scholarly journals The Value Of Buildings And Structures For Permafrost Damage Prediction: The Case Of Eastern Russian Arctic

2021 ◽  
Vol 14 (4) ◽  
pp. 83-92 ◽  
Author(s):  
Svetlana V. Badina ◽  
Alexey A. Pankratov
Keyword(s):  
Spatial Information ◽  
Calculated Data ◽  
Economic Consequences ◽  
Standard Industrial Classification ◽  
Russian Arctic ◽  
Economic Activities ◽  
Damage Prediction ◽  
Fixed Assets ◽  
Visual Graphic ◽  
Accounting Reports

 The relevance of the study lay in the need to obtain reliable information on the possible economic consequences of changing geocryological conditions in the Russian Arctic, to find methods for preventing (reducing) potential damage, increasing the safety of the population and economy in the areas of the highest geocryological risks, and ensuring balanced socio-economic development in the Russian Arctic permafrost zone for the long term. The study aimed to assess the cost of fixed assets, including their most vulnerable part – buildings and structures (case study: municipalities of the Russian Arctic Asian sector). Economic sectoral structure was evaluated in accordance with the Russian Standard Industrial Classification of Economic Activities using primary statistical data – closed data from companies accounting reports. The work used statistical, cartographic, and visual-graphic methods, as well as methods for analyzing spatial information and microeconomic data. According to calculations, the Russian Arctic Asian sector concentrates the fixed assets of commercial companies with a total value of about 14.8 trillion rubles, including buildings and structures worth 10.7 trillion rubles. The obtained calculated data can be used in modeling the directions of state policy in the field of climate change adaptation and territory protection from natural hazards.

scholarly journals Моделирование деятельности микропредприятий в Российских регионах

2020 ◽  
pp. 24-37
Author(s):  
Юлия Пиньковецкая
Keyword(s):  
Production Function ◽  
Spatial Data ◽  
Methodological Approach ◽  
Research Process ◽  
Production Functions ◽  
Management Tool ◽  
Economic Activities ◽  
Fixed Assets ◽  
Administrative Units ◽  
The Relationship

Целью исследования являлась оценка двухфакторной производственной функции, характеризующей взаимосвязь обо-рота микропредприятий от величины заработной платы работников и потока инвестиций в основной капитал. Рас-смотрена производственная функция, аналогичная функции Кобба-Дугласа, без ограничений на сумму степеней при факторах. Исследование базировалось на статистических пространственных данных, использовалась информация по 82 регионам России за 2017 г. Производственная функция представляет собой эффективный инструмент управления. Полученные новые знания имеют научное и практическое значение. The goal of the research was to estimate the two-factor production function, which characterizes the relationship between the microenterprise turnover and the employees rate of wages and the flow of investments into the fixed assets. The research examined a production function similar to that of Cobb-Douglas function, without the restrictions on the sum of degrees under factors. The research was based on statistical spatial data; using the information on 82 regions of Russia for 2017. The production function is an effective management tool. The new knowledge obtained is of scientific and practical im-portance. The methodological approach and tools proposed in the article for evaluating the production functions, describing the set of the microenterprises activities in the regions, can be applied in scientific research on the entrepreneurship issues, as well as in justifying the programs of this economy sector devel-opment at the federal and regional levels. The methodology and tools that were used in the research process can be applied in similar studies in the countries with a significant number of territorial (administrative) units. Further research is related to the evaluation of production functions for a set of microenterprises that are specialized in various types of economic activities, as well as those located in municipalities of specific regions.

scholarly journals Conducting Icos as a Modern Investment Approach for Implementation of Innovations for the Ukrainian Railway Transport

2018 ◽  
Vol 7 (4.3) ◽  
pp. 597
Author(s):  
I Zaitseva ◽  
M Ieromina ◽  
Y Prudius
Keyword(s):  
Road Transport ◽  
Innovation Activity ◽  
Railway Transport ◽  
Decentralized System ◽  
Fixed Assets ◽  
Railway Industry ◽  
Accounting Reports ◽  
National Road ◽  
Transport Complex ◽  
Implementation Of Innovations

The Ukrainian railway transport is the leading branch in the national road transport complex. Until recently, the Ukrainian railways have been satisfying the transportation needs of the economy and the population. Today, the service life of the technical resource of railways is practically expired. Therefore, there is a threat that the railway transport fails to satisfy future transportation needs of the Ukrainian economy.According to the accounting reports of Ukrzaliznytsya PJSC, at the end of 2016, the deterioration level of the fixed assets in the industry was 69.4%. In the context of a constant budget shortfall, the most urgent issue for Ukrainian railways is focusing on activation of innovation activity. We believe that most of the schemes of the traditional economy in the 21st century no longer work; therefore, alternatives should be searched for, the most obvious of which now is the cryptoeconomy with its decentralized system. The development and implementation of innovations in the Ukrainian railway industry requires new approaches to the system of financing innovations in the country; in this respect, ICO is a modern and promising method of attracting investments.  

scholarly journals O4E.1 Cross-walking countries’ industry classifications using concordance files compared to fuzzy data matching, to utilise an international exposure dataset

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A39.1-A39
Author(s):  
Ganesh Selvaraj ◽  
Michael Butchard
Keyword(s):  
Big Data ◽  
New Zealand ◽  
Data Science ◽  
Health And Safety ◽  
Standard Industrial Classification ◽  
Fuzzy Data ◽  
Economic Activities ◽  
Data Matching ◽  
Industry Classification ◽  
Common Domain

BackgroundCarcinogen exposure data can potentially guide the work of health and safety (H and S) regulators. This project aims to use CAREX Canada data to estimate carcinogen exposures in New Zealand industries. This requires the creation of a cross-walk between the countries’ industry classifications.MethodsAgile and big-data-science methodologies were used to construct two versions of an industry classification cross-walk from the 2006 Australian and New Zealand Standard Industrial Classification (ANZSIC06) to the Canadian version of the 2002 North American Industrial Classification (NAICS2002), used by CAREX Canada.Firstly, concordance files from government statistics bureaus cross-walked the path: ANZSIC06 ->International Standard Industrial Classification of All Economic Activities Rev4 ->NAICS2017->NAICS2012->NAICS2007->NAICS2002. The cross-walk accounted for ‘one-to-many-to-one’, non-machine formats, and missing/erroneous values.Secondly, a fuzzy data matching pipeline was designed. Data preparation removed redundant, stop, and common domain words, and lemmatised using morphological analysis (e.g. fishing to fish). Data matching used a hybrid algorithm combining ‘JaroWinkler-distance’ and a token-sort approach (i.e. ignoring the positional occurrence of words in a sentence) to match descriptions. A trial-and-error approach was used to assign weightings and concatenate the hierarchical industry classification levels to improve match accuracy. Python language was used for implementation.For each method, random samples of 50 matches were manually classified as either poor or sufficient by two people. Disagreements were discussed and consensus reached.ResultsThe concordance cross-walk sample had 52% (95% C.I. 38%–66%) sufficient matches compared to 84% (95% C.I. 74%–94%) for the fuzzy data matching pipeline cross-walk sample.ConclusionsCross-walking countries’ industry classifications using a fuzzy data matching pipeline was more accurate than using a concordance cross-walk. The pipeline is modular enough to easily include more components. This work is part of a vision to design a semantic big-data lake, enabling integration of any data relevant to H and S.

Public-sector Intervention in Embodying the New Economy in Inner Urban Areas: The Barcelona Experience

Urban Studies ◽  
2009 ◽  
Vol 46 (5-6) ◽  
pp. 1137-1155 ◽  
Author(s):  
Antònia Casellas ◽  
Montserrat Pallares-Barbera
Keyword(s):  
Urban Areas ◽  
City Council ◽  
Turn Of The Century ◽  
Growth Strategy ◽  
Economic Consequences ◽  
Economic Activities ◽  
Public Agency ◽  
Knowledge Based ◽  
The City ◽  
Radical Transformation

This article investigates the urban and economic revitalisation of a traditional industrial working-class neighbourhood into a knowledge-based economic district. It explores why and how this new district is the result of an assertive public policy led by Barcelona's city council and implemented by a quasi-public agency. The project represents the most important urban-growth strategy in the city at the turn of the century and also exemplifies the advantages and shortcomings of many of the policy elements that have contributed to the radical transformation of Barcelona in recent decades. The article further highlights methodological challenges regarding the conceptualisation and operationalisation of new economic activities and it discusses the spatial and uncertain economic consequences of this ambitious approach by the local government.

scholarly journals Mobility-based real-time economic monitoring amid the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alessandro Spelta ◽  
Paolo Pagnottoni
Keyword(s):  
Real Time ◽  
Industrial Production ◽  
Human Mobility ◽  
Substitution Effect ◽  
Economic Consequences ◽  
Economic Losses ◽  
Real Economy ◽  
Mobility Patterns ◽  
Economic Activities ◽  
The Real

AbstractMobility restrictions have been identified as key non-pharmaceutical interventions to limit the spread of the SARS-COV-2 epidemics. However, these interventions present significant drawbacks to the social fabric and negative outcomes for the real economy. In this paper we propose a real-time monitoring framework for tracking the economic consequences of various forms of mobility reductions involving European countries. We adopt a granular representation of mobility patterns during both the first and second waves of SARS-COV-2 in Italy, Germany, France and Spain to provide an analytical characterization of the rate of losses of industrial production by means of a nowcasting methodology. Our approach exploits the information encoded in massive datasets of human mobility provided by Facebook and Google, which are published at higher frequencies than the target economic variables, in order to obtain an early estimate before the official data becomes available. Our results show, in first place, the ability of mobility-related policies to induce a contraction of mobility patterns across jurisdictions. Besides this contraction, we observe a substitution effect which increases mobility within jurisdictions. Secondly, we show how industrial production strictly follows the dynamics of population commuting patterns and of human mobility trends, which thus provide information on the day-by-day variations in countries’ economic activities. Our work, besides shedding light on how policy interventions targeted to induce a mobility contraction impact the real economy, constitutes a practical toolbox for helping governments to design appropriate and balanced policy actions aimed at containing the SARS-COV-2 spread, while mitigating the detrimental effect on the economy. Our study reveals how complex mobility patterns can have unequal consequences to economic losses across countries and call for a more tailored implementation of restrictions to balance the containment of contagion with the need to sustain economic activities.

Characterising spatial logistics employment clusters

2014 ◽  
Vol 44 (3) ◽  
pp. 221-241 ◽  
Author(s):  
Prem Chhetri ◽  
Tim Butcher ◽  
Brian Corbitt
Keyword(s):  
Spatial Autocorrelation ◽  
Service Industry ◽  
Spatial Clustering ◽  
Principal Component ◽  
Urban Setting ◽  
Standard Industrial Classification ◽  
Economic Activities ◽  
Total Employment ◽  
Content Type ◽  
Postal Services

Purpose – The purpose of this paper is twofold. First to identify economic activities and broader spatial logistics functions that characterise an urban setting, and second to delineate significant spatial logistics employment clusters to represent the underlying regional geography of the logistics landscape. Design/methodology/approach – Using the four-digit Australian and New Zealand Standard Industrial Classification, industries “explicitly” related to logistics were identified and aggregated with respect to employment. A principal component analysis was conducted to capture the functional interdependence of inter-related industries and measures of spatial autocorrelation were also applied to identify spatial logistics employment clusters. Findings – The results show that the logistics sector accounts for 3.57 per cent of total employment and that road freight, postal services, and air and space transport are major employers of logistics managers. The research shows significant spatial clustering of logistics employment in the western and southern corridors of Melbourne, associated spatially with manufacturing, service industry and retail hubs in those areas. Research limitations/implications – This research offers empirically informed insights into the composition of spatial logistics employment clusters to regions that lack a means of production that would otherwise support the economy. Inability to measure the size of the logistics sector due to overlaps with other sectors such as manufacturing is a limitation of the data used. Practical implications – The research offers policymakers and practitioners an empirically founded basis on which decisions about future infrastructure investment can be evaluated to support cluster development and achieve economies of agglomeration. Originality/value – The key value of this research is the quantification of spatial logistics employment clusters using spatial autocorrelation measures to empirically identify and spatially contextualize logistics hubs.

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