The current and projected trends of growth in online shopping might change the activity and travel patterns in Christchurch, one of the largest cities in New Zealand. Online shopping might reduce consumers’ shopping trips, but it has substantially increased courier companies’ trips to deliver parcels to the end-consumers because a considerable proportion of parcels are often required to be redelivered due to consumers not being at home during the first delivery attempt. This also adds to the operational cost of courier companies and adverse traffic impacts. To mitigate these issues, collection-and-delivery points (CDPs) have recently been introduced in New Zealand on a trial basis. This study aims to identify the optimal density and locations for establishing CDPs in Christchurch using a modified p-median location-allocation (LA) model. A consumer-centric approach to locating CDPs has been adopted by considering the socio-demographic characteristics of Christchurch’s residents and the distances to/from CDPs. Non-traditional CDP locations (e.g., supermarkets and dairies) were considered as potential candidate facilities and were found to be more suitable as CDPs than traditional post shops. Based on consumers’ shopping pattern, supermarkets appeared to be the most frequently visited and preferred type of facility to be used as CDPs. However, the results of the LA analyses show that dairies are the most accessible locations, and CDPs at dairies located within two kilometres will encourage consumers to walk and cycle to receive their parcels from CDPs. The results suggest the optimal location configuration for each type of facility considered, based on their spatial distribution in the city.

Urban population in India has increased significantly from 62 million in 1951 to 378 million in 2011 in six decades. It is estimated to reach 540 million by the year 2021. This reflects on likely pressure on urban transportation system. The situation necessarily calls plans for balanced personal and public transport system. Mandatory trips bear more importance in this regard owing to their higher share in urban trips. Mode share and their choice behaviour in estimation of such trips play vital role in analysing and boosting sustainable transportation. Logit modelling approach is the conventional method generally adopted for analysing mode choice behaviour, which is based on the principle of random utility maximization derived from econometric theory. However, such models cannot address uncertainity prevailing in the choice decisions. On the contrary, fuzzy logic bypasses the binary crisp derivations of the inputs and accepts multivalued inputs in linguistic expressions, which make possible to resemble the human behaviour closely. Therefore, the attempt here is to develop fuzzy logic based mode choice model for education trips, which constitutes a good share in mandatory trips by covering various income groups of Indian society.

Rapid growth in petrol and diesel-powered vehicles has resulted in significant increases in tailpipe greenhouse gas emissions and air pollution, both of which harm public health in Indian cities. Furthermore, India’s dependence on imported fuel to transport people and goods threatens its fuel security. Therefore, electric mobility has been sought to deal with these issues. The governments have framed several plans and policies to promote electric vehicles (EVs) and achieve the target of EV30@30. However, EV adoption in Indian states has been slow. Therefore, this paper aims to estimate the number of EVs needed to be registered to achieve the desired target by 2030 by taking a case study of four states: Delhi, Uttar Pradesh, Karnataka, and Gujarat. The vehicular registration data used in this paper has been obtained from the government database. The study looks at the EV adoption rates of passenger vehicles such as two-wheelers, cars, auto-rickshaws (including e-rickshaws), and buses. According to the findings, the average annual share of passenger EVs is less than 2% in Delhi, less than 1% in Uttar Pradesh, and less than 0.5% in Karnataka and Gujarat during the study period. According to the models’ estimates, Delhi, Uttar Pradesh, Gujarat, and Karnataka will need to register 0.31 million, 1.51 million, 0.88 million, and 0.79 million passenger EVs, respectively, in FY 2030–2031 to achieve a 30% EV share of total registrations.

Background: Due to the remarkable growth in online retail sales in New Zealand, a large number of parcels are needed to be delivered to consumers’ doorsteps. Home deliveries in major New Zealand cities (e.g., Christchurch) typically occur between 9 a.m. and 6 p.m. on weekdays, when many home delivery attempts fail. This leads to adverse effects, such as vehicular traffic in residential areas and greater air pollution per parcel delivered. However, home deliveries outside of typical business hours (i.e., before 9 a.m. and after 5 p.m.) might be worthwhile to help subside the above issues. Therefore, this study investigated consumers’ preferences for receiving home deliveries during various times, such as early morning, morning, afternoon, late afternoon, and evening. Methods: The data used in this study were obtained via an online survey of 355 residents of Christchurch city. Non-parametric tests, namely the Friedman test, Wilcoxon signed-rank test, and ordinal logistic regression, were carried out to examine consumer preferences for the above time slots. Results: The results showed that consumers preferred the late afternoon (3 p.m. to 6 p.m.) time slot the most for receiving home deliveries. Conclusion: It appeared that the off-peak delivery option is less likely to draw the desired consumer patronage and is thus less likely to assist in lowering the number of unsuccessful home deliveries, the transportation costs incurred by service providers, traffic congestion, and pollution in urban areas.