Voice Assistant as a Corporate Competitive Strategy at the Healthcare Market

DOI: 10.33917/es-1.193.2024.132-137

The article describes the competitive strategy of a pharmaceutical company in the context of digitalization of society. It describes how the patient’s voice assistant allows the company to influence levels of demand, receive information about the behavior patterns of the target audience and increases the brand’s points of contact with the target audience. The technology of developing a voice assistant for the healthcare industry is presented, and mechanisms of influence on the target audience are described.


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4. Prentice С., Loureiro S.M., Guerreiro J. Engaging with intelligent voice assistants for wellbeing and brand attachment. Journal of Brand Management, 2023, no 30, pp. 449–460. 10.1057/s41262-023-00321-0 Engaging with intelligent voice assistants for wellbeing and brand attachment.

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Digitalization of the healthcare sector in Japan based on artificial intelligence technology: key problems and solutions

DOI: 10.33917/mic-5.100.2021.87-102

The article deals with a description and analysis of the policy of modernization of the healthcare sector implemented by the Japanese government on the basis of artificial technology, provides particular examples of some research projects and cases of practical application of the described technologies, identifies problem areas of the policy being implemented and projects being developed.

Modernization of the healthcare sector and medical services based on using of the latest digital technologies, in particular, artificial intelligence technology, is one of the key current global trends. In Russia, the digital transformation of healthcare is defined as one of the key tasks and is carried out within the framework of the National Project «Healthcare».

The study of successful examples of the introduction of artificial intelligence technology, as well as problems that hinder or slow down the integration of this technology and ways to overcome them, can be a valuable lesson for countries also involved in the development of national strategies for the development of artificial intelligence.

Big data analytics in law enforcement activities

DOI: 10.33917/mic-1.90.2020.107-114

The article suggests possible approaches to creating new methods, algorithms, and software tools for analyzing structured and unstructured data, as well as a methodology for using the created tools in solving applied problems, taking into account foreign experience in developing and implementing applied intelligent information systems in special services and law enforcement agencies.

Trump’s Election Strategy: Neuromathematical Key to Deeper Layers of the American Voter Consciousness

DOI: 10.33917/es-7.165.2019.78-93

The key factor determining success of Trump’s election strategy was the use of cognitive neurophysiology methods — digital identification of a virtual doppelganger of a real voter in information and social networks. Semantization of the states of consciousness and psyche of individuals, being identified in the Global Network, on the basis of computational decisions allows to encapsulate (grab) an integral position that suits most people available for monitoring in order to set the vector of stable convergence of Trump’s election platform and the views of a particular American voter described and analyzed. Identification allows to influence the dominant focus of the emotional-imagination block for remote cognitive correction of the people’s political position in conditions of strategic bifurcation (elections). Russian developments in the field of personality neuro-management are also of great scientific and practical importance

Architecture of the National Data Management System for Creating Proactive Artificial Intelligence

DOI: 10.33917/es-7.165.2019.94-104

The article examines two approaches to formation of a national data management system (NDMS). The first approach is based on applying statistical data for predictive analytics to forecast the future. However, to ensure social progress, a proactive approach is required, aimed at creation of such a NDMS, which can be used to build the future implementing moral values. The authors substantiate that a proactive approach should be based on the principles of economic cybernetics, which allow to develop and introduce proactive artificial intelligence (AI) for improving the economic management efficiency. Its core is a Dynamic Model of Interbranch-Intersectoral Balance (MIIB), representing a system of algorithms for matching end consumers’ orders and manufacturers’ capabilities. The MIIB table, which presents all the relationships of economic agents, defines the architecture of the National Data Management System (NDMS) for the proactive AI functioning

Digital Organizations: Trends and Development Prospects in the Future

#6. For the High Norm
Digital Organizations: Trends and Development Prospects in the Future

Most of the business conferences today are organized around the theme “How we realized the importance of Big Data and became the most successful in our market”. It is safe to say that since 2015, the business has been covered by a wave of so-called hype about digital technologies, and those who create these technologies have taken dominant positions in the economy structure. If we take the Fortune-100 list for the 1960s, we’ll find that about 80% of the companies on this list have ceased to exist, and one of the reasons for this is denying inevitability of digitalization.

Human Resources Management Trends

#5. Longstanding Generation
Human Resources Management Trends

The article examines the impact of digital on human resources management, and its strategic component on the basis of the positions of leading experts in recent years. The content characteristics of a new generation of employees are given that determine the context of such topical areas of HR activities as motivation, recruiting, leadership. Conclusions are made about a meaningful change in the HR management activities, author also reveals some problems and prospects for using Big Data in HR.