119049 Moscow, Russia
Shabolovka 26, office 4415а
+7 (495) 916-89-00 *26146
Irina Ivashkovskaya —
Head of the School, Head of Corporate Finance Research Center, Dr., tenured professor
Olga Lukashova —
Alexey Yushkin —
The textbook covers such important aspects of financial planning as methodological development of financial planning mechanisms, budgeting, forecasting the growth rate of the company and the company's value. Financial planning mechanisms in organizations should be adapted to the specific focus of the main business processes.When developing the optimal mechanism for planning financial resources and sources of their formation, developers of financial plans should be guided by the principles of scientific news and target orientation, the basic principles of financial planning in organizations. In this regard, the system knowledge gained from the study of this publication allows students to gain theoretical knowledge and practical skills in the competent preparation and implementation of financial plans and effective management of the company.
In this paper we are going to review both theoretical studies in the field of intellectual capital measurement and empirical research, devoted to analyses of intellectual capital influence on companies’ value and financial performance. As a result, potential areas for further investigations in this field were revealed.
Considering groups of intellectual capital measurement methods, we identified that direct intellectual capital methods and scorecard methods are the most appropriate for the purpose of IC components measurement. To obtain objective results of measurement it seems reasonable to develop system of proxy indicators for all intellectual capital components (human, structural and relational capitals) and subcomponents (process and innovation, client and network capitals). Basing on existing literature, we make an attempt to identify and systemize indicators, associated with intellectual capital and reveal that network capital metrics remain under-researched and deserve closer examination. It was also found that investigators should develop the system of intellectual capital indicators, taking into account industry specificity.
As for empirical studies, in order to investigate the influence of intellectual capital on corporate value and financial performance, it seems reasonable to elaborate models, which include factors, associated with all intellectual capital components and subcomponents and, what is just as important, their interrelations. Furthermore, it is vital to investigate the relationships between the values of IC components for companies. The models should be adopted for both developed and developing countries. It is also important to analyze the influence of intellectual capital in various industries separately, taking into consideration phase of economic cycle.
This article evaluates the benefits to merchants resulting from participation in the retail payments market. Using surveys to obtain a representative sample of 800 traditional (offline) Russian merchants, the article finds significant, robust evidence in favor of positive merchant's benefits. This study further separates the benefits into direct and opportunity: finding that the non-welfare improving regulatory initiatives might result from the failure to account for the opportunity benefits to merchants. This article also examines the factors affecting the level of merchants' benefits. Results show that factors affecting the value of benefits and the probability of accepting payment cards differ. Findings imply that unbalanced intervention may be detrimental to the agents' welfare, leading to a suggested mechanism for ex-ante evaluation of the effect of shocks and interventions.
The use of Big Data technology has been a modern trend in the travel industry over the last 10 years. At present, almost all travel companies that desire to stay profitable and be customeroriented use the Big Data technology. Therefore, we have several questions to answer: should we use Big Data in tourism or should we not? How to use it? What kind of risks we should consider in order to achieve effective results? These research problems were examined through a thorough analysis of Russian and world travel markets using statistical data on several sites, programs, and organizations that are associated with the tourism industry (e.g., Booking.com, Trivago). The main result of this study is to substantiate the importance of Big Data technology for the travel industry. Big Data technology helps to personally connect companies and clients of the sector so that their interaction would lead to their mutual benefits. The net result of this interaction is an increase in the economical aspect of the sector and thus the country’s growth.
The main goal of this paper is to study interconnections between credit ratings and financial indicators of industrial companies from BRICS countries. We use method of patterns, one of the modern methods of nonlinear modeling, to identify groups of heterogeneous objects with different influence on ratings. Additionally, in this research, we evaluate Tobit regression model for selected groups and establish some credit rating patterns for the BRICS industrial companies. Our results of Tobin model, may have practical implementation in short-term financial management.
Technologies may have significant effects on productivity in the agricultural sector as documented in the related literature. However, those impacts vary from country to country. These differences could partially reflect the distinct scientific landscapes, science technology and innovation (STI) policies and approaches to R&D. In order to explain the cross-country volatility of agricultural productivity, we aim to study issues of STI development in the agricultural sector in each country. Among other characteristics of STI in general and the scientific landscape, in particular, we looked at the diversification of research publication between subfields of agricultural science. We estimated the research diversification parameter and studied its relation to economic performance of an agricultural sector. Our main finding shows that R&D funding, if carefully balanced with the diversification of agricultural science, could improve research performance and eventually productivity in an agricultural sector.