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.

Reading between the lines: analyzing online reviews by using a multi-method Web-analytics approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alekh Gour ◽  
Shikha Aggarwal ◽  
Mehmet Erdem
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Topic Modeling ◽  
Online Reviews ◽  
Machine Learning Algorithms ◽  
Web Analytics ◽  
Content Type ◽  
Marketing Tool ◽  
Multi Method Approach ◽  
Method Approach

Purpose The dynamic yet volatile nature of tourism and travel industry in a competitive environment calls for enhanced marketing intelligence and analytics, especially for those entities with limited marketing budgets. The past decade has witnessed an increased use of user-generated content (UGC) analysis as a marketing tool to make better informed decisions. Likewise, textual data analysis of UGC has gained much attention among tourism and hospitality scholars. Nonetheless, most of the scholarly works have focused on the singular application of an existing method or technique rather than using a multi-method approach. The purpose of this study is to propose a novel Web analytics methodology to examine online reviews posted by tourists in real time and assist decision-makers tasked with marketing strategy and intelligence. Design/methodology/approach For illustration, the case of tourism campaign in India was undertaken. A total of 305,298 reviews were collected, and after filtering, 276,154 reviews were qualified for analysis using a string of models. Descriptive charts, sentiment analysis, clustering, topic modeling and machine learning algorithms for real-time classification were applied. Findings Using big data from TripAdvisor, a total of 145 tourist destinations were clustered based on tourists’ perceptions. Further exploration of each cluster through topic modeling was conducted, which revealed interesting insights into satisfiers and dissatisfiers of different clusters of destinations. The results supported the use of the proposed multi-method Web-analytics approach. Practical implications The proposed machine learning model demonstrated that it could provide real-time information on the sentiments in each incoming review about a destination. This information might be useful for taking timely action for improvisation or controlling a service situation. Originality/value In terms of Web-analytics and UGC, a comprehensive analytical model to perform an end-to-end understanding of tourist behavior patterns and offer the potential for real-time interpretation is rarely proposed. The current study not only proposes such a model but also offers empirical evidence for a successful application. It contributes to the literature by providing scholars interested in textual analytics a step-by-step guide to implement a multi-method approach.

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.

Customer delight during a crisis: understanding delight through the lens of transformative service research

2020 ◽  
Vol 32 (1) ◽  
pp. 129-141 ◽  
Author(s):  
Donald C. Barnes ◽  
Jessica Mesmer-Magnus ◽  
Lisa L. Scribner ◽  
Alexandra Krallman ◽  
Rebecca M. Guidice
Keyword(s):  
Critical Incident ◽  
Service Providers ◽  
Psychological Theory ◽  
Well Being ◽  
Service Research ◽  
Service Encounters ◽  
Need Fulfillment ◽  
Content Type ◽  
Customer Delight ◽  
Service Experiences

PurposeThe unprecedented dynamics of the COVID-19 pandemic has forced firms to re-envision the customer experience and find new ways to ensure positive service encounters. This context has underscored the reality that drivers of customer delight in a “traditional” context are not the same in a crisis context. While research has tended to identify hedonic need fulfillment as key to customer well-being and, ultimately, to invoking customer delight, the majority of studies were conducted in inherently positive contexts, which may limit generalizability to more challenging contexts. Through the combined lens of transformative service research (TSR) and psychological theory on hedonic and eudaimonic human needs, we evaluate the extent to which need fulfillment is the root of customer well-being and that meeting well-being needs ultimately promotes delight. We argue that in crisis contexts, the salience of needs shifts from hedonic to eudaimonic and the extent to which service experiences fulfill eudaimonic needs determines the experience and meaning of delight.Design/methodology/approachUtilizing the critical incident technique, this research surveyed 240 respondents who were asked to explain in detail a time they experienced customer delight during the COVID-19 pandemic. We analyzed their responses according to whether these incidents reflected the salience of hedonic versus eudaimonic need fulfillment.FindingsThe results support the notion that the salience of eudaimonic needs become more pronounced during times of crisis and that service providers are more likely to elicit perceptions of delight when they leverage meeting eudaimonic needs over the hedonic needs that are typically emphasized in traditional service encounters.Originality/valueWe discuss the implications of these findings for integrating the TSR and customer delight literatures to better understand how service experiences that meet salient needs produce customer well-being and delight. Ultimately, we find customer delight can benefit well-being across individual, collective and societal levels.

A Tourism Knowledge Model through Topic Modeling from Online Reviews

2021 ◽  
Author(s):  
Valentinus R. Hananto ◽  
Uwe Serdült ◽  
Victor Kryssanov
Keyword(s):  
Topic Modeling ◽  
Online Reviews ◽  
Knowledge Model

Customer Rating Prediction Using Text Analysis of Online Reviews

2021 ◽  
Vol 32 (1) ◽  
pp. 89-103
Author(s):  
Minji Yoon ◽  
Chang Kyoo Cho ◽  
Yong Won Seo
Keyword(s):  
Text Analysis ◽  
Online Reviews ◽  
Rating Prediction

scholarly journals A Comparative Study of Customer Perceptions of Urban and Rural Bed and Breakfasts in Beijing: An Analysis of Online Reviews

2021 ◽  
Vol 13 (20) ◽  
pp. 11303
Author(s):  
Xin Zhang ◽  
Jiaming Liu ◽  
He Zhu ◽  
Zongcai Huang ◽  
Shuying Zhang ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Comparative Study ◽  
Public Transportation ◽  
Local Governments ◽  
Service Design ◽  
Online Reviews ◽  
Influential Factor ◽  
The Sustainable Development ◽  
Customer Perceptions ◽  
Design Style

The differences between urban and rural B&Bs should be emphasized, which is critical for the sustainable development of the B&B industry. This study identified and compared the topics that customers were concerned about for urban and rural B&Bs in Beijing by analyzing 13,241 online reviews obtained from the website Ctrip. The results showed that customers focused on 10 common topics: “room”, “location”, “host”, “experience”, “surroundings”, “facilities”, “service”, “design/style”, “value”, and “entertainment”. However, the importance of each topic varied between urban and rural B&Bs. Customers paid more attention to the room. Urban B&B customers were more concerned about location. The convenience of urban B&Bs was more prominent than that of rural B&Bs, especially in terms of public transportation and commercial services. While rural B&B customers were more concerned about experience, service, design/style, and entertainment. In addition, the “host” is the most crucial and influential factor in the development of B&Bs. This study made contributions to customer perceptions of B&Bs from a comparative perspective and enriched the understanding of the characteristics of urban and rural B&Bs. In the part of practice, this study might provide enlightenment for B&B operators and local governments to take measures for B&Bs sustainable development.

Validating Perceived Sustainable Design Features Using a Novel Collage Approach

2021 ◽  
Author(s):  
Nasreddine El-Dehaibi ◽  
Ting Liao ◽  
Erin F. MacDonald
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Sustainable Design ◽  
Design Method ◽  
Online Reviews ◽  
Design Features ◽  
Customer Perceptions ◽  
Product Features ◽  
Social Environmental

Abstract Fierce e-commerce competition challenges designers to differentiate their products on platforms such as Amazon. To achieve this differentiation, designers must first understand how customers perceive product features. This paper builds on our previous work where we extracted features perceived as sustainable for French Press coffee carafes using annotations of Amazon reviews and natural language processing (NLP). We identified a gap between customer perceptions of sustainability and engineered sustainability. We now test our findings with a relatively new design method of collage placement and investigate how designers can use perceived features to set their products apart. We created collage activities for participants to evaluate French Press products on the three aspects of sustainability: social, environmental, and economic, and on how much they like the products. During the activity participants placed products along the two axes of the collage, sustainability and likeability, and labeled products with descriptive features that we provided. We found that participants more often selected features perceived as sustainable when placing products higher on the sustainability axis, demonstrating that these features resonated with customers. We also measured a low correlation between the two-axes of the collage activity, indicating that perceived sustainability and likeability can be measured separately. In addition, we found that product perceptions across sustainability aspects may differ between demographics. Based on these results, we confirm that features perceived as sustainable that are extracted from online reviews resonate with customers when thinking of various sustainability aspects and that the collage is an effective tool for assessing sustainability perceptions.

The Role of Digital Service Encounters on Customers' Perceptions of Companies

2010 ◽  
pp. 88-97
Author(s):  
Kristina Heinonen
Keyword(s):  
Empirical Study ◽  
Two Dimensions ◽  
Service Encounter ◽  
The Internet ◽  
Service Encounters ◽  
Customer Perceptions ◽  
Digital Service ◽  
A Company ◽  
E Mail

The service encounter occurs whenever a customer interacts with a company personally or through technology through, for example, the Internet, e-mail, or telephone. Nowadays, customers frequently initiate the encounter as, for example, inquiries, information searches, and complaints are conveniently performed online. This article explores the role of digital service encounters on customer perceptions of companies. Digital service encounters in this article denote remote customer-company interactions via the Internet or e-mail. The focus is on active customers initiating interactions and on customer perceptions of company responses to these interactions. A conceptual framework that captures customer perceived service encounter value on two dimensions (responsiveness and personalization) is proposed. An empirical study exploring the value of company responses to digital contacts indicated that many contacts are responded to promptly and satisfyingly. However, there are also significant differences in the value of the service encounter. Some service encounters are perceived as unpersonalized, and some are even left without response.

Analysis of Online Hotel Reviews During the COVID-19 Pandemic Using Topic Modeling

2021 ◽  
pp. 478-494
Author(s):  
Özlem Ergüt
Keyword(s):  
Text Mining ◽  
Service Quality ◽  
Topic Modeling ◽  
Online Reviews ◽  
Current Situation ◽  
Tourism Industry ◽  
Daily Lives ◽  
New Normal ◽  
Tourism Sector ◽  
The World

The world is facing the COVID-19 pandemic that has impacted economies and millions of people worldwide. The fact that COVID-19 is highly contagious from person to person has greatly affected the daily lives of people, and it has also had a devastating effect on many sectors, particularly the tourism industry. In order to mitigate losses for the tourism sector and for it to gain a new dynamism under the current pandemic conditions, monitoring and analyzing online reviews is an important factor for better understanding the needs and desires of customers. The purpose of this study was to determine the main topics in online reviews by foreign guests staying in İstanbul during the pandemic period using text mining techniques. The information obtained as a result of the analysis is important in terms of understanding how to manage the current situation, developing suggestions for solutions, improving service quality, making future decisions, and adapting to the new normal.

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