The article substantiates the essence of the concept of "social capital" as a resource in terms of formed, permanent, established types of highly effective socio-economic interactions. In addition, the main directions of its manifestation and its structural elements are defined. It is stated that for quantitative measurement of social capital at the enterprise level, it is necessary to establish its precise framework, to determine its structure and key features. As an object of accounting, social capital should be regarded as an intangible asset. The expediency of using the Value explorer method for social capital estimation, which requires some necessary steps, has been substantiated as follows: the use of clearly established algorithm of actions in the implementation of rational selection for a new product; the use of internal and external innovations in the process of generating new ideas and production of innovations within the framework of the product realization strategy; identify areas of key competitive advantages related to social capital; determining the role of the sphere of competitive advantages in production and sales of products; gross profit distribution by key competitive advantages; calculation of the potential of the competitive advantages sphere; assessment of the durability and sustainability of the competitive advantages of the enterprise and calculation of the present value of all elements of social capital of the enterprise. Five main levels of social intangibles are identified and grounded. The study allows to form an appropriate matrix to analyze the effectiveness of their use in the enterprise.

The purpose of the study is to examine the impact of corporate governance mechanisms on the financial performance of listed industrial companies in Oman. As the main research method, panel data regression analysis was used to analyze data from 36 Omani industrial companies, listed on the Muscat Stock Exchange for the period 2017–2021. Three regression models were developed using three dependent variables (Return on Assets, Return on Equity, Return on Sales), seven independent variables (Board Size, Independent and Non-executive Board Members, Board Meeting, Chief Executive Officer, Dummy variable for Board Change, Dummy variable for the Secretary on the Board, Dummy variable for Internal Auditor), and two control variables (Leverage, Size of the company). According to the research results, a negative influence of the Board Size and Dummy variable for the presence of the Secretary on the Board on the Return on Assets indicator at 10% and 5% significance level was found; moreover, there is a positive influence of Leverage and Size of the company at the 1% and 5% significance level on Return of Assets. Although, none of the independent variables used has a significant impact on the Return on Equity indicator. Return on Sales is significantly affected only by two control variables, i.e., a negative impact of Leverage at the 10% significance level and a positive impact of the Size of the company at the 10% significance level. The results obtained in the study indicate the imperfection of the corporate governance mechanisms implemented by Omani industrial companies in the field of ensuring financial efficiency.

AUTHORSDmytro Zakharov https://orcid.org/0000-0003-3423-0093 AbstractThe article explores social capital and its impact on economic development. This paper aims to analyze the role of trust in the process of growth and economic development. The interdependence of GDP per capita and trust level as an element of social capital has been analyzed. The correlation between trust and GDP per capita in 43 countries has been reflected. World Values Survey (WVS) was used to obtain empirical trust data.To determine the relationship between confidence level and GDP per capita, the correlation model was built. The regression coefficient b = 0.834 shows the average change in the effective indicator. Thus, with an increase of 1 unit of trust, GDP per capita rises by an average of 0.834. The coefficient of determination indicates that 60.68% of cases of changes in trust lead to a change in GDP per capita. The result suggests that trust serves as a tool in assisting the economic growth and company's value. The study examines the tools that help to build trust, as economic development as a whole depends on it.

The purpose of this study is to determine the influence of counterparties on the formation of an enterprise’s social capital, which is a component of measuring its value. The size of social capital is the result of the synergistic effect of all its components, namely, trust, social networks, and social norms. In this research study, the components of social capital in an enterprise are estimated to be part of the relationship with the stakeholders of the enterprise, including counterparties. Liquidity and financial stability are the criteria for choosing counterparties and for assessing cooperation prospects with them. Additionally, there are rating organizations such as Transparency International Ukraine, whose 2016 results were taken as a basis for the selection of research objects. Organizational transparency and disclosure of data indicate the intention of a company to be open to stakeholders at all levels to increase their confidence. Thus, the level of transparency of activity and the stability of the social network are interdependent. This study examines and analyzes the cooperation of enterprises with other stakeholders to determine its impact on the formation of the social capital of enterprises. The results will provide a basis for the development of a social capital assessment method.

The main approaches to the definition of the category "social capital" in the historical context are considered. Elements of social capital (social norms, social network, trust) have been defined as well as its main functions have been identified, which were formed during the evolution of this concept. The influence of the hybrid war on the formation of social capital in the context of public trust in business structures in Ukraine is determined. The role of social networks as a source of creation, accumulation and restoration of social capital has been investigated. The importance of the existence of network links that affect the socialization of society and the expansion of its communicative borders in the conditions of the development of modern socio-economic relations has been noted.

Aspects of digital transformation as a part of Industry 4.0 are analyzed. The sharing economy and sharing platform development are shown through a historical retrospective. Characteristic features of current changes in economic development related to the global industrial Internet infrastructure, big data, cloud technologies, artificial intelligence are noted. The importance of the components of social capital for the construction of a horizontal network of stable relationships is investigated. The most popular types of sharing economy are presented. The results of a survey among participants in the program «Norway-Ukraine. Professional Adaptation. Integration into the State System» are analyzed. This program takes a course on starting your own business. The purpose of the survey was to determine the importance of the components of social capital for starting your own business and the ability to build a sharing business. The results of the survey show a low level of trust, weak partnerships, and a reluctance to cooperate with government institutions. The survey showed critical points that need to be quickly fixed for socio-economic development and social capital building. Further development of the sharing economy depends on the effective use of online platforms. The article clarifies the essence and features of the sharing economy. Modern online network platforms and gives their classification are considered.

The coronacrisis accelerated the process of economic digitization. New technologies are changing approaches to the organization of labor, as a result of a process of changing classic business models. The competitive environment in all market sectors is changing. Businesses at all levels are working to integrate technology for creating a sustainable, mobile, and digital business model. Accordingly, to ensure this process, technical support in the form of data hubs, data centers, etc. is required. Strategies of digitalization of different countries are considered. It is determined that the digitization process provides these basic factors for the beginning of qualitative changes: infrastructure upgrades, expansion of databases, widespread mobile devices with a high level of communication capabilities, increasing accessibility and expanding the use of the Internet. As a result, digitalization leads to a general «connection» and the total impact of these processes on all sectors of the economy: industry, transport, finance, health, education, and others. For an objective assessment of performance and business opportunities, it is proposed to include in the management report information on development prospects, key risks, the achievement of declared goals, and strategic plans, taking into account the degree of consequences caused by the COVID-19 pandemic. Businesses should review their accounting and reporting policies to provide accurate and up-to-date information on stakeholder performance.

In contemporary digital security systems, the generation and management of cryptographic keys, such as passwords and pin codes, often rely on stochastic random processes and intricate mathematical transformations. While these keys ensure robust security, their storage and distribution necessitate sophisticated and costly mechanisms. This study explores an alternative approach that leverages biometric data for generating cryptographic keys, thereby eliminating the need for complex storage and distribution processes. The paper investigates biometric key generation technologies based on deep learning models, specifically utilizing convolutional neural networks to extract biometric features from human facial images. Subsequently, code-based cryptographic extractors are employed to process the primary extracted features. The performance of various deep learning models and the extractor is evaluated by considering Type 1 and Type 2 errors. The optimized algorithm parameters yield an error rate of less than 10%, rendering the generated keys suitable for biometric authentication. Additionally, this study demonstrates that the application of code-based cryptographic extractors provides a post-quantum level of security, further enhancing the practicality and effectiveness of biometric key generation technologies in modern information security systems. This research contributes to the ongoing efforts towards secure, efficient, and user-friendly authentication and encryption methods, harnessing the power of biometric data and deep learning techniques.