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Record W4405303321 · doi:10.25683/volbi.2019.49.444

ПЕРСПЕКТИВЫ РАЗВИТИЯ ТОРГОВЫХ ЦЕНТРОВ В РОССИЙСКОЙ ФЕДЕРАЦИИ

2019· article· ru· W4405303321 on OpenAlexaboutno aff
О.А. Косарева

Bibliographic record

VenueБизнес, образование, право · 2019
Typearticle
Languageru
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Distribution (mathematics)Christian ministryGross domestic productPopulationExternal tradeProduct (mathematics)Russian federationBusinessRetail tradeEconomicsEconomyGeographyInternational tradeRegional scienceEconomic growthCommercePolitical science

Abstract

fetched live from OpenAlex

Статья посвящена анализу основных тенденций и перспектив развития торговых центров в Российской Федерации. Рассмотрено изменение структуры валового внутреннего продукта за последние пять лет и место торговли в общем объеме ВВП, показана динамика снижения доли данной сферы экономики и выявлены факторы, влияющие на количественные и качественные изменения макроэкономических показателей. Проведен анализ оперативных данных Росстата за I квартал текущего года. Отмечены причины сокращения производительности труда в секторе розничной торговли за последние пять лет. Показано снижение доли рыночных продаж в пользу торговых организаций за последние десять лет, а также изменения, происходящие на рынках непродовольственных товаров и продовольствия. Рассмотрены основные направления развития торговли в Российской Федерации согласно проекту стратегии, разработанному Минпромторгом. Проведен анализ динамики ввода торговых центров по регионам, выявлены изменения в ранее сформированном прогнозе на текущий год, определены основные причины этих изменений. Показана тенденция снижения средней площади новых торговых центров в Москве и регионах, а также основные причины, влияющие на этот показатель. Проведен анализ распределения площадей в разрезе городов с различной численностью населения, показана тенденция снижения доли городовмиллионников и повышение доли городов с населением менее 300 тыс. чело век. Дана оценка активности ретейлеров за последние годы, рассмотрены основные тенденции в развитии ключевых сетевых игроков рынка и форматов розничных торговых предприятий, в том числе международных брендов The article is devoted to the analysis of the main trends and prospects of development of shopping centers in the Russian Fed eration. The article considers the changes in the structure of gross domestic product over the past five years, and the place of trade in the total GDP, shows the dynamics of the decline in the share of this sector of the economy and identifies factors affecting the quantitative and qualitative changes in macroeconomic indicators. The analysis of operational data of Rosstat for the first quarter of this year has provided. The reasons for reduction of labor produc tivity in the retail sector over the past five years have been noted. The article shows the decline in the share of market sales in favor of trade organizations over the past ten years, as well as changes occurring in the markets of nonfood products and food. The main directions of trade development in the Russian Federation according to the draft of Strategy developed by the Ministry of industry and trade are considered. The analysis of dynamics of input of shopping centers on regions is carried out, changes in earlier created forecast for the current year are revealed the main reasons of these changes are defined. The tendency of decrease of the average area of new shopping centers in Moscow and regions, and also the main reasons influencing this indicator is shown. The analysis of the distribution of areas in terms of cities with various population sizes is carried out. The trend of reducing the share of cities and the increase in the share of cities with population less than 300 thousand people is illustrated. The activity of retailers in recent years is assessed, the main trends in the development of key network players of the market and formats of retail trade enterprises, including international brands, are considered

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.009
Scholarly communication0.0110.007
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0300.010

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.276
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2019
Admission routes1
Has abstractyes

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