The positive results that are frequently associated with business process management, can only be achieved through triggering of the process by its users and the correct execution by the process operators. Unfortunately, business scandals in various domains have shown that companies, or rather the process operating subjects, sometimes do not execute their processes according to given standards or do not use existing processes at all. This failure in process execution can lead not only to suboptimal performance but also to life threatening disasters. By circumvention of official channels, individuals within the company create shadow organizations. Thus, unofficial processes and shadow IT systems emerge, which run alongside the official organization. This in turn has several disadvantages, mong others increased complexity and lack of transparency, compliance risks and higher costs. It is, therefore, of crucial importance to understand, why people accept or dismiss official business processes. Basically, this question calls for an explorative empirical research approach. A possible way of investigation is field studies in business organizations. However, such a form of study is expensive, time-consuming and it is difficult to attract a sizeable number of qualified participants. Moreover, there are known methodical problems with empirical research that relies on questioning people about their own sphere of responsibility. In this paper, we suggest to proceed in a different way to determine whether a process fits the end users. Our methodology is based on setting up process acceptance experiments in a crowdsourcing environment that allow for a more objective investigation at reduced time and cost, as compared to classical field studies. Refs 27. Figs 6. Tables 3.
The late choice of the type of alleged infringement in administrative investigations, when company (alleged infringer) presents evidence first and then responsible agency decides on the content of infringement on the basis of evidence produced by company has significant incentive effect. This rule demotivates alleged infringers to present evidence under the procedure of administrative inspection in time and as complete as possible. In addition, incentives to provide evidence are limited if the agency has the opportunity to select among different types of alleged infringement and to use evidence presented by company in its favor as evidence of a certain type of alleged infringement. Time sequencing of decisions when the choice of the type of infringement is made just after agency collects evidence from company inevitably results in decisionsof infringement, which company then appeals in the court. The experience of Russian antitrust investigations — with two indicative illustrations (Novolipetsky metallurgical plant case and the case with largest Russian retailers specialized in computers and home electronics) shows the importance for the company of being suspected in certain infringement to decide on the amount of evidence. Incentives to provide evidence are studied through the lens of all-pay auction framework to explaining the effects of procedural rules inadministrative enforcement that is inquisitorial in nature, in contrast to adversarial ones. It is shown that prosecutorial bias or asymmetric burden of proof is not necessary to suppress the incentives of the target of investigation to produce evidence.
The paper proposes a bootstrap methodology for estimating cost efficiency in data envelopment analysis. We consider the conventional concept of Fare, Grosskopf and Lovellcost efficiency, for which our algorithm re-samples “naive” input-oriented efficiency scores, rescales original inputs to bring them to the frontier, and then re-estimates cost efficiency scores for the rescaled inputs. Next, we examine Tone cost efficiency, where input prices vary across producers. Here we show that the direct modification on bootstrap algorithms by Simar and Wilson are applicable. We consider cases both with the absence and presence of environmental variables (i.e. input variables not directly controlled by firms). The bootstrap methodology exploits these assumptions: 1) the sample are i.i.d. random variables with the continuous joint probability density function with support over production set; 2) the frontier is smooth; and 3) the probability of observing firms on the frontier approaches unity with an increase in sample. The results of simulations for a multi-input, multi-output Cobb–Douglas production function with correlated outputs, and correlated technical and cost efficiency, show consistency of our proposed algorithm, even for small samples. Finally, we offer real data estimates for the Japanese banking industry in 2013. Our package “rDEA,” developed in the R language, is available from the GitHub and CRAN repository.
Economies, like Russia, blessed with resource abundance, do not usually perform well during the period of commodity price boom. The optimal policy of managing resource revenues prescribes to commit the permanent income rule to smooth the resource dividend in efficiency units and to smooth the real exchange rate. During the commodity price boom, Russia followed partially this prescribed policy, but the situation changed after the crash of oil and gas prices in 2014. Possible ways to overcome the consequences of low oil and gas prices are discussed, paying particular attention to the lack of economic complexity and the need for diversification and capabilities for growth and development of the Russian economy.
Consideration of investment activity of companies in relation to macroeconomic factors suggests that they have an optimal investment policy. In the majority of works devoted to the analysis of investment activity of companies, attention has been mainly focused on the influence of internal factors as they are manageable, and less has been paid to external factors. In the Russian reality, since it may result in a companies’ bankruptcy, over-investment occurs less frequently than under-investment. Therefore, the priority question is — what has a bigger impact on over-investment, is it macroeconomic factors, or internal factors? The goal of our study is to establish the macro-drivers having the strongest impact on the likelihood of over-investment in Russian companies. For measuring the influence of macro-drivers, a binary choice regression model is estimated on the basis of panel data. The results reveal that the biggest impact on the probability of over-investment, has the oil price volatility decreasing it by 38%, the volatility of the exchange rate takes second place (–29%) and the growth rate of the Gross Domestic Product and the inflation rate have an inconsequential influence (7% and less than –1% respectively). At the end of the paper, the analysis of the speed of adjustment to target levels of investment, shows that in the macroeconomic environment Russia experienced in 2012–2017, companies would have target levels of investment, adjustment to which would occur gradually, over a period of around 2 to 5 years depending on the industry.
This article presents the results of theoretical and empirical study in which athe authors constructed and tested a multifactor model of the Russian stock returns. This model was imroved by corerecting for autocorrelation in residuals and checking for autoregresive conditional heteroscendasity. The article counter conventional wisdom that study of the Russian financial system is necessary plagued by instability of interdependencies.
At present, the focus of discussions on digital transformation has shifted from issues of its necessity to problems of assessing a company’s readiness for digital transformation. The specificity of digital transformation in Russia requires new criteria of readiness and prioritization of existing criteria. This study explores a combination of factors (prerequisites) that determine the readiness of Russian companies for digital transformation. Our hypothesis is that it is possible to systematize and formalize these prerequisites, which can be presented as a framework for assessing readiness. The purpose of the study is to design such a framework that takes into account not only the current state of the company, but also its previous development. The paper formulates the requirements for the readiness assessment system in the form of a framework. It also proposes a method of desing a framework with these requirements. The method combines analysis of practical cases and theoretical study of modern concepts and best management practices. As a result of applying the proposed method a framework for a company’s readiness for digital transformation assessment (DTRA) is created. The DTRA framework includes criteria and characteristics of readiness grouped into domains. It is intended for a qualitative evaluation of readiness and for understanding obstacles to success of the digital transformation.
Analysis of trade cooperation between countries and identification of the most significant market participants is of great importance, both theoretically and empirically. The global trading community forms a network of international relations defined by trade contracts in various industries. Export-import trade flows are one of the key indicators of the level of cooperation among countries and the state of the global economy. The high intensity of such contacts across groups of countries suggests the existence of clusters in this market segment, consisting of central players—exporters and importers, who often define rules for other participants. Understanding the existence and identification of such a center helps to develop an optimal international trade strategy. The purpose of this contribution is to identify factors affecting trade flows among different countries. Statistical analysis of the international trade relations does not always reveal all the essential aspects of cooperation. This paper combines the methods of graph theory and econometric analysis to study the parameters of trade flows among countries. The parameters used in the network analysis make it possible to obtain additional characteristics of market participants, which help to evaluate their significance in the world trade. The paper also identifies some key mathematical and economic characteristics of export-import flows connecting destination countries. We have analyzed the directions of changes in world trade and established correspondences between metric characteristics of graph vertices and parameters of world trade models. The Russian indicators in export/import categories and its largest sales agents are estimated. The identification of the key intermediaries and importers (centers and authorities) on each of the markets in question has been carried out. As an example for this identification the market of agricultural products among the world's largest exporters and importers of the product were used.
This paper estimates the attractiveness of investing in paintings relative to the stock market. The art market is analyzed in the context of heterogeneity in order to identify main trends, including an analysis of the number of lots sold and sales prices for different countries using an extensive sample of open results of painting trades (data obtained contains about 500,000 observations). Heterogeneity of the market is shown even in a separate segment of paintings. The composition of artists in quantitative characteristics, even within isolated groups, is extremely heterogeneous. Based on the sample of re-traded paintings, the effect of the relationship between price and the moment of sale of a painting (the survival model) is analyzed. The probability of selling a painting is estimated depending on the length of the lot placement. With the help of the accelerated life model, factors influencing the speed of the sale of the picture are estimated. The analysis was carried out for different regions of sale and different nationalities of the authors of the paintings. Results obtained can be used when considering investing in art as a tool for portfolio diversification.
The modern model of the corporation involves the separation of property and control, which
often leads to the emergence of corporate conflicts, which are a serious obstacle to the effec
tive distribution of capital. The study of the relationship of dividend policy and the quality of
corporate governance is an important task. On the one hand, decisions on payout policy and
capital structure can be viewed as mechanisms for resolving agency conflicts or substitutes for
best corporate governance practices. On the other hand, the quality of corporate governance
itself is a determining factor in financial decisions. This paper attempts to explain previously
obtained contradictory empirical results using the theory of the corporate life cycle. The dir
rection of the relationship between dividend payments and quality of corporate governance at
different stages in the life cycle may vary. For the ISS index, the outcome theory better explains
the payout policy in later stages of the life cycle for mature, stable companies that have signifi
cant resources to resolve agency conflicts. The model of substitutes, in turn, explains the use
of the payout policy at the early stages of the life cycle, when the cost of building high-quality
corporate governance far exceeds potential losses from dividend payments.
The lack of liquidity in the banking sector was a key factor in the deployment of the latest financial crisis, but at the moment the authors do not know indicators to measure the liquidity risk for the banking system as a whole. In this paper, we propose an indicator that allows you to measure the adequacy of liquidity. Its construction is based on the separation of accounts, bank balance for liquid and illiquid based on a comparison of statistics intramonth flows and stocks at the end of the month. We show that for the Russian banking system this indicator will display the instability of the system, associated with a lack of liquidity, as well as a leading indicator for the banking crises of 2008 and 2014's. The question of stability of distribution of the banks on this indicator during the crisis in the Russian economy is researched. Also in the work it is shown that the change in the time horizon in the calculation of the liquidity of the proposed definition of the indicator is a measure not only of the current liquidity risk, but the risk of instant liquidity and quality of funding.
The article investigates the institutional factors that affect the motivation index wich is measured as the proportion between the share of Improvement-Driven entrepreneurs and necessity-driven entrepreneurs. The difference between entrepreneurs with necessity and opportunity motivation figures the difference in entrepreneurial behavior. Those of them who consider an income increase and anindependence desire as the motives of their activities (Improvement-Driven Entrepreneurs) are ready for large investments in business creation, for the production of new products and for the usage of new technologies, providing a greater contribution to economic development. We test few hypotheses using data of Global Entrepreneurship Monitor Survey for the period 2007–2016. The results confirm the existence of positive relationship between the level of economic development and the motivation index, an increase in the share of Improvement-Driven entrepreneurs is typical for developed countries. Despite the necessity to develop all types of entrepreneurship, which are widely discussed in policy and programs for small and medium businesses, the promotion of Improvement-Driven Entrepreneurship entrepreneurs can contribute to GDP growth by creating new, including innovative, products and technologies, as well as increasing the scale of business. We found confirmation of the hypothesis that the protection of property rights, the regulation of corruption and the quality of education have a positive effect on the motivation index. Theconfidence that income and property are protected increases the likelihood of opting for voluntary entrepreneurship. Protection of rights affects not so much the general level of entrepreneurial activity, but rather the change in its “quality”. The perception of society as corrupt also reduces the level of forced entrepreneurship, but restricting corruption more strongly stimulates highly competitive entrepreneurs than forced ones.
A dynamic stochastic general equilibrium model with multiple sectors is constructed. The production is divided into 5 sectors: mining; manufacturing; electricity, gas and water; trade, transport and communication; other. The interaction of sectors includes competition for different sources of demand and production factors. They also use production of other sectors as production factor. The model is estimated on 29 time-series of Russia statistical data with maximum likelihood method. The model produces high quality of out-of-sample forecasts (better than autoregressions). The consequences of export price decline, restriction of access to foreign finance, tighter monetary policy and higher government spending are computed.
The main result achieved in this research to be considered is the new valuation methodology having been derived in the real options' framework. The new model allows to estimate the additional effect given to the independent companies by their co-financing, the real options' approach having been applied. Thus, the new methodology is based on the newly derived formula Ito for several independent Wiener processes. In this article the valuation results achieved by the new methodology having been implemented are compared with the ones recieved by the conventional income approach. Here some basic distinctions of the model should be hilighted:
The comanies of interest are to be independent, i.e. none of them should get any economic effect from the free cash flow of that of the others.
The companies of interest are to be public corporations with their shares being characterised by a high liquidity level, in order to be able to become a good approximation for the Weiner process.
The newly developed IT solution, based on the model having been proposed, is in charge of the Higher School of Management of the St. Petersburg University and is taught under the 'Financial management' Masters' programme.