COMPREHENSIVE DATA ANALYTICS STUDY OF THE AIRLINE INDUSTRY FROM 2012–2020 USING TABLE AU Article Swipe

PDF

K. Nihanth , Stephen B. Harsh , Ajmeera Kiran , D O Moses ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.33564/ijeast.2025.v10i01.012

The airline industry is increasingly leveraging data-driven techniques to improve customer satisfaction, operational efficiency, and sustainability. Several studies focus on utilizing text mining, sentiment analysis, and machine learning to analyze customer feedback from social media platforms, such as Twitter, to better understand passenger experiences. Hybrid models combining lexicon-based methods with deep learning have been proposed to enhance sentiment accuracy, while methodologies for analyzing flight delays, cancellations, and safety reports have been introduced to identify operational inefficiencies. Furthermore, sustainability practices in the airline industry are explored through machine learning clustering and bibliometric analysis, providing valuable insights for airlines to improve their environmental performance. This study also highlights the importance of integrating structured flight operation data with customer sentiment data for more comprehensive insights. Additionally, the use of Tableau facilitates realtime visual storytelling, allowing stakeholders to make faster and more informed decisions. Overall, the integration of advanced data analysis methods offers significant potential to enhance airline operations and customer service while addressing sustainability challenges.

Related Topics

Concepts

Table (database) Analytics Data science Data analysis Computer science Business Data mining

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.33564/ijeast.2025.v10i01.012
PDF: https://doi.org/10.33564/ijeast.2025.v10i01.012
OA Status: diamond
References: 12
Related Works: 10
OpenAlex ID: https://openalex.org/W4412361808

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4412361808

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.33564/ijeast.2025.v10i01.012

Digital Object Identifier
Title: COMPREHENSIVE DATA ANALYTICS STUDY OF THE AIRLINE INDUSTRY FROM 2012–2020 USING TABLE AU

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2025

Year of publication
Publication date: 2025-05-01

Full publication date if available
Authors: K. Nihanth, Stephen B. Harsh, Ajmeera Kiran, D O Moses

List of authors in order
Landing page: https://doi.org/10.33564/ijeast.2025.v10i01.012

Publisher landing page
PDF URL: https://doi.org/10.33564/ijeast.2025.v10i01.012

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: diamond

Open access status per OpenAlex
OA URL: https://doi.org/10.33564/ijeast.2025.v10i01.012

Direct OA link when available
Concepts: Table (database), Analytics, Data science, Data analysis, Computer science, Business, Data mining

Top concepts (fields/topics) attached by OpenAlex
Cited by: 0

Total citation count in OpenAlex
References (count): 12

Number of works referenced by this work
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4412361808
doi	https://doi.org/10.33564/ijeast.2025.v10i01.012
ids.doi	https://doi.org/10.33564/ijeast.2025.v10i01.012
ids.openalex	https://openalex.org/W4412361808
fwci	0.0
type	article
title	COMPREHENSIVE DATA ANALYTICS STUDY OF THE AIRLINE INDUSTRY FROM 2012–2020 USING TABLE AU
biblio.issue	01
biblio.volume	10
biblio.last_page	90
biblio.first_page	82
topics[0].id	https://openalex.org/T11918
topics[0].field.id	https://openalex.org/fields/18
topics[0].field.display_name	Decision Sciences
topics[0].score	0.9071999788284302
topics[0].domain.id	https://openalex.org/domains/2
topics[0].domain.display_name	Social Sciences
topics[0].subfield.id	https://openalex.org/subfields/1803
topics[0].subfield.display_name	Management Science and Operations Research
topics[0].display_name	Forecasting Techniques and Applications
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C45235069
concepts[0].level	2
concepts[0].score	0.7000499963760376
concepts[0].wikidata	https://www.wikidata.org/wiki/Q278425
concepts[0].display_name	Table (database)
concepts[1].id	https://openalex.org/C79158427
concepts[1].level	2
concepts[1].score	0.6757125854492188
concepts[1].wikidata	https://www.wikidata.org/wiki/Q485396
concepts[1].display_name	Analytics
concepts[2].id	https://openalex.org/C2522767166
concepts[2].level	1
concepts[2].score	0.48984500765800476
concepts[2].wikidata	https://www.wikidata.org/wiki/Q2374463
concepts[2].display_name	Data science
concepts[3].id	https://openalex.org/C175801342
concepts[3].level	2
concepts[3].score	0.44442489743232727
concepts[3].wikidata	https://www.wikidata.org/wiki/Q1988917
concepts[3].display_name	Data analysis
concepts[4].id	https://openalex.org/C41008148
concepts[4].level	0
concepts[4].score	0.38677680492401123
concepts[4].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[4].display_name	Computer science
concepts[5].id	https://openalex.org/C144133560
concepts[5].level	0
concepts[5].score	0.3729901909828186
concepts[5].wikidata	https://www.wikidata.org/wiki/Q4830453
concepts[5].display_name	Business
concepts[6].id	https://openalex.org/C124101348
concepts[6].level	1
concepts[6].score	0.24321141839027405
concepts[6].wikidata	https://www.wikidata.org/wiki/Q172491
concepts[6].display_name	Data mining
keywords[0].id	https://openalex.org/keywords/table
keywords[0].score	0.7000499963760376
keywords[0].display_name	Table (database)
keywords[1].id	https://openalex.org/keywords/analytics
keywords[1].score	0.6757125854492188
keywords[1].display_name	Analytics
keywords[2].id	https://openalex.org/keywords/data-science
keywords[2].score	0.48984500765800476
keywords[2].display_name	Data science
keywords[3].id	https://openalex.org/keywords/data-analysis
keywords[3].score	0.44442489743232727
keywords[3].display_name	Data analysis
keywords[4].id	https://openalex.org/keywords/computer-science
keywords[4].score	0.38677680492401123
keywords[4].display_name	Computer science
keywords[5].id	https://openalex.org/keywords/business
keywords[5].score	0.3729901909828186
keywords[5].display_name	Business
keywords[6].id	https://openalex.org/keywords/data-mining
keywords[6].score	0.24321141839027405
keywords[6].display_name	Data mining
language	en
locations[0].id	doi:10.33564/ijeast.2025.v10i01.012
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S4210216920
locations[0].source.issn	2455-2143
locations[0].source.type	journal
locations[0].source.is_oa	True
locations[0].source.issn_l	2455-2143
locations[0].source.is_core	False
locations[0].source.is_in_doaj	False
locations[0].source.display_name	International Journal of Engineering Applied Sciences and Technology
locations[0].source.host_organization	https://openalex.org/P4360969357
locations[0].source.host_organization_name	IJEAST
locations[0].source.host_organization_lineage	https://openalex.org/P4360969357
locations[0].source.host_organization_lineage_names	IJEAST
locations[0].license
locations[0].pdf_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
locations[0].version	publishedVersion
locations[0].raw_type	journal-article
locations[0].license_id
locations[0].is_accepted	True
locations[0].is_published	True
locations[0].raw_source_name	International Journal of Engineering Applied Sciences and Technology
locations[0].landing_page_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A5118962172
authorships[0].author.orcid
authorships[0].author.display_name	K. Nihanth
authorships[0].author_position	first
authorships[0].raw_author_name	K. Nihanth
authorships[0].is_corresponding	False
authorships[1].author.id	https://openalex.org/A5030650106
authorships[1].author.orcid
authorships[1].author.display_name	Stephen B. Harsh
authorships[1].author_position	middle
authorships[1].raw_author_name	S. Harsh
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A5087336365
authorships[2].author.orcid	https://orcid.org/0000-0003-3826-4346
authorships[2].author.display_name	Ajmeera Kiran
authorships[2].author_position	middle
authorships[2].raw_author_name	A.Sai Kiran
authorships[2].is_corresponding	False
authorships[3].author.id	https://openalex.org/A5109498828
authorships[3].author.orcid
authorships[3].author.display_name	D O Moses
authorships[3].author_position	last
authorships[3].raw_author_name	Dr. Diana Moses
authorships[3].is_corresponding	False
has_content.pdf	True
has_content.grobid_xml	True
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
open_access.oa_status	diamond
open_access.any_repository_has_fulltext	False
created_date	2025-07-12T00:00:00
display_name	COMPREHENSIVE DATA ANALYTICS STUDY OF THE AIRLINE INDUSTRY FROM 2012–2020 USING TABLE AU
has_fulltext	True
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T11918
primary_topic.field.id	https://openalex.org/fields/18
primary_topic.field.display_name	Decision Sciences
primary_topic.score	0.9071999788284302
primary_topic.domain.id	https://openalex.org/domains/2
primary_topic.domain.display_name	Social Sciences
primary_topic.subfield.id	https://openalex.org/subfields/1803
primary_topic.subfield.display_name	Management Science and Operations Research
primary_topic.display_name	Forecasting Techniques and Applications
related_works	https://openalex.org/W4226266853, https://openalex.org/W4210252074, https://openalex.org/W3092201768, https://openalex.org/W2796632413, https://openalex.org/W2740083192, https://openalex.org/W2508885301, https://openalex.org/W2794907032, https://openalex.org/W4255802207, https://openalex.org/W4298181270, https://openalex.org/W4385267788
cited_by_count	0
locations_count	1
best_oa_location.id	doi:10.33564/ijeast.2025.v10i01.012
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S4210216920
best_oa_location.source.issn	2455-2143
best_oa_location.source.type	journal
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l	2455-2143
best_oa_location.source.is_core	False
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	International Journal of Engineering Applied Sciences and Technology
best_oa_location.source.host_organization	https://openalex.org/P4360969357
best_oa_location.source.host_organization_name	IJEAST
best_oa_location.source.host_organization_lineage	https://openalex.org/P4360969357
best_oa_location.source.host_organization_lineage_names	IJEAST
best_oa_location.license
best_oa_location.pdf_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
best_oa_location.version	publishedVersion
best_oa_location.raw_type	journal-article
best_oa_location.license_id
best_oa_location.is_accepted	True
best_oa_location.is_published	True
best_oa_location.raw_source_name	International Journal of Engineering Applied Sciences and Technology
best_oa_location.landing_page_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
primary_location.id	doi:10.33564/ijeast.2025.v10i01.012
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S4210216920
primary_location.source.issn	2455-2143
primary_location.source.type	journal
primary_location.source.is_oa	True
primary_location.source.issn_l	2455-2143
primary_location.source.is_core	False
primary_location.source.is_in_doaj	False
primary_location.source.display_name	International Journal of Engineering Applied Sciences and Technology
primary_location.source.host_organization	https://openalex.org/P4360969357
primary_location.source.host_organization_name	IJEAST
primary_location.source.host_organization_lineage	https://openalex.org/P4360969357
primary_location.source.host_organization_lineage_names	IJEAST
primary_location.license
primary_location.pdf_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
primary_location.version	publishedVersion
primary_location.raw_type	journal-article
primary_location.license_id
primary_location.is_accepted	True
primary_location.is_published	True
primary_location.raw_source_name	International Journal of Engineering Applied Sciences and Technology
primary_location.landing_page_url	https://doi.org/10.33564/ijeast.2025.v10i01.012
publication_date	2025-05-01
publication_year	2025
referenced_works	https://openalex.org/W4293330951, https://openalex.org/W4292428590, https://openalex.org/W2956699707, https://openalex.org/W3204582429, https://openalex.org/W4311344045, https://openalex.org/W3088719258, https://openalex.org/W3111077109, https://openalex.org/W4387940100, https://openalex.org/W4396731645, https://openalex.org/W3164180342, https://openalex.org/W2939399411, https://openalex.org/W3133280145
referenced_works_count	12
abstract_inverted_index.as	37
abstract_inverted_index.in	79
abstract_inverted_index.is	3
abstract_inverted_index.of	108, 125, 143
abstract_inverted_index.on	19
abstract_inverted_index.to	8, 28, 39, 55, 72, 97, 133, 151
abstract_inverted_index.The	0
abstract_inverted_index.and	14, 25, 66, 89, 136, 155
abstract_inverted_index.are	83
abstract_inverted_index.for	61, 95, 118
abstract_inverted_index.the	80, 106, 123, 141
abstract_inverted_index.use	124
abstract_inverted_index.This	102
abstract_inverted_index.also	104
abstract_inverted_index.been	53, 70
abstract_inverted_index.data	113, 117, 145
abstract_inverted_index.deep	50
abstract_inverted_index.from	32
abstract_inverted_index.have	52, 69
abstract_inverted_index.make	134
abstract_inverted_index.more	119, 137
abstract_inverted_index.such	36
abstract_inverted_index.text	21
abstract_inverted_index.with	49, 114
abstract_inverted_index.focus	18
abstract_inverted_index.media	34
abstract_inverted_index.study	103
abstract_inverted_index.their	99
abstract_inverted_index.while	59, 158
abstract_inverted_index.Hybrid	44
abstract_inverted_index.better	40
abstract_inverted_index.faster	135
abstract_inverted_index.flight	63, 111
abstract_inverted_index.models	45
abstract_inverted_index.offers	148
abstract_inverted_index.safety	67
abstract_inverted_index.social	33
abstract_inverted_index.visual	129
abstract_inverted_index.Several	16
abstract_inverted_index.Tableau	126
abstract_inverted_index.airline	1, 81, 153
abstract_inverted_index.analyze	29
abstract_inverted_index.delays,	64
abstract_inverted_index.enhance	56, 152
abstract_inverted_index.improve	9, 98
abstract_inverted_index.machine	26, 86
abstract_inverted_index.methods	48, 147
abstract_inverted_index.mining,	22
abstract_inverted_index.reports	68
abstract_inverted_index.service	157
abstract_inverted_index.studies	17
abstract_inverted_index.through	85
abstract_inverted_index.Overall,	140
abstract_inverted_index.Twitter,	38
abstract_inverted_index.advanced	144
abstract_inverted_index.airlines	96
abstract_inverted_index.allowing	131
abstract_inverted_index.analysis	146
abstract_inverted_index.customer	10, 30, 115, 156
abstract_inverted_index.explored	84
abstract_inverted_index.feedback	31
abstract_inverted_index.identify	73
abstract_inverted_index.industry	2, 82
abstract_inverted_index.informed	138
abstract_inverted_index.insights	94
abstract_inverted_index.learning	27, 51, 87
abstract_inverted_index.proposed	54
abstract_inverted_index.realtime	128
abstract_inverted_index.valuable	93
abstract_inverted_index.accuracy,	58
abstract_inverted_index.analysis,	24, 91
abstract_inverted_index.analyzing	62
abstract_inverted_index.combining	46
abstract_inverted_index.insights.	121
abstract_inverted_index.operation	112
abstract_inverted_index.passenger	42
abstract_inverted_index.potential	150
abstract_inverted_index.practices	78
abstract_inverted_index.providing	92
abstract_inverted_index.sentiment	23, 57, 116
abstract_inverted_index.utilizing	20
abstract_inverted_index.addressing	159
abstract_inverted_index.clustering	88
abstract_inverted_index.decisions.	139
abstract_inverted_index.highlights	105
abstract_inverted_index.importance	107
abstract_inverted_index.introduced	71
abstract_inverted_index.leveraging	5
abstract_inverted_index.operations	154
abstract_inverted_index.platforms,	35
abstract_inverted_index.structured	110
abstract_inverted_index.techniques	7
abstract_inverted_index.understand	41
abstract_inverted_index.challenges.	161
abstract_inverted_index.data-driven	6
abstract_inverted_index.efficiency,	13
abstract_inverted_index.facilitates	127
abstract_inverted_index.integrating	109
abstract_inverted_index.integration	142
abstract_inverted_index.operational	12, 74
abstract_inverted_index.significant	149
abstract_inverted_index.Furthermore,	76
abstract_inverted_index.bibliometric	90
abstract_inverted_index.experiences.	43
abstract_inverted_index.increasingly	4
abstract_inverted_index.performance.	101
abstract_inverted_index.stakeholders	132
abstract_inverted_index.Additionally,	122
abstract_inverted_index.comprehensive	120
abstract_inverted_index.environmental	100
abstract_inverted_index.lexicon-based	47
abstract_inverted_index.methodologies	60
abstract_inverted_index.satisfaction,	11
abstract_inverted_index.storytelling,	130
abstract_inverted_index.cancellations,	65
abstract_inverted_index.sustainability	77, 160
abstract_inverted_index.inefficiencies.	75
abstract_inverted_index.sustainability.	15
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	4
citation_normalized_percentile.value	0.33623931
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True