Стратегические решения и риск-менеджмент, 2020, том 11, № 1

Strategic 
Decisions 
and 
Risk  
Management

Издается с 2010 года

&

решения

рискcтратегические

менеджмент

Т. 11, № 1/2020

ISSN 2618-947X (Print)
ISSN 2618-9984 (Online)
НАУЧНЫЙ 
РЕЦЕНЗИРУЕМЫЙ 
ЖУРНАЛ

16+

Стратегические решения 
и риск-менеджмент

ISSN 2618-947X (Print)
ISSN 2618-9984 (Online)
НАУЧНЫЙ 
РЕЦЕНЗИРУЕМЫЙ ЖУРНАЛ

Издается с 2010 года
DOI: 10.17747/2618-947X-2020-1
Издание перерегистрировано в Федеральной службе по надзору в сфере связи, информационных технологий  
и массовых коммуникаций (Роскомнадзор). Свидетельство ПИ № ФС-72389 от 28.02.2018 
Предыдущее название «Эффективное Антикризисное Управление» 
Периодичность издания – 4 номера в год

&
решения
рискcтратегические
менеджмент

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а также взаимосвязанными рисками 
в условиях четвертой промышленной 
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о возможных альтернативных сценариях 
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и общественном секторе, а также стратегические изменения в деятельности, 
связанные с четвертой промышленной 
революцией;
● стратегические управленческие решения: методы разработки, обоснования, 
принятия, реализации и контроля;
● инновации, предпринимательство 
и формирование новых бизнес-моделей 
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переходом к устойчивому развитию 
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● стратегии управления различными 
видами рисков, в том числе связанными 
с внедрением технологий Индустрии 4.0;
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и принятия управленческих решений 
в контексте четвертой промышленной 
революции.

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технологий Индустрии 4.0, экономики знания и инноваций, представителей органов 
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Strategic Decisions  
and Risk Management

Published since 2010
DOI: 10.17747/2618-947X-2020-1

ISSN 2618-947X (Print)
ISSN 2618-9984 (Online)
ScIeNtIfIc aNd PractIcal 
revIewed jOurNal

Decisions and management risks-management «Decisions and management risks-management» 
Journal Is registered by Federal Service for Supervision in the sphere of communication, information technologies and mass communications 
(Roscomnadzor). Certificate ПИ № ФС 77–72389 dated 28.02.2018
Periodicity – 4 times per year

&
decisions
risk
strategic
management

Online www.jsdrm.ru 

Editorial tEam
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Deputy Editor-in-Chief – Natalia Linder
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Founder – The Finance University under 
the Government of the Russian Federation 
(Finance University), Real Economy 
Publishing House

Publisher – Real Economy Publishing House
Aims and Scope – “Strategic Decisions 
and Risk Management” – an international, 
interdisciplinary peer-reviewed open access 
journal refereed open-access journal, 
publishes original scientific articles with the 
results of advanced theoretical and applied 
research in key areas of strategic management, 
management of scientific, technical and 
innovation activities, as well as interrelated 
risks in the fourth industrial revolution, 
informing readers about possible alternative 
scenarios for the future development of 
companies for timely making the right 
management decisions.

The journal pays special attention to the 
original theoretical and empirical research 
of such major problems and directions of 
development of management in the conditions 
of the fourth industrial  
revolution as:
• Strategic management in business and the 
public sector, as well as strategic changes 
in activities related to the fourth industrial 
revolution;
• Strategic management decisions: methods 
of development, justification, adoption, 
implementation and control;
• Innovation, entrepreneurship and the 
formation of new business models in 
the conditions of the fourth industrial 
revolution;
• Management of technological development 
in the context of Industry 4.0;
• Formation of sustainable competitive 
advantages and management of the 
transition to sustainable development in the 
conditions of Industry 4.0;
• Strategies for managing various types of 
risks, including risks related with adaptation 
of technology of Industry 4.0;
• Features of risk management and 
management decisions in the context of the 
fourth industrial revolution.

“Strategic Decisions and Risk Management” 
accepts articles from authors from different 
countries. The materials submitted to the 
editorial board must have high standards of 
scientific knowledge and be distinguished 
by originality. The quality of articles is 
estimated by careful, two-sided blind 
review. The editorial board and reviewers 
of the journal combines together leading 
experts at the global and national levels 
in the strategic management sphere and 
innovation development, management of 
the implementation technologies of Industry 
4.0, knowledge of innovation and economics, 
representatives of government bodies and 
development institutions.

The journal is included in the scroll of 
scientific publications, recommended by 
Higher Attestation Commission at the 
Ministry of Education and Science of the 
Russian Federation for publication of the main 
results of the degree candidate and doctor of 
sciences.
Indexation – Russian Science Citation 
Index (RSCI), Academy Google, Base, DOAJ 
(Directory of Open Access Journals), EBSCO, 
Copac|Jisk, MIAR (Information Matrix for the 
Analysis of Journals), NSD (Norwegian Centre 
for Research Data), Open Archives Initiative, 
Research Bible, “Socionet”, WorldCat, Ulrich’s 
Periodicals Directory,RePEc: Research Papers 
in Economics and others.

Быков Андрей 
Александрович
Доктор физикоматематических наук, 
профессор, заслуженный 
деятель науки РФ, вицепрезидент Российского 
научного общества анализа 
риска, Москва

Гительман 
Лазарь Давидович
Доктор экономических наук, 
профессор, заведующий 
кафедрой систем 
управления энергетикой 
и промышленными 
предприятиями Высшей 
школы экономики и 
менеджмента, Уральский 
федеральный университет 
имени первого Президента 
России Б. Н. Ельцина, 
Екатеринбург

Карлик 
Александр Евсеевич
Доктор экономических наук, 
профессор, заведующий 
кафедрой экономики и 
управления предприятиями 
и производственными 
комплексами, Санкт- 
Петербургский 
государственный 
экономический университет, 
Санкт-Петербург

Крчо Сдан
Ph.D, доцент Университета 
экономики, финансов и 
управления FEFA (Республика 
Сербия), соучредитель и 
генеральный директор 
компании DunavNET

Клейнер 
Георгий Борисович
Доктор экономических 
наук, профессор, членкорреспондент РАН, 
заместитель директора 
Центрального экономикоматематического института 
Российской академии наук, 
научный руководитель 
стратегических инициатив 
и проектов научноинтеграционного объединения 
«АБАДА», Москва

Линдер Наталия 
Вячеславовна
Кандидат экономических 
наук, профессор, заместитель 
главного редактора, 
заместитель декана по науке 
и развитию ППС факультета 
«Высшая школа управления», 
Финансовый университет при 
Правительстве Российской 
Федерации, Москва

Логинов Евгений 
Леонидович
Доктор экономических наук, 
профессор РАН, дважды 
лауреат премии Правительства 
РФ в области науки и техники, 
заместитель директора по 
научной работе, ФГБУН 
Институт проблем рынка 
Российской академии наук 
(ИПР РАН), Москва

Мартин-де-Кастро 
Григорио 
Профессор по стратегии и 
инновациям, Департамент 
менеджмента, Мадридский 
Университет Комплютенсе, 
Мадрид, Испания

Маринова Светла
Ph.D., доцент, Университет 
Ольборга, Дания

Панова 
Галина Сергеевна
Доктор экономических наук, 
профессор, заведующая 
кафедрой «Банки, денежное 
обращение и кредит», 
Московский государственный 
институт международных 
отношений (университет) 
Министерства иностранных 
дел Российской Федерации, 
Москва

Петровский 
Алексей Борисович
Доктор технических наук, 
профессор, главный научный 
сотрудник, заведующий 
отделом методов и систем 
поддержки принятия 
решений, Федеральный 
исследовательский центр 
«Информатика и управление» 
Российской академии наук, 
Москва

Прокофьев Станислав 
Евгеньевич
Доктор экономических наук, 
профессор, заведующий 
кафедрой «Государственное и 
муниципальное управление», 
Финансовый университет при 
Правительстве Российской 
Федерации, Москва

Растова Юлия 
Ивановна
Доктор экономических 
наук, профессор, 
Санкт-Петербургский 
государственный 
экономический университет, 
Санкт-Петербург

Солесвик Марина
Ph.D., профессор, бизнесшкола Университета НОРД, 
Норвегия

Томинц Полона
Ph.D., профессор, Департамент 
количественных методов 
анализа Факультета экономики 
и бизнеса, Университет 
Марибора, Словения

Умберто Паниелло
Доцент кафедры бизнес- 
аналитики и цифровых  
бизнес-моделей, 
Политехнический университет 
Бари (Италия) 

Федотова Марина  
Алексеевна
Доктор экономических наук, 
профессор, руководитель 
Департамента корпоративных 
финансов и корпоративного 
управления, Финансовый 
университет при 
Правительстве Российской 
Федерации, Москва

Цветков Валерий 
Анатольевич
Доктор экономических 
наук, профессор, членкорреспондент РАН, директор, 
Институт проблем рынка 
Российской академии наук, 
Москва

Юданов Андрей Юрьевич
Доктор экономических наук, 
профессор, Финансовый 
университет при 
Правительстве Российской 
Федерации, Москва

редакциОнная кОллегия

ПредседаТелЬ 
редакциОннОЙ 
кОллегии

Порфирьев Борис Николаевич 
Доктор экономических наук, 
профессор, академик РАН, директор 
Института народнохозяйственного 
прогнозирования, заведующий  
лабораторией анализа  
и прогнозирования природных  
и техногенных рисков экономики,  
РАН, Москва

ЗаМесТиТелЬ 
ПредседаТеля

Эскиндаров Михаил 
Абдрахманович 
Доктор экономических наук, 
профессор, ректор, Финансовый 
университет при Правительстве 
Российской Федерации,  
Москва

главнЫЙ  
редакТОр

Трачук Аркадий Владимирович 
Доктор экономических наук, 
профессор, руководитель Департамента 
менеджмента, декан факультета 
«Высшая школа управления», 
Финансовый университет 
при Правительстве Российской 
Федерации, генеральный директор  
АО «Гознак», Москва

ЧленЫ редакциОнная кОллегия

Andrey Bykov  
Doctor of Physical and Mathematical Sciences, 
Professor, Honored Scientist of Russia, VicePresident of the Russian Scientific Society for 
Risk Analysis, Moscow

Lazar Gitelman  
Doctor of Economics, Professor, Head of 
Academic Department of Economics of 
Industrial and Energy Systems, Graduate 
School of Economics and Management, 
Ural Federal University named after the 
first President of Russia Boris Yeltsin, 
Yekaterinburg

Alexander Karlik 
Doctor of Economics, Professor, Head of the 
Department of Economics and Management 
of Enterprises and Industrial Complexes,  
St. Petersburg State University of Economics, 
St. Petersburg

Georgy Kleiner 
Doctor of Economics, Professor, 
Corresponding Member of the Russian 
Academy of Sciences, Deputy Director of the 
Central Economics and Mathematics Institute 
of the Russian Academy of Sciences, Research 
Advisor of Strategic Initiatives and Projects 
of the Scientific and Integration Association 
“ABADA”, Moscow

Srđan Krčo  
Associate Professor position at FEFA (Faculty 
for Economics, Finance and Administration), 
a co-founder and CEO of DunavNET

Natalia Linder 
Ph.D. in Economics, Professor, deputy  
chief editor, associate dean in science  
and development of the higher-education 
teaching personnel of the faculty  
“Higher school of management”,  
Financial university at Government  
of the Russian Federation, Moscow city

Evgeny Loginov  
Doctor of Economics, Professor, Deputy 
Director for Science, Market Economy 
Institute, Russian Academy of Sciences, 
Moscow

Gregorio Martín-de-Castro
Ph.D. Professor of Strategy and Innovation, 
Department of Management, Universidad 
Complutense de Madrid, Madrid, Spain

Svetla Marinova 
PhD, Associate Professor, Aalborg University, 
Denmark

Galina Panova 
Doctor of Economics, Professor, Head of 
Academic Department “Banks, Money 
Circulation and Credit”, Moscow State Institute 
of International Relations (University) of the 
Ministry of Foreign Affairs of the Russian 
Federation, Moscow

Alexey Petrovsky 
Doctor of Sciences in Engineering, Professor, 
Chief Scientist, Head of the Methods and 
decision support systems Department, Federal 
Research Center “Computer science and 
management”, Russian Academy of Sciences, 
Moscow

Stanislav Prokofiev  
Doctor of Economics, Professor, Head of State 
and Municipal Administration Department, 
Financial University under the Government of 
the Russian Federation, Moscow

Julia Rastova 
Doctor of Economics, Professor, St. Petersburg 
State University of Economics, St. Petersburg

Marina Solesvik 
PhD, Professor, Business School of NORD 
University, Norway

Polona Tominc  
Ph.D., is a full-time Professor at the 
Department of Quantitative Economic 
Analysis at the Faculty of Economics and 
Business, University of Maribor, Slovenia

Valeriy Tsvetkov  
Doctor of Economics, Professor, 
Corresponding Member of RAS, Director, 
Market Economy Institute, Russian Academy 
of Sciences, Moscow

Umberto Panniello
Assistant Professor of Business Intelligence 
and E-Business Models Politecnico  
di Bari (Italy)

Marina Fedotova  
Doctor of Economics, Professor, Head 
of Corporate Finance and Governance 
Department, Financial University under 
the Government of the Russian Federation, 
Moscow

Andrey Yudanov  
Doctor of Economics, Professor, Financial 
University under the Government of the 
Russian Federation, Moscow

editOrial team

President  
OF tHe editOrial 
BOard

Boris Porfiriev  
Doctor of Economics, Professor, RAS 
Academician, Director of the Institute 
for National Economic Forecasts, Head 
of Analysis and Forecasting of Natural 
and Technogenic Risks of Economics 
Laboratory, RAS, Moscow

dePutY  
CHairman

Mikhail Eskindarov  
Doctor of Economics, Professor, 
Chancellor, Financial University under the 
Government of the Russian Federation, 
Moscow

editOr-in-CHieF

Arkady Trachuk 
Doctor of Economics, Professor,  
Head of Management department,  
dean of the faculty “Higher school  
of management”, Financial university  
at Government of the Russian Federation, 
Director general “Goznak” JSC,  
Moscow city

memBers OF tHe editOrial BOard

сОдержание

стратегические решения и риск-менеджмент  
Т. 11, № 1/2020

70

Поиск бизнес-модели образовательным стартапом 
в сегменте взрослого обучения 
на российском рынке

З.В. Чавкин

56

Влияние инноваций на экспортную деятельность: 
эмпирический анализ российских компаний

 С.И. Фаязова

48

Развитие конкурентного преимущества 
логистической платформы  
на основе цифровизации хабов

Е.Р. Счисляева, С.Е. Барыкин, Е.А. Коваленко, А.Ю. Бурова

98

Система риск-менеджмента –  
инструмент успешной реализации  
международных мегапроектов

Д.В. Шамин

14

Сертификаты возобновляемой энергии:  
возможности и эффективность применения

М.М. Балашов

28 Механизмы возврата инвестиций  
в строительство мусоросжигательных заводов  
путем продажи электроэнергии и мощности

 Е.А. Мельникова

8

децентрализация  
в цифровом обществе:  
парадокс дизайна

Е. Поунарес

COntents

strategic decisions and risk management 
Vol. 11, № 1/2020

70

Searching for business model by Edtech startups  
in adult education segment on the russian market

Z.V. Chavkin

56

innovation influence on export activities: 
еmpirical analysis of russian companies

S.I. Faiazova

48

digitalization of logistics hubs  
as a competitive advantage

E.R. Schislyaeva, S.E. Barykin, E.A. Kovalenko, A.Yu. Burova 

98

the risk management system 
is a tool for the successful  
implementation of international megaprojects

D.V. Shamin

14

renewable energy certificates:
application potential and effiency

М.М. Balashov

28

return on investment mechanisms 
of the incinerators development 
by selling electricity and power

E.А. Melnikova

8

decentralization 
in digital societies.
a design paradox

E. Pournaras

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Т. 11, № 1/2020

DOI: 10.17747/2618-947X-2020-1-8-13

Decentralization  
in digital societies. 
A design paradox

E. Pournaras1

1 School of Computing, University of Leeds

AbstrAct
D

igital societies come with a design paradox: On the one hand, technologies, such as Internet of Things, pervasive and ubiquitous 
systems, allow a distributed local intelligence in interconnected devices of our everyday life such as smart phones, smart thermostats, 
self-driving cars, etc. On the other hand, Big Data collection and storage is managed in a highly centralized fashion, resulting in privacyintrusion, surveillance actions, discriminatory and segregation social phenomena. What is the difference between a distributed and 
a decentralized system design? How “decentralized” is the processing of our data nowadays? Does centralized design undermine 
autonomy? Can the level of decentralization in the implemented technologies influence ethical and social dimensions, such as social 
justice? Can decentralization convey sustainability? Are there parallelisms between the decentralization of digital technology and the 
decentralization of urban development? 
 

KeywOrDs: 
decentralization, big data, privacy, autonomy, democracy.

FOr cItAtIOn: 
Pournaras E. (2020). Decentralization in digital societies a design paradox. Strategic Decisions and Risk Management, 11(1), 8-13. 
DOI: 10.17747/2618-947X-2020-1-8-13.

4.0

This essay is based on material presented at the 2016 Salon Festival, Maloja Palace, Switzerland:  
In Pursuit of the Beautiful Soul, The Public Sphere Salons. 
URL: https://www.publicspheresalons.com.

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Децентрализация  
в цифровом обществе:  
парадокс дизайна

 Е. Поунарес1

1 Школа  вычислений, университет Лидса, Лидс, 
Великобритания

АннотАция 
Ц

ифровая трансформация основывается на автоматизированных процессах и инвестициях в новые технологии: искусственный интеллект, блокчейн, анализ данных и интернет вещей. Но в центре успешной стратегии цифровой трансформации 
все равно находится человек. Цифровая трансформация порождает парадоксы новых моделей: с одной стороны, распространяются повсеместно технологии, такие, как интернет вещей, большие данные позволяют улучшить продукты и услуги для 
потребителей, предложить им новую ценность и т. д. Но, с другой стороны, аналитика данных и их хранение управляются 
высокоцентрализованным способом, приводящим к вторжению в частную жизнь людей, контролю за их действиями, к дискриминационным и сегрегационным социальным явлениям. В статье рассматриваются вопросы: каково различие между распределенным и децентрализованным системным проектированием? Как возможна организация «децентрализованной» обработки 
персональных  данных в наше время? Подрывают ли централизованный сбор и обработка данных автономию? Может ли 
децентрализация во внедренных технологиях влиять на этические и социальные параметры, такие, как социальная справедливость? Ведет ли децентрализация к  устойчивости функционирования систем? Есть ли взаимосвязь между децентрализацией 
цифровых технологий и децентрализацией городского развития?
В статье делается вывод о том, что децентрализаванные системы имеют гораздо большую эффективность в современных 
условиях и являются альтернативой или естественной адаптацией к сложившимся условиям. Например, децентрализованное 
производство электроэнергии делает людей одновременно производителями и потребителями, что приводит к повышению 
энергоэффективности. Точно так же аналитика данных не является монополией систем больших данных. Анализ может также 
быть выполнен полностью децентрализованным способом как общественное благо с использованием коллективного разума.

Ключевые словА: 
децентрализация, большие данные, неприкосновенность частной жизни, автономность, демократия.

Для цитировАния: 
Поунарес Е. (2020). Децентрализация в цифровом обществе: парадокс дизайна // Стратегические решения и риск-менеджмент. 
Т. 11. № 1. С. 8–13. DOI: 10.17747/2618-947X-2020-1-8-13.

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1. rHIZOMe OF tHe bIG,  
sUPPressIOn OF tHe sMALL

Are data actually “Big” in digital societies? Scratching the 
surface of Big Data is used as a philosophical narrative for an 
in-depth comprehension of the buzzword, the actual design it 
conveys and the techno-socio-economic implications of this 
design. 
Information and Communication Technologies (ICT) such as 
Internet of Things, ubiquitous and pervasive computing, wearable 
devices and other have brought paramount opportunities for 
sustainable digital societies in application domains such as Smart 
Cities, Smart Grids and ambient-assisted living. Digital societies 
provide functionality and services that reason based on empirical 
data. The vast majority of these data can be generated locally 
by each citizen who uses the aforementioned ICT technologies. 
Given that nowadays most citizens in developed and developing 
countries have access to some of these technologies, the data 
generation is highly participatory and decentralized by design. 
The data corresponding to each citizen are only a small fraction 
of the total data generated at a global scale. Therefore, the 
proportion of data corresponding to each citizen is nowadays 
magnitudes lower compared to the past when the participatory 
actions based on ICT were minimal and only large corporations 
could have access to these costly technologies. We ultimately live 
in an era of “Small Data”.
So what makes the “Small Data” “Big”? Does Big Data convey 
a misconception or a paradox? Big Data is actually a rhizome of 
massive data collection practices governed by large corporations 
or governments whose systems design is highly detached 
from the decentralized nature of data generation. This practice 
suppresses and eventually undermines the inherent decentralized 
design of digital societies. Although Big Data technologies claim 
decentralized/distributed processing of data using programming 
models such as MapReduce, these technologies are actually 
deployed and used in highly centralized settings. Data are 
collected, stored and processed in large energy-intensive data 
centers, over which citizens have no control and authority. 
Distributed data processing within this highly centralized setting 
exclusively serves corporate performance and competitiveness. 
However, given the current economic arena, only a few powerful 
business players can invest on such expensive computational 
resources. This results in a cascade of centralization and power 
concentration as a tactical utility1 mingled in technical, social, 
business, economic and political realities. The sustainability and 
cohesion of digital societies comes in question.

2. tHe OnGOInG bAttLe  
beHInD tHe new MAnIFestAtIOn

The debate on centralized vs. decentralized design dates 
back to non-digital societies and its existence has philosophical 
relevance and significance. Cummings [Cummings, 1995] relies 
on semantic decomposition to argue that the two terms are a binary 

undecidable opposition. They cannot be conceptualized apart from 
each other due to the intrinsically divided logic of writing. This 
creates inherently cyclic dynamics in the perceptions between 
centralization and decentralization. This philosophical view has 
reflections in empirical observations on fiscal, administrative, 
regulatory, market and financial centralization/decentralization 
of public services [Ahmad et al., 2005; De Vries, 2000]. It is even 
pointed out that the same arguments are used to support either 
centralization or decentralization and that opposing arguments 
appear to support the same view among different countries. These 
contradicting views also have ideological origins, for instance, 
references to decentralization swing over anarchism, libertarian 
socialism and even neo-liberalism.
Gershenson and Heylighen [Gershenson, Heylighen, 2005] 
illustrate the perspective of complexity science that moves 
beyond distinction conservation of classical sciences [Heylighen, 
1989] and introduces the indeterminacy in which observations 
or distinctions made by observers in different contexts can vary. 
Beyond the prevalent conceptual applicability of indeterminacy in 
quantum mechanics, the indeterminancy between centralization 
and decentralization becomes more apparent when studying 
topological and spectral properties of complex networks 
representing techno-socio-economic systems [Albert, Barabási, 
2002; Boccaletti et al., 2006; Provan, Kenis, 2008; Strogatz, 2001].

3. cAscADe eFFects OF DesIGn

Significant challenges that digital societies face nowadays 
stem from their design. For example, practices of privacy violation 
are a major concern in the Big Data era. Privacy can be violated 
(1) as a result of low citizens’ awereness about the implications 
of giving away their personal data or (2) by advanced inference 
techniques applied to partial/incomplete citizens’ data. In both 
cases, centralization plays a key role. These privacy violations 
are a structural effect originated from the centralized design in 
information management.
In the former case, complex privacy settings and policies 
in data collection are a mainstream that keep citizens underinformed about which of their personal data are collected and 
how they are used. Even when some privacy control is given 
back to citizens, this is counter-intuitively institutionalized 
and determined by the centralized authority that collects the 
data, the same potential violator of privacy. The notion of 
conflict of interest does not apply in this case. This centrally 
determined privacy control can ironically turn out be deceiving 
or opportunistic as choices about privacy are personal data 
collected as well. For example, the control of which friends can 
see a picture uploaded in a centralized social network reveals 
a level of trust, a ranking of human relationships camouflaged 
under a notion of privacy determination. At the end, most social 
networks may allow each individual to choose what is shared 
with everyone else except themselves. In conclusion, unless 
citizens self-institute and self-determine information sharing, 
centralized data collection cannot by design contribute to 
citizens’ awareness in privacy and can even further violate their 
privacy.

1 [Cummings, 1995] recalls former organization theorists with this view for the future digital societies.

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In the latter case of privacy intrusion via inference, it is 
again the centralized design that opens up ways to violate 
privacy. Inference is usually performed by deducing some 
missing or new type of information by using analysis of 
data sources. For example, identifying the TV channel and 
audiovisual content does not require the explicit reveal of 
this information by household residents. Surprisingly, it can 
be also inferred with high accuracy using household energy 
consumption data captured by smart meters [Greveler et al., 
2012]. Privacy threats by inference are even more challenging 
for citizens to perceive, and therefore, to be aware of. Usually, 
privacy policies do not explicitly reflect on such threats. It 
is when different collected data streams are centralized and 
processed by powerful computational resources that unlimited 
inference opportunities arise. When data remain distributed 
and under citizens’ control, inference is either literally 
or computationally infeasible. Decentralization entails a 
significant level of privacy-by-design, and can be adopted as a 
tactical utility for privacy-preservation.
Privacy intrusion has a cascade of implications on autonomy of 
decision making, individuals’ freedom and therefore, democracy 
[Helbing, Pournaras, 2015]. In a digital society of centralized 
information systems, new powerful ways of surveillance, 
discrimination, manipulation of public opinion and totalitarian 
e-governance emerge. Highly commercialized recommender 
systems or over/under-regulated computational markets often 
lack of a legitimate transparent access to citizens’ data. As a 
result, the semiotics of information in opinion formation and 
decision-making are fundamentally altered [Eco, 2014].

4. tHe OXyMOrOn  
OF sUstAInAbILIty

Centralization also has an environmental impact. For 
example, the carbom emmisions of datacenters account for 14% 
of the ICT footprint [Webb et al., 2008], 2% of all electricity 
usage in the USA and 1.3% globally [Brown et al., 2008]. There 
is an active ongoing research on energy efficiency and savings of 
centralized computing infrastructures [Beloglazov et al., 2011], 
however, the energy consumption of data centers continues to 
grow [Brown et al., 2008].
Energy efficiency in data centers cannot justify sustainability 
as the underlying environmental manifestation of the centralized 
design smolders unnoticed. If privacy could be preserved, data 
centers might not be needed at first place, or at least to the scale 
they are required nowadays. Beyond the ethical dimension, 
privacy violations such as the ones illustrated earlier have a 
measurable environmental impact as they require storage and 
processing capacity. Even if these computational resources are 
environmental-friendly, sustainability remains an oxymoron. 
Moreover, the need for a large-scale use of centralized data 
centers can be further limited if the underutilized disk space 
and processing capacity of personal computers and other 
distributed computational resources are explored [Benet, 2014; 
Swan, 2015]. Decentralizing the energy efficiency by focusing 
on environmental-friendly end-user technology can be a more 
effective and sustainable approach [Nurminen, Noyranen, 2008; 

Pantazis et al., 2013; Pournaras, 2013; Pournaras et al., 2014a; 
Wang et al., 2009].
The design bond between physical and digital finds another 
manifestation in the development of rural and urban environments. 
The centralization of information systems results in large ICT 
corporations physically close to administrative centers of cities, 
where they can sustain their business activities. This results in a 
further alienation of rural areas and losses of their competitive 
advantages. Undoubtedly and regardless of the design of 
information systems, citizens can benefit from higher quality 
of public services supported by digital means [Kostakis et al., 
2015]. However, rather than Smart Towns or Smart Villages, it 
is no wonder that Smart Cities are the mainstream nowadays. 
Although the status quo suggests the city as the incubator 
of innovation, a more physiocratic view would mandate the 
repatriation of the innovation outcome in rural areas for reflecting 
the benefits to real economy and growth [Heinonen, 2013]. Such 
considerations are highly applicable in countries of the European 
South affected by the economic crisis and especially Greece that 
has a high level of urbanization, nevertheless an economy relying 
on primary sector of the economy.

5. cLAIMInG tHe ‘seLF’

Eco [Eco, 2014] argues that true control in communication 
comes from the actual control of information meaning and its 
interpretation. This turns information from an instrument for 
producing economic merchandise into a chief merchandise. 
The tactical centralization in the Big Data era creates 
unlimited opportunities for control over meaning and its 
interpretation. The suppression of the inherent decentralized 
design of digital societies, along with the magma of 
power concentration by the centralization of information 
systems undermines the ‘self’ of self-instituting societies. 
Consequently, the foundations of democracy are undermined, 
as Castoriadis sees to the self-instituting societies the dawn 
of democracy back to ancient Greece [Castoriadis, 1983; 
Castoriadis, Curtis, 1991].
This discussion does not imply that decentralization is a 
panacea and centralized design the cause of an upcoming dystopian 
future. Decentralized systems such as peer-to-peer networks have 
been criticized for the security holes, free-riding or illegal content 
sharing [Wallach, 2003]. Several of these issues are addressed by 
new novel decentralized technologies such as blockchain [Swan, 
2015], while others are a result of the existing well-established 
economic and political interests opposing a transition towards 
decentralization. Distinguishing between a weak outcome because 
of the transition to decentralization and a weak outcome because of 
a fundamental aw in the actual decentralized design is a challenge 
to be addressed [Ahmad et al., 2005].
There is a plethora of applications in which decentralized 
information systems are an alternative or a natural fit within the 
domain applied. For example, decentralized micro-generation of 
energy empowers citizens to be both consumers and producers. 
Centralized computations for matching energy supply and demand 
in this dynamic decentralized environment can undermine 
privacy and autonomy as discussed earlier. In contrast, the 
reliability of Smart Grids can improve via self-organizing multi

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agent systems running decentralized optimization mechanisms. 
Decentralization does not only contribute to cost-effectiveness 
but also to a welfare by minimizing human discomfort and 
maximizing social fairness [Pournaras et al., 2014a; 2014b]. 
Similarly, data analytics are not a monopoly of Big Data systems. 
Measurements can also be performed in a fully decentralized 
fashion as a public good using collective intelligence distributed 
over computational resources of participatory citizens [Jesus 
et al., 2015; Pournaras et al., 2018; 2015].
Although the battle of decentralization in the Big Data era 
may resemble a digital guerrilla warfare, this battle is actually the 
claim of the missing ‘self’ from self-instituting digital societies, 
the claim of a digital democracy worth pursuing.

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