THE SMART CITY TRANSPORT AND LOGISTICS SYSTEM: THEORY, METHODOLOGY AND PRACTICE Текст научной статьи по специальности «Строительство и архитектура»

DOI: 10.29141/2218-5003-2021-12-6-5 <°

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JEL Classification: B52, O18, P25, R41 *

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The smart city transport and logistics system: jj

Theory, methodology and practice *

Gleb V. Savin1 <

1 Ural State University of Economics, Ekaterinburg, Russia s

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Abstract. Forming the systems of flow processes management in the context of limited resources and a sharing economy is 5f among the most pressing problems of digitalization. The scientific review analyses the theoretical and methodological foundations g and special features of forming the smart city transport and logistics systems in practice, as well as the promising trends in their de- ^ velopment aimed at increasing the level of mobility. Methodologically, the study rests on institutional and evolutionary economics 2 theories, sustainable development theory, as well as the provisions of the quantitative school of management. The methods of = systemic, comparative and cluster analysis were applied. Using VOSviewer software, the author analyses research publications indexed in the Russian and global citation databases and selects the articles dedicated to the latest trends in the field of mobility, transport and logistics. The research outlines the dominant trends and specifics of the smart mobility services development in real time for businesses and individuals, as well as intelligent transportation systems and highly autonomous vehicles in smart cities worldwide. The findings prove that the development of the Internet of Things underlies all trends, and a tendency to the formation of a multimodal environment, in particular. The study substantiates the necessity to develop the concept of urban logistics as a tool that expands the opportunities for forming sustainable systems of flow processes management in an urban area. The research results can complement the research trends in the development of the smart city transport and logistics system, formulate the norms and rules for cooperation of economic agents, and also serve as a theoretical and methodological framework for further research.

Keywords: municipal administration; smart city; intelligent transportation system; highly autonomous vehicles; bibliometric analysis.

Funding: The study was funded by the Russian Foundation for Basic Research within the framework of the project no. 20-11050039.

Paper submitted: July 30, 2021

For citation: Savin G.V. (2021). The smart city transport and logistics system: Theory, methodology and practice. Upravlenets -The Manager, vol. 12, no. 6, pp. 67-86. DOI: 10.29141/2218-5003-2021-12-6-5.

Формирование транспортно-логистической системы Smart City: теория, методология и практика

Г.В. Савин1

1 Уральский государственный экономический университет, г. Екатеринбург, РФ

Аннотация. Одной из актуальных проблем цифровизации является проблема формирования систем управления потоковыми процессами в условиях ограниченных ресурсов и экономики совместного пользования. В статье представлен научный обзор, в рамках которого анализируются теоретико-методологические основы и особенности практической им-плементации формирования транспортно-логистических систем умных городов, а также перспективные тренды их развития, направленные на повышение уровня мобильности. Методологическую базу исследования составили институционально-эволюционная экономическая теория, теория устойчивого развития, а также положения школы количественных методов в управлении. Использовались методы системного, сравнительного и кластерного анализа. С помощью программы VOSviewer выполнен библиометрический анализ публикаций из зарубежных и российских баз цитирования и выбраны статьи, отражающие передовые тенденции в области мобильности, транспорта и логистики. Обозначены основные тенденции и специфика развития сервисов умной мобильности в режиме реального времени как для бизнеса, так и для граждан, а также интеллектуальных транспортных систем и высокоавтоматизированных транспортных средств в умных городах мира. Доказано, что основой всех тенденций выступает развитие Интернета вещей, выделен тренд на формирование мультимодального сообщества. Обоснована необходимость развития концепции городской логистики как инструмента, расширяющего возможности формирования устойчивых систем управления потоковыми процессами в городе. Полученные результаты могут дополнить исследовательские тренды развития транспортно-логистической системы умного города, сформировать нормы и правила сотрудничества экономических агентов, а также послужить теоретико-методологической основой будущих научных изысканий.

Ключевые слова: муниципальное управление; умный город; интеллектуальная транспортная система; высокоавтоматизированные транспортные средства; библиометрический анализ.

Финансирование: Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 20-11050039.

Дата поступления статьи: 30 июля 2021 г.

Ссылка для цитирования: Savin G.V. (2021). The smart city transport and logistics system: Theory, methodology and practice // Управленец. Т. 12, № 6. С. 67-86. DOI: 10.29141/2218-5003-2021-12-6-5.

I INTRODUCTION

3 Currently, relationships between economic agents are

£ moving to a new level, which is characterized by new

g forms and principles of interaction, as well as by an in-

£ crease in transaction costs associated with the search for

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£ information, negotiations, maintenance of contractual I obligations, and opportunistic behaviour. Relationships Ü are being transformed into a digital area of the information space of autonomous algorithms for business, population and government authorities, while ensuring the integration of intra-industrial, business and other processes.

In this context, the traditional transport and logistics system (TLS) of any city slows down the turnover of economic resources, which results in the growth of people's personal consumer spending, economic losses of businesses and budgets of different levels.

There is a persisting trend towards the development of points of growth in the global economy. The smart city transport and logistics system serves as the basis for organization and effective functioning of the socioeconomic system, as well as a crucial infrastructure project in the field of management that lays the foundation for other spheres (economy, environment, management, standards of living, etc.). The transformation of this system under digitalization requires significant administration changes to be made in order to achieve high interor-ganizational logistic coordination of flow processes.

The relevance of the present scientific overview is due to the trends of digitalization, which forms new models and realities of human functioning, as well as their economic activity. At the same time, current relationships are characterized by the growing number of services in comparison with material production, as well as by new forms and principles of interaction, and an increase in transaction costs.

Within the paradigm of sustainable development, smart cities are formed, in which digital technologies are introduced into the economy, healthcare, waste disposal, housing and utilities infrastructure, transport and other spheres. This allows one to plan, execute and control flow processes and resources, including service and information, in the most efficient way. The mentioned trends are focused primarily on the growth in the quality of human life, which is impossible without the development of innovative and science-intensive technologies, industries, and modern management systems.

It is worth highlighting that amid the cyclical nature of economic development and the crisis of the world economy, there is a growing need for assessing the total logistics costs. In addition, the role of the planned effective use of limited resources is increasing to accumulate intelligent assets that enhance the competitiveness of national economy, enterprises, and firms in a city, in particular.

The global processes of the smart city transport and logistics system formation are reduced to building intelli-

gent transport systems (ITSs), which are designed to deal with economic and social problems, ensure safety control, increase mobility and reduce harmful emissions into the environment. At that, cooperative intelligent transport systems are being established all over the world, as well as technologies and projects of highly autonomous vehicles (HAVs) are being developed.

The purpose of the research is to systematize the theoretical and methodological approaches to studying the smart city transport and logistics system and the practical foundations of its development in order to attain a higher level of inter-organizational interaction between economic agents and reduce transaction costs.

To fulfil the stated purpose, the following objectives have to be accomplished:

• to generalize the Russian and global experience of digital transformation and perform a theoretical cross-section of scientific branches in the field of the smart city transport and logistics system formation, as well as to determine semantic analogues of the concept and the main approaches to its examination;

• to identify promising research clusters that act as the major competitive knowledge domains and allow devising new avenues for reducing transaction costs, as well as ensuring the transport and logistics system of a new type to be formed;

• to carry out comparative analysis and systematize the main performance indicators of TLSs in smart cities all over the world in the context of ongoing and completed infrastructure projects; to compile a list of cities leading in the successful implementation of special practices for achieving a higher level of inter-organizational interaction between economic agents, and to identify the threshold levels of digitalization in the field of traffic management.

The purpose and objectives of the research serve as a rationale for forming its information base. The article presents an analytical overview of research publications indexed in the citation databases Scopus, Web of Science and eLibrary, as well as institutions characterizing the given research area and its practical implementation, and offer the primary directions of scientific studies, development of technologies and infrastructure in the field of forming the TLS of a smart city.

The research results make a contribution to the scientific theoretical and methodological framework for developing a new type of the flow processes management system.

RESEARCH METHODOLOGY

The object of the research is the smart city transport and logistics system, and the subject of the research is digitalization processes in the development of this system.

To address the mentioned issues covering several scientific research areas, the logic of analysis is based on the

fact that, from the standpoint of its practical implementation, the transport and logistics system is an infrastructure project encouraging the most efficient movement of economic resources.

At the first stage of the study, through system analysis, we identified semantic analogues of the concept of the smart city transport and logistics system in the Russian and international citation databases. At the second stage, we analysed the major articles on the topic under consideration using the VOSviewer bibliometric tool and formed research clusters in the field of mobility, transport and logistics that contained the relevant research avenues and characterized the strength of the connection between them. Next, having performed a comparative analysis of the cities leading in each of the identified clusters, we systematized their current performance indicators (traffic, time, CO2 emissions, congestion), which made it possible to draw conclusions about the level of inter-organizational interaction under digitalization and propose the author's vision of the TLS development in a smart city in the future.

The studies on intelligent transport systems and networks prevail among the foreign publications we have analysed. The scientific interest is also ignited by the discourse about the establishment of urban distribution logistics centres and consolidation centres and about the provision of active, inclusive mobility, etc. Moreover, the problem of sustainable urban planning in the context of the growing population is associated with urban logistics designed to ensure the most efficient transportation of people and goods, and the attempts to suggest possible

variations of urban logistics policy in view of creating a sustainable transport system are analysed.

Another aspect of the research valuation is digital initiatives on developing services that enhance the competitiveness of cities due to the fact that they provide living in a relatively stable and safe society while using clean and renewable energy sources and maintaining high rates of economic efficiency in the context of a balanced and sustainable use of economic resources. From this perspective, there are currently no generally accepted rules and norms for the interaction of economic agents.

It is worth emphasizing that the topic under review prompts us to analyse a wider range of scientific publications addressing the problem of insufficient elaboration of the term "transport and logistics system", as well as to intertwine it with intelligent transport systems, logistics centres and, naturally, with initiatives for the formation and development of a smart city. In addition, a 78 % increase in demand and a 21 % rise in congestion projected by 2030, coupled with the predominance of digital technologies and solutions implemented in the world today, indicate that there are made attempts to create intelligent control systems and do intensive search for solutions to optimize the last mile in urban areas using green logistics.

Thus, in the absence of a unified approach, we aim to suggest own interpretation of the concept of the smart city transport and logistics system. To do so, we perform a bibliometric analysis in Scopus, Web of Science and eLi-brary citation databases that highlight the semantic load of this category (Fig. 1, 2).

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14 000 12 000 10 000 8 000 6 000 4 000 2 000 0

— Smart city Transport

— Logistics

— Mobility

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Fig. 1. Number of scientific publications on transport, logistics and mobility in a smart city indexed in Scopus and Web of Science databases, 2000-2020 Рис. 1. Количество публикаций по вопросам изучения транспорта, логистики и мобильности в умном городе в базах данных Scopus и Web of Science, 2000-2020

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Fig. 2. Number of scientific publications on transport and logistics system and intelligent transport system in a smart city in the eLibrary database, 2000-2020 Рис. 2. Количество публикаций по вопросам изучения транспортно-логистической и интеллектуальной транспортной систем умного города в базе данных eLibrary, 2000-2020

g The bibliographic cross-section includes more than 3 75,000 articles on various improvements in smart cities. £ The use of VOSviewer enabled us to get the most accurate g and complete results to detail the research topic. £ The foreign citation databases widely operate the defi-£ nition of smart city. The year of 1974 witnessed the first at-< tempts to examine this topic; however, the most intense S debate in the academic community started in 2000 after a progressive increase in the number of scientific articles on the given subject. Analysis of research activity shows that the semantic meaning of the term"smart" implies the associated development of society, infrastructure, urban planning, digital technologies, etc. Infrastructure development is associated with energy, networks, and transport.

In the context of the studied subject, a number of researchers [Kramers et al., 2014; Bibri, Krogstie, 2017; Val-cárcel-Aguiar, Murias, Rodríguez-González, 2019; Zhang et al., 2020; Sharifi, 2020] investigate economic, social and environmental aspects of sustainability, and effective resource management, in particular [Schneider et al., 2019]. At that, studies on smart mobility take the lead [Paiva et al., 2021], and the following initiatives are highlighted: the development of consolidation centres, autonomous and green transport (no more than 120 g of CO2 emissions per 1 km), ensuring effective calibration of access time, introducing a progressive scale of road toll schemes, and the use of alternative delivery modes.

Researchers pay special attention to the necessity to ensure sustainability and environmental friendliness of supplies amid the rapid development of e-commerce, as well as to the transport and logistics system and the development of mobility, which are promising targets for technological improvements.

In the international citation databases, there are three basic aspects for exploring smart cities, these are mobility (1,956 articles in 2020, and 989 for the first half of 2021), transport (2,044 and 1,037 articles, respectively), and logistics (611 and 376 articles, respectively).

However, in the Russian scientific community, the situation is different: the pivotal role belongs to the studies on the optimization of logistic processes in the implementation of information and communication technologies (ICT) in enterprises and supply chains and on the use of digital services in cities and regions. The number of Russian-language articles in this field of research is significantly less than foreign ones, but it is growing steadily (334 articles in 2020, and 124 articles in the first half of 2021).

Hence, a smart city transport and logistics system refers to a unified system of flow processes management, which is focused on achieving sustainable use of resources and ensuring zero losses for all categories of economic agents in the field of traffic management [Savin, 2020a].

There emerges a question as to how the traditional transport and logistics system of a city differs from its

smart category. The answer is obvious: they differ in the application of new principles of organization and management of flow processes when using ICT, that, in particular, ensure the reliability, accuracy and security of the transmitted digital information in real time. At the same time, environmental friendliness when applying the principles of urban logistics is of special importance.

The tardy analysis of the semantic categories of the smart city transport and logistics systems, which is typical of the Russian research segment, allows us to highlight the main trends of a theoretical, methodological and practical nature observed in foreign citation databases. In addition, we can correlate the concept with selective domestic developments and get a general idea of the formation of transport and logistics systems in the future.

In conclusion, it is worth stressing that, along with digital solutions in the field of intelligent transport systems development and the introduction of highly autonomous vehicles, it is logistics that will drive the implementation of smart mobility as a smart city component in the coming years.

THEORETICAL AND METHODOLOGICAL APPROACHES TO STUDYING THE SMART CITY TRANSPORT AND LOGISTICS SYSTEM: CURRENT AND PROSPECTIVE SCIENTIFIC RESEARCH

Currently, a system-based approach in the field of urban policy and planning founded on digital technologies, as well as social, environmental and economic innovations has been formed.

Multidimensional and conceptual problems in defining smart cities support the view that the introduction of digital solutions, the knowledge economy, citizen engagement, social and institutional innovation, and information management are essential elements of smart cities' development [Cocchia, 2014; Talari et al., 2017; Mora, Bolici, Deakin, 2017; Pereira et al., 2018; Ruhlandt, 2018; Guo Y.-M. et al., 2019; Zhao, Tang, Zou, 2019; Wamba, Que-iroz, 2019; Echebarria, Barrutia, Aguado-Moralejo, 2021; Janik, Ryszko, Szafraniec, 2020; Moradi, 2020; Pérez et al., 2020; Sharifi, 2020; Zheng et al., 2020].

Moreover, in the context of the sustainable development paradigm while forming a smart city, which enjoys all the advantages of the spatial concentration of mass consumption, high savings from wholesale and retail trade operations, reduced delivery times, and increased convenience for buyers and customers, there are significant transformations in the transport and logistics system and introduced social and environmental innovations.

Among the promising avenues for the formation of a smart city are the development of mobility [Bonne-fon, Shariff, Rahwan, 2016; Rafael et al., 2020; Paiva et al., 2021] and the introduction of the 15-minute city concept [Moreno et al., 2021], which decentralizes the urban infrastructure and implies that all necessary amenities should be located within a short distance.

It should be noted that the concept of smart mobility is in line with the scientific paradigm of sustainable development in the field of people and goods transportation, and is also linked with modern digital technologies within the Internet of Things (loT), big data, blockchain, and artificial intelligence. However, a number of researchers claim that smart mobility requires no digital technologies to be involved, which only complement this concept [Docherty, Marsden, Anable, 2018; Bucchiarone, 2019].

A bibliometric analysis of the smart city TLSs from the standpoint of mobility (Fig. 3) allows identifying the distinguishing features of their formation: the development of public transport [Docherty, Marsden, Anable, 2018; Jin, Kong, Sui, 2019; Ceder, 2021], intelligent transport systems [Balasubramaniam et al., 2021; Bryazgina, Kurguzov, Belov, 2020], and information processing and analysis centres focused on the introduction of services for improving consumers' quality of life [Mirri et al., 2016; Bel-bachir et al., 2019; Lopez, Farooq, 2020].

At that, the initiatives aimed at improving mobility indicators make it possible to slightly increase the quality of life in the smart city transport and logistics system [Savin, 2020b].

Some researchers note that mobility is focused on meeting human needs and implies a consumer choice, as well as takes into account the minimum level of emissions and low transportation costs. Mobility embraces sensors for gathering information in real time (including mobile phones) and intelligent video surveillance, autonomous decision-making algorithms, an information system, etc.

[Amoretti, Belli, Zanichelli, 2017, Aleta, Alonso, Ruiz, 2017; Yigitcanlar, Kamruzzaman, 2019; Paiva et al., 2021].

Currently, there is an obvious trend towards the formation of a multimodal environment in the field of smart mobility [Groth, 2019; Mukhtar-Landgren, Paulsson, 2021] in the development of the sharing economy [Rong, Xiao, Wang, 2019; Schneider et al., 2019].

We agree that smart mobility may not cover all consumer groups, but its development depends on investments in digital and intelligent systems infrastructure, as well as 4/5G networks, including highly autonomous vehicles [Bonnefon, Shariff, Rahwan, 2016; Cugurullo et al., 2021; Guo H. et al., 2020; Rafael et al., 2020; Mourad, Puchinger, van Woensel, 2021]. In addition, in today's situation, among the central elements that slow down the development of the concept of smart mobility are the provision of legal regulation, interoperability, personal data protection and cybersecurity [Elisa et al., 2018; Naz et al., 2019; Behrendt, 2020], ethical and legal issues in the context of artificial intelligence [Martinho et al., 2021; Naniev, 2020], and allocation of responsibilities.

Another aspect associated with smart mobility is the development of an intelligent transport system, which is oriented towards using modern ICT to solve the issues of choosing flow processes management system amid limited human rationality. Such systems reduce transportation time (by 10-15 %), the number of transport stops (by 20-40 %), fuel consumption (by 5-15 %), logistics costs (by 5-25 %), as well as increase inventory turnover (by 15-45 %), safety (up to 60 % in certain road sections), and

Fig. 3. Key terms in the field of smart city mobility and their relationships: analysis of publications indexed in Scopus, Web of Science and eLibrary databases, 2000-2021 Рис. 3. Ключевые термины в области изучения мобильности в умном городе и их взаимосвязи: результаты анализа публикаций 2000-2021 гг. в базах данных Scopus, Web of Science и eLibrary

environmental friendliness (a 5-15 % decline in harmful emissions into the atmosphere).

In the field of transport, the analysis of terms allows us to form the following main research clusters (Fig. 4): 1) assessment of the workload and development of intelligent transport systems; 2) Internet of Things, data analysis, and security; 3) processes of transportation and traffic management; 4) sustainable development; 5) energy efficiency and electric transport.

The clusters highlighted in purple and yellow concentrate on modern approaches to deploying intelligent transport systems in the world and planning the functioning of urban transport [Gohar, Muzammal, Ur Rahman, 2018; Pan et al., 2021], including parking systems, congestion reduction, traffic forecasting, security systems, emergency management, payment management, organization of freight transportation and information services on public transport using technologies for spatial positioning, as well as receiving, processing, exchanging and distributing information.

The introduction of ICT and the development of intelligent transport systems are expected to serve as the basis for the management and optimization of traffic flows [Schwerdfeger, Boysen, 2020]. These systems are regarded as an optimal opportunity to use investment, planning and resources1. Today, within the framework of the ISO Technical Committee 204, there is implemented the cross-country research cooperation in the field of archi-

1 Intelligent Transport Systems (ITS) for sustainable mobility. https://unece.org/fileadmin/DAM/trans/publications/Intelligent_ Transport_Systems_for_Sustainable_Mobility.PDF.

tecture, autonomous identification of vehicles and equipment, and freight transport management, as well as there are tested the standards for cooperative intelligent transport systems and adaptive traffic control systems (Sydney Coordinated Adaptive Traffic System SCRAM, GLIDE, Vehicle Information and Communication Systems, etc.).

In terms of studying smart cities, the Internet of Things is the most comprehensive research subject in the field of security [Hammi et al., 2018; Elisa et al., 2018; Naz et al., 2019], intelligent infrastructure development [Barns et al., 2017; Minoli, Sohraby, Occhiogrosso, 2017; Kosim-khuzhaev, Skoryupina, 2020], and in-depth examination of digital technologies for information analysis and processing. Within the smart city concept, special attention is paid to the introduction of V2V technologies in the field of IEEE 802.bd and NR-V2X, DSRC according to IEEE 802.11p that ensure the interaction of transport vehicles, as well as to convolutional and recurrent neural networks, deep learning systems, machine learning, computer vision improvement, and analysis of distributed data ledger application [Balasubramaniam et al., 2021; Savin, 2021].

The given research on transport and logistics systems from the perspective of logistics focuses not only informatization of the main flow processes for all economic agents, but also takes into account congestion, traffic and optimization (Fig. 5).

Nowadays, the development of urban logistics [Savin, 2020c] acts as a powerful tool for forming sustainability and mobility, and the emergence of effective transport systems, in particular [Hu et al., 2019; Dolati Neghabadi, Evrard Samuel, Espinouse, 2019]. At the same time, there

Fig. 4. Key terms in the field of transport and their relationships: analysis of publications indexed in Scopus, Web of Science and eLibrary databases, 2000-2021 Рис. 4. Ключевые термины в области изучения транспорта и их взаимосвязи: результаты анализа публикаций

2000-2021 гг. в базах данных Scopus, Web of Science и eLibrary

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Fig. 5. Key terms in the field of logistics and their relationships: analysis of publications indexed in Scopus, Web of Science and eLibrary databases, 2000-2021 Рис. 5. Ключевые термины в области изучения логистики и их взаимосвязи: результаты анализа публикаций 2000-2021 гг. в базах данных Scopus, Web of Science и eLibrary

appear studies on locating and operating urban consolidation centres [Aljohani, Thompson, 2016] and pick-up points, the use of drones [Shavarani et al., 2019; Macrina et al., 2020] and alternative transport; some attempts are made to optimize the last mile [Oliveira et al., 2017; Lim, Jin, Srai, 2018; Melacini et al., 2018; Ranieri et al., 2018; Olsson, Hellstrom, Pâlsson, 2019; Simoni et al., 2020] and crowdshipping [Szmelter-Jarosz, Rzesny-Cieplinska, 2020; Devari, Nikolaev, He, 2017; Binetti et al., 2019; Dai, Jia, Liu, 2020; Gatta et al., 2019]; much attention is devoted to reducing emissions, developing green logistics [Perboli, Rosano, 2019; Ren et al., 2020; Mello Bandeira et al., 2019; Zhang et al., 2020; Asghari, Mirzapour Al-e-hashem, 2021; Moghdani et al., 2021; Patella et al., 2021], routing, delivery time windows [Cortés-Murcia, Prodhon, Murat Afsar, 2019; Galkin, Sysoev, 2020], and organizing stakeholder participation [Tompson, 2017; Szmelter-Jarosz, Rzesny-Cieplinska, 2020].

It is worth emphasizing that the existing penetration of digital technologies accelerates the flow processes of economic activity and human functioning and creates risks of resource management, which requires a new development paradigm to be found within the framework of institutional and evolutionary economics theory [Popov, 2020]. In this context, the new paradigm "mobility as a service" [Amoretti, Belli, Zanichelli, 2017; Müller, Wirtz, Schmidt, 2020; Pahwa, Starly, 2021; Ho et al., 2021] and the use of the full toolkit of urban logistics can contribute to implementing and complementing the systems approach. It will provide the effective flow processes management in the smart city transport and logistics system

and offer a complete range of services in real time upon the request of both business and citizens.

Currently, in order to assess smart city, a ranking approach (IESE Cities in Motion Index, Global Power City Index, The Global Cities Index, EasyPark Smart City Index, etc.) is applied, which examines mobility and transport: time in traffic jams, average commute time, taxi fares, availability of parking apps, number of parking spaces, number of electric charging points, as well as smart transport initiatives (smart traffic lights, strategies to reduce vehicle use and increase public transport use, interagency collaboration, road safety , open transport data), etc.

Present TLS research studies concentrate on building mobility development simulation models [Del Vecchio et al., 2019; Beaver et al., 2020; Kronsell, Mukhtar-Landgren, 2020]; infrastructure design [Barns et al., 2017; Fu, Zhu, 2021; Fontaine et al., 2021], public transport efficiency [Johansson et al., 2017; Gatta, Marcucci, Site et al., 2019; Jin, Kong, Sui, 2019; Mathirajan, Devadas, Ramanathan, 2021; Ceder, 2021], routing [Beaver et al., 2020; Paiva et al., 2020], traffic [Dong et al., 2020; Wang, Quan, Ochieng, 2020], traffic flow modelling [Anda, Erath, Fourie, 2017], etc.

All of the mentioned models are insufficient to attain the main goal — that is, to ensure the logistic coordination of flow processes, — and the scrutiny of the socio-economic system is centred around methodological holism, which employs a holistic approach to this system. Numerous economic agents, namely firms and households, create friction in the field of flow processes organization [Wang, Quan, Ochieng, 2020]. As a result,

I representative analysis is only possible with a general

3 evaluation of the movement of passengers and goods

£ within certain boundaries. This outcome can be achieved

g through the combined design of the smart city TLS [Savin,

£ Bronnikov, 2018; Caird, Hallett, 2019] in terms of the crea-

u

£ tion of a single ecosystem [Lagorio, Pinto, Golini, 2017; < Longo, Zappatore, Navathe, 2019; Komninos et al., 2021] S and the transport-logistic, digital and smart infrastructure, as well as the development of norms and regulations for the interaction between economic agents.

With the arithmetic growth of population and urbanization, needs grow geometrically, which poses the question of organizing flow processes in the development of the "mobility as a service" global platform. Within the framework of sustainable development, the formation of a unified technological system is a significant milestone in the integration of transport and logistics. At that, a change in the management system, an increase in automation and robot application, and a rise in the number of services will add new essential elements to the transport and logistics system of a smart city.

The growing number of economic agents prompts the search for new approaches that would allow adapting to the new economic paradigm while promoting cooperation and simultaneously passing on selective research mutations in terms of the succession of current research approaches and ideas initiated by firms, as well as in the context of social innovation in the formation of smart cities.

Amid the direct structural relationships of transport-logistics and socio-economic systems, consumer-initiated innovations exert an overwhelming impact on flow processes. At that, logistics can contribute to the economic development when selecting the best of them from the position of not only rational choice, but also improving the quality of human life.

Thus, various theoretical and methodological approaches are being currently implemented; they are associated with sustainable development and a better quality of life in the field of the growing indicators of mobility, transport and logistics. However, there is considerable confusion in interpreting the transport and logistics system and filling this definition with a more specific meaningful non-digital idea. In addition, no unified norms and rules for economic agents to interact while introducing ICT are shaped, and the maximum levels of possible and necessary digitalization are not considered.

SPECIAL FEATURES OF IMPLEMENTING THE SMART CITY TRANSPORT AND LOGISTICS SYSTEMS IN PRACTICE

At the moment, there are active discussions about the concept of sustainable development and urban logistics policy in view of creating the smart city transport and logistics system [Hu et al., 2019; Rodrigues, Vale, Costa, 2020; Reda et al., 2020; Viu-Roig, Alvarez-Palau, 2020; Patella et al., 2021] that is designed to reduce congestion and emissions and ensure a higher level of mobility. Its current state is attributed to the introduction of digital services, autonomous vehicles on public roads, the formation of intelligent transport systems, but these initiatives are limited by financial, technological, legal, institutional and other barriers.

The successful formation of the transport and logistics system is founded on the proper functioning of the Internet, "regulatory sandboxes" and legislation, as well as the introduction of ICT (Table 1), preparation of the appropriate infrastructure, and work with the population. It is noteworthy that the average stable Internet speed serves as the basis for the development of modern digital technologies, and countries with stable data transmission networks are more active in developing ICT.

Country's position in the overall ranking Autonomous Vehicles Readiness Index1 Position in the ICT development ranking2

Policy and legislation Technology and innovation Infrastructure Consumer acceptance

1. Singapore 1 11 5 1 1

2. The Netherlands 3 10 1 7 7

3. Norway 10 5 3 5 10

4. United States 6 2 9 6 2

5. Finland 4 8 11 2 6

6. Sweden 15 6 8 3 4

7. South Korea 16 7 2 10 13

8. United Arab Emirates 8 22 4 4 21

9. United Kingdom 2 9 16 12 8

10. Denmark 12 15 10 8 5

11. Japan 18 3 6 18 9

Table 1 - Autonomous vehicles and ICT development country rankings, 2020 Таблица 1 - Рейтинги стран в области развития высокоавтоматизированных транспортных средств

и информационно-коммуникационных технологий, 2020 г.

Table 1 (concluded) ° Окончание табл. 1 g

Country's position in the overall ranking Autonomous Vehicles Readiness Index1 Position in the ICT development ranking2

Policy and legislation Technology and innovation Infrastructure Consumer acceptance

12. Canada 9 13 13 13 17

13. Taiwan 13 14 14 15 -

14. Germany 7 4 19 21 15

15. Australia 17 17 12 9 11

16. Israel 19 1 25 11 -

17. New Zealand 5 19 20 14 12

18. Austria 11 16 7 24 20

19. France 14 12 17 19 16

20. China 21 20 22 16 22

21. Belgium 20 18 18 23 19

22. Spain 23 23 15 17 23

23. Czech Republic 22 25 24 22 28

24. Italy 27 21 23 26 26

25. Hungary 25 24 21 28 31

26. Russia 26 26 27 20 42

27. Chile 24 27 26 25 30

28. Mexico 29 29 28 27 53

29. India 28 28 29 30 63

30. Brazil 30 30 30 29 44

Note: 1 Autonomous Vehicles Readiness Index. Assessing countries' openness and preparedness for autonomous vehicles. https:// assets.kpmg/content/dam/kpmg/ru/pdf/2020/08/ru-ru-autonomous-vehicles-readiness-index-2020.pdf; 2 Shaping the New Normal with Intelligent Connectivity. https://www.huawei.com/minisite/gci/en/.

Many leading economies are characterized by a high level of ontogeny of the broadband and mobile Internet. They concentrate their efforts and initiatives on building secure Internet servers, translate information systems to Web 2.0 (3.0), invest in next-generation software, popularize IoT analytics and analytic scalability, and initiate cybersecurity education. Moreover, they actively develop ITC business models, direct careful attention to employee training, patent work and R&D, invest in the development of 4G/5G, fibre optic networks, and invest in cloud infrastructure, the Internet of Things and artificial intelligence.

Amid the global trend towards digitalization, there stand out two ways of developing intelligent transport systems and introducing autonomous vehicles:

• vehicle machine learning in decision-making in the context of interaction with pedestrians and stationary objects;

• enhancing the infrastructure with accounting and information systems when integrating with the ITS, the development of which in many cities lags behind due to high costs of both bringing the current infrastructure in line with established standards and creating a new world-class digital and intelligent infrastructure.

The formation of road traffic control centres (RTCCs) is underway amid the improvement processes in the framework architecture (FRAME, U.S. DoT ITS et al.) in order to

protect the environment ensuring safety and a high level of mobility.

There are a substantial number of system aggregators globally that provide transportation services of both people and goods. The booming and well-known mobility development services are the following:

• selecting private car drivers (Blablacar, Uber, Yandex, Kiwitaxi, taxi.eu, Gett, YouDrive, etc.);

• carsharing (Addumacar, Cambio Car2go, Enjoy, Enterprise, Flinkster, Sharengo, Zipcar, etc.);

• bicycle rental (Velib, Yellow Bike, Black Bikes, Deutsche Bahn, Lidl, Nextbike, Mattia 46 Bikes, Bycyklen, Velobyke, etc.);

• scooter sharing (YouDrive Lite, Revel, Skoda Auto Digila, Hoop, Whosh, Bounce, etc.).

Among the most advanced companies that develop highly autonomous vehicles are Tesla, Nissan, Volvo, Audi, Google, Apple, Yandex and others. The projects and initiatives undertaken are given in Table 2.

The formation of the smart city transport and logistics system involves numerous technologies and solutions, which are embodied in ready-made projects, however, cooperative (autonomous) systems are only at the early stage of their development.

Firstly, it is required to strengthen the relationships between economic agents in the field of cooperation and

Table 2 - Main projects in the field of highly autonomous vehicles, 2020 Таблица 2 - Основные проекты в области высокоавтоматизированных транспортных средств, 2020 г.

Country Projects and outcome

Singapore Technical Reference for Autonomous Vehicles (TR 68), model framework for voluntary implementation of AI-based systems (Model AI Governance Framework)

The Netherlands Tests of self-driving trucks convoys, share of electric vehicles (hybrids) is 15 %

Norway Driverless buses with a speed limit of 20-25 km/h. Unmanned snow clearing machines. Share of electric vehicles (hybrids) is 56 %

United States Uber tests in San Francisco, self-driving vehicles (Origin, Apple, Tesla, etc.)

Finland Regulatory sandboxes for any autonomous vehicle challenge. Unmanned bus on public roads

Sweden Self-driving electric truck Einride Pod

South Korea Future Car Industry National Vision aimed at promoting electric and hydrogen vehicles

United Arab Emirates Strategy stipulating that 25 % of all transport in the country will be smart and driverless by 2030

United Kingdom The Automated and Electric Vehicle Act. Testing an unmanned bus on public roads

Denmark The Danish Road Traffic Act with amendments on self-driving cars. Test drives of an automated bus SmartBus

Japan The Road Transport Vehicle Act and the Road Traffic Act with amendments on self-driving vehicles. Launching Honda with level 3-4 autonomous driving technology

Canada Autonomous Vehicle Innovation Network. Partial municipal subsidies for ride-hailing trips instead of using a public bus system

Taiwan Pure-electric, self-driving minibus The WinBus

Australia Automated passenger vehicles BusBot, Intellibus on public roads. Autonomous haul trucks in mining operations

Germany Freightliner Cascadia truck and bus with autonomous control system. Testing autonomous vehicles on public roads. Cars with level 4 autonomous driving technology are allowed

Israel Own fleet of self-driving vehicles

New Zealand Automated bus on public roads. Unmanned aircraft system (drones)

Austria Testing autonomous mini-buses, flying taxi project

France A legal framework to launch self-driving transport by 2021. Opening of a proving ground. 16 projects in the field of unmanned vehicles

China 100 robot taxis with a speed limit of up to 80 km/h. Testing Pony.ai on public roads

Belgium Test drive of an autonomous shuttle bus

Spain Test drive of self-driving buses. Legal framework on the popularization of electric vehicles

Czech Republic Testing autonomous vehicles. BMW proving ground

Italy Developing a smart road network. Test drives of autonomous Next buses and Olli cars. Developing V2V technologies

Hungary ZalaZone proving ground. Developing an autonomous parking system to use in garage complexes

Russia Lunching a self-driving taxi. Autonomous delivery robots. Test drives of unmanned trucks

Chile Autonomous haul trucks in mining works. Testing self-driving buses on public roads. A plan to reach a 40 % level in using electric vehicles

Mexico Plans to learn from the USA experience

India Plans to increase the share of electric vehicles

Brazil Autonomous haul trucks in mining operations

the development of a unified management system in order to ensure cooperation and coordination.

Secondly, in order to improve the efficiency of using highly autonomous vehicles, the present infrastructure should be transformed and HAVs need to be tested on public roads.

Thirdly, the formation of the smart city transport and logistics system requires a new approach based on a digital road model, which can handle the problem of TLS congestion on a fast-track basis. Such an approach will ensure the turnover of resources and increase mobility

within the theory of sustainable development, as well as improve the environmental situation.

Table 3 presents the rankings of the world's smart cities implementing innovations in the field of mobility, transport and logistics.

Today's development of the smart city transport and logistics systems allow us to draw the following conclusions.

1. There exist successful practices of TLS implementation in which the congestion level is quite low with regard to the city's population (Tokyo, London, Vienna,

Table 3 - Main rankings of smart cities and their indicators in the field of traffic and congestion i

of the transport and logistics system, 2020 3

Таблица 3 - Основные рейтинги умных городов и их показатели в области трафика и перегруженности §

транспортно-логистической системы, 2020 Я

о

M

City IESE1 GPCI2 GCI3 EPSCI4 Traffic5 Congestion6, %

Index Min CO2 emissions per capita, tonnes

1. London 1 1 2 3 155.42 43.85 0.45 31

2. New York 2 2 1 1 161.50 42.79 0.71 26

3. Amsterdam 3 6 23 30 97.90 29.47 0.51 18

4. Paris 4 4 3 6 152.02 41.56 0.66 32

5. Reykjavik 5 - - - 90.99 19.96 0.80 16

6. Tokyo 6 3 4 2 130.48 41.20 0.27 41

7. Singapore 7 5 9 5 147.60 41.23 0.59 27

8. Copenhagen 8 19 - 47 86.91 28.58 0.39 18

9. Berlin 9 7 15 12 100.57 33.88 0.31 30

10. Vienna 10 16 22 25 77.79 26.45 0.36 26

11. Hong Kong 11 9 6 56 145.69 42.72 0.39 30

12. Seoul 12 8 17 14 157.47 42.14 0.72 -

13. Stockholm 13 22 - 32 120.56 35.91 0.53 23

14. Oslo 14 - - 42 109.14 31.34 0.66 20

15. Zurich 15 20 - 62 102.34 33.64 0.37 27

16. Los Angeles 16 12 7 4 340.31 60.35 3.63 27

17. Chicago 17 25 8 7 191.20 42.07 1.81 17

18. Toronto 18 18 19 10 203.02 45.15 1.62 22

19. Sydney 19 11 11 15 194.17 39.88 1.64 28

20. Melbourne 20 14 18 11 176.39 40.51 1.52 23

21. San Francisco 21 24 13 9 254.06 50.90 2.19 21

22. Helsinki 22 32 - 58 92.82 30.86 0.40 15

23. Washington 23 36 10 19 187.48 40.37 1.95 17

24. Madrid 24 13 16 28 137.67 35.03 1.08 15

25. Boston 25 27 21 8 213.08 45.42 2.0 15

87. Moscow 87 30 20 97 219.33 51.31 1.09 54

Note:1IESE Cities in Motion Index 2020. https://media.iese.edu/research/pdfs/ST-0542-E.pdf; 2Global Power City Index 2020. http:// mori-m-foundation.or.jp/pdf/GPCI2020_summary.pdf; 3Global City Index. https://www.kearney.com/global-cities/2020; 4EasyPark Smart City Index 2020. https://www.easyparkgroup.com/smart-cities-index; 5Numbeo. https://www.numbeo.com; 6TomTom. Traffic congestion ranking. https://www.tomtom.com.

Berlin, Copenhagen, etc.); many of them create ultra-low emission zones (London, Amsterdam, Berlin, Stockholm, Oslo, etc.) and advance electric transport and related infrastructure. Their development models can be viewed as best practices.

2. Currently, adaptive ITS solutions are being implemented with Tokyo, Singapore and Seoul leading in this area. The systems of fixation, informing and intelligent information processing are established, which are focused on passenger and freight transport management.

3. Vehicle machine learning occupies the central place among autonomous transport systems technologies. Today, its legal framework is being formulated, new tech-

nologies (V2V, ADAS, CNN, RNN, DRL) and the specific infrastructure are being developed and implemented, as well as consumers are familiarized with these innovations. Singapore, the Netherlands, Norway, the USA, and Finland are the leaders in this area. Many countries are introducing highly autonomous vehicles on public roads.

4. Residents of the megacities use the metro (Tokyo - 58,75 %, New York - 44,12 %, London - 43,58 %, Paris -40,71 %, Seoul - 39,60 %) and trams (Vienna - 11,96 %) as frequently as possible, while other municipalities promote cycling (Rotterdam - 42,86 %, Amsterdam - 40,74 %, Copenhagen - 38,98 %, Berlin - 26,52 %), introduce administrative bans, develop the concept of a multimodal

I community in the field of mobility, and businesses ex-

3 plore alternative delivery methods. £ Thus, the development of the smart city transport

g and logistics service in the world is poorly integrated and

£ mostly characterized by technological improvements

£ that correspond to the scientific paradigm of sustainable

< development.

I

CONCLUSION

The analysis of research publications suggests that the scientific paradigm of sustainable development with the intensive introduction of ICT is only partially formed. From the perspective of the system approach, the formation stages and specifics of transport and logistics systems' evolution, as well as the transformation of the current forms of relationships under digitalization and the growing role of formal and informal institutions, are of great importance. It should be pointed out that the use of the theoretical and methodological toolkit for urban logistics makes it possible to provide additional economic benefits and reduce transaction costs when establishing sustainable regional transport and logistics systems.

The contribution of the scientists listed in the study is substantial and undeniable, and the practical imple-

mentation and adopted technological improvements are arousing intense interest among researchers. However, in the age of the digital economy, there is a need for new theoretical and methodological research in the formation and evolutionary development of the integrated smart city transport and logistics system.

It should be noted that, within the framework of the institutional-evolutionary approach, the systems with the minimum level of transaction costs play a dominant role. Achieving this indicator is only possible with the coordination of the functioning and development of all economic agents. We believe that in these conditions there is a need to provide modelling of the digital logistics institute, which formulates the basic principles and rules for organizing flow processes to attain a higher level of inter-organizational interaction between economic agents in the TLS of a smart city.

The presented analytical review allows drawing a general idea of the trends in the development of the concept of smart mobility in urban areas, as well as determining possible variations in the formation of the smart city transport and logistics systems that provide future savings for all categories of economic agents.

References

Bryazgina E.O., Kurguzov V.B., Belov M.Yu. (2020). Osnovnye vektory razvitiya ITS Rossiyskoy Federatsii [The main vectors of development of the ITS of the Russian Federation]. Transport Rossiyskoy Federatsii - Transport of the Russian Federation, no. 3-4(88-89), pp. 28-30.

Galkin A.V., Sysoev A.S. (2020). Upravlenie transportnymi potokami v intellektual'noy transportnoy sisteme [Traffic management in an intelligent transport system]. Matematicheskie metody v tekhnike i tekhnologiyakh - Mathematical Methods in Technics and Technologies, no. 6, pp. 32-35.

Kosimkhuzhaev A.A., Skoryupina L.S. (2020). Iskusstvennyy intellekt v gorodskoy transportnoy seti [Artificial intelligence in the urban transport network]. Khimiya. Ekologiya. Urbanistika - Chemistry. Environment. Urban studies, no. 3, pp. 118-122.

Naniev A.T. (2020). Voprosy pravovoy reglamentatsii bespilotnogo (avtonomnogo) transporta v Rossiyskoy Federatsii [Issues of legal regulation of unmanned (autonomous) transport in the Russian Federation]. Innovatsii. Nauka. Obrazovanie - Innovations. Science. Education, no. 19, pp. 336-339.

Popov E.V. (2020). Ekonotronika [Econotronics]. Tyumen: TSU Publisher.

Savin G.V. (2020a). Transportno-logisticheskaya sistema «umnogo» goroda: teoriya ipraktika [Transport and logistics system of the "smart" city: Theory and practice]. Moscow: Pervoe ekonomicheskoe izdatel'stvo.

Savin G.V. (2020b). Pokazatel' kachestva transportno-logisticheskoy sistemy umnogo goroda [Quality indicator of the smart city transportation and logistics system]. Ekonomicheskiy analiz: teoriya i praktika - Economic Analysis: Theory and Practice, vol. 9, no. 11(506), pp. 2116-2135. https://doi.org/10.24891/ea.19.11.2116.

Aleta N.B., Alonso C.M., Ruiz R.M.A. (2017). Smart mobility and smart environment in the Spanish cities. Transportation Research Procedia, vol. 24, pp. 163-170. https://doi.org/10.1016/j.trpro.2017.05.084.

Aljohani K., Thompson R.G. (2016). Impacts of logistics sprawl on the urban environment and logistics: Taxonomy and review of literature. Journal of Transport Geography, vol. 57, pp. 255-263. https://doi.org/10.1016/j.jtrangeo.2016.08.009.

Amoretti M., Belli L., Zanichelli F. (2017). UTravel: Smart mobility with a novel user profiling and recommendation approach. Pervasive and Mobile Computing, vol. 38, part 2, pp. 474-489. https://doi.org/10.1016/j.pmcj.2016.08.008.

Anda C., Erath A., Fourie P.J. (2017). Transport modelling in the age of big data. International Journal of Urban Science, vol. 21, Issue sup1: Special Issue: Future Cities, pp. 19-42. https://doi.org/10.1080/12265934.2017.1281150.

Asghari M., Mirzapour Al-e-hashem S.M.J. (2021). Green vehicle routing problem: A state-of-the-art review. International Journal of Production Economics, vol. 231, 107899. https://doi.org/10.1016/jJjpe.2020.107899.

Balasubramaniam A., Jami G.M.J., Menon V.G., Paul A. (2021). Blockchain for intelligent transport system. IETE Technical Review, vol. 38, no. 4, pp. 438-449. https://doi.org/10.1080/02564602.2020.1766385.

Barns S., Cosgrave E., Acuto M., Mcneill D. (2017). Digital infrastructures and urban governance. Urban Policy and Research, vol. 35, issue 1, pp. 20-31. https://doi.org/10.1080/08111146.2016.1235032.

EE

Beaver L.E., Chalaki B., Mahbub A.M.I., Zhao L., Zayas R., Malikopoulos A.A. (2020). Demonstration of a time-efficient mobility system using a scaled smart city. Vehicle System Dynamics, vol. 58, issue 5, pp. 787-804. https://doi.org/10.1080/00423114. 2020.1730412.

Behrendt F. (2020). Mobility and data: Cycling the utopian Internet of Things. Mobilities, vol. 15, issue 1, pp. 81-105. https://doi. org/10.1080/17450101.2019.1698763.

Belbachir A., El Fallah-Seghrouchni A., Casals A., Pasin M. (2019). Smart mobility using multi-agent system. Procedia Computer Science, vol. 151, pp. 447-454. https://doi.org/10.1016/j.procs.2019.04.061.

Bibri S.E., Krogstie J. (2017). Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustainable Cities and Society, vol. 31, pp. 183-212. https://dx.doi.org/10.1016Zj.scs.2017.02.016.

Binetti M., Caggiani L., Camporeale R., Ottomanelli M. (2019). A sustainable crowdsourced delivery system to foster free-float- «j ing bike-sharing. Sustainability, vol. 11, issue 10, 2772. https://doi.org/10.3390/su11102772.

Bonnefon J.F., Shariff A., Rahwan I. (2016). The social dilemma of autonomous vehicles. Science, vol. 352, issue 6293, pp. 15731576. DOI: 10.1126/science.aaf2654. S

Bucchiarone A. (2019). Collective adaptation through multi-agents ensembles: The case of smart urban mobility. ACM Transactions on Autonomous and Adaptive Systems, vol. 14, issue 2, Article No.: 6, pp. 1-28. https://doi.org/10.1145/3355562.

Caird S.P., Hallett S.H. (2019). Towards evaluation design for smart city development. Journal of Urban Design, vol. 24, issue 2, pp. 188-209. https://doi.org/10.1080/13574809.2018.1469402.

Ceder A.A. (2021). Urban mobility and public transport: Future perspectives and review. International Journal of Urban Sciences, vol. 25, issue 4, pp. 455-479. https://doi.org/10.1080/12265934.2020.1799846.

Cocchia A. (2014). Smart and digital city: A systematic literature review. In: R. Dameri, C. Rosenthal-Sabroux (Eds.). Smart City. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-06160-3_2.

Cortes-Murcia D.L., Prodhon C., Murat Afsar H. (2019). The electric vehicle routing problem with time windows, partial recharges and satellite customers. Transportation Research Part E: Logistics and Transportation Review, vol. 130, pp. 184-206. https:// doi.org/10.1016/j.tre.2019.08.015.

Cugurullo F., Acheampong R.A., Gueriau M., Dusparic I. (2021). The transition to autonomous cars, the redesign of cities and the future of urban sustainability. Urban Geography, vol. 42, issue 6, pp. 1-27. doi.org/10.1080/02723638.2020.1746096.

Dai Q., Jia H., Liu Y. (2020). Private vehicle-based crowdshipping for intercity express transportation: Feasibility assessment. International Journal of Distributed Sensor Networks, vol. 16. https://doi.org/10.1177/1550147720908203.

Del Vecchio P., Secundo G., Maruccia Y., Passiante G. (2019). A system dynamic approach for the smart mobility of people: Implications in the age of big data. Technological Forecasting and Social Change, vol. 149, 119771. https://doi.org/10.1016/j. techfore.2019.119771.

Devari A., Nikolaev A.G., He Q. (2017). Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers. Transportation Research Part E: Logistics and Transportation Review, vol. 105, pp. 105-122. https:// doi.org/10.1016/j.tre.2017.06.011.

Docherty I., Marsden G., Anable J. (2018). The governance of smart mobility. Transportation Research Part A: Policy and Practice, vol. 115, pp. 114-125. https://doi.org/10.10167j.tra.2017.09.012.

Dolati Neghabadi P., Evrard Samuel K., Espinouse M.-L. (2019). Systematic literature review on city logistics: Overview, classification and analysis. International Journal of Production Research, vol. 57, issue 3, pp. 865-887. https://doi.org/10.1080/00207 543.2018.1489153.

Dong C., Ma R., Yin Y., Shi B., Zhang W., Zhang Y. (2020). Traffic conflict analysis of motor vehicles and nonmotor vehicles based on improved cellular automata. Mathematical Problems in Engineering, vol. 2020, Article ID 2529816, pp. 1-11. https://doi. org/10.1155/2020/2529816.

Echebarria C., Barrutia J.M., Aguado-Moralejo I. (2021). The Smart City journey: A systematic review and future research agenda. Innovation: The European Journal of Social Science Research, vol. 34, issue 2, pp. 159-201. https://doi.org/10.1080/13511610 .2020.1785277.

Elisa N., Yang L., Chao F., Cao Y. (2018). A framework of blockchain-based secure and privacy-preserving E-government system. Wireless Networks. https://doi.org/10.1007/s11276-018-1883-0.

Fontaine P., Crainic T.G., Jabali O., Rei W. (2021). Scheduled service network design with resource management for two-tier multimodal city logistic. European Journal of Operational Research, vol. 294, issue 2, pp. 558-570. https://doi.org/10.1016/j. ejor.2021.02.009.

Fu Y., Zhu J. (2021). Trusted data infrastructure for smart cities: A blockchain perspective. Building Research & Information. vol. 49, issue 1, pp. 21-37. https://doi.org/10.1080/09613218.2020.1784703.

Gatta V., Marcucci E., Nigro M., Serafini S. (2019). Sustainable urban freight transport adopting public transport-based crowd-shipping for B2C deliveries. European Transport Research Review, vol. 11, article no. 13. https://doi.org/10.1186/s12544-019-0352-x.

Gatta V., Marcucci E., Site P.D., Pira M.L., Carrocci C.S. (2019). Planning with stakeholders: Analysing alternative off-hour delivery solutions via an interactive multi-criteria approach. Research in Transportation Economics, vol. 73, pp. 53-62. https://doi. org/10.1016/j.retrec.2018.12.004.

Gohar M., Muzammal M., Ur Rahman A. (2018). SMART TSS: Defining transportation system behavior using big data analytics in smart cities. Sustainable Cities and Society, vol. 41, pp. 114-119. https://doi.org/10.1016/j.scs.2018.05.008.

Groth S. (2019). Multimodal divide: Reproduction of transport poverty in smart mobility trends. Transportation Research Part A: Policy and Practice, vol. 125, pp. 56-71. https://doi.org/10.1016/j.tra.2019.04.018.

8 • Государственное и муниципальное управление

® Guo H., Li W., Nejad M., Shen C.-C. (2020). Proof-of-event recording system for autonomous vehicles: A blockchain-based solu-fi tion. IEEE Access, vol. 8, 182776-182786.

s Guo Y.-M., Huang Z.-L., Guo J., Li H., Guo X.-R., Nkeli M.J. (2019). Bibliometric Analysis on Smart Cities Research. Sustainability, ^ vol. 11, issue 13. https://doi.org/10.3390/su11133606.

o Hammi M.T., Hammi B., Bellot P., Serhrouchni A. (2018). Bubbles of trust: A decentralized blockchain based authentication sys-=j tem for IoT. Computers & Security, vol. 78, pp. 126-142. https://doi.org/10.1016/j.cose.2018.06.004. £ Ho C.Q., Hensher D.A., Reck D.J., Lorimer S., Lu I. (2021). MaaS bundle design and implementation: Lessons from the Sydney S MaaS trial. Transportation Research Part A: Policy and Practice, vol. 149, pp. 339-376. https://doi.org/10.10167j.tra.2021.05.010. g Hu W., Dong J., Hwang B.-g., Ren R., Chen Z. (2019). A scientometrics review on city logistics literature: Research trends, advanced theory and practice. Sustainability, vol. 11, issue 10, 2724. https://doi.org/10.3390/su11102724.

Janik A., Ryszko A., Szafraniec M. (2020). Scientific landscape of smart and sustainable cities literature: A bibliometric analysis. Sustainability, vol. 12, issue 3, 779. https://doi.org/10.3390/su12030779.

Jin S.T., Kong H., Sui D.Z. (2019). Uber, public transit, and urban transportation equity: A case study in New York City. The Professional Geographer, vol. 71, issue 2, pp. 315-330. https://doi.org/10.1080/00330124.2018.1531038.

Johansson E., Hiselius L.W., Koglin T., Wretstrand A. (2017). Evaluation of public transport: Regional policies and planning practices in Sweden. Urban, Planning and Transport Research, vol. 5, pp. 59-77. D0I:10.1080/21650020.2017.1395291.

Komninos N., Kakderi C., Collado A., Papadaki I., Panori A. (2021). Digital transformation of city ecosystems: Platforms shaping engagement and externalities across vertical markets. Journal of Urban Technology, vol. 28, issue 1-2, pp. 93-114. https://doi. org/10.1080/10630732.2020.1805712.

Kramers A., Hojer M., Lovehagen N., Wangel J. (2014). Smart sustainable cities-Exploring ICT solutions for reduced energy use in cities. Environmental Modelling and Software, vol. 56, pp. 52-62. https://doi.org/10.1016/j.envsoft.2013.12.019.

Kronsell A., Mukhtar-Landgren D. (2020), Experimental governance of smart mobility: Some normative implications (pp. 119135). In: A. Paulsson, C.H. S0rensen (Eds.). Shaping smart mobility futures: Governance and policy instruments in times of sustainability transitions. Emerald Publishing Limited, Bingley. https://doi.org/10.1108/978-1-83982-650-420201007.

Lagorio A., Pinto R., Golini R. (2017). Urban logistics ecosystem: A system of system framework for stakeholders in urban freight transport projects. IFAC-PapersOnLine, vol. 50, issue 1, pp. 7284-7289. https://doi.org/10.1016/j.ifacol.2017.08.1402.

Lim S.F.W.T., Jin X., Srai J.S. (2018). Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution & Logistics Management, vol. 48, no. 3, pp. 308-332. https://doi.org/10.1108/IJPDLM-02-2017-0081.

Longo A., Zappatore M., Navathe S.B. (2019). The unified chart of mobility services: Towards a systemic approach to analyze service quality in smart mobility ecosystem. Journal of Parallel and Distributed Computing, vol. 127, pp. 118-133. https://doi. org/10.1016/j.jpdc.2018.12.009.

Lopez D., Farooq B. (2020). A multi-layered blockchain framework for smart mobility data-markets. Transportation Research Part C: Emerging Technologies, vol. 111, pp. 588-615. https://doi.org/10.1016/j.trc.2020.01.002.

Macrina G., Di Puglia Pugliese L., Guerriero F., Laporte G. (2020). Drone-aided routing: A literature review. Transportation Research Part C: Emerging Technologies, vol. 120, 102762. https://doi.org/10.1016/j.trc.2020.102762.

Martinho A., Herber N., Kroesen M., Chorus C. (2021). Ethical issues in focus by the autonomous vehicles industry. Transport Reviews, vol. 41, issue 5, pp. 556-577. https://doi.org/10.1080/01441647.2020.1862355.

Mathirajan M., Devadas R., Ramanathan R. (2021). Transport analytics in action: A cloud-based decision support system for efficient city bus transportation. Journal of Information and Optimization Sciences, vol. 42, issue 2, pp. 371-416. https://doi.or g/10.1080/02522667.2019.1688948.

Melacini M., Perotti S., Rasini M., Tappia E. (2018). E-fulfilment and distribution in omni-channel retailing: A systematic literature review. International Journal of Physical Distribution & Logistics Management, vol. 48, no. 4, pp. 391-414. https://doi. org/10.1108/IJPDLM-02-2017-0101.

Mello Bandeira R.A., Goes G.V., Schmitz Gon^alves D.N., Almedia D'Agosto M., Oliveira C.M.d. (2019). Electric vehicles in the last mile of urban freight transportation: A sustainability assessment of postal deliveries in Rio de Janeiro-Brazil. Transportation Research Part D: Transport and Environment, vol. 67, pp. 491-502. https://doi.org/10.1016Zj.trd.2018.12.017.

Minoli D., Sohraby K., Occhiogrosso B. (2017). IoT considerations, requirements, and architectures for smart buildings-energy optimization and next-generation building management systems. IEEE Internet Things Journal, vol. 4, issue 1, pp. 269-283. DOI: 10.1109/JI0T.2017.2647881.

Mirri S., Prandi C., Salomoni P., Callegati F., Melis A., Prandini M. (2016). A service-oriented approach to crowdsensing for accessible smart mobility scenarios. Mobile Information Systems, vol. 2016, Article ID 2821680. https://doi.org/10.1155/2016/2821680.

Moghdani R., Salimifard K., Demir E., Benyettou A. (2021). The green vehicle routing problem: A systematic literature review. Journal of Cleaner Production, vol. 279, 123691. https://doi.org/10.1016/jjclepro.2020.123691.

Mora L., Bolici R., Deakin M. (2017). The first two decades of smart-city research: A bibliometric analysis. Journal of Urban Technology, vol. 24, issue 1, pp. 3-27. https://doi.org/10.1080/10630732.2017.1285123.

Moradi S. (2020). The scientometrics of literature on smart cities. Library Hi Tech, vol. 38, no. 2, pp. 385-398. https://doi. org/10.1108/LHT-12-2018-0203.

Moreno C., Allam Z., Chabaud D., Gall C., Pratlong F. (2021). Introducing the"15-Minute City": Sustainability, Resilience and place identity in future post-pandemic cities. Smart Cities, vol. 4, issue 1, pp. 93-111. https://doi.org/10.3390/smartcities4010006.

Mourad A., Puchinger J., van Woensel T. (2021). Integrating autonomous delivery service into a passenger transportation sys- ® tem. International Journal of Production Research. vol. 59, issue 7, pp. 2116-2139. https://doi.org/10.1080/00207543.2020.1 * 746850. ^

о

Mukhtar-Landgren D., Paulsson A. (2021). Governing smart mobility: Policy instrumentation, technological utopianism, and ^ the administrative quest for knowledge. Administrative Theory & Praxis, vol. 43, issue 2, pp. 135-153. https://doi.org/10.108 о 0/10841806.2020.1782111. g

Müller W.M., Wirtz B.W., Schmidt F. (2020). Public smart service provision in smart cities: A case-study-based approach. Interna- < tional Journal of Public Administration, vol. 43, issue 6, pp. 499-516. https://doi.org/10.1080/01900692.2019.1636395. §

Naz M., Al-zahrani F.A., Khalid R., Javaid N., Qamar A.M., Afzal M.K., Shafiq M. (2019). A secure data sharing platform using block- jjj chain and interplanetary file system. Sustainability, vol. 11, no. 24, 7054. https://doi.org/10.3390/su11247054. ¡¡¡r

Oliveira C.M.d., Mello Bandeira R.A., Goes G.V., Schmitz Gon^alves D.N., Almeida D'Agosto M. (2017). Sustainable vehicles-based £ alternatives in last mile distribution of urban freight transport: A Systematic literature review. Sustainability, vol. 9, issue 8, 1324. https://doi.org/10.3390/su9081324. |

Olsson J., Hellström D., Pálsson H. (2019). Framework of last mile logistics research: A systematic review of the literature. Sustain- = ability, vol. 11, no. 24, 7131. https://doi.org/10.3390/su11247131.

Pahwa D., Starly B. (2021). Dynamic matching with deep reinforcement learning for a two-sided Manufacturing-as-a-Service (MaaS) marketplace. Manufacturing Letters, vol. 29, pp. 11-14. https://doi.org/10.1016/j.mfglet.2021.05.005.

Paiva S., Ahad M.A., Tripathi G., Feroz N., Casalino G. (2021). Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges. Sensors, vol. 21, issue 6, 2143. https://doi.org/10.3390/s21062143.

Pan S., Zhou W., Piramuthu S., Giannikas V., Chen C. (2021). Smart city for sustainable urban freight logistics. International Journal of Production Research, vol. 59, issue 7, pp. 2079-2089. https://doi.org/10.1080/00207543.2021.1893970.

Patella S.M., Grazieschi G., Gatta V., Marcucci E., Carrese S. (2021). The adoption of green vehicles in last mile logistics: A systematic review. Sustainability, vol. 13, issue 1, 6. https://doi.org/10.3390/su13010006.

Perboli G., Rosano M. (2019). Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models. Transportation Research Part C: Emerging Technologies, vol. 99, pp. 19-36. https://doi.org/10.1016/j. trc.2019.01.006.

Pereira G., Parycek P., Falco E., Kleinhans R. (2018). Smart governance in the context of smart cities: A literature review. Information Polity, vol. 23, no. 2, pp. 143-162. https://doi.org/10.3233/IP-170067.

Pérez L.M., Oltra-Badenes R., Oltra Gutiérrez J.V., Gil-Gómez H. (2020). A bibliometric diagnosis and analysis about smart cities. Sustainability, vol. 12, no. 16, 6357. https://doi.org/10.3390/su12166357.

Rafael S., Correia L.P., Lopes D., Bandeira J., Coelho M.C., Andrade M., Borrego C., Miranda A.I. (2020). Autonomous vehicles opportunities for cities air quality. Science of The Total Environment, vol. 712, 136546. https://doi.org/10.1016/j.scito-tenv.2020.136546.

Ranieri L., Digiesi S., Silvestri B., Roccotelli M. (2018). A review of last mile logistics innovations in an externalities cost reduction vision. Sustainability, vol. 10, no. 3, 782. https://doi.org/10.3390/su10030782.

Reda A.K., Gebresenbet G., Tavasszy L., Ljungberg D. (2020). Identification of the regional and economic contexts of sustainable urban logistics policies. Sustainability, vol. 12, no. 20, 8322. https://doi.org/10.3390/su12208322.

Ren R., Hu W., Dong J., Sun B., Chen Y., Chen Z. (2020). A systematic literature review of green and sustainable logistics: Bibliometric analysis, research trend and knowledge taxonomy. International Journal of Environmental Research and Public Health, vol. 17, no. 1, 261. https://doi.org/10.3390/ijerph17010261.

Rodrigues N., Vale M., Costa P. (2020). Urban experimentation and smart cities: A Foucauldian and autonomist approach. Territory, Politics, Governance, vol. 14, pp. 1-19. https://doi.org/10.1080/21622671.2020.1777896.

Rong K., Xiao F., Wang Y. (2019). Redundancy in the sharing economy. Resources, Conservation and Recycling, vol. 151, 104455. https://doi.org/10.1016/j.resconrec.2019.104455.

Ruhlandt R.W.S. (2018). The governance of smart cities: A systematic literature review. Cities, vol. 81, pp. 1-23. https://doi. org/10.1016/j.cities.2018.02.014.

Savin G. (2020c). Smart City Logistics. First conference on sustainable development: Industrial future of territories, vol. 208, article no. 04005. https://doi.org/10.1051/e3sconf/202020804005.

Savin G. (2021). Information support of the flow processes in the smart city transport and logistics system: methodology basis. International scientific forum on computer and energy Sciences, WFCES. https://doi.org/10.1051/e3sconf/202127001017.

Savin G., Bronnikov S.A. (2018). Design to the city transport and logistics system in the conditions of increase of rates of institutional and technological changes. Business Logistics in Modern Management Proceedings of the 18th international scientific conference. Pp. 485-500.

Schneider P., Folkens L., Meyer A., Fauk T. (2019). Sustainability and dimensions of a nexus approach in a sharing economy. Sustainability, vol. 11, no. 3, 909. https://doi.org/10.3390/su11030909.

Schwerdfeger S., Boysen N. (2020). Optimizing the changing locations of mobile parcel lockers in last-mile distribution. European Journal of Operational Research, vol. 285, issue 3, pp. 1077-1094. https://doi.org/10.1016/j.ejor.2020.02.033.

Sharifi A. (2020). A typology of smart city assessment tools and indicator sets. Sustainable Cities and Society, vol. 53, 101936. https://doi.org/10.10167j.scs.2019.101936.

Shavarani S.M., Mosallaeipour S., Golabi M., izbirak G. (2019). A congested capacitated multi-level fuzzy facility location problem: An efficient drone delivery system. Computers & Operations Research, vol. 108, pp. 57-68. https://doi.org/10.1016/j. cor.2019.04.001.

® Simoni M.D., Marcucci E., Gatta V., Claudel C.G. (2020). Potential last-mile impacts of crowdshipping services: A simulation* based evaluation. Transportation, vol. 47, pp. 1933-1954. https://doi.org/10.1007/s11116-019-10028-4. s Szmelter-Jarosz A., Rzesny-Ciepliñska J. (2020). Priorities of urban transport system stakeholders according to crowd logistics ^ solutions in city areas. A sustainability perspective. Sustainability, vol. 12, no. 1, 317. https://doi.org/10.3390/su12010317. о Talari S., Shafie-khah M., Siano P., Loia V., Tommasetti A., Catalao J.P.S. (2017). A review of smart cities based on the Internet of =j Things concept. Energies, vol. 10, no. 4, 421. https://doi.org/10.3390/en10040421.

ш Tompson T. (2017). Understanding the contextual development of smart city initiatives: A pragmatist methodology. SheJi:The < Journal of Design, Economics, and Innovation, vol. 3, issue 3, pp. 210-228. https://doi.org/10.1016/j.sheji.2017.11.004. g Valcárcel-Aguiar B., Murias P., Rodríguez-González D. (2019). Sustainable urban liveability: A practical proposal based on a composite indicator. Sustainability, vol. 11, no. 1, 86. https://doi.org/10.3390/su11010086.

Viu-Roig M., Alvarez-Palau E.J. (2020). The impact of e-commerce-related last-mile logistics on cities: A systematic literature review. Sustainability, vol. 12, no. 16, 6492. https://doi.org/10.3390/su12166492.

Wamba S.F., Queiroz M.M. (2019). A bibliometric analysis and research agenda on smart cities. IFIP Advances in Information and Communication Technology, vol. 558. Springer, Cham. https://doi.org/10.1007/978-3-030-20671-0_22.

Wang H., Quan W., Ochieng W.Y. (2020). Smart Road stud based two-lane traffic surveillance. Journal of Intelligent Transportation Systems, vol. 24, issue 5, pp. 480-493. http://dx.doi.org/10.1080/15472450.2019.1610405.

Yigitcanlar T., Kamruzzaman M. (2019). Smart Cities and mobility: Does the smartness of Australian cities lead to sustainable commuting patterns? Journal of Urban Technology, vol. 26, no. 2, pp. 21-46. https://doi.org/10.1080/10630732.2018.14767 94.

Zhang M., Sun M., Bi D., Liu T. (2020). Green logistics development decision-making: Factor identification and hierarchical framework construction. IEEE Access, 8, pp. 1198-1205.

Zhao L., Tang Z.-Y., Zou X. (2019). Mapping the knowledge domain of smart-city research: A bibliometric and scientometric analysis. Sustainability, vol. 11, pp. 127897-127912. DOI: 10.1109/ACCESS.2020.3008443.

Zheng C., Yuan J., Zhu L., Zhang Y., Shao Q. (2020). From digital to sustainable: A scientometric review of smart city literature between 1990 and 2019. Journal of Cleaner Production, vol. 258, 120689. https://doi.org/10.1016/j.jclepro.2020.120689.

Источники

Брязгина Е.О., Кургузов В.Б., Белов М.Ю. (2020). Основные векторы развития ИТС Российской Федерации // Транспорт Российской Федерации. № 3-4 (88-89). С. 28-30.

Галкин А.В., Сысоев А.С. (2020). Управление транспортными потоками в интеллектуальной транспортной системе // Математические методы в технике и технологиях. №. 6. С. 32-35.

Косимхужаев А.А., Скорюпина Л.С. (2020). Искусственный интеллект в городской транспортной сети // Химия. Экология. Урбанистика. № 3. С. 118-122.

Наниев А.Т. (2020). Вопросы правовой регламентации беспилотного (автономного) транспорта в Российской Федерации // Инновации. Наука. Образование. № 19. С. 336-339.

Попов Е.В. (2020). Эконотроника: монография. Тюмень: Издательство Тюменского государственного университета.

Савин Г.В. (2020a). Транспортно-логистическая система «умного» города: теория и практика. Москва: Первое экономическое издательство.

Савин Г.В. (2020b). Показатель качества транспортно-логистической системы умного города // Экономический анализ: теория и практика. Т. 9., №11 (506). С. 2116-2135. https://doi.org/10.24891/ea.19.11.2116.

Aleta N.B., Alonso C.M., Ruiz R.M.A. (2017). Smart mobility and smart environment in the Spanish cities. Transportation Research Procedia, vol. 24, pp. 163-170. https://doi.org/10.1016/j.trpro.2017.05.084.

Aljohani K., Thompson R.G. (2016). Impacts of logistics sprawl on the urban environment and logistics: Taxonomy and review of literature. Journal of Transport Geography, vol. 57, pp. 255-263. https://doi.org/10.1016/jjtrangeo.2016.08.009.

Amoretti M., Belli L., Zanichelli F. (2017). UTravel: Smart mobility with a novel user profiling and recommendation approach. Pervasive and Mobile Computing, vol. 38, part 2, pp. 474-489. https://doi.org/10.1016/j.pmcj.2016.08.008.

Anda C., Erath A., Fourie P.J. (2017). Transport modelling in the age of big data. International Journal of Urban Science, vol. 21, Issue sup1: Special Issue: Future Cities, pp. 19-42. https://doi.org/10.1080/12265934.2017.1281150.

Asghari M., Mirzapour Al-e-hashem S.M.J. (2021). Green vehicle routing problem: A state-of-the-art review. International Journal of Production Economics, vol. 231, 107899. https://doi.org/10.1016/j.ijpe.2020.107899.

Balasubramaniam A., Jami G.M.J., Menon V.G., Paul A. (2021). Blockchain for intelligent transport system. IETE Technical Review, vol. 38, no. 4, pp. 438-449. https://doi.org/10.1080/02564602.2020.1766385.

Barns S., Cosgrave E., Acuto M., Mcneill D. (2017). Digital infrastructures and urban governance. Urban Policy and Research, vol. 35, issue 1, pp. 20-31. https://doi.org/10.1080/08111146.2016.1235032.

Beaver L.E., Chalaki B., Mahbub A.M.I., Zhao L., Zayas R., Malikopoulos A.A. (2020). Demonstration of a time-efficient mobility system using a scaled smart city. Vehicle System Dynamics, vol. 58, issue 5, pp. 787-804. https://doi.org/10.1080/00423114. 2020.1730412.

Behrendt F. (2020). Mobility and data: Cycling the utopian Internet of Things. Mobilities, vol. 15, issue 1, pp. 81-105. https://doi. org/10.1080/17450101.2019.1698763.

Belbachir A., El Fallah-Seghrouchni A., Casals A., Pasin M. (2019). Smart mobility using multi-agent system. Procedia Computer Science, vol. 151, pp. 447-454. https://doi.org/10.1016/j.procs.2019.04.061.

EE

Bibri S.E., Krogstie J. (2017). Smart sustainable cities of the future: An extensive interdisciplinary literature review. Sustainable ® Cities and Society, vol. 31, pp. 183-212. https://dx.doi.Org/10.1016/j.scs.2017.02.016. ^

Binetti M., Caggiani L., Camporeale R., Ottomanelli M. (2019). A sustainable crowdsourced delivery system to foster free-float- ^ ing bike-sharing. Sustainability, vol. 11, issue 10, 2772. https://doi.org/10.3390/su11102772. >

Bonnefon J.F., Shariff A., Rahwan I. (2016). The social dilemma of autonomous vehicles. Science, vol. 352, issue 6293, pp. 1573- о 1576. DOI: 10.1126/science.aaf2654. g

Bucchiarone A. (2019). Collective adaptation through multi-agents ensembles: The case of smart urban mobility. ACM Transac- | tions on Autonomous and Adaptive Systems, vol. 14, issue 2, Article No.: 6, pp. 1-28. https://doi.org/10.1145/3355562. |

Caird S.P., Hallett S.H. (2019). Towards evaluation design for smart city development. Journal of Urban Design, vol. 24, issue 2,

pp. 188-209. https://doi.org/10.1080/13574809.2018.1469402. £

Ceder A.A. (2021). Urban mobility and public transport: Future perspectives and review. International Journal of Urban Sciences, z vol. 25, issue 4, pp. 455-479. https://doi.org/10.1080/12265934.2020.1799846. £

Cocchia A. (2014). Smart and digital city: A systematic literature review. In: R. Dameri, C. Rosenthal-Sabroux (Eds.). Smart City. « Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-06160-3_2. =

Cortes-Murcia D.L., Prodhon C., Murat Afsar H. (2019). The electric vehicle routing problem with time windows, partial recharges and satellite customers. Transportation Research Part E: Logistics and Transportation Review, vol. 130, pp. 184-206. https:// doi.org/10.1016/j.tre.2019.08.015. Cugurullo F., Acheampong R.A., Gueriau M., Dusparic I. (2021). The transition to autonomous cars, the redesign of cities and the

future of urban sustainability. Urban Geography, vol. 42, issue 6, pp. 1-27. doi.org/10.1080/02723638.2020.1746096. Dai Q., Jia H., Liu Y. (2020). Private vehicle-based crowdshipping for intercity express transportation: Feasibility assessment.

International Journal of Distributed Sensor Networks, vol. 16. https://doi.org/10.1177/1550147720908203. Del Vecchio P., Secundo G., Maruccia Y., Passiante G. (2019). A system dynamic approach for the smart mobility of people: Implications in the age of big data. Technological Forecasting and Social Change, vol. 149, 119771. https://doi.org/10.1016/j. techfore.2019.119771.

Devari A., Nikolaev A.G., He Q. (2017). Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers. Transportation Research Part E: Logistics and Transportation Review, vol. 105, pp. 105-122. https:// doi.org/10.1016/j.tre.2017.06.011. Docherty I., Marsden G., Anable J. (2018). The governance of smart mobility. Transportation Research Part A: Policy and Practice,

vol. 115, pp. 114-125. https://doi.org/10.1016/j.tra.2017.09.012. Dolati Neghabadi P., Evrard Samuel K., Espinouse M.-L. (2019). Systematic literature review on city logistics: Overview, classification and analysis. International Journal of Production Research, vol. 57, issue 3, pp. 865-887. https://doi.org/10.1080/00207 543.2018.1489153.

Dong C., Ma R., Yin Y., Shi B., Zhang W., Zhang Y. (2020). Traffic conflict analysis of motor vehicles and nonmotor vehicles based on improved cellular automata. Mathematical Problems in Engineering, vol. 2020, Article ID 2529816, pp. 1-11. https://doi. org/10.1155/2020/2529816.

Echebarria C., Barrutia J.M., Aguado-Moralejo I. (2021). The Smart City journey: A systematic review and future research agenda. Innovation: The European Journal of Social Science Research, vol. 34, issue 2, pp. 159-201. https://doi.org/10.1080/13511610 .2020.1785277.

Elisa N., Yang L., Chao F., Cao Y. (2018). A framework of blockchain-based secure and privacy-preserving E-government system.

Wireless Networks. https://doi.org/10.1007/s11276-018-1883-0. Fontaine P., Crainic T.G., Jabali O., Rei W. (2021). Scheduled service network design with resource management for two-tier multimodal city logistic. European Journal of Operational Research, vol. 294, issue 2, pp. 558-570. https://doi.org/10.1016/j. ejor.2021.02.009.

Fu Y., Zhu J. (2021). Trusted data infrastructure for smart cities: A blockchain perspective. Building Research & Information. vol. 49,

issue 1, pp. 21-37. https://doi.org/10.1080/09613218.2020.1784703. Gatta V., Marcucci E., Nigro M., Serafini S. (2019). Sustainable urban freight transport adopting public transport-based crowd-shipping for B2C deliveries. European Transport Research Review, vol. 11, article no. 13. https://doi.org/10.1186/s12544-019-0352-x.

Gatta V., Marcucci E., Site P.D., Pira M.L., Carrocci C.S. (2019). Planning with stakeholders: Analysing alternative off-hour delivery solutions via an interactive multi-criteria approach. Research in Transportation Economics, vol. 73, pp. 53-62. https://doi. org/10.1016/j.retrec.2018.12.004. Gohar M., Muzammal M., Ur Rahman A. (2018). SMART TSS: Defining transportation system behavior using big data analytics in

smart cities. Sustainable Cities and Society, vol. 41, pp. 114-119. https://doi.org/10.1016/j.scs.2018.05.008. Groth S. (2019). Multimodal divide: Reproduction of transport poverty in smart mobility trends. Transportation Research Part A:

Policy and Practice, vol. 125, pp. 56-71. https://doi.org/10.10167j.tra.2019.04.018. Guo H., Li W., Nejad M., Shen C.-C. (2020). Proof-of-event recording system for autonomous vehicles: A blockchain-based solution. IEEE Access, vol. 8, 182776-182786. Guo Y.-M., Huang Z.-L., Guo J., Li H., Guo X.-R., Nkeli M.J. (2019). Bibliometric Analysis on Smart Cities Research. Sustainability,

vol. 11, issue 13. https://doi.org/10.3390/su11133606. Hammi M.T., Hammi B., Bellot P., Serhrouchni A. (2018). Bubbles of trust: A decentralized blockchain based authentication system for IoT. Computers & Security, vol. 78, pp. 126-142. https://doi.org/10.1016/j.cose.2018.06.004.

® Ho C.Q., Hensher D.A., Reck D.J., Lorimer S., Lu I. (2021). MaaS bundle design and implementation: Lessons from the Sydney

* MaaS trial. Transportation Research Part A: Policy and Practice, vol. 149, pp. 339-376. https://doi.org/10.10167j.tra.2021.05.010.

§ Hu W., Dong J., Hwang B.-g., Ren R., Chen Z. (2019). A scientometrics review on city logistics literature: Research trends, ad-

^ vanced theory and practice. Sustainability, vol. 11, issue 10, 2724. https://doi.org/10.3390/su11102724.

0 Janik A., Ryszko A., Szafraniec M. (2020). Scientific landscape of smart and sustainable cities literature: A bibliometric analysis.

£ Sustainability, vol. 12, issue 3, 779. https://doi.org/10.3390/su12030779.

ш Jin S.T., Kong H., Sui D.Z. (2019). Uber, public transit, and urban transportation equity: A case study in New York City. TheProfes-

1 sional Geographer, vol. 71, issue 2, pp. 315-330. https://doi.org/10.1080/00330124.2018.1531038.

g Johansson E., Hiselius L.W., Koglin T., Wretstrand A. (2017). Evaluation of public transport: Regional policies and planning practices in Sweden. Urban, Planning and Transport Research, vol. 5, pp. 59-77. D0I:10.1080/21650020.2017.1395291.

Komninos N., Kakderi C., Collado A., Papadaki I., Panori A. (2021). Digital transformation of city ecosystems: Platforms shaping engagement and externalities across vertical markets. Journal of Urban Technology, vol. 28, issue 1-2, pp. 93-114. https://doi. org/10.1080/10630732.2020.1805712.

Kramers A., Höjer M., Lövehagen N., Wangel J. (2014). Smart sustainable cities-Exploring ICT solutions for reduced energy use in cities. Environmental Modelling and Software, vol. 56, pp. 52-62. https://doi.org/10.1016/j.envsoft.2013.12.019.

Kronsell A., Mukhtar-Landgren D. (2020), Experimental governance of smart mobility: Some normative implications (pp. 119135). In: A. Paulsson, C.H. S0rensen (Eds.). Shaping smart mobility futures: Governance and policy instruments in times of sustainability transitions. Emerald Publishing Limited, Bingley. https://doi.org/10.1108/978-1-83982-650-420201007.

Lagorio A., Pinto R., Golini R. (2017). Urban logistics ecosystem: A system of system framework for stakeholders in urban freight transport projects. IFAC-PapersOnLine, vol. 50, issue 1, pp. 7284-7289. https://doi.org/10.1016/j.ifacol.2017.08.1402.

Lim S.F.W.T., Jin X., Srai J.S. (2018). Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution & Logistics Management, vol. 48, no. 3, pp. 308-332. https://doi.org/10.1108/IJPDLM-02-2017-0081.

Longo A., Zappatore M., Navathe S.B. (2019). The unified chart of mobility services: Towards a systemic approach to analyze service quality in smart mobility ecosystem. Journal of Parallel and Distributed Computing, vol. 127, pp. 118-133. https://doi. org/10.1016/j.jpdc.2018.12.009.

Lopez D., Farooq B. (2020). A multi-layered blockchain framework for smart mobility data-markets. Transportation Research Part C: Emerging Technologies, vol. 111, pp. 588-615. https://doi.org/10.1016/j.trc.2020.01.002.

Macrina G., Di Puglia Pugliese L., Guerriero F., Laporte G. (2020). Drone-aided routing: A literature review. Transportation Research Part C: Emerging Technologies, vol. 120, 102762. https://doi.org/10.1016/j.trc.2020.102762.

Martinho A., Herber N., Kroesen M., Chorus C. (2021). Ethical issues in focus by the autonomous vehicles industry. Transport Reviews, vol. 41, issue 5, pp. 556-577. https://doi.org/10.1080/01441647.2020.1862355.

Mathirajan M., Devadas R., Ramanathan R. (2021). Transport analytics in action: A cloud-based decision support system for efficient city bus transportation. Journal of Information and Optimization Sciences, vol. 42, issue 2, pp. 371-416. https://doi.or g/10.1080/02522667.2019.1688948.

Melacini M., Perotti S., Rasini M., Tappia E. (2018). E-fulfilment and distribution in omni-channel retailing: A systematic literature review. International Journal of Physical Distribution & Logistics Management, vol. 48, no. 4, pp. 391-414. https://doi. org/10.1108/IJPDLM-02-2017-0101.

Mello Bandeira R.A., Goes G.V., Schmitz Gonçalves D.N., Almedia D'Agosto M., Oliveira C.M.d. (2019). Electric vehicles in the last mile of urban freight transportation: A sustainability assessment of postal deliveries in Rio de Janeiro-Brazil. Transportation Research Part D: Transport and Environment, vol. 67, pp. 491-502. https://doi.org/10.1016/j.trd.2018.12.017.

Minoli D., Sohraby K., Occhiogrosso B. (2017). IoT considerations, requirements, and architectures for smart buildings-energy optimization and next-generation building management systems. IEEE Internet Things Journal, vol. 4, issue 1, pp. 269-283. DOI: 10.1109/JI0T.2017.2647881.

Mirri S., Prandi C., Salomoni P., Callegati F., Melis A., Prandini M. (2016). A service-oriented approach to crowdsensing for accessible smart mobility scenarios. Mobile Information Systems, vol. 2016, Article ID 2821680. https://doi.org/10.1155/2016/2821680.

Moghdani R., Salimifard K., Demir E., Benyettou A. (2021). The green vehicle routing problem: A systematic literature review. Journal of Cleaner Production, vol. 279, 123691. https://doi.org/10.1016/j.jclepro.2020.123691.

Mora L., Bolici R., Deakin M. (2017). The first two decades of smart-city research: A bibliometric analysis. Journal of Urban Technology, vol. 24, issue 1, pp. 3-27. https://doi.org/10.1080/10630732.2017.1285123.

Moradi S. (2020). The scientometrics of literature on smart cities. Library Hi Tech, vol. 38, no. 2, pp. 385-398. https://doi. org/10.1108/LHT-12-2018-0203.

Moreno C., Allam Z., Chabaud D., Gall C., Pratlong F. (2021). Introducing the"15-Minute City": Sustainability, Resilience and place identity in future post-pandemic cities. Smart Cities, vol. 4, issue 1, pp. 93-111. https://doi.org/10.3390/smartcities4010006.

Mourad A., Puchinger J., van Woensel T. (2021). Integrating autonomous delivery service into a passenger transportation system. International Journal of Production Research. vol. 59, issue 7, pp. 2116-2139. https://doi.org/10.1080/00207543.2020.1 746850.

Mukhtar-Landgren D., Paulsson A. (2021). Governing smart mobility: Policy instrumentation, technological utopianism, and the administrative quest for knowledge. Administrative Theory & Praxis, vol. 43, issue 2, pp. 135-153. https://doi.org/10.108 0/10841806.2020.1782111.

Müller W.M., Wirtz B.W., Schmidt F. (2020). Public smart service provision in smart cities: A case-study-based approach. International Journal of Public Administration, vol. 43, issue 6, pp. 499-516. https://doi.org/10.1080/01900692.2019.1636395.

Naz M., Al-zahrani F.A., Khalid R., Javaid N., Qamar A.M., Afzal M.K., Shafiq M. (2019). A secure data sharing platform using block- ¿ chain and interplanetary file system. Sustainability, vol. 11, no. 24, 7054. https://doi.org/10.3390/su11247054. *

Oliveira C.M.d., Mello Bandeira R.A., Goes G.V., Schmitz Gon^alves D.N., Almeida D'Agosto M. (2017). Sustainable vehicles-based ^ alternatives in last mile distribution of urban freight transport: A Systematic literature review. Sustainability, vol. 9, issue 8, ^ 1324. https://doi.org/10.3390/su9081324. S

Olsson J., Hellstrom D., Pálsson H. (2019). Framework of last mile logistics research: A systematic review of the literature. Sustain- g ability, vol. 11, no. 24, 7131. https://doi.org/10.3390/su11247131. |

Pahwa D., Starly B. (2021). Dynamic matching with deep reinforcement learning for a two-sided Manufacturing-as-a-Service | (MaaS) marketplace. Manufacturing Letters, vol. 29, pp. 11-14. https://doi.org/10.1016/j.mfglet.2021.05.005. jjj

Paiva S., Ahad M.A., Tripathi G., Feroz N., Casalino G. (2021). Enabling technologies for urban smart mobility: Recent trends, op- 5r portunities and challenges. Sensors, vol. 21, issue 6, 2143. https://doi.org/10.3390/s21062143. £

Pan S., Zhou W., Piramuthu S., Giannikas V., Chen C. (2021). Smart city for sustainable urban freight logistics. International Jour- s¿ nal of Production Research, vol. 59, issue 7, pp. 2079-2089. https://doi.org/10.1080/00207543.2021.1893970. |

Patella S.M., Grazieschi G., Gatta V., Marcucci E., Carrese S. (2021). The adoption of green vehicles in last mile logistics: A system- = atic review. Sustainability, vol. 13, issue 1, 6. https://doi.org/10.3390/su13010006.

Perboli G., Rosano M. (2019). Parcel delivery in urban areas: Opportunities and threats for the mix of traditional and green business models. Transportation Research Part C: Emerging Technologies, vol. 99, pp. 19-36. https://doi.org/10.1016/j. trc.2019.01.006.

Pereira G., Parycek P., Falco E., Kleinhans R. (2018). Smart governance in the context of smart cities: A literature review. Information Polity, vol. 23, no. 2, pp. 143-162. https://doi.org/10.3233/IP-170067.

Pérez L.M., Oltra-Badenes R., Oltra Gutiérrez J.V., Gil-Gómez H. (2020). A bibliometric diagnosis and analysis about smart cities. Sustainability, vol. 12, no. 16, 6357. https://doi.org/10.3390/su12166357.

Rafael S., Correia L.P., Lopes D., Bandeira J., Coelho M.C., Andrade M., Borrego C., Miranda A.I. (2020). Autonomous vehicles opportunities for cities air quality. Science of The Total Environment, vol. 712, 136546. https://doi.org/10.1016/j.scito-tenv.2020.136546.

Ranieri L., Digiesi S., Silvestri B., Roccotelli M. (2018). A review of last mile logistics innovations in an externalities cost reduction vision. Sustainability, vol. 10, no. 3, 782. https://doi.org/10.3390/su10030782.

Reda A.K., Gebresenbet G., Tavasszy L., Ljungberg D. (2020). Identification of the regional and economic contexts of sustainable urban logistics policies. Sustainability, vol. 12, no. 20, 8322. https://doi.org/10.3390/su12208322.

Ren R., Hu W., Dong J., Sun B., Chen Y., Chen Z. (2020). A systematic literature review of green and sustainable logistics: Bibliometric analysis, research trend and knowledge taxonomy. International Journal of Environmental Research and Public Health, vol. 17, no. 1, 261. https://doi.org/10.3390/ijerph17010261.

Rodrigues N., Vale M., Costa P. (2020). Urban experimentation and smart cities: A Foucauldian and autonomist approach. Territory, Politics, Governance, vol. 14, pp. 1-19. https://doi.org/10.1080/21622671.2020.1777896.

Rong K., Xiao F., Wang Y. (2019). Redundancy in the sharing economy. Resources, Conservation and Recycling, vol. 151, 104455. https://doi.org/10.1016/j.resconrec.2019.104455.

Ruhlandt R.W.S. (2018). The governance of smart cities: A systematic literature review. Cities, vol. 81, pp. 1-23. https://doi. org/10.1016/j.cities.2018.02.014.

Savin G. (2020c). Smart City Logistics. First conference on sustainable development: Industrial future of territories, vol. 208, article no. 04005. https://doi.org/10.1051/e3sconf/202020804005.

Savin G. (2021). Information support of the flow processes in the smart city transport and logistics system: methodology basis. International scientific forum on computer and energy Sciences, WFCES. https://doi.org/10.1051/e3sconf/202127001017.

Savin G., Bronnikov S.A. (2018). Design to the city transport and logistics system in the conditions of increase of rates of institutional and technological changes. Business Logistics in Modern Management Proceedings of the 18th international scientific conference. Pp. 485-500.

Schneider P., Folkens L., Meyer A., Fauk T. (2019). Sustainability and dimensions of a nexus approach in a sharing economy. Sustainability, vol. 11, no. 3, 909. https://doi.org/10.3390/su11030909.

Schwerdfeger S., Boysen N. (2020). Optimizing the changing locations of mobile parcel lockers in last-mile distribution. European Journal of Operational Research, vol. 285, issue 3, pp. 1077-1094. https://doi.org/10.1016/j.ejor.2020.02.033.

Sharifi A. (2020). A typology of smart city assessment tools and indicator sets. Sustainable Cities and Society, vol. 53, 101936. https://doi.org/10.10167j.scs.2019.101936.

Shavarani S.M., Mosallaeipour S., Golabi M., izbirak G. (2019). A congested capacitated multi-level fuzzy facility location problem: An efficient drone delivery system. Computers & Operations Research, vol. 108, pp. 57-68. https://doi.org/10.1016/j. cor.2019.04.001.

Simoni M.D., Marcucci E., Gatta V., Claudel C.G. (2020). Potential last-mile impacts of crowdshipping services: A simulation-based evaluation. Transportation, vol. 47, pp. 1933-1954. https://doi.org/10.1007/s11116-019-10028-4.

Szmelter-Jarosz A., Rzesny-Ciepliñska J. (2020). Priorities of urban transport system stakeholders according to crowd logistics solutions in city areas. A sustainability perspective. Sustainability, vol. 12, no. 1, 317. https://doi.org/10.3390/su12010317.

Talari S., Shafie-khah M., Siano P., Loia V., Tommasetti A., Catalao J.P.S. (2017). A review of smart cities based on the Internet of Things concept. Energies, vol. 10, no. 4, 421. https://doi.org/10.3390/en10040421.

Tompson T. (2017). Understanding the contextual development of smart city initiatives: A pragmatist methodology. She Ji: The Journal of Design, Economics, and Innovation, vol. 3, issue 3, pp. 210-228. https://doi.org/10.1016/j.sheji.2017.11.004.

® Valcárcel-Aguiar B., Murias P., Rodríguez-González D. (2019). Sustainable urban liveability: A practical proposal based on a com* posite indicator. Sustainability, vol. 11, no. 1, 86. https://doi.org/10.3390/su11010086.

s Viu-Roig M., Alvarez-Palau E.J. (2020). The impact of e-commerce-related last-mile logistics on cities: A systematic literature ^ review. Sustainability, vol. 12, no. 16, 6492. https://doi.org/10.3390/su12166492.

o Wamba S.F., Queiroz M.M. (2019). A bibliometric analysis and research agenda on smart cities. IFIP Advances in Information and =j Communication Technology, vol. 558. Springer, Cham. https://doi.org/10.1007/978-3-030-20671-0_22. ш Wang H., Quan W., Ochieng W.Y. (2020). Smart Road stud based two-lane traffic surveillance. Journal of Intelligent Transportation S Systems, vol. 24, issue 5, pp. 480-493. http://dx.doi.org/10.1080/15472450.2019.1610405.

g Yigitcanlar T., Kamruzzaman M. (2019). Smart Cities and mobility: Does the smartness of Australian cities lead to sustainable commuting patterns? Journal of Urban Technology, vol. 26, no. 2, pp. 21-46. https://doi.org/10.1080/10630732.2018.14767 94.

Zhang M., Sun M., Bi D., Liu T. (2020). Green logistics development decision-making: Factor identification and hierarchical framework construction. IEEE Access, 8, pp. 1198-1205.

Zhao L., Tang Z.-Y., Zou X. (2019). Mapping the knowledge domain of smart-city research: A bibliometric and scientometric analysis. Sustainability, vol. 11, pp. 127897-127912. DOI: 10.1109/ACCESS.2020.3008443.

Zheng C., Yuan J., Zhu L., Zhang Y., Shao Q. (2020). From digital to sustainable: A scientometric review of smart city literature between 1990 and 2019. Journal of Cleaner Production, vol. 258, 120689. https://doi.org/10.1016/j.jclepro.2020.120689.

Information about the author Информация об авторе

Gleb V. Savin

Cand. Sc. (Econ.), Associate Professor of Logistics and Commerce Dept. Ural State University of Economics (62/45 8 Marta/Narodnoy Voli St., Ekaterinburg, 620144, Russia). E-mail: glebsavin@ya.ru.

Савин Глеб Владимирович

Кандидат экономических наук, доцент кафедры логистики и коммерции. Уральский государственный экономический университет (620144, РФ, г. Екатеринбург, ул. 8 Марта/Народной Воли, 62/45). E-mail: glebsavin@ya.ru.