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Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

The field of global leadership has flourished and advanced in the preceding decade. However, in contrast to the term global leadership, which enjoys conceptual clarity enabling accumulative progress, the construct of global leadership effectiveness is comparatively undertheorized, with instances of definitional ambiguity and disjointed methodological operationalizations across studies. The purpose of this chapter is, thus, to provide a systematic review of the global leadership effectiveness literature. In doing so, our contributions are fourfold. First, we offer an inclusive, comprehensive definition of global leadership effectiveness. Second, we map its construct domain. Third, we review research findings at the individual, group, and organizational levels. Finally, we integrate extant insights and offer suggestions for future research, organized within the typology of the content domain along the identified dimensions of global leadership effectiveness. Together, our goal is to build a foundation for future research examining the roles of leadership and the global context as antecedents of global leadership effectiveness.

Purpose: The main aim of the study is to provide a tool for non-financial information in decision-making. We analysed the non-financial data in the annual reports in order to show the usage of this information in financial decision processes.

Need for the Study: Main financial reports such as balance sheets and income statements can be analysed by statistical methods. However, an expanded financial reporting framework needs new analysing methods due to unstructured and big data. The study offers a solution to the analysis problem that comes with non-financial reporting, which is an essential communication tool in corporate reporting.

Methodology: Text mining analysis of annual reports is conducted using software named R. To simplify the problem, we try to predict the companies’ corporate governance qualifications using text mining. K Nearest Neighbor, Naive Bayes and Decision Tree machine learning algorithms were used.

Findings: Our analysis illustrates that K Nearest Neighbor has classified the highest number of correct classifications by 85%, compared to 50% for the random walk. The empirical evidence suggests that text mining can be used by all stakeholders as a financial analysis method.

Practical Implications: Combining financial statement analyses with financial reporting analyses will decrease the information asymmetry between the company and stakeholders. So stakeholders can make more accurate decisions. Analysis of non-financial data with text mining will provide a decisive competitive advantage, especially for investors to make the right decisions. This method will lead to allocating scarce resources more effectively. Another contribution of the study is that stakeholders can predict the corporate governance qualification of the company from the annual reports even if it does not include in the Corporate Governance Index (CGI).

Agency problems are more severe for multinational corporations (MNCs) and multinational enterprises compared to their domestic counterparts. As companies develop diversified operations, their managers face more challenges. An incentive compensation structure has been designed to align the benefits of managers with those of shareholders. Additionally, corporate social responsibility (CSR) has become increasingly crucial for companies. MNCs must gain the trust of more investors to improve their corporate reputation and financial performance. CSR enables MNCs with a high sense of social responsibility to expand their investor base, reduce perceived risks, and decrease information asymmetry. Our empirical findings reveal that Taiwanese MNCs can enhance their performance by implementing cash-based compensation and pursuing CSR activities.

This study focuses on examining the impact of energy consumption, economic structure, population, and manufacturing output on the CO₂ emissions of selected emerging countries by utilizing the Structural Time Series Model (STSM). Based on the annual data ranging from 1970 to 2019, the model is built up using total primary energy consumption, GDP per capita, population and manufacturing value-added, and, finally, a stochastic Underlying Emission Trend as explanatory variables. STSM is extended by the introduction of the notion of Underlying Energy Demand Trend (UEDT) as a factor for exogenous effects, including development in technical progress, energy efficiency improvements, changes in human behaviors, economy, and environmental regulations. In this context, STSM and the notion of UEDT are implemented to form a forecasting model for CO₂ emissions of the selected emerging countries. The model discovers the significant influences of all selected variables of CO₂ emissions. The results suggest that the most forceful factor in CO₂ emissions is the total primary energy supply. Furthermore, while the long-term impact of economic growth on CO₂ emissions is negative for some emerging economies, it is positive for several others. The model also measures the long-term manufacturing value-added elasticity of CO₂ emissions in these emerging economies.

Since March (1991) presented his ideas on organizational learning, hundreds of empirical tests have been conducted on relationships among the activities of exploration, exploitation, ambidexterity, and firm performance. Despite continued interest in his ideas, there has not been a systematic assessment of extant research to reveal whether, and to what extent, these activities relate to firm performance. This study uses meta-analysis to take a next step by aggregating results of 117 studies from more than 21,000 firms. I find strong performance effects for exploration and exploitation, but contrary to received theory, I discover ambidexterity yields weaker effects than a focus on either exploration or exploitation. Thus, I leverage these findings to offer future research opportunities.