Opportunity-Sensing Capability and Corporate Vitality of Domestic Airlines in Nigeria

Purpose: This study examined the relationship between opportunity-sensing capability and corporate vitality of domestic airlines in Nigeria. Materials and Methods: The study adopted an explanatory cross sectional survey research design which was carried out at the organizational level of analysis. The population of this study was the nine (9) operational scheduled domestic airline operators in Nigeria. The managers involved were: Station Manager, Cabin Service Manager, Director of Airline Services, Operations Manager and Regional Manager. The study adopted the entire population as a census. The reliability of the instrument was ascertained using the Cronbach alpha reliability instrument with all items scoring above 0.70. The Spearman Rank Order Correlation Coefficient was utilized to establish the level of relationship as hypothesized with the aid of Statistical Package for Social Sciences version 23.0. Results: Findings from the study revealed a strong positive significant relationship between sensing capability and corporate vitality of domestic airlines in Nigeria. It was concluded that when domestic airlines in Nigeria deploy their opportunity sensing capability it enhances the corporate vitality especially in the dynamic business environment. Unique contribution to theory, practice and policy: It was recommended, that there is need for domestic airlines to have more business forums in order to understand the changing trends within their business operational environment and detect fundamental shifts in their industry. They should look for opportunities to improve the ways in which new knowledge is acquired, analyzed, interpreted and distributed, as well as utilized in making good corporate decisions.

1199. Decreased Human Respiratory Syncytial Virus Activity during the COVID-19 Pandemic in Japan: An Ecological Time-Series Analysis, 2014 through 2020

Background Non-pharmaceutical interventions (NPIs), such as sanitary measures and travel restrictions, aimed at controlling the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may affect the transmission dynamics of human respiratory syncytial virus (HRSV). We aimed to quantify the contribution of the sales of hand hygiene products and the number of international and domestic airline passenger arrivals on HRSV epidemic in Japan. Methods The monthly number of HRSV cases per sentinel site (HRSV activity) in 2020 was compared with the average of the corresponding period in the previous 6 years (from January 2014 to December 2020) using a monthly paired t-test. A generalized linear Poisson regression model was used to regress the time-series of the monthly HRSV activity against NPI indicators, including sale of hand hygiene products and the number of domestic and international airline passengers, while controlling for meteorological conditions (monthly average temperature and relative humidity) and seasonal variations between years (2014–2020). Results The average number of monthly HRSV case notifications in 2020 decreased by approximately 85% (P < 0.001) compared to those in the preceding 6 years (2014–2019) (Figure 1A). For every average ¥1 billion (approximately &9,000,000/£6,800,00) spent on hand hygiene products during the current month and 1 month before (lag 0-1 months) there was a 0.22% (P = 0.02) decrease in HRSV infections (Table 1). An increase of average 1,000 domestic and international airline passenger arrivals during the previous 1–2 months (lag 1–2 months) was associated with a 4.6×10−4% (P < 0.001) and 1.1×10−3% (P = 0.007) increase in the monthly number of HRSV infections, respectively. Figure 1. Monthly seasonal variations of number of HRSV activity, NPI indicators, and meteorological conditions during 2014-2020. (A) Monthly seasonal variations of number of HRSV cases per sentinel sites based on national HRSV surveillance data during 2014-2020. (B) Monthly seasonal variations of retail sales of hand hygiene products per ¥1 billion (unit: yen) during 2014-2020. (C) Monthly seasonal variations of number of domestic airline passengers per 1,000 population (unit: person) during 2014-2020. (D) Monthly seasonal variations of number of international airline passengers per 1,000 population (unit: person) during 2014-2020. (E) Monthly seasonal variations of average temperature (unit: ℃) throughout Japan during 2014-2020. (F) Monthly seasonal variations of relative humidity (unit: %) throughout Japan during 2014-2020. Table 1. Generalized linear Poisson regression model for the monthly number of human respiratory syncytial virus cases among prefectures in Japan. Conclusion This study suggests that there is an association between the decrease in the monthly number of HRSV cases and improved hygiene and sanitary measures and travel restrictions for COVID-19 in Japan, indicating that these public health interventions can contribute to the suppression of HRSV activity. These findings may help in public health policy and decision making. Disclosures All Authors: No reported disclosures

Consumer Behavior while Choosing Air Travel in India

The domestic airline industry of India has been witnessing an enormous transformation over the period. Different class of people can avail this service due to modern specifications, affordability rates, ease of reachability, frequency of flights, quality of service, etc. The recent studies depict that the number of customers opting for domestic air travel has a steep increase when compared to the past numbers. This has been possible due to increase in connectivity of different areas and reducing the flight fares to increase the accessibility and reachability for the customers. Reducing fares and increasing connectivity does not only help the customers but it has also helped a lot to contribute to the business of airlines to a very large extent. This research mainly focuses on the consumer behavior while choosing different airlines. There are multiple factors which affect while choosing the appropriate flight company for travelling. There are different class of customers and accordingly the airline companies need to match their preferences. Some consumers want affordable rates whereas some customers want better quality o service. This research will basically give an idea which factors pertain the most while choosing the perfect flight for domestic travel within India. Keywords: Quality Service, IndiGo, SpiceJet, Go Air, Air Asia, Vistara, Air India, Statista, Holidify

Perceived Interactional Justice of Service Recovery and Post-recovery Satisfaction: A Study of Domestic Airline Customers in South West Nigeria

This study examined perceived interactional justice of service recovery and post-recovery satisfaction: a study of domestic airline customers in south west Nigeria. This study adopted the perceived justice theory to service recovery with the three dimensions of justice underpinning the study’s conceptual framework/research model. Quantitative research design was employed. The unit of analysis comprised of domestic airline customers in south west geopolitical zone of Nigeria. Quota and purposive sampling were the sampling techniques and a sample of 1,998 respondents was statistically drawn using Cochran. Questionnaire was the research instrument; exploratory factor analysis through principal component extraction method was used to statistically measure construct validity while Cronbach Alpha was used to establish the reliability of the instrument. Hypothesized relationships in the path diagram resulting from the research model were tested using Partial Least Square Structural Equation Modeling (PLS-SEM) with the aid of IBM®SPSS®AMOSTM25. The finding of this study showed that interactional justice had significant and positive influence on post-recovery satisfaction. It was recommended that airline companies operating in the study area should focus more attention to interactional justice by ensuring prompt response, politeness, listening to customer’s complaints individually, and makes good efforts to tackle the complaints in a satisfactory manner.

Perceived Distributive Justice of Service Recovery and Post-recovery Satisfaction: A Study of Domestic Airline Customers in South West Nigeria

This study examined perceived distributive justice of service recovery and post-recovery satisfaction: a study of domestic airline customers in south west Nigeria. The study adopted the perceived justice theory to service recovery with the three dimensions of justice underpinning the study’s conceptual framework/research model. Quantitative research design was employed. The unit of analysis comprised of domestic airline customers in south west geopolitical zone of Nigeria. Quota and purposive sampling were the sampling techniques and a sample of 1,998 respondents was statistically drawn using Cochran. Questionnaire was the research instrument; exploratory factor analysis through principal component extraction method was used to statistically measure construct validity while Cronbach Alpha was used to establish the reliability of the instrument. Hypothesized relationships in the path diagram resulting from the research model were tested using Partial Least Square Structural Equation Modeling (PLS-SEM) with the aid of IBM®SPSS®AMOSTM25. The finding of this study showed that distributive justice had significant and positive influence on post-recovery satisfaction. It was recommended that airline companies operating in the zone should organize regular training programmes for their staff on how to work with emerging aviation technologies so as to minimize errors and reduce costs that are associated with compensation.

Prediction of Domestic Airline Tickets using Machine Learning

Airlines usually keep their price strategies as commercial secrets and information is always asymmetric, it is difficult for ordinary customers to estimate future flight price changes. However, a reasonable prediction can help customers make decisions when to buy air tickets for a lower price. Flight price prediction can be regarded as a typical time series prediction problem. When you give customers a device that can help them save some money, they will pay you back with loyalty, which is priceless. Interesting fact: Fareboom users started spending twice as much time per session within a month of the release of an airfare price forecasting feature. Considering the features such as departure time, the number of days left for departure and time of the day it will give the best time to buy the ticket. Features are extracted from the collected data to apply Random Forest Machine Learning (ML) model. Then using this information, we are intended to build a system that can help buyers whether to buy a ticket or not. We have used Random Forest Algorithm which is a popular machine learning algorithm that belongs to the supervised learning technique. It can be used for both Classification and Regression problems in ML. It is based on the concept of ensemble learning, which is a process of combining multiple classifiers to solve a complex problem and to improve the performance of the model. With that said, random forests are a strong modelling technique and much more robust than a single decision tree. They aggregate many decision trees to limit over fitting as well as error due to bias and therefore yield useful results. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them.

Encouraging Competition in Indonesia's Tourism Industry

Currently and in the future, Indonesia is still very dependent on tourism to cover the current account deficit and the national budget deficit. In fact, because the government and tourism industry players have to overcome various obstacles, it is difficult to achieve the goal of visiting tourists to Indonesia every year. Therefore, this study aims to promote tourism by increasing competitiveness. On the other hand, there are still uncoordinated relationships and sectoral egos between various ministries and local governments, which weaken competitiveness, such as lack of promotional activities, high domestic airline ticket prices, and limited number of tourist ports.The results of this study prove that the government has made a lot of efforts in developing tourism and determining 10 main destinations as tourism icons.