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Despite all the anti-corruption measures and anti-corruption initiatives, people offer or accept bribes without any hesitation. As anywhere in the world, the negative consequences of corruption lead to a reduction in direct investment, increase inequality and poverty, distort and use public investment and reduce public revenues. The purpose of this article is to study the criminological measures to counteract corruption offences in the field of illegal gambling.

The methodological basis of the study is the provisions of the theory of knowledge: the laws of dialectical materialism, philosophical categories and scientific principles of cognition of social and legal reality.

Although many components of foreign state anti-corruption programmes are quite problematic to apply in modern realities in the Republic of Kazakhstan, according to legal scholars, through gradual implementation into the legislation of the Republic of Kazakhstan because of the systematic improvement by the state of the content of regulations and responsible implementation of anti-corruption strategies. In this regard, one of the conditions in the fight against corruption is actions aimed at using the best practices of countries that are similar to each other in terms of religion, habits, traditions, ethics and morality.

Anti-corruption initiatives using information and communication technologies, such as digital public services and e-government, crowdsourcing platforms, tools for exposing, transparency portals, blockchain and artificial intelligence technologies can provide significant assistance in combating manifestations of corruption in the field of illegal gambling on the internet in the Republic of Kazakhstan.

Based on the tenets of the conservation of resources (COR) theory, this study investigated the influence of different leadership styles on organizational performance in the context of a Eurasian country (i.e. Kazakhstan). It further examined the moderating role of corporate culture in the leadership-organizational performance relationship.

Using the quantitative survey method, the study collected data from 321 managerial employees working in local and multinational corporations in Kazakhstan. The collected data were analysed using SPSS software, and factor analysis, path analysis and hierarchical regression analysis were conducted to validate the hypotheses. Furthermore, structural equation modelling was developed to assess the moderating effects of the variables.

The findings reveal that among different leadership styles, transformational, transactional and paternal leadership have higher influences on organizational performance. Among different corporate cultures, clan culture appears to have higher moderating effects on the leadership-organizational performance relationship. The moderating role of corporate culture on the leadership influence-organizational performance relationship supports the “resource caravan” effects of the composition model theory.

Based on the premises of the COR theory, this study suggests developing multiple leadership competencies among managerial employees to be more effective in any given organizational or country context. As a result of the inclusiveness of multiple competencies, the study further suggests the consideration of an “integrated leadership approach” in the Eurasian context. Consistent with the national cultural syndrome, and as preferred by employees, managers could focus on developing a clan or group culture to strengthen their influencing power on employees.

The study adopts the COR theory by considering leadership competencies as unique resources of individual managers, which suggests the development of an “integrated leadership approach” for better management development and improved organizational performance. Furthermore, the study contributes by validating the applicability of the “conservation of resources” and the “composition model” theories in leadership studies.

The goal of the study is to examine the effects of management discussion and analysis (MD&A) sentiment in public companies' annual reports on corporate investment incentives in developing economies.

The authors use sentiment analysis of MD&A texts based on Loughran and McDonald (2011) and combination of panel data regression, logit model and random forest. The text data consists of 3,511 annual reports of Chinese listed companies for the period from 2010 to 2019.

This paper provides empirical evidence of signaling theory that sentiment of annual reports and MD&A influences corporate decisions on both M&A and internal investments. The authors found that comparing to annual reports MD&A sentiment has more stable and significant explanatory and predictive power.

This paper confirms the importance of MD&A sentiment for corporate investment decision taking and provides practical techniques for analysts and researchers to study corporate investment incentives from the point of view of signaling theory.

The study aims to expand the domains of signaling theory and corporate investment valuation by including a broader range of data on companies' M&A and internal investments in developing economies. To explore the impact of MD&A sentiment on corporate investment, a state-of-the-art set of text mining and machine learning techniques is used. The authors' results confirm that MD&A has signaling effect and can get a positive market response. Furthermore, this study enhances the empirical evidence of overconfidence theory, i.e. optimistic management whose MD&A tend to positive overestimates the management's investments decision and also underestimate the potential risk to the firm.

The purpose of our study is to study the impact of chief executive officer (CEO) optimism and narcissism on the company's capital structure.

(1) The authors opt for regression, machine learning and text analysis to explore the impact of narcissism and optimism on the capital structure. (2) We analyze CEO interviews and employ three methods to evaluate narcissism: the dictionary proposed by Anglin, which enabled us to assess the following components: authority, superiority, vanity and exhibitionism; count of first-person singular and plural pronouns and count of CEO photos displayed. Following this approach, we were able to make a more thorough assessment of corporate narcissism. (3) Latent Dirichlet allocation (LDA) technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs and to find differences between the topics of interviews and letters provided by narcissistic and non-narcissistic CEOs.

Our research demonstrates that narcissism has a slight and nonlinear impact on capital structure. However, our findings suggest that there is an impact of pessimism and uncertainty under pandemic conditions when managers predicted doom and completely changed their strategies. We applied various approaches to estimate the gender distribution of CEOs and found that the median values of optimism and narcissism do not depend on sex. Using LDA, we examined the content and key topics of CEO interviews, defined as positive and negative. There are some differences in the topics: narcissistic CEOs are more likely to speak about long-term goals, projects and problems; they often talk about their brand and business processes.

First, we examine the COVID-19 pandemic period and evaluate how CEO optimism and pessimism affect their financial decisions under specific external conditions. The pandemic forced companies to shift the way they worked: either to switch to the remote work model or to interrupt operations; to lose or, on the contrary, attract clients. In addition, during this period, corporate management can have a different outlook on their company’s financial performance and goals. The LDA technique helped to find the differences in the corporate rhetoric of narcissistic and non-narcissistic CEOs. Second, we use three methods to evaluate narcissism. Third, the research is based on a set of advanced methods: machine learning techniques (random forest to reveal a nonlinear impact of CEO optimism and narcissism on capital structure).

Explores the extent of employee surveillance in the western world and queries why the USA uses surveillance measures to a greater extent than other developed nations. Suggests that American managers choose surveillance methods which include the control of workers’ bodies in the production process. Lists the batteries of tests and monitoring to which US employees can now be subjected – including searching employee computer files, voice/e‐mail, monitoring telephone calls, drug tests, alcohol tests, criminal record checks, lie detector and handwriting tests. Notes also the companies which are opposed to worker and consumer privacy rights. Pinpoints the use of surveillance as a means to ensure that employees do not withold production. Reports that employees dislike monitoring and that it may adversely affect their performance and productivity. Argues that Americans like to address complex social problems with technological means, there are no data protection laws in the USA, and that these two factors, combined with the “employment‐at‐will” doctrine, have all contributed to make it possible (and easy) for employers to use technological surveillance of their workforce. Outlines some of the ways employers insist on the purification of workers’ bodies.

For some special manipulators such as the ones work at the space station, nuclear or some other unmanned environments, the overload, collision, vibration, temperature change or release of the internal stress would affect the structural parameters. And thus the operation precision might constantly decrease in long-term use. In these unmanned environments, the unattended manipulators should calibrate itself when they execute high precision operations or proceed self-maintenances. The purpose of this paper is to propose an automatic visual assistant on-line calibration (AVOC) method based on multi-markers.

A camera fixed on the end of the manipulator is used to measure one to three identification points, which forms an unstable multi-sensor eye-in-hand system. A Gaussian motion method which combines the linear quadratic regulator control and extended Kalman filter together is proposed to make the manipulator track the planned trajectories when its inaccurate structural parameters form uncertain motion errors. And a Monte-Carlo method is proposed to form a high precision and stable signal acquisition when the visual system has measurement errors and intermittent signal feedback. An automatic sampling process is adopted to select the optimal measurement points basing on their variances.

Data analysis and experiment results prove the efficiency and feasibility of the method proposed in this paper. With this method, the positioning accuracy is largely promoted from about 2 mm to 0.04–0.05 mm.

Experiments were carried out successfully on a manipulator in a life sciences glove box that will work at the Chinese space station. It is a low cost and efficient manipulator calibration method. The whole autonomic calibration process takes less than 10 min and requires no human intervention. In addition, this method not only can be used in the calibration of other unmanned articulated manipulator that works in deep ocean, nuclear industry or space but also be useful for the maintenance work in modern factories owing a lot of industrial robots.