This paper proposes a discussion of three scenarios related to e-grocery distribution developments, in order to identify and analyze the impacts of new forms of proximity deliveries on households’ shopping trip flows. Firstly, we present the two basic logistics models adopted by online retailers (in-warehouse picking and in-store picking), as well as the three main proximity delivery approaches in e-grocery. Secondly, we focus on city logistics, more particularly on the relations between e-grocery development and the related various urban goods movement flows. Thirdly, we propose to study the impact of these systems on consumer's purchasing trips and, to this end, we use an empirical simulation approach in order to make a comparison of these three scenarios.

Urban Logistics and e-Grocery: Have Proximity Delivery Services A Positive Impact On Shopping Trips?

Last-mile delivering: Analysis of environment-friendly transport

The Sustainable and Smart Mobility Strategy: Country Comparative Overview

The explosion of e-commerce creates new opportunities for courier companies to thrive, making the industry one of the success stories, due to its sustainability and resilience during the pandemic. As customers become more familiar with COVID-19, they adopt new online purchasing behaviors toward branding preferences. The purpose of this paper is to analyze the impact of risk familiarization on courier companies’ digital branding. This paper investigates the application of the psychometric paradigm by Fischhoff ho suggested risk novelty as a key factor for the level of risk perception. Five big companies with global trading activities were selected and analyzed on a three-period time: the year before, the first year, and the second year of the COVID-19 pandemic, by using passive crowdsourcing data. The results indicate that after the first year of the pandemic, online customers’ risk perception of COVID-19 hazards decreased, and consumers returned to their pre-COVID-19 behavior regarding brand preference. However, the dramatic escalation of new infections caused by new COVID-19 mutations reversed their online purchasing attitude from non-branded to branded preferences. The outcomes of the research can be used by scientists and supply chain risk managers to redefine risk mitigation strategies, COVID-related information marketing strategies and innovation investments within the industry. The research further introduces dynamic simulation modeling to be used as a risk management tool in favor of courier companies’ proper resource allocation and digital optimization.

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The Long-Term Risk Familiarity Effect on Courier Services' Digital Branding during the COVID-19 Crisis

The paper proposes synergetic approach for simulation the processes of optimization of routes for the delivery of goods taking into account the non-stationary dynamics of traffic flows on sections of the urban road network. Within the framework of synergetic Lorentz model, the analytical dependences of the change in the speed of the traffic flow on the characteristic time of the change in the dynamics of the traffic flow and the density of the traffic flow in the network sections are determined. Further, based on the obtained dependence of the traffic flow speed on its density by using a modified self-organization algorithm of the ant colony, the route on the network is optimized. Here the urban road network is represented as a bidirectional weighted graph. The main element of the modification is that it implements the possibility of asynchronous movement of the each ant colony agent at a certain speed. In addition, it is also possible to fix the results of optimization of a partially traveled path for calculating a further route when the edge weight (length) of the graph changes during the movement. This allows you to management the route optimization process, taking into account the dynamic state of the network, which depends on the speed of movement of vehicles on certain sections of the 171 network. These changes in speed can be caused by an increase in the congestion of network sections, the occurrence of traffic jams, emergency situations, etc. To test the proposed method, simulation of route optimization processes was carried out within the framework of the traveling salesman problem, taking into account the real dynamics of traffic flows on the example of the road network of Kyiv city. Here, when conducting research on some selected sections of the network, the average density of traffic flows at certain points in time during the day was experimentally determined. Based on the simulation results, a number of effects were identified. These effects are associated with the rebuilding of optimal routes when the average speeds of vehicles on the model sections of the network decrease to certain boundary values corresponding to certain modes of traffic flow. The paper discusses the possibility of using the proposed method in intelligent transportation systems. In particular, this method can be used to solve dynamic vehicle routing problems using information about traffic prediction. KEYWORDS: TRAFFIC FLOW, URBAN ROAD NETWORK, SYNERGETIC LORENTZ MODEL, SYNERGETIC APPROACH, ANT ALGORITHM

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Dynamic routing of cargo delivery processes in cities base on synergetic approach

E-business leads some changes in urban freight transport, due to an higher level of demand for goods and services, sport network. A key logistical problem of e-commerce is the delivery on the last step and is known as the problem of the last mile delivery (LMD). In this context, the chapter presents the results of a study carried out in Ukraine where e-shoppers (consumers) were interviewed. The dependences of the method of purchasing and receiving goods from customer socio-economic data have been pointed out. Then, the indications for defining solutions to optimize the deliveries in terms of transport operators, receivers and collectivity costs have been obtained.

Optimizing Last Mile Delivering Through the Analysis of Shoppers’ Behaviour

A synergetic approach for simulation the processes of optimizing cargo delivery routes, taking into account the non-stationary dynamics of traffic flows on sections of the urban road network is proposed. Here, route optimization is carried out using a modified ant colony self-organization algorithm. At that, the analytical dependences of the change in the speed of the traffic flow on the characteristic time and load density on sections of the road network are determined in the framework of the synergetic Lorentz model. Simulation of the building of optimal routes is carried out using the proposed approach on the example of the Kiev city. The possibility of using this approach to solve the problems of efficient control of the process of routing freight traffic in conditions of the real dynamics of traffic flows is shown. Prospects for the use of the developed approach in intelligent transportation systems are discussed, for example, in solving problems of dynamic routing of vehicles using traffic prediction information.

Viktor Danchuk

Papers

Optimizing Last Mile Delivering Through the Analysis of Shoppers’ Behaviour

Simulation of Processes for Optimizing the Delivery Routes of Goods on Urban Road Networks by a Synergetic Approach