Start Day Trial Product recommendations are a must-have feature for all ecommerce websites, as they can drive sales, increase conversion rate and order value.
The growing popularity of online product review forums invites the development of models and metrics that allow firms to harness these new sources of information for decision support.
Our work contributes in this direction by proposing a novel family of diffusion models that capture some of the uniq Our work contributes in this direction by proposing a novel family of diffusion models that capture some of the unique aspects of the entertainment industry and testing their performance in the context of very early post-release motion picture revenue forecasting.
We show that the addition of online product review metrics to a benchmark model that includes pre-release marketing, theater availability and professional critic reviews substantially increases its forecasting accuracy; the forecasting accuracy of our best model outperforms that of several previously published models.
In addition to its contributions in diffusion theory our study reconciles some inconsistencies among previous studies with respect to what online review metrics are statistically significant in forecasting entertainment good sales. Furthermore, it demonstrates the value of online product review metrics for purposes other than assessing consumer sentiment about a product.
Show Context Citation Context This paper contributes to a better understanding of how such metrics can add value Electronic word-of-mouth in hospitality and tourism management by Stephen W.
Goldsmith, Bing Pan - Tourism Management" Interpersonal influence and word-of-mouth WOM are ranked the most important information source when a consumer is making a purchase decision. This influence may be especially important in the hospitality and tourism industry, whose intangible products are difficult to evaluate prior to their consu This influence may be especially important in the hospitality and tourism industry, whose intangible products are difficult to evaluate prior to their consumption.
When WOM becomes digital, the large-scale, anonymous, ephemeral nature of the Internet induces new ways of capturing, analyzing, interpreting, and managing online WOM. This paper describes online interpersonal influence, or eWOM, as a potentially cost-effective means for marketing hospitality and tourism, and discusses some of the nascent technological and ethical issues facing marketers as they seek to harness emerging eWOM technologies.
Impact of Online Consumer Reviews on Sales: This article examines how product and consumer characteristics moderate the influence of online consumer reviews on product sales using data from the video game industry.
The findings indicate that online reviews are more influential for less popular games and games whose players have greater Intern The findings indicate that online reviews are more influential for less popular games and games whose players have greater Internet experience.
The authors discuss the implications of these results in light of the increased share of niche products in recent years.
Abstract — This paper presents a concept that enables consumers to access and share product recommendations using their mobile phone. Based on a review of current product recommendation mechanisms it devises a concept called APriori.
APriori leverages the potential of auto-ID-enabled mobile phones Since mobile users cannot be expected to have the patience and time to compose text-based reviews on mobile phones, we introduce a new rating concept that allows users to generate new rating criteria.
The concept is tailored to the limited attention and input options of mobile users in real-world environment. This work describes the architecture, implementation, and evaluation of APriori. For an evaluation we have taken the approach of interviewing 26 users in the frames of a formative user study, with the goal to further improve the system for an application in the real world.
In addition, the paper discusses open issues regarding community-based product recommendations on mobile phones and proposes solutions. These concepts also have been researched. The availability of handsets with Internet capabilities empowers people for the first time to generate content and share experiences with products independent of computers fixed to specific location Proceedings of the 13th international conference on Intelligent user interfaces" Written opinion on products and other entities can be important to consumers and researchers, but expensive and difficult to analyze.consumers’ product choices.
Therefore, the main objective of this study is to investigate the inﬂuence of online product recommendations on consumers’ online product choices. In addition, we explore the moderating inﬂuence of variables related to recommendation sources and the purchase decision. Open Influence is a global influencer marketing solution focused on generating value for brands across all the major social media platforms.
Dec 28, · If you’ve ever bought anything online, you’ve encountered a typical online review. You might have found an aggregated “star” rating for a product you wanted to buy, or a poorly-spelled.
BrightLocal's Local Consumer Review Survey explores how customers use online consumer reviews when choosing which businesses to visit and buy from. Find out the impact of online reviews, the latest on fake reviews, and why you should tackle negative reviews in our report.
Journal of Retailing 80 () – The inﬂuence of online product recommendations on consumers’ online choices Sylvain Senecala,∗, Jacques Nantela,1 a HEC Montreal, University of Montreal, Chemin de la Cote-Sainte-Catherine, Montreal, Que., Canada H3T 2A7 Abstract. A recommender system or a recommendation system (sometimes replacing "system" with a synonym such as platform or engine) is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item..
Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and.