The Effect of Online Q&As and Product Reviews on Product Performance Metrics: Amazon.com as a Case Study

2021 ◽  
Vol 20 (01) ◽  
pp. 2150005
Author(s):  
Reza Mousavi ◽  
Bidyut Hazarika ◽  
Kuanchin Chen ◽  
Muhammad Razi
Keyword(s):  
Performance Metrics ◽  
Online Reviews ◽  
Review Literature ◽  
Product Performance ◽  
Product Reviews ◽  
Product Sale ◽  
Comparison Shopping ◽  
Questions And Answers ◽  
Review Helpfulness

Online reviews have received an overwhelming interest in the recent decades. Comparatively speaking, the online product questions and answers (Q&As) have received less attention than online reviews, despite that they both affect the image and the value of a project. Although online reviews and Q&As are both forms of user generated knowledge ion online communities, they may affect customers decision making differently. Furthermore, Q&As are very useful for pre-purchase information-searching and comparison shopping, especially when online product reviews either do not provide the needed answer or getting the desired information requires additional “cost” (i.e. time and effort) to sort out. Our findings show that Q&A traits had a varying effect on the product performance. We also found that review helpfulness is another important factor that affects product sale and popularity on e-commerce sites. The present study adds to existing electronic word-of-mouth (eWOM) and product review literature.

scholarly journals Exploring Determinants of Attraction and Helpfulness of Online Product Review: A Consumer Behaviour Perspective

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Xu Chen ◽  
Jie Sheng ◽  
Xiaojun Wang ◽  
Jiangshan Deng
Keyword(s):  
Mixed Method ◽  
Consumer Behaviour ◽  
Online Reviews ◽  
Product Reviews ◽  
Implicit Information ◽  
Online Product Review ◽  
Review Helpfulness ◽  
Research Findings ◽  
The Impact ◽  
Method Approach

To assist filtering and sorting massive review messages, this paper attempts to examine the determinants of review attraction and helpfulness. Our analysis divides consumers’ reading process into “notice stage” and “comprehend stage” and considers the impact of “explicit information” and “implicit information” of review attraction and review helpfulness. 633 online product reviews were collected from Amazon China. A mixed-method approach is employed to test the conceptual model proposed for examining the influencing factors of review attraction and helpfulness. The empirical results show that reviews with negative extremity, more words, and higher reviewer rank easily gain more attraction and reviews with negative extremity, higher reviewer rank, mixed subjective property, and mixed sentiment seem to be more helpful. The research findings provide some important insights, which will help online businesses to encourage consumers to write good quality reviews and take more active actions to maximise the value of online reviews.

scholarly journals Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach

2022 ◽  
Vol 3 (4) ◽  
pp. 283-294
Author(s):  
M. Duraipandian ◽  
R. Vinothkanna
Keyword(s):  
Opinion Mining ◽  
Online Reviews ◽  
Classification Model ◽  
Product Reviews ◽  
Consumer Evaluations ◽  
Proposed Model ◽  
Svm Model ◽  
Review Helpfulness ◽  
Hybrid Classification ◽  
Corporate Trust

Customers post online product reviews based on their own experience. They may share their thoughts and comments on items on online shopping websites. The sentiment analysis comprises of opinion or idea process and process of sorting high rating reviews according to how well the product satisfies. Opinion mining is a technique for extracting useful data from large amounts of texts in order to use those to enhance or expand a company's operations. According to consumer evaluations, many of the goods aren't as good as they seem. It's common that buyers submit their thoughts on a product but then forget to rate it. The prior data preprocessing is more efficient to extract the features by CNN approach. This proposed methodology breaks down each user's rating prediction model into two parts: one based on the review text and other based on the user rating matrix with the help of CNN feature engineering. The goal of this study is to classify all reviews into ratings by SVM model. This proposed classification model provides good accuracy to predict the online reviews efficiently. For reviews without ratings, a further prediction of feelings is generated using multiple classifiers. The benefits of this proposed model are honed using helpfulness ratings from a small number of evaluations such as accuracy, F1 score, sensitivity, and precision. According to studies using the standard benchmark dataset, the accuracy of customized recommendation services, user happiness, and corporate trust may all be enhanced by including review helpfulness information in the recommender system.

Let Photos Speak: The Effect of User-Generated Visual Content on Hotel Review Helpfulness

2021 ◽  
pp. 109634802110191
Author(s):  
Chunhong Li ◽  
Linchi Kwok ◽  
Karen L. Xie ◽  
Jianwei Liu ◽  
Qiang Ye
Keyword(s):  
Methodological Approach ◽  
Online Reviews ◽  
Review Literature ◽  
Media Richness Theory ◽  
Positive Effects ◽  
Review Helpfulness ◽  
Econometric Analyses ◽  
Hotel Managers ◽  
Processing Techniques ◽  
Textual Content

A picture is worth a thousand words. User-generated photos (UGPs) are increasingly accompanying online reviews of hotels. This article draws on media richness theory to estimate the effects of UGPs on hotel reviews’ helpfulness. Based on a sample of 1,159,590 valid reviews with 464,316 photos, we utilized an integrated analytical model incorporating both econometric analyses and image-processing techniques. The results show that reviews accompanied by UGPs are generally rated as more helpful than those with textual content only. Furthermore, photos showing guestroom objects were rated as more helpful than those showing food & beverages. Finally, the positive effects of UGPs on review helpfulness were especially prominent for hotels with lower prices and negative reviews. This study adds new insights to the online review literature and advances the methodological approach in analyzing unstructured user-generated content. This study provides important implications for hotel managers and online booking platforms regarding UGP management.

scholarly journals Cluster Analysis of Online Shop Product Reviews Using K-Means Clustering

2020 ◽  
Vol 3 (02) ◽  
pp. 142-151
Author(s):  
Rena Nainggolan ◽  
Eviyanty Purba
Keyword(s):  
Cluster Analysis ◽  
Design Methodology ◽  
Clustering Algorithm ◽  
Online Reviews ◽  
Product Reviews ◽  
Potential Customers ◽  
Practical Implications

Purpose:This research aims to mine review data on one of the e-commerce sites which ultimately produces clusters using the K-Means Clustering algorithm that can help potential customers to make a decision before deciding to buy a product or service. Design/methodology/approach: By using Octoparse we mine opinion or comment data in the form of customer online reviews, after getting the data we group the data using the k-emans clustering methode to obtain cluster Findings: Cluster Analysys can can help potential customers to make a decision before deciding to buy a product or service Research limitations/implications: WWW.Lazada.Com Practical implications: State your implication here. Originality/value: Paper type: This paper can be categorized as case study paper      

Can two-sided messages increase the helpfulness of online reviews?

2016 ◽  
Vol 40 (3) ◽  
pp. 316-332 ◽  
Author(s):  
Ming-Yi Chen
Keyword(s):  
Past Research ◽  
Online Reviews ◽  
Review Literature ◽  
Product Type ◽  
Online Review ◽  
Dual Processing ◽  
Content Type ◽  
Wide Range ◽  
Review Helpfulness ◽  
Message Sidedness

Purpose – Online reviews are increasingly available for a wide range of products and services. Several studies have demonstrated the benefits of the presence of customer reviews to an online retailer, but the issue of what makes online reviews helpful to a consumer in the process of making a purchase decision remains uninvestigated. The paper aims to discuss this issue. Design/methodology/approach – Given the strategic potential of online reviews, this study drew on past research to develop a conceptual understanding of the components of helpfulness and to further empirically test the model using actual online review data from iPeen.com in Taiwan. A content analysis of 989 reviews across four products identified the interplay effects of review sidedness, reviewer’s expertise, and product type on the helpfulness of an online review. Findings – For search goods, consumers consider two-sided reviews to be more helpful than one-sided reviews when the reviewers are experts in writing such articles, whereas they consider two-sided reviews to be equally helpful as one-sided reviews when the reviewers are novices. Conversely, for experience goods, consumers consider one-sided reviews to be more helpful than two-sided reviews when the reviewers are experts in writing review articles, but they consider one-sided reviews to be equally helpful as two-sided reviews when the reviewers are novices. Practical implications – With an understanding of how review sidedness affects online review helpfulness, online retailers could establish the policy for promoting the helpfulness of reviews more effectively. Originality/value – This research yields at least three important contributions: first, it contributes to the message sidedness literature by showing which arguments (one- or two-sided) are deemed to be helpful; second, it contributes to the online peer review literature by demonstrating the importance of considering product type and heuristic cues (i.e. the reviewer’s expertise) when explaining helpfulness; and third, the results in this research demonstrate that people are drawn to dual-processing; that is, the judgment of online review helpfulness is determined by heuristic cues (e.g. the status of the reviewer) and systematic processing (e.g. review content).

scholarly journals The impact of online reviews on e-commerce sales in India: a case study

2021 ◽  
pp. 1-17 ◽  
Author(s):  
Mithun S. Ullal ◽  
Cristi Spulbar ◽  
Iqbal Thonse Hawaldar ◽  
Virgil Popescu ◽  
Ramona Birau
Keyword(s):  
Online Reviews ◽  
The Impact

Failure mode and effect analysis (FMEA) to improve collaborative project-based learning: Case study of a Study and Research Path in mechanical engineering

2021 ◽  
pp. 030641902199904
Author(s):  
Elena Bartolomé ◽  
Paula Benítez
Keyword(s):  
Active Learning ◽  
Failure Mode ◽  
Mechanical Engineering ◽  
Failure Modes ◽  
Collaborative Study ◽  
Project Based Learning ◽  
Educational Process ◽  
Effect Analysis ◽  
Questions And Answers

Failure Mode and Effect Analysis (FMEA) is a powerful quality tool, widely used in industry, for the identification of failure modes, their effects and causes. In this work, we investigated the utility of FMEA in the education field to improve active learning processes. In our case study, the FMEA principles were adapted to assess the risk of failures in a Mechanical Engineering course on “Theory of Machines and Mechanisms” conducted through a project-based, collaborative “Study and Research Path (SRP)” methodology. The SRP is an active learning instruction format which is initiated by a generating question that leads to a sequence of derived questions and answers, and combines moments of study and inquiry. By applying the FMEA, the teaching team was able to identify the most critical failures of the process, and implement corrective actions to improve the SRP in the subsequent year. Thus, our work shows that FMEA represents a simple tool of risk assesment which can serve to identify criticality in educational process, and improve the quality of active learning.

scholarly journals A Case Study of a Negotiated Tender within a Small-to-Medium Construction Contractor: Modelling Project Cost Variance

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 260
Author(s):  
James Ellis ◽  
David John Edwards ◽  
Wellington Didibhuku Thwala ◽  
Obuks Ejohwomu ◽  
Ernest Effah Ameyaw ◽  
...  
Keyword(s):  
Construction Industry ◽  
Study Data ◽  
Review Literature ◽  
Third Party ◽  
Open Book ◽  
Competitive Tendering ◽  
Construction Contractor ◽  
The Uk ◽  
Insight Into

This research explores the failure of competitively tendered projects in the UK construction industry to procure the most suited contractor(s) to conduct the works. Such work may have equal relevance for other developed nations globally. This research seeks to teach clients and their representatives that “lowest price” does not mean “best value”, by presenting a case study of a successfully negotiated tender undertaken by a small-to-medium enterprise (SME) contractor; SME studies are relatively scant in academic literature. By applying the “lessons learnt” principle, this study seeks to improve future practice through the development of a novel alternative procurement option (i.e., negotiation). A mixed philosophical stance combining interpretivism and pragmatism was used—interpretivism to critically review literature in order to form the basis of inductive research to discuss negotiation as a viable procurement route, and pragmatism to analyse perceptions of tendering and procurement. The methods used follow a three-stage waterfall process including: (1) literature review and pilot study; (2) quantitative analysis of case study data; and (3) qualitative data collection via a focus group. Our research underscores the need to advise clients and their representatives of the importance of understanding the scope of works allowed within a tender submission before discounting it based solely on price. In addition, we highlight the failings of competitive tendering, which results in increased costs and project duration once the works commence on site. These findings provide new contemporary insight into procurement and tendering in the construction industry, with emphasis on SME contractors, existing relationships, and open-book negotiation. This research illustrates the adverse effects of early cost estimates produced without first securing a true understanding of project buildability and programming. Our work concludes with a novel insight into an alternative procurement option that involves early SME contractor involvement in an open-book environment, without the need for a third-party cost control.

scholarly journals The Implementation of Visual Comfort Evaluation in the Evidence-Based Design Process Using Lighting Simulation

2021 ◽  
Vol 11 (11) ◽  
pp. 4982
Author(s):  
Anahita Davoodi ◽  
Peter Johansson ◽  
Myriam Aries
Keyword(s):  
Performance Metrics ◽  
Analysis Data ◽  
Evidence Based ◽  
Visual Comfort ◽  
Simulation Tools ◽  
Post Occupancy Evaluation ◽  
Lighting Simulation ◽  
Insight Into

Validation of the EBD-SIM (evidence-based design-simulation) framework, a conceptual framework developed to integrate the use of lighting simulation in the EBD process, suggested that EBD’s post-occupancy evaluation (POE) should be conducted more frequently. A follow-up field study was designed for subjective–objective results implementation in the EBD process using lighting simulation tools. In this real-time case study, the visual comfort of the occupants was evaluated. The visual comfort analysis data were collected via simulations and questionnaires for subjective visual comfort perceptions. The follow-up study, conducted in June, confirmed the results of the original study, conducted in October, but additionally found correlations with annual performance metrics. This study shows that, at least for the variables related to daylight, a POE needs to be conducted at different times of the year to obtain a more comprehensive insight into the users’ perception of the lit environment.

Effect of Manufacturing Variability on Turbine Engine Performance: A Probabilistic Study

2013 ◽  
Author(s):  
Michael Gorelik ◽  
Jacob Obayomi ◽  
Jack Slovisky ◽  
Dan Frias ◽  
Howie Swanson ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Model Development ◽  
Engine Performance ◽  
Performance Model ◽  
Probabilistic Methods ◽  
System Level ◽  
Turbine Engine ◽  
Probabilistic Study ◽  
Blade Geometry

While turbine engine Original Equipment Manufacturers (OEMs) accumulated significant experience in the application of probabilistic methods (PM) and uncertainty quantification (UQ) methods to specific technical disciplines and engine components, experience with system-level PM applications has been limited. To demonstrate the feasibility and benefits of an integrated PM-based system, a numerical case study has been developed around the Honeywell turbine engine application. The case study uses experimental observations of engine performance such as horsepower and fuel flow from a population of engines. Due to manufacturing variability, there are unit-to-unit and supplier-to-supplier variations in compressor blade geometry. Blade inspection data are available for the characterization of these geometric variations, and CFD analysis can be linked to the engine performance model, so that the effect of blade geometry variation on system-level performance characteristics can be quantified. Other elements of the case study included the use of engine performance and blade geometry data to perform Bayesian updating of the model inputs, such as efficiency adders and turbine tip clearances. A probabilistic engine performance model was developed, system-level sensitivity analysis performed, and the predicted distribution of engine performance metrics was calibrated against the observed distributions. This paper describes the model development approach and key simulation results. The benefits of using PM and UQ methods in the system-level framework are discussed. This case study was developed under Defense Advanced Research Projects Agency (DARPA) funding which is gratefully acknowledged.

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