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.

Exploring the determinants of and predicting the helpfulness of online user reviews using decision trees

2017 ◽  
Vol 55 (4) ◽  
pp. 681-700 ◽  
Author(s):  
Sangjae Lee ◽  
Joon Yeon Choeh
Keyword(s):  
Decision Tree ◽  
Nearest Neighbor ◽  
Decision Rules ◽  
Online Reviews ◽  
K Nearest Neighbor ◽  
Product Data ◽  
Content Type ◽  
Logistics Regression ◽  
Review Helpfulness ◽  
High Level

Purpose The purpose of this paper is to suggest important determinants for helpfulness from the reviews’ product data, review characteristics, and textual characteristics, and identify the more crucial factors among these determinants by using statistical methods. Furthermore, this study intends to propose a classification-based review recommender using a decision tree (CRDT) that uses a decision tree to identify and recommend reviews that have a high level of helpfulness. Design/methodology/approach This study used publicly available data from Amazon.com to construct measures of determinants and helpfulness. To examine this, the authors collected data about economic transactions on Amazon.com and analyzed the associated review system. The final sample included 10,000 reviews composed of 4,799 helpful and 5,201 not helpful reviews. Findings The study selected more crucial determinants from a comprehensive group of product, reviewer, and textual characteristics through using a t-test and logistics regression. The five important variables found to be significant in both t-test and logistic regression analysis were the total number of reviews for the product, the reviewer’s history macro, the reviewer’s rank, the disclosure of the reviewer’s name, and the length of the review in words. The decision tree method produced decision rules for determining helpfulness from the value of the product data, review characteristics, and textual characteristics. The prediction accuracy of CRDT was better than that of the k-nearest neighbor (kNN) method and linear multivariate discriminant analysis in terms of prediction error. CRDT can suggest better determinants that have a greater effect on the degree of helpfulness. Practical implications The important factors suggested as affecting review helpfulness should be considered in the design of websites, as online retail sites with more helpful reviews can provide a greater potential value to customers. The results of the study suggest managers and marketers better understand customers’ review and increase the value to customers by proving enhanced diagnosticity to consumers. Originality/value This study is different from previous studies in that it investigated the holistic aspect of determinants, that is, product, review, and textual characteristics for classifying helpful reviews, and selected more crucial determinants from a comprehensive group of product, reviewer, and textual characteristics by using a t-test and logistics regression. This study utilized a decision tree, which has rarely been used in predicting review helpfulness, to provide rules for identifying helpful online reviews.

scholarly journals Using Bayesian Network to Predict Online Review Helpfulness

2020 ◽  
Vol 12 (17) ◽  
pp. 6997
Author(s):  
Sangjae Lee ◽  
Kun Chang Lee ◽  
Joon Yeon Choeh
Keyword(s):  
Bayesian Network ◽  
Nearest Neighbor ◽  
Online Reviews ◽  
Website Design ◽  
K Nearest Neighbor ◽  
Business Decision ◽  
The Neural Network ◽  
Online Word Of Mouth ◽  
Final Sample ◽  
Review Helpfulness

The enormous volume and largely varying quality of available reviews provide a great obstacle to seek out the most helpful reviews. While Naive Bayesian Network (NBN) is one of the matured artificial intelligence approaches for business decision support, the usage of NBN to predict the helpfulness of online reviews is lacking. This study intends to suggest HPNBN (a helpfulness prediction model using NBN), which adopts NBN for helpfulness prediction. This study crawled sample data from Amazon website and 8699 reviews comprise the final sample. Twenty-one predictors represent reviewer and textual traits as well as product traits of the reviews. We investigate how the expanded list of predictors including product, reviewer, and textual characteristics of eWOM (online word-of-mouth) has an effect on helpfulness by suggesting conditional probabilities of the binned determinants. The prediction accuracy of NBN outperformed that of the k-nearest neighbor (kNN) method and the neural network (NN) model. The results of this study can support determining helpfulness and support website design to induce review helpfulness. This study will help decision-makers predict the helpfulness of the review comments posted to their websites and manage more effective customer satisfaction strategies. When prospect customers feel such review helpfulness, they will have a stronger intention to pay a regular visit to the target website.

Moderating effect of bank size on the relationship between financial soundness and financial performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Peter Njagi Kirimi ◽  
Samuel Nduati Kariuki ◽  
Kennedy Nyabuto Ocharo
Keyword(s):  
Financial Performance ◽  
Commercial Banks ◽  
Management Practices ◽  
Banking Sector ◽  
Optimal Level ◽  
Moderating Effect ◽  
Content Type ◽  
Study Results ◽  
Financial Soundness ◽  
The Relationship

PurposeThis study analyzed the moderating effect of bank size on the relationship between financial soundness and financial performance of commercial banks in Kenya.Design/methodology/approachThe study employed data from 39 commercial banks for ten years from 2009 to 2018. Panel data regression model was used to analyze data.FindingsThe study results established a negative moderating effect of bank size on the relationship between commercial banks' financial soundness and net interest margin (NIM) and return on assets (ROA) with the results indicating a correlation coefficient of −0.1699 and −0.218, respectively. However, an absence of moderating effect was established when return on equity (ROE) was used as a measure of financial performance.Practical implicationsThe paper finding recommends that banks' management and other policy makers should consider the effect of bank size while devising financial soundness policies to ensure optimal level of banks' financial soundness aimed at improving banks' financial performance. In addition, bankers associations should come up with policies to standardize asset quality management practices to ensure continuous positive performance of the banking sector.Originality/valueThe study shows the contribution and applicability of the theory of production in the banking sector.

Satisfaction with service recovery: moderating effect of age in word-of-mouth

2015 ◽  
Vol 32 (6) ◽  
pp. 470-484 ◽  
Author(s):  
Beatriz Moliner-Velázquez ◽  
María-Eugenia Ruiz-Molina ◽  
Teresa Fayos-Gardó
Keyword(s):  
Word Of Mouth ◽  
Causal Attributions ◽  
Service Recovery ◽  
Moderating Effect ◽  
Direct Effects ◽  
Content Type ◽  
Multigroup Analysis ◽  
Online Word Of Mouth ◽  
The Relationship ◽  
Effect Of Age

Purpose – The purpose of this paper is, first, to analyze the direct effects of the relationship chain “causal attributions and recovery efforts → satisfaction with service recovery → conventional and online word-of-mouth intentions” and, second, to study the moderating role of age in the relationship between satisfaction and subsequent word-of-mouth. Consumer assessment and behavior associated with service recovery is a topic of considerable interest for both academics and practitioners. Design/methodology/approach – From an empirical perspective, this paper uses a sample of 336 individuals who experienced service failure at a retail store to estimate a structural equation model. Additionally, a multigroup analysis allows testing the existence of a moderating effect of age on the hypothesized relations. Findings – Results allow to confirm the direct effects of causal attributions and recovery efforts on satisfaction with service recovery, and the impact of the latter, in turn, on conventional and online word-of-mouth intentions. Furthermore, the multigroup analysis reveals that age moderates the relationship between satisfaction and online word-of-mouth. Practical implications – In service recovery situations, retailers should concentrate their efforts at providing evidence of the failure as temporary and inevitable as well as offering material or economic compensation. Originality/value – This paper contributes to the identification of the most relevant variables influencing customer satisfaction with service recovery in a retail context. In addition to this, these results provide support to the importance of age on online word-of-mouth behavior.

How E-WOM motivations vary by hotel review website

2018 ◽  
Vol 30 (8) ◽  
pp. 2730-2751 ◽  
Author(s):  
Amanda Mapel Belarmino ◽  
Yoon Koh
Keyword(s):  
Service Recovery ◽  
Online Reviews ◽  
Moderating Effect ◽  
Third Party ◽  
Travel Agency ◽  
Content Type ◽  
The Us ◽  
Online Travel ◽  
Online Travel Agency ◽  
The Relationship

Purpose Based on equity theory, this paper investigates if guests write on different review websites because of different internal motivations. Furthermore, it examines the moderating effect of service’ exceeds, neutral, negative, and service recovery–on the relationship between motivations and type of website to write reviews. Design/methodology/approach To exam if the star ratings of the same hotels were significantly different across hotel, online travel agency, and third-party review websites, this study collected 12,000 star ratings from 40 hotels across the US and conducted t-tests. A survey of 1,600 US travelers was administered to uncover the motivations for writing on different websites/website combinations. Four different scenarios were used to test the moderating effect of service: exceeds, neutral, negative, and service-recovery. These responses were analyzed using backwards stepwise regression. Findings Star ratings for the same hotel do differ among the three websites; hotel is the highest and third-party is the lowest. There are seven distinct groups of guests. Guests are motivated to write reviews to balance inequitable relationships. They decide which website/website combination best improves the equity relationship. This research indicates that guests’ choice of website is based on different internal motivations. The moderating effect of the service experience was significant. Originality/value This paper contributes to the literature by examining different motivations to write online reviews by website. Prior research typically examined one website or aggregated results from multiple websites, ignoring website specific differences. This can help hoteliers to understand why initiatives to promote reviews on certain websites may be unsuccessful.

Assessing restaurant review helpfulness through big data: dual-process and social influence theory

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wooseok Kwon ◽  
Minwoo Lee ◽  
Ki-Joon Back ◽  
Kyung Young Lee
Keyword(s):  
Social Influence ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Online Reviews ◽  
Dual Process ◽  
Content Type ◽  
Social Influence Theory ◽  
Information Cues ◽  
Review Helpfulness ◽  
The Relationship

Purpose This study aims to uncover how heuristic information cues (HIC) and systematic information cues (SIC) of online reviews influence review helpfulness and examine a moderating role of social influence in the process of assessing review helpfulness. In particular, this study conceptualizes a theoretical framework based on dual-process and social influence theory (SIT) and empirically tests the proposed hypotheses by analyzing a broad set of actual customer review data. Design/methodology/approach For 4,177,377 online reviews posted on Yelp.com from 2004 to 2018, this study used data mining and text analysis to extract independent variables. Zero-inflated negative binomial regression analysis was conducted to test the hypothesized model. Findings The present study demonstrates that both HIC and SIC have a significant relationship with review helpfulness. Normative social influence cue (NSIC) strengthened the relationship between HIC and review helpfulness. However, the moderating effect of NSIC was not valid in the relationship between SIC and review helpfulness. Originality/value This study contributes to the extant research on review helpfulness by providing a conceptual framework underpinned by dual-process theory and SIT. The study not only identifies determinants of review helpfulness but also reveals how social influences can impact individuals’ judgment on review helpfulness. By offering a state-of-the-art analysis with a vast amount of online reviews, this study contributes to the methodological improvement of further empirical research.

The effect of emotions, eWOM quality and online review sequence on consumer intention to follow advice obtained from digital services

2020 ◽  
Vol 31 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Carla Ruiz-Mafe ◽  
Enrique Bigné-Alcañiz ◽  
Rafael Currás-Pérez
Keyword(s):  
Structural Model ◽  
Online Reviews ◽  
Moderating Effect ◽  
Online Information ◽  
Bias Effect ◽  
Content Type ◽  
Digital Services ◽  
Information Cues ◽  
Cognitive Information ◽  
The Impact

PurposeThis paper analyses the interrelationships between emotions, the cognitive information cues of online reviews and intention to follow the advice obtained from digital platforms, paying special attention to the moderating effect of the sequencing of review valence.Design/methodology/approachThe data were collected from 830 Spanish Tripadvisor users. In a two-step approach, a measurement model was estimated and a structural model analysed to test the proposed hypotheses. SmartPLS 3.0 software was used. The moderating effect of sequencing of reviews is tested.FindingsThe data analysis showed a bias effect of review sequence on the impact of online information cues and emotions on intention to follow advice obtained from Tripadvisor. When the online reviews of a restaurant begin with positive commentaries, their perceived persuasiveness is a stronger driver of the pleasure and arousal elicited by online reviews than when they begin with negative reviews. On the other hand, the perceived helpfulness of online reviews only triggers arousal when the user reads negative, followed by positive, comments. The impact of pleasure on intention to follow the advice provided in an online travel community is higher with positive-negative than with negative-positive sequences.Originality/valueWhile researchers have demonstrated the benefits of customer reviews on company sales, a largely uninvestigated issue is the interplay between emotions and cognitive information cues in the processing of online reviews. This is one of the first studies to examine the moderating effect of conflicting reviews on the impact of emotions and cognitive information cues on consumer intention to follow the advice obtained from digital services.

scholarly journals Feasibility of Using Floor Vibration to Detect Human Falls

2020 ◽  
Vol 18 (1) ◽  
pp. 200
Author(s):  
Yu Shao ◽  
Xinyue Wang ◽  
Wenjie Song ◽  
Sobia Ilyas ◽  
Haibo Guo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Human Body ◽  
Nearest Neighbor ◽  
Body Movement ◽  
Modern Society ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
K Nearest Neighbor ◽  
Study Results ◽  
Floor Vibration

With the increasing aging population in modern society, falls as well as fall-induced injuries in elderly people become one of the major public health problems. This study proposes a classification framework that uses floor vibrations to detect fall events as well as distinguish different fall postures. A scaled 3D-printed model with twelve fully adjustable joints that can simulate human body movement was built to generate human fall data. The mass proportion of a human body takes was carefully studied and was reflected in the model. Object drops, human falling tests were carried out and the vibration signature generated in the floor was recorded for analyses. Machine learning algorithms including K-means algorithm and K nearest neighbor algorithm were introduced in the classification process. Three classifiers (human walking versus human fall, human fall versus object drop, human falls from different postures) were developed in this study. Results showed that the three proposed classifiers can achieve the accuracy of 100, 85, and 91%. This paper developed a framework of using floor vibration to build the pattern recognition system in detecting human falls based on a machine learning approach.

Exploring privacy and trust for employee monitoring

2015 ◽  
Vol 115 (1) ◽  
pp. 88-106 ◽  
Author(s):  
Shuchih Ernest Chang ◽  
Anne Yenching Liu ◽  
Sungmin Lin
Keyword(s):  
Organizational Culture ◽  
Employee Performance ◽  
Full Time ◽  
Negative Effects ◽  
Content Type ◽  
Positive Effects ◽  
Study Results ◽  
Employee Monitoring ◽  
Communication Privacy ◽  
The Relationship

Purpose – The purpose of this paper is to evaluate privacy boundaries and explores employees’ reactions in employee monitoring. Design/methodology/approach – The research used the metaphor of boundary turbulence in the Communication Privacy Management (CPM) theory to demonstrate the psychological effect on employees. The model comprised organizational culture, CPM, trust, and employee performance in employee monitoring to further investigated the influence exerted by organizational culture and how employees viewed their trust within the organization when implementing employee monitoring. Variables were measured empirically by administrating questionnaires to full-time employees in organizations that currently practice employee monitoring. Findings – The findings showed that a control-oriented organizational culture raised communication privacy turbulence in CPM. The communication privacy turbulence in CPM mostly had negative effects on trust in employee monitoring policy, but not on trust in employee monitoring members. Both trust in employee monitoring policy and trust in employee monitoring members had positive effects on employee commitment and compliance to employee monitoring. Research limitations/implications – This research applied the CPM theory in workplace privacy to explore the relationship between employees’ privacy and trust. The results provide insights of why employees feel psychological resistance when they are forced to accept the practice of employee monitoring. In addition, this study explored the relationship between CPM and trust, and offer support and verification to prior studies. Practical implications – For practitioners, the findings help organizations to improve the performance of their employees and to design a more effective environment for employee monitoring. Originality/value – A research model was proposed to study the impacts of CPM on employee monitoring, after a broad survey on related researches. The validated model and its corresponding study results can be referenced by organization managers and decision makers to make favorable tactics for achieving their goals of implementing employee monitoring.

How does renqing influence purchase intentions in the Chinese business-to-business context?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xun Zhang ◽  
Biao Xu ◽  
Jun Wu
Keyword(s):  
Positive Relationship ◽  
Purchase Intentions ◽  
Moderating Effect ◽  
Content Type ◽  
Mediating Role ◽  
Chinese Business ◽  
The Relationship ◽  
Business To Business ◽  
Positive Effect

Purpose This study aims to examine the relationship between renqing and purchase intentions and the mechanism of its impact in the Chinese business-to-business (B2B) context. Design/methodology/approach Renqing in China has played an important role in business relationships and has been receiving increased attention in both practice and theory. However, little is known about whether it can influence purchase intentions in a rational B2B condition. This research aims to examine the relationship between renqing and purchase intentions and the mechanism of its impact in the Chinese B2B context. Based on a survey of 1,010 industry buyers from 468 Chinese downstream buyer companies, the empirical findings indicate a positive relationship between renqing and purchase intentions and the mediating role of long-term orientation (LTO) for increasing purchase intentions. In addition, this study also finds that product involvement (PI) has a negative moderating effect on the relationship between renqing and purchase intentions, which means that renqing has a big positive effect on purchase intentions in low PI conditions. The results highlight several implications for B2B companies that sell products to Chinese enterprises. Findings The empirical findings indicate a positive relationship between renqing and purchase intentions and the mediating role of LTO for increasing purchase intentions. In addition, this study also finds that PI has a negative moderating effect on the relationship between renqing and purchase intentions, which means that renqing has a big positive effect on purchase intentions in low PI conditions. Originality/value First of all, by answering the research question, this study shows that renqing has a positive effect on purchase intentions in Chinese B2B context. Second, this study elucidates the influence mechanism of renqing on purchase intention and identifies the mediating effect of LTO and the moderating effect of PI.

Sign in / Sign up

Export Citation Format

Share Document