Retail Sales Of Consumer Goods Research Articles

Technology Finance and Urban Development: A Quantitative Approach to Shaping a New Future for Shrinking Cities

Using a dataset of 30 cities of different administrative levels in Liaoning Province, China, for the period 2007-2020, this study proposes a novel quantitative methodology for assessing the impact of socio-economic factors on the attractiveness of shrinking cities. By combining a shrinkage model with principal component analysis and extreme value normalisation of key indicators such as population size, GDP, retail sales of consumer goods, public budget expenditure, and secondary and tertiary employment, we provide a detailed analysis of the phenomenon of shrinking cities and its drivers. Using an interdisciplinary approach involving economics, psychology and sociology, we redefine traditional indicators for assessing the attractiveness of cities by analogising urban population dynamics to the process of molecular transfer in physical chemistry. This approach allows us to quantify the attractiveness of cities in four ways: socio-economic attractiveness, cost of living, public services and employment opportunities. The case study of Fushun illustrates the application of our model, revealing the potential for negative attractiveness across all dimensions and highlighting the multifaceted challenges facing shrinking cities. Our findings highlight the critical role of balanced socio-economic development, well-developed public services, affordable living conditions and adequate employment opportunities in enhancing the attractiveness of cities. This comprehensive framework provides valuable insights for urban planners and policymakers aiming to mitigate urban shrinkage and promote sustainable urban development.

Spatiotemporal differentiation calendar for car and truck flow on expressways: A case study of Jiangsu, China

The transport objects and demands of cars and trucks differ, leading to different spatiotemporal characteristics in their flow patterns. Existing studies on expressway flow are mainly focused on the overall traffic, however, a decomposition analysis of cars and trucks is necessary to accurately explore traffic prediction, management, and dynamic toll policy. This study presents calendars and spatial distribution of car and truck flow based on toll fee data in Jiangsu Province, China. Additionally, the influencing factors are explored by using Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models. The results show that: (1) car flow follows a regular pattern of low from Monday–Thursday and high from Friday–Sunday, while high from Monday–Friday and low from Saturday–Sunday for truck flow. This law is not obvious in the total flow calendar. (2) The car flow predominantly accumulates in the 0–20 km range, while the truck flow is concentrated within the 20–40 km range. (3) The spatial distributions are stable for both car and truck flow, characterized by higher flows in the southern part of Jiangsu and lower in the northern region. Gaps in truck flow between cities are greater than those in car flow, narrowing during holidays/festivals than on weekdays or weekends. (4) private vehicle possession and travel time to Shanghai are the main influencing factors on car flow during different periods, the number of research institutions and the added value of tertiary industry are positively correlated on weekdays and weekends, respectively. Total retail sales of consumer goods is the main factor affecting truck flow during different periods, total import and export goods can be attributed to weekdays, while per capita disposable income affects weekends and festivals. Finally, the findings of this study offer insights for the optimal implementation of toll policies.

Spatio-temporal evolution and driving factors of new urbanization in central China based on multi-source data.

Urbanization is an inevitable outcome of the development of human society to a certain stage, and it is also an irreversible pattern of the concentration degree of human society. Based on multi-source data such as remote sensing images, ecological environment and socio-economic data, the evaluation index system of new urbanization is constructed from multi-dimensions of population, economy, society, space and ecology. To explore the spatio temporal evolution and driving factors of urbanization in 80 prefecture-level cities in central China from 2013 to 2021 by using entropy method, spatial autocorrelation model and geographic detector. The results show that: (1) The level of new urbanization continues to grow, with the average value rising from 0.1562 in 2013 to 0.2557 in 2021, and the regional differences are obvious, forming a circle structure with Wuhan, Zhengzhou and other provincial capitals as the center and weakening radiation to surrounding cities. (2) The agglomeration of ecological urbanization is significant, and the agglomeration trend is gradually enhanced. The high-high agglomeration areas tend to Xinzhou City, most prefecture-level cities in Hubei Province and some prefecture-level cities in Southern Hunan Province, while the low-low agglomeration areas tend to Changzhi City, most prefecture level cities in Henan Province and some prefecture-level cities in Northern Anhui Province. (3) The night light index, total retail sales of consumer goods, investment in fixed assets, proportion of built-up areas and urban economic density are the main driving factors affecting the level of new urbanization. (4) The interaction of driving factors shows double factor enhancement and nonlinear enhancement effects.

Analysis of railway accessibility in Fujian Province and the influence of economic development on its spatial differentiation.

Understanding railway accessibility supports railway regulation and development, but few studies consider different perspectives. We study the spatial distribution of accessibility indicators at the county (city) scale in Fujian Province by spatiotemporal syntax and weighted average travel time using railway timetable data. Export trade, rich commercial activities, and high-speed rail had a significant positive effect on objective accessibility. Fuzhou, Sanming, and Longyan were main transfer centers. The most accessible nodes based on weighted average travel time formed a "U"-shaped corridor along the coast. The county-wide average accessibility was 1.72h. According to spatiotemporal syntax, local general public budget expenditure (0.758993) and export volume of goods-total retail sales of consumer goods (0.956257) had the most interactive impact, while according to weighted average accessibility, import volume of goods (0.618447) and per capita gross regional product-import volume of goods (0.878573) did. These results provide reference for transportation planning and regional development in Fujian Province.

Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic

The Catering Service Industry (CSI) experienced profound impacts due to the COVID-19 pandemic. However, the long-term and multi-timepoint analysis using big data remained limited, influencing governmental decision-making. We applied Kernel Density Estimation, Shannon Diversity Index, and the Geographic detector to explore the spatial heterogeneity and determinants of the CSI in Beijing during the pandemic, with monthly granularity. The temporal-spatial dynamics of the CSI presented a "W"-shaped trend from 2018 to 2023, with pivotal shifts aligning with key pandemic stages. Spatial characteristics exhibited heterogeneity, with greater stability in the city center and more pronounced shifts in peripheral urban zones. Districts facing intricate outbreaks showed lower catering income, and Chinese eateries exhibited heightened resilience compared to others. The CSI displayed strong interconnections with living service sectors. Development in each district was influenced by economic level, population distribution, service facilities convenience, and the risk of the COVID-19 pandemic. Dominant factors included total retail sales of consumer goods, permanent population, average Baidu Heat Index, density of transportation and catering service facilities, infection cases and the consecutive days with confirmed cases existing. Consequently, we suggested seizing post-pandemic recovery as an avenue to unlock the CSI's substantial potential, ushering a fresh phase of growth.

Anta Sports International Acquisition Battle: From Nothing to Something and From Small to Big Metamorphosis

Under the impact of the three-year epidemic, China's total retail sales of consumer goods declined and consumers' propensity to consume continued to weaken, but sales in the sporting goods industry continued to grow steadily, with growth rates exceeding those of total retail sales of consumer goods. Chinese consumers are more resilient in their consumption of sporting goods, and after China's opening up, the proportion of Chinese people participating in outdoor sports has increased dramatically, creating greater demand in the market. In this context, the high-end outdoor sports brand beginning of the fire. However, in this the biggest winner is behind the Anta, a local Chinese brand acquired Finland's high-end sporting goods brand Amer Sports, and successfully turned a loss into profit. As matter of fact, such an opportunity Anta not only seized once, this paper focuses on the analysis of Anta's acquisition of FILA and Anta's acquisition of Amer Sports two classic cases, explored Anta through cross-border mergers and acquisitions to achieve the metamorphosis from scratch, from small to large, for other popular clothing brands to reshape the product grade, expand the share of the international market to provide experience and reference.

Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Prediction of municipal solid waste (MSW) generation plays an essential role in effective waste management. The main objectives of this study were to develop models for accurate prediction of MSW generation (MSWG) and analyze the influence of dominant variables on MSWG. To elevate the model's prediction accuracy, more than 50 municipal variables were considered original variables, which were selected from 12 categories. According to the screening results, the dominant variables are classified into four categories: urban greening, population size and residential density, regional economic development and resident income and expenditure. Among the seven machine learning methods, back propagation (BP) neural network has the best model evaluation effect. The R2 of the BP neural network model of Jiangsu, Zhejiang and Shandong provinces were 0.969, 0.941 and 0.971 respectively. The prediction accuracy of Shandong province (93.8%) was the best, followed by Jiangsu province (92.3%) and Zhejiang province (72.7%). The correlation between dominant variables and the MSWG was mined, suggesting that regional GDP and the total retail sales of consumer goods were the most important dominant variables affecting MSWG. Moreover, the MSWG might not absolutely associate with the population size and residential density. The method used in this study is a practical tool for policymakers on regional/local waste management and MSWG control.

Assessment of Socio-Economic Adaptability to Ageing in Resource-Based Cities and Its Obstacle Factor

The resource-based city is a type of city with pronounced ageing problems. Correctly grasping the socio-economic adaptability to ageing in resource-based cities can help actively guide the direction of urban development and build a new socio-economic order for the elderly. This paper first selects 125 resource-based cities in China from 2000 to 2020 for characteristic analysis, and finds that resource-based cities are characterized by fast growth rate and a large proportion of ageing population, deep ageing, large regional differences and uncoordinated ageing development with regional socio-economic development levels. The research objective of this article is to explore the temporal evolution characteristics, spatial patterns, agglomeration characteristics, and factors hindering the socio-economic adaptability to ageing in resource-based cities in China from 2000 to 2020. Therefore, an indicator system for assessing the socio-economic adaptability to ageing was constructed, and the improved entropy-weighted TOPSIS model was used to measure the socio-economic adaptability to ageing in 113 resource-based cities in China from 2000 to 2020. The spatio-temporal variation characteristics of the socio-economic adaptability to ageing in resource-based cities were analyzed by descriptive analysis and Moran’s index, and the main obstacle dimensions and obstacle indicators were clarified by the obstacle factor model. The findings can be summarized as follows: Temporal Analysis: Over the timeframe assessed, the socio-economic adaptability of ageing in resource cities demonstrates a consistent year-on-year improvement. The spatial clustering pattern exhibits a noteworthy trend of “significant-significant-insignificant”. Spatial Pattern: Examining the spatial arrangement from 2000 to 2020, areas with medium-low and low adaptability are prominently concentrated in Eastern China and Northeastern China, while regions with medium-high and high adaptability are focal in Northern China and Eastern China. Hebei Province and its neighboring provinces consistently display H-H clustering, contrasting with the Southwestern regions that persistently exhibit L-L clustering. Obstacle Degree Analysis: Across the 2000 to 2020 period, dimensions related to economic development, social participation, and social security consistently emerge as the primary obstacles. Notably, the top 12 average annual obstacle indicators are selected, and within economic development dimension all 4 indicators predominate as the key obstacles. Within the social participation dimension, tertiary sector value added and total retail sales of consumer goods per capita feature as primary obstacles. Regarding social security, impediments are primarily associated with the ratio of Medicare coverage, the ratio of pension coverage, alongside the development level of the social security sector. In the domain of service provision, key obstacle indicators include park area per capita, number of books in public libraries per 100 inhabitants, and public trams and buses per 10,000 inhabitants.

Spatiotemporal evolution law and driving mechanism of production–living–ecological space from 2000 to 2020 in Xinjiang, China

Xinjiang is located in the northwest of China, with a vast territory and abundant resources, which holds an important strategic position for China. However, the climate in the region is arid and the ecological environment is fragile. In recent years, with the growth of population and the improvement of economic development level, construction and agricultural land in Xinjiang have gradually expanded, and ecological land has been extensively occupied. The competition between land resources is becoming increasingly fierce, leading to some ecological and environmental problems in the region. In this context, understanding the spatiotemporal changes and driving factors of Xinjiang's production space, living space and ecological space (PLES) is of great practical significance for promoting sustainable development in the region, and can also provide reference for the research of PLES in other arid areas at home and abroad. At present, most of the research on PLES is focused on small-scale areas such as urban agglomerations, rural areas, and watersheds, or non arid areas with relatively superior natural conditions, with less research on large-scale arid areas. In this study, the transfer matrix, the center of gravity movement trajectory, Moran's I and the spatial conflict measurement model were used to illustrate the spatial–temporal evolution of PLES in Xinjiang, and the correlation coefficient was used to determine the main factors affecting the change of PLES. Results show that (1) Xinjiang is dominated by ecological space, which accounts for more than 90% of the total area of Xinjiang and has significant continuity. They are mainly distributed in Tarim, Turpan, and the northern Junggar Basin. The production space area accounts for about 5% of the total area of Xinjiang and is distributed in the vicinity of the Tianshan and Kunlun Mountains. Living space accounts for about 1% of Xinjiang's total area and is scattered around cities. (2) From 2000 to 2020, the change degree of PLES in Xinjiang in the last decade is higher than that in the first decade, most of which is the transformation from ecological space to production space. The three types of spaces influence and restrict each other in the development process. (3) Population, crop sown area, natural conditions, policy and the development level of agricultural science and technology are the main factors affecting the spatial distribution of production. Environmental factors such as altitude, soil erosion and temperature have a great influence on ecological space. Population, the output value of various industries and total retail sales of consumer goods are the main factors affecting residential space. The evolution of Xinjiang PLES is the result of multiple factors. (4) The medium spatial conflict dominates, mainly distributed in Tarim Basin and Junggar Basin. The weak and strong space conflicts are concentrated in the oases in the north of the Tianshan and Kunlun Mountains, and the number is small. From 2000 to 2020, the increasing degree of spatial conflicts in Xinjiang is due to land desertification.

Contradiction or harmony? Spatial and temporal relationships between new urbanization and rural revitalization in the Yellow River Basin from a coupling perspective.

Integrating urban and rural areas is the only way to achieve sustainable regional development. To comprehensively build an evaluation index system for new urbanization and rural revitalization (NU-RR), taking the Yellow River Basin (YRB) as research object, and the coupled coordination degree (CCD) model, relative development degree (RDD) model and gravity model are used to quantitatively measure the spatial and temporal patterns, synchronous development status and spatial linkages of the coupled coordination of NU-RR from 2005 to 2020. The factors influencing the CCD are identified with the help of the geographic detector model. The findings indicate that: (1) From 2005 to 2020, the combined indexes of NU-RR in the YRB show an increasing trend, while rural revitalization is growing slower than new urbanization. (2) The CCD of NU-RR in the YRB shows spatial structure characterized by "high in the east and low in the west" and undergoes an evolutionary process of "low coupling-medium coupling-high coupling". (3) The spatial disparities in the state of coupled and coordinated development of different cities are significant, mainly showing the spatial distribution characteristics dominated by the lagging new urbanization. (4) The spatial connection of CCD is networked and polarized, and the interprovincial barrier effect is weakened. (5) Total retail sales of consumer goods per capita and local general public budget expenditure as a share of GDP are the primary influencing elements affecting the CCD of NU-RR in the YRB. The interaction is manifested as bivariate enhance and nonlinear enhancement. The study's findings can guide decisions to promote high-quality urban-rural integration development in the YRB.

The Impact of Fiscal Policy on Households’ Expectation: Evidence from China’s Total Retail Sales of Consumer Goods

This study is based on the growing economic pressure to the downside that China experienced since COVID-19. This epidemic has weakened the country's financial capacity and lowered households’ consumption expectations. The paper explores the health spending, general government spending, VAT revenue, and total retail sales of consumer products. The core task of this study is to examine how fiscal policy affects consumption. The National Bureau of Statistics and the Ministry of Finance's data for the years 2020 to 2023 are chosen using the quantitative study methodology. According to the research results, it is concluded that increasing some special types of fiscal expenditure will play an important role in encouraging people to consume during the pandemic. Based on the aforementioned findings, it is helpful to suggest the following solutions and countermeasures. Governments should increase social security spending to ensure the basic needs of low-income groups are met, while also increasing medical spending to improve people's health and increase their willingness to consume.

Spatiotemporal Evolution and Cause Analysis of Innovation Ecosystem Niche Fitness: A Case Study of the Yellow River Basin

In this study, we explore the evolution and formation mechanism of innovation ecosystem niche fitness from three perspectives: theoretical analysis, model construction, and empirical testing. Based on the niche theory, a theoretical framework for the innovation ecosystem is constructed. Spatiotemporal analysis and qualitative comparison methods are employed to estimate the innovation niche fitness of nine provinces located in the Yellow River Basin, and their spatiotemporal characteristics and differences in terms of formation mechanism differences are then explored. The results show that: (1) temporally, from 2000 to 2017, the innovation niche fitness in the Yellow River Basin experienced minor fluctuations. However, since 2017, there has been a considerable increase. Spatially, the midstream and downstream regions, particularly in the provinces of Shandong, Henan, and Sichuan, have a higher innovation fitness. Conversely, the upstream regions of Qinghai, Ningxia, Gansu, and Inner Mongolia display a lower fitness because of the lack of advantages in innovation elements. (2) The innovation niche fitness is heavily influenced by several factors, including the number of industrial enterprises above designated size, R&D personnel, higher education institutions, scientific research institutions, expenditure for technical renovation, sales revenue of new products, total expenditure on R&D, and the total retail sales of consumer goods. (3) Four mechanisms explain high innovation niche fitness, each of which corresponds to different regions. The formation mechanisms of low innovation niche fitness can be categorized into two paths, which have an asymmetric relationship with the formation mechanisms of high innovation niche fitness. Therefore, provinces and regions should focus on these advantages to enhance the innovation niche fitness. Our research will serve as a theoretical reference to enhance the overall innovation capacity of the Yellow River Basin in the future.

New-type urbanization efficiency measurement in Shanghai under the background of industry city integration.

With the development of urbanization, the problem of the disintegrated between industry and city became more prominent, exploring the reasons. The efficiency of new-type industry has been the crucial factor in city-industry integration. This paper constructs the measurement index system of new-type urbanization via DEA-BCC methodology, starting from the quality of urbanization to analyze the efficiency of urbanization. This paper chooses the total energy consumption, general public budget expenditure, and the proportion of employment personnel in the tertiary industry in all urban units as input variables. The total retail sales of consumer goods, urbanization rate, average annual concentration of pm2.5 (popW), and built-up area as output variables. This paper uses DEA method to measure the comprehensive efficiency value, technical efficiency value, and scale efficiency value of new urbanization in Shanghai, and analyzes the influencing factors of urbanization efficiency. The results show the following: (1) The overall level of comprehensive efficiency value, technical efficiency value, and scale efficiency of Shanghai's new-type urbanization are relatively high, especially the technical efficiency basically stays at a high level. The overall trend of scale efficiency and comprehensive efficiency is consistent, and the comprehensive efficiency is greatly influenced by scale efficiency. (2) The technical efficiency of urbanization in Shanghai is close to the optimal, and there is little space for further increasing technological input to improve the comprehensive efficiency of new-type urbanization. The scale efficiency is slightly lower than the technical efficiency, and there is still some space for optimization. (3) In terms of urbanization input indicators, Shanghai's total energy consumption and general public budget input were too much in the early years, which led to the reduction of urbanization efficiency, and the situation has been improved in recent years. In terms of the output index of urbanization, increasing the total retail sales of social consumer goods and the output of built-up area can make the urbanization efficiency of Shanghai reach the optimal efficiency.

Analysis of Factors Influencing Public Budget Revenue in Nanjing Based on LASSO Regression

Based on the data of Nanjing Statistical Yearbook from 2008 to 2020, the influencing factors of public budget income in Nanjing were investigated by using LASSO method for screening and analysis. The evaluation index system of the study covers the annual per capita disposable income of urban households in Nanjing, the consumer price index of urban residents, etc., with a total of 12 explanatory variables. The study adopts a cross-validation method to adjust the values of the parameters, and uses the LASSO regression model to finally screen out three main influencing factors. According to the estimated values of regression coefficients, the annual per capita disposable income of urban households, total retail sales of consumer goods and fiscal expenditure are positively correlated with public budget revenue; based on these findings, suggestions for the future development of Nanjing are proposed.

Impacts of Urbanization on Drainage System Health and Sustainable Drainage Recommendations for Future Scenarios—A Small City Case in China

China is urbanizing at an unprecedented rate, but also accelerating the use of water resources and overloading of urban drainage systems. To analyze the impact of urbanization on the drainage-system health in Jinxi, a typical small case area in China, this study proposed an innovative methodological framework for evaluation and prediction based on statistical and modeling methods, which provides a demonstration and reference for urban development and drainage-system construction in developing countries. The result shows that the comprehensive urbanization index (CUI) of Jinxi shows an overall upward trend between 2009 and 2020. The drainage-system health index (DHI) shows a U-shaped trend of decreasing and then increasing, with the threshold in 2016. The years when the DHI and CUI are in balanced development occurred in 2014 and 2018. The impact of urbanization on the drainage-system health is divided into positive and negative aspects, depending on the drainage demands of the urban development. According to the predicted results, it is suggested that the next drainage upgrading measures will be favorable for sustainable urban development when the urbanization rate reaches 60%, the gross industrial output increases by 10%, or the total retail sales of consumer goods increase by 40%.

Spatial Patterns and Development Characteristics of China's Postgraduate Education

Using four types of publicly available datasets and ArcGIS software, the authors identify the spatial characteristics of postgraduate education in China at three scales: comprehensive economic zone, provincial, and city. They also employ geographically weighted regression and ordinary least squares to study the factors influencing the spatial pattern of postgraduate education in Gin at the city scale. The findings show that the number of postgraduate education institutions increases as the longitude of a city increases, but the number decreases from coast to inland. Second, postgraduate education institutions tend to group together in provincial capitals and megacities. Finally, GDP, per capita GDP, population size, local income, and total retail sales of consumer goods significantly impact postgraduate education development. The study contributes to the literature and provides insights for practitioners in promoting urban planning and infrastructure development.

Borderland Economic Resilience under COVID-19: Evidence from China-Russia Border Regions.

The COVID-19 pandemic has had a great impact on the global economy and trade, and border regions have been hit severely because of their high dependency on foreign trade. To understand better the economic impact of COVID-19 on border regions, we developed a COVID-19 economic resilience analytical framework and empirically examined 10 Chinese-Russian border cities in Northeast China. We quantitatively analyzed five dimensions of economic resilience, distinguished four types of shock, and examined the determinants of economic resilience. The results show that: (1) the COVID-19 pandemic has wide-ranging impacts in the border areas, with import–export trade and retail sales of consumer goods being the most vulnerable and sensitive to the shock. The whole economy of the border areas is in the downward stage of the resistance period; (2) from a multi-dimensional perspective, foreign trade and consumption are the most vulnerable components of the borderland economic system, while industrial resilience and income resilience have improved against the trend, showing that they have good crisis resistance; (3) borderland economic resilience is a spatially heterogeneous phenomenon, with each border city showing different characteristics; (4) economic openness, fiscal expenditure, and asset investment are the key drivers of economic resilience, and the interaction between the influencing factors presents a nonlinear and bi-factor enhancement of them. The findings shed light on how border economies can respond to COVID-19, and how they are useful in formulating policies to respond to the crisis.

CURRENT SITUATION AND SOLUTIONS TO VIETNAM'S ECONOMIC RECOVERY AFTER THE COVID-19 PANDEMIC

Assessing the recovery of Vietnam's economy, domestic and international experts said that Vietnam's economy is "resilient and recovering", gradually becoming a destination of interest for foreign investors. Evidence of the recovery of Vietnam's economy are economic indicators such as GDP growth rate, total retail sales of consumer goods and services, number of newly registered enterprises, production and business situation... of the first quarter of 2022 all increased compared to the first quarter of 2021. However, according to experts, Vietnam's economy has not yet maximized resource efficiency. The article mentions the recovery results of Vietnam's economy and solutions for Vietnam's economic development after the Covid-19 pandemic.

Spatial Dynamics and Determinants of Population Urbanization in the Upper Reaches of the Yellow River

The spatiotemporal evolution of population urbanization and its relationship with economic variables are important aspects of socioeconomic research and essential for revealing the mechanism of urban construction and evolution. To study the spatial heterogeneity and influencing mechanisms of population urbanization in the upper reaches of the Yellow River, this study investigated the spatial distribution and dynamic evolution of population urbanization using nuclear density analysis, exploratory spatial data analysis and the geographical detector model. The results showed that the rate of population urbanization in the upper reaches of the Yellow River increased annually since 2000 and that the nuclear density curve changed from a single–peaked mode in 2000 to a double–peaked mode in 2018. The spatial distribution of the population urbanization level was uneven, that is, high in the north and low in the south, with substantial spatial agglomeration and spatial autocorrelation. The main distribution of hot spots was in the Yinchuan area in the north, while cold spots were distributed mainly in the south. Analysis revealed that changes in population urbanization level were mainly attributable to the influence of economic and employment opportunities, such as regional GDP, GDP per capita, proportion of tertiary industry in GDP, and total retail sales of consumer goods.

Analysis And Prediction of Influencing Factors of Total Retail Sales of Consumer Goods in China——Based on Multiple Linear Regression Models and ARIMA Models

This paper takes the annual data of total retail sales of consumer goods in China from 2001 to 2020 as the research object. Using methods such as principal component estimation, ridge regression and Lasso regression, a multivariate linear regression model is established, and the regression results of the three models are compared and analyzed, and the significant factors affecting the total retail sales of consumer goods in China are the income level of residents, the level of consumption of residents, and the development of the tertiary industry, and the less significant factors are demographic factors. In addition, this paper takes the annual data of china's total retail sales of social consumer goods from 1973 to 2020 as the research object, and uses the ALAMA (0,1,1) model to predict and analyze the total retail sales of social consumer goods in China in the next ten years, and concludes that the total retail sales of social consumer goods in China will gradually rise from 2021 to 2030, which is consistent with the actual situation. Thus, it puts forward rationalization suggestions for increasing the total retail sales of consumer goods in China and promoting economic development.