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1 – 10 of 465Ali Hassan Ali, Ahmed Farouk Kineber, Ahmed Elyamany, Ahmed Hussein Ibrahim and Ahmed Osama Daoud
This study aims to identify the most significant barriers and the stationary barrier to modular construction (MC) implementation and promote MC widespread use. By doing so, the…
Abstract
Purpose
This study aims to identify the most significant barriers and the stationary barrier to modular construction (MC) implementation and promote MC widespread use. By doing so, the construction industry can leverage the benefits of MC, such as faster construction times, improved quality control, reduced waste and increased sustainability.
Design/methodology/approach
This study uses a Gini’s mean analysis approach to identify the stationary barriers hindering the MC adoption in residential projects. The research focuses on the Egyptian context and uses a questionnaire survey to gather data from professionals in the construction industry.
Findings
According to the survey findings, the top five significant MC barriers are inability to modify the design; contractors asking for high bidding prices (higher initial cost); scepticism, conservation and resistance of clients to innovation and change; transportation restrictions; and lack of a one-size-fits-all tool for the design. In addition, Gini’s mean of dispersion demonstrated that the stationary barrier that faces MC adoption is the apprehension that architectural creativity will suffer because of MC.
Practical implications
The identified obstacles could be useful for decision makers in countries that have not yet adopted MC and may aid in the planning process to manage the risks associated with MC projects. The paper stresses the significance of devising techniques to overcome these barriers and proposes several methods to tackle these challenges.
Originality/value
This study fills the knowledge gap by identifying the stationary barrier and emphasising the potential risks associated with MC barriers. Furthermore, it suggests several strategies for overcoming and reducing these barriers in developing countries residential projects.
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Ignacio Manuel Luque Raya and Pablo Luque Raya
Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.
Abstract
Purpose
Having defined liquidity, the aim is to assess the predictive capacity of its representative variables, so that economic fluctuations may be better understood.
Design/methodology/approach
Conceptual variables that are representative of liquidity will be used to formulate the predictions. The results of various machine learning models will be compared, leading to some reflections on the predictive value of the liquidity variables, with a view to defining their selection.
Findings
The predictive capacity of the model was also found to vary depending on the source of the liquidity, in so far as the data on liquidity within the private sector contributed more than the data on public sector liquidity to the prediction of economic fluctuations. International liquidity was seen as a more diffuse concept, and the standardization of its definition could be the focus of future studies. A benchmarking process was also performed when applying the state-of-the-art machine learning models.
Originality/value
Better understanding of these variables might help us toward a deeper understanding of the operation of financial markets. Liquidity, one of the key financial market variables, is neither well-defined nor standardized in the existing literature, which calls for further study. Hence, the novelty of an applied study employing modern data science techniques can provide a fresh perspective on financial markets.
流動資金,無論是在金融市場方面,抑或是在實體經濟方面,均為市場趨勢最明確的預報因素之一
因此,就了解經濟週期和經濟發展而言,流動資金是一個極其重要的概念。本研究擬在安全資產的價格預測方面取得進步。安全資產代表了經濟的實際情況,特別是美國的十年期國債。
研究目的
流動資金的定義上面已說明了; 為進一步了解經濟波動,本研究擬對流動資金代表性變量的預測能力進行評估。
研究方法
研究使用作為流動資金代表的概念變項去規劃預測。各機器學習模型的結果會作比較,這會帶來對流動資金變量的預測值的深思,而深思的目的是確定其選擇。
研究結果
只要在私營部門內流動資金的數據比公營部門的流動資金數據、在預測經濟波動方面貢獻更大時,我們發現、模型的預測能力也會依賴流動資金的來源而存在差異。國際流動資金被視為一個晦澀的概念,而它的定義的標準化,或許應是未來學術研究的焦點。當應用最先進的機器學習模型時,標桿分析法的步驟也施行了。
研究的原創性
若我們對有關的變量加深認識,我們就可更深入地理解金融市場的運作。流動資金,雖是金融市場中一個極其重要的變量,但在現存的學術文獻裏,不但沒有明確的定義,而且也沒有被標準化; 就此而言,未來的研究或許可在這方面作進一步的探討。因此,本研究為富有新穎思維的應用研究,研究使用了現代數據科學技術,這可為探討金融市場提供一個全新的視角。
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M. Mary Victoria Florence and E. Priyadarshini
This study aims to propose the use of time series autoregressive integrated moving average (ARIMA) models to predict gas path performance in aero engines. The gas path is a…
Abstract
Purpose
This study aims to propose the use of time series autoregressive integrated moving average (ARIMA) models to predict gas path performance in aero engines. The gas path is a critical component of an aero engine and its performance is essential for safe and efficient operation of the engine.
Design/methodology/approach
The study analyzes a data set of gas path performance parameters obtained from a fleet of aero engines. The data is preprocessed and then fitted to ARIMA models to predict the future values of the gas path performance parameters. The performance of the ARIMA models is evaluated using various statistical metrics such as mean absolute error, mean squared error and root mean squared error. The results show that the ARIMA models can accurately predict the gas path performance parameters in aero engines.
Findings
The proposed methodology can be used for real-time monitoring and controlling the gas path performance parameters in aero engines, which can improve the safety and efficiency of the engines. Both the Box-Ljung test and the residual analysis were used to demonstrate that the models for both time series were adequate.
Research limitations/implications
To determine whether or not the two series were stationary, the Augmented Dickey–Fuller unit root test was used in this study. The first-order ARIMA models were selected based on the observed autocorrelation function and partial autocorrelation function.
Originality/value
Further, the authors find that the trend of predicted values and original values are similar and the error between them is small.
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Shanaka Herath, Vince Mangioni, Song Shi and Xin Janet Ge
House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers…
Abstract
Purpose
House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.
Design/methodology/approach
We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.
Findings
Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.
Research limitations/implications
We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.
Originality/value
To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.
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Ahmet Keser, Ibrahim Cutcu, Sunil Tiwari, Mehmet Vahit Eren, S.S. Askar and Mohamed Abouhawwash
The main objective of this research is to investigate if there is a long-term relationship between “terrorism” and sustainable “economic growth” in Big Ten Countries.
Abstract
Purpose
The main objective of this research is to investigate if there is a long-term relationship between “terrorism” and sustainable “economic growth” in Big Ten Countries.
Design/methodology/approach
The data was tested via Panel ARDL Analysis. The growth rate (GR) is the dependent variable, and the “Global Terror Index (GTI)” is the independent variable as the terror indicator. The ratio of Foreign Direct Investment (FDI) to the Gross Domestic Product (GDP), and the ratio of External Balance (EB) to Gross Domestic Product (GDP) are included in the model as the control variables due to their effect on the growth rate. A Panel ARDL analysis is conducted to examine the existence of long-term co-integration between terror and the economy. The planning of the study, the formation of its theoretical and conceptual framework, and the literature research were carried out in 2 months, and the collection of data, the creation of the methodology and the analysis of the analyzes were carried out in 2 months, the interpretation of the findings and the development of policy recommendations were carried out within a period of 1 month. The entire study was completed in a total of 5 months.
Findings
Results showed that “Terror” has a negative impact on “Growth Rate” in the long term while “External Balance” and “Foreign Direct Investment” positively affect the Growth Rate. The coefficients for the short term are not statistically significant.
Research limitations/implications
The sample is only limited to Big Ten including China, India, Indonesia, South Korea, Argentina, Brazil, Mexico, Turkey, Poland and South Africa. The period for annual data collection covers the years between 2002 and 2019 and due to the unavailability of data.
Practical implications
Considering the risks and the mutual negative effect that turns into a vicious circle between terrorism and the economy, it is necessary to eliminate the problems that cause terrorism in the mentioned countries, on the one hand, and to develop policies that will improve economic performance on the other.
Social implications
Trustful law enforcement bodies have to be established and supported by all technological means to prevent terror. The conditions causing terror have to be investigated carefully and the problems causing terror or internal conflict have to be solved. International cooperation against terrorism has to be strengthened and partnerships, information, experience sharing have to be supported at the maximum levels.
Originality/value
It is certain that terror might have a negative influence on the performance of economies. But the limited number of studies within this vein and the small size of their sample groups mostly including single-country case studies require conducting a study by using a larger sample group of countries. Big Ten here represents at least half of the population of the world and different regions of the Globe.
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Faris Alshubiri and Syed Jamil
The present study aims to compare the effect of international paid remittances on financial development in three Gulf Cooperation Council (GCC) countries from 1985 to 2020.
Abstract
Purpose
The present study aims to compare the effect of international paid remittances on financial development in three Gulf Cooperation Council (GCC) countries from 1985 to 2020.
Design/methodology/approach
The study applied the bound cointegration technique and the autoregressive distributed lag (ARDL) method for long- and short-run estimations as well as diagnostic tests to increase robustness.
Findings
The ARDL long-run results showed that international paid remittances had a significant negative effect on financial development in Oman and Saudi Arabia but an insignificant negative effect in Bahrain. The error correction model for the short run of the ARDL slowdown model showed that international paid remittances had a significant positive effect on financial development in Oman, Bahrain, and Saudi Arabia.
Originality/value
Few studies have examined remittance outflows from GCC countries, which are enriched by oil wealth and located in one of the most stable geographical areas in the world. The findings from this study can help policymakers understand how to enable remittances and investments in order to establish regulations that will preserve remittance inflows and meet target services.
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Ayodeji Emmanuel Oke, Ahmed Farouk Kineber, Oluwaseun Akindele and Damilola Ekundayo
To realize full benefits without sacrificing the practicality of such projects, the decision-making process for residential building construction needs to include sustainability…
Abstract
Purpose
To realize full benefits without sacrificing the practicality of such projects, the decision-making process for residential building construction needs to include sustainability principles at every level. Therefore, this paper aims to investigate the applicability of radio frequency identification (RFID) and identify the barriers that impede its successful adoption in construction projects to achieve sustainability.
Design/methodology/approach
This paper opted for a quantitative approach by using a structured questionnaire survey. A total of 107 responses were collected from Nigerian construction practitioners involved in private and public construction businesses.
Findings
The results showed the high cost of RFID implementation, with a mean score of 4.42 as the top-ranked barrier, followed by lack of security, maintenance, power availability and inadequate training. This study further deployed Ginni’s mean difference measure of dispersion and revealed that the stationary barrier to adopting RFID technology is the lack of demand.
Practical implications
The findings of this research can assist decision-makers in improving the sustainability of all building projects by implementing RFID.
Originality/value
The findings of this study will serve as the basis for comprehension and critically evaluate the numerous barriers preventing the widespread adoption of RFID technology.
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Marcel Peppel, Stefan Spinler and Matthias Winkenbach
The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel…
Abstract
Purpose
The e-commerce boom presents new challenges for last-mile delivery (LMD), which may be mitigated by new delivery technologies. This paper evaluates the impact of mobile parcel lockers (MPL) on costs and CO2 equivalent (CO2e) emissions in existing LMD networks, which include home delivery and shipments to stationary parcel lockers.
Design/methodology/approach
To describe customers’ preferences, we design a multinomial logit model based on recipients’ travel distance to pick-up locations and availability at home. Based on route cost estimation, we define the operating costs for MPLs. We devise a mathematical model with binary decision variables to optimize the location of MPLs.
Findings
Our study demonstrates that integrating MPLs leads to additional cost savings of 8.7% and extra CO2e emissions savings of up to 5.4%. Our analysis of several regional clusters suggests that MPLs yield benefits in highly populous cities but may result in additional emissions in more rural areas where recipients drive longer distances to pick-ups.
Originality/value
This paper designs a suitable operating model for MPLs and demonstrates environmental and economic savings. Moreover, it adds recipients’ availability at home to receive parcels improving the accuracy of stochastic demand. In addition, MPLs are evaluated in the context of several regional clusters ranging from large cities to rural areas. Thus, we provide managerial guidance to logistics service providers how and where to deploy MPLs.
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Xingwen Wu, Zhenxian Zhang, Wubin Cai, Ningrui Yang, Xuesong Jin, Ping Wang, Zefeng Wen, Maoru Chi, Shuling Liang and Yunhua Huang
This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.
Abstract
Purpose
This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.
Design/methodology/approach
Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.
Findings
The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.
Originality/value
The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.
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Guglielmo Maria Caporale, Luis Alberiko Gil-Alana and Eduard Melnicenco
This paper aims to analyse the persistence of the S&P500 and DAX 30 stock indices as well as of the Fed’s Effective Federal Funds rate and of the European Central Bank’s Marginal…
Abstract
Purpose
This paper aims to analyse the persistence of the S&P500 and DAX 30 stock indices as well as of the Fed’s Effective Federal Funds rate and of the European Central Bank’s Marginal Lending Facility rate, and the long-run linkages between stock prices and interest rates in the USA and Europe, respectively.
Design/methodology/approach
The methodology is based on the concepts of fractional integration and cointegration.
Findings
Using monthly data from January 1999 to December 2022, the results can be summarised as follows. All series examined are non-stationary: stock prices are found to be I(1) while interest rates display orders of integration substantially above 1, which implies a rejection of the hypothesis of mean reversion in all cases examined.
Originality/value
This paper uses an appropriate econometric framework to obtain new, reliable empirical evidence. All four series are highly persistent, and mean reversion does not occur in any single case. Moreover, the fractional cointegration analysis suggests that stock prices and interest rates are not linked in the long run.
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