Unveiling the Nexus: Exploring Service Quality's Impact on Student Satisfaction and Loyalty in Higher Education | Chapter 07 | Recent Research Advances in Arts and Social Studies Vol. 9

 

The purpose of this research is to empirically examine and analyze the influence of Service Quality on Satisfaction and its impact on Student Loyalty. This study adopts a descriptive (survey) method with a quantitative approach design. The data used consists of primary and secondary data. The population in this study is students of the Faculty of Economics at Lancang Kuning University, with a sample size of 100 individuals adopting Slovin's proposition. The sampling technique used is non-random sampling with the Accidental Sampling method. Data analysis is conducted using Structural Equation Modelling (SEM) with the Warp PLS application. The research results indicate that there is a significant influence of the physical, reliability, and assurance dimensions on customer satisfaction, whereas responsiveness and empathy aspects are not significant. The satisfaction variable has a significant influence on loyalty. The research results also show that all dimensions and variables have positive relationships, both from the perspective of service quality on satisfaction and satisfaction on loyalty.

 

Author(s) Details :-

 

Arizal N.
Universitas Lancang Kuning, Pekanbaru, 28265, Indonesia.

 

Wita Dwika Listihana

Universitas Lancang Kuning, Pekanbaru, 28265, Indonesia.

 

Please see the book here :- https://doi.org/10.9734/bpi/rraass/v9/12298F

Forecasting Air Traffic for Indigo Airlines: An ARFIMA Approach | Chapter 8 | Science and Technology: Developments and Applications Vol. 9

Most of the time the nature of the traffic is bursty. This traffic congestion may be studied mathematically as LRD (long-range dependence) or self-similarity. The subject of the analysis is Indigo with the number of passengers travelled by Domestic flights being the focus. The analysis utilized time series data on the number of passengers traveling on Air India domestic flights from January 2012 to December 2018. The data has been taken from the Directorate General of Civil Aviation (DGCA) website. SPSS and STATA software were used for this analysis. This study fitted the time series models ARIMA and ARFIMA (or FARIMA) to flight Indian domestic flight passenger data, which exhibit self-similarity and Long Range Dependence (LRD). In this scenario, the ARFIMA model is anticipated to outperform the ARIMA model. ARIMA and ARFIMA models were applied to air traffic data and a comparison was conducted. The optimal model has been determined utilizing RMSE, MAE, and MAPE metrics. This model can effectively assess air traffic flow and optimize Indigo's services. The results show that RMSE, MAE and MAPE are lower for the ARFIMA model than ARIMA. Also, the R-squared value is greater for the ARFIMA model than ARIMA, which shows ARFIMA model is superior to ARIMA for this data. In conclusion, predictions regarding the future air traffic of Indigo domestic carriers may be made with the help of the ARFIMA model as it is beneficial for Indigo to adjust their services with the help of this study.

 

Author (s) Details

Manohar Dingari
Anurag University, Hyderabad, India.

 

V. Sumalatha
Veeranari Chakari Ilamma Women’s University, Koti, Hyderabad, India.

 

S. Hariprasad
Anurag University, Hyderabad, India.

 

S. Lavanya
Visvesvaraya College of Engineering and Technology, Hyderabad, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v9/5117

Unveiling the Nexus: Exploring Service Quality's Impact on Student Satisfaction and Loyalty in Higher Education | Chapter 7 | Recent Research Advances in Arts and Social Studies Vol. 9

The purpose of this research is to empirically examine and analyze the influence of Service Quality on Satisfaction and its impact on Student Loyalty. This study adopts a descriptive (survey) method with a quantitative approach design. The data used consists of primary and secondary data. The population in this study is students of the Faculty of Economics at Lancang Kuning University, with a sample size of 100 individuals adopting Slovin's proposition. The sampling technique used is non-random sampling with the Accidental Sampling method. Data analysis is conducted using Structural Equation Modelling (SEM) with the Warp PLS application. The research results indicate that there is a significant influence of the physical, reliability, and assurance dimensions on customer satisfaction, whereas responsiveness and empathy aspects are not significant. The satisfaction variable has a significant influence on loyalty. The research results also show that all dimensions and variables have positive relationships, both from the perspective of service quality on satisfaction and satisfaction on loyalty.

 

Author(s)details:-

 

Arizal N.
Universitas Lancang Kuning, Pekanbaru, 28265, Indonesia.

 

Wita Dwika Listihana
Universitas Lancang Kuning, Pekanbaru, 28265, Indonesia.

 

Please See the book here :- https://doi.org/10.9734/bpi/rraass/v9/12298F

Research on Time Series Analysis for Long Memory Process of Air Traffic Using ARFIMA | Chapter 1 | Recent Studies in Mathematics and Computer Science Vol. 3

 In the present study, the time series models ARIMA and ARFIMA or FARIMA models have been fitted to Air

India domestic air passengers, which considered as self similarity and Long Range Dependence (LRD). In such
case ARFIMA model is expected to be superior to ARIMA. We fitted ARIMA and ARFIMA models to air
traffic data and compared. Then the best model has been identified using RMSE, MAE and MAPE values. This
model can be useful to analyze the air traffic flow and revise the services of Air India. The analysis was carried
out using time series data on number of passengers travelling by Air India domestic flights during January 2012
to December 2018.

Author(s) Details

Manohar Dingari

Department of Mathematics, School of Technology, GITAM University, Hyderabad-502329, India.

D. Mallikarjuna Reddy
Department of Mathematics, School of Technology, GITAM University, Hyderabad-502329, India.

V. Sumalatha
Department of Statistics, OSMANIA University, Hyderabad, India.

View Book :- http://bp.bookpi.org/index.php/bpi/catalog/book/233