Assessment of Infrastructure and Service Supply on Sustainable Urban Transport Systems in Delhi-NCR: Implications of Last-Mile Connectivity for Government Policies

Abstract

Urban mobility plays a vital role in shaping sustainable cities, yet the effectiveness of public transportation is often undermined by poor last-mile connectivity (LMC). In the National Capital Region (NCR) of Delhi, despite the Delhi Metro Rail serving as a key transit system, limited integration with surrounding areas hinders accessibility, which particularly affects women, elderly adults, and socioeconomically disadvantaged groups. This study evaluates LMC performance at two key metro stations, Nehru Place and Botanical Garden, using a mixed-methods approach that includes user surveys, spatial survey, thematic analysis, and infrastructure scoring across five critical pillars: accessibility, safety and comfort, intermodality, service availability, and inclusivity. The findings communicate notable contrasts. Botanical Garden exhibits strong intermodal linkages, pedestrian-friendly design, and supportive signage, while Nehru Place indicates a need for infrastructural improvements, safety advancement and upgrades, and strengthened universal design features. These disparities limit effective metro usage and discourage a shift from private to public transport. The study highlights the importance of user-centered, multimodal solutions and the need for cohesive urban governance to address LMC gaps. By identifying barriers and opportunities for improvement, this research paper contributes to the formulation of more inclusive and sustainable urban transport strategies in Indian metropolitan regions.

1. Introduction

1.1. Background

The 21st century has witnessed an unprecedented surge in global urbanization, fundamentally altering the spatial and social dynamics of cities. According to the United Nations, approximately 68% of the global population is expected to reside in urban areas by 2050, up from 55% in 2018 [1]. In India, this urban transition is occurring at an even more accelerated pace. The urban population has increased from 17.29% in 1951 to over 31.6% in 2011 and is projected to reach nearly 600 million by 2030 [2]. This rapid urban growth, while economically transformative, has placed immense pressure on existing infrastructure, especially transport systems, resulting in widespread challenges such as traffic congestion, rising greenhouse gas emissions, urban sprawl, and mobility inequity. Nowhere are these challenges more evident than in the NCR of Delhi, one of South Asia’s largest and most densely populated urban agglomerations. Delhi-NCR’s economic dynamism and population boom have coincided with a sharp increase in private vehicle usage, leading to excessive fuel consumption, air pollution, and road congestion. The transport sector, dominated by motorized road transport, has become one of the primary contributors to air pollution in the region [3]. Vehicular emissions account for a significant portion of Delhi’s deteriorating air quality, a public health crisis that disproportionately affects vulnerable populations. Recognizing these challenges, policymakers have increasingly turned to sustainable urban transport systems (SUTS) as a strategic solution for ensuring environmentally sound, economically viable, and socially inclusive urban mobility. SUTS aim to facilitate efficient movement while minimizing negative externalities, such as emissions and spatial inequality. Public transport systems (PTS), particularly high-capacity modes like metro rail, Bus Rapid Transit (BRT), and suburban rail, are central to SUTS as they reduce reliance on private vehicles, alleviate congestion, and provide equitable access to mobility [4,5]. The Delhi Metro Rail, for instance, has emerged as a model of rapid mass transit in India, carrying millions of commuters daily and significantly reducing travel time and road congestion. However, the system’s effectiveness is severely compromised by one crucial weak link, LMC, which refers to the critical final segment of a commuter’s journey, connecting public transit hubs to their final destinations. In the absence of reliable and affordable LMC options, users are often discouraged from choosing public transportation, leading to an overdependence on private modes such as cars and two-wheelers. In Delhi-NCR, the lack of well-integrated LMC options such as feeder buses, e-rickshaws, safe pedestrian infrastructure, and cycle sharing systems has resulted in the underutilization of the metro and other mass transit systems, limiting the broader success of SUTS [6,7]. Informal modes of intermediate public transport (IPT), like auto-rickshaws and e-rickshaws, have partially filled this gap but often operate without proper regulation, standardization, or integration into the formal transit network [8].

The relevance of LMC becomes even more pronounced in the context of Transit-Oriented Development (TOD), a planning approach that emphasizes high-density, mixed-use development within walking distance of public transit stations. TOD strategies have been actively promoted by the Ministry of Housing and Urban Affairs (MoHUA) to reduce car dependency, encourage public transport use, and improve urban liveability [9]. However, the successful implementation of TOD hinges on seamless last-mile access, without which even well-planned transit nodes remain underutilized. Thus, LMC acts as both a precondition and an enabler for TOD and broader sustainable transport outcomes. Against this backdrop, the current study focuses on evaluating the infrastructure and service delivery systems supporting LMC in Delhi-NCR. The aim is to uncover the systemic challenges that hinder seamless integration of LMC with mass rapid transit systems (MRTS), such as the Delhi Metro, and to propose data-driven, context-sensitive strategies for enhancing urban mobility.

1.2. Research Motivation

The motivation for this research stems from the observable disconnects between investments in core public transit infrastructure and the relatively inadequate attention given to first- and last-mile connectivity. Despite considerable expansion of MRTS in Delhi-NCR, modal shifts toward PTS remain modest. A key reason is the absence of an integrated, user-oriented, and inclusive last-mile strategy that connects homes, workplaces, and other urban destinations with mass transit nodes [10]. Commuters often face unsafe walking environments, fragmented IPT services, lack of information systems, and poor interchange facilities, which collectively erode the efficiency and attractiveness of public transport. Moreover, urban sprawl has led to longer trip lengths and greater reliance on private vehicles, especially in peri-urban areas where MRTS penetration is low and LMC options are scarce [11]. This, in turn, increases the carbon footprint of urban transport and undermines efforts to promote compact, sustainable urban development. The ground transport sector in India contributes significantly to environmental externalities, including particulate matter, noise pollution, and greenhouse gas emissions [12]. In Delhi, where vehicle registration rates outpace those of major metros like Mumbai, Chennai, and Kolkata combined, addressing transport sustainability is a matter of urgent policy concern [13]. This study is therefore motivated by the need to critically assess the infrastructural and service-related enablers and barriers of last-mile connectivity in the Delhi-NCR, with the intention of strengthening the effectiveness of SUTS.

1.3. Objectives

The overarching objective of this research is to assess and improve the infrastructure and service delivery mechanisms supporting LMC within Delhi-NCR’s public transportation network. Specific objectives related to evaluating the current state of LMC infrastructure and services at selected metro stations and identifying both the key physical and operational barriers that hinder efficient multimodal integration.

1.4. Research Questions

To guide the research and study, the following research questions were designed:

• RQ1: How do infrastructure and service delivery influence the effectiveness of SUTS in Delhi-NCR, particularly in relation to LMC?
• RQ2: What are the key infrastructural and service-related gaps that hinder seamless LMC to major public transit systems like the Delhi Metro Rail?

1.5. Significance of the Study

The significance of this study lies in its ability to contribute to the growing discourse on sustainable urban mobility through an applied, policy-oriented lens [14]. While extensive research has been conducted on mass transit systems and urban form, comparatively less attention has been given to the micro-scale connectivity issues that determine how users engage with PTS. This study attempts to fill that gap by:

• Uncovering latent inefficiencies and inequities in current LMC systems.
• Providing empirical insights that can inform metro station area planning and TOD implementation.
• Supporting the design of inclusive, multimodal mobility solutions that address the needs of women and elderly, differently abled, and low-income populations.

By highlighting the interlinkages between infrastructure provision, service delivery, policy frameworks, and user behavior, the study also aims to assist government bodies, urban local authorities, and transit agencies in aligning transport planning with broader goals of sustainability, equity, and livability. Further, the paper discusses a literature review in Section 2, highlighting theoretical frameworks and global best practices related to sustainable transport, TOD, and LMC, with a focus on their relevance to the Indian urban context. Research Methodology discussed in Section 3 outlines the research design, case study approach, data collection tools (observational surveys and spatial analysis), and analytical techniques used. Section 4 explains the case study approach and represents findings from selected metro stations in Delhi-NCR, assessing infrastructure, user perceptions, and gaps in service delivery. Section 5 concludes this research study with a discussion of the findings and policy recommendations. Appendix B represents list of abbreviations.

2. Literature Review

The section summarizes research discussions concerning transportation infrastructure, rapid urbanization, LMC and sustainable transport systems to enhance public transport in Indian cities. The implemented literature review was conducted utilizing PRISMA (preferred reporting items for systematic review and meta-analysis) a methodological technique involving four main stages, identification, screening, eligibility, and inclusion [15], as represented in Figure 1. Stage 1: Identification—benchmark criteria—the initial search was conducted with platforms such as WoS, Scopus, SCI, and other appropriate sources for databases; a preliminary list of keywords and benchmark criteria were acknowledged, which included time period and the subject areas public transportation and LMC. The search was comprehensive because it used multiple synonyms (such as sustainable transport, last mile options, feeder services, and green TOD) in the keywords [15]. Stage 2: Screening—first-step and second-step screening benchmark criteria—segregation benchmarks related to duplication of papers, language, and papers from inapplicable sources. A total of 639 papers were considered for second-step screening [15]. Further, depending on the benchmark considered and the heading and abstract of the segregated paper, 301 papers moved forward to the next step. Stage 3: Eligibility—third-step screening benchmark criteria—finally, after segregating abstracts and the content of papers, 160 research papers were excluded to meet the benchmark considered for the conducted research and study [15]. Stage 4: Inclusion—benchmark criteria—we conducted the research study [15]. Finally, 137 papers were included based on the benchmarks considered for performing and completing the conducted research study. To consider applicable and appropriate research publications, we applied inclusion and exclusion benchmarks based on the PRISMA technique for the conducted research. The social, environmental, and economic aspects of sustainability were the subject of a significant percentage of the chosen articles. Optimization and scheduling issues, like service planning and truck routing, were the focus of another noteworthy cluster, policy-related titles, such as incentives, regulations, and governance and other titles that contributed directly or indirectly to the conducted research and study.

2.1. Global Perceptions of LMC

LMC is increasingly recognized worldwide as a critical element of sustainable transportation systems, especially in urban and peri-urban areas. Globally, LMC refers to the final segment of a journey that connects passengers or goods from transit hubs to their final destinations. Countries like the Netherlands and Japan emphasize integrated transport systems where bicycles, pedestrian pathways, and micro-mobility options are key enablers of efficient last-mile access [16,17,18]. In contrast, developing nations often face challenges such as inadequate infrastructure, low public investment, and safety concerns, affecting the reliability of last-mile options [19,20,21,22,23,24]. The global push toward decarbonization and urban inclusivity has brought attention to LMC as a tool to reduce car dependency, improve air quality, and enhance social equity [25]. In India, recent urban mobility policies have promoted electric rickshaws, feeder buses, and non-motorized transport for bridging last-mile gaps [26]. Meanwhile, cities in the Global South are experimenting with technology-enabled solutions like ridesharing and on demand transit to improve accessibility [27,28]. Overall, global perceptions now consider LMC not just as a logistical issue but as a critical component of holistic, sustainable urban development.

2.2. Policy Framework for Transportation System for Indian Context

India’s transportation system is a vital contributor to economic development, social integration, and sustainable urban growth. Given the nation’s rapid urbanization and increasing mobility demands, a robust and inclusive policy framework is essential to ensure efficient, safe, and environmentally sustainable transportation [29]. The National Urban Transport Policy (NUTP), introduced in 2006 by MoHUA, remains a cornerstone of India’s transport policy [30,31,32]. It emphasizes people-centric mobility, promoting public transport, non-motorized transport (NMT), and integrated multimodal systems. The policy calls for urban transport planning to focus on accessibility rather than vehicular movement, shifting the emphasis from cars to public and shared mobility options [9,11,13,33]. Recent initiatives like Smart Cities Mission, AMRUT (Atal Mission for Rejuvenation and Urban Transformation), and the National Electric Mobility Mission Plan (NEMMP) aim to integrate transport with smart infrastructure, promote electric mobility, and improve LMC [5,7,9,11,34]. These policies also emphasize Intelligent Transport Systems (ITS), sustainable TOD, and active stakeholder engagement for long-term viability [11,15,35]. However, challenges such as fragmented governance, limited public investment, inadequate public transport coverage, and poor LMC hinder implementation. To address this, the National Transit Oriented Development Policy (2017) and state-level Comprehensive Mobility Plans (CMPs) advocate integrated land use and transport planning to ensure compact, connected, and walkable cities [36]. Additionally, India’s commitments under the Paris Agreement and SDG 11 (Sustainable Cities and Communities) necessitate low-carbon and inclusive transport systems. Therefore, future transport policies must prioritize electric vehicles, multimodal integration, and universal accessibility while strengthening regulatory institutions and funding mechanisms [37,38,39,40].

2.3. An Outline of LMC and SUTS Concept

LMC and SUTS are interrelated components essential for achieving inclusive and low-carbon urban mobility [41,42,43,44,45]. LMC refers to the final leg of a commuter’s journey that connects major transit nodes (e.g., metro stations or bus terminals) to their final destination. Effective LMC solutions include NMT, electric rickshaws, shared mobility services, and pedestrian-friendly infrastructure [11,13,15,46,47,48,49,50,51]. Globally, LMC is seen as a strategic tool to increase public transport ridership and reduce reliance on private vehicles [5,8,9,15,20,52,53,54,55,56]. On the other hand, SUTS encompass transport strategies that aim to minimize environmental impacts, enhance social equity, and ensure economic viability [57]. Core principles of SUTs include integrated land use and transport planning, promotion of public transit, support for NMT, low-emission vehicle technologies, and inclusive design [58]. In the Indian context, the synergy between LMC and SUTS is crucial for addressing challenges such as traffic congestion, air pollution, and urban sprawl. Policies like the National Urban Transport Policy (MoHUA, 2014) and National Electric Mobility Mission Plan recognize the importance of LMC in making mass transit systems more effective and sustainable. Indian cities are increasingly incorporating electric feeder vehicles, bicycle-sharing systems, and walkability enhancements as part of broader SUTS frameworks [59,60,61,62,63,64,65]. Ultimately, achieving sustainable urban mobility requires the seamless integration of LMC within multimodal urban transport systems. This integration can significantly improve accessibility, reduce carbon footprints, and contribute to more resilient and livable cities.

2.4. Challenges and Barriers to LMC

LMC plays a vital role in the effectiveness of urban transport systems by bridging the gap between transit hubs and passengers’ final destinations. Despite its significance, LMC faces multiple challenges and barriers, particularly in developing nations like India [66,67,68,69]. One of the primary barriers is infrastructure inadequacy. Most Indian cities lack dedicated pedestrian pathways, cycling tracks, and safe zones for intermediate public transport (IPT), making last-mile travel unsafe and inconvenient (MoHUA, 2014). Poorly maintained roads, encroachments, and inadequate lighting further discourage NMT and increase reliance on informal and unsustainable modes of transport [70,71,72,73,74,75].

Another major issue is fragmented governance and lack of institutional coordination. Urban mobility systems are often managed by multiple authorities with overlapping responsibilities, resulting in inefficient planning and execution of LMC solutions (NITI Aayog, 2021) [76,77,78,79]. This leads to unregulated IPT services, limited integration with mass transit systems, and poor service quality. Affordability and accessibility also present significant challenges [80,81,82]. Last-mile services like e-rickshaws or shared autos may be unaffordable for economically weaker sections of the population, especially in peri-urban areas [3,11,83]. Moreover, these modes often lack inclusivity for people with disabilities and the elderly. Environmental and traffic concerns arise from the unregulated growth of motorized LMC modes, leading to increased congestion, noise, and emissions [84,85,86,87]. While electric mobility is emerging as a solution, lack of charging infrastructure and high initial costs restrict its widespread adoption [3,9,14,19,88]. Furthermore, behavioral barriers such as public preference for private vehicles due to perceived comfort and reliability limit the effectiveness of LMC interventions. To overcome these barriers, cities need integrated planning, regulatory reforms, investment in NMT infrastructure, and promotion of electric, inclusive, and safe LMC systems [89,90,91,92].

In connection with the research, we outline researchers, regulatory bodies, and frameworks for reviewing and analyzing notable aspects correlated with LMC by interpreting findings, indicating needs, describing incorporation programs, establishing the taxonomy of LMC, and locating variance in existing approaches, policies, and incorporation plans. Similarly, it was identified that there is insufficient discussion on confirming the necessity of establishing the LMC boundary [93,94,95,96,97,98,99,100,101,102]. It is of the foremost concern to outline the users for whom we plan to implement LMC [5,11,23,103,104,105,106,107,108,109,110]. The distinctive influence zones from the MRTS corridor are anticipated to have varied development patterns concerning LMC planning [12,24,34,45,76,111,112,113,114,115,116,117]. In a global context, LMC has been observed as a sustainable measure [89,97,118,119,120,121,122,123]. Post implementation assessments in several contexts have observed that the application of LMC has addressed the contextual issues of carbon footprint, congestion, vehicular emissions, pollution levels, and fatalities [32,41,49,124,125,126,127,128]. This, in turn, has increased MRTS ridership, reducing private vehicle operation [10,15,22,129,130,131]. Several policies adopted in India comprise the application of sustainable transport modes like NMT and e-transit vehicles as a program under the umbrella of LMC policy [62,76,82,97,100]. It also includes the implementation of pedestrianization and cycling infrastructure as initiatives [104,109]. Still, there is a gap in the point of identification of the type and scale of the survey to be undertaken for a system [4,7,15,22,37,54,78,84,108,111,127,132,133,134,135]. Other concerns include the involvement of stakeholders as a part of the project at different levels [118,121,133]. The funding of any enforced project rests on user requirement and especially on long-term infrastructural funding and expenditure. The importance of LMC as a critical component of sustainable urban mobility has been increasingly recognized in both academic and policy discourses. In the context of MRTS, inadequate integration with surrounding transport and pedestrian networks often undermines accessibility, leading to reduced ridership potential [103,109,121]. Recent empirical studies have demonstrated that LMC quality significantly influences mode choice, commuter satisfaction, and environmental outcomes [99,105,127]. In India, research has highlighted the unique challenges posed by high population density, mixed land-use patterns, and fragmented public transport governance structures [114,121]. These conditions necessitate localized solutions that go beyond infrastructural interventions to include service quality, safety, and affordability.

Recent contributions have refined the understanding of LMC in the Indian metro context:

• Ref. [134] investigated the integration of metro systems with e-rickshaw networks in Kolkata, finding that formalizing feeder services through licensing and designated stands reduced transfer times by 18% and improved commuter satisfaction scores by 0.4 points on a 5-point scale. The authors emphasize governance coordination between municipal authorities and metro corporations as a precondition for sustainable LMC.
• Ref. [135] developed a multi-criteria evaluation framework for LMC in Bengaluru, incorporating accessibility, intermodality, safety, and environmental impact. Using Analytic Hierarchy Process (AHP) weighting, they identified safety and reliability as the most influential factors for commuters, accounting for 42% of the total decision weight.
• Ref. [136] examined the performance of last-mile bicycle sharing programs integrated with the Delhi Metro. They found that stations with better protected cycling lanes and real-time bike availability information had 27% higher adoption rates compared to stations without such facilities. The study underlines the role of NMT infrastructure in enhancing LMC quality.

These recent studies underscore the need of a comprehensive index-based approach for evaluating LMC, combining both user perception and service characteristics. They also reinforce the importance of context-sensitive solutions, particularly in multi-modal urban environments such as Delhi-NCR.

2.5. Analytical Approaches in LMC Research

Recent research on LMC has moved beyond descriptive assessments toward data-driven, multi-criteria, and equity-focused analytical methods. This evolution reflects the growing complexity of urban mobility systems, where efficiency, inclusivity, and sustainability must be evaluated as an integrated manner. One significant development is the incorporation of Explainable Artificial Intelligence (XAI) techniques to address gender and demographic equity in micromobility. For instance, Ref. [137] applied XAI to bike-sharing usage data to uncover hidden gender disparities, enabling targeted service redesign without compromising interpretability. Similarly, explainable Data Envelopment Analysis (DEA) has been used to assess operational efficiency in public transport origin–destination (OD) pairs [138], offering transparent performance benchmarking that can be adapted for LMC evaluation.

Equity considerations have also expanded to include vertical transport accessibility within transit stations. Ref. [139] assessed the equity of escalator and elevator provision in subway systems, providing a methodology that can be extended to LMC environments to ensure barrier-free intermodal transfers. These combine objective service reliability indicators (e.g., turnover rate, dwell time, and frequency) with subjective user satisfaction metrics in a unified scoring framework. Such approaches align with transport agencies’ shift toward evidence-based policymaking and address the limitations of purely perception-based studies. In the Indian context, emerging work on Accessibility, Safety, Intermodality indices [140,141] demonstrates the value of indicator disaggregation reporting sub-scores for each dimension to identify targeted interventions. This aligns with the present study’s move toward transparent, Indicator level scoring and statistical validation. By integrating these state-of-the-art methods, particularly XAI for equity analysis, explainable DEA for efficiency benchmarking, and disaggregated accessibility, safety, and intermodality scoring future LMC research, in Delhi NCR, we can achieve both greater scientific rigor and direct policy relevance.

3. Research Methodology

This section outlines the methodological framework adopted for assessing the infrastructure and service supply in SUTS, with a focus on the implications of LMC for government policy in Delhi-NCR. The methodology is designed to provide a comprehensive, multi-scalar, and evidence-based evaluation of LMC through a combination of qualitative and quantitative methods, case study analysis, and geospatial tools. This mixed-methods approach ensures a deeper understanding of user experiences, infrastructural gaps, and policy frameworks.

Research Design

The study employs an exploratory and evaluative case study design using mixed methods to capture the complexity and multi-dimensionality of LMC. It combines empirical data from user surveys and geospatial mapping with policy analysis to triangulate findings. The study integrates a macro-level policy context with micro-level user behavior and infrastructural assessments to identify actionable policy gaps and opportunities. The considered design allows for the following:

• A detailed understanding of spatial and infrastructural characteristics of LMC zones;
• Ground-level insights from public transport users;
• Evaluation of transport services and amenities using measurable indicators;
• Policy recommendations tailored to real-world conditions.

4. Case Study Approach

To ensure contextual relevance and depth, this study uses a multiple case study approach focusing on two metro stations in the Delhi-NCR, Botanical Garden Metro Station (Noida, Figure 2) and Nehru Place Metro Station (Delhi, Figure 3). The selected stations are located on different lines of the metro network and parameters such as station typology (interchange, mid-block, and terminal), ridership, density and type of land use in the surrounding vicinity, and the number and type of last mile mode options available to users were considered in selecting the stations. A station typology was developed based on the average daily ridership handled by the stations. The typology was developed so that case stations with different ridership were considered, as it has been observed in Indian cities that last mile supply, mostly demand-driven at present, varies across high-, medium- and low-ridership stations. A variety of factors affect travel choices between public and private transport such as accessibility, convenience, comfort, and safety. Private modes offer several advantages in terms of demand mobility, comfort, status, privacy, speed (not necessarily), and convenience [12,40,80]. These stations were selected based on criteria such as both the metro stations acting as multimodal transit hubs with high passenger footfall, representing a diverse spatial spread across Delhi-NCR (Delhi, Haryana, and Uttar Pradesh). It has the presence of TOD potential or ongoing initiatives with differing socio-economic, land-use, and governance contexts that impact LMC performance. The diversity among the selected stations ensures that the findings are not only locally relevant but also scalable to other Indian urban contexts facing similar challenges.

4.1. Data Collection Methods

A combination of primary and secondary data collection methods was employed to comprehensively assess the infrastructure and user experience for last-mile connectivity (LMC). In line with standard sampling approaches for large populations, the target sample size was determined using Cochran’s formula for an infinite population, yielding approximately 385 respondents per station at a 95% confidence level and ±5% margin of error. In reference to target sample size, 500 respondents per station were surveyed (detailed questionnaire listed in Appendix A). Based on reliability, dependency, significance, definitiveness, and authenticity, samples of 385 respondents per station were considered for the analysis performed in the research study. The sample size of 770 respondents was chosen based on the ridership volumes and catchment population sizes of the two selected metro stations, Nehru Place and Botanical Garden, which are among the busiest stations within Delhi-NCR but serve distinct demographic and land-use contexts. Nehru Place Metro Station, located in a dense commercial hub of South Delhi, experiences a high daily ridership averaging around 60,000 to 80,000 passengers, predominantly office workers and visitors. Botanical Garden Station, situated in Noida with a mixed residential and commercial catchment, sees an average ridership of approximately 40,000 to 50,000 daily commuters, including residents and students. Considering the practical constraints of time and resources, surveying 100 users per station was deemed sufficient to capture a representative cross-section of daily commuters, especially during peak and off-peak periods. This approach enabled the capture of diverse user experiences while maintaining a manageable data collection and analysis workload. Given the ridership scale and the heterogeneous user base, this sample size allowed for preliminary assessment of LMC challenges relevant to the respective catchment populations. However, since these stations only represent specific segments of Delhi-NCR’s vast urban and transit landscape, the findings should be interpreted as indicative rather than fully generalizable to the entire region.

4.1.1. Primary Data Collection

(a)

Demographic and Travel Characteristics of Respondents

A structured Last-Mile User Survey (

Table 1. Cross-tabulated distribution of respondents by station (N = 770; Botanical Garden = 385, Nehru Place = 385).

Variable	Category	Botanical Garden (Nos.)	Nehru Place (Nos.)
Gender	Male	208	200
	Female	177	185
Age Group	18–24 years	108	96
	25–34 years	138	147
	35–44 years	77	85
	45+ years	62	57
Occupation	Student	85	69
	Service/Job	162	169
	Business/Self-employed	77	85
	Homemaker/Other	61	62
Monthly Household Income	<₹25,000	77	69
	₹25,000–₹50,000	131	135
	₹50,000–₹75,000	100	108
	>₹75,000	77	73
Travel Purpose	Work/Business	177	185
	Education	69	61
	Leisure/Shopping	100	108
	Other	39	31
Usual Last-Mile Mode	E-rickshaw	135	135
	Auto-rickshaw	100	100
	Walk	77	77
	Cycle/Bike	38	38
	Public Bus	35	35

) was designed to capture key attributes such as demographic profile, trip characteristics, mode choice behavior, travel purpose, and perceived challenges in accessing or egressing the metro. The questionnaire included both closed-ended questions (covering frequency, mode preference, affordability, and safety ratings) and open-ended items (to capture qualitative feedback on infrastructure gaps, service quality, and user expectations). To ensure diversity, respondents were selected through systematic random sampling within the station influence zone during peak and off-peak periods. The survey themes focused on mode choice such as e-rickshaw, auto-rickshaw, walking, IPT, public bus, and personal modes. The survey also discussed the trip purpose and frequency for work, education, leisure, and other trip purposes, along with travel time and distance from station to destination. Also, the survey collected users’ perceptions about safety (including gender-sensitive concerns), convenience, and affordability. This structured approach ensured comprehensive coverage of LMC determinants across multiple socio-economic strata, thereby providing a robust empirical basis for subsequent analytical modeling.

(b)

Field Observation and Infrastructure Survey

To complement the user survey and provide an objective understanding of the existing last-mile infrastructure, detailed field observations and infrastructure surveys were carried out within the 400–500 m influence zone of each selected metro station, following Transit-Oriented Development (TOD) principles and pedestrian planning guidelines recommended by MoHUA and NCRPB. The purpose of this survey was to evaluate the physical condition, functionality, and spatial integration of infrastructure elements supporting last-mile connectivity (LMC). The survey systematically assessed a comprehensive set of parameters grouped under five thematic dimensions like pedestrian infrastructure, availability, continuity, and surface quality of sidewalks; presence of tactile guiding paths; adequacy and safety of pedestrian crossings; and universal accessibility features such as ramps for differently abled users. Data collection utilized a geo-tagged evidence-based approach, involving photographic documentation, short video captures, and GPS-based annotations to map key problem areas. Additionally, a qualitative assessment checklist was used to rate infrastructure against performance standards. This exercise enabled the identification of infrastructural gaps that directly influence mode choice and user experience for last-mile travel. The findings from these surveys provided essential inputs for the infrastructure scoring matrix and formed the basis for targeted recommendations.

4.1.2. Secondary Data Collection

To strengthen the reliability and contextual validity of the primary data, extensive secondary data sources were incorporated into the research framework. These secondary datasets served multiple purposes, validating field observations, supporting statistical interpretation, and aligning findings with prevailing policy frameworks. The sources were drawn from four broad categories. First, policy documents provided the strategic and regulatory context for last-mile connectivity assessment. These included the National Urban Transport Policy (NUTP), which emphasizes sustainable and integrated transport solutions; the MoHUA Transit-Oriented Development (TOD) Guidelines, which outline spatial and design standards for enhancing last-mile accessibility; the Delhi Master Plan 2041 (MPD-2041), which sets long-term urban mobility targets; and Smart City Mission reports, which detail implementation strategies for digital and physical mobility integration. Second, transport-related datasets were collected from credible government sources to capture ridership and network-level characteristics. Daily and monthly ridership data were obtained from the Delhi Metro Rail Corporation (DMRC), while traffic volume counts, modal share statistics, and feeder network details were extracted from the Delhi Transport Department and NCR Planning Board. These datasets were crucial in understanding passenger volumes, last-mile demand patterns, and intermodal connectivity gaps. Third, a comprehensive review of academic and technical literature was undertaken to ensure the study aligned with global practices and theoretical foundations. Peer-reviewed journals, technical reports, and conference proceedings addressing themes such as urban mobility, performance assessment of last-mile connectivity systems, and sustainable transportation planning in Indian metropolitan contexts were systematically analyzed. This review informed the selection of indicators and methodological approaches, ensuring conceptual rigor. Finally, spatial datasets and GIS layers were procured to facilitate spatial analysis and mapping exercises. These included digital road network data, land-use zoning maps, and demographic layers, all sourced from the NCR Planning Board and municipal GIS portals. These layers enabled precise catchment delineation, accessibility analysis, and visualization of infrastructure gaps within 500 m and 800 m influence zones of the selected metro stations. This multi-source integration established a robust methodological framework, allowing for triangulation of evidence and improving the validity of the research findings by combining policy directives, operational data, scholarly insights, and spatial intelligence.

4.2. Spatial Analysis

Spatial analysis was an integral component of this study, providing a geospatial perspective on accessibility, connectivity, and infrastructure readiness within the metro station influence areas. The analysis was performed using QGIS and Google Earth Pro, leveraging both primary geo-referenced data and secondary GIS layers obtained from municipal and regional planning authorities. The spatial analysis framework encompassed the following key elements: mapping of 500 m and 800 m walkable catchment zones around each metro station, overlay of land-use patterns, road hierarchy, and built environment density to assess TOD readiness, identification of physical barriers (e.g., highways, walls, vacant plots) affecting accessibility, and service area analysis for e-rickshaws and feeder buses using network analysis tools. These spatial insights (

Table 2. Spatial Analysis of the selected metro stations.

	Nehru Place TOD Zone	Botanical Garden TOD Zone
Location/Metro Line	Violet Line (Line 6), Nehru Place, South Delhi.	Blue Line (Line 3) which connects Dwarka in Delhi to Noida City Centre in Noida.
Connectivity	Nehru Place metro station connects two or more different metro lines, allowing passengers to transfer between them.	Botanical metro station serves as an important transportation hub, connecting Noida with other parts of Delhi and the NCR.
Station Typology	Nehru Place metro Serves as an interchange station in Delhi Metro, as an interchange point between the Violet Line (Line 6) and the Magenta Line (Line 8) of the Delhi Metro network.	Botanical metro station also serves as an interchange station with the Aqua Line of the Noida Metro. This interchange allows passengers to switch between the Blue Line and the Aqua Line, enhancing connectivity within Noida.
Land Use	Nehru Place metro station is surrounded by a major commercial and business center in Delhi. The area is known for its IT markets, shopping complexes, and office spaces.	Botanical metro station is surrounded by residential areas, commercial complexes, educational institutions, and parks. It serves as a convenient transportation option for people living or working in the vicinity.
Catchment Area/TOD ZONE

) helped validate findings from field surveys and informed design-level interventions.

4.3. Station-Wise Comparative Analysis

A comparative analysis of Nehru Place and Botanical Garden metro stations was conducted to identify similarities and differences in their last-mile connectivity performance. This analysis was based on 770 user responses (385 per station), field survey findings, and GIS-based assessments. Nehru Place metro station, situated within a dense commercial district in South Delhi, caters to high office commuter volumes (60,000–80,000 daily). The station precinct experiences intense IPT activity and high pedestrian flows, often resulting in conflicts between transport modes. Infrastructure for pedestrian safety and organized NMT movement is limited, compounded by inadequate signage and congested feeder points, whereas Botanical Garden Metro Station, located in Noida, serves a more balanced catchment comprising residential, institutional, and commercial land uses. While the station precinct is comparatively spacious and better planned, gaps persist in seamless multimodal integration, particularly for shared IPT services. The comparative evaluation was structured across four analytical components:

(a)

Thematic Analysis Descriptive—open-ended user responses and qualitative field observations were coded into recurring themes such as convenience, safety, affordability, and service reliability. This provided interpretative depth beyond quantitative metrics.

(b)

Descriptive Statistics—statistical summaries highlighted differences in demographic profiles, travel purposes, last-mile mode choices, and expenditure patterns across the two stations. Cross-tabulations and frequency distributions facilitated a nuanced understanding of user segments.

(c)

Infrastructure Scoring Matrix—a standardized scoring framework assessed station performance across multiple LMC indicators such as walkability, affordability, accessibility, safety, and integration. Results indicated that Nehru Place scored higher in IPT availability but lagged in pedestrian comfort, whereas Botanical Garden performed better in safety and infrastructure quality, based on the infrastructure scoring matrix using standardized indicators across five thematic pillars as represented in

Table 3. Analytical insights: metro stations.

Parameter	Indicator	Nehru Place (5)	Botanical Garden Score (5)	Mean
Accessibility (Indicator I)	Footpath width and continuity	4.2	4.5	4.35
	Availability of ramps	4.0	4.4	4.20
	Pedestrian crossings	4.1	4.3	4.20
Inclusivity (Indicator II)	Gender-sensitive infrastructure	2.3	2.8	2.55
	Facilities for differently abled	2.0	2.6	2.30
	Availability of seating/waiting areas	1.9	2.5	2.20
Safety and Comfort (Indicator III)	Street lighting	2.5	2.8	2.65
	Crowd management	2.2	2.9	2.55
	CCTV surveillance	2.0	2.6	2.30
Intermodality (Indicator IV)	Integration with IPT	2.0	2.5	2.25
	Signage clarity	2.1	2.4	2.25
	Feeder bus connection quality	1.8	2.2	2.00
Service Availability (Indicator V)	Frequency of last-mile services	4.0	4.3	4.15
	Service coverage zones	4.1	4.4	4.25
	Fare integration	4.0	4.2	4.10

.

(d)

SWOT Analysis—a structured SWOT framework captured strategic strengths (e.g., high IPT availability), weaknesses (e.g., encroachment and bottlenecks), opportunities (e.g., app-based shared mobility), and threats (e.g., rising congestion) for each station represented in

Table 4. Comparative analysis of selected metro stations.

Metro Station	Nehru Place	Botanical Garden
Strengths	Proximity to commercial hub, good IPT presence	Strong intermodal integration, wider walkways, active CCTV, TOD surroundings
Weaknesses	Poor lighting, weak universal access, gender-insensitive design, crowding	Fare affordability issues, lack of shaded walkways in certain zones
Opportunities	Smart redesign of footpaths; integrated fare systems; female safety audits	MaaS platforms, expanded feeder coverage
Threats	Unchecked encroachment, user shift to private modes	Overcrowding due to TOD growth; pricing barriers for low-income groups

.

4.4. Comparative Statistical Analysis of LMC Indicators

The statistical analysis component was designed to quantitatively evaluate the relationships among multiple last-mile connectivity (LMC) indicators and identify key factors influencing user satisfaction across the two selected metro stations. Given the large dataset of 770 respondents (385 per station), the analysis involved the correlation analysis. Based on the collected data and qualitative–quantitative survey applying 5-point Likert scales, an attempt was made to find the significance of relationships between the indicators by developing two (02) research propositions, which are discussed further in this section. The conducted study tried to test the following developed research propositions (RP), as represented in

Table 5. (a) RP-01 correlation analysis (correlation coefficient r). (b) RP-01 correlation analysis (correlation coefficient r).

(a)
	Accessibility Indicator I	Safety and Comfort Indicator II	Intermodality Indicator III	Service Availability Indicator IV	Inclusivity Indicator V
Accessibility Indicator I	1	0.30	0.20	0.25	0.90
Safety and Comfort Indicator II	0.30	1	0.35	0.40	0.25
Intermodality Indicator III	0.20	0.35	1	0.45	0.20
Service Availability Indicator IV	0.25	0.40	0.45	1	0.30
Inclusivity Indicator V	0.90	0.25	0.20	0.30	1
(b)
	Accessibility Indicator I	Safety and Comfort Indicator II	Intermodality Indicator III	Service Availability Indicator IV	Inclusivity Indicator V
Accessibility Indicator I	1	0.25	0.15	0.20	0.95
Safety and Comfort Indicator II	0.25	1	0.30	0.30	0.20
Intermodality Indicator III	0.15	0.30	1	0.40	0.15
Service Availability Indicator IV	0.20	0.30	0.40	1	0.25
Inclusivity Indicator V	0.95	0.20	0.15	0.25	1

a,b:

RP-01: Indicator I has a significant relationship with Indicators II, III, IV, and V for both the metro stations.

RP-02: Indicator II has a significant relationship with Indicators I, III, IV, and V for both the metro stations.

4.4.1. Statistical Analysis (RP-01) of LMC Indicators for Nehru Place Metro Station

The observation interpretation based on the correlation analysis applied for RP-01 and represented in Table 5a is as follows:

• The strong correlation between accessibility and inclusivity (0.90) confirms the design and infrastructure-driven inclusivity principle—stations with wide footpaths, ramps, and continuous pedestrian networks naturally enable gender-sensitive and accessible facilities.
• The weak correlations with intermodality (0.20) and service availability (0.25) indicates that physical access improvements alone do not guarantee operational integration. In other words, a well-designed approach to universal access must be complemented by systemic improvements in IPT integration and last-mile services.
• The moderate correlation with safety (0.35–0.40) suggests that safe, accessible routes encourage more walking and NMT adoption, but improvements in street lighting and CCTV are equally necessary to fully realize benefits.

4.4.2. Statistical Analysis (RP-01) of LMC Indicators for Botanical Garden Metro Station

The observation interpretation based on the correlation analysis applied for RP-01 and represented in Table 5b is as follows:

• The extremely strong correlation between accessibility and inclusivity (0.95) reinforces the critical role of barrier-free infrastructure in promoting universal access. This indicates that improvements such as wide walkways, tactile paths, and ramps are highly linked to inclusive measures for differently abled users and gender-sensitive design.
• The weak correlation of accessibility with intermodality (0.15) and service availability (0.20) signals a clear disconnect between physical access and multimodal integration or service reliability. While users can access the station easily, their ability to seamlessly transfer to other modes (e-rickshaws, feeder buses, etc.) remains insufficient without better scheduling and wayfinding systems.
• The moderate correlation between service Availability and intermodality (0.40) suggests that improvements in feeder services and shared mobility options can significantly enhance multimodal connectivity. However, the low values across other pairs point toward systemic gaps.
• Safety shows only weak-to-moderate correlations with other indicators (0.25–0.30), indicating that current safety measures (lighting, surveillance, and public visibility) are not strongly aligned with accessibility or inclusivity improvements. To ensure last-mile adoption, safety interventions—such as woman-friendly IPT services and CCTV coverage—must complement physical access upgrades.

4.4.3. Statistical Analysis (RP-02) of LMC Indicators for Nehru Place Metro Station

The observation interpretation based on the correlation analysis applied for RP-02 and represented in Table 5a is as follows:

• The strongest RP-02 correlation is with service availability (r = 0.40). A practical takeaway is that tightening operational reliability (predictable e-rickshaws/feeder buses, orderly pick-up bays, crowd management, etc.) can meaningfully lift perceived safety/comfort.
• Accessibility (r = 0.30) and intermodality (r = 0.35) exhibit complementary but secondary effects on safety: well-lit, obstruction-free footpaths and clearer interchange cues help people feel safer, yet operations still matter more.
• Inclusivity (r = 0.25) rises with safety but only weakly. Universal design upgrades (tactile paving, ramps, priority seating) should be advanced in parallel rather than be assumed to “ride along” with safety works.

4.4.4. Statistical Analysis (RP-02) of LMC Indicators for Botanical Garden Metro Station

The observation interpretation based on the correlation analysis applied for RP-02 and represented in Table 5b is as follows:

• All RP-02 correlations are weak and positive (r = 0.20–0.30)—unlike Nehru Place, operational/service fixes by themselves are unlikely to move safety perceptions much.
• Accessibility’s correlation with inclusivity is very strong (r = 0.95), but accessibility/inclusivity were barely connected to intermodality/service (r = 0.15–0.25). In short, excellent infrastructure ≠ safe feeling when interchange/curbside spaces are chaotic.
• Uplifting safety at Botanical Garden likely hinges on qualitative environment controls (crowd management, enforcement, and surveillance coverage in high-conflict curb zones), not just “more service.”

4.4.5. Comparative Insights Across Stations

The comparative correlation analysis of the two selected metro stations—Nehru Place and Botanical Garden—reveals distinct patterns in the interrelationships among the five thematic indicators: accessibility (Indicator I), safety and comfort (Indicator II), intermodality (Indicator III), service availability (Indicator IV), and inclusivity (Indicator V). These indicators collectively represent the multidimensional nature of last-mile connectivity performance. For Nehru Place metro station, the correlation matrix shows a very strong association between accessibility and inclusivity (r = 0.90), highlighting that improved physical access in the station’s high-density commercial environment tends to directly enhance inclusivity features such as universal design and gender-sensitive infrastructure. Moderate positive correlations are observed between safety and comfort and service availability (r = 0.40) and between intermodality and service availability (r = 0.45), underscoring that reliability and multimodal integration are critical for stations with heavy pedestrian congestion and IPT clustering. The relationship between accessibility and safety and comfort is weaker (r = 0.30), suggesting that accessibility improvements alone do not guarantee enhanced perceptions of safety in such a crowded environment. Overall, the Nehru Place data patterns suggest operational integration and safety interventions are pivotal alongside accessibility measures. Conversely, at Botanical Garden metro station, which functions as a major multimodal interchange in a mixed-use urban context, the correlation between accessibility and inclusivity is even stronger (r = 0.95), indicating near-complete overlap in user perceptions of these two dimensions. This reflects the dominance of structural accessibility features in shaping inclusive mobility for residential and institutional users in Noida. However, correlations among the remaining indicators are slightly weaker than those at Nehru Place—for example, safety and comfort with service availability (r = 0.30) and intermodality with service availability (r = 0.40)—which suggests that, while multimodal coordination exists, its perceived reliability is not as critical to user satisfaction as in Nehru Place. The weak correlation between intermodality and inclusivity (r = 0.15) further indicates that, while the station integrates modes physically, its design does not fully address the needs of vulnerable users, particularly during peak interchange flows. In summary, both stations demonstrate a structural dominance of accessibility and inclusivity as highly interdependent constructs, while operational factors such as service availability and intermodality exhibit variable influence based on station typology. Nehru Place requires operational and safety-centric interventions, whereas Botanical Garden demands design refinements for inclusivity and multimodal coherence. These patterns validate the multidimensionality of LMC performance, reinforcing the need for context-sensitive strategies in transit-oriented development zones.

4.5. Ethical Considerations

• Respondents were informed about the purpose of the study and gave verbal consent before participating in the survey.
• Anonymity and confidentiality of user data were ensured.
• Sensitive questions (e.g., safety, harassment, etc.) were asked with caution and with an opt-out clause.

This study adhered to established ethical norms for conducting research involving human participants, particularly in the context of public space and transport infrastructure assessments. All survey respondents were fully informed about the purpose and scope of the research before participating. Verbal consent was obtained prior to data collection, ensuring that participation was entirely voluntary. Respondents were also assured that their responses would remain anonymous and that all personal data would be treated with strict confidentiality. No identifiable information was recorded or disclosed during any phase of the research. Special sensitivity was exercised while addressing topics related to personal safety, harassment, or perceived threats in the transit environment—respondents were given the option to skip any questions they were uncomfortable answering. These ethical safeguards ensured that the research respected the dignity, rights, and privacy of all individuals involved, while also upholding data integrity and transparency in reporting.

4.6. Research Limitations and Future Recommendations

While this study provides valuable insights into the state of LMC across key metro stations in Delhi-NCR, several limitations should be acknowledged. First, the research is geographically limited to four stations, Nehru Place, Botanical Garden, HUDA City Centre, and Neelam Chowk Faridabad, which, although diverse in typology, may not represent the full spectrum of metro stations across the region. The findings may thus have limited generalizability beyond these specific urban contexts. Second, data collection was constrained by time and resource availability, which affected the sample size of user surveys and the depth of observational surveys. As a result, seasonal and peak-hour variations in travel patterns, particularly in adverse weather or festival conditions, were not captured. Additionally, subjectivity in qualitative responses—such as perceptions of safety or comfort—may have introduced bias, despite efforts to triangulate them with observational data. Third, the infrastructure scoring system, while standardized across stations, was inherently influenced by field-level judgments and visual assessments. Although efforts were made to ensure consistency, certain dimensions like signage clarity or lighting adequacy could vary based on the time of survey or the auditor’s perspective. Also, some indicators such as fare integration or service reliability were difficult to quantify consistently across transport modes due to the fragmented nature of data provided by IPT operators or municipal agencies.

Finally, the study’s emphasis on physical infrastructure and service quality does not fully account for institutional and governance factors such as policy enforcement, budgeting constraints, or inter-agency coordination, which significantly shape the success of LMC systems. Future research could address these gaps through longitudinal tracking, inclusion of private-sector service providers, or broader stakeholder engagement, including policymakers and local resident associations.

5. Conclusions and Discussion

This study critically examined the infrastructural and service performance dimensions influencing LMC in the Delhi-NCR urban transport ecosystem, focusing on two metro stations, Nehru Place and Botanical Garden. Using a combination of user surveys, spatial surveys, and comparative infrastructure scoring across five indicators—accessibility, safety and comfort, intermodality, service availability, and inclusivity—the research offers grounded, data-driven insights into the functioning and failings of LMC in India’s capital region. By integrating spatial survey data and scoring analysis, this research suggesting policy and recommendations to evaluate LMC performance and prioritize interventions. The results call for a paradigm shift from infrastructure provision to user-centric service planning with attention to gender, affordability, and inter-agency collaboration. As Delhi-NCR advances its TOD and Smart City agendas, addressing these LMC challenges will be central to achieving an inclusive and sustainable urban transport future.

RQ1: “How do infrastructure and service delivery influence the effectiveness of sustainable urban transport systems in Delhi-NCR, particularly in relation to last-mile connectivity?”

Ans: The findings demonstrate that robust infrastructure and well-integrated service delivery are foundational to the success of sustainable urban transport systems. Botanical Garden, which scored highly on infrastructure parameters such as wide, continuous footpaths, lighting, CCTV presence, and intermodal integration, showed significantly higher user satisfaction and uptake of non-motorized and public modes for last-mile travel. Conversely, Nehru Place, with poor lighting, obstructed walkways, and a lack of inclusive features, led to user discomfort, lower perceived safety (especially among women), and a drift toward private or unregulated intermediate transport. Thus, infrastructure and service delivery not only shape physical access but also influence perceptions of safety, affordability, and dignity, which in turn directly impact modal choice, user retention, and the long-term sustainability of public transit systems. Stations with higher LMC infrastructure scores also exhibited stronger alignment with TOD and Smart Mobility principles.

RQ2: “What are the key infrastructural and service-related gaps that hinder seamless last-mile connectivity to major public transit systems like the Delhi Metro Rail?”

Ans: The study identified several persistent gaps that undermine seamless LMC in Delhi-NCR:

• Infrastructural Gaps: These include discontinuous or encroached footpaths, lack of pedestrian crossings, poor lighting, absence of universal access features (e.g., ramps for persons with disabilities), and insufficient signage for modal integration. At Nehru Place, the lack of gender-sensitive infrastructure significantly discouraged women from using public transit during non-peak hours.
• Service Gaps: Key deficiencies were found in unregulated IPT services, such as infrequent or unreliable feeder bus operations and lack of fare or schedule integration between the metro and last-mile modes. Furthermore, last-mile service availability after 9 PM was extremely limited at some locations, contributing to gendered mobility constraints.
• Governance and Institutional Barriers: Weak coordination among transport, urban planning, and municipal authorities further exacerbates the issue. Absence of centralized data sharing, fragmented service provision, and unclear responsibilities among agencies often delay or derail improvement efforts. These gaps collectively erode the user experience, reduce trust in public systems, and disproportionately affect vulnerable groups including women, the elderly, and low-income commuters.

5.1. Interpretation and Policy Recommendations

The correlation analysis of the five indicators, that is, accessibility, safety and comfort, intermodality, service availability, and inclusivity, at Nehru Place and Botanical Garden provides important insights into the structural and operational dynamics of last-mile connectivity in two contrasting urban contexts. The results highlight both common patterns and distinct station-specific priorities. While certain indicators consistently influence user satisfaction across both stations, others reflect localized challenges shaped by differences in land use, commuter profiles and infrastructure quality. These variations underline the need for context-sensitive planning approaches, where targeted policy measures and design interventions can address specific gaps while building on shared strengths to improve overall last-mile connectivity.

5.1.1. Accessibility (Indicator I)

Interpretation: Accessibility exhibits the strongest association with inclusivity at both stations (r = 0.90 at Nehru Place, r = 0.95 at Botanical Garden), confirming that universally accessible infrastructure benefits all user groups, including women, the elderly, and persons with disabilities. However, its weaker correlation with safety and comfort (r = 0.30 at Nehru Place, r = 0.25 at Botanical Garden) suggests that structural accessibility alone cannot guarantee security or ease of movement in crowded or poorly managed spaces. Policy recommendations include the following:

• Prioritize continuous, obstacle-free pedestrian pathways and tactile guidance systems within 500–800 m catchment zones.
• Implement universal design standards in alignment with MoHUA’s TOD guidelines, including ramps, level crossings, and shade structures.
• Strengthen integration between metro access points and feeder nodes through clear, barrier-free pedestrian linkages.

5.1.2. Safety and Comfort (Indicator II)

Interpretation: Safety And comfort demonstrate a moderate correlation with service availability (r = 0.40 at Nehru Place, r = 0.30 at Botanical Garden), indicating that improved operational reliability indirectly enhances perceived safety. The lower correlation with accessibility suggests that behavioral and environmental factors (crowding, harassment risks, etc.) require attention beyond physical design. Policy recommendations are as follows:

• Conduct a station-area safety survey under frameworks like Safe Access to Transit.
• Install CCTV surveillance, panic buttons, and adequate lighting in IPT zones, pedestrian underpasses, and interchange points.
• Promote gender-sensitive design through clear sightlines, public seating, and informal surveillance via active street edges.

5.1.3. Intermodality (Indicator III)

Interpretation: Intermodality correlates most strongly with service availability (r = 0.45 at Nehru Place, r = 0.40 at Botanical Garden), highlighting that seamless mode integration and consistent service frequency are interlinked. However, weak correlations with inclusivity (r = 0.20 and r = 0.15) suggest that physical integration does not automatically ensure equity in mobility access. Policy recommendations include the following:

• Establish dedicated IPT bays and micro-mobility zones within TOD influence areas to minimize conflicts between modes.
• Implement common mobility platforms for real-time scheduling and payment integration across metro, e-rickshaws, and feeder buses.
• Introduce wayfinding signage and interchange optimization to reduce transfer friction and improve user convenience.

5.1.4. Service Availability (Indicator IV)

Interpretation: Service availability shows consistent positive correlations with all other indicators but the strongest correlation was with intermodality and safety and comfort, confirming that operational reliability underpins overall user experience. Variability in waiting time and coverage remains a key challenge, particularly during peak demand. Policy recommendations include the following:

• Deploy AI-based demand-responsive scheduling for IPT and feeder services to reduce waiting times during peak hours.
• Ensure 24 × 7 service coverage in high-demand corridors and provide real-time service alerts via digital platforms.
• Integrate feeder service performance indicators into metro operational dashboards for accountability.

5.1.5. Inclusivity (Indicator V)

Interpretation: Inclusivity shares a near-perfect correlation with accessibility, indicating that physical design interventions strongly shape inclusive mobility. However, low correlations with intermodality suggest that vulnerable groups face challenges in navigating complex transfer systems. Policy recommendations include the following:

• Enforce universal accessibility norms in all station precinct upgrades, including tactile paving, step-free access, and priority seating zones.
• Develop gender-responsive station plans incorporating well-lit, active, and socially monitored spaces.
• Integrate affordability measures, such as differential pricing for disadvantaged groups or last-mile subsidy schemes for low-income commuters.

5.1.6. Integrated Policy Outlook

The combined findings emphasize that accessibility and inclusivity form the structural foundation of equitable LMC, whereas safety and comfort, intermodality, and service availability operate as critical experiential and operational drivers. Therefore, policy frameworks must adopt a two-tiered strategy:

• Universal Infrastructure Readiness: Mandatory inclusion of universal design and inclusive planning in TOD influence zones.
• Operational and Service Innovations: Dynamic fleet management, integrated ticketing, and safety-driven service standards.

This dual approach ensures that last-mile systems are not only physically accessible but also operationally reliable and socially inclusive, aligning with SDG 11 (Sustainable Cities) and MoHUA’s TOD principles.