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After the global financial crisis, many countries deregulated their banking sectors. The banking sector has become the major funding supplier in most emerging countries. Bank in Indonesia has provided an essential role as an intermediary institution in matching up surplus and deficit parties with a relatively concentrated market structure. Moreover, banks should innovate and diversify to provide excellent products and services to their customers and win the market. More diversified banks are expected to have better performance and more resilience, especially during a crisis. This study examines the relationship among bank market power, diversification, and bank stability of listed bank companies in Indonesia from 2008 to 2020. This study employs a two-step system GMM to deal with potential endogeneity. This study finds that banks’ market power and diversification affect bank stability, and the presence of crisis encourages banks to be more prudent. The result of this study provides insightful implications for academics and policy-makers.

This chapter examines the impact of macroeconomic factors on the financial performance of Chinese companies. Using multiple regression analysis, the study finds that gross domestic product (GDP) growth rate, inflation rate, interest rate, exchange rate, and government expenditure are significant predictors of the financial performance of Chinese companies. The results show that GDP growth rate, leverage, size, liquidity, profitability, and growth in sales all have significant positive impacts on financial performance, while growth in assets has a negative impact. The study provides insights into the impact of macroeconomic factors on the financial performance of Chinese companies. Policymakers and investors should take these findings into account when making decisions about economic policies and investments, and companies operating in China should be aware of the potential impact of these factors on their financial performance and look for ways to manage them effectively. The chapter also includes a model specification test and a robustness test to validate the accuracy of the results. The findings have important guiding significance for policy makers and investors in making economic policies and investment decisions. However, the study has limitations such as the use of horizontal panel data and the limited data sources used.

Road transport networks might face the most significant transformation in the following decades, mostly due to the anticipated introduction of Connected and Automated Vehicles (CAVs). The introduction of connectivity and automation will be realised gradually. There are distinctive levels of automation starting from single-dimension automated functionalities, such as regulating the vehicle’s longitudinal behaviour via Adaptive Cruise Control (ACC) systems. Although the technological readiness level is undeniably far from full vehicle automation, there are already commercially available lower-level automated vehicles. The penetration rate of vehicles equipped with Advanced Driver Assistance Systems (ADAS) such as ACC or Cooperative-ACC is constantly increasing bringing new driving behaviours into existing infrastructure, especially on motorways. Lately, several experiments have been conducted with platoons of ACC and CACC-equipped vehicles aiming to study the characteristics and properties of the traffic flow composed by them. This chapter aims to gather the most significant efforts on the topic and present the recent status of research and policy. The impact analysis presented within this chapter is multi-dimensional spanning from traffic flow oscillations and string stability, traffic safety to driving behaviour, energy consumption, and policy, all factors where automation has the potential to contribute to a more sustainable transport system. Investigations through analytical approaches and simulation studies are discussed as well, in comparison to empirical insights, attempting to generalise experimental conclusions. At the end of this chapter, the reader should have a clear view of the existing and potential benefits of CAVs but also the existing and future challenges they can bring.

In this study, we develop understanding of factors that shape the propensity of market incumbents to collaborate in response to the threat posed by new market entrants. We are particularly interested in instances when a market's competitive structure becomes unsettled by new entrants who engage in nonconforming strategic tactics. In such situations, we propose two factors – strategic similarity among competitors and market-share instability – will systematically shape competitors' collaborative response to new entrants. To test our theory, we use data on strategic tactics and collaborative dynamics in the US airline industry from 1989 to 2010. We demonstrate that greater strategic similarity among a market's incumbents increases the likelihood of cooperation in response to the threat of a nonconforming new entrant, while greater market-share instability reduces cooperative response. Through this study, we extend existing understanding of the contextual circumstances under which established competitors recognize their mutual interests and band together.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

The objective of this chapter is to discuss how different techniques in Regional Science and Peace Science and the emerging techniques in Management Science can be used in analysing Disaster Management and Global pandemic with special reference to developing countries. It is necessary for me to first discuss the subjects of Disaster Management, Regional Science, Peace Science and Management Science. The objective of this chapter is to emphasise that the studies of Disaster Management should be more integrated with socioeconomic and geographical factors. The greatest disaster facing the world is the possibility of war, particularly nuclear war, and the preparation of the means of destruction through military spending.

We evaluate the hypothesis of temporal stability in risk preferences using two recent data sets from longitudinal lab experiments. Both experiments included a combination of decision tasks that allows one to identify a full set of structural parameters characterizing risk preferences under Cumulative Prospect Theory (CPT), including loss aversion. We consider temporal stability in those structural parameters at both population and individual levels. The population-level stability pertains to whether the distribution of risk preferences across individuals in the subject population remains stable over time. The individual-level stability pertains to within-individual correlation in risk preferences over time. We embed the CPT structure in a random coefficient model that allows us to evaluate temporal stability at both levels in a coherent manner, without having to switch between different sets of models to draw inferences at a specific level.

This chapter explores the influence of the banking and insurance sectors on the economic growth of Czechia, a nation with unique financial dynamics ideal for this study. Our aim is to ascertain the contribution of these financial institutions to economic growth, addressing the divergence in empirical findings that have marked this research area for decades. We scrutinise the impact of various factors, including sectoral development and the efficiency and stability of these institutions, all within the Czech context. Utilising the Granger causality test, we assess the role of several indicators related to the development of the banking and insurance sectors. Our findings reveal that in Czechia, the evolution and operational efficiency of these financial institutions significantly drive economic growth. This study provides an in-depth understanding of the role these sectors play in the Czech economic landscape, affirming their crucial contribution to the nation's economic prosperity.