Examining the Supply Chain Integration Impact on Economy by Regression Model

Abstract— In this study, we examine the current state of supply chain integration, estimate the economic impact of inadequate integration, and identify opportunities for governmental organizations to provide critical standards infrastructures that will improve the efficiency of supply chain communications. The development of methods to reduce the impact of multicollinearity in the construction of a linear regression model is an urgent task of applied econometrics. The article proposes a method for reducing multicollinearity in the construction of a linear regression model for evaluating the supply chain impact on economy. In the case of non-stationary multidimensional time series, it is assumed that all variables have a polynomial trend. Each predictor xj(t) is decomposed into a trend and a remainder uj(t), and then a regression y(t) is constructed for time t and the remainder uj(t). In this case, the regression coefficients for uj(t) are equal to the regression coefficients for xj(t), but they are estimated using less correlated regressors SCM. The article gives a quantitative assessment of the increase in the accuracy of the forecast of the considered model in comparison with other models. In the case of spatial variables, the proposed approach is that some Xj regressors SCM correlated with others are replaced by the sum of two summands. One of them is the predicted value of Xj obtained from the regression equation Xj on the predictor correlated with it; the other is the remainder of this regression Uj. As a result, we get a new set of regressors SCM that are much less correlated with each other. The new regressors - the remnants of Uj - are susceptible to meaningful interpretation. However, the new regression equation changes the regression coefficients only for variables that act as dependent variables in auxiliary regressions. The application of the proposed method is illustrated by examples through the supply chain process. Calculations are performed in the R software environment

The Combined Method of Forecasting the Investments within the Framework of Panel Data Models

The article is devoted to the panel data modeling of the firm's investments depending on its market value and the size of fixed assets. The Grunfeld's investment data as provided in R package were used as the initial data. The data frame contains annual observations for 11 firms over 20 years. The main econometric models for panel data (pooled model, fixed effects model, random effects model) were estimated. To make choice the most effective specification of the model the character of effects was tested. The heterogeneity of firms was explained by individual random factors. The comparative analysis of parameters' estimates was performed using the basic panel data models and their optimal combination in the framework of combined assessment (forecasting). Weight coefficients of hybrid forecasts are assigned as directed by the combined model list in accordance with standard optimality requirements. It was shown that the results of the combined assessment coincided with the estimates of the random effects model

INFORMATION SYSTEM QUALITY CONTROL KNOWLEDGE

Совершенствование образовательной системы связывают с необходимостью управления качеством образовательных услуг. Контроль качества знаний является важной частью ученого процесса. Проникновение компьютеров во все области деятельности меняет подходы и технологии, которые ранее в них применялись.The development of the educational system is associated with the need to control the quality of educational services. Quality control knowledge is an important part of the scientific process. The penetration of computers into all areas of activities changing approaches and technologies that previously they were used

АНАЛІЗ КІБЕРБЕЗПЕКИ ВЕБОРІЄНТОВАНИХ ІНДУСТРІАЛЬНИХ IoT-СИСТЕМ

У сучасному світі питання кібербезпеки є одним із найважливіших, особливо в контексті динамічного розвитку веборієнтованих індустріальних систем Інтернету речей (IoT). Предметом дослідження є забезпечення кібербезпеки веборієнтованих індустріальних IoT-систем. Мета статті – аналіз наявних методів аналізу кібербезпеки, виявлення обмежень і формування вимог до нової концепції оцінювання, що передбачає шляхи усунення виявлених обмежень. Завдання, що розв’язуються: аналіз методів, засобів і технологій організації веборієнтованих індустріальних IoT-систем і питань забезпечення їх кібербезпеки. Застосовані методи: аналіз джерел, системний аналіз. Результати дослідження. Аналіз джерел показав, що проблема забезпечення кібербезпеки індустріальних IoT-систем є актуальною завдяки використанню в одній системі новітніх інформаційних технологій (ІТ) і традиційних операційних технологій (ОТ), таких як індустріальні протоколи тощо. Крім того, постійне зростання кількості та різновидів атак, спрямованих саме на індустріальні IoT-системи, є додатковими рушіями подальшого розвитку методів оцінювання та забезпечення кібербезпеки. Пропонується узагальнена концепція оцінювання та забезпечення кібербезпеки веборієнтованих індустріальних IoT-систем, яка містить етапи ідентифікації, аналізу, підвищення захищеності, виявлення та захисту. Висновки. Питання забезпечення кібербезпеки веборієнтованих індустріальних IoT-систем є надзвичайно актуальним, а наявні методи аналізу й засоби забезпечення не повністю задовольняють вимоги до таких систем. Саме тому розроблення та застосування запропонованої концепції оцінювання та забезпечення кібербезпеки дасть змогу суттєво вплинути на підвищення кібербезпеки індустріальних IoT-систем

Directions of Digital Technologies Development in the Supply Chain Management of the Russian Economy

Abstract— The main objective of this paper is to investigate the digitalization and technologies impact on supply chain management of agricultural industry.  This paper provides practical examples of supply chain digitalization, as well as its socio-economic and environmental effects. The absence of processes that are compatible with the high production requirements adopted in foreign markets can lead to crisis phenomena in domestic industries with high potential and rapid growth dynamics in agriculture industry. Agriculture in Russia is an integral part of the agro-industrial complex, and the program “Digitalization of its supply chain” should provide participants with the opportunity to use broadband, mobile, LPWAN communications, information technologies (small and big data, management platforms, etc.) of the domestic instrument industry (tags, controllers, sensors, control units) to improve significantly the efficiency of agriculture. The opportunities for modernizing the industry are huge. Food security of the country and the development of export potential, turn agriculture into a high-tech industry that can not only provide food for itself, but also many countries of the world through the global supply chain system, as well as create opportunities for the introduction of new innovative developments that have not exist before, stimulate management decisions that can provide the population with high-quality and safe products. According to expert estimates, during the season, the farmer has to make more than 40 different decisions in limited time intervals. Many of these solutions, which affect directly the production economy, are objects of digitalization in supply chain

A novel graph decomposition approach to the automatic processing of poorly formalized data : innovative ideas : a management case study

In the following paper we present a novel approach to unstructured data processing by imposing a hierarchical graph-based structure on the data and decomposing it into separate subgraphs according to optimization criteria. In the scope of the paper we also consider the problem of automatic classification of textual data for the synthesizing the hierarchical data structure. The proposed approach uses textual information on the first stage to classify ideas, innovations, and objects of intellectual property (OIPs) to construct a multilayered graph. Numerical criteria are used to decompose constructed graph into separate subgraphs. In the scope of the research we apply the developed approach to the innovative ideas in a management case study. The research has been conducted in the scope of a joint research project with financial aid of Ministry of Education and Science of Russian Federation RFMEFI57314X0007.peer-reviewe

Instrumental Variables Estimation of Systems of Simultaneous Equations: Interrelation of Methods

The article is devoted to the interrelation between methods of estimating parameters of simultaneous equations. Simultaneous equations model (SEM) is commonly used to model complex socio-economic phenomena. SEM is a set of linear simultaneous equations in which response variables are among explanatory variables in each equation of regression. This causes the problem of endogeneity and leads to biased and inconsistent estimation of parameters. There is a number of special methods to solve the problem of endogeneity of regressors: method of instrumental variables (IV), indirect least squares method (ILS), two-stage least squares method (2SLS), and three-stage least squares method (3SLS). In this article, the relationship between 2SLS and IV, ILS and 2SLS, ILS and OLS with restrictions on structural parameters, as well as the equivalence of point estimates of parameters and autocovariance matrices, is shown using empirical example

Falkland Island peatland development processes and the pervasive presence of fire

Palaeoecological analyses of Falkland Island peat profiles have largely been confined to pollen analyses. In order to improve understanding of long-term Falkland Island peat development processes, the plant macrofossil and stable isotope stratigraphy of an 11,550 year Falkland Island Cortaderia pilosa (‘whitegrass’) peat profile was investigated. The peatland developed into an acid, whitegrass peatland via a poor fen stage. Macrofossil charcoal indicate that local fires have frequently occurred throughout the development of the peatland. Raman spectroscopy analyses indicate changes in the intensity of burning which are likely to be related to changes in fuel types, abundance of fine fuels due to reduced evapotranspiration/higher rainfall (under weaker Southern Westerly Winds), peat moisture and human disturbance. Stable isotope and thermogravimetric analyses were used to identify a period of enhanced decomposition of the peat matrices dating from ∼7020 cal yr BP, which possibly reflects increasing strength of the Southern Westerly winds. The application of Raman spectroscopy and thermogravimetric analyses to the Falkland Island peat profile identified changes in fire intensity and decomposition which were not detectable using the techniques of macrofossil charcoal and plant macrofossil analyses.</p

Falkland Island peatland development processes and the pervasive presence of fire

Acknowledgments RJP secured funding for this research from the Quaternary Research Association, University of York and the Russian Science Foundation (19-14-00102). We thank Paul Brickle and other members of the South Atlantic Environmental Research Institute for their help with logistics, David Large for valuable discussions about Falkland Islands peat and all landowners for access permission. This work is dedicated to Richard J. Payne who was tragically killed while climbing Peak 6477, a previously unclimbed subsidiary peak of Nanda Devi (Garhwal Himalayas) in May 2019. CRediT authorship contribution statement Dmitri Mauquoy: Conceptualization, Investigation, Writing - original draft, Writing - review & editing. Richard J. Payne: Conceptualization, Investigation. Kirill V. Babeshko: Investigation, Writing - original draft, Writing - review & editing. Rebecca Bartlett: Investigation, Writing - original draft, Writing - review & editing. Ian Boomer: Investigation. Hannah Bowey: Investigation. Chris D. Evans: Conceptualization, Writing - original draft, Writing - review & editing. Fin Ring-Hrubesh: Investigation. David Muirhead: Methodology, Investigation, Writing - original draft, Writing - review & editing. Matthew O’Callaghan: Investigation. Natalia Piotrowska: Investigation. Graham Rush: Investigation. Thomas Sloan: Investigation. Craig Smeaton: Methodology, Investigation, Writing - original draft. Andrey N. Tsyganov: Investigation, Writing - original draft, Writing - review & editing. Yuri A. Mazei: Investigation, Writing - original draft, Writing - review & editing.Peer reviewedPostprin

Forest history, peatland development and mid- to late-Holocene environmental change in the southern taiga forest of central European Russia

Understanding the long-term ecological dynamics of boreal forests is essential for assessment of the possible responses and feedbacks of forest ecosystems to climate change. New data on past forest dynamics and peatland development were obtained from a peat sequence in the southern Valdai Hills (European Russia) based on pollen, plant macrofossil, micro-charcoal, peat humification, and testate amoeba analyses. In terms of vegetation history, the results demonstrate a dominance of broadleaved forests in the study area from 7000 4000 cal yr BP. Picea was initially a minor component of this forest but increased in cover rapidly with climatic cooling beginning at 4000 cal yr BP, becoming the dominant species. Broadleaved species persisted until 900 cal yr, with evidence for intensified felling and forest management over recent centuries. Over the last four hundred years there is evidence for widespread paludification and the establishment of Picea-Sphagnum forests. These data demonstrate how modern wet woodlands have been shaped by a combination of climatic and anthropogenic factors over several millennia. The results also demonstrate the value of a multiproxy approach in understanding long-term forest ecology