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Using the modified theory of planned behavior, this study aims to understand residents’ supporting or rejecting mindsets toward legalizing gambling in Kinmen, Taiwan, where exists a complex and somewhat contradictory relationships between economic growth and the preservation of the natural environment in the context of tourism specifically to small island destinations. This study develops a convenience sampling procedure in which 365 questionnaires are collected. A series of hypotheses tests are conducted via structural equation modeling. This study notices that perceived behavioral control is the most important attribute affecting behavioral intention. However, behavioral intention does not necessarily lead to actual behavior. Attitude is considered as a more reliable predictor of actual action. Attitude relied heavily on positive perceived behavioral control. Further, the respondents are concerned more about how legalizing gambling affects their current lifestyle.

In this chapter, we estimate the Expected Shortfall (ES) in conditional autoregressive expectile models by using a nonparametric multiple expectile regression via gradient tree boosting. This approach has the advantages generated by the flexibility of not having to rely on data assumptions and avoids the drawbacks and fragilities of a restrictive estimator such as Historical Simulation. We consider distinct specifications for the information sets that produce the ES estimates. The results obtained with simulated and real market data indicate that the proposed approach has good performance, with some distinctions between the specifications.

This chapter aims to help librarians understand the underlying rationale for Resource Description and Access (RDA) and recognize the great potential of the Semantic Web for libraries.

It explains the linked data model and Semantic Web technologies in basic, informative terms, and describes how the Semantic Web is constructed. Semantic Web standards and technologies are discussed in detail, including URI, RDF, and ontologies. The study also traces the development of RDA and some of the major library Semantic Web projects. The authors explore how RDA shapes bibliographical data and prepares it for linked data in the Semantic Web. In addition, this study examines what libraries in the United States and the rest of the world have achieved in implementing RDA since its release.

RDA is the correct approach libraries should take.

This is the first and only chapter that covers the development of RDA in other countries as well as in the United States. It is highly informative for anyone who wishes to understand the RDA and Semantic Web and their relevance to libraries in a short period of time.

Introduction: India has the 15th-largest domestic natural gas consumption (NGC), critical to sustainable economic growth. Promoting natural gas will have a crucial impact on production in all industries.

Purpose: This research gives an overview of NGC and gross domestic product (GDP) in India from 1990 to 2021 and investigates the association and nature of causality between NGC and GDP in India.

Methodology: For the years 1990 through 2021, we used annual statistics from the NGC and the GDP of India. Both research variables data have been taken from the World Bank Indicator.

Findings: There is no causality and correlation between natural gas and GDP in India.

Practical Implications: Based on the research, the Government of India can create different policies for substituting natural gas for other energy sources to have a healthier impact on a sustainable environment in the short and long term. In the future, researchers can work on environmental degradation and GDP.

Purpose: The advent of the fintech revolution has brought a tremendous increase in the dissemination of digital financial services. Although digital financial services increase financial inclusion through financial intermediation, it also increases the chances of systematic risk.

Need: In the quest to satisfy the curious minds, the authors have examined the influence of digital financial services on banking stability and efficiency.

Methodology: To achieve the above objectives, the authors have used the Auto-Regressive Distribution Lag (ARDL) estimation technique on the annual data set of India and the United States from 2004 to 2018. In addition, to estimate the long-run cointegration, the ARDL bound approach is also used.

Findings: The empirical analysis concludes that in the short run, the expansion of digital financial services in India in the form of internet-based transactions and mobile money transactions creates a negative and significant impact on banking efficiency and stability. Meaning, banking sector efficiency and stability fall by 0.09% and 0.05% with a 1% increase in digital financial services. However, in the long run, digital financial services enhance banking stability and efficiency in India. Besides, the study also reveals that in a developed country like the United States, both in the short run and long run, expansion of digital financial services helps in improving banking efficiency and stability. Furthermore, in context to control variables, the findings suggest that in the short run, industrial productivity has a negative influence on the Indian banking sector efficiency and stability, compared to the positive impact in the long run. This is unlike the United States, where both in the long-run and short-run, industrial productivity has a positive influence on the banking sector’s efficiency and stability.

Practical implication: The findings reveal several policy implications and suggest policy synergies between digital financial services, banking stability and efficiency.

Based on government data from 1993 to 2008, this chapter aims to compute and analyze the trends of inequity in interprovincial and regional per-student spending in China's compulsory education, and to ascertain the potential impact of changes in education financing policies. Appropriate inequity measures (Gini and Theil index and Gini decomposition, among others) are employed to provide a systematic picture of the trends. Main findings include: (1) all inequity measures show large and overall increased disparities among provinces and among regions, between 1993 and 2008. (2) However, a slight drop of spending inequity is observed at the primary education level around 2002 and a larger reduction in 2005 and on. There are more turning points in the trend of lower-secondary per-student spending among provinces. These patterns are consistent across different inequity measures and spending indicators (per-student total spending, per-student recurrent spending, and per-student nonpersonnel spending). (3) The trend toward more balanced resource allocation around 2002 and 2005 could be the impact from the Reform of Tax and Administrative Charges and the New Mechanism for Financing Rural Compulsory Education. An increased share of budgetary expenditure in determining total spending suggests that equalizing financing policies have the potential to induce a significant reduction in spending inequity. These findings may help policy makers to better understand and alter the extent of spending inequity in compulsory education. This is an original empirical study that systematically derives the spending inequity trends over a long period in China's compulsory education.