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This article examines the determinants of fertility, using annual data sets from 1980 to 2017 for two major developed economies of the Asian region, namely Hong Kong (China) and South Korea. The article applies the non-linear autoregressive distributed lag model to study the impact of economic uncertainty on fertility decisions in these two countries. Using output volatility measure of economic uncertainty, the study shows that there is an asymmetric impact of economic uncertainty upon fertility decisions. Such an exploration demonstrates the extent of the impact of insecurity in the economy on fertility decisions. Furthermore, the study also explores the impact of infant mortality rate, old-age population, urbanization, income per capita, female employment levels, percentage of women in marriage or union, contraceptive prevalence and human capital formation on fertility decisions in these two advanced economies. The results confirm the asymmetry because the impact of the positive change of uncertainty and the impact of the negative change are not identical. The study concludes that for these major industrialized economies of Asia, economic uncertainty apart from the traditional demographic and economic factors appears to be a crucial factor in impacting fertility decisions.

PurposeThis paper aims to consider the role of geopolitical risk in explaining tourism demand in India, a major tourist destination of the Asian region. Furthermore, the study also considers how in addition to geopolitical risk, economic policy uncertainty, economic growth, exchange rate, inflation and trade openness impact tourism demand.Design/methodology/approachThe Bayer and Hanck (2013) method of cointegration is applied to explore the relationship between geopolitical risk and tourism demand. Furthermore, the study has also used the auto distributed lag model to determine whether there is a long-run cointegrating association between tourism demand, geopolitical risk, economic policy uncertainty, economic growth, exchange rate and trade openness. Finally, the vector error correction model confirms the direction of causality across the set of the major variables.FindingsThis paper finds that geopolitical risk adversely impacts inbound international travel to India. This study also obtains the consistency of the results across different estimation techniques controlling for important macro variables. The Granger causality test confirms the unidirectional causality from geopolitical risk to tourism and further from economic uncertainty to tourism. The findings from the study confirm that geopolitical risks have long-term repercussions on the tourism sector in India. The results indicate that there is an urgent need to develop a pre-crisis management plan to protect the aura of Indian tourism. The tourism business houses should develop skilful marketing strategies in the post-crisis to boost the confidence of the tourists.Research limitations/implicationsThis paper provides valuable practical implications to tourism business houses. The tourism business houses can explore geopolitical risk measure and economic policy uncertainty measure to analyse the demand for international tourism in India. Further, the major stakeholders can establish platforms to help tourists to overcome the fear associated with geopolitical risk.Originality/valueThis study is the first of its kind to explore the geopolitical risks and their long-run consequences in the context of tourism in India. The study puts emphasis on the role of national policy to maintain peace otherwise it would be detrimental to tourism.

PurposeThis study attempts to explore the determinants of tourism demand that impact tourist arrivals in Australia from Asia using an augmented panel gravity model.Design/methodology/approachThe augmented panel gravity model was utilised to analyse the demand for Australian tourism from 15 major countries of Asia over the period 1991 to 2018. Tourist arrivals were the dependent variable while per capita gross domestic product (GDP) and weighted distance were important explanatory variables. Further other indicators like population, money supply, globalisation, price index, exchange rate, uncertainty and two dummy variables were added as control variables.FindingsThe results demonstrate based on the novel methodology of Pesaran (2006), namely CCE (common correlated effects) that tourist arrivals are impacted positively and significantly by per capita GDP of both the country of origin and destination country, globalisation also impacts tourist flows positively. However, tourist arrivals are adversely affected by distance and prices confirming the economic theory.Originality/valueGravity models have been intensively used in the recent literature on tourism; however, this study has attempted to explore tourism demand from Asia into Australia which is indeed an unexplored area further the study has used the CCE methodology which takes care of the problems of cross-sectional dependence unlike the earlier methods widely used in the literature like the DOLS and the FMOLS. Last by utilising a wide-ranging set of macro factors the study contributes a novel assessment to the recent literature on tourism demand model.

"Smart City" programs and strategies have become one of the most dominant urban agendas for local governments worldwide in the past two decades. The rapid urbanization rate and unprecedented growth of megacities in the 21st century triggered drastic changes in traditional ways of urban policy and planning, leading to an influx of digital technology applications for fast and efficient urban management. With the rising popularity in making our cities "smart", several domains of urban management, urban infrastructure, and urban quality-of-life have seen increasing dependence on advanced information and communication technologies (ICTs) that optimize and control the day-to-day functioning of urban systems. Smart Cities, essentially, act as digital networks that obtain large-scale real-time data on urban systems, process them, and make decisions on how to manage them efficiently. The book presents 26 chapters, which are organized around five topics: (1) Conceptual framework for smart cities and communities; (2) Technical concepts and models for smart city and communities; (3) Civic engagement and citizen participation; (4) Case studies from the Global North; and (5) Case studies from the Global South

The practice of early marriage is deeply rooted in the socio-cultural structure and is well prevalent in rural India despite marriage-prohibiting laws. The paper examines happiness and psychological well-being and its influence by various aspects of marriage among young married women. Multistage sampling technique was used to interview 654 married women, 13-24 years in rural West Bengal. Mean age at marriage was found to be 16 years. One-third reported adjustment problem initially after marriage. Logistic regression analysis results showed marital happiness was positively influenced by less spousal difference in opinion; couple educational status, able to adjust marital problems and wish to have same life partner given an option of partner selection. No significant association was found between happiness and type of marriage and husband's currently staying with wife.