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The study investigated the perceived causes of structural failure of public buildings, frequency of stability checks, stability checking procedures, measures to enhance public building stability checks and the roles of facility managers in the Accra Metropolis of Ghana.

Following a comprehensive literature review, the study employed a structured questionnaire survey and gathered the opinions of sixty-seven facility managers on the facility management practices. Following statistical pretesting of the dataset for reliability, distribution and agreement among the responses, the study analysed the dataset using mean scoring and weighted analysis.

The analysis showed that external building inspectors rarely inspect stability checks of the studied public buildings in Accra. It is also found that both reactive and proactive stability checking protocols are implemented in public buildings in Accra, but inadequate knowledge of facility managers limits technical stability checks. The study further revealed that stability checks of public buildings can be enhanced through incorporating site and location conditions into the design early upfront, active engagement of facility managers in the design and construction of public buildings, adequate budgetary provisioning for planned maintenance of public buildings, and encouraging appropriate use of public buildings.

This paper, to the best of the authors' knowledge, represents the first attempt to comprehensively examine the causes of structural failure of public buildings, frequency of stability checks, stability checking procedures, measures to enhance public building stability checks and the roles of facility managers in Ghana, from the perspective facility management.

This study aims to examine the impact of economic policy uncertainty and bank competition on the financial stability of the Chinese banking industry. This study answers two fundamental questions. First, does economic policy uncertainty (EPU) affects the financial stability of banks in China? Second, does competition affect the financial stability of the Chinese banking sector?

The sample includes all commercial banks to provide a full picture of the Chinese banking sector. This study covers the time between 2011 and 2019. The sample period captures different EPU spikes and key policy changes. This study used different econometric methodologies such as the generalized method of moments and the fixed effect and ordinary least square estimation models. Furthermore, this study used the Instrumental Variable model to solve endogeneity, autocorrelation and unobserved heterogeneity concerns. Besides, alternative EPU and financial stability measures were used. Moreover, this study reestimates the model after dropping the big five state-owned banks.

This study found that both EPU and competition reduce financial stability. This implies that EPU has a negative impact on financial stability. This shows that uncertainty distorts resource allocation efficiency and creates confusion, leading to financial instability in the banking sector. Besides, this study found that competition negatively affects financial stability. This result implies that high competition pushes banks toward riskier activities that ultimately lead to increased financial instability.

This study is the first of its kind that examines the impact of EPU and competition on the financial stability of the Chinese banking sector. This study conducted several robustness tests such as the instrumental variable model, alternative measurement and sample construction methods. This study brings policy implications and lessons for the banking sector.

The purpose of the paper is to address money demand instability and investigate the impact of economic uncertainty, stock market uncertainty and monetary uncertainty on money demand in India over the period 2003Q1–2019Q4.

The study checks the stationarity of the variables through standard unit root tests. Based on the mixed order of variables' integration, the authors adopt the autoregressive distributed lag (ARDL) model to confirm the cointegration and check the stability of the money demand function (MDF).

The findings confirm the presence of cointegration and reveal a well-specified MDF, which exhibits stable parameters. Besides the conventional variables, all forms of uncertainties emerge as the essential long-term determinants of money demand. Long-run findings show that people demand more money to avoid the future financial crunch amid high economic, monetary and stock market uncertainties.

The paper recommends, based on the findings, incorporating the monetary aggregates in the monetary policy framework as one of the essential information variables to control the fluctuation in the price level under the current flexible inflation targeting (FIT) regime.

The findings also add to the knowledge of economic agents in terms of the overall response of individuals to changes in different forms of uncertainties, thereby helping to formulate their portfolios more diligently.

The current work is the first of its kind in the Indian context. The incorporation of uncertainty measures in the MDF adds to the existing knowledge on money demand.

Parallel assembly sequence planning (PASP) reduces the overall assembly effort and time at the product development stage. Methodological difficulties at framework development and computational issues at their implementation made the PASP complex to achieve. This paper aims to propose a novel stability concept for subassembly detection to minimize the complexities in PASP.

In this research, a heuristic method is developed to identify, represent and implement the stability predicate to perform subassembly detection and assembly sequence planning (ASP) at the further stages. Stability is organized into static, dynamic, enriched and no stability between the mating assembly parts. The combination of parts that possesses higher fitness is promoted to formulate the final solution about PASP.

The results obtained by applying the proposed concept on complex configurations revealed that stability predicate plays a dominant role in valid subassembly detection and final sequence generation further.

The value of the presented study lies in the three types of stability conditions and effective integration to existed ASP method. Unlike the existed heuristics in subassembly detection, the proposed concept identifies the parallel subassemblies during ASP.

The spectrally selective solar absorption paint is prepared from spinel-based mixed metal oxides with inorganic binder as a key component. Inorganic binder (furnace cement) is blended with mixed metal oxide pigment during synthesis. High temperature stability upto 1,100ºC is achieved by the use of this modified coating system. The purpose of this paper is to work on solar selective coating synthesis, and application of a coating as a water-borne paint is the additive key feature that helps in reduction of solvent use.

The paint was formulated using water-based system, and the main component of colorant was made by mixed metal oxide–based spinel pigment and highly temperature stable inorganic binder.

The paint formed shows excellent absorptive power with low emittance even at high temperature. Optical and thermal properties were determined along with adhesion, abrasion and other properties. The solar absorptance for these samples were as = 0.93–0.95 with corresponding thermal emittance of eT = 0.096 (at room temperature) and 0.2–0.22 (at elevated temperature 100°C).

The paint formed shows excellent absorptive power with low emittance even at high temperature. The paint can be applied in solar absorptive tower system. The obtained results indicated excellent thermal stability of prepared paint coatings. As inorganic binder was used, the paint has reduction in solvent use, and being water as a base, it is environment friendly, easy to apply and durable at high temperatures, as the binder itself is stable up to 1,500ºC.

THE B.206 had its origin in the B.206X experimental aircraft which was built in 1961 to obtain aerodynamic and structural data for the production series, and it first flew in August 1961.

The purpose of this paper is to examine the relationship between tourism sector development and poverty reduction in India using annual data from 1970 to 2018. The paper attempts to answer the critical question: Is tourism pro-poor in India?

Stationarity properties of the series are checked by using the ADF unit root test. The paper uses the Auto Regressive Distributed Lag (ARDL) bound testing approach to cointegration to examine the existence of long-run relationships; error-correction mechanism for the short-run dynamics, and Granger non-causality test to test the direction of causality.

The cointegration test confirms a long-run relationship between tourism development and poverty reduction for India. The ARDL test results suggest that tourism development and economic growth reduces poverty in both the long run and the short run. Furthermore, inflation had a negative and significant short-run impact on the poverty reduction variable. The causality test confirms that there is a positive and unidirectional causality running from tourism development to poverty reduction confirming that tourism development is pro-poor in India.

This study implies that poverty in India can be reduced by tourism sector growth and price stability. For a fast-growing economy with respect to economic growth and tourism sector growth, this may have far-reaching implications toward inclusive growth in India.

This paper is the first of its kind to empirically examine the causal relationship between tourism sector development and poverty reduction in India using modern econometric techniques.

This paper aims to propose and analyse a two-prey–one-predator system with mixed functional response.

The predator exhibits Holling type IV functional response to one prey and Holling type I response to other. The occurrence of various positive equilibrium points with feasibility conditions are determined. The local and global stability of interior equilibrium points are examined. The boundedness of system is analysed. The sufficient conditions for persistence of the system is obtained by using Bendixson–Dulac criteria. Numerical simulations are carried out to illustrate the analytical findings.

The authors have derived the local and global stability condition of interior equilibrium of the system.

The authors observe that the critical values of some system parameter undergo Hopf bifurcation around some selective equilibrium. Hence, numerical simulations reveal the condition for the system to be stable and oscillatory.

While Blockchain can serve us, Bitcoin threatens our survival. If Bitcoin is assumed to be a country, it will rank 38th globally for energy consumption. With 90.2 metric million tonnes of carbon dioxide, Bitcoin mining and trading has emerged as an environmental threat. The current study investigates how the trading-specific variables, the prices of Crypto Index and Ethereum, affect bitcoin-based energy consumption. Also, the role of mining-specific variables is analyzed.

The study uses monthly data from various sources collected from December 2018 to January 2023. The authors used the Autoregressive Distributed Lag (ARDL) Model to determine the short- and long-term relationships between variables. This study uses the Theory of Green Marketing and the Theory of Cross Elasticity of Demand as a theoretical lens.

The findings show that escalating crypto market index and Ethereum prices with a one-month lag increases bitcoin-specific electricity consumption and carbon emissions. Green investors may shift to cryptocurrencies based on consensus other than of Proof-of-Work. Ethereum behaves like a substitute for Bitcoin, reflected by the long-term positive relationship between Bitcoin's energy consumption and Ethereum prices.

The study analyses how the crypto market index and Ethereum price affect bitcoin-based energy use. The relationships identified are substantiated by the literature to provide suggestions to green investors and policymakers to mitigate the harmful impact of Bitcoin's colossal energy consumption on the natural environment.

This study undertakes a comprehensive investigation into the far-reaching repercussions of Covid-19 stimulus packages and containment policies on stock returns, meticulously examining a diverse array of 14 distinct markets.

This study employed the Panel SVAR model to analyze the relationships between various policies and stock market performance during the Covid-19 outbreak. The sample comprises 5432 daily observations spanning from December 2020 to January 2022 for the 14 selected markets, with missing data excluded.

The findings reveal three consistent impacts across all 14 markets. Firstly, stock returns immediately reversed and decreased within a day when Governments tightened containment policies. Secondly, economic stimulus packages led to a fall in stock returns. Thirdly, an increasing death rate caused the stock return to decrease in the following two days. These findings are supported by the uniform impulse responses in all three shocks, including common, composite and idiosyncratic shocks. Furthermore, all inverse root tests satisfy the stability conditions, indicating the stability and reliability of Panel SVAR estimations.

One vital implication is that all government decisions and measures taken against the shock of Covid-19 must consider economic impacts to avoid unnecessary financial losses and support the effective functioning of stock markets during similar shocks. Secondly, investors should view the decline in stock returns due to Covid-19 effects as temporary, resulting from anxiety about the outbreak. The study highlights the importance of monitoring the impact of policies on financial markets and the broader economy during crises. Overall, these insights can prove helpful for investment decisions and policymaking during future crises.

This study constitutes a noteworthy addition to the literature on behavioural finance and the efficient market hypothesis, offering a meticulous analysis of the multifaceted repercussions of Covid-19 on market interactions. In particular, it unveils the magnitude, duration and intricate patterns of market volatilities linked to significant shock events, encompassing a comprehensive dataset spanning 14 distinct markets.