Nowadays, the web increasingly influences retail sales. An in-depth analysis of consumer decision-making in the context of e-business has become an important issue for internet vendors. However, factors affecting e-business are complicated and intertwined. To stimulate online sales, understanding key influential factors and causal relationships among the factors is important. To gain more insights into this issue, this paper introduces a hybrid method, which combines the Decision Making Trial and Evaluation Laboratory (DEMATEL) with the analytic network process, called DANP method, to find out the driving factors that influence the online business mostly. By DEMATEL approach the causal graph showed that “online service” dimension has the highest degree of direct impact on other dimensions; thus, the internet vendor is suggested to made strong efforts on service quality throughout the online shopping process. In addition, the study adopted DANP to measure the importance of key factors, among which “transaction security” proves to be the most important criterion. Hence, transaction security should be treated with top priority to boost the online businesses. From our study with DANP approach, the comprehensive information can be visually detected so that the decision makers can spotlight on the root causes to develop effectual actions.

Under the rapid change of the global financial environment, the risk control of the credit granting is viewed as the foremost task to each bank. With the impact one by one from financial crisis and European debt crisis, the steady bank business is also facing the severe challenge. Banks approve the credits for their customers and then make money from the interest. Credit granting is not only the primary job but also the main source of income. The quality of credit granting concerns not just the reclaims of creditor’s rights; it also affects the successful running of banks. To enhance the reliability and usefulness of bank credit risk assessment, we first will delve in the facets and indexes in the bank credit risk assessment. Then, we will examine the different dimensions of cause–effect relationships and correlations in the assessment process. Finally, the study focuses on how to raise the functions and benefits of the bank credit risk assessment. In those five credit risk evaluation dimensions, A “optional capability” and D “competitiveness” are of high relation and high prominence among those dimensions, influencing other items obviously. By actively focusing on these two dimensions and improving their credit risk assessment ability will solve the foremost problems and also solve other facets of credit risk assessment problems at the same time.

Financial supervision means that monetary authorities have the power to supervise and manage financial institutions according to laws. Monetary authorities have this power because of the requirements of improving financial services, protecting the rights of depositors, adapting to industrial development, ensuring financial fair trade, and maintaining stable financial order. To establish evaluation criteria for bank supervision in China, this study integrated fuzzy theory and the decision making trial and evaluation laboratory (DEMATEL) and proposes a fuzzy-DEMATEL model. First, fuzzy theory was applied to examine bank supervision criteria and analyze fuzzy semantics. Second, the fuzzy-DEMATEL model was used to calculate the degree to which financial supervision criteria mutually influenced one another and their causal relationship. Finally, an evaluation criteria model for evaluating bank and financial supervision was established.

It is necessary to promote harmony between the economic growth of tourism and the resource environment to achieve the green and sustainable development of China’s tourism industry. The research objects were taken in 30 provinces and cities in China. The green innovation efficiency of tourism is measured and evaluated based on the super-efficient SBM model and Moran index. The spatial and temporal heterogeneity of the influencing factors of green innovation efficiency is analyzed using the GWR model. The study shows that: (1) The level of green innovation efficiency of the tourism industry as a whole keeps improving during the study period, but the development is uneven among eastern, central, and western provinces. (2) The spatial correlation of the green innovation efficiency of the tourism industry in 30 provinces and cities keeps getting closer and closer, and some regions show the characteristics of spatial aggregation. (3) The green innovation efficiency of the tourism industry is affected by various factors, such as the level of economic development and the level of professional development of the tourism industry. (4) Tourism green innovation efficiency is influenced by various factors, such as economic development level and tourism professional development level, and there are apparent intensity differences and spatial heterogeneity among various influencing factors. Finally, reasonable countermeasures are proposed to promote the overall improvement and balanced development of green innovation efficiency in China’s tourism industry.