Search results

Urban population growth has increased housing density, which has expanded the construction of low-cost low-rise residential in urban areas. Good building performance and effective low-cost low-rise residential quality lead to higher user satisfaction and improve building sustainability. This study aims to focus on the factors influencing the sustainability of low-cost low-rise residential in the West Malaysia urban area to assess resident satisfaction.

A mixed-mode approach with both qualitative and quantitative were used in this study. Semi-structured interviews were conducted with 12 stakeholders to identify the common factors influencing sustainability in low-cost low-rise residential. Subsequently, questionnaire surveys were formed and distributed among building users to determine the satisfaction level with low-cost low-rise residential building performance.

The finding demonstrates that accessibility is the key factor to achieving sustainability of low-cost low-rise residential. The finding also related to the factor that influences both stakeholders and building user satisfaction levels. This study also identifies key areas that require attention to improve user satisfaction with building sustainability and building performance of low-cost low-rise residential.

This study aims to determine stakeholder and building user satisfaction levels in relation to the sustainable building factor. A few indicators have been set up to identify the factors that most influence the sustainability and environment of low-cost low-rise residential buildings. Each subchapter has a few recommendations to improve the performance of low-cost low-rise residential. Each of the factors mentioned is related to social, economic and environmental sustainability. In addition, the study discovered a strong connection between low-cost low-rise residential performance and user satisfaction.

This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms.

The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors.

Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users’ vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues.

The study is unique from the point of view that it investigates earnings management from the prospective of revenue’s classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

The purpose of this study is designed to achieve the learning process in producing studies involving economic issues and scenarios in business management in Malaysia. In addition, this study will provide exposure to the integration of managerial skills by using both microeconomics and macroeconomics concepts and theories to aid decision-making in a business environment.

The research method comprised qualitative methodology of literature review, case study and quantitative methodology of multiple linear regression (MLR). In this case, seven microeconomics and macroeconomics factors which are believed to significantly affect house price index (HPI) are taken into consideration which includes gross domestic product, consumer price index (CPI), government tax and subsidy on housing, overnight policy rate, unemployment rate (UNEMP), the median income (INC) and cost of production index.

This research has resulted in three significant factors affecting HPI from MLR, which include CPI, UNEMP and INC where the increase of these factors will cause a high increment of HPI. The other four factors are not significant.

Malaysia has been facing the stagnancy in house market these recent years due to issues such as massive oversupply, impacting Malaysia’s economy specifically focusing on domestic direct investment. To avoid oversupply issues, the vitality of future house demand and pricing forecast should be comprehended by involved bodies for more effective planning for the house development industry. To make a better and bigger impact, this research is intended to analyse the microeconomic and macroeconomic factors affecting the HPI to better understand the significance of each of these factors to the changes of HPI to resolve these economic issues.

Hospital building maintenance management constitutes a pertinent issue of global concern for all healthcare stakeholders. In Malaysia, the maintenance management of hospital buildings is instrumental to the Government’s goal of providing efficient healthcare services to the Government's citizenry. However, there is a paucity of studies that have comprehensively explored all dimensions of hospital building defects in relation to maintenance management. Consequently, this study seeks to evaluate the defects of hospital buildings in Malaysia with the aim of proffering viable solutions for the rectification and prevention of the issue.

The study utilised a quantitative approach for data collection.

The findings indicated that cracked floors, floor tile failures, wall tiles failure, blocked water closets, and damaged windows were some of the flaws that degrade hospital buildings. The study’s outcomes reveal that defects not only deface the aesthetic appearance of hospital buildings but also inhibit the functionality of the buildings and depreciate the overall satisfaction.

Considering the indispensable role of hospital buildings in the grand scheme of healthcare service provision and ensuring the well-being of people, the issue of defects necessitates an urgent re-evaluation of the maintenance management practices of hospital buildings in Malaysia. Previous studies on the maintenance management of hospital buildings in Malaysia have focused primarily on design, safety, and construction.

This is particularly important because defects in hospital buildings across the country have recently led to incessant ceiling collapses, fire outbreaks, ceiling, roof collapses, and other structural failures. These problems are typically the result of poor maintenance management, exacerbated by poor design and construction. These disasters pose significant risks to the lives of hospital building users.

This study offers invaluable insights for maintenance organisations and maintenance department staff who are genuinely interested in improving hospital buildings’ maintenance management to optimise staff's performance and enhance the user satisfaction of hospital buildings in Malaysia and globally.

Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

The purpose of this paper is to report on the results of a study carried out to identify and analyse which potential subject areas may have impact on developments in the field of building maintenance (BM). That is, it is intended to contribute to the integration of new approaches so that building maintenance management (BMM) becomes as automated, digital and intelligent or smartness as possible in the near future.

The research approach has resulted in a theory that is essentially based on a qualitative design. The route followed was a literature review, involving the collection, analysis and interpretation of carefully selected information, mostly from recently published records. The data assembled and the empirical experience itself made it possible to present a comprehensive viewpoint and some future outlooks.

Five thematic areas considered as potentially impactful for BM developments have been highlighted, analysed and generically labelled as thematic base words, which are monitoring, automation, digitalisation, intelligence and smart. It is believed that these may be aspects that will lay the groundwork for a much more advanced and integrated agenda, featured by a high-tech vision.

This is thought to be a different way of looking at the problem, as it addresses five current issues together. Trendy technological aspects are quite innovative and advantageous for BMM, providing opportunities not yet widely explored and boosting the paradigm shift.

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

This paper aims to examine the effects of investor sentiment on the development of the real estate corporate bond market in Vietnam.

The research uses an autoregressive distributed lag (ARDL) model with quarterly data. Additionally, the study employs Google Trends search data (GVSI) related to topics such as “Real Estate” and “Corporate Bond” to construct a sentiment index.

The empirical outcomes reveal that real estate market sentiment improves the growth of the real estate corporate bond market, while stock market sentiment reduces it. Also, there is evidence of a long-run negative effect of corporate bond market sentiment on the total value of real estate bond issuance. Further empirical research evidences the short-term effect of sentiment and economic factors on corporate bond development in the real estate industry.

Due to difficulties in collecting data, this paper has the limited sample of 54 valid quarterly observations. Moreover, the sentiment index based on Google search volume data only reflects the interest level of investors, not their attitudes.

These results yield important implications for policymakers in respect of strengthening the corporate bond market platform and maintaining stability in macroeconomic and monetary policies in order to promote efficient and sustainable market development.

The study offers some suggestions for regulators and governments to improve the real estate corporate bond market.

This is the first quantitative study to examine the effect of sentiment factors on real estate corporate bond development in Vietnam.

The objective of this research is to identify the economic, demographic, sanitary and even cultural factors which explain the variability in the cross-section of returns in different markets globally during the first weeks after the outbreak of COVID-19.

Building on the event study methodology and using seemingly unrelated equations, the authors created several indicators on the impact of the pandemic in 75 different markets. Then, and using cross-sectional regressions robust to heteroscedasticity and using an algorithm to select independent variables from more than 30 factors, the authors determine which factors were behind the different stock market reactions to the pandemic.

Higher currency depreciation, inflation, interest rate or government deficit led to higher returns, while higher life expectancy, ageing population, GDP per capita or health spending led to the opposite effect. However, the positive effect of competitiveness and the negative effect of income inequality stand out for their statistical and economic significance.

This research provides a global view of investors' reaction to an extreme and unique event. Using a sample of 75 capital markets and testing the relevance of more than 30 variables from all categories, it is, to the authors' knowledge, the largest and most ambitious study of its kind.