The digital economy and sharing platforms generate new types of mechanisms, ensuring credible commitments. Transparency and bilateral rating systems for both consumers and producers constrain opportunistic behavior, thus creating trust. The main hypothesis is that sharing companies and platforms act as a substitute for institutional trust. Country- level data analysis shows that there is a negative correlation between the sharing economy index and institutional trust and a positive correlation between the sharing economy index and institutional quality. The findings support the idea that as sharing companies can compensate for the lack of institutional trust and stimulate economic transactions, they are especially useful in the countries with a low level of trust.
The article discusses the role of sharing economy in hospitality and tourism sector. The paper argues that sharing economy business models are perceived as sustaining innovations at the time of their emergence. To date they demonstrate the features of disruptive innovations, exerting a growing and ambiguous influence on all key elements of tourism industry structure. The example of Greece discussed in the article shows the opportunities and threats for new business models in hospitality and tourism, as well as the need for existing market players to adapt to new conditions and to improve legal framework and mechanisms for their implementation. All these will help to mitigate possible negative effects of sharing economy development and to create conditions for realizing the benefits of sharing economy for business, government and society.
The transformation of society and the development of digital technologies have significantly affected consumer behavior: consumer identity is now spreading to digital environment, with a new segment of digital consumers being developed. As a result of digitalization, new business models are emerging, for example, commercial sharing systems, the full functioning of which is impossible without the existence of digital platforms and the Internet. Despite the popularity of the topic of commercial sharing systems in the research environment and a wide range of tools used in research, at the moment no attempts have been made to study a digital profile of commercial sharing services users based on the analysis of their social networks profiles. Social network data are one of the most extensive sources of information about consumers: the ability to analyze consumer behavior in social networks can become a significant competitive advantage for companies, as it allows them to quickly extract objective information about the users. The objective of the study is to develop digital profiles of commercial sharing systems' users based on their digital footprint data. The empirical basis of the study is the publications (posts) of commercial sharing communities' subscribers on a popular Russian social network VKontakte. The information posted by users in social networks was collected using Python (the API, Application Programming Interface are used), the sample size comprises 24,000 profiles. The collected data have been processed and analyzed using the topic modeling method, as a result of the analysis, 12 main topics are identified characterizing users' interests. Based on individual topic profiles, topic profiles of communities are formed, furthermore, differences in the digital behavior commercial sharing systems profiles were identified. The application of data on user behavior in digital environment creates new opportunities for digital companies and can become the basis for improving the performance of personalization services, timely adaptation of product offers and approaches to interaction with customers, as well as become the basis for the development of ecosystems.
The paper discusses the main approaches to the sharing economy definition, the characteristics of the sharing economy business model, as well as drivers and barriers that consumers of the sharing economy face. Empirical research includes the survey of the Airbnb customers. A series of in-depth interviews followed by quantitative survey are conducted to identify the factors that determine the consumers behavior in the sharing economy. As a result of qualitative and quantitative research, four groups of factors are revealed: economic, social, personal, and environmental. In addition, as a result of cluster analysis, five clusters of consumers are identified: economical, socially active, supporters of new sensations, initiative and home. The results are of great interest to researchers and management practitioners in order to form a deeper understanding of the expectations and behavioral patterns of the Russian customers in a shared economy.
The article traces the impact of innovation on employment and workers income during industrial revolutions. The aim of the study is to identify the business model that contributes to improving the well-being and reducing negative impact of innovative transformations on employees. To achieve this goal, we analyze: the conceptions of industrial revolutions; the "Engels pause", which arose during the First Industrial Revolution as a "surge" in inequality due to the contradiction between productivity growth and profit, on the one hand, and the stagnation of workers' real incomes, on the other; the effect of replacing manual labor with automated one; the problems of technological unemployment; the digital business model of sharing economy. The findings report conclusions concerning the change in economic development paradigm as a result of the replacement of classical consumption models by sharing economy business model, on the prospects of the sharing economy business model in the context of its ability to solve employment problems, overcome technological unemployment and increase employees' income. The achieved results can be useful for policymakers and corporate structures that design innovative development strategies.
In the context of fundamental changes in the economy and the labor market, the introduction of educational programs in the field of data analysis and machine learning at all levels of education with the priority of integrating mathematical, natural science and socio-humanitarian knowledge becomes important. An overview and analysis of foreign experience and main discussion topics in the development of educational modules for data science and machine learning for adolescents and adolescents is presented.
The "language or dialect" problem has remained topical for the Karelian language for a century and a half now. Finnic language specialists from Russia and Finland have not managed to hammer out a common opinion regarding Ludic subdialects: whether they belong to Karelian or form a language of their own. Lately, the long-standing concept of Karelian Proper and Livvi sub-dialects as belonging to the same language has also been questioned. An unresolved issue is the dialectal division of the Karelian language. Seeking to fi nd the lexical criteria for determining the linguistic status of certain Karelian varieties (idioms) in this study, we applied the lexicostatistical approach. Th e percentages of matches between idioms were calculated using Swadesh basic vocabulary (100-word) list. Data on 30 Karelian and Veps sub-dialects were selected from the "Comparative Onomasiology Dictionary of Karelian, Veps, and Sami Dialects" (2007). Based on the threshold match percentages for discrimination between languages (91–90 %), all the idioms fell into two groups: the Karelian and the Veps languages. Mikhailovskoe Village sub-dialect occupies a transitional position between them. Th e results demonstrate a relatively identical composition of the basic vocabulary of Karelian Proper, including Tver, as well as of Livvi and Ludic sub-dialects. Within the Karelian language, sub-dialects formed three large groups: 1) Karelian-Proper sub-dialects of Northern Karelia; 2) Karelian-Proper sub-dialects of Central Russia; 3) Karelian-Proper sub-dialects of Middle Karelia together with Livvi and Ludic sub-dialects. The results of the study are going to be used in working on the dialectal classification of the Karelian language, which primarily relies on linguistic criteria.
вопрос об использовании персональных данных граждан очень важен ; и решением данного вопроса должно послужить принятие законодательства ; четко регулирующее деятельность операторов персональных данных. Авторами рассмотрен один из эффективных подходов к защите персональных данных – обезличивания ; а также выявлены две абсолютно противоположные тенденции к принятию законов. Обезличивание данных не только является защитой интересов государства и ; в первую очередь ; граждан ; но и механизмом ; который позволит рекламным ; страховым и иным компаниям улучшать качество своих продуктов и услуг. ; the question of the citizens' personal data processing is very important ; and the solution for this problem should be the adoption of legislation expressly regulating the activities of personal data operators. The authors considered one of the most effective approaches to personal data protection – anonymization ; as well as identified two developments to adoption of legislation. Anonymization not only protects the interests of the state and ; first and foremost ; the citizens ; but it is also a mechanism that will allow advertising ; insurance and other companies to improve the quality of their products and services.
В статье автор проводит анализ развития цифровой дипломатии и дипломатии данных на современном этапе. Отличительной чертой является то, что автором сделано сравнение нескольких стран в этой области, подчеркнуты как плюсы, так и указаны возможные недостатки. Приведенные примеры и сделанные автором прогнозы дают возможность взглянуть на вопрос развития цифровой дипломатии под другим углом. Автором высказывается мнение о том, что цифровая дипломатия представляет собой очень мощный инструмент, через который потом будет расширено понятие «мягкая сила».
A data-sociology approach is introduced by analyzing results obtained by the Russian voluntary networking community «Dissernet». As is the case with data-journalism, data-sociology is based on the publically accessible (open source) data and takes advantage of modern information processing technologies. The results obtained in the framework of this study help to reconstruct a socio-landscape and to reveal problematic areas where any sort of fraud is highly welcomed. As a matter of fact, the same areas are highly problematic for society as a whole. Data collected by the «Dissernet» allow practical conclusions to be drawn about the work of various professional groups of people, e.g. expert committies in science and higher education (Dissertation Committies), editorial boards of scientiic journals, as well as governmental bodies at regional and federal level.
Рассматриваются основные законодательные акты о защите персональных данных стран Евросоюза, США и стран постсоветского пространства. Проводится анализ основных требований, выдвигаемых к программным и аппаратно-программным средствам защиты персональных данных. ; Розглядаються основні законодавчі акти про захист персональних даних країн Євросоюзу, США і країн пострадянського простору. Проводиться аналіз основних вимог, висунутих до програмних і апаратно-програмних засобів захисту персональних даних. ; Main legislative acts about personal data protection in European Union, USA and post-soviet countries are considered. Analysis of the main requirements to software and hardware- software of personal data protection is made.
