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Sustainability represents innovative elements in determining the profitability of real estate investments, among other factors, including the green component in real estate. Evidence from the literature has pointed out that incorporating green features into residential buildings can reduce operational costs and increase the building’s value. Although green real estate is considered the future trend of choice, it is still being determined whether prospective buyers are willing to accept the extra cost of green residential investment. Therefore, this study aims to investigate the effect of housing attributes and green certification on residential real estate prices.

The impact of the housing attribute and green certification in the residential sectors was assessed using a transaction data set comprising approximately 861 residential units sold in Selangor, Malaysia, between 2014 and 2022. Linear and quantile regression were used in this study by using SPSS software for a robust result.

The findings indicate that the market price of residential properties in Malaysia is influenced by housing attributes, transaction types and Green Building Index certification. The empirical evidence from this study suggests that green certification significantly affects the sales price of residential properties in Malaysia. The findings of this research will help investors identify measurable factors that affect the transaction prices of green-certified residential real estate. These identifications will facilitate the development of strategic plans aimed at achieving sustainable rates of return in the sustainable residential real estate market.

Specifically, this research will contribute to achieving area 4 of the 11th Malaysia Plan, which pertains to pursuing green growth for sustainability and resilience. This will be achieved by enhancing awareness among investors and homebuyers regarding the importance of green residential buildings in contributing to the environment, the economy and society.

The regression model for housing attributes and green certification on house price developed in this study could offer valuable benefits to support and advance Malaysia in realising its medium and long-term goals for green technology.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble.

House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data.

The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense.

The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates.

A tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability.

The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market.

The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.

Systems thinking calls for a shift of our mindset from seeing just parts to seeing the whole reality in its structured dynamic unity and interconnectedness. Systems thinking fosters a sensibility to see subtle connections between components and parts of reality, especially the free enterprise capitalist system (FECS). It enables us to see ourselves as active participants or partners of FECS and not mere induced factors of its production–distribution–consumption processes. Systems thinking seeks to identify the economic “structures” that underlie complex situations in FECS that bring about high versus low leveraged changes. A system is strengthened and reinforced by feedback of reciprocal exchanges that makes the system alive, transparent, human, and humanizing.

In Part I, we explore basic laws or patterns of behaviors as understood by systems thinking; in Part II we examine the basic archetypes or structured behaviors of systems thinking; in both parts we strive to see reality through the lens of critical thinking to help us understand patterns and structures of behavior among systems and their component parts. In conclusion, we argue for compatibility and complementarity of critical thinking and systems thinking to identify and resolve management problems created by our flawed thinking, and sedimented by our wanton assumptions, presumptions, suppositions and presuppositions, biases, and prejudices. Such thinking will also identify unnecessary economic and political structures of the self-serving policies we create, which imprison us.

This study proposes a framework based on salience theory and shows that focusing on one type of risk (idiosyncratic or systemic) can explain overpricing of securities ex ante, and resales at low prices during crisis periods.

The author consider an overlapping generations (OLG) model where each generation lives for two periods and there is no population growth. Agents (investors) start their lives with an endowment W > 0 and have mean-variance utility. They invest their endowment when young and consume when old. Each period, the young investors optimally choose their portfolio from different risky assets acquired from the old generation, all assumed to be in fixed supply.

The author show that investor salience bias can explain excess volatility of asset prices and the resulting fire-sales in periods of financial turmoil. A change in salience – from one component (idiosyncratic) to the other (systemic) – will generate excess volatility. Interestingly, higher risk aversion generally exacerbates the excess volatility of prices. Moreover, the model predicts that if a big systemic shock hits the financial system, due to salience bias the price of systemic assets falls sharply. This relates to the observed fire-sales of assets during the global financial crisis.

The proposed model and results suggest that there may be a scope for intervention in financial markets during turbulences. In terms of ex ante policies the study suggests that investors and regulator should use better risk assessment technologies.

This is the first study constructing a tractable model based on the argument that investor salience may exacerbate the excess volatility of prices during financial downturns. The author relate salience to two types of risk; idiosyncratic and systemic and assume that investors' risk perception is biased towards the type of risk that is currently salient based on prior beliefs or past data. The author show that the diversification fallacy of the precrisis period, where seemingly safe assets were overpriced, can be explained by agents overweighing idiosyncratic risk and ignoring systemic risk.

The main objective of this study is to consider how to benefit efficiently from the significant potential of humanitarian operations by individuals. For this purpose, this study aims to assess failure factors in humanitarian supply chain operations after the Kermanshah earthquake considering the role of all parties, focusing on individuals who did not wish to work with formal organisations on the whole. In the aftermath of the Kermanshah earthquake, which occurred on 12 November 2017, improvised groups of Iranian civilians from all over the country played an important role in humanitarian supply chain operations as individuals. Although most of these groups sincerely intended to help the affected society, victims could not benefit properly from these significant potential humanitarian actions. On the contrary, these potential actions caused some issues during humanitarian operations, such as blocking roads, inappropriate last-mile distribution, wasting resources and so on.

This research study considers mixed methods, including an on-site survey, semi-structured interviewing and a questionnaire designed for statistical analyses. The analysis included 140 responses to the questionnaire, semi-structured interviews with 32 affected families, interviews with 5 emergency managers from the Housing Foundation of the Islamic Republic of Iran and on-site survey reports.

This study presents a framework for humanitarian supply chain management to deal with future disasters in the same area or areas with similar characteristics to the case study. In general, the results of this study demonstrate that the nature of humanitarian supply chain operations makes it impossible to consider that these operations are free of challenges. However, several influential factors, such as training humanitarian actors and integrated management, might considerably increase the efficiency of humanitarian operations by individuals.

This study highlights the influential factors of inappropriate humanitarian operations by individuals, derived from an analysis of the Kermanshah case and literature review. The authors suggest a framework to benefit from the significant potential of individuals with wide-ranging experiences and proficiency, for future cases similar to the case study.

In particular, in this article, the authors investigate the degree of persistence in the credit-to-gross domestic product (GDP) ratio in 44 Organisation for Economic Co-operation and Development (OECD) economies in the context of nonlinear deterministic trends.

The authors use Chebyshev's polynomials in time, which allow us to model changes in the data in a smoother way than by structural breaks.

This study’s results indicate that approximately one-quarter of the series display non-linear structures, and only Argentina displays a mean reverting pattern.

Policy implications of the results obtained are discussed at the end of the manuscript.

The authors use an approach developed that allows for non-linear trends based on Chebyshev polynomials in time, with the residuals being fractionally integrated or integrated of order d, where d can be any real value.

This paper aims to study antiques enthusiasts’ perspectives on the recent stagnancy in the antiques market, along with their suggestions on how the antiques trade can forge a more secure path forward.

Using a qualitative analysis approach through netnography, this paper examines archived comments of antiques enthusiasts on a “r/antiques” subreddit.

This research studies connoisseurs’ insights into the reduction in antiques sales experienced by a wide cross-section of sellers, particularly independent and small business retailers. Specifically, the results of this paper’s discourse analysis show that technological advances on one hand and socioeconomic factors (e.g. income, family structure and lifestyle) on the other hand have had a significant negative impact on demand for antiques. In addition, specific attributes such as authenticity and sustainability emerged as potential key marketing elements for invigorating the broader public’s interest in purchasing antiques.

Despite their significant insights into the antiques market, antiques enthusiasts have not received the academic attention they deserve. Through discourse analysis of comments in an online antiques community, this paper draws attention to the vulnerabilities of antiques markets to a protracted climate of slow sales, while highlighting potential strategies on how to turn the tide for struggling antiques stores.

Trade relations between China and the USA have been marked by conflict, especially since China’s membership in the World Trade Organization (WTO). These conflicts have been analyzed from a variety of perspectives, including the loss of jobs in the USA due to Chinese imports, competition in high technology sectors and the balance of trade. Conceptual frameworks have employed models of domestic differences as well as models of international power distribution. Among domestic differences examined are the existence of state-owned enterprises in China compared to the domination of the USA economy by private firms, the large role of the Communist Party in China and the influence of labor and environmental and labor groups in the USA. Power distribution theories focus on the systemic effects of the distribution of power on trade openness and on the pattern of intra-bloc versus between-bloc trade. This paper aims to examine the role of macroeconomic policy factors in China and the USA, in particular, the role of national patterns of savings, investment and consumption (both private and government). The paper concludes that insofar as the balance of trade is an important component of the trade conflict, domestic macroeconomic factors continue to be important. The resolution of the conflict will have to take into account the respective macroeconomic policies of China and the USA.

The design is an analytic case study of US–China trade relations with a particular focus on the balance of trade. The conceptual framework employed involves an analysis of macroeconomic policy categories, especially the overall pattern of savings (household, firm and government), investment and consumption. Process tracing over time since China's membership in the WTO is carried out with an eye toward the relationship between the balance of trade and macroeconomic policy.

The main findings are that there is a strong relation between the respective macroeconomic policies of the USA and China and their trade relations. The domestic political economy of the USA encourages consumption and a low rate of savings. The opposite is true of China where household income is low by design and national savings are high. China depends on the USA to consume what is not consumed domestically. The USA depends on Chinese imports for additional consumption encouraged by its low rate of savings. The two economies are locked in a mutual dependence.

Key research implications are that there should be more focus on domestic macroeconomic policies since these are the root causes of the trade imbalance. This is not to say that trade frictions centering on jobs, subsidies and competition in high technology are unimportant. However, without the resolution of differences in the management of macroeconomic policies, trade conflicts between the USA and China will continue.

Practical implications are huge, in some ways much more important than the academic implications. Macroeconomic policy differences in savings, investment, government spending, taxation and infrastructure are important. Furthermore, there are available tools in both China and the USA to manage the macroeconomy, particularly, monetary and fiscal policy.

One implication of this paper is that satisfaction or dissatisfaction of workers is dependent on income distribution which in turn affects trade. Treatment of people in different socioeconomic categories, such as the elderly, the young, and those at working age are a function of macroeconomic policies.

Many people have written about macroeconomics. It is a conventional subfield of economics. The originality of this paper lies in its advocacy of a shift of focus and attention and in the argument that traditional macroeconomics is related to trade. Despite its importance, macroeconomics has not been the center of attention for most political scientists, though economists have made it more central.