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This chapter shows how to construct and test case-based macro models. The chapter makes use of national data to examine influences on quality-of-life of national cultures as complex wholes and entrepreneurship activities in Brazil, Russia, India, China, Germany, and the United States (the six focal nations) plus Denmark (a small-size, economically developed, nation). The study tests McClelland’s (1961) and more recent scholars’ proposition that some cultural configurations nurture entrepreneur startups, while other cultures are biased toward thwarting startups. The study applies complexity theory to develop and empirically test a general theory of cultures’, entrepreneurship’s, and innovation’s impact on quality-of-life across nations. Because culture represents a complex whole of attitudes, beliefs, values, and behavior, the study applies a set-theoretic approach to theory development and testing of alternative cultural configurations. Each of 28 economical developed and developing nations is scored for the level of the national cultures for each of six focal countries. The study selected for the study enables multi-way comparisons of culture-entrepreneurship-innovation-QOL among large- and small-sized developing and developed nations. The findings graphically present the complex national cultural configuration (x-axis) with entrepreneur nurture/thwart (y-axis) of the 28 nations compared to the six focal nations. The findings also include recognizing national cultures (e.g., Switzerland, the United States) nurturing entrepreneurial behavior versus other national cultures (e.g., Brazil and India) thwarting entrepreneurial behavior. The study concludes with a call to recognize the implicit shift in culturally implicit thinking and behavior necessary for advancing national platforms designed to successfully nurture entrepreneurship. Entrepreneur strategy implications include the observation that actions nurturing firm start-ups by nations low in entrepreneurship will unlikely to be successful without reducing such nations’ high levels of corruption.

Below are summaries of some of the most cited works on amenities by economists. The review started with key recent works, such as those by Edward Glaeser et al., and worked back to major earlier works. Review articles were given preference, as they provide a summary of the field. Website addresses are available for many papers, to facilitate global access.

The purpose of this chapter is to examine the consequences of closing institutions for people with disabilities and accommodating them in Supported Residential Services. Issues that had been raised by an advocacy movement included shortcomings in privacy, dignity, control and meaningful activity in institutions, which led to their closure. The study applied a quality of life measurement which was commensurate with the ethical paradigms of welfare, autonomy and communitarianism to investigate whether community living in supported residences produced fulfilling lives and better outcomes than the institutions they replaced. Twenty-seven people with a disability and/or mental health issue in Supported Residential Services in Victoria, Australia were interviewed using the ‘Lehman Quality of Life Questionnaire’. An investigation into the Quality of Life of one group of de-institutionalised residents revealed that issues remain. People in the Supported Residences appear to be no better off than when they were in institutions. The study identified that it was common for a resident to have no phone, no friends outside the residence, little or no family contact, no disposable money and no job. However, since there was no research conducted before de-institutionalisation, the impact of the policy change is difficult to determine. Applying ethical measures, such as the Capabilities approach, reveals that issues remain. Practical implications from this study are first, that positive measures need to be added to de-institutionalisation to achieve satisfactory outcomes and second, that policy makers would be better informed and likely more effective if data were collected before and after significant changes.

Tokyo is the most populated urban area in the world, with a population of 36.5 million. The sheer number of people creates a wide variety of living environments for its residents to choose from. Using a questionnaire survey dataset with 4,120 respondents, this chapter examines the impacts of individuals’ attributes on their preferences to various quality of life (QOL) factors, as well as whether the actual choices of residential districts reflect their preferences.

Individuals’ attributes such as sex, age, marital status, the number and ages of children, and income affect the emphasis that they place on choosing a place to live. Although parents with school-aged or smaller children place a greater emphasis on childcare/school services, natural environment, public services, working communities, and moderate consumer price in local shops; young single white-collars tend to trade safety and environment for shorter commute and therefore select places high on access-related attributes.

For QOL factors such as the public transit, access to work, natural environment, and clean air/water, satisfaction levels show clear geographical patterns and access-related factors earn high scores in the city center, whereas the nature-related factors are higher in the suburb. In these attributes, correlation between city residents’ emphasis on these attributes and satisfaction scores are high, suggesting that people can successfully choose the place of living according to their emphases.

For other factors, such as childcare/education and other public services provided by the municipalities, residents’ preferences for, and the city's offerings are rarely aligned. One possible reason is that the information on the level and availability of these services is difficult for prospective residents to know. Therefore, public resources should be targeted to solve this mismatching problem through (1) raising the quality of services in areas where the need is prevalent but the satisfaction level is low and (2) providing more information on the level of services that each municipality is offering, to allow prospective residents to choose the right place that meets their need.

This chapter examines the associations between gender, social support, and health outcomes for individuals living with HIV disease. We include social integration and social isolation as structural measures of social support as well as perceived social support and social conflict as functional measures of social support. We include both mental health and physical health outcomes, which are too often studied in isolation of each other.

Data are from the Coping with HIV/AIDS in the Southeast (CHASE) study; this study reports on baseline data from 611 participants collected from 2001 to 2002. We first examined differences by gender and race, and then used blocked linear regression to determine the additive effects of the social support variables on both mental and physical health outcomes while controlling for potential confounders.

There were notable differences in the significance and strength of social support variables in health outcome models for men and women. Unlike men, social conflict was the strongest predictor of greater psychological distress and poorer physical health-related quality of life among women.

While the results from this study contribute to a greater understanding of gender differences in the relationships between social support and health outcomes, the data used for this study are limited to those living with HIV/AIDS in the Southeast.

Our findings suggest that social conflict may be more detrimental for the health of women than men.

Large regional disparities lead, among other things, to significant internal migration flows. Internal migrations, on the other hand, reinforce existing regional disparities by causing a lack of human capital in underdeveloped regions. In this chapter, we apply the Multiple Criteria Decision Aiding (MCDA) sorting method, ELECTRE Tri-C, to determine the current internal migration potential for districts in Serbia. The method will provide four classes of migration potential, ranging from strong emigration to strong immigration potential, based on the main drivers of internal migration. The main determinants of internal migration flows fall into three groups: (1) economic and labour market indicators, (2) demographic indicators and (3) housing market and amenities indicators.