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This paper studies a concept for protecting vulnerable population groups during pandemics using direct home deliveries of essential supplies, from a distribution logistics perspective. The purpose of this paper is to evaluate feasible and resource-efficient home delivery strategies, including collaboration between retailers and logistics service providers based on a practical application.

A food home delivery concept in urban areas during pandemics is mathematically modeled. All seniors living in a district of Berlin, Germany, represent the vulnerable population supplied by a grocery distribution center. A capacitated vehicle routing problem (CVRP) is developed in combination with a k-means clustering algorithm. To manage this large-scale problem efficiently, mixed-integer programming (MIP) is used. The impact of collaboration and additional delivery scenarios is examined with a sensitivity analysis.

Roughly 45 medically vulnerable persons can be served by one delivery vehicle in the baseline scenario. Operational measures allow a drastic decrease in required resources by reducing service quality. In this way, home delivery for the vulnerable population of Berlin can be achieved. This requires collaboration between grocery and parcel services and public authorities as well as overcoming accompanying challenges.

Developing a home delivery concept for providing essential goods to urban vulnerable groups during pandemics creates a special value. Setting a large-scale CVRP with variable fleet size in combination with a clustering algorithm contributes to the originality.

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.

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.

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.

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.