Voice of airline passenger: A text mining approach to understand customer satisfaction

Sezgen, Eren; Mason, Keith; Mayer, Robert

doi:10.1016/j.jairtraman.2019.04.001

Cited by 143 publications

(114 citation statements)

References 65 publications

(102 reference statements)

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“…This dashboard would facilitate the results collected from social media and its effect on tourism would be discussed [192]. Furthermore, Sezgen et al [193] investigated the primary drivers of customer satisfaction and dissatisfaction of both full-service and low-cost carriers and of economy and premium class cabins using TripAdvisor passenger reviews for fifty (50) airlines. Text mining in social media platforms has been used to automatically rank different brands and make recommendations.…”

Section: Other Social Media Platformsmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

185

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Text mining in big data analytics is emerging as a powerful tool for harnessing the power of unstructured textual data by analyzing it to extract new knowledge and to identify significant patterns and correlations hidden in the data. This study seeks to determine the state of text mining research by examining the developments within published literature over past years and provide valuable insights for practitioners and researchers on the predominant trends, methods, and applications of text mining research. In accordance with this, more than 200 academic journal articles on the subject are included and discussed in this review; the state-of-the-art text mining approaches and techniques used for analyzing transcripts and speeches, meeting transcripts, and academic journal articles, as well as websites, emails, blogs, and social media platforms, across a broad range of application areas are also investigated. Additionally, the benefits and challenges related to text mining are also briefly outlined.

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Section: Other Social Media Platformsmentioning

confidence: 99%

Text Mining in Big Data Analytics

Hassani

Beneki

Unger

et al. 2020

BDCC

185

View full text Add to dashboard Cite

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“…When the expectations are not met, negative disconfirmation takes place due to the gap between the guests' expectations and perceptions of service performance. Failure in the delivery of services often results in guest dissatisfaction and complaining behavior, such as negative word-of-mouth, complaints, and higher customer turnover [66]. The following complaint is an example of the type of issues that were raised with respect to the attributes of cleanliness and hotel:…”

Section: Differences Between the Online Complaining Behavior Of Asianmentioning

confidence: 99%

Does Culture of Origin Have an Impact on Online Complaining Behaviors? The Perceptions of Asians and Non-Asians

2020

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The main purpose of this study was to analyze and compare the online complaining behavior of Asian and non-Asian hotels guests who have posted negative hotel reviews on TripAdvisor to voice their dissatisfaction towards a select set of hotel service attributes. A qualitative content analysis of texts which relied on manual coding was used while examining 2020 online complaining reviews directed at 353 UK hotels and posted by visitors originating from 63 countries. The results from the word frequency analysis reveal that both Asian and non-Asian travelers tend to put more emphasis on Booking and Reviews when posting complaints online. Based on a manual qualitative content analysis, 11 different major online complaint categories and 65 sub-categories were identified. Among its important findings, results of this study show that non-Asian guests frequently make complaints which are longer and more detailed than Asian customers. Managerial implications and opportunities for future studies are also discussed.Sustainability 2020, 12, 1838 2 of 37 booking intentions [7,8], consumer decision-making [9], consumer attitudes [10,11], and perception of trust [12]. Research on online consumer behavior has demonstrated that negative reviews hold more sway than positive reviews; therefore, consumers will give more weight to negative information when making judgments or performing decision-making tasks [13]. An example of this can be seen in a study by Casaló, Flavián, Guinalíu, and Ekinci (2015) on travelers' perceived usefulness of online reviews. The results show that the travelers find negative online reviews more useful than positive ones. Nevertheless, although the significance and the influence of online reviews is well recognized, the important question of how to understand online complaining behavior within the context of different cultural backgrounds still remains, with only a few researchers focusing on the relevant factors thus far.Customer dissatisfaction and consumer complaining behavior were quick to draw attention from the researchers of and service providers in the hospitality industry. Although consumer complaints do give hoteliers the opportunity to improve their marketing programs in ways that can enhance customer satisfaction and hotel profitability, they can also impact the hotel's reputations and potentially do great damage to the company [14]. Thus, we duly recognize the importance that must be attached to proper and applicable understandings of consumer complaint behavior. Literature has argued that complaint behavior may manifest itself differently on account of the distinct norms that are inherent to varying cultures [15]. For example, Ngai, Heung, Wong, and Chan (2007) examined the different attitudes Asian and non-Asian hotel guests held towards complaining behavior. The study found out that Asian guests were less likely to complain directly to the hotels for fear of "losing face", preferring rather to take non-direct action, such as through negative word-of-mouth. Yuksel, Kilinc, and Yuksel (2006) ...

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“…Experts in the field usually will make the deci- giving an option to high-income leisure passengers 126 to upgrade [8]. It provides a choice as an answer to 127 most passenger dissatisfaction, which is seat com-128 fort and legroom, luggage/flight disruptions and staff 129 behaviours which occur in both LCCs and FSCs [14]. more of the cost of economy, and even four times higher for several routes [16].…”

Section: Introductionmentioning

confidence: 99%

Designing a floor plan using aircraft seat comfort knowledge by aircraft interior experts

Anjani

Song

Vink

2021

WOR

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BACKGROUND: Recent research indicated that an 18′′ ×30′′ aircraft seat resulted in nearly the same level of comfort as a 17′′ ×34′′ seat. However, it took less space in the floor plan. OBJECTIVES: This study explores seat layouts preferred by experts regarding different criteria. Those results of the experts are later compared to layouts produced by computational algorithms to evaluate the advantages of each method. METHODS: Eighty-eight experts in the field of aircraft interior were invited to make a floor plan of a part of a Boeing 777 aircraft where comfort was one of the main goals. Participants worked in groups of 3 and are given the freedom to design a section of the cabin between economy and first-class (5.87 m wide and 3.7 m long), where besides these two types of seats, an old business-class size seat of 20′′ ×36′′ was introduced as well for more flexibilities in design. Computational algorithms were also applied with the same inputs and constraints to generate layouts as a comparison. RESULTS: In total, 29 floor-plans were made, and these plans were analysed to compare against the complexity of the operations, the number of passengers on board, the revenue of the airline, and the width of the aisle. Results showed that 14 groups opted for the economy seats, while the rest utilized a hybrid setup where the business class seats were used in the configuration. These results are compared to the 126 computerized layouts generated. CONCLUSIONS: Among all layouts designed by experts, a combination of 28 18′′ ×30′′ seats and 20 17′′ ×34′′ seats had the highest potential revenue of US$21,984. This floor plan fits the regulations with an aisle width of 0.93 m. The computerized layout had a better outcome in maximizing profit of US$22,416 with 32 18′′ ×30′′ seats and 16 20′′ ×36′′ seats. However, the comfort of such results was to be explored as some seats were rotated 90 degrees.

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Voice of airline passenger: A text mining approach to understand customer satisfaction

Cited by 143 publications

References 65 publications

Text Mining in Big Data Analytics

Text Mining in Big Data Analytics

Does Culture of Origin Have an Impact on Online Complaining Behaviors? The Perceptions of Asians and Non-Asians

Designing a floor plan using aircraft seat comfort knowledge by aircraft interior experts

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