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South Africa is in the last stage of the first demographic transition (FDT) – yet already depicts aspects of the second transition. The last stage of the FDT is characterized by lower levels of fertility closer to or at the replacement level of the average of 2.1 children per woman, and improvements in mortality displayed by declining infant and childhood mortality leading to increasing life expectancy at birth. The second demographic transition (SDT) is driven by lifestyle changes that are determinants of demographic patterns. Such lifestyle changes are declining marriage rates, increasing attention on human development, and thus changing family formation patterns. South Africa’s youth are at the centre of this transition. The population census of 2011 shows an age structure of South Africa that is characterized by a larger proportion of 20-35-year-olds. This resulted from a long period of declining fertility and to some extent improvements in mortality at all ages. This age structure, with adequate investments - is expected to yield a period of economic growth resulting from a reduced dependency ratio. However, improved health care, investments in human development, and higher employment opportunities are required to harness the benefit. This chapter aims to explore the national and provincial preparedness of South African youth to contribute to economic growth of the country. In particular, the chapter will focus on demographic factors such as sex ratio; youth mortality and morbidity; and youth fertility levels as these factors are highly correlated with human development.

This paper aims to unpack the nexus of development and demography controlling for three important variables to represent the meaning of development, that is, poverty rate, unemployment rate and human development index (HDI). Demographic variables are proxied with total fertility rate (TFR) and net migration rate (NMR).

This research applies cluster analysis at the provincial level using INDO-DAPOER and 2015 Intercensal Population Survey data sets.

Demographic and development status of Indonesian provinces can be classified into four clusters, and members of these clusters are mostly dissimilar with those of previous groupings on demographic dividends (Adioetomo, 2018). With only less than 50% matching rate, the author argues that there is no simple linear relationship between demographic and development variables.

The most recent data set on Population Census Year 2020 has not been made available at the time of the writing. Also sometimes known as unsupervised classification, cluster analysis is about finding groups in a set of objects characterised only by certain measurements; therefore, findings of this study need to be positioned solely within the context of development and demography.

Taxonomy in this study offers a more nuanced and contextual understanding of the diverse challenges at the local and regional levels. Recommendations from this study lead to asymmetrical design in development policies and budget proportions at local levels.

It is expected that the findings are relevant to the input of policymaking process within the sphere of development and demography, especially for countries with significant size of populations and grappling with development issues.

To the author’s understanding, this paper is the first to discuss the impact of “demographic dividend” to economic development in Indonesia using the approach of cluster analysis. The expected contribution of this work is twofold: Firstly, the author would like to ignite a discourse on the nexus of development and demography using the most recent data set and cutting-edge method. Secondly, the findings are relevant to the input of policymaking process within the sphere of development and demography, especially for countries with significant size of populations and grappling with development issues.

This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value.

Multi-level modelling (MLM) method is used to develop the house price forecasting models. The neighbourhood effects, that is, socio-economic conditions that exist in various locations, are included in this study. Data from the local government area in Greater Sydney, Australia, has been collected to test the developed model.

Results show that the multi-level models can account for the neighbourhood effects and provide accurate forecasting results.

It is believed that the impacts on specific households may be different because of the price differences in various geographic areas. The “neighbourhood” is an important consideration in housing purchase decisions.

While increasing housing supply provisions to match the housing demand, governments may consider improving the quality of neighbourhood conditions such as transportation, surrounding environment and public space security.

The demand and supply of housing in different locations have not behaved uniformly over time, that is, they demonstrate spatial heterogeneity. The use of MLM extends the standard hedonic model to incorporate physical characteristics and socio-economic variables to estimate dwelling prices.

This chapter focuses on the heterogeneous pathways (including marital and cohabiting union and parenting histories) through which people navigate their family life courses from adolescence through mid-life, and their implications for union dissolution in middle and later life. The analyses draw on data (retrospective, cross-sectional) from the 2011 and 2017 Canadian General Social Surveys. The study sample includes individuals aged 50 and over (n = 14,547) who were in a union at age 50. Sequence analyses are used to identify the most common family life course trajectories among these individuals from adolescence through midlife (ages 15–50). Logistic regression analyses then address the implications of these trajectories for union dissolution in middle and later life (ages 50+). The results reveal four main family trajectories that characterize the earlier years of the adult life course: married with children, cohabiting with children, single or cohabiting without children, and married without children. These family trajectories, together with their level of complexity, play an important role in relation to both marital and cohabiting union dissolution outcomes in later life.

This research aims to better understand the Zillennial Generation within the workplace, specifically using the perspectives of Business Stakeholders within the context of Northern Ireland. Understanding the perceptions of Zillennials in the workplace is important due to their growing numbers and subsequent impact on the future of work.

A case study approach is used to gain a deeper understanding of stakeholder opinions and experiences of Zillennials. The authors draw on extant research and use semi-structured interviews to explore the experiences and views of stakeholders within three case firms employing Zillennials.

The study concludes that discrepancies can be seen between Zillennial performance and behaviour, compared with Business Stakeholder workplace expectations. Findings suggest that according to Business Stakeholders observations, Zillennials display some, but not all, attributes of Generation Z and Millennials. Business Stakeholders observations also reveal that Zillennials demonstrate some, but not all, entrepreneurial behaviours and competencies.

While many studies focus on both Generation Z and Millennials, research focused on unique cusp generations is limited. No research has been conducted that investigates the perception of Zillennials within the context of Northern Ireland.

The penetration of technology and the strengthening of evidence-based policies have paved the way for the automated delivery of social services. This study aims to discuss the inherent risks of this automatization, particularly those associated with the discrimination, exclusion and inequality problem, which the authors package under the theoretical umbrella of a digital welfare state (DWS).

This conceptual article reviews the literature on the welfare DWS, with an empirical focus on the recent experience of selected countries from India, Kenya and Sweden. These countries reflect three different types of welfare regimes but are connected by the same digital social risk. The authors’ exploration also includes questions about what this DWS has in common with and how it differs from the previous era. This article illustrates that there has been a very similar trajectory in regards to the development of the DWS and the associated risks in the examined countries.

DWS has triggered new social risks (e.g. discrimination, exclusion and inequality in welfare access) that are a result of data breaches experienced by citizens. Further, vulnerable groups in the digital age should be viewed not only as those who lack access to welfare services, such as education, health and employment, but also as those without internet access, without digital skills and excluded from the DWS system.

The article calls for the development of scholarly research into the DWS in particular and the contemporary one in general. The authors also predict that a critical aspect of the future regime typology rests in the ability to mobilize resources to address contemporary digital risks, as every country is equally vulnerable to them. Overall, this article can be considered to be one of the initial works that focus on cross-national comparison across different meta-welfare regimes.

PANK and PUNK are two acronyms for ‘Professional Aunt/Uncle with No Kids’. The former was created in 2007 by Melanie Notkin, a Canadian specialising in marketing, to refer to those women without children who are involved in raising their niece/nephews. They can be ‘by blood’, with whom they share family ties, or ‘by choice’, that is, sons and daughters of friends. A PANK or PUNK can be couples, singles or those who do not want to or cannot have child/children on their own but again who love children and want to spend time with them, so who spare special time to look after them, especially on a vacation time. They share some common characteristics such as helping the niece/nephew financially, influencing them, being well-connected and researchers, being devoted nesters, and enjoying travelling with their nieces and nephews while contributing to their personal developments.

Agricultural and food systems in the Mekong Region are undergoing transformations because of increasing engagement in international trade, alongside economic growth, dietary change and urbanisation. Food systems approaches are often used to understand these kinds of transformation processes, with particular strengths in linking social, economic and environmental dimensions of food at multiple scales. We argue that while the food systems approach strives to provide a comprehensive understanding of food production, consumption and environmental drivers, it is less well equipped to shed light on the role of actors, knowledge and power in transformation processes and on the divergent impacts and outcomes of these processes for different actors. We suggest that an approach that uses food systems as heuristics but complements it with attention to actors, knowledge and power improves our understanding of transformations such as those underway in the Mekong Region. The key transformations in the region include the emergence of regional food markets and vertically integrated supply chains that control increasing share of the market, increase in contract farming particularly in the peripheries of the region, replacement of crops cultivated for human consumption with corn grown for animal feed. These transformations are increasingly marginalising small-scale farmers, while at the same time, many other farmers increasingly pursue non-agricultural livelihoods. Food consumption is also changing, with integrated supply chains controlling substantial part of the mass market. Our analysis highlights that theoretical innovations grounded in political economy, agrarian change, development studies and rural livelihoods can help to increase theoretical depth of inquiries to accommodate the increasingly global dimensions of food. As a result, we map out a future research agenda to unpack the dynamic food system interactions and to unveil the social, economic and environmental impacts of these rapid transformations. We identify policy and managerial implications coupled with sustainable pathways for change.