DOCSLIB.ORG

Research on the Measurement of Manufacturing Industry Integration Level of Shandong Capital City Cluster

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Research on the Measurement of Manufacturing Industry Integration Level of Shandong Capital City Cluster E3S Web of Conferences 214, 02037 (2020) https://doi.org/10.1051/e3sconf/202021402037 EBLDM 2020 Research on the Measurement of Manufacturing Industry Integration Level of Shandong Capital City Cluster Yang Zhao1 a 1Shandong Management University Jinan, China Abstract: This paper analyzes the integration level of regional manufacturing industry by measuring the similarity coefficient of manufacturing industry structure and regional division index between Jinan, the capital city of Shandong province, and other cities in the region from 2012 to 2017. From 2012 to 2017, the similarity coefficient of industrial structure of Shandong capital city cluster is declining; the regional division index is rising; and the industrial transformation of Jinan in the region has made remarkable progress, which is conducive to the continuous improvement of regional integration level. fierce, which will lead to regional protection between 1 INTRODUCTION regions. On the other hand, if the similarity coefficient of industrial structure between regions is too low, the The level of industrial integration is an important industrial synergy between regions must be poor, and the indicator to measure the level of regional integration. industrial connection between regions will not be According to economic theory, regional division of labor strong[1]. The calculation formula of industrial structure is a spatial form of social division of labor, while similarity coefficient is as follows: industrial division is an organizational form of regional division of labor. Regional division of labor according to (1) their own resource endowments can improve production ∑=1 2 2 efficiency. Shandong capital city cluster includes Jinan, In this Formula = √(,∑ S=ij1 is the)(∑ =similarity1 ) coefficient of Zibo, Dezhou, Liaocheng, Tai'an, Laiwu, and Zouping, industrial structure of two regions in the area, Xik, Xjk, six prefecture-level cities and one county-level city, with respectively, are the ratio of k industry in the industrial a total population of 30.91 million by 2017 and an area of structure of region i and the ratio of k industry in the 43000 square kilometers. Taking Jinan as the center, the industrial structure of region j. The value range of Sij is provincial capital city cluster is a typical generally 0 ~ 1. The smaller the value of Sij is, the more "center-periphery" spatial mode. Since the different the industrial structure is between the two implementation of the model, regional coordination and regions. The closer Sij is to 1, the higher the industrial integration has made remarkable progress, but there are structure similarity is between the two regions. still some areas leave much to be desired in the process of development. This paper attempts to analyze the regional B. Regional Division of Labor Index integration progress of the capital city cluster in Shandong Since Paul R. Krugman put forward the index of province from the perspective of industrial integration. regional division of labor, the index of regional division of labor has become an important index to measure regional integration. The calculation formula of regional 2 THE SETTING OF INDUSTRIAL INTEGRATION division index is as follows[2][3]: INDEX (2) In this paper, similarity coefficient of industrial structure In the formula, S is the regional division index of and index of regional division of labor are used to S =jk∑ =1 | − | region j and region k; q and q are the total industrial measure the industrial integration level of the cities in the k j output value of the two regions respectively, and q and capital city cluster of Shandong province. ik qij are the output value of industry i of the two regions A. Similarity Coefficient of Industrial Structure respectively. Sjk value ranges from 0 to 2. If the industrial The similarity coefficient of industrial structure is structures of the two regions are identical, the index is 0; used to measure the similarities and differences of if the industrial structures of the two regions are industrial structure between regions. If the similarity of completely different, the index is 2. industrial structure between regions is very high, the industrial competition between regions must be very [email protected] © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). E3S Web of Conferences 214, 02037 (2020) https://doi.org/10.1051/e3sconf/202021402037 EBLDM 2020 3 THE MEASUREMENT OF INDUSTRIAL China's manufacturing industry is divided into 31 categories. The manufacturing output value of each city in INTEGRATION LEVEL OF THE CAPITAL CITY the capital city cluster of Shandong province is mainly CLUSTER IN SHANDONG PROVINCE concentrated in the top 29 categories. Due to the changes of industry classification standard over the years, this The data of this paper comes from the statistical yearbook paper adjusts the classifications of some manufacturing of each city in the capital city cluster of Shandong industry to ensure the consistency of the industry statistics province. Because Zouping is a county-level city, the data over the years. After the adjustment, the scale of its manufacturing industry is too small compared manufacturing industries in the capital city cluster of with other prefecture-level cities, it is not considered in Shandong province are divided into 26 categories, which the comparison. According to the industry classification are as follows: standard set by China National Bureau of Statistics, TABLE I. CATEGORIES OF MANUFACTURING INDUSTRIES IN THE CAPITAL CITY CLUSTER OF SHANDONG PROVINCE Industry category Industry category Industry category Industry category Petroleum processing, Agricultural and sideline textile industry Furniture manufacturing coking, and nuclear fuel food processing industry processing industry Textile clothing, clothing Chemical raw materials and Paper making and paper Food manufacturing industry, chemical fiber chemical products manufacturing manufacturing industry manufacturing industry Leather, fur, feather and their Wine, beverage, and refined Printing and recording media Pharmaceutical products, and footwear tea manufacturing reproduction industry manufacturing industry Culture and education, Wood processing and wood, industry and beauty, sports Rubber and plastic products Tobacco products industry bamboo, rattan, palm, and and entertainment products industry grass products industry manufacturing industry Nonmetallic mineral products General equipment Nonferrous metal smelting Transportation equipment industry manufacturing and rolling industry manufacturing industry Manufacturing of computer, Ferrous metal smelting and Special equipment Metal products industry communication and other rolling industry manufacturing industry electronic equipment Electrical machinery and Instrument manufacturing equipment manufacturing industry industry A. Calculation of Similarity Coefficient of Industrial 1 Structure 0.8 This paper measures the industrial structure similarity Zibo coefficient of the manufacturing industries of Jinan city 0.6 Tai'an cluster from 2012 to 2017. The provincial capital city cluster is a regional spatial structure with Jinan as the 0.4 Dezhou center and other cities as the periphery. Therefore, the 0.2 similarity coefficient of industrial structure is mainly used Liaocheng to calculate the industrial structure similarity between 0 Laiwu Jinan and the peripheral cities. The results are as follows: TABLE II. INDUSTRIAL STRUCTURE SIMILARITY 2012 2013 2014 2015 2016 2017 Figure 1. industrial structure similarity Zibo 0.65 0.61 0.62 0.64 0.59 0.48 Tai'an 0.80 0.80 0.81 0.89 0.85 0.66 As shown in the figure1 above, the similarity Dezhou 0.63 0.68 0.71 0.91 0.86 0.69 Liaocheng 0.57 0.59 0.60 0.83 0.80 0.63 coefficient of manufacturing industrial structure between Laiwu 0.43 0.43 0.47 0.42 0.39 0.26 Jinan, the center, and the surrounding cities shows a trend of rising first and then declining. Before 2015, Tai'an had the highest similarity with Jinan's manufacturing industrial structure, and Laiwu had the lowest similarity. After 2015, the similarity coefficient of manufacturing industrial structure between Jinan and Dezhou was the highest, and 2015 was a turning point. The manufacturing industrial structure of Jinan and the surrounding cities shows an obvious downward trend. 2 E3S Web of Conferences 214, 02037 (2020) https://doi.org/10.1051/e3sconf/202021402037 EBLDM 2020 3 THE MEASUREMENT OF INDUSTRIAL China's manufacturing industry is divided into 31 B. Calculation of the Regional Division of Labor Index As for Tai’an, it has no manufacturing industry with categories. The manufacturing output value of each city in special advantage, only some industries, such as chemical INTEGRATION LEVEL OF THE CAPITAL CITY The index of regional division of labor between Jinan, the capital city cluster of Shandong province is mainly the center of the capital city cluster of Shandong province, raw materials and chemical products manufacturing, CLUSTER IN SHANDONG PROVINCE concentrated in the top 29 categories. Due to the changes and the surrounding cities is calculated. The results are as general equipment manufacturing, and non-metallic of industry classification standard over the years, this follows: mineral products industry, accounted for slightly 10% of The data of this paper comes from the statistical yearbook paper adjusts the classifications of some manufacturing
Load more

Recommended publications
  • A New Indicator to Assess Public Perception of Air Pollution Based on Complaint Data
    applied sciences Article A New Indicator to Assess Public Perception of Air Pollution Based on Complaint Data Yong Sun 1 , Fengxiang Jin 2, Yan Zheng 1, Min Ji 1,* and Huimeng Wang 2,3 1 College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China; [email protected] (Y.S.); [email protected] (Y.Z.) 2 College of Surveying and Geo-Informatics, Shandong Jianzhu University, Ji’nan 250101, China; [email protected] (F.J.); [email protected] (H.W.) 3 State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China * Correspondence: [email protected] Abstract: Severe air pollution problems have led to a rise in the Chinese public’s concern, and it is necessary to use monitoring stations to monitor and evaluate pollutant levels. However, monitoring stations are limited, and the public is everywhere. It is also essential to understand the public’s awareness and behavioral response to air pollution. Air pollution complaint data can more directly reflect the public’s real air quality perception than social media data. Therefore, based on air pollution complaint data and sentiment analysis, we proposed a new air pollution perception index (APPI) in this paper. Firstly, we constructed the emotional dictionary for air pollution and used sentiment analysis to calculate public complaints’ emotional intensity. Secondly, we used the piecewise function to obtain the APPI based on the complaint Kernel density and complaint emotion Kriging interpolation, and we further analyzed the change of center of gravity of the APPI.
    [Show full text]
  • Emperor's River: China's Grand Canal – Philipp Scholz Rittermann July 1
    Emperor’s River: China’s Grand Canal – Philipp Scholz Rittermann July 1 – November 30, 2014 Harn Museum of Art -- Rubin Gallery Introduction In 2009 and 2010, photographer Philipp Scholz Rittermann traveled along China’s Grand Canal to capture the country’s booming economy, and rapidly changing landscape and social structure. Rittermann’s photographic interests are largely focused on the built environment, and the way people and the planet are transformed by it. He traveled to China first as an invited artist and then on succeeding trips to document this massive waterway. Having mastered, in previous projects, the digital panorama—a format hungry for information—he found his ideal subject in the People’s Republic of China. The number of bridges, boats, scooters, railways, and the subject of the series itself, the Grand Canal, speaks to Rittermann’s fascination with passage. This material manifestation of movement becomes symbolic of our collective human journey in the 21st century. Accelerated passage and progress are the means by which this particular culture, China, and subsequently the world, plunges headlong into the future. Rittermann wants to momentarily arrest these unprecedented changes to reflect on their ramifications. As we voyage out of one century into another, his photographs become lyrical topographical maps from which to chart the course of a brave new world. — Carol McCusker, Curator About the Artist & Series To make his photographs, Philipp Rittermann handholds a digital camera, panning across a scene, making exposures every few seconds, anticipating what is about to happen in each frame. The specific needs of each frame (light, perspective, focal separation) must be understood in a fraction of a second while shooting.
    [Show full text]
  • Qingdao City Shandong Province Zip Code >>> DOWNLOAD (Mirror #1)
    Qingdao City Shandong Province Zip Code >>> DOWNLOAD (Mirror #1) 1 / 3 Area Code & Zip Code; . hence its name 'Spring City'. Shandong Province is also considered the birthplace of China's . the shell-carving and beer of Qingdao. .Shandong china zip code . of Shandong Province,Shouguang 262700,Shandong,China;2Ruifeng Seed Industry Co.,Ltd,of Shouguang City,Shouguang 262700,Shandong .China Woodworking Machinery supplier, Woodworking Machine, Edge Banding Machine Manufacturers/ Suppliers - Qingdao Schnell Woodworking Machinery Co., Ltd.Qingdao Lizhong Rubber Co., Ltd. Telephone 13583252201. Zip code 266000 . Address: Liaoyang province Qingdao city Shandong District Road No.what is the zip code for Qingdao City, Shandong Prov China? . The postal code of Qingdao is 266000. i cant find the area code for gaomi city, shandong province.Province City Add Zip Email * Content * Code * Product Category Bamboo floor press Heavy bamboo press . No.111,Jing'Er Road,Pingdu, Qingdao >> .Shandong Gulun Rubber Co., Ltd. is a comprehensive . Zhongshan Street,Dezhou City, China, Zip Code . No.182,Haier Road,Qingdao City,Shandong Province E .. Qingdao City, Shandong Province, Qingdao, Shandong, China Telephone: Zip Code: Fax: Please sign in to . Qingdao Lifeng Rubber Co., Ltd., .Shandong Mcrfee Import and Export Co., Ltd. No. 139 Liuquan North Road, High-Tech Zone, Zibo City, Shandong Province Telephone: Zip Code: Fax: . Zip Code: Fax .Qingdao Dayu Paper Co., Ltd. Mr. Ike. .Qianlou Rubber Industrial Park, Mingcun Town, Pingdu, Qingdao City, Shandong Province.Postal code: 266000: . is a city in eastern Shandong Province on the east . the CCP-led Red Army entered Qingdao and the city and province have been under PRC .QingDao Meilleur Railway Co.,LTD AddressJinLing Industrial Park, JiHongTan Street, ChengYang District, Qingdao City, ShanDong Province, CHINA.
    [Show full text]
  • Prevalence, Risk Factors, and Medical Costs of Chlamydia Trachomatis
    Huai et al. BMC Infectious Diseases (2018) 18:534 https://doi.org/10.1186/s12879-018-3432-y RESEARCH ARTICLE Open Access Prevalence, risk factors, and medical costs of Chlamydia trachomatis infections in Shandong Province, China: a population- based, cross-sectional study Pengcheng Huai1,2,3 , Furong Li2, Zhen Li2, Lele Sun2,4,Xi’an Fu2,4, Qing Pan2,4, Gongqi Yu2,4, Zemin Chai2,4, Tongsheng Chu2, Zihao Mi2,4, Fangfang Bao2,4, Honglei Wang2,4, Bingni Zhou2,4, Chuan Wang2,4, Yonghu Sun2,4, Guiye Niu2,4, Yuan Zhang2,4, Fanghui Fu2,4, Xiaoqiao Lang2,4, Xiaoling Wang2,4, Hui Zhao2,4, Daina Liu2,4, Hong Liu2,4, Dianchang Liu2, Jian Liu2, Aiqiang Xu3,5 and Furen Zhang2,4* Abstract Background: A population-based study of Chlamydia trachomatis (CT) infections is essential in designing a specific control program; however, no large investigation of CT infections among the general population in mainland China has been conducted since 2000. We aimed to determine the prevalence, risk factors, and associated medical costs of CT among residents, 18–49 years of age, in Shandong, China. Methods: From May to August 2016, a multistage probability sampling survey involving 8074 individuals was distributed. Data were collected via face-to-face interviews, followed by self-administered questionnaire surveys. First-void urines were collected and tested for CT and Neisseria gonorrhoeae (NG) using nucleic acid amplification. Results: The weighted prevalence of CT infection was 2.3% (95% confidence interval [CI], 1.5–3.2) in females and 2.7% (1. 6–3.8) in males. Women, 30–34 years of age, had the highest prevalence of CT infections (3.5%, 2.6–4.4), while the highest prevalence of CT infections in males was in those 18–24 years of age (4.3%, 0.0–8.8).
    [Show full text]
  • Reliability Optimization of a Railway Network
    sustainability Article Reliability Optimization of a Railway Network Xuelei Meng 1,2,*, Yahui Wang 3, Limin Jia 2 and Lei Li 4 1 School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China 2 State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China; [email protected] 3 School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China; [email protected] 4 Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, Zhejiang, China; [email protected] * Correspondence: [email protected] Received: 7 October 2020; Accepted: 14 November 2020; Published: 24 November 2020 Abstract: With the increase of the railway operating mileage, the railway network is becoming more and more complicated. We expect to build more railway lines to offer the possibility to offer more high quality service for the passengers, while the investment is often limited. Therefore, it is very important to decide the pairs of cities to add new railway lines under the condition of limited construction investment in order to optimize the railway line network to maximize the reliability of the railway network to deal with the railway passenger transport task under emergency conditions. In this paper, we firstly define the reliability of the railway networks based on probability theory by analyzing three minor cases. Then we construct a reliability optimization model for the railway network to solve the problem, expecting to enhance the railway network with the limited investment. The goal is to make an optimal decision when choosing where to add new railway lines to maximize the reliability of the whole railway network, taking the construction investment as the main constraint, which is turned to the building mileage limit.
    [Show full text]
  • The Mineral Industry of China in 2016
    2016 Minerals Yearbook CHINA [ADVANCE RELEASE] U.S. Department of the Interior December 2018 U.S. Geological Survey The Mineral Industry of China By Sean Xun In China, unprecedented economic growth since the late of the country’s total nonagricultural employment. In 2016, 20th century had resulted in large increases in the country’s the total investment in fixed assets (excluding that by rural production of and demand for mineral commodities. These households; see reference at the end of the paragraph for a changes were dominating factors in the development of the detailed definition) was $8.78 trillion, of which $2.72 trillion global mineral industry during the past two decades. In more was invested in the manufacturing sector and $149 billion was recent years, owing to the country’s economic slowdown invested in the mining sector (National Bureau of Statistics of and to stricter environmental regulations in place by the China, 2017b, sec. 3–1, 3–3, 3–6, 4–5, 10–6). Government since late 2012, the mineral industry in China had In 2016, the foreign direct investment (FDI) actually used faced some challenges, such as underutilization of production in China was $126 billion, which was the same as in 2015. capacity, slow demand growth, and low profitability. To In 2016, about 0.08% of the FDI was directed to the mining address these challenges, the Government had implemented sector compared with 0.2% in 2015, and 27% was directed to policies of capacity control (to restrict the addition of new the manufacturing sector compared with 31% in 2015.
    [Show full text]
  • Federal Register/Vol. 86, No. 119/Thursday, June 24, 2021/Notices
    33222 Federal Register / Vol. 86, No. 119 / Thursday, June 24, 2021 / Notices MPROVE Co., Limited Shanghai Jade Shuttle Hardware Tools Co., Wire Products Manufacturing Co., Ltd. Nailtech Co., Ltd. Ltd. Wuhu Diamond Metal Products Co., ltd Nanjing Duraturf Co., Ltd. Shanghai March Import & Export Co., Ltd. Wulian Zhanpeng Metals Co., Ltd. Nanjing Nuochun Hardware Co., Ltd. Shanghai Seti Enterprise Int’l Co., Ltd. Wuxi Holtrent International Co., Ltd. Nanjing Tianxingtong Electronic Technology Shanghai Shenda Imp. & Exp. Co., Ltd Wuxi Yushea Furniture Co., Ltd. Co., Ltd. Shanghai Sutek Industries Co., Ltd. Xiamen Hongju Printing Industry &trade Co., Nanjing Tianyu International Co., Ltd. Shanghai Television and Electronics Import Ltd. Nanjing Toua Hardware & Tools Co., Ltd. and Export Co., Ltd. Xuzhou Cip International Group Co, Ltd. Nanjing Zeejoe International Trade Shanghai Yiren Machinery Co., Ltd. Yiwu Competency Trading Co., Ltd. Nantong Intlevel Trade Co., Ltd. Shanghai Yueda Fasteners Co., Ltd. Yiwu Kingland Import & Export Co. Natuzzi China Limited Shanghai Zoonlion Industrial Co., Limited Yiwu Taisheng Decoration Materials Limited Nielsen Bainbridge LLC Shanghai Zoonlion Industrial Co., Ltd. Yiwu Yipeng Import & Export Co., Ltd. Ningbo Adv. Tools Co., Ltd. Shanxi Easyfix Trade Co., Ltd. Yongchang Metal Product Co., Ltd. Ningbo Angelstar Trading Co., Ltd. Shanxi Fastener & Hardware Products Youngwoo Fasteners Co., Ltd. Ningbo Bright Max Co., Ltd. Shanxi Xinjintai Hardware Co., Ltd. Yuyao Dingfeng Engineering Co. Ltd. Ningbo Fine Hardware Production Co., Ltd. Shaoxing Bohui Import and Export Co., Ltd Zhanghaiding Hardware Co., Ltd. Ningbo Freewill Imp. & Exp. Co., Ltd. Shaoxing Chengye Metal Producing Co., Ltd. Zhangjiagang Lianfeng Metals Products Co., Ningbo Home-dollar Imp.& Exp.
    [Show full text]
  • Spatial Optimization and Mode Analysis of Primary Industry Structure in Yellow River Delta Ping Yang, Yujian Yang
    Spatial Optimization and Mode Analysis of Primary Industry Structure in Yellow River Delta Ping Yang, Yujian Yang To cite this version: Ping Yang, Yujian Yang. Spatial Optimization and Mode Analysis of Primary Industry Structure in Yellow River Delta. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. pp.150-160, 10.1007/978-3-642-36137-1_19. hal-01348227 HAL Id: hal-01348227 https://hal.inria.fr/hal-01348227 Submitted on 22 Jul 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Spatial Optimization and Mode Analysis of Primary Industry Structure in Yellow River Delta Ping Yang, Yujian Yang* 1 The institute of sustainable development of Shandong Agricultural Science Academy 2S & T Information Engineering Technology Center of Shandong Academy of Agricultural Science, Information center of agronomy College of Shandong University *Corresponding author, Address: S&T Information Engineering Research Center, Number 202 Gongye North Road,
    [Show full text]
  • Fiscal Reform and Land Public Finance: Zouping County In
    Fiscal Reform and Land Public 7 Finance: Zouping County in National Context h SUSAN H. WHITING and has become a key source of fi scal revenue for local governments in China. LAs the value of land has increased with urbanization and economic development, local governments have sought to exploit their control over land in order to gener- ate both on- and off - budget revenue. Scholars and policy makers have come to refer to this phenomenon as “land public fi nance.” Th is chapter argues that land public fi nance is in large part an outgrowth of trends in central- local fi scal relations. During the course of China’s transition from a planned to a market economy, central- local fi scal relations have undergone a series of fundamental reforms. Cur- rent challenges grow out of a number of features of the Chinese po liti cal economy, the most important of which is the mismatch between the allocation of revenues and the assignment of expenditure responsibilities across levels of government. Local governments— county governments in particular— oft en lack adequate rev- enues within the formal fi scal system to fi nance the wide range of public goods and ser vices they are mandated by higher levels to provide. Th e mismatch between revenues and expenditure responsibilities leads to heavy reliance on intergovern- mental fi scal transfers that, nonetheless, have not yet eff ectively redressed revenue inadequacy or the high levels of in e qual ity that have emerged in the context of economic reform. Th is fi scal gap drives additional problems, including the growth of hidden government debts and off - budget funds at the local level.
    [Show full text]
  • Land-Use Efficiency in Shandong (China)
    sustainability Article Land-Use Efficiency in Shandong (China): Empirical Analysis Based on a Super-SBM Model Yayuan Pang and Xinjun Wang * Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; [email protected] * Correspondence: [email protected] Received: 20 November 2020; Accepted: 14 December 2020; Published: 18 December 2020 Abstract: A reasonable evaluation of land-use efficiency is an important issue in land use and development. By using a super-SBM model, the construction and cultivated land-use efficiency of 17 cities in Shandong from 2006 to 2018 were estimated and the spatial-temporal variation was analyzed. The results showed that: (1) The land use efficiency levels were quite different, and low-efficiency cities impacted the overall development process. (2) The efficiency values of construction land generally fluctuated and rose, meaning that room remains for future efficiency improvements. Cultivated land generally showed a high utilization efficiency, but it fluctuated and decreased. (3) The construction land-use efficiency was highest in the midland region, especially in Laiwu city, followed by the eastern region and Qingdao city, and the western region. The spatial variation in cultivated land presented a trend of “high in the middle, low in the periphery,” centered on Jinan and Yantai city. (4) Pure technical efficiency was the main restriction driving inefficient utilization in the western region, while scale efficiency played that role in the east. Based on the findings, policy suggestions were proposed to improve the land-use efficiency in Shandong and promote urban sustainable development. Keywords: land use; efficiency level; super-SBM model; Shandong Province; construction land; cultivated land 1.
    [Show full text]
  • Cereal Series/Protein Series Jiangxi Cowin Food Co., Ltd. Huangjindui
    产品总称 委托方名称(英) 申请地址(英) Huangjindui Industrial Park, Shanggao County, Yichun City, Jiangxi Province, Cereal Series/Protein Series Jiangxi Cowin Food Co., Ltd. China Folic acid/D-calcium Pantothenate/Thiamine Mononitrate/Thiamine East of Huangdian Village (West of Tongxingfengan), Kenli Town, Kenli County, Hydrochloride/Riboflavin/Beta Alanine/Pyridoxine Xinfa Pharmaceutical Co., Ltd. Dongying City, Shandong Province, 257500, China Hydrochloride/Sucralose/Dexpanthenol LMZ Herbal Toothpaste Liuzhou LMZ Co.,Ltd. No.282 Donghuan Road,Liuzhou City,Guangxi,China Flavor/Seasoning Hubei Handyware Food Biotech Co.,Ltd. 6 Dongdi Road, Xiantao City, Hubei Province, China SODIUM CARBOXYMETHYL CELLULOSE(CMC) ANQIU EAGLE CELLULOSE CO., LTD Xinbingmaying Village, Linghe Town, Anqiu City, Weifang City, Shandong Province No. 569, Yingerle Road, Economic Development Zone, Qingyun County, Dezhou, biscuit Shandong Yingerle Hwa Tai Food Industry Co., Ltd Shandong, China (Mainland) Maltose， Malt Extract， Dry Malt Extract， Barley Extract Guangzhou Heliyuan Foodstuff Co.,LTD Mache Village, Shitan Town, Zengcheng, Guangzhou，Guangdong，China No.3, Xinxing Road, Wuqing Development Area, Tianjin Hi-tech Industrial Park, Non-Dairy Whip Topping\PREMIX Rich Bakery Products(Tianjin)Co.,Ltd. Tianjin, China. Edible oils and fats / Filling of foods/Milk Beverages TIANJIN YOSHIYOSHI FOOD CO., LTD. No. 52 Bohai Road, TEDA, Tianjin, China Solid beverage/Milk tea mate（Non dairy creamer）/Flavored 2nd phase of Diqiuhuanpo, Economic Development Zone, Deqing County, Huzhou Zhejiang Qiyiniao Biological Technology Co., Ltd. concentrated beverage/ Fruit jam/Bubble jam City, Zhejiang Province, P.R. China Solid beverage/Flavored concentrated beverage/Concentrated juice/ Hangzhou Jiahe Food Co.,Ltd No.5 Yaojia Road Gouzhuang Liangzhu Street Yuhang District Hangzhou Fruit Jam Production of Hydrolyzed Vegetable Protein Powder/Caramel Color/Red Fermented Rice Powder/Monascus Red Color/Monascus Yellow Shandong Zhonghui Biotechnology Co., Ltd.
    [Show full text]
  • Your Paper's Title Starts Here
    4th National Conference on Electrical, Electronics and Computer Engineering (NCEECE 2015) Performance comprehensive assessment method for intelligent transportation system of Shandong Province ， Changying Chen1 a， Xiuhong Yang2,b and Qi Feng1,c 1 Information Institute, Shandong Academy of Sciences, Jinan 250014, China, 2 Jinan Quancheng Middle School of Shandong Province, Jinan 250011, China, [email protected], b. [email protected], [email protected] Keywords: intelligent transportation; assessment; Shandong Province Abstract. Intelligent transportation system (ITS) is an effective method for solving existing traffic jam, traffic rules violation reduction and traffic low efficiency. We introduce the development of Shandong ITS construction in the latest three years, based on which we present a performance comprehensive assessment method for expressway and national and provincial highway (NPH) ITS construction. We comprehensively assess all quantitative parameters for Shandong all municipal ITS construction with the method. We further analyze the distribution of all municipal planned total investment, emphasizing all municipal distributions of current period total construction investment and construction fund and asset practical investment. All the analysis includes two situations: expressway and NPH. Practical data analysis shows that the difference of all municipal practical fund and asset investments is the main reason that cause the distinction of comprehensive performance assessment when investment difference is significant. The result can guide future ITS construction of Shandong and even China. It has also reference value for the assessment of other similar system construction. 1 Introduction With the increase of Chinese population, vehicle sale volume increases year after year. However, the increase of highway volume lags behind that of vehicle volume greatly.
    [Show full text]