Trade hubs and wholesale markets are major freight handling/generating areas in cities involved in urban and regional goods distribution. Freight transport infrastructure is capital intensive which requires due diligence to get maximum benefits and efficiency with overall sustainable city development. Due to the scarce availability of land in urban areas, there is a need for optimum usage of freight handling areas in cities. This research study aims to compare the performance and efficiency of different wholesale markets of Jaipur City in India. This research paper is based on an empirical study carried out in the city of Jaipur. The paper assesses the efficiency of five major freight handling areas in case a city using the Data Envelopment Analysis (DEA) method. Primary data for operational efficiency of freight handling areas supplemented by secondary data for the year 2019 is used for DEA analysis. DEA CRS-based efficiency model is used for assessing the efficiency analysis of freight handling areas. A sensitivity analysis of parameters has been carried out to assess the robustness of the results. Based on the findings, recommendations were made at the policy level to improve the overall efficiency and effectiveness of freight management.

Road fatalities are a severe cause of concern for policymakers and administrators in developing countries like India, especially on rural highways. Some of the major causes of these road crashes are poor road design, the geometry of the intersection and lack of traffic calming measures. Road safety audits are essential for road design in the purview of the overall safety of all road users and minimising road accidents. Black spot identification and its mitigation measures are essential steps to reduce overall road accidents. Black spots are short stretches where accidents/fatalities take place repeatedly. Long-term safety measures for black spots are time- consuming and cost-intensive. This research study aims to verify the efficacy of short-term and cost-effective treatments and mitigation countermeasures on blackspots in the peri-urban road sections of Indian highways. The results of this research study confirm the positive efficacy of short-term measures, which are cost-effective and can be implemented before the implementation of permanent long-term solutions

Bicycle-sharing systems (BSSs) have emerged as an important climate-smart transportation strategy in many cities, supporting sustainable low-carbon societies. Despite becoming permanent fixtures in the Western urban landscape, bike share implementation in Asia has been disappointing, apart from China. However, future bike share growth trends indicate that Asian cities are potential hubs for bike share schemes. As a result, it is critical to investigate the current operations of bike-share schemes in these cities to understand the factors influencing bike-share use in various urban areas, which can improve system performance and encourage more use in the future. This paper investigates usage trends in a bike-sharing scheme that has been in operation in Chennai since 2019. While many studies have been conducted on how bike-sharing schemes are changing mobility in cities around the world, particularly in developed countries, few have addressed the dynamics of these schemes in cities in developing countries such as India. One of the reasons for looking at a city like Chennai is to see if metropolitan cities in developing countries benefit from bike-sharing schemes and if bike-sharing schemes can play a prominent role in these cities, as these cities face many transportation challenges such as congestion, delay, pollution, accidents, and last mile connectivity issues, among others. The study used app data to conduct an exploratory analysis to examine the impact of factors such as temporal, weather, travel characteristics, and bike type (conventional or E-bike) on bike share usage in the city. The MNL model results from this study related to bike-share ride duration (short, medium, and long) can help other cities in developing countries improve and/or expand their existing bike-share networks, as well as cities planning to launch new bike-share programs. Furthermore, examining the impact of different temporal, and weather factors on mode usage behaviour (conventional and e-bike) in bike share provides insights into user preferences and how these factors influence user mode choice behaviour in similar cities.

User satisfaction plays a vital role in the success of any public transport system. Recent studies in the field of social science have emphasized the significance of extracting valuable information from social media platforms to track and analyse user behaviour. Public participation is crucial in decision-making processes, and the use of social media data has emerged as a valuable tool for engaging public transport users through the internet, smartphone apps, and social media platforms. This paper aims to explore the feasibility of utilizing Twitter data to evaluate user perceptions of the Delhi metro, presenting a comprehensive methodology for extracting, processing, and interpreting the collected data. The research focuses on the Delhi metro as a pilot case, utilizing user satisfaction surveys. This study proposes an innovative approach as an addition to the existing structure, providing valuable insights for updating feedback data. Data collection involves extracting user feedback from social media posts, particularly tweets. A comprehensive framework is presented to efficiently extract and analyse user opinions on transportation services from Twitter. The development and validation process of the framework are illustrated through a case study specifically focusing on the Delhi Metro. The methodology comprises several steps. Initially, Twitter data is collected and pre-processed from a specific area and time to eliminate erroneous and redundant information. Text classification models, trained on manually labelled datasets, are then applied to filter Twitter data related to personal opinions on transportation services. Additionally, topic modelling and tokenization techniques are employed to extract relevant semantic content necessary for data analysis. This research proposes a framework based on social media data to capture the satisfaction of a large user base of public transport, enabling the improvement of user satisfaction characterization and location. Moreover, the study identifies potential sources of social network-related data that can be utilized in transport planning, discussing their advantages and limitations. In conclusion, this study highlights the potential of utilizing Twitter data for evaluating user perceptions of the Delhi metro. The comprehensive framework presented enables efficient extraction and analysis of user opinions on transportation services. By leveraging social media data, public transport systems can better understand user satisfaction and enhance their services accordingly. Additionally, the research identifies the opportunities and limitations of utilizing social network-related data for transport planning purposes. This study contributes to the field by demonstrating the value of social media data in improving public transport systems and informing decision-making processes.

Bike-sharing is one of the world’s fastest-growing new modes of transportation, with new schemes appearing on a regular basis. This paper examines the usage trends in a bike-sharing scheme operating in Chandigarh since 2020. While many studies have been conducted on how bike-sharing schemes are changing mobility in cities worldwide, particularly in developed countries, few have examined the dynamics of these schemes in cities in developing countries like India. One of the reasons for looking at a city like Chandigarh is to see if medium and smaller cities in developing countries benefit from bikesharing schemes and if bike-sharing schemes can play a prominent role in these cities. The study conducted an exploratory analysis using app data to examine the impact of factors such as temporal, weather, travel characteristics, and bike type (conventional or E-bike) on bike share usage in the city. Some of the research findings on the impact of various factors on bicycle ride durations (short, medium, and long) can assist other cities in developing countries in planning new bike station networks. Furthermore, analysing mode selection (conventional and E-bike) in bike share provides insights into user preferences and how various influencing factors influence their mode choice behaviour in similar cities.

The transportation of goods within cities has become a significant concern in urban planning due to the heavy burden it places on urban transportation systems and the significant social costs it incurs. There is a consensus that current urban planning and practices lack sufficient attention to understanding the features, challenges, and possibilities of freight transportation. Among all contributors to city logistics, wholesale markets play a prominent role. This research paper focuses on presenting the freight generation (FG) and freight trip generation (FTG) of perishable and non-perishable goods in wholesale markets, along with their operational characteristics. The study examines four markets, two dealing with perishable items and the other two with non-perishable items. The city of Calicut in the state of Kerala, India, is selected as a case study. A commercial establishment survey has been conducted for all four markets, and primary data has been collected. The null hypothesis assumes that the characteristics of both perishable and non-perishable markets are the same. Hypothesis tests, including both parametric and non-parametric tests, have been performed to evaluate the operational characteristics. Partial Least Square and Quantile regression (QR) methods are utilized to assess both freight generation and freight trip generation across the markets. The regression models use the dependent and independent variables obtained from a literature review. This research study has calibrated FG and FTG models that can be applied to address and present a case for the infrastructure requirements of both wholesalers and freight carriers in wholesale markets, aiming for sustainable city development.

Metro interchanges play a crucial role in ensuring the efficiency and effectiveness of a metro system by facilitating seamless transfers, reducing travel times, and enhancing the overall commuting experience. Well-designed and well-maintained interchanges contribute significantly to the success of a metro network by providing efficient connectivity and promoting public transportation usage. This research aims to study, identify, and prioritize the significant parameters essential for the planning and design of metro interchanges. Additionally, it aims to develop a composite level of service for metro interchanges to enable their comprehensive evaluation. The proposed approach utilizes a mixed methods methodology that incorporates various surveys and analytical techniques, including primary surveys, clustering analysis, and the analytical hierarchy process. A case study of four metro interchange stations in Delhi was chosen in order to comprehend the current user behaviour and determine the composite level of service. In order to calculate the overall quality of service and rating, user opinions were gathered to evaluate the degree of service for each parameter. The effectiveness, functionality, and user experience of metro interchange stations are all evaluated. This is accomplished by using the metro interchange composite index, a thorough measures that takes into account a number of interchange infrastructure components, including safety, comfort, convenience, universal accessibility, interchange time, information provision, and facilities as observed through user behaviour. The findings of this research provide valuable insights for urban planners, transportation authorities, and metro system operators. By identifying and improving the significant parameters, such as accessibility, signage, wayfinding, safety, and aesthetics, metro interchanges can be optimized to enhance overall efficiency and user satisfaction. In summary, this research presents a comprehensive approach for evaluating metro interchanges, encompassing effectiveness, functionality, and user experience. The utilization of the metro interchange composite index provides a robust framework for assessing and improving the performance of interchange stations. By considering user behaviour and preferences, this study contributes to the development of more user-centric and efficient metro systems.

Mode choice modelling plays a critical role in metropolitan cities, especially during off-peak hours (OPH), as it provides crucial insights into commuter behaviour and preferences which are crucial for policymakers to make informed decisions that optimize resources, alleviate congestion, and promote sustainable transportation options. By analyzing mode choices during non-peak times, cities can develop efficient transportation systems tailored to the unique needs of metropolitan areas, resulting in enhanced overall mobility and reduced environmental impact. However, there is a notable dearth of research focused on mode choice behaviour during off-peak hours, particularly in developing countries like India. To address this research gap, the present study selected New Delhi as a case city to examine the travel behaviour of different mode users during peak hours (PH) and identify the factors influencing their shift to off-peak hours. The study encompassed five modes of transportation: Car (4W), 2W (two-wheeler), Bus, Metro, and Auto. The study conducted a primary survey encompassing socio-economic factors, travel characteristics, and mode choice behaviour. The binary Logit model was employed to explore the shift between peak and off-peak hours. The outcomes of the study revealed significant differences in mode choice behaviour between peak and off-peak hours. This understanding of commuter preferences during non-peak times provides valuable insights for policymakers, enabling them to develop targeted strategies to encourage mode shift from peak to off-peak hours to enhance overall mobility and reduce environmental impact.

The monsoon pattern has shifted across Kerala. This, combined with significant deforestation and hill denuding, has resulted in catastrophic floods and landslides, particularly during the Southwest monsoon. Urgent relief services were to be delivered in a timely and accurate manner in order to sustain the lives of the impacted people. Even though resources were sent to several relief camps, they were either in excess or shortage on multiple instances. The conditions that prevailed during the monsoon time, as well as concerns and challenges during disaster relief efforts, must first be investigated for the effective operation of these supply chain activities. This research aims to develop a disaster logistics hub location selection decision support system, based on the Fuzzy Analytic Hierarchy Process (FAHP) and Best Worst Method (BWM), to meet the needs of disaster victims and rescue teams in the event of flooding, and to implement the proposed systems in Kuttanad, Kerala. Initially, the criteria are determined and structured in the hierarchy, and the weightage for the criteria is done via a questionnaire technique. Expert opinion on nine points scale was gathered from a set of experts working under different levels of positions during disaster management. The weights obtained by the FAHP and BWM methods were statistically analysed and compared for the reliability of the two techniques. The suggested model and application results may throw light on future work, particularly in the realm of disaster logistics management.

Public bike sharing is an increasingly popular mode of transportation in India, and understanding the factors influencing the intention to use bike share is crucial. This study employs a comprehensive approach by integrating the theory of planned behaviour (TPB), theory of interpersonal behaviour (TIB), and the technology acceptance model (TAM). Additionally, variables such as policy support, habits, external factors, and perceived bicycling conditions are also considered. A sample of 450 respondents from Delhi, the capital city of India, was collected to assess their intention to use bike sharing. The study employed Structural Equation Modelling, to examine the relationships among variables. The findings demonstrate that the research model effectively explains residents' intention to use bike share. Factors such as perceived ease of use, behavioural attitude, subjective norms, and habits have direct and positive effects on the intention to use bike share. Notably, perceived ease of use, behavioural attitude, and policy support have the most substantial impact on the intention to use bike share. Conversely, perceived bicycling conditions and external factors exert negative effects on bike share usage intentions. This study provides valuable insights into the acceptance of bike sharing and offers a strategic direction for promoting bike sharing in Indian cities.

Mobility as a Service (MaaS) has emerged as a transformative concept in urban transportation, integrating multiple modes of transportation through digital platforms to provide seamless travel experiences. By utilizing smartphone applications, MaaS simplifies trip planning, real-time information access, and consolidated payment systems, offering convenience to users. However, MaaS research has primarily focused on developed countries with well-established transport systems, making it crucial to explore its potential and challenges in developing cities of the global south, such as Noida in India. In this study, Noida, a satellite town of NCT Delhi, was chosen as only case study to gather data on user behaviour and preferences regarding app-based mobility services. A comprehensive survey collected information on socio-economic factors, personal vehicle ownership, commuting patterns, public transport usage, and attitudes towards digital ecosystems and app-based mobility services. Principal Component Analysis and K-means Clustering techniques were applied to identify distinct user types and categories, providing insights into user preferences and expectations. The analysis of the collected data revealed user clusters and their respective characteristics. The sustainability aspects of on-demand mobility services were evaluated, comparing user perceptions with private vehicle usage. The study also examined the impact of app-based mobility services on public transport and identified barriers and constraints specific to different user clusters, contributing to a better understanding of the feasibility of implementing MaaS. The findings will provide valuable insights for policymakers and transportation authorities, enabling the development of strategies and interventions to enhance urban mobility and foster MaaS adoption. By addressing the specific needs and preferences of users, MaaS can play a significant role in improving the efficiency and sustainability of transportation in complex urban environment cities like Noida in India.

In recent years bike share schemes have become increasingly popular in developing countries. Many cities have initiated bike-sharing schemes to promote sustainable mobility, increase bicycle usage, and enhance public transport's first and last-mile connectivity options. During the last few years, India also experienced a boom in bike-sharing schemes. However, unlike developed countries in Europe and America, limited research is available on bike-share schemes in developing countries like India. As a result, these countries face many problems in planning, designing, and operating bike-share schemes. This article considered Delhi a case study to address some of these problems and contribute to India's knowledge of bike-share schemes. The study considered different bike-share scheme operations in Delhi to analyse the bike-share characteristics and evaluate their impact on bike-share usage and ridership. Further, spatial analysis of bike-share schemes was also conducted to analyse the accessibility of bike stations to other facilities such as public transport systems, points of interest and their impact on bike-share usage and ridership. Moreover, a user-based survey was conducted to understand bike-share users' socioeconomic, trip characteristics, and preferences. Furthermore, a swot analysis was conducted to explore the city's strengths, weaknesses, and opportunities for operating bike-share schemes. Finally, based on the evaluation of bike-share schemes in Delhi, the study proposed various planning and policy-level recommendations to improve the bike-sharing schemes in similar size cities in developing countries like India.

•Identified future potential growth centres for bike share schemes.•Evaluated the performance of bike-share schemes from an infrastructural point of view in India and the Global Context.•Identified the difference between Public bike share schemes in Indian cities and other developed cities.•Examined the role of bike share as a mode of urban transport and how it varies in different cities.•Lessons learnt from best practices for operating bike share schemes in Indian cities.