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The conceptual framework of mathematical modeling (e.g., Lesh & Doerr, 2003) is a vital area in mathematics education research, and its implementation has potential for deeply involving children in integrated and meaningful learning. In mathematical modeling learners are active agents in content-integrated, real-world problem solving. This emphasis on integrating multiple content areas to answer big questions, the pursuit of mathematical modeling, descends from Dewey’s work. We present the definition, principles, and design of modeling practices for readers who may be familiar with early childhood curriculum but less so with using modeling for learning. We explore the application of mathematical modeling to early childhood classrooms and its compatibility with early childhood pedagogies and philosophies. Young children may often be underestimated, assumed to be unable to pose big questions that can be answered through activity, experience, and data; but we discuss how young children can be engaged in problems through mathematical modeling. Finally, as preservice teacher educators, we discuss preparing preservice and in-service teachers for modeling in their classrooms. We offer examples and guidance for early childhood teachers to engage in authentic practice – meeting children where their interests are and creating integrated problem-solving experiences.

Investment in non-listed real estate funds (NREFs) in an emerging economy like India has its own challenges that entail a detailed understanding of the risks. The purpose of this paper is to identify the key risk factors across the life cycle of a NREF, based on a considered feedback of various real estate fund management stakeholders. It is important for the investors and fund managers to appreciate these risk factors to make informed investment decisions.

The present study based on the literature survey and discussion with experts identifies 39 risk attributes, which were further summarized using factor analysis into a smaller set of factors impacting NREF returns (risk). The relative importance of each risk attribute was examined and ranked using the relative importance index (RII). Further, cluster analysis using Euclidian distance was used to partition these risk attributes in various segments depending on their importance.

The risk attributes are summarized as five risk factors, i.e. regulatory RISK, foreign direct investment risk, entry risk, business risk and project risk. Whereas the top five perceived risk attributes are investee/partner risk, project entitlement risk, title risk, legislative and regulatory risk and project execution risk.

This study has significance to the industry practitioners and the academic community in developing an understanding of the dynamic nature of risks across the life cycle of the NREFs in India and classifying them at the macro-meso-micro levels.

This paper is one of the first attempts to understand the risks impacting NREFs in India. It will help investors develop a better strategic understanding of the risks across the life cycle of an investment.

Not all problems are solvable using traditional problem‐solving or research methodologies, primarily because the problem defies definition. Backward Utopian Iteration suggests the use of the systems approach to solving these problems by focusing on the goal or output of the system.

The chapter analyses the anti-immigration political parties in the European Union (EU) as a challenge for the EU values such as human dignity, freedom, democracy, equality, rule of law, and human rights. As the main constituents of the political groups in the European Parliament, the single elected body of the EU, the parties in the member states require a special scrutiny. In this context, the study aims at understanding and exposing how anti-immigration political parties in the EU discursively construct immigration as a threat. Taking into consideration their salient rise in the 2019 European election, it focuses on the discourses of the relevant parties delivered during the debates of the first half of the ninth (2019–2024) parliamentary term by using critical discourse analysis as its theoretical and methodological framework. The main argument of the study is that these political parties securitize immigration within three main discourse topics: immigration as a security threat, as an economic threat, and as a cultural threat.

This study provides an extensive risk assessment framework for nonlisted real estate funds' (NREFs) portfolio management in India across their life cycle; that is, the investment stage, the monitoring stage and the exit stage in an emerging market context. The study of risk across these three stages is a new addition to the literature and assumes importance in the context of real estate portfolio management for NREFs in the emerging markets (e.g. India), which are predominantly an opportunistic investment play.

The risk assessment framework is built on the multiactor/multicriteria risk priorities, using analytical hierarchy process (AHP), obtained from 35 experts in four real estate fund management professional groups; namely, investors/fund managers, valuers, consultants and international developers.

The results demonstrate that the real estate portfolio management risk priorities change across the three life cycle stages of the fund. At the investment stage, specific risks are most critical; at the monitoring stage, it is important to concentrate on all three risks – specific, systematic and management risks; and at the exit stage, systematic risk plays a crucial role. Real estate portfolio management risk evaluation at the subfactor level shows that investee/partner and location selection needs to be critically evaluated at the time of the investment; project execution and quality of development must be monitored during the construction/monitoring period; and repatriation of the funds, currency volatility and exit risk (resale) are critical at the exit stage of the fund.

The understanding of the real estate portfolio management risk transformation across the life cycle stages is crucial for NREF managers for risk minimization, transfer and mitigation strategy formulation in their real estate portfolios. Unlike previous research that evaluates investment risk, this study breaks the NREF's risks into the investment, monitoring and exit stages. The key risk factors for each stage depend on the NREF's real estate activities for that stage. These activities, in turn, give rise to a typical risk profile for that stage. The findings are crucial for the various stakeholders of real estate fund management and policymakers in an emerging market context; particularly India, one of the fastest growing major economies in the world.

This risk assessment framework for simultaneously assessing risk across the three life cycle stages of NREFs is a new addition to the literature.

This paper investigates the dynamic nature of risk in pre-, during- and post-COVID duration. It investigates how commercial office portfolio stakeholders in India perceived risk during the COVID pandemic, their risk response and mitigation strategies, and emerging structural changes that would impact the commercial office portfolio (COP) in the post-COVID period.

A qualitative and applied research method is adopted for the study. Through purposive sampling, commercial office portfolio stakeholders were selected and interviewed using a semi-structured questionnaire having two parts. In the first part, risk attributes were accessed on the Likert scale and in the second part there were open-ended questions.

The uncertainty during the COVID period increased the risk perception significantly. There was a sense of urgency to retain the tenants, preserve the headline rentals and keep the properties operational. COP managers were forthcoming to offer rent deferments, common area maintenance discounts and upgrades in the physical office in form of touchless equipment, better air filters, etc. Post-pandemic there would be extensive use of technology and data for facility management and space utilization analytics; mainstreaming of hybrid working and flexible office spaces; increased certification of buildings; adoption of ESG and sustainability norms; and better-designed buildings with a focus on EHS and wellbeing.

Identifying structural changes in the post-pandemic period will help the COP managers to align their portfolios to the emerging office market requirements.

This study helps in developing an understanding of the dynamic nature of the risk across pre-, during- and post-COVID periods. And risk responses and mitigation strategies adopted during the COVID period in an emerging market.

The South African listed property market has changed its legal basis from property loan stock companies and property unit trusts to adopt the more familiar international structure, real estate investment trusts. The main distinction is how shareholding is structured and investment returns are paid out to shareholders, which results in a different tax treatment. It is hoped that this change would attract more foreign investment, but it is questionable if this is sufficient to convince global investors who, amidst a seeming worsening of the stability in the political and economic environment, would probably need more insight into aspects such as investment decision making within these South African organisations. The paper aims to discuss these issues.

Using a balanced scorecard (BSC) framework, this study investigates the relevance of investment decision-making frameworks in South Africa. A survey using a sample of institutional investors that are included in the South African Property Market Index was conducted.

The study found similarities in decision-making priorities of South African institutional investors to those of previous studies. With the focus on retail property, tenant mix and secondary to that, quality of the centre management team is found to be important for forecasting expected returns in a retail investment decision environment. Diversification strategies were found to have similar results to previous studies, leaning more towards geographic location than economic location. Further, the study suggested the use of a BSC framework, linking the financial information and different financial ratios to nonfinancial aspects that need specific consideration in a retail investment environment.

Retail property is considered to be of particular concern due to the business enterprise value that could be created if superior management techniques are applied. The investment decision stage concerned with forecasting expected returns relies on financial and quantitative models such as those derived from Modern Portfolio Theory. In a shopping mall environment, however, future performance is driven by nonfinancial factors, for example, tenant mix and superior customer experience. Therefore, forecasting expected returns in a retail environment requires a nuanced approach relative to other commercial property sectors.

The paper is considered to be original in its analysis of the retail real estate market in South Africa. This offers new insight into retail properties specifically, but also how investors in South Africa react to decision-making practices. This adds value in the internationalisation of the property market and the consistency and transparent practices applied globally.

In this paper, we examine dynamic relationships among three housing market variables and a stock market index in a multivariate vector autoregressive error correction (VAREC) model. It is first found that, in the USA, sales and the median sales price of the existing single‐family homes and the 30‐year mortgage rate have unit roots, while the New York Stock Exchange (NYSE) value‐weighted portfolio returns appear random. Moreover, it is found that not only are three real estate variables cointegrated with one another but that they are also cointegrated with the stock index returns. After controlling for the unit root problem and cointegration, a multivariate VAREC model is further developed to examine dynamic relationships among the four variables using Johansen’s approach. It is found that the price, mortgage rate, and stock returns affect sales. It is found that the mortgage rate and stock returns affect the price. The 30‐year mortgage rate is affected by sales and the stock returns. Except for the mortgage rate which is negatively correlated with the stock returns, significant evidence is not found that sales and the median sales price affect the stock returns directly.

This study aims to examine that personality traits are associated with the investor’s ability to exhibit disposition effect, herding behavior and overconfidence. It also explores how risk-attitude can modify investor behavior by moderating the association between personality traits, disposition effect, herding and overconfidence.

Data were collected from 396 respondents by using personally administrated survey. Confirmatory factor analysis (CFA) was used to confirm the validity and reliability of data. Regression analysis was used to test the proposed hypotheses.

The results supported the proposed hypotheses and showed that extravert investors were more likely to exhibit disposition effect, herding and overconfidence. The conscientiousness trait was associated with disposition effect and overconfidence, while neuroticism was associated with herding behavior. The results confirmed the moderating effect of risk aversion on the association between personality traits, disposition effect, herding and overconfidence.

This study demonstrates how risk aversion modes the strength of association between psychological characteristics (represented by personality traits) and cognitive biases (disposition effect, herding and overconfidence). The results support the “auction” interpretation of investors' behavior by suggesting that personality traits are associated with investment decision-making and that investors are marginal price setters.

The purpose of this paper is to examine the sources of direct real estate portfolio returns and their relative performance against Investment Property Databank (IPD) benchmark returns. Active property management consists of the concepts of property transaction execution and operational management, which can be classified as the main drivers of excess return sources.

Using a sample of three different portfolios managed by two institutional investors, the paper is able to estimate the relevant factors of active property management on annual excess returns for commercial and residential property sectors via a panel regression technique.

Empirical evidence shows that property‐specific effects exhibit significant sources of excess returns, but property management cannot be identified as their main driver. Furthermore, the sources of excess returns do not differ significantly across sectors; when controlled for property age and size, it is found that their influence is rather limited.

Information about the drivers of excess returns and their variations among property types may lead to superior investment decisions during portfolio rebalancing, and thus promote more efficient capital allocation. Information about return factors, i.e. about property and operational management, can substantially improve property selection and market timing in the asset allocation process. Hence, investors basing their property investment strategies on the impact of selected return factors could enhance the risk‐adjusted performance of their property portfolios.

This paper aims to contribute to the existing literature by identifying and quantifying the excess return sources of a given property portfolio over a predefined benchmark. Due to the lack of property‐related data, there is only limited research on the sources of direct property returns, such as property characteristics or active property management. The authors explore three main questions in this paper. First, they examine sources of excess returns over a benchmark index for several property sectors. Second, they analyze whether the drivers of excess returns vary significantly across these sectors. Third, they determine to what extent excess property returns are influenced by the “economic age” and “rentable area” of a building.