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exploratory spatial data analysis of ISO 9001 certification trends and innovation performance in South America 5

Exploratory Spatial Data Analysis of ISO 9001 certification ...

5th International Conference on Quality Engineering and Management: A Better World with Quality! Quality in the Digital Transformation, ICQEM 2022

作者： Sordan, J.E. Oprime, P.C. Condé, G.C.P. Bueno, C.R. Pimenta, M.L. Federal University of São Carlos – UFSCar Brazil Federal University of Uberlândia – UFU Brazil

ISBN: (纸本)9789895491117

Purpose – The present paper aims to present an exploratory spatial data analysis (ESDA) of ISO 9001 certification trends and innovation performance in order to identify geographic patterns and spatial autocorrelation between performance innovation and annual growth rate of ISO 9001 certificates in South America. Design/methodology/approach – Using secondary data regarding the number of ISO 9001 valid certificates and innovation indexes, our methodological procedure combines descriptive analysis and ESDA to verify spatial autocorrelation hypotheses and spill-over effects across countries. Findings – The results reveal spatial patterns regarding the ISO 9000 certification trends in South American countries. The ESDA results call attention to the association of annual growth rate of ISO 9001 certificates with gross capital formation, expenditure on education, and high-tech manufacturing. In addition, the study points to spatial clusters regarding these measures. Research limitations/implications - As the study relies on South American country data, future research should explore spatial patterns and spill-over effects using samples from other regions or continents. Practical implications - This study discusses the association between ISO 9001 Quality Management Systems (QMS) and innovation performance from a geographic perspective. Moreover, the findings indicate associations between the demand for ISO 9001 certificates and innovation performance indicators. Originality/value – This paper presents an exploratory study regarding the effect of innovation performance and ISO 9001 QMS certification in South American countries using ESDA techniques. © 2022 Universidade do Minho. All rights reserved.

关键词： exploratory spatial data analysis ISO 9001 Quality Management

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Study of Malnutrition in Children Under Five in Peru Using the exploratory spatial data analysis 7th

Study of Malnutrition in Children Under Five in Peru Using t...

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7th Brazilian Technology Symposium (BTSym) - Emerging Trends and Challenges in Technology

作者： Gonzalez Cusi, Bryan Martin Solano Davila, Olga Lidia Univ Nacl Mayor San Marcos Fac Ciencias Matemat Lima Peru

ISBN: (纸本)9783031044359;9783031044342

This research presents the application of the exploratory spatial data analysis to assess the type of spatial pattern that follows the cases of patients with malnutrition in children under 5 years who were attended in the Ministry of Health of Peru (MINSA, after its Spanish abbreviation) in 2017. The results demonstrated that malnutrition cases in children under 5 years were non-homogeneously distributed throughout Peru in 2017. The boxplot identified that a larger number of malnutrition cases in girls under five years was presented in the departments of Piura, Loreto, and Ucayali;and in the case of the boys was in Piura, Cajamarca, and Ucayali. The rates map evidenced that a higher rate of malnutrition was presented in the departments of Piura, Cajamarca, Loreto, Ucayali, Madre de Dios, and Ayacucho. The LISA indexes found the presence of significant clusters in departments with a high demand for this disease as in Loreto, as well as significant clusters in departments with less demand as in Lima, Moquegua, and Puno. The Moran's Index indicated that the spatial dependence is positive and almost nil.

关键词： exploratory spatial data analysis Malnutrition LISA map Moran's Index

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Evaluation of Agricultural Modernization Development Level based on exploratory spatial data analysis and Back Propagation Neural Network 1

Evaluation of Agricultural Modernization Development Level b...

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1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Liu, Wenjie Aba Teachers University Aba Prefecture China

ISBN: (纸本)9798350352931

Recent days, agricultural modernization represents a transformative shift from traditional farming practices to a modern, science-driven agricultural system. The existing approaches for assessing agricultural modernization development level have encountered significant challenges which includes, model interoperability, identification of patterns and relationships, variability in temporal and spatial variables. Therefore, this paper proposes exploratory spatial data analysis-Backpropagation Neural Network (ESDABPNN) for Evaluation of Agricultural Modernization Development Level which is employed on statistical yearbook of Chinese government. Then, the data is preprocessed by using data normalization which effectively improved the model interoperability. After that, the ESDA-BPNN is used for analyzing the agricultural development which effectively identified the patterns and relationships between neighboring regions, highlighted the areas of high agricultural modernization. Finally, obstacle degree model is used for identifying key constraints and quantifies the obstacle impact. The proposed ESDA has increased in the year 2024 C 1 has increased 22%, C2 increased 24%, C3 increased 25%, C4 increases 22% and C5 increases 24%, where, C1, C2, C3, C4 and C 5 are per unit arable machinery, irrigation rate, per capita electricity consumption, agriculture results of expenditure, area of arable land per household when compared with existing ESDA. © 2024 IEEE.

关键词： backpropagation neural network evaluation of agricultural modernization development level exploratory spatial data analysis obstacle degree model statistical yearbook of chinese government

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Study on the evolution of B&Bs spatial distribution based on exploratory spatial data analysis (ESDA) and its influencing factors-with Yangtze River Delta as an example

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EUROPEAN JOURNAL OF REMOTE SENSING 2021年第Supp 2期54卷 296-308页

作者： Qiu, Yishu Zhu, Zhenmin Huang, Heping Bing, Zhenhua Shanghai Business Sch Sch Hotel Management Shanghai 201400 Peoples R China

In the "era of sharing economy 2.0", China's B&Bs industry enjoys rapid development as a new business format, boosting regional economy to reach a new height. This paper selects the Yangtze River Delta region, China's largest economic zone, as the research area, and takes exploratory spatial data analysis (ESDA) and GIS to study the agglomeration characteristics and evolutionary trajectories of B&Bs spatial patterns amid 2013-2017. The results indicate that: (1) B&Bs in the Yangtze River Delta region exhibit balanced development. (2) From the perspective of global spatial autocorrelation analysis, B&Bs spatial distribution features significant spatial autocorrelation, with spatial agglomeration degree on the rise. (3) From the perspective of local spatial autocorrelation analysis, it gradually shows a gradual decreasing pattern from the east to the west, forming a significant high concentration of eastern cities and a low concentration of western cities. By comparing the results of the 3 years, Huzhou and Shanghai showed a significant high concentration from 2013 to 2015, and neighboring cities such as Suzhou, Jiaxing and Hangzhou have shown a high approaching trend, indicating that in recent years, the development awareness of the industry is converging. (4) The four factors: endowment of tourism resources, transportation convenience, policy conditions and residents' living standards exert important influences on B&Bs spatial distribution.

关键词： exploratory spatial data analysis Yangtze River Delta region B&Bs spatial distribution

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Drivers of winegrowers' decision on land use abandonment based on exploratory spatial data analysis and multilevel models

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LAND USE POLICY 2023年 132卷

作者： Calafat-Marzal, Consuelo Sanchez-Garcia, Mercedes Gallego-Salguero, Aurea Pineiro, Veronica Univ Politecn Valencia Dept Econ & Ciencias Sociales Valencia Spain Univ Publ Navarra Dept Gest Empresas Campus Arrosadia Pamplona Spain Univ Politecn Valencia Dept Ingn Cartograf Geodesia & Fotogrametria Valencia Spain Univ Nacl Dept Agron Bahia Blanca Argentina

The frequency of producers opting to abandon agricultural land has become increasingly, highlighting the sig-nificance of this phenomenon due to its environmental, landscape, and socio-economic impacts. The decisions of producers to abandon or maintain/improve their farms depend on individual and contextual factors. The aims of this research are twofold. Firstly, to evaluate the influence of the neighbours on the winegrowers' decisions, using spatial analysis. Secondly, to clarify the specific importance of each of the individual and contextual drivers in farmers' decisions to improve their farms, to keep them unchanged or to abandon them, using multilevel models. The results obtained for the case study of vineyards in Spain, reveal a strong agglomeration phenomenon in farmers' decisions indicating that producers make land use decisions influenced by what their neighbours do. A multilevel analysis identifies that individual factors are determinant and that the influence of contextual factors is conditioned by the innovation process at farm level. Individual drivers, such as size, innovation, Protected Designations of Origin and irrigation influence vineyard area, with irrigation having the greatest overall influence, and is expected to be decisive in climate change projections. The Protected Designations of Origin are driving forces that dynamize the territory and achieve productive concentrations, encouraging winegrowers to replant, but they are not enough to halt abandonment. The elements that slow down the abandonment of plots are irrigation and the combination of innovation and context variables, mainly the combination of modernised plots in the municipalities with trading options.

关键词： Multinomial multilevel analysis exploratory spatial data analysis Wine sector Abandonment land

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Cluster identification A joint application of industry concentration analysis and exploratory spatial data analysis (ESDA)

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COMPETITIVENESS REVIEW 2019年第4期29卷 401-415页

作者： Manzini, Reinaldo Belickas Luiz, Di Serio Carlos Escola Super Propaganda & Mkt Dept Management Sao Paulo Brazil Fundacao Getulio Vargas Sch Business Adm Sao Paulo Brazil

Purpose This paper aims to contribute to the approaches based on traditional industry concentration statistics for identifying clusters by complementing them with the techniques of exploratory spatial data analysis (ESDA). Design/methodology/approach Using a sample with 34,500 observations retrieved from the social information annual report released by Brazil Ministry of Labor and Employment, the methodology was designed to make a comparison between the application of industry concentration statistics and ESDA statistics. Findings As the results show, the geographic distribution measures proved to be fundamental for longitudinal studies on regional dynamics and industrial agglomerations, and the local indicator of spatial association statistic tends to overcome the limitation of the industry concentration approach. Research limitations/implications - In the period considered, due to economic, structural and circumstantial questions, activities linked to the transformation industry have been losing ground in the value creation process in Brazil. In this sense, the study of other industries may generate other types of insights that should be considered in the process of regional development. Originality/value This paper offers a critical analysis of empirical approaches and methodological advances with an emphasis on the treatment of special effects: spatial dependence, spatial heterogeneity and spatial scale. However, the regional dynamic presents a temporal dimension and a spatial dimension. The role of space has increasingly attracted attention in the analysis of economic changes. This work has identified opportunities for incorporating spatial effects in regional analysis over time.

关键词： Clusters exploratory spatial data analysis Industry concentration analysis

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Mapping mHealth (mobile health) and mobile penetrations in sub-Saharan Africa for strategic regional collaboration in mHealth scale-up: an application of exploratory spatial data analysis

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GLOBALIZATION AND HEALTH 2017年第1期13卷 63-63页

作者： Lee, Seohyun Cho, Yoon-min Kim, Sun-Young Univ Texas Hlth Sci Ctr Houston Sch Publ Hlth Dept Management Policy & Community Hlth 1200 Pressler St Houston TX 77030 USA Seoul Natl Univ Grad Sch Publ Hlth Dept Publ Hlth 1 Gwanak Ro Seoul 08826 South Korea Seoul Natl Univ Grad Sch Publ Hlth Ctr Global Hlth Res 1 Gwanak Ro Seoul 08826 South Korea

Background: Mobile health (mHealth), a term used for healthcare delivery via mobile devices, has gained attention as an innovative technology for better access to healthcare and support for performance of health workers in the global health context. Despite large expansion of mHealth across sub-Saharan Africa, regional collaboration for scale-up has not made progress since last decade. Methods: As a groundwork for strategic planning for regional collaboration, the study attempted to identify spatial patterns of mHealth implementation in sub-Saharan Africa using an exploratory spatial data analysis. In order to obtain comprehensive data on the total number of mHelath programs implemented between 2006 and 2016 in each of the 48 sub-Saharan Africa countries, we performed a systematic data collection from various sources, including: the WHO eHealth database, the World Bank Projects & Operations database, and the USAID mHealth database. Additional spatial analysis was performed for mobile cellular subscriptions per 100 people to suggest strategic regional collaboration for improving mobile penetration rates along with the mHealth initiative. Global Moran's I and Local Indicator of spatial Association (LISA) were calculated for mHealth programs and mobile subscriptions per 100 population to investigate spatial autocorrelation, which indicates the presence of local clustering and spatial disparities. Results: From our systematic data collection, the total number of mHealth programs implemented in sub-Saharan Africa between 2006 and 2016 was 487 (same programs implemented in multiple countries were counted separately). Of these, the eastern region with 17 countries and the western region with 16 countries had 287 and 145 mHealth programs, respectively. Despite low levels of global autocorrelation, LISA enabled us to detect meaningful local clusters. Overall, the eastern part of sub-Saharan Africa shows high-high association for mHealth programs. As for mobile subscription r

关键词： mHealth exploratory spatial data analysis spatial autocorrelation Sub-Saharan Africa

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An empirical study on transit-oriented low-carbon urban land use planning: exploratory spatial data analysis (ESDA) on Shanghai, China

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HABITAT INTERNATIONAL 2016年 53卷 379-389页

作者： Dou, Yi Luo, Xiao Dong, Liang Wu, Chuntao Liang, Hanwei Ren, Jingzheng Natl Inst Environm Studies Ctr Social & Environm Syst Res 16-2 Onogawa Tsukuba Ibaraki 3058506 Japan Tongji Univ Coll Architecture & Urban Planning 1239 Siping Rd Shanghai 200092 Peoples R China Shanghai Tongji Urban Planning & Design Inst 1111 North Zhongshan Rd Shanghai Peoples R China Leiden Univ CML Leiden Netherlands Nanjing Univ Informat Sci & Technol Sch Geog & Remote Sensing Nanjing 210044 Jiangsu Peoples R China Sichuan Univ Sch Tourism 2 South SectYihuan Rd Chengdu 610064 Peoples R China Univ Southern Denmark Dept Technol & Innovat Campusvej 55 DK-5230 Odense M Denmark

Low-carbon urban development is a hot spot of global concerns for fighting against climate change for China, transportation sector has a significant contribution to urban CO2 emissions, while the emissions are still increasing. Transit-Oriented Development (TOD) strategies provide a novel approach for urban planners to facilitate the urban carbon mitigation from transportation sector in long-term. While TOD strategies are emerging cases, they are merely qualitatively discussed in China, lacking practical indicators and quantitative verification for supporting the real urban plan. With such circumstance, this study aims to conduct an empirical and quantitative study on the applications of TOD strategy in Shanghai based on exploratory spatial data analysis (ESDA) and the updating data. Firstly, the changes of urban morphology were quantitatively analyzed by spatial cluster analysis, which reveals the layer structure changes and residents migration at about 1 km accuracy. Secondly, accessibility was selected as an indicator for urban transportation and estimated by method based on Time Cost Weighted Distance. Finally, the effectiveness of TOD was investigated by evaluating the integration between population and transportation accessibility with Geographic Weighted Regression model. Results highlight that TOD can effectively improve the transportation network with higher accessibility and lower urban carbon emissions. The outcomes of this study provide critical insights to the recent practice in Shanghai, as well as the practical guidance to low carbon urban planning in developing countries. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： TOD Low carbon urban planning exploratory spatial data analysis Accessibility China

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Estimation of Vulnerable Areas to Faults Caused by Tree Vegetation in Power Distribution Systems

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IEEE ACCESS 2024年 12卷 48472-48484页

作者： Santos, Andreia S. Faria, Lucas Teles Boschi, Leticia S. Lopes, Mara Lucia M. Minussi, Carlos R. Sao Paulo State Univ UNESP Dept Elect Engn BR-15385000 Ilha Solteira SP Brazil Sao Paulo State Univ UNESP Dept Energy Engn BR-19274000 Rosana SP Brazil

Faults in power distribution feeders cause damage to power utilities due to the deterioration of reliability and power quality indexes and the displacement of field maintenance teams to replace or repair power grid equipment. Additionally, consumer units have energy supply interruptions for an undetermined time. Studies in specialized literature usually detect, classify, and locate faults after they occur. In contrast, preventing faults by estimating areas vulnerable to them is crucial to mitigate all inconveniences and additional costs after they occur. Tree vegetation is an essential factor contributing to faults. In this sense, an enhanced method for tree vegetation mapping by areas is developed using multilayer perceptron neural networks trained on high-resolution images from Google Earth. A geographic space is incorporated to estimate the regions vulnerable to failures due to tree vegetation. Geographically weighted spatial analysis is applied from local variables aggregated by areas. spatial data analysis is used to real faults and tree vegetation data from a medium-sized Brazilian city via QGIS and R programming environments. As a result, thematic maps are produced with the areas whose feeders are vulnerable to faults, where there is a moderate positive correlation by regions between the faults in distribution transformers and tree vegetation in the northeast and southwest areas of the city under study.

关键词： exploratory spatial data analysis power distribution systems spatial data analysis steady-state fault

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The temporal and spatial evolution of green finance and carbon emissions in the Pearl River Delta region: An analysis of impact pathways

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JOURNAL OF CLEANER PRODUCTION 2024年 446卷

作者： Wang, Congqi Liu, Pengzhen Ibrahim, Haslindar Yuan, Ruixi Univ Sains Malaysia Sch Management George Town 11800 Malaysia Jinan Univ Sch Econ Guangzhou 510632 Peoples R China

The issue of carbon emissions has become increasingly urgent in tandem with the rapid growth of the economy in the Pearl River Delta region. This paper uses kernel density estimation and standard deviation ellipses based on Pearl River Delta data from 2012 to 2021 to explore the spatiotemporal evolution trends of green financing and carbon emissions. Additionally, it uses a spatial Durbin model to examine the spatial effects of green finance on carbon emissions. The results indicate the following: Firstly, over the years, green finance shows an overall increasing trend, with an internal spatial pattern characterized by higher levels in the northeast and lower levels in the southwest. In contrast, carbon emissions are decreasing, with an internal spatial pattern characterized by higher levels in the southwest and lower levels in the northeast. Secondly, more and more green financing initiatives are aiming towards the Pearl River Delta's northeast, suggesting a more significant concentration of such initiatives there than elsewhere. At the same time, carbon emissions seem to converge on the southwest of the Pearl River Delta, which could indicate that this area generally has greater carbon emission levels. Finally, the spatial effect results reveal that improving green finance levels can significantly inhibit carbon emission levels in the Pearl River Delta region. Evidence of spatial spillover effects indicates that the carbon emissions in neighboring areas are influenced to some extent. This study on green finance and carbon emissions' spatiotemporal characteristics and spatial impact gives a development path and theoretical support for sustainable development goals in the global economy.

关键词： Pearl River Delta Green finance Carbon emissions exploratory spatial data analysis spatial spillover effects

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