scholarly journals A Text Analytics-Based Importance Performance Analysis and Its Application to Airline Service

2019 ◽  
Vol 11 (21) ◽  
pp. 6153 ◽  
Author(s):  
Seungju Nam ◽  
Hyun Cheol Lee
Keyword(s):  
Firm Performance ◽  
Performance Analysis ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Text Analytics ◽  
Service Experience ◽  
Customer Perceptions ◽  
Statistical Correlations ◽  
Air Transport Industry ◽  
Service Experiences

We introduce a new importance-performance analysis (IPA) methodology while making use of direct service experience perceptions represented by online reviews with numerical ratings. The proposed IPA, which we call the text analytics-based IPA (TAIPA), allows the real-time calculation of importance using the probability distribution of word frequency via the latent Dirichlet allocation (LDA) application to online reviews, and of performance using numerical rating values. The importance is also adjusted with the help of a sentiment analysis of online reviews to provide more precise measurements for service experience perceptions. To ensure an evaluation of the entire service process, we employ service encounters, in which service experiences occur and thus most customer perceptions are created, as a set of attributes composed of LDA topics that contain direct perceptions of service experiences. We investigate statistical correlations between TAIPA calculations and typical benchmarks of firm performance in the air-transport industry to verify how effective the proposed TAIPA is with respect to the degree that customer satisfaction is represented. As a primary result, TAIPA is more effective than comparison targets in that it shows stronger correlations with firm performance. TAIPA is specialized in determining which service step (i.e., a one-to-one relationship with a service encounter) needs to be improved. Moreover, TAIPA is flexible in considering multiple competitors.

Approach for Importance–Performance Analysis of Product Attributes From Online Reviews

2021 ◽  
Vol 143 (8) ◽  
Author(s):  
Junegak Joung ◽  
Harrison M. Kim
Keyword(s):  
Neural Network ◽  
Performance Analysis ◽  
Sentiment Analysis ◽  
High Performance ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Product Attributes ◽  
Ibm Watson ◽  
Promising Source

Abstract The importance–performance analysis (IPA) is a widely used technique to guide strategic planning for the improvement of customer satisfaction. Compared with surveys, numerous online reviews can be easily collected at a lower cost. Online reviews provide a promising source for the IPA. This paper proposes an approach for conducting the IPA from online reviews for product design. Product attributes from online reviews are first identified by latent Dirichlet allocation. The performance of the identified attributes is subsequently estimated by the aspect-based sentiment analysis of IBM Watson. Finally, the importance of the identified attributes is estimated by evaluating the effect of sentiments of each product attribute on the overall rating using an explainable deep neural network. A Shapley additive explanation-based method is proposed to estimate the importance values of product attributes with a low variance by combining the effect of the input features from multiple optimal neural networks with a high performance. A case study of smartphones is presented to demonstrate the proposed approach. The performance and importance estimates of the proposed approach are compared with those of previous sentiment analysis and neural network-based method, and the results exhibit that the former can perform IPA more reliably. The proposed approach uses minimal manual operation and can support companies to take decisions rapidly and effectively, compared with survey-based methods.

scholarly journals AN AUTOMATED METHOD TO CONDUCT IMPORTANCE-PERFORMANCE ANALYSIS OF PRODUCT ATTRIBUTES FROM ONLINE REVIEWS - AN EXTENSION WITH A CASE STUDY

2021 ◽  
Vol 1 ◽  
pp. 417-426
Author(s):  
Kangcheng Lin ◽  
Harrison Kim
Keyword(s):  
Performance Analysis ◽  
Latent Dirichlet Allocation ◽  
Product Information ◽  
Online Reviews ◽  
Product Attributes ◽  
Attribute Importance ◽  
Online Data ◽  
Automated Method ◽  
Ibm Watson

AbstractWith the growth of online marketplaces and social media, product designers have been seeing an exponential growth of data available, which can serve as an extremely valuable source of information communicated from customers without geographical limitations. The data will reveal customers’ preferences, which can be expensive and slow to obtain via traditional methods such as survey and questionnaires. While existing methods in the literature have been proposed to extract product information and make inference from online data, they have limitations, especially in providing reliable results and in dealing with data sparsity. Therefore, this paper proposes a method to conduct an Important-performance analysis from online reviews. The major steps of this method involve using latent Dirichlet allocation (LDA) to identify product attributes, using IBM Watson Natural Language Understanding tool to perform aspect-based sentiment analysis, and using XGBoost model to infer product attribute importance from the collected dataset. In our case study, we have collected over 150,000 text reviews of more than 3,000 laptops from Amazon.

Customer and Non‐Customer Perceptions of Third Party Services: Are They Similar?

1992 ◽  
Vol 3 (1) ◽  
pp. 12-22 ◽  
Author(s):  
Dan Sarel ◽  
Walter Zinn
Keyword(s):  
Latin America ◽  
Firm Performance ◽  
Performance Analysis ◽  
Competitive Advantage ◽  
Customer Service ◽  
Third Party ◽  
Competitive Performance ◽  
Customer Perceptions ◽  
Simultaneous Evaluation

Competitive performance analysis typically relies on customer service surveys. This research highlights the importance of systematically including non‐customer input to customer service surveys. Findings indicate that perceptions of customers and non‐customers both on service importance and on firm performance can be significantly different. This research also examines the special requirements needed to apply results of customer service surveys in Latin America. Finally, a method for the simultaneous evaluation of multiple competitors is recommended. Strategies for developing competitive advantage based on the findings are discussed.

Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach

2021 ◽  
Vol 49 (1) ◽  
pp. 699-728
Author(s):  
Tianjie Deng ◽  
◽  
Young-Jin Lee ◽  
Karen Xie ◽  
◽  
...  
Keyword(s):  
Firm Performance ◽  
Online Reviews ◽  
Text Analytics

scholarly journals Redesigning In-Flight Service with Service Blueprint Based on Text Analysis

2018 ◽  
Vol 10 (12) ◽  
pp. 4492 ◽  
Author(s):  
Seungju Nam ◽  
Chunghun Ha ◽  
Hyun Lee
Keyword(s):  
Real Time ◽  
Word Frequency ◽  
Text Analysis ◽  
Topic Modeling ◽  
Online Reviews ◽  
Service Process ◽  
Service Encounters ◽  
Customer Perceptions ◽  
Service Experiences ◽  
Service Blueprint

Airline services should be passenger-focused to be sustainable. In this study, we redesign an in-flight service process using a service blueprint while incorporating direct customer perceptions of service experiences. To incorporate these, we apply topic modeling to 64,706 passenger-written online reviews of airline services. Passenger experiences of in-flight services are the sum of experiences from service encounters in all the subsequent steps and we assume that their direct perceptions of their experiences are faithfully contained in the online reviews. Topics extracted from the reviews can be regarded as service encounters based strongly on passenger experiences. Then, the service encounters are reorganized within the framework of a service blueprint. The results show that the complexity, a number of service steps, decreases by 38% compared to the benchmark service blueprint. However, the divergence, a latitude of service steps, should increase for a couple of service encounters. Moreover, we quantitatively analyze the divergence using the probability of word frequency statistically distributed across topics. The in-flight service using the proposed design could be sustainable with respect to customer-focused service while considering direct customer experiences in real-time.

scholarly journals The Effects of Online Information on E-Book Pricing Strategies: A Text Analytics Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kang Li ◽  
Lunchuan Zhang ◽  
Dianwei Wang ◽  
Dinglu Pan
Keyword(s):  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Online Information ◽  
Pricing Strategies ◽  
Text Analytics ◽  
Online Data ◽  
Managerial Implication ◽  
Multiple Regression Method ◽  
Book Prices ◽  
The Impact

Nowadays, electronic book vendors are increasingly proactive in trying to strategically capitalize on online big data generated by consumers. It will bring great profit for vendors if they can make the most of online reviews to figure out the impact of online data on the selling prices of e-books. In this paper, we complement an emerging body of research to explore how e-book prices could be affected by online information via analyzing the sheer volume of online data from e-book websites, namely, we first employ a domain ontology-based method to select the most discriminative features that may affect e-book prices. Then, the topic modeling method latent Dirichlet allocation and aspect-oriented sentiment analysis methods are applied as a supplement. Using the multiple regression method, we identify the key features that may have effects on the prices of e-books and give the related regression equation. In our results, some factors including paper book prices, paper book pages corresponding to the e-book, and e-book content have significant effects on the price of e-books. The managerial implication is that e-book firms can obtain a reference price for an e-book and may dynamically adjust the price to increase e-book sales according to our data analysis results.

ANALYSING SENTIMENTS OF ONLINE REVIEWS ON RESTAURANTS IN MALAYSIA USING PREDICTIVE TEXT ANALYTICS

2018 ◽  
Vol 2018 ◽  
pp. 200-200
Author(s):  
Kok Wei Khong ◽  
◽  
Fon Sim Ong ◽  
Babajide AbuBakr Muritala ◽  
Ken Kyid Yeoh
Keyword(s):  
Online Reviews ◽  
Text Analytics

Analisis Kualitas Pelayanan Pada Unit Perijinan Angkutan Dan Kendaraan Wajib Uji Dinas Perhubungan Kabupaten Karanganyar

2020 ◽  
Vol 4 (02) ◽  
Author(s):  
Fachry Prasetyo ◽  
Priyanto Susiloadi
Keyword(s):  
Performance Analysis ◽  
Service Quality ◽  
Sampling Method ◽  
Sampling Technique ◽  
Primary Data ◽  
Good Service ◽  
Analysis Techniques ◽  
User Community ◽  
Customer Perceptions ◽  
Level Of Satisfaction

Good service quality in public services will give an impetus to the user community to give a good assessment. Good service by the State Civil Servants (ASN) in the Transportation Obligatory Licensing Unit (UPAKWU) in the Karanganyar District Transportation Department was apparently still receiving complaints from the service user community. This shows that there are still some shortcomings in the implementation of the service system in the office. The sampling technique uses accidental sampling method. The data used are primary data obtained directly from respondents by providing a list of questions or questionnaires. Data analysis techniques using Importance-Performance Analysis (IPA) are used to measure the level of satisfaction of someone over the performance of other parties, and Cartesian Diagrams to determine service indicators that satisfy or do not satisfy consumers. The results showed that: Service quality in UPAKWU Karanganyar Regency according to customer perceptions has not been satisfactory, despite having good service performance / above average. This is based on the results of the Importance Performance Analysis analysis which gets a result of 94.36% (Total Tki

Mining numerical measure of consumers’ product evaluation expressed in words based on latent Dirichlet allocation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ziang Wang ◽  
Feng Yang
Keyword(s):  
Latent Dirichlet Allocation ◽  
Product Evaluation ◽  
Online Reviews ◽  
Product Evaluations ◽  
Product Attributes ◽  
Data Set ◽  
Content Type ◽  
Face To Face ◽  
Online Retailers ◽  
Dirichlet Allocation

Purpose It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word. Design/methodology/approach First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model. Findings The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment. Originality/value This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews

2019 ◽  
Vol 70 ◽  
pp. 460-478 ◽  
Author(s):  
Jian-Wu Bi ◽  
Yang Liu ◽  
Zhi-Ping Fan ◽  
Jin Zhang
Keyword(s):  
Performance Analysis ◽  
Online Reviews ◽  
Wisdom Of Crowds
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