scholarly journals Determinants of online clothing review helpfulness: the roles of review concreteness, variance and valence

2021 ◽  
Vol 72 (06) ◽  
pp. 639-644
Author(s):  
YIBING SHAO ◽  
XIAOFEN JI ◽  
LILIN CAI ◽  
SONIA AKTER
Keyword(s):  
Information Source ◽  
Online Reviews ◽  
Purchasing Decisions ◽  
Essential Information ◽  
Factors Affecting ◽  
Review Helpfulness ◽  
Purchasing Behaviour ◽  
Textual Content ◽  
The Relationship ◽  
Significant Factors

Online reviews have emerged as an essential information source for online clothing purchasing behaviour. It is thus paramount for marketers to understand what makes online clothing review helpful to consumers. This research primarily aims to examine the relationship between review textual content factors and review helpfulness in the context of online clothing purchasing. Experiments on review concreteness (concrete or abstract), review variance (consistent or inconsistent) and review valence (positive or negative), between participants were conducted to explore the interaction effect. The findings suggest that online clothing review concreteness, variance and valence are significant factors affecting review helpfulness. Additionally, this study’s findings show that abstract review, negatively review and inconsistent review has a stronger effect on online clothing review helpfulness than concrete review, positively review and consistent review. The findings will help customers to write better clothing reviews, help retailers to manage their websites intelligently and aid customers in their product purchasing decisions.

Impact of Online Reviews on Purchasing Decisions

2016 ◽  
pp. 278-291
Author(s):  
Dhiraj Jain ◽  
Lovish Bhansali ◽  
K. Sanal Nair
Keyword(s):  
Online Reviews ◽  
Purchasing Decisions ◽  
Electronic Products ◽  
Consumer Reviews ◽  
Online Consumer Reviews ◽  
Online Sales ◽  
Purchasing Behaviour ◽  
The Impact ◽  
Informed Consumer ◽  
The Relationship

Internet has enabled today's consumer to transform himself from passive to an active and an informed consumer who can share his experiences, opinions about product or services with an infinite number of consumers around the globe. These reviews or opinions are further used by potential buyers of that particular product or service via electronic Word of Mouth (e-WOM). The study on the impact of e-WOM on online sales has gradually emerged but a number of questions still remain unanswered. The aim of this study is to assess the impact of one type of e-WOM i.e., the online consumer reviews, on purchasing decisions of electronic products. This empirical study also focuses on the relationship between reviews and purchasing behaviour. An instrument was prepared to measure the proposed constructs, with questionnaire items taken from prior studies but adapted to fit the context of e-commerce. The survey was applied to academicians in India through internet. The results show that consumer reviews have a causal impact on consumer purchasing behaviour and they have an effect on choosing the products by consumer. Finally, the results and their implications are discussed.

scholarly journals Fatigue Performance of Thin Laser Butt Welds in HSLA Steel

Metals ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1499
Author(s):  
Patricio G. Riofrío ◽  
Fernando Antunes ◽  
José Ferreira ◽  
António Castanhola Batista ◽  
Carlos Capela
Keyword(s):  
Fatigue Strength ◽  
Fatigue Behavior ◽  
Hsla Steel ◽  
High Strength ◽  
Butt Joints ◽  
Factors Affecting ◽  
Weld Profile ◽  
The Relationship ◽  
Good Agreement ◽  
Significant Factors

This work is focused on understanding the significant factors affecting the fatigue strength of laser-welded butt joints in thin high-strength low-alloy (HSLA) steel. The effects of the weld profile, imperfections, hardness, and residual stresses were considered to explain the results found in the S-N curves of four welded series. The results showed acceptable fatigue strength although the welded series presented multiple-imperfections. The analysis of fatigue behavior at low stress levels through the stress-concentrating effect explained the influence of each factor on the S-N curves of the welded series. The fatigue limits of the welded series predicted through the stress-concentrating effect and by the relationship proposed by Murakami showed good agreement with the experimental results.

scholarly journals Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals

2020 ◽  
pp. 004728752091678 ◽  
Author(s):  
Raffaele Filieri ◽  
Claudio Vitari ◽  
Elisabetta Raguseo
Keyword(s):  
Product Quality ◽  
Online Reviews ◽  
Average Score ◽  
Consumer Review ◽  
Quality Signals ◽  
Review Helpfulness ◽  
Online Consumer Review ◽  
The Relationship ◽  
Moderating Role

Contrasting findings about the role of extremely negative ratings (ENRR) are found in the literature, thus suggesting that not all ENRR are perceived as helpful by consumers. In order to shed light on the most helpful ENRR, we have drawn on negativity bias and signaling theory, and we have analyzed the moderating role of product quality signals in the relationship between ENRR and review helpfulness. The study is based on the analysis of 9,479 online reviews, posted on TripAdvisor.com, pertaining to 220 French hotels. The findings highlight that ENRR is judged as being more helpful when the hotel has been awarded a certificate of excellence, and when the average rating score and the hotel classification are higher. On the basis of these results, we recommend that managers of higher category hotels, with a certificate of excellence and with higher average score ratings, pay more attention to extremely negative judgments.

scholarly journals Users’ Sentiment Analysis of Shopping Websites Based on Online Reviews

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaohong Wang ◽  
Shuang Dong
Keyword(s):  
Sentiment Analysis ◽  
Text Analysis ◽  
Online Shopping ◽  
Rapid Development ◽  
Online Reviews ◽  
Analysis Method ◽  
Purchasing Decisions ◽  
Emotional Words ◽  
Fine Grained ◽  
The Relationship

AbstractWith the rapid development of online shopping, how to explore the value of online reviews, so as to give full play to their role in potential users’ purchasing decisions. Based on text mining and quantitative analysis, this paper studies the sentiment analysis of online reviews on B2C shopping website. The main attributes of commodity or service are extracted based on the order of word frequency in the online reviews. Text analysis method is used to judge the relationship between attributes of commodity or service and its emotional words. The fine-grained sentimental polarity and intensity of attributes are identified to analyze users’ concerns and preferences. The research shows that users pay more attention to the configuration and after-sales service of mobile, and have a positive sentimental orientation to most of attributes, especially unlocking function, hand feeling attribute and logistics service; and have a neutral sentimental orientation towards the attributes of battery and memory, and a negative sentimental orientation towards the membrane of mobile phone. The results can provide a reference for consumers to make purchasing decisions, for enterprises to improve product quality, and for shopping platform to optimize service.

Introduction

2017 ◽  
Author(s):  
Jeremy Gregory
Keyword(s):  
Eighteenth Century ◽  
Anglican Church ◽  
Factors Affecting ◽  
Global Power ◽  
Long Eighteenth Century ◽  
The Relationship ◽  
The Church ◽  
Significant Factors ◽  
Established Church

This introductory chapter discusses the two ‘E-word’ coordinates of the volume—‘Establishment’ and ‘Empire’—which were arguably the most significant factors affecting the Anglican Church between 1662 and 1829 and asks what the consequences were for the Church of its establishment status and how it was affected by being the established Church of an emerging global power. The chapter surveys the historiography and argues that the Church was far more vital to the period than is often maintained. The chapter also explores the relationship between Anglicanism and two other ‘E-words’—‘Enlightenment’ and ‘Evangelicalism’—which have often been seen as critical reactions against the Church. While the themes of ‘Establishment’, ‘Empire’, ‘Enlightenment’, and ‘Evangelicalism’ had separate, and sometimes competing, trajectories, as this volume indicates, Anglicanism during the long eighteenth century could also hold them together in distinctive ways.

The Relationship between Online Reviews, Brand Trust, and Willingness to Buy

2015 ◽  
pp. 139-161 ◽  
Author(s):  
V. Cheng ◽  
J. Rhodes ◽  
P. Lok
Keyword(s):  
Decision Making ◽  
Online Reviews ◽  
Mediating Effect ◽  
Consumer Decision Making ◽  
Brand Trust ◽  
Purchasing Decisions ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Willingness To Buy ◽  
The Relationship

This chapter investigates how online customer reviews affect consumer decision-making (willingness to buy) during their first purchase of services or products using brand trust as a mediating variable. A brief literature review, rationale and significance, and methodology are discussed, and a conceptual framework based on the relationships between the stated variables is adopted in this empirical study to demonstrate linkages and insights. The findings demonstrate that the “reliability dimension” of brand trust had a mediating effect on online customer reviews' valence to willingness to buy, while the “intentionality dimension” of brand trust had little effect. Furthermore, the findings demonstrate that online customer reviews generated by in-group and out-group reviewers have little effect on purchasing decisions (willingness to buy). These results suggest that marketers should focus more on managing negative online customer reviews that have a damaging effect on brand trust.

The moderating effect of movie production efficiency on the relationship between eWOM and review helpfulness

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sangjae Lee ◽  
Joon Yeon Choeh
Keyword(s):  
Production Efficiency ◽  
Nearest Neighbor ◽  
Online Reviews ◽  
Moderating Effect ◽  
K Nearest Neighbor ◽  
Content Type ◽  
Online Word Of Mouth ◽  
Study Results ◽  
Review Helpfulness ◽  
The Relationship

Purpose This paper aims to intend to study the effect of movie production efficiency on eWOM and the moderating effect of efficiency on the relationship between eWOM and review helpfulness for movies. Design/methodology/approach Production efficiency is suggested by comparing the power of movie resources (e.g. the power of actors, directors, distributors, production companies) against box-office revenue through a data envelopment analysis (DEA). Findings The study results present that the number of reviews, the number of reviews by reviewers and review extremity are greater in an efficient subsample than in an inefficient subsample. For efficient movies, the review depth and the strength of the sentiments in the reviews are more positively related to review helpfulness. The prediction results for review helpfulness using the k-nearest neighbor method and automatic neural networks show that the efficient subsample provides a significantly lower prediction error rate than the inefficient subsample. The study results can support the effective facilitation of helpful online movie reviews. Originality/value As the numbers of online reviews are increasingly used to provide purchase decision support, it becomes crucial to understand which attributes represent average helpful reviews for movies. While previous studies have examined eWOM (online word-of-mouth) variables as predictors of helpfulness on movie websites, the role of the production efficiency of movies has not been examined considering the relationship between eWOM and review helpfulness for movies.

scholarly journals Characteristics of PM2.5 and Black Carbon Exposure Among Subway Workers

2019 ◽  
Vol 16 (16) ◽  
pp. 2901 ◽  
Author(s):  
Sangjun Choi ◽  
Ju-Hyun Park ◽  
So-Yeon Kim ◽  
Hyunseok Kwak ◽  
Dongwon Kim ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Black Carbon ◽  
Subway Station ◽  
Mixed Effect ◽  
Factors Affecting ◽  
Average Proportion ◽  
Exposure Levels ◽  
Train Drivers ◽  
The Relationship ◽  
Significant Factors

This study aimed to assess the characteristics of exposure to both PM2.5 and black carbon (BC) among subway workers. A total of 61 subway workers, including 26, 23, and 12 subway station managers, maintenance engineers, and train drivers, respectively, were investigated in 2018. Real-time measurements of airborne PM2.5 and BC were simultaneously conducted around the breathing zones of workers. Maintenance engineers had the highest average levels of exposure to both PM2.5 and BC (PM2.5, 76 µg/m3; BC, 9.3 µg/m3), followed by train drivers (63.2 µg/m3, 5.9 µg/m3) and subway station managers (39.7 µg/m3, 2.2 µg/m3). In terms of the relationship between mass concentrations of PM2.5 and BC, train drivers demonstrated the strongest correlation (R = 0.72), indicating that the proportion of BC contained in PM2.5 is relatively steady. The average proportion of BC in PM2.5 among maintenance engineers (13.0%) was higher than that among train drivers (9.4%) and subway station managers (6.4%). Univariate and mixed effect multiple analyses demonstrated the type of task and worksite to be significant factors affecting exposure levels in maintenance engineers and subway station managers. The use of diesel engine motorcars in tunnel maintenance was found to be a key contributor to PM2.5 and BC exposure levels among subway workers.

Exploring influential factors affecting guest satisfaction

2020 ◽  
Vol 11 (1) ◽  
pp. 137-153 ◽  
Author(s):  
Minwoo Lee ◽  
Yanjun (Maggie) Cai ◽  
Agnes DeFranco ◽  
Jongseo Lee
Keyword(s):  
Social Media ◽  
Big Data ◽  
Online Reviews ◽  
Influential Factors ◽  
Business Analytics ◽  
Content Type ◽  
Factors Affecting ◽  
Starting Point ◽  
Guest Satisfaction ◽  
Significant Factors

Purpose Electronic word of mouth in the form of user-generated content (UGC) in social media plays an important role in influencing customer decision-making and enhancing service providers’ brand images, sales and service innovations. While few research studies have explored real content generated by hotel guests in social media, business analytics techniques are still not widely seen in the literature and how such techniques can be deployed to benefit hoteliers has not been fully explored. Thus, this study aims to explore the significant factors that affect hotel guest satisfaction via UGC and business analytics and also to showcase the use of business analytics tools for both the hospitality industry and the academic world. Design/methodology/approach This study uses big data and business analytics techniques. Big data and business analytics enable hoteliers to develop effective and efficient strategies improving products and services for guest satisfaction. Therefore, this study analyzes 200,431 hotel reviews on Tripadvisor.com through business analytics to explore and assess the significant factors affecting guest satisfaction. Findings The findings show that service, room and value evaluations are the top-three factors affecting overall guests’ satisfaction. While brand type and negative emotions are negatively associated with guests’ satisfaction, all other factors considered were positively associated with guests’ satisfaction. Originality/value The current study serves as a great starting point to further explore the relationship between specific evaluation factors and guests’ overall satisfaction by analyzing user-generated online reviews through business analytics so as to assist hoteliers to resolve performance-related problems by analyzing service gaps that exist in these influential factors.

Design Preference Centered Review Recommendation: A Similarity Learning Approach

2011 ◽  
Author(s):  
Jian Jin ◽  
Ying Liu ◽  
Ping Ji ◽  
Richard Fung
Keyword(s):  
Classification Problem ◽  
Online Reviews ◽  
Learning Approach ◽  
Similarity Learning ◽  
Customer Reviews ◽  
Customer Preferences ◽  
Review Helpfulness ◽  
Review Recommendation ◽  
Design Preference ◽  
The Relationship

The rise of e-commerce websites like Amazon and Alibaba is changing the way how designers seek information to identify customer preferences in product design. From the feedbacks posted by consumers, either positive or negative, product designers can monitor the trend of consumers’ perception with respect to their product offerings and make efforts to improve accordingly. Starting from feature extraction from review documents, existing methods in identifying helpful online reviews regard the helpfulness prediction problem as a regression or classification problem and have not considered the relationship between customer reviews. Also, these approaches only consider the online helpfulness voting ratio or a unified helpfulness rating as the gold criteria for helpfulness evaluation and neglect various personal preferences from product designers. Therefore, in this paper, the focus is on how to predict reviews’ helpfulness by taking into account the personal preferences from both reviewers and designers. We start to analyze review helpfulness from both a generic aspect and a personal preference aspect. Classification methods and the proposed review similarity learning approach are utilized to estimate from the generic angle of helpfulness, while nearest neighbourhood based methods are adopted to reflect concerns from personal perspectives. Finally, a regression algorithm is called upon to predict review helpfulness based on the inputs from both aspects. Our experimental study, using a large quantity of review data crawled from Amazon and real ratings from product designers demonstrates the effectiveness of our approach and it opens a possibility for customized helpful review routing.

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