeography Planning and DevelopmentAdvertisingHotel industryBrand attitudeHospitality industrySocial mediaComercialización e Investigación de MercadosAction (philosophy)Negative word-of-mouthTourism Leisure and Hospitality Management0502 economics and business050211 marketingSocial mediaBusiness050212 sport leisure & tourismHotel industryConsumer behaviour
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Mining Customer Requirement from Helpful Online Reviews

2014

Today there are a huge quantity of online reviews available across different categories of products. The key question is how to select helpful online reviews and what can we learn from the abundant reviews. In this paper, we first conclude five categories of features to predict reviews' helpfulness from the perspective of a product designer and then present an approach based on conjoint analysis to measure customer requirement. The suggested approach are demonstrated using product data from a popular Chinese mobile phone market.

helpfulneEngineeringMeasure (data warehouse)Product designbusiness.industryPerspective (graphical)product designData scienceOnline reviewConjoint analysisKano modelMobile phoneHelpfulnessbrandKey (cryptography)Kano modelMarketingbusinessconjoint analysi2014 Enterprise Systems Conference
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