The article substantiates the need for a radical review of approaches to the training of managers in high technological industries, whose professional activity context is defined by continuous crises, growing uncertainty, dynamic trends, the massive emergence of the newest technical, organizational, and IT solutions, and a profound transformation of markets. Building upon their own research, analysis of expert opinions from top managers, university professors and the best practices of the world's leading universities, the authors identify trends indicating the growing role of the fundamental knowledge possessed by managers, who are capable of raising up to the challenges of an unstable environment. Links are determined between fundamental training and the flexibility of managerial thinking. A conceptual vision is presented of the peculiarities of managerial thinking and of conditions for developing its flexibility in the educational process.

The scientific novelty of the article includes arguments substantiating the need for stepping up fundamental training in line with objective demand for changes in the content of managerial functions. Such training is based on three components: methodology of anticipatory management; scientific and technological foundations of production and technologies of the future; a vision of professional activity and changes that will be brought about by the introduction of new technologies. On the applied side, the authors have designed a concrete structure of fundamental training and a mix of training methods that promote flexibility of thinking and have proved effective as part of Masters in Management programs.

The interaction of companies in the innovation process is the basis for successful innovative development, as it allows industrial companies to reduce the time to market new products, cut production costs, increase operating profit. At the same time, an optimal choice of key partners is necessary to succeed in achieving the overall goals of innovative development. Currently, there are no studies that would answer the questions: is the interaction of companies implementing different models of innovative behavior effective? Will innovative companies earn a positive return from interaction with imitation companies? What models of interaction can be optimal between innovative companies and imitation companies?

The purpose of this study is to determine how the structure of the partnership, membership and characteristics influence the innovative performance of industrial companies. The study was conducted on a sample of 270 large Russian industrial companies. An econometric model based on the Cobb - Douglas production function was used for the analysis.

The last fifteen years are characterized by a sharp increase in the share of high-tech companies in terms of attracting investment resources in the world's leading stock markets. High-tech companies over this period significantly outpaced value stocks in terms of return on investment. On the one hand, what is happening is a natural process, since in the face of accelerating industry changes, both in traditional sectors and in sub-sectors of the new economy, there are more opportunities for the emergence of companies with disruptive innovations. High market capitalizations of such companies are a natural metric of fundamental shifts in the economy. On the other hand, the very nature of investment decision-making is changing, since an objective assessment of the intrinsic value of the business of high-tech companies is becoming vaguer, more controversial, dependent on future scenarios, and subject to interpretations. And these interpretations, according to the theory of reflexivity, are increasingly having a feedback effect on fundamentals, especially in high-tech companies.

The purpose of this article is to conceptualize a new heuristic model of the “effective interpreter”, which, in the conditions of high reflexivity and narrative contexts of the stock market, has significantly diverged across a number of key attributes from the traditional model of the “rational investor”. The author compares the two models. The process of divergence of the two models occurs under the influence of a number of behavioral heuristics and cognitive biases. At the same time, the author emphasizes that a high narrative component in the value of companies does not always and necessarily mean the predominance of irrationality. Here it is more correct to assume some correlation between the rise of narrative decision contexts and the cognitive challenges of investment decision makers.

As one of the possible directions for further research, the author notes the systematization of the main factors of cognitive biases, which seem to make switching to the “effective interpreter” model in portfolio investments in high-tech companies irreversible in the current conditions.

Leveraging on the Ibrahim Index of African Governance (IIAG) and economic growth rate data from the World Bank (WB), this study employs a robust VAR time series methodology in delineating the relationship between corruption and economic growth in Zimbabwe. Noting the worsening corruption levels coupled with a grim economic performance, this study informs policy for the new political administration keen to fight corruption. The study affirms a unidirectional causality flowing from corruption to economic growth and a negative impulse response. To increase the fortunes of the economy in the future, current action to ‘stop’ corruption is obligatory.

Publication of new releases of professional standards in different areas is always a challenge for experts since usually after such events organizations, which declare following principles formulated in those standards formally or informally, start implementing new processes. That is why it is necessary to understand the difference between the new release of a standard and a previous one. That circumstance is extremely important since risk management standards from the ISO family declare that the risk management has to become an intrinsic essential part of all business processes in an organization. In case of Russian national standards GOST R ISO 31000:2019 and GOST R ISO 31000:2010 Russian professional community didn’t perform the work mentioned above. The reason was the COVID-19 pandemic which influenced the economics in general and activity of all professional communities in particular. The aim of the article under consideration is to fill in that gap.

The article is devoted to the substantiation of the model of the formation of an industrial development ecosystem based on modern digital technologies in industry.

The article deals with the problems of technological sovereignty of the Russian economy. It is shown that the solution of this problem is possible only on the basis of an industrial development ecosystem – a system of production chains of the most important types of industrial products, a technological development platform, interaction of subjects of industrial production with consumers of its products in the domestic and foreign markets. The necessity of concentration of industrial potential, resources of technological development, qualified personnel potential and direction to create conditions for providing the Russian economy with products corresponding to the world technological level is shown. The article analyzes the main existing and promising models of the functioning of an industrial enterprise. A detailed description of the barriers and difficulties on the way of digitalization of industrial enterprises in the Russian Federation is given.

In order to form the ecosystem of industrial development of the Russian Federation, the directions of identifying and assessing the state of production and technological personnel potential, its compliance with the needs of the domestic market are formulated. Recommendations are given on the creation of an ecosystem structure, mechanisms for the interaction of its various elements, a management and coordination system based on digital technologies for creating a system of individual elements that form information and analytical centers in various functional areas of the ecosystem.

A model of the ecosystem of industrial and technological development of the Russian economy based on digital technologies is proposed.

A set of mechanisms that contribute to reducing the level of uncertainty is proposed, and a design method of interaction within the framework of the digital industrial enterprise technology platform model is described.

The article formulates recommendations for the digitalization of an industrial enterprise in the new technological conditions of economic and social development, in the so-called new technological paradigm “Industry 4.0”, the characteristic features of which are minimal use of manual and mechanized labor, as well as a low level of transaction costs.

A new approach is proposed, on the basis of which industrial enterprises will interact on the basis of shared access to information and digital resources and the ability to combine the development of innovative projects and value chains necessary to create competitive products in order to increase the operational efficiency of enterprises.

Currently, retail is one of the fastest growing segments of the Russian economy with a noticeable real practical implementation and application of digital solutions. The introduction of digital products covering the trading process confidently brings the industry closer to the leading pool of digitalization industries (banks, ICT, insurance, media, industry, etc.), becoming the main tool in attracting consumers and increasing profits.

The article describes the results of an experiment on the introduction of automation for the management of assortment matrices of goods. The positive effect and profit for retail companies are shown. In conclusion, recommendations are offered on the formation of a methodology for various participants in the assortment management process.