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Article
Publication date: 1 October 1998

P. Alotto, P. Molfino, G. Molinari, M. Nervi and R. Orlando

In this paper a code for the solution of nonlinear thermo‐magnetic problems, arising in the transient analysis of thermal and electromagnetic fields in resistive toroidal field…

229

Abstract

In this paper a code for the solution of nonlinear thermo‐magnetic problems, arising in the transient analysis of thermal and electromagnetic fields in resistive toroidal field coils of tokamak devices, is presented. A formulation based on the electric vector potential T and the magnetic total scalar potential Ψ for the analysis of the thermo‐magnetic skin effect phenomenon in the toroidal field coils of proposed tokamaks has been used, and the results obtained are reported, reviewed and discussed.

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COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 17 no. 5
Type: Research Article
ISSN: 0332-1649

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Book part
Publication date: 26 November 2015

Douglas Biklen

The focus of this chapter is primarily on Burton Blatt’s investigations and exposés of closed institutions. These are the catalysts that served to set the stage for subsequent…

Abstract

The focus of this chapter is primarily on Burton Blatt’s investigations and exposés of closed institutions. These are the catalysts that served to set the stage for subsequent campaigns for inclusive schooling. The chapter also discusses issues of educability, the meaning of the concept of intellectual disability, the role of science in inclusion and treatment, and frameworks for pursuing, performing, and maintaining inclusive education and living. And in the interests of full disclosure, readers will note the personal connection between Biklen and Blatt, a result of sustained collaboration over many years.

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Foundations of Inclusive Education Research
Type: Book
ISBN: 978-1-78560-416-4

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Article
Publication date: 1 March 2006

Edwin H.W. Chan, W.S. Wong, Ann A.C. Cheung and Grace K.L. Lee

The purpose of this research is to review the regulatory framework for natural ventilation design affecting the health of residents, to identify the relationship between the main…

858

Abstract

Purpose

The purpose of this research is to review the regulatory framework for natural ventilation design affecting the health of residents, to identify the relationship between the main components of the indoor environmental quality (IEQ) and current building designs, and to propose improvements to the design standards or guidelines especially for those related to natural ventilation controls.

Design/methodology/approach

Building designs can influence the IEQ and therefore, legislation regulating such designs should be reviewed beforehand. Afterwards, site measurements to vacant residential building blocks on two different sites are carried out to collect radon levels contained in the air within the buildings. The major purpose of this measurement is to find out the relationship between radon concentration and residential building designs.

Findings

It is found that there is room for improvement in the building laws in Hong Kong regulating building designs which affect natural ventilation and IEQ.

Originality/value

This paper contributes to the understanding of the practical needs of the construction industry and may remedy any lack of consideration of commercial reality in the research process.

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Structural Survey, vol. 24 no. 2
Type: Research Article
ISSN: 0263-080X

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Article
Publication date: 27 September 2019

Giuseppe Orlando, Rosa Maria Mininni and Michele Bufalo

The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are…

365

Abstract

Purpose

The purpose of this study is to suggest a new framework that we call the CIR#, which allows forecasting interest rates from observed financial market data even when rates are negative. In doing so, we have the objective is to maintain the market volatility structure as well as the analytical tractability of the original CIR model.

Design/methodology/approach

The novelty of the proposed methodology consists in using the CIR model to forecast the evolution of interest rates by an appropriate partitioning of the data sample and calibration. The latter is performed by replacing the standard Brownian motion process in the random term of the model with normally distributed standardized residuals of the “optimal” autoregressive integrated moving average (ARIMA) model.

Findings

The suggested model is quite powerful for the following reasons. First, the historical market data sample is partitioned into sub-groups to capture all the statistically significant changes of variance in the interest rates. An appropriate translation of market rates to positive values was included in the procedure to overcome the issue of negative/near-to-zero values. Second, this study has introduced a new way of calibrating the CIR model parameters to each sub-group partitioning the actual historical data. The standard Brownian motion process in the random part of the model is replaced with normally distributed standardized residuals of the “optimal” ARIMA model suitably chosen for each sub-group. As a result, exact CIR fitted values to the observed market data are calculated and the computational cost of the numerical procedure is considerably reduced. Third, this work shows that the CIR model is efficient and able to follow very closely the structure of market interest rates (especially for short maturities that, notoriously, are very difficult to handle) and to predict future interest rates better than the original CIR model. As a measure of goodness of fit, this study obtained high values of the statistics R2 and small values of the root of the mean square error for each sub-group and the entire data sample.

Research limitations/implications

A limitation is related to the specific dataset as we are examining the period around the 2008 financial crisis for about 5 years and by using monthly data. Future research will show the predictive power of the model by extending the dataset in terms of frequency and size.

Practical implications

Improved ability to model/forecast interest rates.

Originality/value

The original value consists in turning the CIR from modeling instantaneous spot rates to forecasting any rate of the yield curve.

Details

Studies in Economics and Finance, vol. 37 no. 2
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 23 September 2019

Giuseppe Orlando, Rosa Maria Mininni and Michele Bufalo

The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among…

686

Abstract

Purpose

The purpose of this paper is to model interest rates from observed financial market data through a new approach to the Cox–Ingersoll–Ross (CIR) model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek framework. However, there are a number of issues in describing interest rate dynamics within the CIR framework on which focus should be placed. Therefore, a new methodology has been proposed that allows forecasting future expected interest rates from observed financial market data by preserving the structure of the original CIR model, even with negative interest rates. The performance of the new approach, tested on monthly-recorded interest rates data, provides a good fit to current data for different term structures.

Design/methodology/approach

To ensure a fitting close to current interest rates, the innovative step in the proposed procedure consists in partitioning the entire available market data sample, usually showing a mixture of probability distributions of the same type, in a suitable number of sub-sample having a normal/gamma distribution. An appropriate translation of market interest rates to positive values has been introduced to overcome the issue of negative/near-to-zero values. Then, the CIR model parameters have been calibrated to the shifted market interest rates and simulated the expected values of interest rates by a Monte Carlo discretization scheme. We have analysed the empirical performance of the proposed methodology for two different monthly-recorded EUR data samples in a money market and a long-term data set, respectively.

Findings

Better results are shown in terms of the root mean square error when a segmentation of the data sample in normally distributed sub-samples is considered. After assessing the accuracy of the proposed procedure, the implemented algorithm was applied to forecast next-month expected interest rates over a historical period of 12 months (fixed window). Through an error analysis, it was observed that our algorithm provides a better fitting of the predicted expected interest rates to market data than the exponentially weighted moving average model. A further confirmation of the efficiency of the proposed algorithm and of the quality of the calibration of the CIR parameters to the observed market interest rates is given by applying the proposed forecasting technique.

Originality/value

This paper has the objective of modelling interest rates from observed financial market data through a new approach to the CIR model. This model is popular among financial institutions mainly because it is a rather simple (uni-factorial) and better model than the former Vasicek model (Section 2). However, there are a number of issues in describing short-term interest rate dynamics within the CIR framework on which focus should be placed. A new methodology has been proposed that allows us to forecast future expected short-term interest rates from observed financial market data by preserving the structure of the original CIR model. The performance of the new approach, tested on monthly data, provides a good fit for different term structures. It is shown how the proposed methodology overcomes both the usual challenges (e.g. simulating regime switching, clustered volatility and skewed tails), as well as the new ones added by the current market environment (particularly the need to model a downward trend to negative interest rates).

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The Journal of Risk Finance, vol. 20 no. 4
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 12 July 2011

Robert C. Ford

The purpose of this paper is to offer insights and lessons learned about how to successfully balance the interests of the many competing stakeholders who can or do influence the…

1119

Abstract

Purpose

The purpose of this paper is to offer insights and lessons learned about how to successfully balance the interests of the many competing stakeholders who can or do influence the CVB's strategy for marketing a destination.

Design/methodology/approach

The study uses a qualitative case study approach utilizing an extensive interview as the method for data collection. A series of structured questions specifically designed to focus the interview on the topic of interest was used to facilitate data collection.

Findings

The paper presents insights from Mr William C. Peeper, the person largely responsible for building the Orlando Orange County Convention and Visitors Bureau from a two‐person organization into the multi million‐dollar operation it became by the time he retired 25 years later. Since the focus of the paper is on how to successfully balance the differing goals of stakeholders to achieve organizational goals, this interview offers a number of lessons learned that can be used by any organizational leader seeking to balance the interests of diverse stakeholders.

Originality/value

This study provides fresh ideas and new insights into how to successfully manage an organization's stakeholders in ways that make it possible to achieve an organization's mission across time. The success Mr Peeper had in gaining sustained support for the mission and goals of the Orlando CVB provides important lessons on how to manage all stakeholders especially the corporate governance structure that is pertinent to any organization that has to accommodate many diverse viewpoints and interests. There is little existing knowledge on managing stakeholders across time as their interests and needs change and the management of them must also adapt.

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International Journal of Contemporary Hospitality Management, vol. 23 no. 5
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 11 September 2017

Jeffery Cole Kreeger and Scott Smith

The purpose of this paper is to determine how much the lodging shared economy (LSE) utilizes minimum length of stay (MLOS) controls to maximize revenue and reduce housekeeping…

656

Abstract

Purpose

The purpose of this paper is to determine how much the lodging shared economy (LSE) utilizes minimum length of stay (MLOS) controls to maximize revenue and reduce housekeeping expense, since cleaning between guest visits represents a substantial variable cost for each guest’s stay. Hosts in the LSE are becoming increasingly perceptive in maximizing revenues.

Design/methodology/approach

Daily data for one year were collected for Vacation Rental by Owner properties in Hilton Head Island, SC and Orlando, FL. The collected data include daily vacancies for two different lengths of stay. Linear regression was used to explore the relationship between relative demand and vacancy length of stay differences.

Findings

During high-demand periods, there were few differences between the availability of short-term and longer-term reservation vacancies, which indicated hosts were not encouraging guests to stay longer during each visit. These results reveal differences in vacancies for three-night vs six-night reservations. A host can generate more revenue and decrease expenses by maximizing booked nights per visit.

Research limitations/implications

Due to confidentiality issues, this study does not capture vacation bookings but instead captures vacancies. In addition, Average Daily Rate was not utilized in this study.

Practical implications

LSE hosts can maximize revenues using MLOS controls. Minimizing housekeeping costs boosts a host’s profitability.

Originality/value

Although this research has been conducted for hotel MLOS, there is a gap in the literature regarding LSE hosts’ use of MLOS.

Details

International Journal of Contemporary Hospitality Management, vol. 29 no. 9
Type: Research Article
ISSN: 0959-6119

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Book part
Publication date: 30 June 2016

Ho Kwan Cheung, Eden King, Alex Lindsey, Ashley Membere, Hannah M. Markell and Molly Kilcullen

Even more than 50 years after the Civil Rights Act of 1964 prohibited discrimination toward a number of groups in employment settings in the United States, workplace…

Abstract

Even more than 50 years after the Civil Rights Act of 1964 prohibited discrimination toward a number of groups in employment settings in the United States, workplace discrimination remains a persistent problem in organizations. This chapter provides a comprehensive review and analysis of contemporary theory and evidence on the nature, causes, and consequences of discrimination before synthesizing potential methods for its reduction. We note the strengths and weaknesses of this scholarship and highlight meaningful future directions. In so doing, we hope to both inform and inspire organizational and scholarly efforts to understand and eliminate workplace discrimination.

Details

Research in Personnel and Human Resources Management
Type: Book
ISBN: 978-1-78635-263-7

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Available. Open Access. Open Access
Article
Publication date: 21 August 2023

Michele Bufalo and Giuseppe Orlando

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this…

1398

Abstract

Purpose

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Design/methodology/approach

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Findings

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

Research limitations/implications

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

Practical implications

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

Social implications

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

Originality/value

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

设计/方法/方法

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

目的

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

研究结果

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

研究局限/启示

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

实际意义

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

社会影响

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创意/价值

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Diseño/metodología/enfoque

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

Objetivo

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Resultados

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

Limitaciones/implicaciones de la investigación

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

Implicaciones prácticas

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

Implicaciones sociales

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

Originalidad/valor

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

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Article
Publication date: 1 January 2000

Kavous Ardalan

It is now common for finance textbooks to discuss the concepts of the CAPM, diversification benefit, and systematic risk, as measured by beta. The purpose of this paper is to…

1067

Abstract

It is now common for finance textbooks to discuss the concepts of the CAPM, diversification benefit, and systematic risk, as measured by beta. The purpose of this paper is to clarify aspects of these concepts and make the textbooks readers aware of them. In particular, this paper seeks to: (1) clarify the notion that “diversification reduces risk,” (2) provide geometric expositions and algebraic expressions of portfolio benefits in the context of both total risk and market risk, and (3) improve the interpretation of beta.

Details

Humanomics, vol. 16 no. 1
Type: Research Article
ISSN: 0828-8666

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