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This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

As a consequence of the huge loss and damage caused by natural disasters all over the world, an impressive amount of attention is currently being given to a holistic approach in disaster risk management (McEntire, Fuller, Johnston, & Weber, 2002). The world experiences more and more natural disaster impacts in spite of numerous efforts, advancing sciences, and more powerful technologies. Indeed, current disasters are more complex, and climate change poses a greater potential for adverse impacts (Aalst & Burton 2002). Hence, there is a need to reassess the existing disaster risk reduction approaches due to problems in the existing risk management approaches, and new risks brought by climate change and by environment degradation.

Purpose: To explore emotional support, daily housework assistance, and economic support for older adults provided by the Vietnamese family within the context of the impacts of socio-economic, demographic, and other factors.

Methodology: (1) The researchers used data from censuses taken from 1989 to 2019; national surveys of Internal Migration, Labor and Employment and other topics; and recent large sample sociological surveys (2) adapted a modified Diamond Care Model (Ochiai, 2009) to analyze effects of the characteristics of older adults; and of the country’s laws, policies, and socio-economic changes, on the families’ caregiving activities supporting the older adults.

Findings: The family is still the most important institution providing care for older adults in Viet Nam. Most older people live with their children and see this as an age-old security solution despite differences related to lifestyles and interests. However, when the average number of working-age people per older person decreases, as older adults live longer, household sizes are smaller, and there is increased large migration, the demand for non-family caregiving for older adults will increase. Since social services to help meet this demand are limited, the traditional family support system for the elderly in Viet Nam will face many challenges as families try to assure the quality of care needed in the very near future.

Value: This chapter shows systematically a relationship between elderly care in the Vietnamese family and socio-economic, demographic, and associated factors based on comprehensive data sources. The results can help us think about how to create an appropriate future model for taking care of older adults in Viet Nam that combines the efforts of families and the support of comprehensive social policies by the community.