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Housing infrastructure is the basic need for people of a community and due to disaster many houses may severaly damaged. Stakeholders and decision makers should focus on this issue and make the infrastructure more resilient against natural hazards. As dependency plays a very important role in resilience, it is important to study the dependencies and correlations among the housing infrastructure resilience factors. The evaluation of dependencies involve vagueness due to subjective judgement of experts.

In this work, the interaction between the housing infrastructure resilience factors are evaluated by using two different approaches such as crisp DEMATEL (Decision-Making and Trial Evaluation Laboratory) and rough DEMATEL (intregated crisp DEMATEL and rough set theory), where rough theory addressed the involvement of vagueness. These two approaches are compared with each other to find the effectiveness of rough DEMATEL over crisp DEMATEL.

The important factors of housing infrastructure resilience are identified by using both the approaches against flood hazard.

The limitation of rough DEMATEL method is that it does not differentiate the type of influence such as positive or negative.

The outcome of the work will helps the stakeholders and ecission makers to make the infrastructure more resilient.

This study identify the imporatnat resilience factors of housing infrastructure against flood hazard by using two methodologies.

Studies the concept of the Cartesian composition of fuzzy finite state machines. Shows that fuzzy finite state machines and their Cartesian composition share many structural properties. Some of these properties are singly generated; retrievability, connectedness, strong connectedness, commutativity, perfection and state independence. Thus a fuzzy finite state machine which is a Cartesian composition of submachines can be studied in terms of smaller machines.

Leadership in higher education has become of increasing importance as the size of the enterprise has grown, and this has naturally led to a growing research interest in the topic. Using systematic review methods, this chapter interrogates and synthesises the research literature on leadership in higher education in terms of its meanings, application and practice, and the issues and critiques raised. It concludes that research into leadership in higher education has been both extensive and global in nature, identifying a variety of understandings, practices and approaches adopted, and the continuing dominance of white men in senior leadership positions. There is clearly scope for more research on this topic, which could both emphasise different issues and give greater recognition to the particular nature of higher education and higher education institutions.

This chapter examines dynamic connectedness among emerging Asian equity markets as well as explores their linkages vis-à-vis other major global markets. We find that international equity markets are tightly integrated. Measuring connectedness based on a generalized Vector Autoregressive (VAR) model, more than half of all total forecast error variance in equity return and volatility shocks come from other markets as opposed to country own shocks. When examining the degree of connectedness over time, we find that international stock markets have become increasingly connected, with a gentle upward trend since the Asian financial crisis (AFC) but with a rapid burst during the global financial crisis (GFC). Despite the growing importance of Asian emerging markets in the world economy, we find that their influence on advanced economies are still relatively small, with no significant increase over time. During the past decade, advanced markets have been consistently net transmitters of shocks while emerging Asian markets act as net receivers. Based on the nature of equity shock spillovers, we also find that advanced countries are still tightly connected among themselves while intraregional connectedness within Asia remains strong. By investigating whether uncertainty plays an important role in explaining the degree of stock market connectedness, we find that economic policy uncertainty (EPU) from the US is an important source of financial shock spillover for the majority of international equity markets. In contrast, US financial market uncertainty as proxied by the VIX index drives equity market spillovers only among advanced economies.

A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to propose NBG-DEA model to measure the performance of decision-making units with complicated network structures.

As the proposed NBG-DEA model is a non-linear mathematical programming, finding its global optimum solution is hard. Therefore, meta-heuristic algorithms are used to solve non-linear optimization problems. Fortunately, the NBG-DEA model optimizes the well-formed problem, so that it can be solved by different non-linear methods including meta-heuristic algorithms. Hence, a meta-heuristic algorithm, called particle swarm optimization (PSO) is proposed to solve the NBG-DEA model in this paper. The case study is Industrial Management Institute (IMI), which is a leading organization in providing consulting management, publication and educational services in Iran. The sub-processes of IMI are considered as players where their pay-off is defined as the efficiency of sub-processes. The network structure of IMI is studied during multiple periods.

The proposed NBG-DEA model is applied to measure the efficiency scores in the IMI case study. The solution found by the PSO algorithm, which is implemented in MATLAB software, is compared with that generated by a classic non-linear method called gradient descent implemented in LINGO software.

The experiments proved that suitable and feasible solutions could be found by solving the NBG-DEA model and shows that PSO algorithm solves this model in reasonable central process unit time.

Due to large amounts of coal burning, huge carbon dioxide emission and poor environmental quality, it is important to identify whether environmental Kuznets curve exists in China and India since in downward period of environmental Kuznets curve, economic growth in these countries will largely contribute to world environmental quality. Further, it helps to make a comparative analysis between China and India on how economic growth will contribute to the environmental quality in both upward and downward period of environmental Kuznets curve due to energy consumption.

This study uses the data of carbon dioxide emission, per capita GDP and energy consumption from 1972 to 2017 to identify individual and panel-level environmental Kuznets curve of China and India. Before going to regression and causality analysis, unit root and cointegration tests are performed.

This study finds the existence of environmental Kuznets curve in China and India at both individual and panel level. Further, due to high energy consumption, environmental quality in China will deteriorate at a lower rate in the long run than that of India. Next, the increase in economic growth or per capita GDP in the long run will deteriorate environmental quality at a lower rate in China than that of India. Besides, with the zero level of energy consumption and per capita GDP, the environmental quality of China will be worse than that of India. However, increase in per capita GDP after threshold level will improve environmental quality in India at a higher rate than that of China.

It helps to formalize the comparative relationship between the two large Asian economies by knowing the influence of economic growth on environmental degradation due to energy consumption. However, this study cannot conclude exactly when China and India can avail the downturn in environmental Kuznets curve.

It firstly establishes a link among energy consumption, economic growth and environmental quality between China and India including comparative pace in both upward and downward period of environmental Kuznets curve.

In this paper, we define and examine the concept of a fuzzy recognizer. If L(M) is the language recognized by an incomplete fuzzy recognizer M, we show that there is a completion M of M such that L(M) = L(M). We also show that if A is a recognizable set of words, then there is a complete accessible fuzzy recognizer M_A such that L(M_A) = A. We lay groundwork to determine rational decompositions of recognizable sets.

This study aims to identify the critical barriers to women’s leadership in Indian corporate sector using the interpretive structural modeling (ISM) approach.

Through data obtained from extant literature and the expert opinion of women seeking higher managerial positions in the Indian corporate sector, this study identified total 18 barriers to women’s leadership. Thereafter, this study used the Delphi technique to identify the most critical barriers and ISM to understand the causal relationship among them, and then ranked them based on relevance.

Of the 13 critical barriers identified, corporate policies, conscious organizational bias and family responsibilities had the highest driving power. By contrast, inadequate career opportunities and the lack of risk-taking ability and assertiveness had the highest dependence power. Unconscious organizational bias and occupational segregation were other prominent barriers.

This study establishes the interrelationships between women’s leadership barriers. It provides a well-defined model which helps to get theoretical insight considering barriers for women leaders in their career progression in the Indian context. Based on the ISM model, these findings can help academicians and researchers gain deep insights into the barriers to women’s leadership in the Indian context, as no studies have been found in the literature concerning the given subject.

Based on the findings, corporations and policymakers can design inclusive leadership policies to support women as they climb the corporate ladder and to enhance their contribution to organizational success.

To the best of the authors’ knowledge, this is the first study to identify barriers to women’s leadership in India using ISM analysis.

Presents fundamental results on fuzzy Mealy machines. Unlike the classical Mealy machine which requires two functions, one to describe the next state and another to describe the output, a fuzzy Mealy machine requires only one fuzzy function to characterize completely the next state and the output produced. Apart from the obvious generalization that can be obtained from corresponding results on fuzzy finite state machines by introduction of an output associated with each transition, introduces the concept of an interval partition of [0, 1] and uses it to obtain more general results.

Academic and popular commentators of Asia find it almost impossible not to reach for metaphors of breathtaking economic and social change, fanned by the winds of globalization. This chapter explores the extent to which young Asian values concerning gender relations in the household, pornography and prostitution are similar to or different from those of young westerners. While some respondents themselves talk of the impact of globalization on attitudes in their countries, clear differences in attitudes as well as vocabularies or justifications for those attitudes are found, the Asian samples, usually but not always, expressing a different set of responses from the Anglophone or Western samples.