This study presents the results of assessing the potential demand for an automated parcel locker (APL) system that is being deployed. A two-stage approach was developed for assessing the potential demand for APL. Within the first stage, we reveal the current demand for attended and unattended deliveries based on Random Utility Modelling. We then estimate grocery shopping activity time expenditures and evaluate possible reductions if the shopping and pickup activities were combined. We determined consumers’ prevailing preferences and behaviours towards post office channel usage (i.e. from 71% for perfumes and cosmetics to 88% for clothes). The discrete choice modelling results revealed both economic and spatial attributes as significant when online shoppers choose a delivery channel. The location for the proposed APL system, i.e. 24/7 minimarkets, would reduce walking time for the pick-up process from 20% - 47% depending on locations of post offices in relation to the online shoppers’ homes.

Data on the daily activity of private cars form the basis of many studies in the field of transportation engineering. In the past, in order to obtain such data, a large number of collection techniques based on travel diaries and driver interviews were used. Telematics applied to vehicles and to a broad range of economic activities has opened up new opportunities for transportation engineers, allowing a significant increase in the volume and detail level of data collected. One of the options for obtaining information on the daily activity of private cars now consists of processing data from automated vehicle monitoring (AVM). Therefore, in this context, and in order to explore the opportunity offered by telematics, this paper presents a methodology for obtaining origin–destination flows through basic info extracted from AVM/floating car data (FCD). Then, the benefits of such a procedure are evaluated through its implementation in a real test case, i.e., the Veneto region in northern Italy where full-day AVM/FCD data were available with about 30,000 vehicles surveyed and more than 388,000 trips identified. Then, the goodness of the proposed methodology for O-D flow estimation is validated through assignment to the road network and comparison with traffic count data. Taking into account aspects of vehicle-sampling observations, this paper also points out issues related to sample representativeness, both in terms of daily activities and spatial coverage. A preliminary descriptive analysis of the O-D flows was carried out, and the analysis of the revealed trip patterns is presented.

The paper presents survey results from shopping behavior transformation in developed and developing countries due to the COVID-19 pandemic outbreak in spring 2020. The survey includes the polling process that covered 515 and 117 young adults, respectively, for two economies and factor analysis to determine the latent intentions of purchase behavior. Shopping patterns were studied for food, medicine, goods of first priority, electronics, clothing, and shoes. According to factor analysis results, we determined nine factors that reveal some similarities in shopping behavior as pro-safe purchases and belt-tightening patterns for both economies. Along with that, we revealed that people from developed countries perceived the greater danger and fear due to the COVID-19 crisis than young adults from developing economy. Based on polling results, the post–COVID-19 shopping channel choice behavior was evaluated for developed and developing economies.

Purpose: The purpose of the paper is to assess the roots of stockpiling behaviors and to give a quantitative assessment of shopping frequency changes for emergency supplies during the coronavirus disease 2019 (COVID-19) pandemic. In addition, the authors aim to determine the sources that influenced emergency supply purchases during the COVID-19 outbreak.Design/methodology/approach: The study used a polling or survey process implementation to collect the data on shopping patterns and to determine the drivers of stockpiling behaviors for the assessment. The polling was conducted using a snowball technique, and descriptive and regression analyses were used to define the roots of the stockpiling behaviors and the shopping frequency changes.Findings: It was determined that 88.0% of end-consumers increased their shopping volumes for emergency supplies. An almost twofold increase in the average duration of usage for stockpiled goods (from 11 to 21 days) was also determined. Also revealed was a reduction in shopping frequency from an average of seven (pre-COVID-19 period) to five (first wave of COVID-19 pandemic) days. Such disproportional increases in purchase volumes along with a slight reduction in shopping frequency indicate the strong stockpile patterns that occurred during the pandemic.Originality/value: The research is based on data from Ukraine, where the number of COVID-19 cases was low. Despite the comparatively low spread of COVID-19 in large cities in Ukraine in relation to other cities globally, people still revealed panic and stockpiling behaviors. The study's quantitative assessment of shopping behaviors reveals the social and economic determinants of the shopping frequency.