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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67174
Volume:
10 |
9 |
Sep 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Master of Business Administration in Operations Management and Business Analytics
Lovely Professional University
India's domestic aviation sector has expanded rapidly since its recovery from the COVID-19 pandemic, and an increasing share of this growth is occurring outside the six major metropolitan hubs. Airline network expansion decisions, however, continue to concentrate on established metropolitan airports, leaving many Tier-II and Tier-III airports comparatively under-evaluated despite demonstrating sustained passenger growth. This study addresses that gap by developing a composite, data-driven framework for evaluating the network expansion potential of India's emerging regional airports. Using official city-wise domestic passenger traffic statistics published by the Directorate General of Civil Aviation (DGCA) for the period 2021–2025, the study analyzed 62 Tier-II and Tier-III airports that satisfied defined data-availability and base-year traffic thresholds. Three indicators 2025 passenger traffic, Compound Annual Growth Rate (CAGR), and overall passenger traffic growth (2021–2025) were standardised through Min–Max normalisation and combined into a weighted Network Expansion Opportunity Index (NEOI), with respective weights of 0.40, 0.30 and 0.30. Airports were additionally classified into five Airport Traffic Tiers (ATT) based on 2025 traffic volume to support interpretation. The analysis shows that market size alone does not determine expansion potential: several medium-sized airports, including Shirdi, Guwahati, Jaipur, Trivandrum and Indore, achieved the highest NEOI scores because sustained growth complemented moderate but rising traffic bases, while some larger airports scored lower owing to slower recent growth. The findings offer airlines, airport operators and policymakers a transparent, replicable, evidence-based tool for prioritising regional network development in India's evolving domestic aviation market.
KEYWORDS
This study set out to evaluate opportunities for airline network expansion in India's emerging Tier-II and Tier-III cities using DGCA passenger traffic data for the period 2021–2025. Rather than relying on passenger traffic volume alone, the study developed and applied a composite Network Expansion Opportunity Index (NEOI) that integrates current market size with two complementary growth measures, CAGR and overall growth, standardised through Min–Max normalisation. Applied to a sample of 62 airports meeting defined screening criteria, the index identified Shirdi, Guwahati, Jaipur, Trivandrum, Indore and Lucknow as the strongest current candidates for network expansion, and showed more broadly that market size and growth momentum are only loosely coupled across India's regional airports. This finding has direct relevance to how airlines, airport operators and policymakers prioritise limited network-planning and investment resources. The NEOI offers a transparent, replicable and readily updatable methodology built entirely on publicly available official statistics, and represents a practical contribution to aviation management research on India's rapidly evolving domestic market.
Das, A. K., Bardhan, A. K., & Fageda, X. (2021). New regional aviation policy in India: Early indicators and lessons learnt. Journal of Air Transport Management. Directorate General of Civil Aviation. (2025). Traffic statistics: Domestic airlines – Passenger traffic (2021–2025). Ministry of Civil Aviation, Government of India. Iyer, K. C., & Jain, S. (2020). Breakeven passenger traffic for regional Indian airports. Transportation Research Procedia, 48, 1805–1814. https://doi.org/10.1016/j.trpro.2020.08.215 Iyer, K. C., & Thomas, N. (2020). A critical review on regional connectivity scheme of India. Transportation Research Procedia, 48, 47–59. https://doi.org/10.1016/j.trpro.2020.08.005 Ministry of Civil Aviation. (2016). National Civil Aviation Policy 2016. Government of India. Ministry of Civil Aviation. (2016). Regional Connectivity Scheme (UDAN): Scheme document. Government of India. Morton, C., & Mattioli, G. (2023). Competition in multi-airport regions: Measuring airport catchments through spatial interaction models. Journal of Air Transport Management, 112, 102457. https://doi.org/10.1016/j.jairtraman.2023.102457 Veerappan, M., Sahu, P. K., Pani, A., Patil, G. R., & Sarkar, A. K. (2020). Analysing and modelling the relationship between air freight movement and airport characteristics in India. Transportation Research Procedia, 48, 74–92. https://doi.org/10.1016/j.trpro.2020.08.007 Zachariah, R. A., Sharma, S., & Kumar, V. (2023). Systematic review of passenger demand forecasting in aviation industry. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-15552-1
Publication Date
9/10/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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