This paper is based on the national strategy of Beijing-Tianjin-Hebei integration. At first, we make strategy analysis on the development of cold chain logistics of fresh agricultural products, using the PEST analysis model to analyze the macro environment and SWOT analysis model to distinguish strengths, weaknesses, opportunities and threats it faced now meticulously, then we discuss the development strategy combination under the integration of the Bei-jing-Tianjin-Hebei region. Secondly, we analyze the cold chain logistics demand of fresh agricultural products in view of the integration of the Bei-jing-Tianjin-Hebei region under the fresh agricultural products categories. The exponential smoothing is used to forecast first, then the secondary exponential smoothing model is set up to make the fitting figure with the actual and predicted value. In addition, we forecast the output in the next few years and analyze the results. Finally, combining with the development strategy combination and prediction analysis, we put forward the development pattern and give a prospect of fresh agricultural products cold chain logistics.

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Forecast and Opportunity Analysis of Cold Chain Logistics Demand of Fresh Agricultural Products under the Integration of Beijing, Tianjin and Hebei

Li, X. and Li, G., 2020. Research on the driving force of the regional economy to the development of ocean port shipping based on multiple regression analysis. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 168–171. Coconut Creek (Florida), ISSN 0749-0208.Most of China's coastal ports are actively stepping forward from service centers with value-added effect to trade and logistics centers with more complete functions. The region with the most abundant water transportation is also the region with the rapid economic development. However, there is a certain contradiction between the economic growth along the ocean coast and the freight volume growth. This paper analyzes the evolution law of economic aggregate and cargo throughput, analyzes the relationship between the economy and shipping, and constructs a model of cargo output and demand by means of multiple regression analysis, in order to complete a simulation study on the distribution of freight volume to water volume and construct a model of shipping demand driven by the economy.

Research on the Driving Force of the Regional Economy to the Development of Ocean Port Shipping Based on Multiple Regression Analysis

The macro-social logistics demand forecast is of great strategic significance to optimize the national or regional economic structure, improve the investment environment and improve the overall competitiveness of regional economy. In this study, the total amount of social logistics in Sichuan province was selected to reflect the social logistics demand, the factors influencing the social logistics demand in Sichuan province were analyzed, and eight economic indicators were summarized. This study first USES the time series prediction model (including the time response model GM (1, 1)), an exponential smoothing model, causal relation model (including multidimensional prediction model GM (1, n) and BP neural network model), to build four methods combination model, weight given solution of linear programming each forecast model, the forecasting result of combination forecast model deviation is minimal. The posterior difference test was applied to the above five models to compare the prediction results of each prediction method.

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Research on the Demand Forecasting Method of Sichuan Social Logistics Based on Positive Weight Combination

Yang, D, 2020 Logistics demand forecast model for port import and export in coastal area In: Yang, Y; Mi, C; Zhao, L, and Lam, S (eds), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering Journal of Coastal Research, Special Issue No 103, pp 678–681 Coconut Creek (Florida), ISSN 0749-0208Port logistics has become one of the main logistics modes In order to ensure the stability of its development, logistics demand forecasting model is often used to predict port logistics, but the forecasting error is large Therefore, the coastal port import and export logistics demand forecasting model is designed This paper analyzes the influencing factors of port import and export logistics demand, obtains the forecast index of port import and export logistics demand, and realizes port import and export logistics demand forecast by using BP neural network So far, the coastal port import and export logistics demand forecasting model has been constructed The experimental results show that the error between the prediction results of this model and the actual results is smaller, and the error between the prediction results of the original model and the actual results is larger Thus, the coastal port import and export logistics demand forecasting model is more accurate, the use of better results

Logistics Demand Forecast Model for Port Import and Export in Coastal Area

To raise the forecast precision of railway freight ton-kilometers, the unbiased GM (1, 1) power model was applied to predict the development trend. The Markov chain method was used to process the random fluctuations and correct the forecast values. Thus the optimized UBGPM-Markov model was established. The example analysis shows that the unbiased GM (1, 1) power model is superior to the GM (1, 1) model in both scope of application and prediction accuracy. Furthermore, the UBGPM-Markov model has reduced the mean absolute prediction error (MAPE) from 1.72% to 0.70%.

Forecast of Railway Freight Ton-Kilometers Based on the UBGPM-Markov Model

Logistics and economic development complement each other. The comprehensive competitiveness of Guangdong provincial economy ranks first in China. Under the influence of COVID-19, the freight development of Guangdong Province has been affected, but there is still lack of quantitative research. It is significant to explore the trend of economic development through the freight development of Guangdong Province. Based on the grey theory model, this paper uses six freight indexes to research freight development of Guangdong Province. Under the assumption that COVID-19 did not happen, we predicted the development value of freight index of Guangdong Province from January to December in 2020 and studied the influence based on the comparison between the predicted value and actual value. The empirical study shows three impact characteristics: stage characteristics, structural characteristics, and entity transmission characteristics. COVID-19 has a negative impact on the development of total freight volume, highway freight volume, waterway freight volume, and air freight volume in Guangdong Province. The influence values were −23.001%, −29.344%, −11.296%, and −3.838%. But, the freight volumes of railway and pipeline were positively affected by 14.343% and 13.057%, respectively, due to their continuity and substitution to other transportation modes. To further explore the abate measures of COVID-19 impact on Guangdong's freight development, the grey correlation model is introduced to study the correlation factors of freight development of Guangdong Province. Through the research of the related factors, this paper puts forward some measures to promote the freight development of Guangdong Province in the postepidemic era. [ABSTRACT FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Research on Freight Development of Guangdong Province Based on Grey Theory Model

PurposeThis paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.Design/methodology/approachThis paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.FindingsThere are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.Research limitations/implicationsBecause the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.Practical implicationsBy studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.Social implicationsThis paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.Originality/valueFirstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

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Research on the network connection mode of logistics economy in Guangdong province based on social network analysis

This study introduces the self-construction methods of consumers and the tendency characteristics of experiential purchase to study the effects of physical purchase and experiential purchase on wellbeing. The dependent self-builders obtain higher happiness from experiential purchase; however, the independent self-builders get higher happiness from physical purchase. Furthermore, consumers with a high purchase experience get higher happiness from experiential purchase. Consumers with high material consumption tendency get significantly higher happiness than physical purchase from experiential purchase. Consumers with high materialism tendency gain higher happiness in experiential purchase, which is in line with the expectations of self-construction and consumption theories. This study provides the first evidence for the impact of self-construction methods on wellbeing with different consumption choices.

Lianhua Liu

Papers

Research on Freight Development of Guangdong Province Based on Grey Theory Model

Research on the network connection mode of logistics economy in Guangdong province based on social network analysis

Who Can Get More Happiness? Effects of Different Self-Construction and Experiential Purchase Tendency on Happiness