Wenting Zhang – författare

This book proposes a method to solve land use problems, and has made some significant contributions to the land use analysis and optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatiotemporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model.

Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China.

This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.

This book proposes a method to solve land use problems, and has made some significant contributions to the land use analysis and optimization study fields. Firstly, three spatio-temporal logit models for land use change analysis, namely, geographically and temporally weighted logit model (GTWLM), spatio-temporal panel logit model (ST-PLM) and generalized spatio-temporal logit model (GSTLM), are proposed. GTWLM, which considers spatio-temporal non-stationarity, includes temporal data in a spatio-temporal framework by proposing a spatiotemporal distance. ST-PLM incorporates the spatio-temporal correlation and individual effect in one model. By integrating GTWLM and ST-PLM, the GSTLM explores spatio-temporal non-stationarity and correlations simultaneously, whilst considering their individual effects to construct an integrated model.

Secondly, a MOO-based two-level spatial planning of land use is proposed. The spatial planning aims at managing and coordinating the land use at different geographic extents and involves spatial layouts and structures of land use at different levels. In spatial planning, GIS and Remote Sensing are used to evaluate, analyze, and measure environmental, economic and social issues. The quantitative relationships between these objectives and spatial land use allocation are then used as rules in the MOO process to simulate environmental conditions under different spatial land use allocation scenarios. The book features a case study of Shenzhen city, the most important Special Economic Zone in China.

This book will be of interest to academics and professionals in the fields of urban planning, land resource management, remote sensing and geographic information systems.

This book introduces environmental, social and governance (ESG) investment and clarifies its characteristics as financial securities. It is forecasted that companies’ ESG information will be reflected in their corporate value as much as their financial information is in the future. The special feature of this book is to reveal the characteristics and impact of ESG investment using various quantitative analyses (e.g. EGARCH, asymmetric DCC, copula, VaR, connectedness, dynamic spillover). This book focuses on the relationship between some ESG indexes and the other economic variables, particularly in light of the recent economic environment (e.g. Global Financial Crisis, COIVID-19 pandemic, crude oil price crash). Readers can grasp a larger picture of ESG investment through a survey of its history and current status, predictions of its future, and interpretation of various empirical analysis results. 

This book starts by introducing the background of the era of data elements, clarifies the theoretical basis and technical methods related to big data, and analyzes the specific application of big data technology in China’s banking industry, the insurance industry, securities investment industry, third-party payment, risk supervision, and other fields. application, and thereby finally summarize useful experiences for big data development as well as effective regulation and supervision. We hope that this book can help with subsequent research and application of big data technology in the financial field. This book has a broad audience, especially scholars and practitioners. It is a valuable reference for researchers in related fields, and it can also provide some insights into financial regulators’ awareness of big data finance. Furthermore, it aids in formulating and improving consumption policies, adjusting economic structures, and preventing risks under financial innovation. This research provides valuable guidance for improving financial innovation as well as the effective regulation thereon by financial regulators.

This book aims to provide first-hand information for readers who are concerned about inclusive finance and sustainable development by summarizing China’s policy measures and practical innovations in the development of inclusive finance and expects to provide China’s experience for the development of inclusive finance in more regions. From a worldwide perspective, a large number of people had been excluded from formal financial services for a long time due to various factors. Even in developed economies with sound financial systems, relatively disadvantaged groups are often denied access to effective financial services. In 2005, the United Nations proposed the concept of Inclusive Finance, emphasizing the extension of financial services to less developed regions and low-income groups in society at an affordable cost by improving financial infrastructure and providing them with reasonably priced and convenient financial services. In 2015, the United Nations adopted the 2030 Agenda forSustainable Development, making inclusive finance an important focus for achieving sustainable development. It has become a global consensus to vigorously develop inclusive finance.

China has attached importance to improving financial services for disadvantaged groups such as rural residents, micro-, small and medium enterprises (MSMEs) and others. In 2013, Developing “Inclusive Finance” became China’s national strategy. In 2015, China formulated the Plan for Promoting the Development of Inclusive Finance (2016-2020). In 2016, during its presidency of the Global Partnership for Financial Inclusion (GPFI), China proposed the issue of "Digital Financial Inclusion" and issued the G20 High-level Principles for Digital Financial Inclusion at the G20 Hangzhou Summit in the same year. Through policy guidance and active practice by the financial sector, China has gradually formed a unique development model of inclusive finance and achieved remarkable successes. Physical outlets, service machines and online service channels have been improved, and basic financial services have generally covered both urban and rural areas. The financial services for rural households and MSMEs have improved significantly. The efficiency and convenience of financial services have been significantly improved, and the satisfaction of financial services has significantly increased. China''s experience in inclusive finance has been recognized by the international community. In 2017, five cases from China were selected in the G20 report on Digital Financial Inclusion: Emerging Policy Approaches.