Modeling of airline passenger loyalty: A comparison of leisure and business travelers

2021 ◽  
pp. 100735
Author(s):  
Dissakoon Chonsalasin ◽  
Sajjakaj Jomnonkwao ◽  
Kattreeya Chanpariyavatevong ◽  
Wimon Laphrom ◽  
Vatanavongs Ratanavaraha
Keyword(s):  
Business Travelers ◽  
Airline Passenger

scholarly journals Airbnb Host Scaling, Seasonal Patterns, and Competition

2021 ◽  
Vol 5 (1) ◽  
pp. 4
Author(s):  
Ruggero Sainaghi ◽  
Rodolfo Baggio
Keyword(s):  
Mutual Information ◽  
Size Effect ◽  
Seasonal Patterns ◽  
Scaling Effect ◽  
Business Travelers ◽  
Explorative Study ◽  
Similarities And Differences ◽  
The City

This paper explores the scaling (size) effect in the seasonal patterns, a proxy for competitive threats, of Airbnb’s host providers, with the aim of understanding possible similarities and differences. This explorative study uses the city of Milan (Italy) as a case and daily occupancy data from Airbnb listings for four completed years (2015–2018). A mutual information-based technique was applied to assess possible synchronizations in the seasonal patterns. Empirical findings show progressive dissimilarities when moving from single to multiple listings, thus indicating a differentiation correlated to the presence of managed listings. There are fewer differences during the seasonal periods more centered around leisure clients and they are higher when considering business travelers. The evidence supports the scaling effect and its ability to reduce the competitive threat among different hosts.

COVID-19: prevalence of job-demands, stress, work–life difficulties and work–life balance among international business travelers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vilmante Kumpikaite-Valiuniene ◽  
Luisa Helena Pinto ◽  
Tahir Gurbanov
Keyword(s):  
International Business ◽  
Job Demands ◽  
Work Life ◽  
Work Life Balance ◽  
Life Balance ◽  
Business Travel ◽  
Content Type ◽  
Business Travelers ◽  
Perceived Change ◽  
Stress Work

PurposeInternational business travelers (IBTs) face daily challenges pertaining to the frequency and duration of travel. Following the outbreak of coronavirus disease (COVID-19), the study aims to draw upon the job demands-resources (JD-R) model and the literature on work–life balance (WLB) to examine how this crisis have disrupted IBTs routines and the implications for their WLB.Design/methodology/approachData were collected in April 2020 with an online survey answered by 141 IBTs from different locations. The first set of analyses examined the perceived change in job-demands (i.e. business travel and workload) including stress and work–life difficulties following the outbreak of COVID-19. The second set of analyses tested the hypotheses that the perceived change in workload and stress predict IBTs' work–life difficulties, which, in turn, affect their WLB.FindingsThe results show that the decline in job-demands (i.e. business travel and workload) after the outbreak of COVID-19 was not enough to reduce IBTs' stress and ameliorate their work–life difficulties and WLB. Only respondents who experienced a decrease in workload, including less relational difficulties, reported a superior WLB.Originality/valueThe study widens the scope and relevance of global mobility studies in crisis settings by timely reporting the changes in job-demands, stress and work–life difficulties among IBTs following the outbreak of COVID-19. Additionally, the research extends the use of the JD-R model in the international context by advancing our knowledge of the interplay between contextual demands and job-demands in affecting IBTs' stress, work–life difficulties and WLB.

Perbandingan Optimasi Feature Selection pada Naïve Bayes untuk Klasifikasi Kepuasan Airline Passenger

2021 ◽  
Vol 5 (3) ◽  
pp. 527-533
Author(s):  
Yoga Religia ◽  
Amali Amali
Keyword(s):  
Feature Selection ◽  
Customer Satisfaction ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Point Of View ◽  
Classification Model ◽  
Passenger Satisfaction ◽  
Airline Passenger ◽  
Bayes Algorithm

The quality of an airline's services cannot be measured from the company's point of view, but must be seen from the point of view of customer satisfaction. Data mining techniques make it possible to predict airline customer satisfaction with a classification model. The Naïve Bayes algorithm has demonstrated outstanding classification accuracy, but currently independent assumptions are rarely discussed. Some literature suggests the use of attribute weighting to reduce independent assumptions, which can be done using particle swarm optimization (PSO) and genetic algorithm (GA) through feature selection. This study conducted a comparison of PSO and GA optimization on Naïve Bayes for the classification of Airline Passenger Satisfaction data taken from www.kaggle.com. After testing, the best performance is obtained from the model formed, namely the classification of Airline Passenger Satisfaction data using the Naïve Bayes algorithm with PSO optimization, where the accuracy value is 86.13%, the precision value is 87.90%, the recall value is 87.29%, and the value is AUC of 0.923.

Changing trends and pretravel preparation of business travelers from Greece during the financial crisis

Public Health ◽  
2019 ◽  
Vol 168 ◽  
pp. 168-171 ◽  
Author(s):  
A. Pavli ◽  
I. Lymperi ◽  
T. Minitsios ◽  
P. Katerelos ◽  
M. Souli ◽  
...  
Keyword(s):  
Financial Crisis ◽  
Business Travelers ◽  
Changing Trends

scholarly journals PASSENGER MANIFEST DATA MANAGEMENT ANALYSIS ON IMMIGRATION EXAMINATION ON THE IMMIGRATION CROSSING APPLICATION (APK) AT IMMIGRATION EXAMINATION AT HUSEIN SASTRANEGARA INTERNATIONAL AIRPORT

2020 ◽  
Vol 2 (2) ◽  
pp. 11-16
Author(s):  
Rizky Andarujati
Keyword(s):  
Data Management ◽  
Maximum Output ◽  
Border Control ◽  
Accurate Data ◽  
International Airport ◽  
Inspection Process ◽  
Airline Passenger ◽  
System Requirements ◽  
Control Management ◽  
Over Time

The existence of the system used by humans over time will experience problems or problems and increase the system requirements needed by system users. One of the applications of SIMKIM at the Air Immigration Checkpoint (TPI) is the Immigration Crossing Application (APK) system. This APK is a transformation of the Border Control Management (BCM) system which has the function of capturing, verifying, matching, and recording data contained in electronic travel documents, namely passports and other travel documents such as visas, travel document readers, biographical & biometric identities, watch lists , automatic border control. If the airline passenger manifest has been integrated with the APK system, the immigration check can be more efficient in terms of how much input is made to produce maximum output, the application of which can be a comparison of the inputs carried out in the immigration inspection process using an integrated APK system to get maximum output in the form of fast immigration checks and accurate data because it is supported by the passenger manifest data.

“How’d you sleep?” measuring business travelers’ sleep quality and satisfaction in hotels

2018 ◽  
Vol 1 (3) ◽  
pp. 188-202 ◽  
Author(s):  
Hsiangting Shatina Chen ◽  
Kimberly Severt ◽  
Yeon Ho Shin ◽  
Adam Knowlden ◽  
Tyra W. Hilliard
Keyword(s):  
Sleep Quality ◽  
Design Methodology ◽  
Demographic Characteristics ◽  
Quality Level ◽  
Fundamental Function ◽  
Content Type ◽  
Business Travelers ◽  
The Past ◽  
Quality Scale ◽  
Business Trip

Purpose The purpose of this paper is to explore business travelers’ sleep experience in hotels by measuring sleep quality and determining the extent to which hotel attributes, demographic characteristics, and hotel quality level influence their sleep quality while staying in hotels. Design/methodology/approach This study utilized a self-reported survey to obtain data from business travelers who have stayed in a hotel at least two nights for a business trip in the past 30 days. A total of 304 business travelers were surveyed in this study. Findings The results indicated that there was a difference in the factors that influenced business travelers’ overall satisfaction with sleep in mid-scale (2.5-3.5 stars) vs upscale hotels (4+stars). The findings showed that business travelers generally had lower sleep quality at hotels and they were more likely affected by noise both outside and inside the guestroom, as well as material elements inside the room. Originality/value This study represents a pioneering attempt at exploring business travelers’ sleep quality and satisfaction with sleep in hotels. Furthermore, this study contributes to the limited research addressing sleep quality as a fundamental function of hotel services. Also, this is the first study to measure business travelers’ sleep quality in hotels by using the sleep quality scale.

Airline Passenger Marketing

2018 ◽  
pp. 273-298
Author(s):  
John G. Wensveen
Keyword(s):  
Airline Passenger
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