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Download Article (PDF) Journal of Risk Analysis and Crisis Response Vol. 9(4); January (2020), pp. 163–167 DOI: https://doi.org/10.2991/jracr.k.200117.001; ISSN 2210-8491; eISSN 2210-8505 https://www.atlantis-press.com/journals/jracr Research Article The Harmonious Development of Big Data Industry and Financial Agglomeration in Guizhou Junmeng Lu1,2,*, Mu Zhang1 1School of Big Data Application and Economics, Guizhou University of Finance and Economics, Guiyang, Huaxi, China 2Guizhou Institution for Technology Innovation and Entrepreneurship Investment, Guizhou University of Finance and Economics, Guiyang, Huaxi, China ARTICLE INFO ABSTRACT Article History It has important practical and theoretical significance to study the coupling relationship and coordinated development between Received 31 January 2019 big data industry and financial agglomeration. This paper used 2015 cross-section data, the intuitionistic fuzzy analytic hierarchy Accepted 17 October 2019 process, the intuitionistic fuzzy number score function, the coupling model and the coupling coordination model to empirically research the coupling and coordination level between Guizhou big data industry and financial agglomeration. The empirical Keywords research shows that there is an obvious imbalance in the coordinated development and obvious spatial heterogeneity of big Big data industry data industry and financial agglomeration in Guizhou. Only Guiyang and Zunyi can achieve the coupling and coordinated financial agglomeration development of big data industry and financial agglomeration. IFAHP coupling model © 2020 The Authors. Published by Atlantis Press SARL. coupled coordination model This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/). 1. INTRODUCTION region and improve the efficiency of resource allocation. Carlin and Mayer [2] studied the impact of various financial sub-industries The 18th national congress of the communist party of China clearly on various industries from the perspective of financial structure, pointed out that scientific and technological innovation should be and found that market-oriented financial structure is conducive taken as the core of development and innovation-driven devel- to the development of high-tech and high-risk industries. Sun and opment strategy should be adopted to facilitate further economic Li [3] used Moran Index and spatial geographic weighted regres- growth, so as to provide a sustained driving force for the improve- sion model to study and believe that the optimization of domestic ment of China’s comprehensive national strength. As a strategic industrial structure is conducive to the agglomeration development emerging industry, big data industry, with its innovative technology of the financial industry, and the financial agglomeration, in turn, content, can well meet the needs of various enterprises and govern- has some promoting effect on the industrial structure. Deng and ment agencies for data resources, meet the needs of various indus- Liu [4] studied the relationship between financial agglomeration tries to follow the trend of Internet development, and make positive and industrial structure upgrading in the eastern, central and west- contributions to economic construction while the industry itself is ern regions of China, and found that regional financial agglom- developing continuously. At present, the big data industry in China eration had a significant positive impact on industrial structure presents a completely different development path from the tradi- upgrading. Through the analysis of the mechanism of action tional industry. China’s big data industry is mainly concentrated among financial development, industrial structure and economic in Beijing, Shanghai, Guangdong and other places with relatively development, Su and Xu [5] believe that regional financial agglom- developed economy, but the place with the most rapid development eration and financial development can support and promote the of big data industry is Guizhou, where the economic development upgrading of regional industrial structure. Most scholars at home and industrial foundation are relatively backward. This phenom- and abroad believe that financial agglomeration is conducive to enon indicates that compared with general industries, big data optimizing industrial structure and promoting industrial devel- industry may have unique development influencing factors. opment, so as to promote economic development in the region. However, the rise of big data industry is still a short period, and Domestic and foreign research achievements on the relationship most of the researches are still at the level of major problems, devel- between financial agglomeration and industrial development are opment trend, competitive advantage and composition and policy relatively abundant. Galbis [1] proposed that the inhibited financial system research that big data industry faces [6–10]. There is no sys- system would easily lead to the imbalance of industrial develop- tematic and authoritative theory and analysis on the factors influ- ment in the region, and the constantly optimized financial struc- encing the development of big data industry, let alone theoretical ture would obviously promote the industrial development in the and empirical research on the interaction and support between big data industry and financial agglomeration. Based on this, this *Corresponding author. Email: [email protected]; [email protected] study was to explore big data industry and financial agglomeration 164 J. Lu and M. Zhang / Journal of Risk Analysis and Crisis Response 9(4) 163–167 coupling between coordination mechanism, taking Guizhou prov- indicators. In this study, cross-sectional data in 2015 were selected ince as a sample, using the Intuitionistic Fuzzy Analytic Hierarchy from statistical yearbooks of Guizhou prefectural cities, statistical Process (IFAHP) and the coupling coordination model to empiri- yearbooks of Guizhou province, China banking and insurance cally analyze the development level and coupling coordination level regulatory commission, China securities regulatory commission, of big data industry and financial agglomeration. It is expected to statistics bureau of Guizhou province, statistics bureau of Guizhou put forward corresponding countermeasures and suggestions for cities and official websites of governments. the development of regional big data industry, which has certain practical and theoretical significance. 3.2. Comprehensive Evaluation Steps based on IFAHP 2. ANALYSIS OF INTERACTION BETWEEN BIG DATA INDUSTRY AND FINANCIAL Step 1: Data standardization. Indicators of the evaluation system AGGLOMERATION for the coupling and coordinated development of the big data industry-financial agglomeration system are all efficiency indica- According to the theory of manufacturers, labour factor, capital tors. The standardized formula is: factor and technology factor are the main driving forces to pro- ()xx− min mote industrial development, and the development of emerging ij j zij = ,,zij ∈[]01, industries has a huge demand for the three factors, especially the ()max xxjj− min capital factor. Referring to China’s big data industrial agglomera- tion areas, most of which are economically developed areas, and big xij is the original index value, max xj and max xj is the maximum data industry, as an emerging industry, its capital demand deter- and minimum value of the original index. mines the development level of big data industry to a large extent. Step 2: Construct the intuitive judgment matrix. By comparing the Therefore, it is speculated that the agglomeration of financial importance of indexes, the qualitative evaluation words of indica- industry in a certain region can promote the development of local tors are converted into intuitionistic fuzzy Numbers, and the intu- big data industry to a certain extent. The role of financial agglomer- itionistic judgment matrix is constructed R = (r ) . Among them, ation in promoting the development of big data is mainly reflected ij n × n r = (m , v )(i,j = 1, 2, …, n), m represent the membership degree, in two aspects. On the one hand, as an emerging industry, big data ij ij ij ij v represent the non-membership degree, m ∈ [0, 1], v ∈ [0, 1], industry is different from the traditional labour-intensive indus- ij ij ij m = v , v = m , m = v = 0.5, m + v ≤ 1. The p = 1 − m − v is the try, its development requires a lot of capital-intensive research and ij ji ij ji ii ii ij ij ij ij ij hesitation degree. development activities, which means that sufficient capital invest- ment can effectively drive the structural adjustment and upgrad- Step 3: Consistency test. The consistency of intuitionistic judgment ing of big data industry and promote the development of big data matrix is tested by constructing consistency intuitionistic judgment industry. On the other hand, financial agglomeration can promote matrix. If it passes the consistency test, skip to step 5. If not, pro- the benign development of big data industry. Specifically, the cap- ceed to step 4. ital allocation function and screening mechanism of the financial Step 4: Revise the intuitive judgment matrix which does not satisfy market can always make investment funds flow to enterprises with the consistency test. Set the parameter s for iteration, s ∈ [0, 1], growth space and development potential, so as to improve the use until it passes the consistency test. efficiency of investment funds, improve the factor productivity
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